diff --git a/docs/404.html b/docs/404.html deleted file mode 100644 index bff792b..0000000 --- a/docs/404.html +++ /dev/null @@ -1,121 +0,0 @@ - - -
- - - - -YEAR: 2021 -COPYRIGHT HOLDER: Jacob B. Socolar & Simon C. Mills -- -
BSD 3-Clause License
-Copyright (c) 2021, Jacob B. Socolar & Simon C. Mills All rights reserved.
-Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
-Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
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- - -vignettes/augmented_models.Rmd
- augmented_models.Rmd
When modeling multiple ecologically comparable species -simultaneously, occupancy models often assume conditional -exchangeability across species and fit species-specific terms as random -effects. Data-augmented multi-species models leverage this -exchangeability assumption to estimate the number and prevalence of -never-detected species within the study region. To do so, the dataset is -augmented with a large number of pseudospecies with all-zero detection -histories, each species (both the observed species and the augmented -pseudospecies) is ascribed a common parameter \(\omega\) giving the Bernoulli probability -that a given (pseudo)species occurs in the study area, and -random-effects exchangeability assumptions are assumed to hold for all -species-specific modeled terms (i.e. intercepts and slopes for occupancy -and detection).
-For a data-augmented multi-species model, we marginalize over the -occupancy status of a closure-unit as for a single-season model yielding -the unit-wise likelihood \(\mathcal{L}_i\), and we additionally -marginalize over the availability of each (pseudo)species, yielding the -species-wise likelihood \[ \mathcal{N}_s = - \begin{cases} - B(1 | \omega)\prod\limits_{i \textrm{ in } I_s}{\mathcal{L}_i} -& \text{if $r_s = 1$} \\ - B(0 | \omega) + B(1 | \omega)\prod\limits_{i \textrm{ in } -I_s}{\mathcal{L}_i}& \text{if $r_s = 0$} - \end{cases} -\] where \(s\) indexes the -species, \(\omega\) is the fitted -availability probability of a species, \(I_s\) is the set of all closure-unit -indices \(i\) pertaining to species -\(s\), \(r_s\) is an indicator that takes the value -\(1\) if there is at least one positive -detection of the (pseudo)species in the entire dataset and \(0\) otherwise.
-Fitting the data-augmented model in requires passing the observed
-data as a three-dimensional array with sites along the first dimension,
-visits along the second, and species along the third. Additionally, we
-must supply the n_aug
argument to
-make_flocker_data()
, specifying how many all-zero
-pseudospecies to augment the data with.
#> Formatting data for a single-season multispecies occupancy model with data augmentation for never-observed species. For details, see make_flocker_data_augmented. All warnings and error messages should be interpreted in the context of make_flocker_data_augmented
-#> formatting rep indices
-#>
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-#> Compiling Stan program...
-#> Start sampling
-Here, the random effect of species is specified using the special
-grouping keyword ff_species
(names beginning with
-ff_
are reserved in flocker
and are not
-allowed as names for user-supplied covariates).
-summary(fm)
-#> Family: occupancy_augmented
-#> Links: mu = identity; occ = identity; Omega = identity
-#> Formula: ff_y | vint(ff_n_unit, ff_n_rep, ff_Q, ff_n_sp, ff_superQ, ff_species, ff_rep_index1, ff_rep_index2, ff_rep_index3, ff_rep_index4) ~ uc1 + ec1 + (1 + uc1 + ec1 | ff_species)
-#> occ ~ (1 | ff_species)
-#> Omega ~ 1
-#> Data: data (Number of observations: 25600)
-#> Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
-#> total post-warmup draws = 4000
-#>
-#> Group-Level Effects:
-#> ~ff_species (Number of levels: 128)
-#> Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
-#> sd(Intercept) 1.61 0.27 1.16 2.23 1.01 1073 1777
-#> sd(uc1) 0.26 0.11 0.07 0.50 1.00 1474 1401
-#> sd(ec1) 0.39 0.09 0.23 0.59 1.00 2359 2859
-#> sd(occ_Intercept) 1.59 0.32 1.12 2.37 1.00 1047 1405
-#> cor(Intercept,uc1) 0.75 0.21 0.17 0.97 1.00 2662 2649
-#> cor(Intercept,ec1) 0.57 0.19 0.13 0.87 1.00 2733 2620
-#> cor(uc1,ec1) 0.59 0.25 -0.00 0.94 1.01 1069 1910
-#>
-#> Population-Level Effects:
-#> Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
-#> Intercept 0.46 0.32 -0.23 1.04 1.01 440 884
-#> occ_Intercept 0.25 0.35 -0.46 0.89 1.01 601 726
-#> Omega_Intercept -1.26 0.22 -1.71 -0.85 1.00 7233 2740
-#> uc1 0.01 0.08 -0.15 0.15 1.00 1035 1347
-#> ec1 0.07 0.09 -0.12 0.25 1.00 1023 2294
-#>
-#> Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
-#> and Tail_ESS are effective sample size measures, and Rhat is the potential
-#> scale reduction factor on split chains (at convergence, Rhat = 1).
flocker
enables users to fit data-augmented models using
-arbitrary brms
formulas for the occupancy and detection
-components. However, we caution that continuous covariates in the
-occupancy sub-model can lead to pitfalls in interpretation. A seemingly
-straightforward application, for example, might be to ask how many
-species are present along an elevational gradient, fitting
-species-specific quadratic elevation-occupancy relationships. In our
-experience, a data-augmented model that includes quadratic elevation
-terms will place an arbitrarily large number of pseudo-species along the
-gradient, but will do so by placing pseudospecies’ estimated elevational
-ranges entirely outside the range covered by the sampling effort (Socolar
-et al 2022). The model is in effect trying to estimate how many
-species occur in a landscape with elevations ranging from negative to
-positive infinity. This extrapolation is unprincipled, most obviously
-because it does not account for hard limits imposed by the physical
-termina of the gradient (valley floor and mountain peak). Thus, although
-flocker
provides functionality to fit continuous covariates
-in the occupancy term, we recommend extreme caution in interpreting
-patterns estimated for never-observed species.
vignettes/flocker_tutorial.Rmd
- flocker_tutorial.Rmd
flocker
is an R package for fitting occupancy models
-that incorportate sophisticated effects structures using simple
-formula-based syntax. flocker
is built on R package
-brms
, which in turn is a front-end for
-Stan
.
This vignette is intended as a companion to Socolar & Mills 2023
-(INSERT LINK), where we provide details of the models and
-post-processing functionality available in flocker
in
-greater detail. Here, we provide illustrative R code for several types
-of model, demonstrating data simulation, model fitting, and model
-post-processing. We also showcase the brms
syntax that
-flocker
can use to fit a variety of sophisticated effect
-structures.
Socolar & Mills (2023) introduce several terms that figure -importantly in this vignette, including:
-closure-unit: The groupings of observations over -which closure -is assumed. In single-species models, a closure-unit corresponds to a -“site” or “point”. In multi-species models, a closure-unit is a -species-site combination. In dynamic (multi-season) models, a -closure-unit is a site-season combination (or species-site-season in a -multi-species dynamic model).
rep-constant, rep-varying: We -refer to models that assume constant detection probabilities across -repeat visits within closure-units as rep-constant models, as -contrasted with rep-varying models that incorporate -event-specific detection covariates. It turns out that rep-constant -models enable a more efficient parametrization of the likelihood than -rep-varying models.
unit covariates, event -covariates: We refer to any covariate that does not vary across -sampling events within closure-units as a “unit covariate”. This -includes covariates that are intrinsically properties of single -closure-units (e.g. the elevations of sites in a single-species model), -covariates that are intrinsically properties of groups of closure units -(e.g. elevations of sites in a multi-species model), and covariates -that are intrinsically properties of sampling events but happen to be -constant within all closure-units (e.g. observer in a sampling design -where every site is visited by exactly one observer). We refer to any -covariate that varies across sampling events within covariates as an -“event covariate”. Note that while unit covariates may appear in either -the occupancy or the detection formula, event covariates are restricted -to the detection formula. Models that incorporate event covariates are -rep-varying (see above); those that do not are -rep-constant.
Installation -instructions are available here. To request features or report bugs -(much appreciated!), please open an issue on -GitHub.
-To make flocker
and brms
functions globally
-available within an R session run:
#> Loading required package: Rcpp
-#> Loading 'brms' package (version 2.20.5). Useful instructions
-#> can be found by typing help('brms'). A more detailed introduction
-#> to the package is available through vignette('brms_overview').
-#>
-#> Attaching package: 'brms'
-#> The following object is masked from 'package:stats':
-#>
-#> ar
-General purpose data simulation is provided via
-simulate_flocker_data()
, which by default will simulate a
-dataset with 30 species sampled at 50 sites using four replicate surveys
-(i.e. a single-season multi-species dataset). Non-default arguments will
-simulate example data for other likelihoods, including multi-season and
-data-augmented occupancy models.
-d <- simulate_flocker_data()
The simulated data d
are in list form, with elements for
-the detection/non-detection observations d$obs
, unit
-covariates d$unit_covs
, and event covariates
-d$event_covs
. d$obs
is a matrix where rows are
-species-site combinations, columns are replicate visits, and entries are
-1
(detection), 0
(nondetection), or
-NA
(no visit). d$unit_covs
is a dataframe
-containing covariates that vary across the rows of obs (i.e. by
-closure-unit) but not across the columns within any given row (i.e. do
-not vary across replicate visits). event_covs
is a named
-list of matrices, with each matrix having the same dimensions as the
-observation matrix. Each list element corresponds to a covariate that
-varies across the columns of d$obs
(i.e. varies between
-replicate visits).
flock()
, the main function in flocker
for
-fitting occupancy models, expects a highly specific data format. The
-function make_flocker_data()
formats data for use with
-flock()
automatically. For single-season models,
-make_flocker_data()
takes as input a matrix or dataframe of
-detection/non-detection data. Rows represent closure-units, columns
-represent repeated sampling events within closure-units, and entries
-must be 0
(nondetection), 1
(detection), or
-NA
(no corresponding sampling event). The data must be
-formatted so that all NA
s are trailing within their rows.
-For example, if some units were sampled four times and other three
-times, the three sampling events must be treated as events 1, 2, and 3
-(with the fourth event NA
) rather than as events 1, 3, and
-4 (with the second event NA
) or any other combination.
Many occupancy models also include covariates that influence
-occupancy or detection probabilities. Unit covariates (see Terms and
-definitions above) can be passed to
-make_flocker_data()
as a dataframe with the same number of
-rows as the observation matrix and data in the same order as the rows of
-the observation matrix. Columns are covariates, and we recommend using
-informative column names. Event covariates (see Terms and
-definitions above) can be passed as a named list of matrices whose
-elements [i, j]
are the covariate values for the sampling
-event represented by the corresponding position of the observation
-matrix. Again, we recommend using informative names for the list
-elements. If the corresponding observation is NA
, then the
-value of the event covariate does not matter.
To pass data to flocker
, we first pass the output from
-simulate_flocker_data()
to
-make_flocker_data()
, which will repackage data and apply
-the necessary formatting:
-fd_rep_varying <- make_flocker_data(
- obs = d$obs,
- unit_covs = d$unit_covs,
- event_covs = d$event_covs
- )
-#> Formatting data for a single-season occupancy model. For details, see make_flocker_data_static. All warnings and error messages should be interpreted in the context of make_flocker_data_static
The function make_flocker_data()
outputs an object of
-class flocker_data
that we can pass to flocker’s model
-fitting function flock()
. Note that this is the general
-workflow users will need to follow with real data. Alternative inputs to
-make_flocker_data()
and flock()
enable the
-user to readily fit multi-season models as well as multi-species models
-with data augmentation (see below).
To fit a model, in this case a single-season multi-species occupancy
-model, we use the function flock()
. By supplying different
-arguments to this function, all flavors of occupancy model available in
-flocker
can be fitted. Formulas for the different
-distributional parameters in the model (occupancy, detection,
-colonization, extinction, and autologistic terms as applicable) are
-provided as one-sided formulas to the relevant arguments of
-flock()
(f_occ
, f_det
,
-f_col
, f_ex
, and f_auto
as
-applicable).
-rep_varying <- flock(
- f_occ = ~ uc1 + (1 + uc1 | species),
- f_det = ~ uc1 + ec1 + (1 + uc1 + ec1 | species),
- flocker_data = fd_rep_varying,
- cores = 4,
- silent = 2,
- refresh = 0
- )
Arguments supplied to flock()
define formulas using
-brms
syntax for the occupancy (f_occ
) and
-detection (f_det
) components, and also provide the
-formatted data. At this stage, the full flexibility and power of
-brms
formula syntax are available to the user (see
-following sections for some examples). rep_varying
is a
-brmsfit
object from package brms
and also a
-flockerfit
object from package flocker
.
-Post-processing functions from brms
will typically not work
-with this object and are instead replaced by flocker
-equivalents.
make_flocker_data()
will automatically format the data
-for a rep-constant model when event_covs = NULL
and the
-desired model is a single-season model without data augmentation. To
-take advantage of the efficiency gains and post-processing functionality
-of the rep-constant model, it is necessary to supply
-event_covs = NULL
to make_flocker_data()
at
-the moment of data formatting; it is insufficient to omit event
-covariates from the detection formula supplied to flock()
-after formatting the data for a rep-varying model.
-fd_rep_constant <- make_flocker_data(
- obs = d$obs,
- unit_covs = d$unit_covs
- )
-#> Formatting data for a single-season occupancy model. For details, see make_flocker_data_static. All warnings and error messages should be interpreted in the context of make_flocker_data_static
-rep_constant <- flock(
- f_occ = ~ uc1 + (1 + uc1 | species),
- f_det = ~ uc1 + (1 + uc1 | species),
- flocker_data = fd_rep_constant,
- save_pars = save_pars(all = TRUE), # for loo with moment matching
- silent = 2,
- refresh = 0,
- cores = 4
- )
Note that within-chain parallelization is available (uniquely so) for -the rep-constant mode:
-
-rep_constant <- flock(
- f_occ = ~ uc1 + (1 + uc1 | species),
- f_det = ~ uc1 + (1 + uc1 | species),
- flocker_data = fd_rep_constant,
- silent = 2,
- refresh = 0,
- chains = 2,
- cores = 2,
- threads = 2
- )
Here we provide code examples to complement the companion publication
-INSERT LINK. For a more complete vignette on multi-season models in
-flocker
, see the multiseason
-models vignette.
First, we simulate some data that are valid for use with multi-season
-models. Here, we will simulate data for three seasons with one unit
-covariate and one event covariate. The data will be simulated under a
-colonization-extinction model with explicit inits, but we will be able
-to fit other models (autologistic, equilibrium inits) to the same data
-(note that simulate_flocker_data()
can also simulate
-directly from these other model types).
-multi_data <- simulate_flocker_data(
- n_season = 3,
- n_pt = 300,
- n_sp = 1,
- multiseason = "colex",
- multi_init = "explicit",
- seed = 1
- )
-
-fd_multi <- make_flocker_data(
- multi_data$obs,
- multi_data$unit_covs,
- multi_data$event_covs,
- type = "multi",
- quiet = TRUE
- )
Below, we fit the colonization-extinction model with an explicit -model for occupancy in the first timestep. Depending on hardware, -fitting this model might take several minutes.
-
-multi_colex <- flock(
- f_occ = ~ uc1,
- f_det = ~ uc1 + ec1,
- f_col = ~ uc1,
- f_ex = ~ uc1,
- flocker_data = fd_multi,
- multiseason = "colex",
- multi_init = "explicit",
- cores = 4,
- silent = 2,
- refresh = 0
-)
Here is the colonization-extinction model using equilibrium occupancy -probabilities in the first timestep:
-
-multi_colex_eq <- flock(
- f_det = ~ uc1 + ec1,
- f_col = ~ uc1,
- f_ex = ~ uc1,
- flocker_data = fd_multi,
- multiseason = "colex",
- multi_init = "equilibrium",
- cores = 4,
- silent = 2,
- refresh = 0
- )
Here is the autologistic model with explicit occupancy probabilities
-in the first timestep. To reflect the stereotypical autologistic model
-with a constant logit-scale offset separating colonization and
-persistence probabilities, we use the formula f_auto = ~ 1
,
-but it is fine to relax this constraint and use,
-e.g. f_auto = ~ uc1
.
-multi_auto <- flock(
- f_occ = ~ uc1,
- f_det = ~ uc1 + ec1,
- f_col = ~ uc1,
- f_auto = ~ 1,
- flocker_data = fd_multi,
- multiseason = "autologistic",
- multi_init = "explicit",
- cores = 4,
- silent = 2,
- refresh = 0
- )
And the autologistic model with equilibrium occupancy probabilities -in the first timestep:
-
-multi_auto_eq <- flock(
- f_det = ~ uc1 + ec1,
- f_col = ~ uc1,
- f_auto = ~ 1,
- flocker_data = fd_multi,
- multiseason = "autologistic",
- multi_init = "equilibrium",
- cores = 4,
- silent = 2,
- refresh = 0
-)
Here we provide code examples to complement the companion publication
-INSERT LINK. For a more complete unified vignette on data-augmented
-models in flocker
, see the data-augmented
-models vignette.
Fitting the data-augmented model in flocker
requires
-passing the observed data as a three-dimensional array with sites along
-the first dimension, visits along the second, and species along the
-third. Additionally, we must supply the n_aug
argument to
-make_flocker_data()
, specifying how many all-zero
-pseudospecies to augment the data with.
-augmented_data <- simulate_flocker_data(
- augmented = TRUE
- )
-fd_augmented <- make_flocker_data(
- augmented_data$obs, augmented_data$unit_covs, augmented_data$event_covs,
- type = "augmented", n_aug = 100,
- quiet = TRUE
- )
-augmented <- flock(
- f_occ = ~ (1 | ff_species),
- f_det = ~ uc1 + ec1 + (1 + uc1 + ec1 | ff_species),
- augmented = TRUE,
- flocker_data = fd_augmented,
- cores = 4,
- silent = 2,
- refresh = 0
- )
Here, the random effect of species is specified using the special
-grouping keyword ff_species
(names beginning with
-ff_
are reserved in flocker
and are not
-allowed as names for user-supplied covariates).
flocker
provides functions for four main types of
-bespoke post-processing for occupancy models.
-fitted_flocker()
get_Z()
provides the posterior distribution for the
-latent occupancy state. predict_flocker()
provides
-posterior predictions at the observed points (e.g. for use in posterior
-predictive checking) or for new data. loo_flocker()
and
-loo_compare_flocker()
both provide functionality for model
-comparison. See below for details on all four types of post-processing.
-Both posterior predictions and model comparison rely on subtle aspects
-of the occupancy model likelihood that we explain in more detail in the
-companion paper INSERT LINK and here.
All post-processing functions from brms
work on
-single-season rep-constant models, but do not work on any other model
-types. For example:
-predictions_rep_constant <- brms::posterior_predict(rep_constant)
-loo_rep_constant <- brms::loo(rep_constant, moment_match = TRUE)
-brms::conditional_effects(rep_constant)
The following functions work on all model types available in
-flocker
.
Fitted values for any of the distributional parameter (one or more of
-occupancy, detection, colonization, extinction, autologistic, and/or
-Omega, the fitted probability that a given (pseudo)species occurrs in
-the metacommunity) are available via fitted_flocker
. For
-example:
-fitted_flocker(rep_constant)
-fitted_flocker(rep_varying)
-fitted_flocker(multi_colex)
-fitted_flocker(augmented)
The function get_Z()
returns the posterior distribution
-of occupancy probabilities across the closure-units. The shape of the
-output depends on the class of model, and is an array in the shape of
-the first visit in obs
as passed to
-make_flocker_data
, with posterior iterations stacked along
-the final dimension. Thus, for a single-season rep-varying model, the
-output is a matrix where rows are posterior iterations, columns are
-closure-units, and values are draws from the posterior distribution of
-occupancy probabilities:
-get_Z(rep_varying)
For all model types, get_Z()
accepts an optional
-new_data
argument. Leaving the default
-new_data = NULL
supplies the posterior for the true
-occupancy state at the locations of the data used to fit the model.
-Otherwise, the posterior is computed over the new data. For
-single-season models, new_data
can be supplied as a
-dataframe of unit covariate values or as a flocker_data
-object. For multi-season models, only a flocker_data
object
-is allowed. Note that if predictions are desired at sites without
-observations, it is acceptable to pass an array of dummy observations
-(e.g. all zeros) to make_flocker_data()
and then to set
-history_condition = FALSE
in the call to
-get_Z()
.
get_Z()
accepts several additional arguments that
-control the way that posterior is obtained and the values returned. See
-the companion paper INSERT LINK and ?get_Z
for details.
The function predict_flocker()
provides posterior
-predictions. By default, predictions are provided for the covariate data
-to which the model were fit, but predictions to new data are also
-possible via the new_data
argument. The output differs by
-model type. For single-season rep-constant models, the return is a
-matrix where rows are iterations, columns are units, and values are the
-number of detections. For single-season rep-varying models, the return
-is an array whose first dimension is units, second dimension is sampling
-events, third dimension is iterations, and values are 1
,
-0
, or NA
, representing detection,
-nondetection, and no corresponding sampling event. For example:
-predict_flocker(rep_varying)
predict_flocker()
accepts several additional arguments
-that control the way that posterior is obtained and the values of
-returned. See the companion paper INSERT LINK and
-?predict_flocker
for details.
The most straightforward way to compare models fit with
-flocker
is the function loo_compare_flocker()
.
-This function takes a list of flocker_fit objects as its argument and
-returns a model comparison table based on the difference in the expected
-log predictive density (elpd) between models. This table is a
-compare.loo
object from loo::loo_compare()
.
-The “leave-one-out” holdouts consist of entire closure-units
-(single-season models), series (multi-season models), or species
-(augmented models), not single sampling events (see the companion paper
-INSERT LINK and here for
-details of why).
loo_compare_flocker()
accepts as input a list of
-flockerfit
objects and outputs a model comparison table.
-For example, we can compare the rep-constant and rep-varying models that
-we fit to the same initial data. Recall that the data were simulated
-with event-covariate effects on detection, and as expected the
-rep-varying model performs best. Note that we ensure that these
-comparisons between rep-constant and rep-varying models are valid by
-omitting the binomial coefficient when computing the log-likelihood for
-the rep-constant model.
-loo_compare_flocker(
- list(rep_constant, rep_varying)
-)
-#> Warning: Some Pareto k diagnostic values are slightly high. See help('pareto-k-diagnostic') for details.
-
-#> Warning: Some Pareto k diagnostic values are slightly high. See help('pareto-k-diagnostic') for details.
-#> elpd_diff se_diff
-#> model2 0.0 0.0
-#> model1 -155.9 17.9
Likewise, we can compare the four flavors of multi-season model that
-we fit above. Recall that the data were simulated under
-colonization-extinction dynamics (rather than autologistic) and under
-explicit initial occupancy probabilities (rather than equilibrium). As
-expected, the multi_colex
model performs best:
-loo_compare_flocker(
- list(multi_colex, multi_colex_eq, multi_auto, multi_auto_eq)
-)
-#> elpd_diff se_diff
-#> model1 0.0 0.0
-#> model2 -17.1 5.9
-#> model3 -53.2 10.1
-#> model4 -65.0 10.3
Flocker also provides the function loo_flocker()
to
-return a table of elpd_loo
, p_loo
, and
-looic
estimates from loo::loo()
or
-brms::loo()
(the latter for single-season rep-constant
-models only).
brms
tips and tricks
-Mastering advanced occupancy modeling via flocker
is
-mostly a matter of mastering the syntax available in brms
.
-Here are some useful pieces of syntax:
Priors can be implemented as they would with any brms
-model. Priors can be specified using set_prior()
, with
-priors specified for groups of parameters (via class
) or
-individual parameters (via coef
). The priors used for a
-particular model can be retrieved using
-brms::prior_summary()
, and the names of the parameters and
-their default priors can be displayed prior to model fitting using
-get_flocker_prior()
which is a drop-in replacement for
-brms::get_prior()
.
-get_flocker_prior(
- f_occ = ~ uc1 + (1 + uc1 | species),
- f_det = ~ uc1 + ec1 + (1 + uc1 + ec1 | species),
- flocker_data = fd_rep_varying
- )
-#> prior class coef group resp dpar nlpar lb ub
-#> (flat) b
-#> (flat) b ec1
-#> (flat) b uc1
-#> lkj(1) cor
-#> lkj(1) cor species
-#> student_t(3, 0, 2.5) Intercept
-#> student_t(3, 0, 2.5) sd 0
-#> student_t(3, 0, 2.5) sd species 0
-#> student_t(3, 0, 2.5) sd ec1 species 0
-#> student_t(3, 0, 2.5) sd Intercept species 0
-#> student_t(3, 0, 2.5) sd uc1 species 0
-#> (flat) b occ
-#> (flat) b uc1 occ
-#> (flat) Intercept occ
-#> student_t(3, 0, 2.5) sd occ 0
-#> student_t(3, 0, 2.5) sd species occ 0
-#> student_t(3, 0, 2.5) sd Intercept species occ 0
-#> student_t(3, 0, 2.5) sd uc1 species occ 0
-#> source
-#> default
-#> (vectorized)
-#> (vectorized)
-#> default
-#> (vectorized)
-#> default
-#> default
-#> (vectorized)
-#> (vectorized)
-#> (vectorized)
-#> (vectorized)
-#> default
-#> (vectorized)
-#> default
-#> default
-#> (vectorized)
-#> (vectorized)
-#> (vectorized)
-brms::prior_summary(rep_varying)
-#> prior class coef group resp dpar nlpar lb ub
-#> (flat) b
-#> (flat) b ec1
-#> (flat) b uc1
-#> (flat) b occ
-#> (flat) b uc1 occ
-#> student_t(3, 0, 2.5) Intercept
-#> (flat) Intercept occ
-#> lkj_corr_cholesky(1) L
-#> lkj_corr_cholesky(1) L species
-#> student_t(3, 0, 2.5) sd 0
-#> student_t(3, 0, 2.5) sd occ 0
-#> student_t(3, 0, 2.5) sd species 0
-#> student_t(3, 0, 2.5) sd ec1 species 0
-#> student_t(3, 0, 2.5) sd Intercept species 0
-#> student_t(3, 0, 2.5) sd uc1 species 0
-#> student_t(3, 0, 2.5) sd species occ 0
-#> student_t(3, 0, 2.5) sd Intercept species occ 0
-#> student_t(3, 0, 2.5) sd uc1 species occ 0
-#> source
-#> default
-#> (vectorized)
-#> (vectorized)
-#> default
-#> (vectorized)
-#> default
-#> default
-#> default
-#> (vectorized)
-#> default
-#> default
-#> (vectorized)
-#> (vectorized)
-#> (vectorized)
-#> (vectorized)
-#> (vectorized)
-#> (vectorized)
-#> (vectorized)
Note that if there are parameters shared between both the occupancy -and detection model formulas, e.g.
-
-get_flocker_prior(
- f_occ = ~ uc1 + (1|species),
- f_det = ~ uc1 + ec2 + (1|species),
- flocker_data = fd_rep_varying
- )
then there will be two entries for each of the shared parameters in
-the prior table (uc1
in this example). Specifying a priors
-for parameters in formulas other than detection can be done with
-reference to the dpar
column, e.g.:
-user_prior <- c(brms::set_prior("normal(0, 1)", coef = "uc1"),
- brms::set_prior("normal(0, 3)", coef = "uc1", dpar = "occ"))
where the uc1
parameter in the occupancy component is
-specified by the addition of the dpar
argument, and the
-uc1
parameter in the detection component is specified
-without reference to dpar
.
For more on priors in brms
, see
-?brms::set_prior
.
Users should understand the implications of the default
-brms
behavior to internally center the design matrix, which
-affects the prior on the intercept gets set (see
-?brms::set_prior
). Here is an example, based on a
-single-season rep-varying model, wherein we set a logistic prior on the
-value of the intercepts (flat on the probability scale) when all
-predictors are held at their means and a moderately regularizing prior
-on the coefficients:
-rep_varying_prior1 <- flock(
- f_occ = ~ uc1,
- f_det = ~ ec1,
- flocker_data = fd_rep_varying,
- prior =
- brms::set_prior("logistic(0,1)", class = "Intercept") +
- brms::set_prior("logistic(0,1)", class = "Intercept", dpar = "occ") +
- brms::set_prior("normal(0,2)", class = "b") +
- brms::set_prior("normal(0,2)", class = "b", dpar = "occ"),
- cores = 4,
- silent = 2,
- refresh = 0
- )
-brms::prior_summary(rep_varying_prior1)
-#> prior class coef group resp dpar nlpar lb ub source
-#> normal(0,2) b user
-#> normal(0,2) b ec1 (vectorized)
-#> normal(0,2) b occ user
-#> normal(0,2) b uc1 occ (vectorized)
-#> logistic(0,1) Intercept user
-#> logistic(0,1) Intercept occ user
Here is an example where we set informative priors on the intercepts -when all covariates are fixed to zero and the same moderately -regularizing prior on the coefficients:
-
-rep_varying_prior2 <- flock(
- f_occ = ~ 0 + Intercept + uc1,
- f_det = ~ 0 + Intercept + ec1,
- flocker_data = fd_rep_varying,
- prior =
- brms::set_prior("normal(0,2)", class = "b") +
- brms::set_prior("normal(0,2)", class = "b", dpar = "occ") +
- brms::set_prior("normal(1, 1)", class = "b", coef = "Intercept") +
- brms::set_prior("normal(-1, 1)", class = "b", coef = "Intercept", dpar = "occ"),
- cores = 4,
- silent = 2,
- refresh = 0
- )
-brms::prior_summary(rep_varying_prior2)
-#> prior class coef group resp dpar nlpar lb ub source
-#> normal(0,2) b user
-#> normal(0,2) b ec1 (vectorized)
-#> normal(1, 1) b Intercept user
-#> normal(0,2) b occ user
-#> normal(-1, 1) b Intercept occ user
-#> normal(0,2) b uc1 occ (vectorized)
Simple formulas follow the same syntax as R’s lm()
-function. For example:
-mod1 <- flock(
- f_occ = ~ uc1 + (1|species),
- f_det = ~ 1,
- flocker_data = fd_rep_constant
- )
Simple random effects follow lme4
syntax, including
-advanced lme4
syntax like ||
for uncorrelated
-effects and /
and :
for expansion of multiple
-grouping terms. Here’s a simple example:
-mod2 <- flock(
- f_occ = ~ uc1 + (1|species),
- f_det = ~ 1,
- flocker_data = fd_rep_constant
- )
When a model includes multiple random effects with the same grouping -term, by default they are modeled as correlated within the -occupancy or detection formulas, but as uncorrelated between -formulas. For example, the code below estimates a single correlation for -the intercept and slope in the occupancy sub-model.
-
-mod3 <- flock(
- f_occ = ~ uc1 + (1 + uc1 | species),
- f_det = ~ ec1 + (1 | species),
- flocker_data = fd_rep_varying
- )
However, this assumption can easily be relaxed using the
-|<ID>|
syntax from brms
. The
-<ID>
is an arbitrary character string representing a
-group of terms to model as correlated. The below code, for example,
-models correlated intercepts in the occupancy and detection sub-models,
-and correlated effects of sc1
on occupancy and
-vc1
on detection, but no correlations between the
-intercepts and the slopes in either sub-model:
-mod4 <- flock(
- f_occ = ~ uc1 + (1 |g1| species) + (0 + uc1 |g2| species),
- f_det = ~ ec1 + (1 |g1| species) + (0 + ec1 |g2| species),
- flocker_data = fd_rep_varying
- )
For more on brms
syntax for random effects syntax, see
-the documentation
-here.
Via brms
, flocker
supports Gaussian
-processes of arbitrary dimensionality (brms::gp()
) as well
-as mgcv
syntax for thin-plate regression splines
-(brms::s()
) and tensor product smooths
-(brms::t2()
), and brms
syntax for monotonic
-effects of ordinal factors via brms::mo()
(see
-here). For example:
-mod5 <- flock(
- f_occ = ~ s(uc1),
- f_det = ~ t2(uc1, ec1),
- flocker_data = fd_rep_varying
- )
-
-mod6 <- flock(
- f_occ = ~ 1,
- f_det = ~ gp(uc1, ec1),
- flocker_data = fd_rep_varying
- )
In addition, brms
provides the ability to estimate
-models wherein the predictors (e.g. for occupancy and detection) are
-parametric nonlinear functions whose parameters have their own
-covariate-based linear predictors. For more details and an example, see
-the nonlinear
-models vignette.
Phylogenetic effects can be included by providing a covariance matrix
-as a data2
argument and using the brms::gr()
-function to link species identities in flocker_data
with
-the supplied covariance matrix. Note that phylogenetic effects can be
-included in either the occupancy component, the detection component, or
-both! In our experience, it can be computationally tractable to include
-multiple phylogenetic effects within a single occupancy model (see Mills et al. 2022).
-# simulate an example phylogeny
-phylogeny <- ape::rtree(30, tip.label = paste0("sp_", 1:30))
-
-# calculate covariance matrix
-A <- ape::vcv.phylo(phylogeny)
-
-mod8 <- flock(
- f_occ = ~ 1 + (1|gr(species, cov = A)),
- f_det = ~ 1 + ec1 + (1|species),
- flocker_data = fd_rep_varying,
- data2 = list(A = A)
- )
-
-mod9 <- flock(
- f_occ = ~ 1 + (1|gr(species, cov = A)),
- f_det = ~ 1 + ec1 + (1|gr(species, cov = A)),
- flocker_data = fd_rep_varying,
- data2 = list(A = A)
- )
See
-here for further details about specifying phylogenetic effects in
-brms
.
In addition to spatial Gaussian processes, brms
provides
-a variety of autoregressive structures, both one-dimensional (see
-brms::ar()
, brms::arma()
) and two-dimensional
-(see brms::car()
, brms::sar()
. See
-here for details about conditional autoregressive (CAR) models in
-brms
, and note that flock()
accepts a
-data2
argument that it can pass to brms
as
-necessary.
Our principle caution for users is that these autoregressive
-structures might lead to degenerate models when applied at the visit
-level (in detection formulas) or at the closure-unit level (in
-occupancy, colonization, extinction, or autologistic formulas) because
-observation-level random effects are often degenerate in regressions
-with Bernoulli responses. Thus we recommend applying autoregressive
-terms to groupings of multiple visits (detection formula) or multiple
-closure-units (other formulas). However, we note that
-flocker
does provide a well-identified
-one-dimensional first-order autoregressive structure for occupancy
-across closure-units in a single-season model. This is achieved by
-co-opting the autologistic parameterization of the multi-season model
-and applying it instead to closure-units arranged along a
-one-dimensional spatial transect, yielding a one-dimensional analog of a
-spatial autologistic occupancy model.
A second caution is to remind users that in multi-species models,
-users will likely want to fit separate spatial terms by species (Doser
-et al 2022). For Gaussian processes, this can be achieved via the
-by
argument to brms::gp()
. For some
-conditional autoregressive structures (those that allow disconnected
-islands), this can be achieved by passing a block-diagonal adjacency
-matrix wherein species are disconnected components.
We note that gaussian process priors for spatially varying
-coefficients are readily achieved via the nonlinear formula syntax of
-brms
. For more details and an example, see the nonlinear
-models vignette.
See
-here for relevant brms
documentation.
flock
will pass any relevant parameters forward to
-brms::brm()
, giving the user important control over the
-algorithmic details of how the model is fit. See ?brms::brm
-for details. To speed up the execution, we recommend supplying the
-argument backend = "cmdstanr"
. This requires the cmdstanr
-package and a working installation of cmdstan; see here for instructions to
-get started and further details.
vignettes/multiseason_models.Rmd
- multiseason_models.Rmd
Multiseason occupancy models, also called dynamic occupancy models, -are models that assume closure over -units that are linked by explicit colonization and extinction -processes.1 That is, sites are surveyed over a series -of more than one timestep,2 closure is assumed to hold within (but not -across) timesteps, and the latent occupancy state is linked across -timesteps within a site via models of local colonization and extinction -processes. Following the terminology introduced here, -we will refer to the units over which closure is assumed as -closure-units or just plain units. Groups of units -that are linked by colonization-extinction dynamics (i.e. units -representing different timesteps within a site) are series.
-In flocker
, we implement these models using a hidden
-markov model (HMM) approach to dealing with the unobserved occupancy
-state in each separate series. Calling our approach a HMM doesn’t
-fundamentally change the model; it serves mainly to highlight the
-connection between multiseason occupancy models and well-developed
-techniques for efficiently computing the likelihood for a series.3 The HMM
-conceptualizes the latent occupancy state as a Markov-like process (the
-process need not be strictly Markovian, because the transition
-probabilities can vary by timestep), where the transition probabilities
-between the two possible states (occupied or unoccupied) are a
-colonization probabilility \(\mathcal{C}\), an extinction probability
-\(\mathcal{E}\), and their complements
-\(1 - \mathcal{C}\) and \(1 - \mathcal{E}\). The complement of the
-extinction probability turns out to be particularly important; we call
-it the persistence probability \(\mathcal{P} = 1 - \mathcal{E}\).
To specify the HMM, we need a model for the \(\mathcal{C}\), a model for \(\mathcal{E}\), and a model for the initial -occupancy probability \(\mathcal{O}\) -in the first timestep. We also need a model for the probability of -observing the data in any particular timestep conditional on the true -occupancy state in that timestep (in the HMM literature, this -probability is referred to as an emission probability).
-Emission probabilities are just fancy HMM terminology for
-the most familiar part of multiseason occupancy model. They are the
-probability of observing the data within a unit given the latent
-occupancy state, and they depend only on the detection sub-model, which
-is no different from a single-season detection sub-model. In
-flocker
, we assume that the logit-scale detection
-probabilities vary according to a suite of covariates that can vary
-across all levels of organization, including down to the visit level.
-This is exactly the same way that flocker
treats the
-detection sub-model in a single-season model.
In “colonization-extinction” models, logit colonization probabilities -\(\mathcal{C}\) and logit extinction -probabilities \(\mathcal{E}\) are both -assumed to vary according to separate predictors based on covariates -that may vary across timesteps within series but never across visits -within closure-units.
-In “autologistic” models, the occupancy probability in timestep \(t + 1\) is assumed to depend on a suite of -site characteristics plus a term that depends on the latent true -occupancy state at time \(t\). Some -treatments write the autologistic model in terms of an “occupancy -probability” that depends on covariates plus the “autologistic term” -that gets added on the logit scale when the site was previously -occupied. However, it is easier to understand this model in terms of its -colonization and extinction probabilities. In fact, the so-called -“occupancy probability” mentioned above is actually a colonization -probability, because it reflects the probability of occupancy -conditional on non-occupancy during the previous timestep. The -logit-scale sum of the colonization probability and the autologistic -term gives the probability of persistence \(\mathcal{P}\).
-Thus, the autologistic model differs from the colonization-extinction -model in that it assumes that colonization and extinction probabilities -are related to one another via an offset that relates colonization to -persistence. If the offset is modeled as constant, then we can think of -this model as ascribing a “suitability” to each site that defines the -position of a pair of probabilities \(\mathcal{C}\) and \(\mathcal{P}\) that differ by a constant on -the logit scale. In practice, \(\mathcal{P}\) is almost always larger than -\(\mathcal{C}\), and so the offset is -positive.
-In addition to the standard autologistic model that treats the offset
-as a constant, flocker
also affords the flexibility to
-model the offset via its own covariate-based predictor, which
-reintroduces flexibility in the relationship between \(\mathcal{P}\) and \(\mathcal{C}\), but tends to retain the idea
-that these probabilities ought to be related to one another and ought to
-tend to move in tandem.
Most examples of multiseason occupancy models in the literature
-include an explicit model for the initial occupancy probability \(\mathcal{O}\) via its own covariate-based
-predictor, which is analogous to the occupancy predictor in a
-single-season model. Thus, a colonization-extinction model would contain
-predictors for detection, colonization, extinction, and initial
-occupancy; an autologistic model would contain linear predictors for
-detection, colonization, the colonization-persistence offset (often
-modeled as a constant), and initial occupancy. flocker
can
-fit either model.
Borrowing from the HMM literature, flocker
also comes
-with optional functionality to handle \(\mathcal{O}\) differently. Any pair of
-time-invariant colonization and extinction probabilities defines an
-equilibrium proportion of sites that are occupied. If colonization and
-extinction remain constant for a long time prior to the first timestep,
-the initial occupancy probability should simply be this equilibrium
-frequency, eliminating the need to parameterize and fit initial
-occupancy separately from colonization and extinction.
-flocker
is equipped to fit models without any separate
-predictor for initial occupancy, and instead to begin with the
-equilibrium frequencies implied by the coloniziation and extinction
-probabilities modeled for the first timestep. Note that this approach is
-sometimes valid even if the colonization and extinction probabilities
-begin to vary during the timeseries being modeled, as long as they are
-invariant for a substantial period up to and including the first year
-modeled. As a concrete example, consider a study system that begins in
-an equilibrium condition, but in which some sites burn in a forest fire
-partway through the study. If the impact of the burn on colonization and
-extinction probabilities is modeled adequately, then the modeled
-probabilites prior to the burn will reflect the equilibrium colonization
-and extinction probabilities in the pre-burn state. It is for this
-reason that, when using equilibrium frequencies as initial occupancy
-probabilities, flocker
always computes the equilibrium
-based on the probabilites modeled for the first timestep.
As an aside, we somewhat regularly encounter confusion that conflates -initial occupancy probabilities \(\mathcal{O}\) with colonization -probabilities \(\mathcal{C}\). This -confusion apparently arises from the notion that the autologistic model -consists of a single-season occupancy model plus an autologistic term, -which leads people to incorrectly surmise that the linear predictor -without the autologistic term gives an occupancy probability. It does -not; it gives a colonization probability, which is typically much lower. -Any modeling exercise that enforces equality between initial occupancy -probabilities and subsequent colonization probabilities should be viewed -skeptically.
-Let’s simulate some data that is valid for use with multiseason -models. Here, we will simulate data for three seasons with one unit -covariate and one event covariate. The data will be simulated under a -colonization-extinction model with explicit inits, but we will be able -to fit other models (autologistic, equilibrium inits) to the same -data.4
-
-library(flocker)
-multi_data <- simulate_flocker_data(
- n_season = 3,
- n_pt = 300,
- n_sp = 1,
- multiseason = "colex",
- multi_init = "explicit",
- seed = 1
- )
-
-fd <- make_flocker_data(
- multi_data$obs,
- multi_data$unit_covs,
- multi_data$event_covs,
- type = "multi",
- quiet = TRUE
- )
Here’s the colonization-extinction model with an explicit model for -occupancy in the first timestep. Depending on hardware, fitting this -model might take 1-5 minutes.
-
-multi_colex <- flock(
- f_occ = ~ uc1,
- f_det = ~ uc1 + ec1,
- f_col = ~ uc1,
- f_ex = ~ uc1,
- flocker_data = fd,
- multiseason = "colex",
- multi_init = "explicit",
- backend = "cmdstanr",
- cores = 4
-)
Here’s the colonization-extinction model using equilibrium occupancy -probabilities in the first timestep:
-
-multi_colex_eq <- flock(
- f_det = ~ uc1 + ec1,
- f_col = ~ uc1,
- f_ex = ~ uc1,
- flocker_data = fd,
- multiseason = "colex",
- multi_init = "equilibrium",
- backend = "cmdstanr",
- cores = 4
-)
Here’s the autologistic model with explicit occupancy probabilities
-in the first timestep. To reflect the stereotypical autologistic model
-with a constant logit-scale offset separating colonization and
-persistence probabilities, we use the formula f_auto = ~ 1
,
-but it is fine to relax this constraint and use,
-e.g. f_auto = ~ uc1
.
-multi_auto <- flock(
- f_occ = ~ uc1,
- f_det = ~ uc1 + ec1,
- f_col = ~ uc1,
- f_auto = ~ 1,
- flocker_data = fd,
- multiseason = "autologistic",
- multi_init = "explicit",
- backend = "cmdstanr",
- cores = 4
-)
And finally the autologistic model with equilibrium occupancy -probabilities in the first timestep:
-
-multi_auto_eq <- flock(
- f_det = ~ uc1 + ec1,
- f_col = ~ uc1,
- f_auto = ~ 1,
- flocker_data = fd,
- multiseason = "autologistic",
- multi_init = "equilibrium",
- backend = "cmdstanr",
- cores = 4
-)
We can reconstruct the occupancy probabilities at every unit using
-the get_Z
function:
-Z <- get_Z(multi_colex_eq)
We can generate posterior predictions:
-
-pp <- predict_flocker(multi_colex_eq)
We can compare the fit of these various models using approximate -leave-one-out cross-validation, where the holdouts consist of entire -series (leave-one-series-out cross-validation).
-
-loo_out <- loo_compare_flocker(
- list(multi_colex, multi_colex_eq, multi_auto, multi_auto_eq)
-)
-loo_out
See the main tutorial vignette for an example of the resulting output -(this vignette does not actual run the models to save on compuational -resources.)
-As we will see, this is true even of multiseason models -with autologistic occupancy dynamics↩︎
It’s fine if some sites are surveyed for just one -timestep, but at least some sites are surveyed for multiple timesteps.↩︎
For the curious, we use the forward algorithm to compute -the likelihood, and the forward-backward algorithm to compute unit-wise -posterior distributions for the latent occupancy state, and the -forward-filtering-backward-sampling algorithm to draw valid posterior -samples for the sequence of latent states↩︎
note that simulate_flocker_data()
can also
-simulate directly from these other model types.↩︎
vignettes/nonlinear_models.Rmd
- nonlinear_models.Rmd
Here we show how we can use flocker
to fit nonlinear
-occupancy models via brms
. In most occupancy models,
-occupancy and detection probabilties are modeled as logit-linear
-combinations of covariates. In some models (e.g. those with splines or
-Gaussian processes), probabilities are modeled as the sum of more
-flexibile functions of covariates. These are straightforward to fit in
-flocker
using the brms
functions
-s()
, t2()
, and gp()
; see the flocker
-tutorial vignette for details.
This vignette focuses on more complicated nonlinear models that
-require the use of special nonlinear brms
formulas. We
-showcase two models. The first fits a parameteric nonlinear predictor.
-The second fits a model with a spatially varying coefficient that is
-given a gaussian process prior.
In this scenario, we consider a model where the response is a -specific nonlinear parametric function whose parameters are fitted and -might or might not depend on covariates. Suppose for example that an -expanding population of a territorial species undergoes logistic growth, -and also that some unknown proportion of territories are unsuitable due -to an unobserved factor, such that occupancy asymptotes at some -probability less than one. Thus, occupancy probability changes through -time as \(\frac{L}{1 + -e^{-k(t-t_0)}}\), where \(L\) is -the asymptote, \(k\) is a growth rate, -\(t\) is time, and \(t_0\) is the timing of the inflection -point. At multiple discrete times, we randomly sample several sites to -survey, and survey each of those sites over several repeat visits.
-
-library(flocker); library(brms)
-set.seed(3)
-
-L <- 0.5
-k <- .1
-t0 <- -5
-t <- seq(-15, 15, 1)
-n_site_per_time <- 30
-n_visit <- 3
-det_prob <- .3
-
-data <- data.frame(
- t = rep(t, n_site_per_time)
-)
-
-data$psi <- L/(1 + exp(-k*(t - t0)))
-data$Z <- rbinom(nrow(data), 1, data$psi)
-data$v1 <- data$Z * rbinom(nrow(data), 1, det_prob)
-data$v2 <- data$Z * rbinom(nrow(data), 1, det_prob)
-data$v3 <- data$Z * rbinom(nrow(data), 1, det_prob)
-
-fd <- make_flocker_data(
- obs = as.matrix(data[,c("v1", "v2", "v3")]),
- unit_covs = data.frame(t = data[,c("t")]),
- event_covs <- list(dummy = matrix(rnorm(n_visit*nrow(data)), ncol = 3))
-)
We wish to fit an occupancy model that recovers the unknown
-parameters \(L\), \(k\), and \(t_0\). We can achieve this using the
-nonlinear formula syntax provided by brms
via
-flocker
.
flocker
will always assume that the occupancy formula is
-provided on the logit scale. Thus, we need to convert our nonlinear
-function giving the occupancy probability to a function giving the logit
-occupancy probability. A bit of simplification via Wolfram Alpha and we
-arrive at \(\log(\frac{L}{1 + e^{-k(t - t_0)}
-- L})\). We then write a brms
formula representing
-occupancy via this function. To specify a formula wherein a
-distributional parameter (occ
in this case, referring to
-occupancy) is nonlinear we need to use brms::set_nl()
-rather than merely providing the nl = TRUE
argument to
-brms::bf()
.
flocker
’s main fitting function flock()
-accepts brmsformula
inputs to its f_det
-argument. When supplying a brmsformula
to
-f_det
(rather than the typical one-sided detection
-formula), the following behaviors are triggered:
Several input checks are turned off. For example,
-flocker
no longer checks to ensure that event covariates
-are absent from the occupancy formula. flocker
also no
-longer explicitly checks that formulas are provided for all of the
-required distributional terms for a given family (detection, occupancy,
-colonization, extinction, and autologistic terms, depending on the
-family).
All inputs to f_occ
, f_col
,
-f_ex
, f_auto
are silently ignored. It is
-obligatory to pass the entire formula for all distributional parameters
-as a single brmsformula
object. This means in turn that the
-user must be familiar with flocker
’s internal naming
-conventions for all of the relevant distributional parameters
-(det
and one or more of occ
,
-colo
, ex
, autologistic
,
-Omega
). If fitting a data-augmented model, it will be
-requried to pass the Omega ~ 1
formula within the
-brmsformula
(When passing the traditional one-sided formula
-to f_det
, flocker
includes the formula for
-Omega
internally and automatically).
Nonlinear formulas that involve data that are required to be
-positive might fail! Internally, some irrelevant data positions get
-filled with -99
, but these positions might still get
-evaluated by the nonlinear formula, even though they make no
-contribution to the likelihood.
With all of that said, we can go ahead and fit this model!
-
-fit <- flock(f_det = brms::bf(
- det ~ 1 + dummy,
- occ ~ log(L/(1 + exp(-k*(t - t0)) - L)),
- L ~ 1,
- k ~ 1,
- t0 ~ 1
- ) +
- brms::set_nl(dpar = "occ"),
- prior =
- c(
- prior(normal(0, 5), nlpar = "t0"),
- prior(normal(0, 1), nlpar = "k"),
- prior(beta(1, 1), nlpar = "L", lb = 0, ub = 1)
- ),
- flocker_data = fd,
- control = list(adapt_delta = 0.9),
- cores = 4)
-summary(fit)
-#> Family: occupancy_single
-#> Links: mu = identity; occ = identity
-#> Formula: ff_y | vint(ff_n_unit, ff_n_rep, ff_Q, ff_rep_index1, ff_rep_index2, ff_rep_index3) ~ 1 + dummy
-#> occ ~ log(L/(1 + exp(-k * (t - t0)) - L))
-#> L ~ 1
-#> k ~ 1
-#> t0 ~ 1
-#> Data: data (Number of observations: 2790)
-#> Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
-#> total post-warmup draws = 4000
-#>
-#> Population-Level Effects:
-#> Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
-#> Intercept -0.90 0.13 -1.17 -0.66 1.00 2455 2297
-#> L_Intercept 0.51 0.10 0.37 0.75 1.00 1249 1281
-#> k_Intercept 0.19 0.08 0.07 0.38 1.00 1176 1905
-#> t0_Intercept -5.82 3.51 -10.60 3.12 1.00 1170 1384
-#> dummy -0.00 0.08 -0.15 0.14 1.00 2794 2315
-#>
-#> Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
-#> and Tail_ESS are effective sample size measures, and Rhat is the potential
-#> scale reduction factor on split chains (at convergence, Rhat = 1).
It works!
-Note that if desired, we could fit more complicated formulas than
-~ 1
for any of the nonlinear parameters. For more see the
-brms
-nonlinear model vignette.
The gp()
function in brms
includes a
-Gaussian process of arbitary dimension in the linear predictor. We can
-use the nonlinear formula syntax to tell brms
to include a
-Gaussian process prior on a coefficient as well.
First we simulate some data wherein the logit of the occupancy -probability depends on a covariate, and the slope of the dependency is -modeled via a two-dimensional spatial Gaussian process:
-
-set.seed(1)
-n <- 2000 # sample size
-lscale <- 0.3 # square root of l of the gaussian kernel
-sigma_gp <- 1 # sigma of the gaussian kernel
-intercept <- 0 # occupancy logit-intercept
-det_intercept <- -1 # detection logit-intercept
-n_visit <- 4
-
-# covariate data for the model
-gp_data <- data.frame(
- x = rnorm(n),
- y = rnorm(n),
- covariate = rnorm(n)
- )
-
-# get distance matrix
-dist.mat <- as.matrix(
- stats::dist(gp_data[,c("x", "y")])
- )
-
-# get covariance matrix
-cov.mat <- sigma_gp^2 * exp(- (dist.mat^2)/(2*lscale^2))
-
-# simulate occupancy data
-gp_data$coef <- mgcv::rmvn(1, rep(0, n), cov.mat)
-gp_data$lp <- intercept + gp_data$coef * gp_data$covariate
-gp_data$psi <- boot::inv.logit(gp_data$lp)
-gp_data$Z <- rbinom(n, 1, gp_data$psi)
-
-# simulate visit data
-obs <- matrix(nrow = n, ncol = n_visit)
-for(j in 1:n_visit){
- obs[,j] <- gp_data$Z * rbinom(n, 1, boot::inv.logit(det_intercept))
-}
And here’s how we can fit this model in flocker
! It
-turns out that we need quite a lot of data points to constrain the
-standard deviation of the Gaussian process, and so we use a Hilbert
-space approximate Gaussian process for computational efficiency.
-fd2 <- make_flocker_data(obs = obs, unit_covs = gp_data[, c("x", "y", "covariate")])
-svc_mod <- flock(
- f_det = brms::bf(
- det ~ 1,
- occ ~ occint + g * covariate,
- occint ~ 1,
- g ~ 0 + gp(x, y, scale = FALSE, k = 20, c = 1.25)
- ) +
- brms::set_nl(dpar = "occ"),
- flocker_data = fd2,
- cores = 4
-)
-summary(svc_mod)
-#> Family: occupancy_single_C
-#> Links: mu = identity; occ = identity
-#> Formula: ff_n_suc | vint(ff_n_trial) ~ 1
-#> occ ~ occint + g * covariate
-#> occint ~ 1
-#> g ~ 0 + gp(x, y, scale = FALSE, k = 20, c = 1.25)
-#> Data: data (Number of observations: 2000)
-#> Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
-#> total post-warmup draws = 4000
-#>
-#> Gaussian Process Terms:
-#> Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
-#> sdgp(g_gpxy) 1.63 0.75 0.71 3.59 1.00 2822 3271
-#> lscale(g_gpxy) 0.23 0.11 0.08 0.49 1.00 3879 3383
-#>
-#> Population-Level Effects:
-#> Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
-#> Intercept -1.04 0.06 -1.15 -0.93 1.00 5341 3409
-#> occint_Intercept 0.09 0.09 -0.08 0.27 1.00 5737 3330
-#>
-#> Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
-#> and Tail_ESS are effective sample size measures, and Rhat is the potential
-#> scale reduction factor on split chains (at convergence, Rhat = 1).
Again, it worked!
-The flocker
R package enables users to fit flexible occupancy models using the extended lme4
formula syntax provided by R package brms
. Also included are functions to format data for occupancy modeling and functions for model post-processing, including posterior predictions, the posterior distribution of the latent true occupancy state, and model comparison. flocker
is under active development: development priorities include better integrated functionality for posterior predictive checking and full cross-validation.
Compared to existing R packages for fitting occupancy models, flocker
is substantially more flexible in the variety of models that can be fit, and contains advanced functionality for model comparison and checking.
To get started, check out our tutorial vignette, available here. For installation instructions, see below.
-Install flocker
in R with
# install.packages("remotes")
-remotes::install_github("jsocolar/flocker")
-flocker
requires a working version of either rstan
or cmdstan
, which are interfaces to Stan, a state-of-the-art the probabilistic programming language. We recommend using cmdstan
if possible. To do so, first install R package cmdstanr
with
install.packages("cmdstanr", repos = c("https://mc-stan.org/r-packages/", getOption("repos")))
-You must additionally install cmdstan itself. We strongly recommend using cmdstanr
to manage the cmdstan installation:
cmdstanr::install_cmdstan()
-Both rstan
and cmdstan
require a working C++ toolchain, which has posed occasional complications for Stan users. See here for rstan
focused advice on installing the toolchain, and see here for cmdstan
focused advice. If you encounter toolchain issues that you are unable to troubleshoot, ask for help at https://discourse.mc-stan.org/.
To request a feature or report a bug (much appreciated!) please open an issue at the GitHub repository. To contribute to flocker
(very much appreciated!) have a look at existing open issues, or open a new issue to discuss.
Please cite flocker
as: * Socolar, J.B. & Mills, S.C. (2023). “flocker: flexible occupancy estimation in R.” R package version XXX, <URL: https://github.com/jsocolar/flocker/>.
Additionally, please consider citing Stan and R package brms.
-get Z given emission likelihoods and state probability
-Z_from_emission(el0, el1, psi_unconditional)
emission likelihood given state 0
emission likelihood given state 1
occupancy probability not conditioned on observation
occupancy probability conditioned on observation
-Backward algorithm
-backward_algorithm(el0, el1, colo, ex)
the emission probabilities given non-occupancy
the emission probabilities given occupancy
a vector giving the colonization probs
a vector giving the extinction probs
an n x 2 matrix giving the backward probabilities
-R/utils.R
- emission_likelihood.Rd
Get emission likelihoods given observations and detection probabilities
-emission_likelihood(state, obs, det)
Compute the emission likelihood for absence (0) or presence (1)
A matrix of observation histories. Rows are units, columns are visits.
A matrix of detection probabilities
a vector of emission likelihoods (one per row)
-Example data to be formatted for use in a single-season occupancy model
-example_flocker_data
## `example_flocker_data` -A list with elements appropriate to pass to make_flocker_data:
A detection/nondetection matrix. Rows are units and colums are - visits
A data.frame of four unit covs. `uc1` and `uc2` are - numeric; `grp` and `species` are categorical. Every level of `species` is - present for every value of `uc1` and `uc2`, as would be the case in a - typical multispecies model
A named list of two matrices, each representing a numeric - covariate that varies by visit but not by species
data-raw/example_flocker_data.R
-A fitted data-augmented occupancy model from flocker
-example_flocker_model_aug
## `example_flocker_model_aug` -A flocker_fit and brmsfit object
-data-raw/example_flocker_model.R
-R/data.R
- example_flocker_model_multi_auto_eq.Rd
A fitted multi-season occupancy model from flocker. -One species 200 point, six season, four rep, missing seasons, missing reps. -autologistic parameterization with equilibrium init.
-example_flocker_model_multi_auto_eq
## `example_flocker_model_multi_auto_eq` -A flocker_fit and brmsfit object
-data-raw/example_flocker_model.R
-R/data.R
- example_flocker_model_multi_auto_ex.Rd
A fitted multi-season occupancy model from flocker. -One species 200 point, six season, four rep, missing seasons, missing reps. -autologistic parameterization with explicit init.
-example_flocker_model_multi_auto_ex
## `example_flocker_model_multi_auto_ex` -A flocker_fit and brmsfit object
-data-raw/example_flocker_model.R
-R/data.R
- example_flocker_model_multi_colex_eq.Rd
A fitted multi-season occupancy model from flocker. -One species 200 point, six season, four rep, missing seasons, missing reps. -colex parameterization with equilibrium init.
-example_flocker_model_multi_colex_eq
## `example_flocker_model_multi_colex_eq` -A flocker_fit and brmsfit object
-data-raw/example_flocker_model.R
-R/data.R
- example_flocker_model_multi_colex_ex.Rd
A fitted multi-season occupancy model from flocker. -One species 200 point, six season, four rep, missing seasons, missing reps. -colex parameterization with explicit init.
-example_flocker_model_multi_colex_ex
## `example_flocker_model_multi_colex_ex` -A flocker_fit and brmsfit object
-data-raw/example_flocker_model.R
-A fitted single-season occupancy model from flocker
-example_flocker_model_single
## `example_flocker_model_single` -A flocker_fit and brmsfit object
-data-raw/example_flocker_model.R
-R/data.R
- example_flocker_model_single_C.Rd
A fitted single-season rep-constant occupancy model from flocker
-example_flocker_model_single_C
## `example_flocker_model_single_C` -A flocker_fit and brmsfit object
-data-raw/example_flocker_model.R
-convert array to long matrix format
-expand_array_3D(a)
3D array to expand
matrix
-convert matrix-like object to long vector format
-expand_matrix(m)
matrix-like object to expand
vector
-extended binomial RNG
-extended_binomial_rng(p, s)
binomial probability
number of successes
a sample representing a possible number of trials
-random samples `y` from the distribution proportional to - binomial_pmf(y | n, s)
-flocker data type lookup
-fdtl()
dataframe giving lookup table for data input types, data output types - and model types
-R/fitted_flocker.R
- fitted_flocker.Rd
Get expected values of the posterior predictive distribution for the modeled -probabilities (occupancy, detection, colonization, extinction, autologistic).
-fitted_flocker(
- flocker_fit,
- components = c("occ", "det", "col", "ex", "auto", "Omega"),
- new_data = NULL,
- unit_level = FALSE,
- summarise = FALSE,
- CI = c(0.05, 0.95),
- draw_ids = NULL,
- response = TRUE,
- re_formula = NULL,
- allow_new_levels = FALSE,
- sample_new_levels = "uncertainty"
-)
A flocker_fit object.
a character vector specifying one or more of "occ", -"det", "col", "ex", "auto", and "Omega" for which to obtain fitted values.
Optional new data at which to evaluate occupancy predictions.
-New data can be passed as a flocker_data object produced by
-make_flocker_data
or as a dataframe with one row per desired
-predicton. If `NULL` (the default) expected values are generated for the
-original data as formatted by make_flocker_data.
Logical; defaults to FALSE. Relevant only when `new_data` -is not a dataframe (i.e. it is `NULL` or a flocker_data object), and useful -only for multiseason models with missing seasons. If FALSE, returns in the -shape of the observation matrix/array with NAs for missing visits. If -TRUE, returns in the shape of the first visit, and returns values for all -units that are not part of a trailing block of never-visited units, -including never-visited units that are part of series with subsequent -visits.
if TRUE, return the expected value and upper and lower bound -of the credible interval, otherwise return posterior draws.
A vector of length 2 specifying the upper and lower bounds of the -credible interval.
Vector of indices of the posterior draws to be -used. If `NULL` (the default) all draws are used in their native order.
Should results be returned on the response or logit scale? -Defaults to `TRUE`, i.e. response scale. However, the autologistic -parameter is not interpretable as a probability and is always returned -on the logit scale regardless of the value of `response`
formula containing group-level effects to be considered in -the prediction. If `NULL` (default), include all group-level effects; if -NA, include no group-level effects.
allow new levels for random effect terms in `new_data`? -Will error if set to `FALSE` and new levels are provided in `new_data`.
If new_data is provided and contains random effect -levels not present in the original data, how should predictions be -handled? Passed directly to `brms::prepare_predictions`, which see.
A list of sets of expected values (one per component). If `new_data` - is a dataframe, each element contains one row per row of `new_data`. - Otherwise, returns in the shape of the observation matrix/array used - to format the flocker_data (but see `unit_level` parameter for further - details).
-The probabilities returned are conditional probabilties (e.g. detection -conditional on occupancy, colonization conditional on previous -non-occupancy, etc). These probabilities are not conditioned on the -observed histories (e.g. the occupancy probability is not fixed to one -at sites with a detection; it is estimated only based on the covariates).
-fitted_flocker(
- example_flocker_model_single,
- summarise = TRUE,
- draw_ids = 1:10
-)
-#> $linpred_occ
-#> , , mean
-#>
-#> visit_1 visit_2 visit_3 visit_4
-#> site_1 0.30506014 0.30506014 0.30506014 0.30506014
-#> site_2 0.25214314 0.25214314 0.25214314 0.25214314
-#> site_3 0.27880227 0.27880227 0.27880227 0.27880227
-#> site_4 0.25791155 0.25791155 0.25791155 0.25791155
-#> site_5 0.29628128 0.29628128 0.29628128 0.29628128
-#> site_6 0.25909364 0.25909364 0.25909364 0.25909364
-#> site_7 0.26196866 0.26196866 0.26196866 0.26196866
-#> site_8 0.27550033 0.27550033 0.27550033 0.27550033
-#> site_9 0.27487547 0.27487547 0.27487547 0.27487547
-#> site_10 0.22613233 0.22613233 0.22613233 0.22613233
-#> site_11 0.26935507 0.26935507 0.26935507 0.26935507
-#> site_12 0.27228569 0.27228569 0.27228569 0.27228569
-#> site_13 0.26874439 0.26874439 0.26874439 0.26874439
-#> site_14 0.26664029 0.26664029 0.26664029 0.26664029
-#> site_15 0.26262186 0.26262186 0.26262186 0.26262186
-#> site_16 0.23214165 0.23214165 0.23214165 0.23214165
-#> site_17 0.25561468 0.25561468 0.25561468 0.25561468
-#> site_18 0.26946611 0.26946611 0.26946611 0.26946611
-#> site_19 0.29171489 0.29171489 0.29171489 0.29171489
-#> site_20 0.26241417 0.26241417 0.26241417 0.26241417
-#> site_21 0.21804653 0.21804653 0.21804653 0.21804653
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-#> , , Q5
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-#> site_677 0.25158824 0.25158824 0.25158824 0.25158824
-#> site_678 0.29032144 0.29032144 0.29032144 0.29032144
-#> site_679 0.27667424 0.27667424 0.27667424 0.27667424
-#> site_680 0.24229787 0.24229787 0.24229787 0.24229787
-#> site_681 0.17753732 0.17753732 0.17753732 0.17753732
-#> site_682 0.27488209 0.27488209 0.27488209 0.27488209
-#> site_683 0.20533100 0.20533100 0.20533100 0.20533100
-#> site_684 0.32405139 0.32405139 0.32405139 0.32405139
-#> site_685 0.18985977 0.18985977 0.18985977 0.18985977
-#> site_686 0.18161122 0.18161122 0.18161122 0.18161122
-#> site_687 0.32033785 0.32033785 0.32033785 0.32033785
-#> site_688 0.27326565 0.27326565 0.27326565 0.27326565
-#> site_689 0.28193187 0.28193187 0.28193187 0.28193187
-#> site_690 0.25053074 0.25053074 0.25053074 0.25053074
-#> site_691 0.40257041 0.40257041 0.40257041 0.40257041
-#> site_692 0.26945356 0.26945356 0.26945356 0.26945356
-#> site_693 0.39419245 0.39419245 0.39419245 0.39419245
-#> site_694 0.26370338 0.26370338 0.26370338 0.26370338
-#> site_695 0.36779920 0.36779920 0.36779920 0.36779920
-#> site_696 0.28302464 0.28302464 0.28302464 0.28302464
-#> site_697 0.29276927 0.29276927 0.29276927 0.29276927
-#> site_698 0.33589645 0.33589645 0.33589645 0.33589645
-#> site_699 0.30244148 0.30244148 0.30244148 0.30244148
-#> site_700 0.24869385 0.24869385 0.24869385 0.24869385
-#> site_701 0.31276566 0.31276566 0.31276566 0.31276566
-#> site_702 0.31684073 0.31684073 0.31684073 0.31684073
-#> site_703 0.28978758 0.28978758 0.28978758 0.28978758
-#> site_704 0.34127678 0.34127678 0.34127678 0.34127678
-#> site_705 0.27940992 0.27940992 0.27940992 0.27940992
-#> site_706 0.27178350 0.27178350 0.27178350 0.27178350
-#> site_707 0.28870277 0.28870277 0.28870277 0.28870277
-#> site_708 0.35778836 0.35778836 0.35778836 0.35778836
-#> site_709 0.31776957 0.31776957 0.31776957 0.31776957
-#> site_710 0.28379299 0.28379299 0.28379299 0.28379299
-#> site_711 0.23962747 0.23962747 0.23962747 0.23962747
-#> site_712 0.31219765 0.31219765 0.31219765 0.31219765
-#> site_713 0.24932686 0.24932686 0.24932686 0.24932686
-#> site_714 0.34312669 0.34312669 0.34312669 0.34312669
-#> site_715 0.24405599 0.24405599 0.24405599 0.24405599
-#> site_716 0.23062977 0.23062977 0.23062977 0.23062977
-#> site_717 0.35225371 0.35225371 0.35225371 0.35225371
-#> site_718 0.30455563 0.30455563 0.30455563 0.30455563
-#> site_719 0.31161613 0.31161613 0.31161613 0.31161613
-#> site_720 0.29350196 0.29350196 0.29350196 0.29350196
-#> site_721 0.41227788 0.41227788 0.41227788 0.41227788
-#> site_722 0.28978005 0.28978005 0.28978005 0.28978005
-#> site_723 0.40836077 0.40836077 0.40836077 0.40836077
-#> site_724 0.28445290 0.28445290 0.28445290 0.28445290
-#> site_725 0.38308713 0.38308713 0.38308713 0.38308713
-#> site_726 0.29547110 0.29547110 0.29547110 0.29547110
-#> site_727 0.31120541 0.31120541 0.31120541 0.31120541
-#> site_728 0.35120563 0.35120563 0.35120563 0.35120563
-#> site_729 0.31577974 0.31577974 0.31577974 0.31577974
-#> site_730 0.26886452 0.26886452 0.26886452 0.26886452
-#> site_731 0.33280291 0.33280291 0.33280291 0.33280291
-#> site_732 0.33522893 0.33522893 0.33522893 0.33522893
-#> site_733 0.30945506 0.30945506 0.30945506 0.30945506
-#> site_734 0.35299245 0.35299245 0.35299245 0.35299245
-#> site_735 0.29549690 0.29549690 0.29549690 0.29549690
-#> site_736 0.28909340 0.28909340 0.28909340 0.28909340
-#> site_737 0.30242095 0.30242095 0.30242095 0.30242095
-#> site_738 0.38331082 0.38331082 0.38331082 0.38331082
-#> site_739 0.33288763 0.33288763 0.33288763 0.33288763
-#> site_740 0.29938500 0.29938500 0.29938500 0.29938500
-#> site_741 0.26456581 0.26456581 0.26456581 0.26456581
-#> site_742 0.32624390 0.32624390 0.32624390 0.32624390
-#> site_743 0.26612287 0.26612287 0.26612287 0.26612287
-#> site_744 0.35420340 0.35420340 0.35420340 0.35420340
-#> site_745 0.26747237 0.26747237 0.26747237 0.26747237
-#> site_746 0.24991334 0.24991334 0.24991334 0.24991334
-#> site_747 0.36374691 0.36374691 0.36374691 0.36374691
-#> site_748 0.31601180 0.31601180 0.31601180 0.31601180
-#> site_749 0.32246170 0.32246170 0.32246170 0.32246170
-#> site_750 0.30949976 0.30949976 0.30949976 0.30949976
-#> site_751 0.31975397 0.31975397 0.31975397 0.31975397
-#> site_752 0.12991976 0.12991976 0.12991976 0.12991976
-#> site_753 0.27848410 0.27848410 0.27848410 0.27848410
-#> site_754 0.12300399 0.12300399 0.12300399 0.12300399
-#> site_755 0.24167878 0.24167878 0.24167878 0.24167878
-#> site_756 0.18498884 0.18498884 0.18498884 0.18498884
-#> site_757 0.15855462 0.15855462 0.15855462 0.15855462
-#> site_758 0.21530475 0.21530475 0.21530475 0.21530475
-#> site_759 0.19621581 0.19621581 0.19621581 0.19621581
-#> site_760 0.11153893 0.11153893 0.11153893 0.11153893
-#> site_761 0.17108305 0.17108305 0.17108305 0.17108305
-#> site_762 0.17638791 0.17638791 0.17638791 0.17638791
-#> site_763 0.16488731 0.16488731 0.16488731 0.16488731
-#> site_764 0.25037088 0.25037088 0.25037088 0.25037088
-#> site_765 0.15824382 0.15824382 0.15824382 0.15824382
-#> site_766 0.14464727 0.14464727 0.14464727 0.14464727
-#> site_767 0.18109311 0.18109311 0.18109311 0.18109311
-#> site_768 0.18045716 0.18045716 0.18045716 0.18045716
-#> site_769 0.19998645 0.19998645 0.19998645 0.19998645
-#> site_770 0.16698586 0.16698586 0.16698586 0.16698586
-#> site_771 0.08900340 0.08900340 0.08900340 0.08900340
-#> site_772 0.21048547 0.21048547 0.21048547 0.21048547
-#> site_773 0.12889822 0.12889822 0.12889822 0.12889822
-#> site_774 0.28523006 0.28523006 0.28523006 0.28523006
-#> site_775 0.10568829 0.10568829 0.10568829 0.10568829
-#> site_776 0.10332263 0.10332263 0.10332263 0.10332263
-#> site_777 0.25588745 0.25588745 0.25588745 0.25588745
-#> site_778 0.21208514 0.21208514 0.21208514 0.21208514
-#> site_779 0.22257038 0.22257038 0.22257038 0.22257038
-#> site_780 0.17093454 0.17093454 0.17093454 0.17093454
-#> site_781 0.63027480 0.63027480 0.63027480 0.63027480
-#> site_782 0.65001320 0.65001320 0.65001320 0.65001320
-#> site_783 0.66564557 0.66564557 0.66564557 0.66564557
-#> site_784 0.69392958 0.69392958 0.69392958 0.69392958
-#> site_785 0.66197791 0.66197791 0.66197791 0.66197791
-#> site_786 0.66326750 0.66326750 0.66326750 0.66326750
-#> site_787 0.69125079 0.69125079 0.69125079 0.69125079
-#> site_788 0.66466646 0.66466646 0.66466646 0.66466646
-#> site_789 0.63619485 0.63619485 0.63619485 0.63619485
-#> site_790 0.72717165 0.72717165 0.72717165 0.72717165
-#> site_791 0.67949779 0.67949779 0.67949779 0.67949779
-#> site_792 0.69195358 0.69195358 0.69195358 0.69195358
-#> site_793 0.66563189 0.66563189 0.66563189 0.66563189
-#> site_794 0.69056088 0.69056088 0.69056088 0.69056088
-#> site_795 0.65663119 0.65663119 0.65663119 0.65663119
-#> site_796 0.64973866 0.64973866 0.64973866 0.64973866
-#> site_797 0.64532665 0.64532665 0.64532665 0.64532665
-#> site_798 0.77921316 0.77921316 0.77921316 0.77921316
-#> site_799 0.66607549 0.66607549 0.66607549 0.66607549
-#> site_800 0.66503335 0.66503335 0.66503335 0.66503335
-#> site_801 0.74660737 0.74660737 0.74660737 0.74660737
-#> site_802 0.65971023 0.65971023 0.65971023 0.65971023
-#> site_803 0.63944788 0.63944788 0.63944788 0.63944788
-#> site_804 0.69940178 0.69940178 0.69940178 0.69940178
-#> site_805 0.70482604 0.70482604 0.70482604 0.70482604
-#> site_806 0.68433561 0.68433561 0.68433561 0.68433561
-#> site_807 0.63414462 0.63414462 0.63414462 0.63414462
-#> site_808 0.63307935 0.63307935 0.63307935 0.63307935
-#> site_809 0.65255060 0.65255060 0.65255060 0.65255060
-#> site_810 0.66798803 0.66798803 0.66798803 0.66798803
-#> site_811 0.49187758 0.49187758 0.49187758 0.49187758
-#> site_812 0.46720165 0.46720165 0.46720165 0.46720165
-#> site_813 0.52075172 0.52075172 0.52075172 0.52075172
-#> site_814 0.48208554 0.48208554 0.48208554 0.48208554
-#> site_815 0.52679461 0.52679461 0.52679461 0.52679461
-#> site_816 0.45638706 0.45638706 0.45638706 0.45638706
-#> site_817 0.49356457 0.49356457 0.49356457 0.49356457
-#> site_818 0.47515973 0.47515973 0.47515973 0.47515973
-#> site_819 0.44760031 0.44760031 0.44760031 0.44760031
-#> site_820 0.44814223 0.44814223 0.44814223 0.44814223
-#> site_821 0.51730905 0.51730905 0.51730905 0.51730905
-#> site_822 0.49637285 0.49637285 0.49637285 0.49637285
-#> site_823 0.48116077 0.48116077 0.48116077 0.48116077
-#> site_824 0.47262722 0.47262722 0.47262722 0.47262722
-#> site_825 0.45082452 0.45082452 0.45082452 0.45082452
-#> site_826 0.44317157 0.44317157 0.44317157 0.44317157
-#> site_827 0.45454752 0.45454752 0.45454752 0.45454752
-#> site_828 0.59402057 0.59402057 0.59402057 0.59402057
-#> site_829 0.49562464 0.49562464 0.49562464 0.49562464
-#> site_830 0.45008289 0.45008289 0.45008289 0.45008289
-#> site_831 0.50145982 0.50145982 0.50145982 0.50145982
-#> site_832 0.44703162 0.44703162 0.44703162 0.44703162
-#> site_833 0.43551427 0.43551427 0.43551427 0.43551427
-#> site_834 0.51959975 0.51959975 0.51959975 0.51959975
-#> site_835 0.49182191 0.49182191 0.49182191 0.49182191
-#> site_836 0.44203816 0.44203816 0.44203816 0.44203816
-#> site_837 0.47349718 0.47349718 0.47349718 0.47349718
-#> site_838 0.43545447 0.43545447 0.43545447 0.43545447
-#> site_839 0.42565758 0.42565758 0.42565758 0.42565758
-#> site_840 0.44626277 0.44626277 0.44626277 0.44626277
-#> site_841 0.36513027 0.36513027 0.36513027 0.36513027
-#> site_842 0.19999881 0.19999881 0.19999881 0.19999881
-#> site_843 0.34123841 0.34123841 0.34123841 0.34123841
-#> site_844 0.19256141 0.19256141 0.19256141 0.19256141
-#> site_845 0.31030156 0.31030156 0.31030156 0.31030156
-#> site_846 0.23723542 0.23723542 0.23723542 0.23723542
-#> site_847 0.22769021 0.22769021 0.22769021 0.22769021
-#> site_848 0.27954436 0.27954436 0.27954436 0.27954436
-#> site_849 0.25321681 0.25321681 0.25321681 0.25321681
-#> site_850 0.17945926 0.17945926 0.17945926 0.17945926
-#> site_851 0.24071268 0.24071268 0.24071268 0.24071268
-#> site_852 0.25004453 0.25004453 0.25004453 0.25004453
-#> site_853 0.22837733 0.22837733 0.22837733 0.22837733
-#> site_854 0.29852125 0.29852125 0.29852125 0.29852125
-#> site_855 0.22151672 0.22151672 0.22151672 0.22151672
-#> site_856 0.21018754 0.21018754 0.21018754 0.21018754
-#> site_857 0.23843733 0.23843733 0.23843733 0.23843733
-#> site_858 0.26729870 0.26729870 0.26729870 0.26729870
-#> site_859 0.26206498 0.26206498 0.26206498 0.26206498
-#> site_860 0.22787169 0.22787169 0.22787169 0.22787169
-#> site_861 0.15766324 0.15766324 0.15766324 0.15766324
-#> site_862 0.26193265 0.26193265 0.26193265 0.26193265
-#> site_863 0.19030905 0.19030905 0.19030905 0.19030905
-#> site_864 0.31710373 0.31710373 0.31710373 0.31710373
-#> site_865 0.17201610 0.17201610 0.17201610 0.17201610
-#> site_866 0.16562187 0.16562187 0.16562187 0.16562187
-#> site_867 0.30869994 0.30869994 0.30869994 0.30869994
-#> site_868 0.26205279 0.26205279 0.26205279 0.26205279
-#> site_869 0.27119492 0.27119492 0.27119492 0.27119492
-#> site_870 0.23544696 0.23544696 0.23544696 0.23544696
-#> site_871 0.72774895 0.72774895 0.72774895 0.72774895
-#> site_872 0.76026444 0.76026444 0.76026444 0.76026444
-#> site_873 0.78550099 0.78550099 0.78550099 0.78550099
-#> site_874 0.79776818 0.79776818 0.79776818 0.79776818
-#> site_875 0.75806990 0.75806990 0.75806990 0.75806990
-#> site_876 0.78105396 0.78105396 0.78105396 0.78105396
-#> site_877 0.80197882 0.80197882 0.80197882 0.80197882
-#> site_878 0.78819423 0.78819423 0.78819423 0.78819423
-#> site_879 0.73627522 0.73627522 0.73627522 0.73627522
-#> site_880 0.85090266 0.85090266 0.85090266 0.85090266
-#> site_881 0.77184434 0.77184434 0.77184434 0.77184434
-#> site_882 0.80615258 0.80615258 0.80615258 0.80615258
-#> site_883 0.76564175 0.76564175 0.76564175 0.76564175
-#> site_884 0.81169210 0.81169210 0.81169210 0.81169210
-#> site_885 0.76358417 0.76358417 0.76358417 0.76358417
-#> site_886 0.76822422 0.76822422 0.76822422 0.76822422
-#> site_887 0.75383213 0.75383213 0.75383213 0.75383213
-#> site_888 0.87078662 0.87078662 0.87078662 0.87078662
-#> site_889 0.76717122 0.76717122 0.76717122 0.76717122
-#> site_890 0.77504476 0.77504476 0.77504476 0.77504476
-#> site_891 0.86001378 0.86001378 0.86001378 0.86001378
-#> site_892 0.78415766 0.78415766 0.78415766 0.78415766
-#> site_893 0.75020019 0.75020019 0.75020019 0.75020019
-#> site_894 0.79145116 0.79145116 0.79145116 0.79145116
-#> site_895 0.81242341 0.81242341 0.81242341 0.81242341
-#> site_896 0.80434574 0.80434574 0.80434574 0.80434574
-#> site_897 0.74851139 0.74851139 0.74851139 0.74851139
-#> site_898 0.74848321 0.74848321 0.74848321 0.74848321
-#> site_899 0.77334290 0.77334290 0.77334290 0.77334290
-#> site_900 0.78528679 0.78528679 0.78528679 0.78528679
-#>
-#>
-#> $linpred_det
-#> , , mean
-#>
-#> visit_1 visit_2 visit_3 visit_4
-#> site_1 0.4203014 0.63416438 0.25865238 0.3886053
-#> site_2 0.4163406 0.62105821 0.25730148 0.3854787
-#> site_3 0.4546375 0.65379665 0.29120076 0.4236528
-#> site_4 0.3371438 0.53364543 0.20115036 0.3097778
-#> site_5 0.5732667 0.74245516 0.40884510 0.5441400
-#> site_6 0.3335865 0.53770624 0.19479247 0.3054522
-#> site_7 0.3385041 0.53298977 0.20304481 0.3113321
-#> site_8 0.2841800 0.48887421 0.15866383 0.2578255
-#> site_9 0.3214210 0.53242446 0.18131499 0.2926380
-#> site_10 0.5201576 0.70780621 0.34902197 0.4889351
-#> site_11 0.4376287 0.63433650 0.27961777 0.4074920
-#> site_12 0.3511914 0.56072946 0.20542606 0.3218247
-#> site_13 0.3796956 0.58611745 0.22730544 0.3495920
-#> site_14 0.5081645 0.70137156 0.33311967 0.4760938
-#> site_15 0.5580858 0.72769212 0.39767151 0.5294072
-#> site_16 0.2995705 0.51032910 0.16701915 0.2718959
-#> site_17 0.4721510 0.66007060 0.30906538 0.4419473
-#> site_18 0.3405669 0.54651217 0.19672393 0.3115792
-#> site_19 0.4289668 0.62249166 0.27594746 0.3996348
-#> site_20 0.3373476 0.53887897 0.19615361 0.3089328
-#> site_21 0.3746457 0.58097932 0.22378806 0.3447492
-#> site_22 0.3945609 0.61394175 0.22975843 0.3619734
-#> site_23 0.5048083 0.69509417 0.33547981 0.4736998
-#> site_24 0.3034228 0.51818125 0.16759447 0.2750124
-#> site_25 0.3321087 0.54264870 0.18976562 0.3030958
-#> site_26 0.4192417 0.62291064 0.26061311 0.3885333
-#> site_27 0.4238904 0.63582025 0.25806023 0.3917486
-#> site_28 0.3248971 0.52831938 0.18731167 0.2969313
-#> site_29 0.4609404 0.65949460 0.29594385 0.4297779
-#> site_30 0.3013508 0.51471975 0.16641027 0.2731600
-#> site_31 0.4590499 0.26581181 0.38217713 0.2345144
-#> site_32 0.4654659 0.27350340 0.39025910 0.2416089
-#> site_33 0.4788452 0.28683296 0.40422839 0.2543055
-#> site_34 0.3885359 0.21807068 0.31955779 0.1914213
-#> site_35 0.5994049 0.40783996 0.52956327 0.3710933
-#> site_36 0.3776890 0.20604915 0.30753025 0.1797529
-#> site_37 0.3847473 0.21846857 0.31761669 0.1922481
-#> site_38 0.3338146 0.17294666 0.26611322 0.1497118
-#> site_39 0.3662926 0.19293553 0.29475386 0.1670242
-#> site_40 0.5434776 0.34364129 0.46846951 0.3075775
-#> site_41 0.4636038 0.27746740 0.39095006 0.2461429
-#> site_42 0.3988298 0.21798382 0.32535780 0.1900019
-#> site_43 0.4195342 0.23558671 0.34596880 0.2062538
-#> site_44 0.5461625 0.34113567 0.46941133 0.3040561
-#> site_45 0.5805878 0.39216718 0.51117418 0.3566446
-#> site_46 0.3447152 0.17832279 0.27497525 0.1541513
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-#> site_774 0.5248353 0.5223012 0.4903611 0.3347257
-#> site_775 0.5131043 0.5106449 0.4795290 0.3277850
-#> site_776 0.6568339 0.6546487 0.6264677 0.4729708
-#> site_777 0.6497785 0.6473826 0.6164650 0.4488796
-#> site_778 0.4814635 0.4789329 0.4470877 0.3014577
-#> site_779 0.6891701 0.6871040 0.6603521 0.5109424
-#> site_780 0.4430502 0.4405897 0.4097715 0.2674607
-#> site_781 0.7059294 0.4601659 0.5920115 0.5591608
-#> site_782 0.6892197 0.3976120 0.5505361 0.5109485
-#> site_783 0.6583282 0.3960803 0.5329478 0.4979943
-#> site_784 0.7025673 0.4327134 0.5671729 0.5335265
-#> site_785 0.7665375 0.5360443 0.6587489 0.6290286
-#> site_786 0.6182892 0.3463493 0.4849125 0.4487867
-#> site_787 0.6604759 0.4045053 0.5385304 0.5044277
-#> site_788 0.6360476 0.3734603 0.5083778 0.4734009
-#> site_789 0.6253643 0.3408565 0.4858261 0.4479415
-#> site_790 0.7263630 0.4392028 0.5956128 0.5568380
-#> site_791 0.6496452 0.3768097 0.5182661 0.4818781
-#> site_792 0.6576937 0.3695445 0.5187504 0.4800109
-#> site_793 0.6512121 0.3567497 0.5056165 0.4654149
-#> site_794 0.7593120 0.4822947 0.6369300 0.5994513
-#> site_795 0.7155134 0.4791879 0.5943464 0.5601109
-#> site_796 0.6121640 0.3546479 0.4862746 0.4521262
-#> site_797 0.8202790 0.5740864 0.7193659 0.6861503
-#> site_798 0.6702864 0.3755335 0.5284584 0.4885619
-#> site_799 0.6822507 0.4487505 0.5618781 0.5334987
-#> site_800 0.6120924 0.3321542 0.4743544 0.4371176
-#> site_801 0.6411990 0.3822306 0.5163501 0.4819067
-#> site_802 0.6260510 0.3565474 0.4941054 0.4583755
-#> site_803 0.6891823 0.4246744 0.5648242 0.5295070
-#> site_804 0.5963813 0.3194456 0.4582840 0.4215184
-#> site_805 0.5731544 0.3009000 0.4345314 0.3988495
-#> site_806 0.6677367 0.4150724 0.5479408 0.5142714
-#> site_807 0.7414710 0.4682879 0.6185807 0.5817243
-#> site_808 0.7090651 0.4384422 0.5847646 0.5484007
-#> site_809 0.6622264 0.3828941 0.5274894 0.4902328
-#> site_810 0.6003264 0.3215433 0.4617305 0.4247583
-#> site_811 0.3523133 0.5357322 0.4078162 0.3228159
-#> site_812 0.3033107 0.4805985 0.3496697 0.2789543
-#> site_813 0.3589350 0.5549687 0.4184438 0.3273436
-#> site_814 0.3423337 0.5188745 0.3948117 0.3147373
-#> site_815 0.4843633 0.6633374 0.5411985 0.4526059
-#> site_816 0.2670508 0.4503764 0.3197034 0.2400965
-#> site_817 0.2932476 0.4709371 0.3452755 0.2661996
-#> site_818 0.2554933 0.4357098 0.3065527 0.2294699
-#> site_819 0.2439267 0.4286092 0.2951187 0.2186204
-#> site_820 0.3619522 0.5618883 0.4228982 0.3314462
-#> site_821 0.3374789 0.5285563 0.3911919 0.3090002
-#> site_822 0.2992921 0.4889163 0.3548973 0.2704540
-#> site_823 0.2651243 0.4640650 0.3179131 0.2387844
-#> site_824 0.3780283 0.6000442 0.4469191 0.3413013
-#> site_825 0.4592141 0.6512695 0.5210115 0.4276964
-#> site_826 0.2809033 0.4580974 0.3323986 0.2542825
-#> site_827 0.4492552 0.6812301 0.5252551 0.4086092
-#> site_828 0.2708497 0.4773740 0.3301986 0.2406784
-#> site_829 0.3572275 0.5350141 0.4111187 0.3308400
-#> site_830 0.2708521 0.4636880 0.3263236 0.2425201
-#> site_831 0.2877763 0.4668306 0.3398812 0.2607758
-#> site_832 0.2601769 0.4426646 0.3114915 0.2339749
-#> site_833 0.3860994 0.5855232 0.4477298 0.3530178
-#> site_834 0.2449350 0.4245185 0.2957179 0.2192054
-#> site_835 0.2439344 0.4217014 0.2941581 0.2184858
-#> site_836 0.3418967 0.5254438 0.3972024 0.3125882
-#> site_837 0.3525631 0.5646492 0.4171070 0.3184783
-#> site_838 0.3051297 0.4993960 0.3627816 0.2750977
-#> site_839 0.3464842 0.5390937 0.4028016 0.3166216
-#> site_840 0.2391815 0.4156226 0.2880241 0.2144405
-#> site_841 0.5867442 0.6559067 0.3530277 0.6780212
-#> site_842 0.5032865 0.5792605 0.2877523 0.6055241
-#> site_843 0.7009052 0.7607970 0.4658989 0.7790895
-#> site_844 0.5637288 0.6313711 0.3492175 0.6531229
-#> site_845 0.7867739 0.8330834 0.5793494 0.8467800
-#> site_846 0.4757580 0.5518246 0.2614457 0.5774631
-#> site_847 0.4442233 0.5142308 0.2423235 0.5378814
-#> site_848 0.4691427 0.5456514 0.2516735 0.5711949
-#> site_849 0.4466790 0.5210602 0.2353585 0.5461324
-#> site_850 0.7494902 0.8032214 0.5210816 0.8192759
-#> site_851 0.6639540 0.7263254 0.4309469 0.7456992
-#> site_852 0.5962287 0.6666520 0.3539172 0.6889930
-#> site_853 0.5790849 0.6532755 0.3331300 0.6769842
-#> site_854 0.6722229 0.7374333 0.4257458 0.7574827
-#> site_855 0.8237622 0.8626321 0.6419367 0.8740410
-#> site_856 0.4898152 0.5620340 0.2733653 0.5861075
-#> site_857 0.7474577 0.8002218 0.5263533 0.8160757
-#> site_858 0.4793266 0.5638630 0.2360346 0.5918289
-#> site_859 0.6132138 0.6791887 0.3896230 0.7001213
-#> site_860 0.5368577 0.6140473 0.2953603 0.6392263
-#> site_861 0.4715085 0.5536336 0.2478670 0.5810123
-#> site_862 0.5409239 0.6315064 0.2594618 0.6604470
-#> site_863 0.7322808 0.7882642 0.5014106 0.8051223
-#> site_864 0.5051358 0.5800670 0.2747334 0.6046997
-#> site_865 0.4888640 0.5637175 0.2688472 0.5890883
-#> site_866 0.6280317 0.6926917 0.3977928 0.7130834
-#> site_867 0.6167061 0.6878480 0.3664812 0.7101943
-#> site_868 0.4944050 0.5717641 0.2660574 0.5972600
-#> site_869 0.6541520 0.7162042 0.4259560 0.7359128
-#> site_870 0.4427018 0.5172739 0.2314648 0.5424856
-#> site_871 0.7316059 0.4206630 0.6271993 0.7292653
-#> site_872 0.7214191 0.3580689 0.5946840 0.7186033
-#> site_873 0.6541655 0.3219341 0.5334072 0.6513549
-#> site_874 0.7228041 0.3875573 0.5974076 0.7199266
-#> site_875 0.7746642 0.4628159 0.6659983 0.7723157
-#> site_876 0.6601405 0.3122370 0.5269193 0.6567751
-#> site_877 0.6939865 0.3755737 0.5814064 0.6914173
-#> site_878 0.6836369 0.3607311 0.5677984 0.6809689
-#> site_879 0.6558217 0.2989510 0.5249461 0.6527882
-#> site_880 0.7489500 0.3886689 0.6306058 0.7463743
-#> site_881 0.6426225 0.2985804 0.5154904 0.6396511
-#> site_882 0.6760897 0.3121651 0.5428570 0.6728804
-#> site_883 0.6711204 0.3149552 0.5343770 0.6679847
-#> site_884 0.7765283 0.4270387 0.6669000 0.7741889
-#> site_885 0.7244320 0.4273235 0.6072429 0.7218195
-#> site_886 0.6248900 0.3024369 0.5055663 0.6220754
-#> site_887 0.8371909 0.5270020 0.7510486 0.8354262
-#> site_888 0.6950048 0.3411424 0.5715970 0.6922204
-#> site_889 0.7137928 0.4146795 0.6015132 0.7112535
-#> site_890 0.6150032 0.2673579 0.4832610 0.6116381
-#> site_891 0.6658537 0.3393292 0.5487944 0.6631441
-#> site_892 0.6530012 0.3153120 0.5296535 0.6501308
-#> site_893 0.6841620 0.3456436 0.5645264 0.6814260
-#> site_894 0.6305940 0.2802819 0.4977169 0.6274510
-#> site_895 0.5963458 0.2489455 0.4572490 0.5927308
-#> site_896 0.6794087 0.3579212 0.5658246 0.6767957
-#> site_897 0.7636265 0.4167604 0.6521463 0.7612142
-#> site_898 0.7521189 0.4126226 0.6417375 0.7497060
-#> site_899 0.6578301 0.3113439 0.5289458 0.6548501
-#> site_900 0.6409140 0.2753906 0.4958105 0.6374827
-#>
-#>
-
-
Fit an occupancy model
-flock(
- f_occ = NULL,
- f_det,
- flocker_data,
- data2 = NULL,
- multiseason = NULL,
- f_col = NULL,
- f_ex = NULL,
- multi_init = NULL,
- f_auto = NULL,
- augmented = FALSE,
- threads = NULL,
- ...
-)
A brms-type model formula for occupancy. If provided, must begin -with "~".
A brms-type model formula for detection. Must begin with "~".
-OR, a brmsformula
object including formulas for all of the relevant
-distributional parameters in the desired model (det and at least one of occ,
-colo, ex, autologistic, and Omega). The $formula
element of the
-brmsformula
must be the detection formula, beginning with det ~
.
-This latter option unadvisable except when necessary (e.g. when a nonlinear
-formula is desired), as input checking is less thorough.
data, generally the output of make_flocker_data()
.
additional data (e.g. a covariance matrix for a phylogenetic -effect)
Must be NULL (the default) or one of "colex" or -"autologistic". If NULL, data must be formatted for a single-season model. -Otherwise, the data must be formatted for a multiseason model. If "colex", a -colonization-extinction model will be fit, and `f_col` and `f_ex` must be -specified. If "autologistic", an autologistic model will be fit, and `f_col` -and `f_ex` must both be NULL.
A brms-type model formula for colonization in -colonization-extinction dynamic models. If provided, must begin with "~".
A brms-type model formula for extinction probabilities in -colonization-extinction dynamic models. If provided, must begin with "~".
Must be NULL unless the model is a dynamic (multiseason) -model, in which case must be either "explicit" or "equilibrium". -If "explicit", then `f_occ` must be provided to model occupancy -probabilities in the first timestep. If "equilibrium", then `f_occ` must be -`NULL` and the initial occupancy probabilities are assumed to be the -(possibly site-specific) equilibrium probabilities from the colonization- -extinction dynamics.
Relevant only for autologistic models. A brms-type model -formula for the autologistic offset parameter (theta). If provided, must -begin with "~".
Logical. Must be TRUE if data are formatted for a -data-augmented multi-species model, and FALSE otherwise.
NULL or positive integer. If integer, the number of threads -to use per chain in within chain parallelization. Currently available only -with single-season rep-constant models, and must be set to NULL otherwise.
additional arguments passed to brms::brm()
a brmsfit
containing the fitted occupancy model.
if (FALSE) {
-fd <- make_flocker_data(
- example_flocker_data$obs,
- example_flocker_data$unit_covs,
- example_flocker_data$event_covs
-)
-flock(f_occ = ~ uc1 + s(uc2) + (1|grp),
- f_det = ~ uc1 + ec1 + s(ec2) + (1|grp),
- flocker_data = fd,
- refresh = 50, chains = 1, warmup = 5, iter = 200,
- adapt_engaged = F, step_size = .05, max_treedepth = 5, seed = 123,
- backend = "cmdstanr")
-}
-
R/flock.R
- flock_.Rd
Fit an occupancy model, or generate Stan code/data for a model, or get the prior -for a model
-flock_(
- output,
- f_occ,
- f_det,
- flocker_data,
- data2 = NULL,
- multiseason = NULL,
- f_col = NULL,
- f_ex = NULL,
- multi_init = NULL,
- f_auto = NULL,
- augmented = FALSE,
- threads = NULL,
- ...
-)
"model" for model fitting, "code" for stancode, "data" for standata, -"prior" for get_prior output
A brms-type model formula for occupancy. If provided, must begin -with "~".
A brms-type model formula for detection. Must begin with "~".
data, generally the output of make_flocker_data()
.
additional data (e.g. a covariance matrix for a phylogenetic -effect)
Must be NULL (the default) or one of "colex" or -"autologistic". If NULL, data must be formatted for a single-season model. -Otherwise, the data must be formatted for a multiseason model. If "colex", a -colonization-extinction model will be fit, and `f_col` and `f_ex` must be -specified. If "autologistic", an autologistic model will be fit, and `f_col` -and `f_ex` must both be NULL.
A brms-type model formula for colonization in -colonization-extinction dynamic models. If provided, must begin with "~".
A brms-type model formula for extinction probabilities in -colonization-extinction dynamic models. If provided, must begin with "~".
Must be NULL unless the model is a dynamic (multiseason) -model, in which case must be either "explicit" or "equilibrium". -If "explicit", then `f_occ` must be provided to model occupancy -probabilities in the first timestep. If "equilibrium", then `f_occ` must be -`NULL` and the initial occupancy probabilities are assumed to be the -(possibly site-specific) equilibrium probabilities from the colonization- -extinction dynamics.
A brms-type model formula for the autologistic offset -parameter (theta). If provided, must begin with "~".
Logical. Must be TRUE if data are formatted for a -data-augmented multi-species model, and FALSE otherwise.
NULL or positive integer. If integer, the number of threads -to use per chain in within chain parallelization.
additional arguments passed to brms::brm()
stan code for brms model or a brmsfit
containing the fitted occupancy model.
column names created in flocker
-flocker_col_names(n_rep = NULL, n_year = NULL)
max number of repeat visits
max length of hmm series in dynamic models
character vector of column names created internally by - make_flocker_data
-type
argument to make_flocker_data
.R/utils.R
- flocker_data_input_types.Rd
Options for the type
argument to make_flocker_data
.
flocker_data_input_types()
character vector of possible inputs
-make_flocker_data
.R/utils.R
- flocker_data_output_types.Rd
Data types that can be returned by make_flocker_data
.
flocker_data_output_types()
character vector of data output types
-R/flock.R
- flocker_fit_code_util.Rd
Either fit a flocker model or output stancode or output standata
-flocker_fit_code_util(
- output,
- f_use,
- data,
- data2,
- family,
- stanvars,
- threads = NULL,
- ...
-)
one of "model", "code", "data", or "prior"
brms formula
brms data
brms data2
brms family
brms stanvars
brms threads
brms ...
output of brms::brm or brms::make_stancode or brms::make_standata
-Model types in flocker as outputted by `flock`
-flocker_model_types()
character vector of types
-Reserved names in flocker
-flocker_reserved()
character vector of regexes matching reserved variable names
-Generate stan code for an occupancy model
-flocker_stancode(
- f_occ = NULL,
- f_det,
- flocker_data,
- data2 = NULL,
- multiseason = NULL,
- f_col = NULL,
- f_ex = NULL,
- multi_init = NULL,
- f_auto = NULL,
- augmented = FALSE,
- threads = NULL,
- ...
-)
A brms-type model formula for occupancy. If provided, must begin -with "~".
A brms-type model formula for detection. Must begin with "~".
-OR, a brmsformula
object including formulas for all of the relevant
-distributional parameters in the desired model (det and at least one of occ,
-colo, ex, autologistic, and Omega). The $formula
element of the
-brmsformula
must be the detection formula, beginning with det ~
.
-This latter option unadvisable except when necessary (e.g. when a nonlinear
-formula is desired), as input checking is less thorough.
data, generally the output of make_flocker_data()
.
additional data (e.g. a covariance matrix for a phylogenetic -effect)
Must be NULL (the default) or one of "colex" or -"autologistic". If NULL, data must be formatted for a single-season model. -Otherwise, the data must be formatted for a multiseason model. If "colex", a -colonization-extinction model will be fit, and `f_col` and `f_ex` must be -specified. If "autologistic", an autologistic model will be fit, and `f_col` -and `f_ex` must both be NULL.
A brms-type model formula for colonization in -colonization-extinction dynamic models. If provided, must begin with "~".
A brms-type model formula for extinction probabilities in -colonization-extinction dynamic models. If provided, must begin with "~".
Must be NULL unless the model is a dynamic (multiseason) -model, in which case must be either "explicit" or "equilibrium". -If "explicit", then `f_occ` must be provided to model occupancy -probabilities in the first timestep. If "equilibrium", then `f_occ` must be -`NULL` and the initial occupancy probabilities are assumed to be the -(possibly site-specific) equilibrium probabilities from the colonization- -extinction dynamics.
Relevant only for autologistic models. A brms-type model -formula for the autologistic offset parameter (theta). If provided, must -begin with "~".
Logical. Must be TRUE if data are formatted for a -data-augmented multi-species model, and FALSE otherwise.
NULL or positive integer. If integer, the number of threads -to use per chain in within chain parallelization. Currently available only -with single-season rep-constant models, and must be set to NULL otherwise.
additional arguments passed to brms::brm()
if (FALSE) {
-fd <- make_flocker_data(
- example_flocker_data$obs,
- example_flocker_data$unit_covs,
- example_flocker_data$event_covs
-)
-flocker_stancode(f_occ = ~ uc1 + s(uc2) + (1|grp),
- f_det = ~ uc1 + ec1 + s(ec2) + (1|grp),
- flocker_data = fd,
- refresh = 50, chains = 1, warmup = 5, iter = 200,
- adapt_engaged = F, step_size = .05, max_treedepth = 5, seed = 123,
- backend = "cmdstanr")
-}
-
Generate stan data for an occupancy model
-flocker_standata(
- f_occ = NULL,
- f_det,
- flocker_data,
- data2 = NULL,
- multiseason = NULL,
- f_col = NULL,
- f_ex = NULL,
- multi_init = NULL,
- f_auto = NULL,
- augmented = FALSE,
- threads = NULL,
- ...
-)
A brms-type model formula for occupancy. If provided, must begin -with "~".
A brms-type model formula for detection. Must begin with "~".
-OR, a brmsformula
object including formulas for all of the relevant
-distributional parameters in the desired model (det and at least one of occ,
-colo, ex, autologistic, and Omega). The $formula
element of the
-brmsformula
must be the detection formula, beginning with det ~
.
-This latter option unadvisable except when necessary (e.g. when a nonlinear
-formula is desired), as input checking is less thorough.
data, generally the output of make_flocker_data()
.
additional data (e.g. a covariance matrix for a phylogenetic -effect)
Must be NULL (the default) or one of "colex" or -"autologistic". If NULL, data must be formatted for a single-season model. -Otherwise, the data must be formatted for a multiseason model. If "colex", a -colonization-extinction model will be fit, and `f_col` and `f_ex` must be -specified. If "autologistic", an autologistic model will be fit, and `f_col` -and `f_ex` must both be NULL.
A brms-type model formula for colonization in -colonization-extinction dynamic models. If provided, must begin with "~".
A brms-type model formula for extinction probabilities in -colonization-extinction dynamic models. If provided, must begin with "~".
Must be NULL unless the model is a dynamic (multiseason) -model, in which case must be either "explicit" or "equilibrium". -If "explicit", then `f_occ` must be provided to model occupancy -probabilities in the first timestep. If "equilibrium", then `f_occ` must be -`NULL` and the initial occupancy probabilities are assumed to be the -(possibly site-specific) equilibrium probabilities from the colonization- -extinction dynamics.
Relevant only for autologistic models. A brms-type model -formula for the autologistic offset parameter (theta). If provided, must -begin with "~".
Logical. Must be TRUE if data are formatted for a -data-augmented multi-species model, and FALSE otherwise.
NULL or positive integer. If integer, the number of threads -to use per chain in within chain parallelization. Currently available only -with single-season rep-constant models, and must be set to NULL otherwise.
additional arguments passed to brms::brm()
if (FALSE) {
-fd <- make_flocker_data(
- example_flocker_data$obs,
- example_flocker_data$unit_covs,
- example_flocker_data$event_covs
-)
-flocker_standata(f_occ = ~ uc1 + s(uc2) + (1|grp),
- f_det = ~ uc1 + ec1 + s(ec2) + (1|grp),
- flocker_data = fd,
- refresh = 50, chains = 1, warmup = 5, iter = 200,
- adapt_engaged = F, step_size = .05, max_treedepth = 5, seed = 123,
- backend = "cmdstanr")
-}
-
Create error message for formula with incorrect syntax
-formula_error(form)
string giving name of formula
string giving text of error
-Forward algorithm
-forward_algorithm(el0, el1, init, colo, ex)
the emission probabilities given non-occupancy
the emission probabilities given occupancy
the initial occupancy probability
a vector giving the colonization probs
a vector giving the extinction probs
an n x 2 matrix giving the forward probabilities associated with - non-occupancy (first column) and occupancy (second column)
-forward backward algorithm
-forward_backward_algorithm(el0, el1, init, colo, ex)
the emission probabilities given non-occupancy
the emission probabilities given occupancy
the initial occupancy probability
a vector giving the colonization probs
a vector giving the extinction probs
a vector of posterior Z probabilities
-R/get_Z.R
- forward_backward_sampling.Rd
Forward filtering backward sampling algorithm
-forward_backward_sampling(el0, el1, init, colo, ex)
the emission probabilities given non-occupancy
the emission probabilities given occupancy
the initial occupancy probability
a vector giving the colonization probs
a vector giving the extinction probs
Forward simulation for a dynamic model
-forward_sim(init, colo, ex, sample = FALSE)
initial occupancy probability
vector of colonization probabilities
vector of extinction probabilities
Should the return be posterior probabilities of occupancy (FALSE), -valid posterior predictive samples (TRUE)
vector of occupancy probabilities or posterior predictive samples
-Get posterior distribution of the Z matrix
-get_Z(
- flocker_fit,
- draw_ids = NULL,
- history_condition = TRUE,
- sample = FALSE,
- new_data = NULL,
- allow_new_levels = FALSE,
- sample_new_levels = "uncertainty"
-)
A flocker_fit object
Vector of indices of the posterior draws to be -used. If `NULL` (the default) all draws are used in their native order.
Should the posterior distribution for Z directly -condition on the observed detection history (`TRUE`) or not (`FALSE`)? -For example, at sites with at least one detection, the true occupancy -state conditioned on the history is one with absolute certainty. Without -directly conditioning on the history, the occupancy state is controlled -by the posterior distribution for the occupancy probability psi.
Should the return be posterior probabilities of occupancy (FALSE), -or bernoulli samples from those probabilities (TRUE)
Optional new data at which to predict the Z matrix. Can be -the output of `make_flocker_data` or the `unit_covs` input to -`make_flocker_data` provided that `history_condition` is `FALSE` and the -occupancy model is for a single season.
allow new levels for random effect terms in `new_data`? -Will error if set to `FALSE` and new levels are provided in `new_data`.
If `new_data` is provided and contains random effect -levels not present in the original data, how should predictions be -handled? Passed directly to `brms::prepare_predictions`, which see.
The posterior Z matrix in the shape of the first visit in `obs` as - passed to make_flocker_data, with posterior iterations stacked along the - final dimension
-if (FALSE) {
-get_Z(example_flocker_model_single)
-}
-
get Z matrix for data-augmented model
-get_Z_augmented(lps, sample, history_condition, obs = NULL)
the linear predictors from the model
logical: return fitted probabilities or bernoulli samples
logical: condition on the observed history?
if history_condition is true, the observed histories
an array of fitted Z probabilities or sampled Z values. Rows are - units and columns are posterior iterations.
-get Z matrix for dynamic model
-get_Z_dynamic(
- init,
- colo,
- ex,
- history_condition,
- sample,
- obs = NULL,
- det = NULL
-)
matrix of initial occupancy probabilities (rows are sites and -columns are draws)
array of colonization probabilities (rows are sites, columns are -timesteps, slices are draws)
array of extinction probabilities (rows are sites, columns are -timesteps, slices are draws)
should we condition on the observed history
Should the return be posterior probabilities of occupancy (FALSE), -valid posterior predictive samples (TRUE).
Array of observations. Must be NULL if history_condition -is FALSE. Rows are sites, columns are visits, and slices are timesteps.
Array of detection probabilities. Ignored (and defaults to NULL) if -history_condition is FALSE. Rows are sites, columns are visits, slices -are timesteps, and slice_2s are draws.
an array of occupancy probabilities or Z samples. Rows are sites, - columns are timesteps, and slices are draws.
-History-conditioning is via the forward-backward algorithm (forward- - filtering-backward-sampling when sample is TRUE)
-get Z matrix for single-season model
-get_Z_single(lps, sample, history_condition, obs = NULL)
the linear predictors from the model
logical: return fitted probabilities or bernoulli samples
logical: condition on the observed history?
if history_condition is true, the observed histories
a matrix of fitted Z probabilities or sampled Z values. Rows are - units and columns are posterior iterations.
-get Z matrix for single-season rep-constant model
-get_Z_single_C(lps, sample, history_condition, obs = NULL)
the linear predictors from the model
logical: return fitted probabilities or bernoulli samples
logical: condition on the observed history?
if history_condition is true, the observed histories
a matrix of fitted Z probabilities or sampled Z values. Rows are - units and columns are posterior iterations.
-Get prior for occupancy model
-get_flocker_prior(
- f_occ = NULL,
- f_det,
- flocker_data,
- data2 = NULL,
- multiseason = NULL,
- f_col = NULL,
- f_ex = NULL,
- multi_init = NULL,
- f_auto = NULL,
- augmented = FALSE,
- threads = NULL,
- ...
-)
A brms-type model formula for occupancy. If provided, must begin -with "~".
A brms-type model formula for detection. Must begin with "~".
-OR, a brmsformula
object including formulas for all of the relevant
-distributional parameters in the desired model (det and at least one of occ,
-colo, ex, autologistic, and Omega). The $formula
element of the
-brmsformula
must be the detection formula, beginning with det ~
.
-This latter option unadvisable except when necessary (e.g. when a nonlinear
-formula is desired), as input checking is less thorough.
data, generally the output of make_flocker_data()
.
additional data (e.g. a covariance matrix for a phylogenetic -effect)
Must be NULL (the default) or one of "colex" or -"autologistic". If NULL, data must be formatted for a single-season model. -Otherwise, the data must be formatted for a multiseason model. If "colex", a -colonization-extinction model will be fit, and `f_col` and `f_ex` must be -specified. If "autologistic", an autologistic model will be fit, and `f_col` -and `f_ex` must both be NULL.
A brms-type model formula for colonization in -colonization-extinction dynamic models. If provided, must begin with "~".
A brms-type model formula for extinction probabilities in -colonization-extinction dynamic models. If provided, must begin with "~".
Must be NULL unless the model is a dynamic (multiseason) -model, in which case must be either "explicit" or "equilibrium". -If "explicit", then `f_occ` must be provided to model occupancy -probabilities in the first timestep. If "equilibrium", then `f_occ` must be -`NULL` and the initial occupancy probabilities are assumed to be the -(possibly site-specific) equilibrium probabilities from the colonization- -extinction dynamics.
Relevant only for autologistic models. A brms-type model -formula for the autologistic offset parameter (theta). If provided, must -begin with "~".
Logical. Must be TRUE if data are formatted for a -data-augmented multi-species model, and FALSE otherwise.
NULL or positive integer. If integer, the number of threads -to use per chain in within chain parallelization. Currently available only -with single-season rep-constant models, and must be set to NULL otherwise.
additional arguments passed to brms::brm()
A dataframe summarizing the parameters on which priors can
- be specified and giving the default priors for those parameters.
- See ?brms::get_prior
for further details.
if (FALSE) {
-fd <- make_flocker_data(
- example_flocker_data$obs,
- example_flocker_data$unit_covs,
- example_flocker_data$event_covs
-)
-get_flocker_prior(
- f_occ = ~ uc1 + + (1|grp),
- f_det = ~ uc1 + ec1 + (1|grp),
- flocker_data = fd
-)
-}
-
R/utils.R
- get_positions.Rd
Get a matrix/array of row numbers from flocker_data$data in the shape of obs
-get_positions(data_object, unit_level = FALSE)
a flocker_fit object or a flocker_data object
logical. If `FALSE`, returns values associated with each visit -in the shape of obs, with NAs for visits that did not occur. -If `TRUE`, returns values associated with each unit in the shape of -the slice of obs corresponding to the first visit. This is relevant in -multiseason models, where it is possible to have units (i.e. timesteps) -that are part of the timeseries and have linear predictors for colonization -etc, but that received no visits. These units are dropped from the -formatted data if they are trailing (at the end of the series) but must be -included otherwise. If `TRUE`, the return will have NAs for the trailing -units that are dropped, but will have row-numbers representing the rows -giving the unit covariates for the never-visited units if the timesteps are -not trailing.
a matrix/array of the same shape as the observations passed to - `make_flocker_data` (for an augmented model, in the shape of the augmented - data created after augmentation) where each element gives the row number in - flocker_data$data where the corresponding element resides. If the data - were formatted for a data-augmented model, the returned array will have - extra slices for all of the augmented species.
-
- All functions- - |
- |
---|---|
- - | -get Z given emission likelihoods and state probability |
-
- - | -Backward algorithm |
-
- - | -Get emission likelihoods given observations and detection probabilities |
-
- - | -Example flocker data |
-
- - | -Example data-augmented flocker model |
-
- - | -Example multi-season flocker model (autologistic equilibrium) |
-
- - | -Example multi-season flocker model (autologistic explicit) |
-
- - | -Example multi-season flocker model (colex equilibirum) |
-
- - | -Example multi-season flocker model (colex explicit) |
-
- - | -Example single-season flocker model |
-
- - | -Example single-season rep-constant flocker model |
-
- - | -convert array to long matrix format |
-
- - | -convert matrix-like object to long vector format |
-
- - | -extended binomial RNG |
-
- - | -flocker data type lookup |
-
- - | -Posterior predictive distributions for modeled probabilities |
-
- - | -Fit an occupancy model |
-
- - | -Fit an occupancy model, or generate Stan code/data for a model, or get the prior -for a model |
-
- - | -column names created in flocker |
-
- - | -Options for the |
-
- - | -Data types that can be returned by |
-
- - | -Either fit a flocker model or output stancode or output standata |
-
- - | -Model types in flocker as outputted by `flock` |
-
- - | -Reserved names in flocker |
-
- - | -Generate stan code for an occupancy model |
-
- - | -Generate stan data for an occupancy model |
-
- - | -Create error message for formula with incorrect syntax |
-
- - | -Forward algorithm |
-
- - | -forward backward algorithm |
-
- - | -Forward filtering backward sampling algorithm |
-
- - | -Forward simulation for a dynamic model |
-
- - | -Get posterior distribution of the Z matrix |
-
- - | -get Z matrix for data-augmented model |
-
- - | -get Z matrix for dynamic model |
-
- - | -get Z matrix for single-season model |
-
- - | -get Z matrix for single-season rep-constant model |
-
- - | -Get prior for occupancy model |
-
- - | -Get a matrix/array of row numbers from flocker_data$data in the shape of obs |
-
- - | -check that object is a flocker data object |
-
- - | -Test whether an object is of class flocker_fit |
-
- - | -check that object is a valid flocker formula |
-
- - | -check that object is a formula |
-
- - | -check that object is a named list with no duplicate names |
-
- - | -check if an object is a single logical value |
-
- - | -check if an object is a single integer (or integerish) > m |
-
- - | -Numerically stable log one-minus inverse logit |
-
- - | -Numerically stable log inverse logit |
-
- - | -log_lik_dynamic |
-
- - | -Compute unit-wise or series-wise log-likelihood matrix for a flocker_fit object |
-
- - | -A log-likelihood function for the rep-constant occupancy model, sufficient for
- |
-
- - | -LOO comparisons for flocker models. |
-
- - | -Compute loo for flocker_fit objects |
-
- - | -Compute loo for a single flocker_fit object |
-
- - | -Create Stan code for transition log-likelihoods in colex model. -These likelihoods ignore disallowed possibilities (detections on unoccupied -units); such possibilities are excluded via the control flow in the -implementation of the forward algorithm. |
-
- - | -Create Stan code for the emission log-likelihood given that the true state - equals one in a rep-varying model. |
-
- - | -Create Stan code for the emission log-likelihood given that the true state - equals one in a rep-constant model. |
-
- - | -Format data for occupancy model with |
-
- - | -#' Format data for data-augmented occupancy model, to be passed to
- |
-
- - | -Format data for dynamic (multi-season) occupancy model, to be passed to
- |
-
- - | -Format data for single-season occupancy model, to be passed to
- |
-
- - | -Create Stan code for forward_colex function, an implementation of the - forward algorithm for use in colex models. |
-
- - | -Create Stan code for likelihood function occupancy_augmented_lpmf for -rep-varying model. |
-
- - | -Create Stan code for likelihood function occupancy_multi_autologistic_eq_lpmf. |
-
- - | -Create Stan code for likelihood function occupancy_multi_autologistic_lpmf. |
-
- - | -Create Stan code for likelihood function occupancy_multi_colex_eq_lpmf. |
-
- - | -Create Stan code for likelihood function occupancy_multi_colex_lpmf. |
-
- - | -Create Stan code for likelihood function occupancy_single_C_lpmf. -The purpose of defining this custom family, rather than using brms's zero-inflated -binomial, is to ensure that the occupancy parameters are interpretable with -values of 1 in the marginalized state reflecting occupancy rather than non- -occupancy. |
-
- - | -Create Stan code for likelihood function occupancy_single_lpmf. |
-
- - | -Create Stan code for likelihood function occupancy_single_lpmf. |
-
- - | -get largest index in a vector that is not NA |
-
- - | -possible values for the `multi_init` parameter if not NULL |
-
- - | -flocker_data_output_types valid for use with colex models |
-
- - | -create a new array with the dimensions of an old array |
-
- - | -create a new matrix with the dimensions of an old matrix |
-
- - | -Get third dimension of a 3D array |
-
- - | -Define the rep-varying augmented occupancy family |
-
- - | -Define the autologistic family |
-
- - | -Define the autologistic_eq family |
-
- - | -Define the colonization-extinction family |
-
- - | -Define the colonization-extinction equilibrium family |
-
- - | -Define the rep-varying occupancy family |
-
- - | -Define the rep-constant occupancy family |
-
- - | -An R implementation of the rep constant lpmf without the binomial coefficient. |
-
- - | -An R implementation of occupancy_C_lpmf including the binomial coefficient. -Not currently in use. |
-
- - | -Define the rep-varying occupancy family with threading |
-
- - | -A list of distributional parameters by model type |
-
- - | -Get posterior predictions from a flocker model |
-
- - | -remove rownames |
-
- - | -flocker_data_output_types that yield rep-constant models |
-
- - | -reshape a matrix of values into a stack of arrays via get_positions |
-
- - | -util for creating example data |
-
- - | -get shared elements between two vectors |
-
- - | -Simulate data for use with |
-
- - | -rbind a matrix or dataframe to itself n times |
-
- - | -summarize matrix of linear predictors to its mean and CI |
-
- - | -flocker_data_output_types valid for use with threading |
-
- - | -Extract lik_type from object of class flocker_fit |
-
- - | -Check validity of params passed to `flock` |
-
- - | -Check validity of params passed to `flock` if `type` is `augmented` |
-
- - | -Check validity of params passed to `flock` if `type` is `multi` |
-
- - | -Check validity of params passed to `flock` if `type` is `single` |
-
- - | -Check validity of params passed to `flock` if `type` is `single_C` |
-
- - | -Check validity of some params passed to flock if `type` is `single` or `single_C` |
-
- - | -Check individual validity of params passed to `flock` |
-
- - | -Check that no event covariates are used in unit formulas |
-
check that object is a flocker data object
-is_flocker_data(x)
object to test
logical; TRUE if x is a flocker data object
-Test whether an object is of class flocker_fit
-is_flocker_fit(x)
object to be tested
logical
-check that object is a valid flocker formula
-is_flocker_formula(x)
object to test
logical; TRUE if x is a valid flocker formula
-check that object is a formula
-is_formula(x)
object to test
logical; TRUE if x is a formula
-R/utils.R
- is_named_list.Rd
check that object is a named list with no duplicate names
-is_named_list(x)
object to test
logical; TRUE if x is a named list with no duplicate names
-check if an object is a single logical value
-is_one_logical(x)
object to test
logical; TRUE if x is a single logical value
-R/utils.R
- is_one_pos_int.Rd
check if an object is a single integer (or integerish) > m
-is_one_pos_int(x, m = 0)
object to test
minimum value for x
logical; TRUE if x is a single positive integer
-Numerically stable log one-minus inverse logit
-log1m_inv_logit(x)
real number or vector of reals
the logarithm of one minus the inverse logit of x
-log1m_inv_logit(0)
-#> [1] -0.6931472
-
Numerically stable log inverse logit
-log_inv_logit(x)
real number or vector of reals
the logarithm of the inverse logit of x
-log_inv_logit(0)
-#> [1] -0.6931472
-
log_lik_dynamic
-log_lik_dynamic(init, colo, ex, obs, det)
matrix of initial occupancy probabilities (rows are series and -columns are draws)
array of colonization probabilities (rows are series, columns are -timesteps, slices are draws)
array of extinction probabilities (rows are series, columns are -timesteps, slices are draws)
Array of observations. Rows are series, columns are visits, and -slices are timesteps.
Array of detection probabilities. Rows are series, columns are -visits, slices are timesteps, and slice_2s are draws.
A log-likelihood matrix. Rows are sites, - columns are draws.
-R/log_lik_occupancy.R
- log_lik_flocker.Rd
Compute unit-wise or series-wise log-likelihood matrix for a flocker_fit object
-log_lik_flocker(flocker_fit, draw_ids = NULL)
A flocker_fit object
the draw ids to compute log-likelihoods for. Defaults to using the full posterior.
A posterior log-likelihood matrix, where iterations are rows and - units, series, or species are columns.
-In single-season models, rows are units (e.g. points or - species-points; suitable for leave-one-unit-out CV). In multiseason models, - rows are series (i.e. points or species-points, suitable for - leave-one-series-out CV). In augmented models, rows are species (suitable - for leave-one-species-out CV).
-if (FALSE) {
-log_lik_flocker(example_flocker_model_single)
-}
-
brms::loo(vc_fit)
to work.R/log_lik_occupancy.R
- log_lik_occupancy_single_C.Rd
A log-likelihood function for the rep-constant occupancy model, sufficient for
-brms::loo(vc_fit)
to work.
log_lik_occupancy_single_C(i, prep)
Posterior iteration
Output of brms::prepare_predictions
. See brms custom families
-vignette at
-https://cran.r-project.org/web/packages/brms/vignettes/brms_customfamilies.html
The log-likelihood for observation i
-LOO comparisons for flocker models.
-loo_compare_flocker(model_list, model_names = NULL, thin = NULL)
a list of flocker_fit objects.
An optional vector of names for the models.
specify the amount of thinning required. 1 or NULL results in no -thinning, 2 retains every other value, 3 every third, etc.
Compute loo for flocker_fit objects
-loo_flocker(x, thin = NULL)
a flocker_fit object or a list of flocker_fit objects
specify the amount of thinning required. 1 or NULL implies no thinning, 2 implies every other value, 3 every third, etc.
a loo object or a list of loo objects
-if (FALSE) {
-loo_flocker(example_flocker_model_single)
-}
-
Compute loo for a single flocker_fit object
-loo_flocker_onefit(x, thin = NULL)
a flocker_fit object
specify the amount of thinning required. 1 or NULL implies no thinning, 2 implies every other value, 3 every third, etc.
a loo object
-R/make_occupancy_lpmf.R
- make_colex_likelihoods.Rd
Create Stan code for transition log-likelihoods in colex model. -These likelihoods ignore disallowed possibilities (detections on unoccupied -units); such possibilities are excluded via the control flow in the -implementation of the forward algorithm.
-make_colex_likelihoods()
Character string of Stan code corresponding to likelihoods for the - possible transitions in a colex model
-R/make_occupancy_lpmf.R
- make_emission_1.Rd
Create Stan code for the emission log-likelihood given that the true state - equals one in a rep-varying model.
-make_emission_1()
Character string of Stan code corresponding to emission_1
-R/make_occupancy_lpmf.R
- make_emission_1_C.Rd
Create Stan code for the emission log-likelihood given that the true state - equals one in a rep-constant model.
-make_emission_1_C()
Character string of Stan code corresponding to emission_1
-flock()
.R/make_flocker_data.R
- make_flocker_data.Rd
Format data for occupancy model with flock()
.
make_flocker_data(
- obs,
- unit_covs = NULL,
- event_covs = NULL,
- type = "single",
- n_aug = NULL,
- quiet = FALSE
-)
If type = "single"
, an I x J matrix-like object where
-closure is assumed across rows and columns are repeated sampling events.
- If type = "multi"
, an I x J x K array where rows are sites or
-species-sites, columns are repeated sampling events, and slices along the
-third dimension are seasons. Allowable values are 1 (detection), 0 (no
-detection), and NA (no sampling event).
- If type = "augmented"
, an L x J x K array where rows L are sites,
-columns J are repeat sampling events, and slices K are species.
- The data must be packed so that, for a given unit (site, site-species,
-site-timestep, site-species-timestep) all realized visits come before any
-missing visits (NAs are trailing within their rows).
If type = "single"
a dataframe of covariates for each
-closure-unit that are constant across repeated sampling events within units.
- If type = "multi"
, a list of such dataframes, one per timestep. All
-dataframes must have identical column names and types, and all
-dataframes must have I rows.
- If type = "augmented"
, a dataframe of covariates for each site that
-are constant across repeated sampling events within sites (no dependence on
-species is allowed).
If type = "single"
, a named list of I x J matrices,
-each one corresponding to a covariate that varies across repeated sampling
-events within closure-units.
- If type = "multi"
, a named list of I x J x K arrays, each one
-corresponding to a covariate that varies across repeated sampling events
-within closure-units.
- If type = "augmented"
, a named list of L x J matrices, each one
-corresponding to a covariate that varies across repeated sampling events
-within sites (no dependence on species is allowed).
The type of occupancy model desired. Options are:
-"single"
for a single_season model,
-"multi"
for a multi-season (dynamic) model, or
-"augmented"
for a single-season multi-species model with
-data-augmentation for never-observed pseudospecies.
Number of pseudo-species to augment. Only applicable if
-type = "augmented"
.
Hide progress bars and informational messages?
A flocker_data list that can be passed as data to flock()
.
make_flocker_data(
- example_flocker_data$obs,
- example_flocker_data$unit_covs,
- example_flocker_data$event_covs
-)
-#> Formatting data for a single-season occupancy model. For details, see make_flocker_data_static. All warnings and error messages should be interpreted in the context of make_flocker_data_static
-#> $data
-#> ff_y uc1 uc2 grp species ec1 ec2
-#> 1 0 -0.56047565 0.42646422 7 sp_1 0.321519971 -0.96540472
-#> 2 0 -0.56047565 0.42646422 3 sp_2 0.321519971 -0.96540472
-#> 3 0 -0.56047565 0.42646422 15 sp_3 0.321519971 -0.96540472
-#> 4 0 -0.56047565 0.42646422 5 sp_4 0.321519971 -0.96540472
-#> 5 1 -0.56047565 0.42646422 8 sp_5 0.321519971 -0.96540472
-#> 6 0 -0.56047565 0.42646422 19 sp_6 0.321519971 -0.96540472
-#> 7 0 -0.56047565 0.42646422 10 sp_7 0.321519971 -0.96540472
-#> 8 0 -0.56047565 0.42646422 18 sp_8 0.321519971 -0.96540472
-#> 9 0 -0.56047565 0.42646422 10 sp_9 0.321519971 -0.96540472
-#> 10 0 -0.56047565 0.42646422 12 sp_10 0.321519971 -0.96540472
-#> 11 1 -0.56047565 0.42646422 2 sp_11 0.321519971 -0.96540472
-#> 12 0 -0.56047565 0.42646422 10 sp_12 0.321519971 -0.96540472
-#> 13 0 -0.56047565 0.42646422 12 sp_13 0.321519971 -0.96540472
-#> 14 0 -0.56047565 0.42646422 20 sp_14 0.321519971 -0.96540472
-#> 15 0 -0.56047565 0.42646422 14 sp_15 0.321519971 -0.96540472
-#> 16 0 -0.56047565 0.42646422 17 sp_16 0.321519971 -0.96540472
-#> 17 1 -0.56047565 0.42646422 14 sp_17 0.321519971 -0.96540472
-#> 18 0 -0.56047565 0.42646422 3 sp_18 0.321519971 -0.96540472
-#> 19 0 -0.56047565 0.42646422 8 sp_19 0.321519971 -0.96540472
-#> 20 1 -0.56047565 0.42646422 14 sp_20 0.321519971 -0.96540472
-#> 21 0 -0.56047565 0.42646422 19 sp_21 0.321519971 -0.96540472
-#> 22 0 -0.56047565 0.42646422 15 sp_22 0.321519971 -0.96540472
-#> 23 0 -0.56047565 0.42646422 17 sp_23 0.321519971 -0.96540472
-#> 24 0 -0.56047565 0.42646422 11 sp_24 0.321519971 -0.96540472
-#> 25 0 -0.56047565 0.42646422 7 sp_25 0.321519971 -0.96540472
-#> 26 0 -0.56047565 0.42646422 15 sp_26 0.321519971 -0.96540472
-#> 27 1 -0.56047565 0.42646422 6 sp_27 0.321519971 -0.96540472
-#> 28 0 -0.56047565 0.42646422 14 sp_28 0.321519971 -0.96540472
-#> 29 0 -0.56047565 0.42646422 7 sp_29 0.321519971 -0.96540472
-#> 30 0 -0.56047565 0.42646422 10 sp_30 0.321519971 -0.96540472
-#> 121 0 -0.23017749 -0.29507148 5 sp_1 0.545146877 -1.18355753
-#> 122 0 -0.23017749 -0.29507148 6 sp_2 0.545146877 -1.18355753
-#> 123 0 -0.23017749 -0.29507148 16 sp_3 0.545146877 -1.18355753
-#> 124 0 -0.23017749 -0.29507148 11 sp_4 0.545146877 -1.18355753
-#> 125 0 -0.23017749 -0.29507148 4 sp_5 0.545146877 -1.18355753
-#> 126 1 -0.23017749 -0.29507148 12 sp_6 0.545146877 -1.18355753
-#> 127 0 -0.23017749 -0.29507148 14 sp_7 0.545146877 -1.18355753
-#> 128 0 -0.23017749 -0.29507148 19 sp_8 0.545146877 -1.18355753
-#> 129 0 -0.23017749 -0.29507148 7 sp_9 0.545146877 -1.18355753
-#> 130 0 -0.23017749 -0.29507148 9 sp_10 0.545146877 -1.18355753
-#> 131 1 -0.23017749 -0.29507148 7 sp_11 0.545146877 -1.18355753
-#> 132 0 -0.23017749 -0.29507148 2 sp_12 0.545146877 -1.18355753
-#> 133 0 -0.23017749 -0.29507148 16 sp_13 0.545146877 -1.18355753
-#> 134 0 -0.23017749 -0.29507148 13 sp_14 0.545146877 -1.18355753
-#> 135 0 -0.23017749 -0.29507148 19 sp_15 0.545146877 -1.18355753
-#> 136 1 -0.23017749 -0.29507148 20 sp_16 0.545146877 -1.18355753
-#> 137 0 -0.23017749 -0.29507148 15 sp_17 0.545146877 -1.18355753
-#> 138 0 -0.23017749 -0.29507148 7 sp_18 0.545146877 -1.18355753
-#> 139 1 -0.23017749 -0.29507148 4 sp_19 0.545146877 -1.18355753
-#> 140 0 -0.23017749 -0.29507148 1 sp_20 0.545146877 -1.18355753
-#> 141 0 -0.23017749 -0.29507148 8 sp_21 0.545146877 -1.18355753
-#> 142 1 -0.23017749 -0.29507148 20 sp_22 0.545146877 -1.18355753
-#> 143 1 -0.23017749 -0.29507148 16 sp_23 0.545146877 -1.18355753
-#> 144 0 -0.23017749 -0.29507148 11 sp_24 0.545146877 -1.18355753
-#> 145 0 -0.23017749 -0.29507148 16 sp_25 0.545146877 -1.18355753
-#> 146 0 -0.23017749 -0.29507148 20 sp_26 0.545146877 -1.18355753
-#> 147 0 -0.23017749 -0.29507148 8 sp_27 0.545146877 -1.18355753
-#> 148 0 -0.23017749 -0.29507148 3 sp_28 0.545146877 -1.18355753
-#> 149 1 -0.23017749 -0.29507148 4 sp_29 0.545146877 -1.18355753
-#> 150 0 -0.23017749 -0.29507148 20 sp_30 0.545146877 -1.18355753
-#> 241 0 1.55870831 0.89512566 12 sp_1 -0.636097623 0.76339802
-#> 242 1 1.55870831 0.89512566 17 sp_2 -0.636097623 0.76339802
-#> 243 0 1.55870831 0.89512566 10 sp_3 -0.636097623 0.76339802
-#> 244 0 1.55870831 0.89512566 20 sp_4 -0.636097623 0.76339802
-#> 245 1 1.55870831 0.89512566 11 sp_5 -0.636097623 0.76339802
-#> 246 0 1.55870831 0.89512566 8 sp_6 -0.636097623 0.76339802
-#> 247 0 1.55870831 0.89512566 14 sp_7 -0.636097623 0.76339802
-#> 248 0 1.55870831 0.89512566 13 sp_8 -0.636097623 0.76339802
-#> 249 0 1.55870831 0.89512566 2 sp_9 -0.636097623 0.76339802
-#> 250 1 1.55870831 0.89512566 11 sp_10 -0.636097623 0.76339802
-#> 251 0 1.55870831 0.89512566 13 sp_11 -0.636097623 0.76339802
-#> 252 0 1.55870831 0.89512566 14 sp_12 -0.636097623 0.76339802
-#> 253 0 1.55870831 0.89512566 6 sp_13 -0.636097623 0.76339802
-#> 254 0 1.55870831 0.89512566 8 sp_14 -0.636097623 0.76339802
-#> 255 1 1.55870831 0.89512566 12 sp_15 -0.636097623 0.76339802
-#> 256 0 1.55870831 0.89512566 4 sp_16 -0.636097623 0.76339802
-#> 257 0 1.55870831 0.89512566 13 sp_17 -0.636097623 0.76339802
-#> 258 0 1.55870831 0.89512566 14 sp_18 -0.636097623 0.76339802
-#> 259 0 1.55870831 0.89512566 16 sp_19 -0.636097623 0.76339802
-#> 260 0 1.55870831 0.89512566 1 sp_20 -0.636097623 0.76339802
-#> 261 0 1.55870831 0.89512566 8 sp_21 -0.636097623 0.76339802
-#> 262 0 1.55870831 0.89512566 8 sp_22 -0.636097623 0.76339802
-#> 263 0 1.55870831 0.89512566 10 sp_23 -0.636097623 0.76339802
-#> 264 0 1.55870831 0.89512566 8 sp_24 -0.636097623 0.76339802
-#> 265 0 1.55870831 0.89512566 18 sp_25 -0.636097623 0.76339802
-#> 266 0 1.55870831 0.89512566 9 sp_26 -0.636097623 0.76339802
-#> 267 0 1.55870831 0.89512566 7 sp_27 -0.636097623 0.76339802
-#> 268 0 1.55870831 0.89512566 7 sp_28 -0.636097623 0.76339802
-#> 269 0 1.55870831 0.89512566 10 sp_29 -0.636097623 0.76339802
-#> 270 1 1.55870831 0.89512566 11 sp_30 -0.636097623 0.76339802
-#> 361 0 0.07050839 0.87813349 1 sp_1 1.376384123 -0.18537799
-#> 362 0 0.07050839 0.87813349 19 sp_2 1.376384123 -0.18537799
-#> 363 0 0.07050839 0.87813349 10 sp_3 1.376384123 -0.18537799
-#> 364 0 0.07050839 0.87813349 13 sp_4 1.376384123 -0.18537799
-#> 365 1 0.07050839 0.87813349 11 sp_5 1.376384123 -0.18537799
-#> 366 0 0.07050839 0.87813349 11 sp_6 1.376384123 -0.18537799
-#> 367 0 0.07050839 0.87813349 20 sp_7 1.376384123 -0.18537799
-#> 368 0 0.07050839 0.87813349 7 sp_8 1.376384123 -0.18537799
-#> 369 0 0.07050839 0.87813349 20 sp_9 1.376384123 -0.18537799
-#> 370 0 0.07050839 0.87813349 9 sp_10 1.376384123 -0.18537799
-#> 371 0 0.07050839 0.87813349 9 sp_11 1.376384123 -0.18537799
-#> 372 0 0.07050839 0.87813349 5 sp_12 1.376384123 -0.18537799
-#> 373 0 0.07050839 0.87813349 14 sp_13 1.376384123 -0.18537799
-#> 374 0 0.07050839 0.87813349 14 sp_14 1.376384123 -0.18537799
-#> 375 0 0.07050839 0.87813349 6 sp_15 1.376384123 -0.18537799
-#> 376 0 0.07050839 0.87813349 1 sp_16 1.376384123 -0.18537799
-#> 377 1 0.07050839 0.87813349 10 sp_17 1.376384123 -0.18537799
-#> 378 1 0.07050839 0.87813349 17 sp_18 1.376384123 -0.18537799
-#> 379 1 0.07050839 0.87813349 17 sp_19 1.376384123 -0.18537799
-#> 380 0 0.07050839 0.87813349 7 sp_20 1.376384123 -0.18537799
-#> 381 0 0.07050839 0.87813349 9 sp_21 1.376384123 -0.18537799
-#> 382 0 0.07050839 0.87813349 20 sp_22 1.376384123 -0.18537799
-#> 383 0 0.07050839 0.87813349 6 sp_23 1.376384123 -0.18537799
-#> 384 0 0.07050839 0.87813349 18 sp_24 1.376384123 -0.18537799
-#> 385 0 0.07050839 0.87813349 17 sp_25 1.376384123 -0.18537799
-#> 386 0 0.07050839 0.87813349 5 sp_26 1.376384123 -0.18537799
-#> 387 1 0.07050839 0.87813349 20 sp_27 1.376384123 -0.18537799
-#> 388 0 0.07050839 0.87813349 3 sp_28 1.376384123 -0.18537799
-#> 389 0 0.07050839 0.87813349 14 sp_29 1.376384123 -0.18537799
-#> 390 0 0.07050839 0.87813349 1 sp_30 1.376384123 -0.18537799
-#> 481 0 0.12928774 0.82158108 2 sp_1 1.012519248 -0.07935506
-#> 482 0 0.12928774 0.82158108 4 sp_2 1.012519248 -0.07935506
-#> 483 0 0.12928774 0.82158108 10 sp_3 1.012519248 -0.07935506
-#> 484 0 0.12928774 0.82158108 1 sp_4 1.012519248 -0.07935506
-#> 485 0 0.12928774 0.82158108 5 sp_5 1.012519248 -0.07935506
-#> 486 0 0.12928774 0.82158108 8 sp_6 1.012519248 -0.07935506
-#> 487 0 0.12928774 0.82158108 13 sp_7 1.012519248 -0.07935506
-#> 488 0 0.12928774 0.82158108 18 sp_8 1.012519248 -0.07935506
-#> 489 1 0.12928774 0.82158108 10 sp_9 1.012519248 -0.07935506
-#> 490 0 0.12928774 0.82158108 6 sp_10 1.012519248 -0.07935506
-#> 491 0 0.12928774 0.82158108 7 sp_11 1.012519248 -0.07935506
-#> 492 0 0.12928774 0.82158108 9 sp_12 1.012519248 -0.07935506
-#> 493 0 0.12928774 0.82158108 16 sp_13 1.012519248 -0.07935506
-#> 494 1 0.12928774 0.82158108 17 sp_14 1.012519248 -0.07935506
-#> 495 0 0.12928774 0.82158108 13 sp_15 1.012519248 -0.07935506
-#> 496 0 0.12928774 0.82158108 8 sp_16 1.012519248 -0.07935506
-#> 497 0 0.12928774 0.82158108 7 sp_17 1.012519248 -0.07935506
-#> 498 0 0.12928774 0.82158108 20 sp_18 1.012519248 -0.07935506
-#> 499 0 0.12928774 0.82158108 18 sp_19 1.012519248 -0.07935506
-#> 500 0 0.12928774 0.82158108 17 sp_20 1.012519248 -0.07935506
-#> 501 0 0.12928774 0.82158108 1 sp_21 1.012519248 -0.07935506
-#> 502 0 0.12928774 0.82158108 2 sp_22 1.012519248 -0.07935506
-#> 503 0 0.12928774 0.82158108 17 sp_23 1.012519248 -0.07935506
-#> 504 0 0.12928774 0.82158108 2 sp_24 1.012519248 -0.07935506
-#> 505 0 0.12928774 0.82158108 13 sp_25 1.012519248 -0.07935506
-#> 506 0 0.12928774 0.82158108 17 sp_26 1.012519248 -0.07935506
-#> 507 0 0.12928774 0.82158108 3 sp_27 1.012519248 -0.07935506
-#> 508 0 0.12928774 0.82158108 18 sp_28 1.012519248 -0.07935506
-#> 509 0 0.12928774 0.82158108 2 sp_29 1.012519248 -0.07935506
-#> 510 0 0.12928774 0.82158108 5 sp_30 1.012519248 -0.07935506
-#> 601 1 1.71506499 0.68864025 12 sp_1 -0.539895140 0.70220997
-#> 602 0 1.71506499 0.68864025 13 sp_2 -0.539895140 0.70220997
-#> 603 0 1.71506499 0.68864025 10 sp_3 -0.539895140 0.70220997
-#> 604 1 1.71506499 0.68864025 6 sp_4 -0.539895140 0.70220997
-#> 605 0 1.71506499 0.68864025 10 sp_5 -0.539895140 0.70220997
-#> 606 0 1.71506499 0.68864025 10 sp_6 -0.539895140 0.70220997
-#> 607 1 1.71506499 0.68864025 6 sp_7 -0.539895140 0.70220997
-#> 608 0 1.71506499 0.68864025 16 sp_8 -0.539895140 0.70220997
-#> 609 0 1.71506499 0.68864025 16 sp_9 -0.539895140 0.70220997
-#> 610 0 1.71506499 0.68864025 3 sp_10 -0.539895140 0.70220997
-#> 611 0 1.71506499 0.68864025 4 sp_11 -0.539895140 0.70220997
-#> 612 0 1.71506499 0.68864025 3 sp_12 -0.539895140 0.70220997
-#> 613 0 1.71506499 0.68864025 3 sp_13 -0.539895140 0.70220997
-#> 614 0 1.71506499 0.68864025 16 sp_14 -0.539895140 0.70220997
-#> 615 0 1.71506499 0.68864025 2 sp_15 -0.539895140 0.70220997
-#> 616 1 1.71506499 0.68864025 15 sp_16 -0.539895140 0.70220997
-#> 617 0 1.71506499 0.68864025 3 sp_17 -0.539895140 0.70220997
-#> 618 0 1.71506499 0.68864025 9 sp_18 -0.539895140 0.70220997
-#> 619 0 1.71506499 0.68864025 7 sp_19 -0.539895140 0.70220997
-#> 620 0 1.71506499 0.68864025 9 sp_20 -0.539895140 0.70220997
-#> 621 0 1.71506499 0.68864025 4 sp_21 -0.539895140 0.70220997
-#> 622 0 1.71506499 0.68864025 2 sp_22 -0.539895140 0.70220997
-#> 623 0 1.71506499 0.68864025 12 sp_23 -0.539895140 0.70220997
-#> 624 0 1.71506499 0.68864025 9 sp_24 -0.539895140 0.70220997
-#> 625 0 1.71506499 0.68864025 11 sp_25 -0.539895140 0.70220997
-#> 626 0 1.71506499 0.68864025 7 sp_26 -0.539895140 0.70220997
-#> 627 0 1.71506499 0.68864025 13 sp_27 -0.539895140 0.70220997
-#> 628 0 1.71506499 0.68864025 5 sp_28 -0.539895140 0.70220997
-#> 629 0 1.71506499 0.68864025 11 sp_29 -0.539895140 0.70220997
-#> 630 0 1.71506499 0.68864025 1 sp_30 -0.539895140 0.70220997
-#> 721 0 0.46091621 0.55391765 19 sp_1 -1.072417884 1.02610781
-#> 722 0 0.46091621 0.55391765 12 sp_2 -1.072417884 1.02610781
-#> 723 0 0.46091621 0.55391765 2 sp_3 -1.072417884 1.02610781
-#> 724 1 0.46091621 0.55391765 17 sp_4 -1.072417884 1.02610781
-#> 725 0 0.46091621 0.55391765 12 sp_5 -1.072417884 1.02610781
-#> 726 0 0.46091621 0.55391765 3 sp_6 -1.072417884 1.02610781
-#> 727 0 0.46091621 0.55391765 18 sp_7 -1.072417884 1.02610781
-#> 728 0 0.46091621 0.55391765 15 sp_8 -1.072417884 1.02610781
-#> 729 0 0.46091621 0.55391765 3 sp_9 -1.072417884 1.02610781
-#> 730 0 0.46091621 0.55391765 19 sp_10 -1.072417884 1.02610781
-#> 731 0 0.46091621 0.55391765 18 sp_11 -1.072417884 1.02610781
-#> 732 0 0.46091621 0.55391765 17 sp_12 -1.072417884 1.02610781
-#> 733 0 0.46091621 0.55391765 6 sp_13 -1.072417884 1.02610781
-#> 734 0 0.46091621 0.55391765 10 sp_14 -1.072417884 1.02610781
-#> 735 0 0.46091621 0.55391765 8 sp_15 -1.072417884 1.02610781
-#> 736 0 0.46091621 0.55391765 10 sp_16 -1.072417884 1.02610781
-#> 737 0 0.46091621 0.55391765 13 sp_17 -1.072417884 1.02610781
-#> 738 0 0.46091621 0.55391765 20 sp_18 -1.072417884 1.02610781
-#> 739 0 0.46091621 0.55391765 6 sp_19 -1.072417884 1.02610781
-#> 740 0 0.46091621 0.55391765 20 sp_20 -1.072417884 1.02610781
-#> 741 0 0.46091621 0.55391765 20 sp_21 -1.072417884 1.02610781
-#> 742 0 0.46091621 0.55391765 9 sp_22 -1.072417884 1.02610781
-#> 743 0 0.46091621 0.55391765 16 sp_23 -1.072417884 1.02610781
-#> 744 0 0.46091621 0.55391765 8 sp_24 -1.072417884 1.02610781
-#> 745 0 0.46091621 0.55391765 7 sp_25 -1.072417884 1.02610781
-#> 746 0 0.46091621 0.55391765 10 sp_26 -1.072417884 1.02610781
-#> 747 0 0.46091621 0.55391765 17 sp_27 -1.072417884 1.02610781
-#> 748 0 0.46091621 0.55391765 18 sp_28 -1.072417884 1.02610781
-#> 749 0 0.46091621 0.55391765 8 sp_29 -1.072417884 1.02610781
-#> 750 0 0.46091621 0.55391765 19 sp_30 -1.072417884 1.02610781
-#> 841 1 -1.26506123 -0.06191171 10 sp_1 0.428912684 -0.90487124
-#> 842 0 -1.26506123 -0.06191171 11 sp_2 0.428912684 -0.90487124
-#> 843 0 -1.26506123 -0.06191171 17 sp_3 0.428912684 -0.90487124
-#> 844 0 -1.26506123 -0.06191171 12 sp_4 0.428912684 -0.90487124
-#> 845 0 -1.26506123 -0.06191171 2 sp_5 0.428912684 -0.90487124
-#> 846 0 -1.26506123 -0.06191171 19 sp_6 0.428912684 -0.90487124
-#> 847 0 -1.26506123 -0.06191171 13 sp_7 0.428912684 -0.90487124
-#> 848 0 -1.26506123 -0.06191171 13 sp_8 0.428912684 -0.90487124
-#> 849 0 -1.26506123 -0.06191171 19 sp_9 0.428912684 -0.90487124
-#> 850 1 -1.26506123 -0.06191171 10 sp_10 0.428912684 -0.90487124
-#> 851 0 -1.26506123 -0.06191171 16 sp_11 0.428912684 -0.90487124
-#> 852 1 -1.26506123 -0.06191171 5 sp_12 0.428912684 -0.90487124
-#> 853 0 -1.26506123 -0.06191171 4 sp_13 0.428912684 -0.90487124
-#> 854 0 -1.26506123 -0.06191171 18 sp_14 0.428912684 -0.90487124
-#> 855 0 -1.26506123 -0.06191171 1 sp_15 0.428912684 -0.90487124
-#> 856 0 -1.26506123 -0.06191171 16 sp_16 0.428912684 -0.90487124
-#> 857 0 -1.26506123 -0.06191171 17 sp_17 0.428912684 -0.90487124
-#> 858 0 -1.26506123 -0.06191171 12 sp_18 0.428912684 -0.90487124
-#> 859 0 -1.26506123 -0.06191171 2 sp_19 0.428912684 -0.90487124
-#> 860 0 -1.26506123 -0.06191171 18 sp_20 0.428912684 -0.90487124
-#> 861 0 -1.26506123 -0.06191171 12 sp_21 0.428912684 -0.90487124
-#> 862 0 -1.26506123 -0.06191171 15 sp_22 0.428912684 -0.90487124
-#> 863 0 -1.26506123 -0.06191171 19 sp_23 0.428912684 -0.90487124
-#> 864 1 -1.26506123 -0.06191171 6 sp_24 0.428912684 -0.90487124
-#> 865 0 -1.26506123 -0.06191171 16 sp_25 0.428912684 -0.90487124
-#> 866 0 -1.26506123 -0.06191171 15 sp_26 0.428912684 -0.90487124
-#> 867 0 -1.26506123 -0.06191171 19 sp_27 0.428912684 -0.90487124
-#> 868 0 -1.26506123 -0.06191171 3 sp_28 0.428912684 -0.90487124
-#> 869 0 -1.26506123 -0.06191171 14 sp_29 0.428912684 -0.90487124
-#> 870 0 -1.26506123 -0.06191171 1 sp_30 0.428912684 -0.90487124
-#> 961 1 -0.68685285 -0.30596266 1 sp_1 -0.482457898 -2.17554647
-#> 962 0 -0.68685285 -0.30596266 16 sp_2 -0.482457898 -2.17554647
-#> 963 0 -0.68685285 -0.30596266 11 sp_3 -0.482457898 -2.17554647
-#> 964 1 -0.68685285 -0.30596266 4 sp_4 -0.482457898 -2.17554647
-#> 965 1 -0.68685285 -0.30596266 12 sp_5 -0.482457898 -2.17554647
-#> 966 1 -0.68685285 -0.30596266 13 sp_6 -0.482457898 -2.17554647
-#> 967 0 -0.68685285 -0.30596266 10 sp_7 -0.482457898 -2.17554647
-#> 968 0 -0.68685285 -0.30596266 10 sp_8 -0.482457898 -2.17554647
-#> 969 0 -0.68685285 -0.30596266 7 sp_9 -0.482457898 -2.17554647
-#> 970 0 -0.68685285 -0.30596266 18 sp_10 -0.482457898 -2.17554647
-#> 971 0 -0.68685285 -0.30596266 17 sp_11 -0.482457898 -2.17554647
-#> 972 1 -0.68685285 -0.30596266 20 sp_12 -0.482457898 -2.17554647
-#> 973 1 -0.68685285 -0.30596266 9 sp_13 -0.482457898 -2.17554647
-#> 974 1 -0.68685285 -0.30596266 11 sp_14 -0.482457898 -2.17554647
-#> 975 1 -0.68685285 -0.30596266 12 sp_15 -0.482457898 -2.17554647
-#> 976 0 -0.68685285 -0.30596266 8 sp_16 -0.482457898 -2.17554647
-#> 977 0 -0.68685285 -0.30596266 18 sp_17 -0.482457898 -2.17554647
-#> 978 0 -0.68685285 -0.30596266 5 sp_18 -0.482457898 -2.17554647
-#> 979 0 -0.68685285 -0.30596266 18 sp_19 -0.482457898 -2.17554647
-#> 980 0 -0.68685285 -0.30596266 6 sp_20 -0.482457898 -2.17554647
-#> 981 0 -0.68685285 -0.30596266 10 sp_21 -0.482457898 -2.17554647
-#> 982 0 -0.68685285 -0.30596266 9 sp_22 -0.482457898 -2.17554647
-#> 983 1 -0.68685285 -0.30596266 11 sp_23 -0.482457898 -2.17554647
-#> 984 0 -0.68685285 -0.30596266 6 sp_24 -0.482457898 -2.17554647
-#> 985 0 -0.68685285 -0.30596266 12 sp_25 -0.482457898 -2.17554647
-#> 986 0 -0.68685285 -0.30596266 19 sp_26 -0.482457898 -2.17554647
-#> 987 0 -0.68685285 -0.30596266 4 sp_27 -0.482457898 -2.17554647
-#> 988 0 -0.68685285 -0.30596266 3 sp_28 -0.482457898 -2.17554647
-#> 989 0 -0.68685285 -0.30596266 14 sp_29 -0.482457898 -2.17554647
-#> 990 1 -0.68685285 -0.30596266 8 sp_30 -0.482457898 -2.17554647
-#> 1081 0 -0.44566197 -0.38047100 6 sp_1 -0.090646571 0.82760513
-#> 1082 0 -0.44566197 -0.38047100 4 sp_2 -0.090646571 0.82760513
-#> 1083 1 -0.44566197 -0.38047100 10 sp_3 -0.090646571 0.82760513
-#> 1084 0 -0.44566197 -0.38047100 16 sp_4 -0.090646571 0.82760513
-#> 1085 0 -0.44566197 -0.38047100 16 sp_5 -0.090646571 0.82760513
-#> 1086 0 -0.44566197 -0.38047100 20 sp_6 -0.090646571 0.82760513
-#> 1087 0 -0.44566197 -0.38047100 10 sp_7 -0.090646571 0.82760513
-#> 1088 0 -0.44566197 -0.38047100 6 sp_8 -0.090646571 0.82760513
-#> 1089 0 -0.44566197 -0.38047100 19 sp_9 -0.090646571 0.82760513
-#> 1090 0 -0.44566197 -0.38047100 4 sp_10 -0.090646571 0.82760513
-#> 1091 0 -0.44566197 -0.38047100 9 sp_11 -0.090646571 0.82760513
-#> 1092 0 -0.44566197 -0.38047100 4 sp_12 -0.090646571 0.82760513
-#> 1093 0 -0.44566197 -0.38047100 15 sp_13 -0.090646571 0.82760513
-#> 1094 0 -0.44566197 -0.38047100 20 sp_14 -0.090646571 0.82760513
-#> 1095 0 -0.44566197 -0.38047100 17 sp_15 -0.090646571 0.82760513
-#> 1096 0 -0.44566197 -0.38047100 7 sp_16 -0.090646571 0.82760513
-#> 1097 0 -0.44566197 -0.38047100 15 sp_17 -0.090646571 0.82760513
-#> 1098 0 -0.44566197 -0.38047100 5 sp_18 -0.090646571 0.82760513
-#> 1099 0 -0.44566197 -0.38047100 14 sp_19 -0.090646571 0.82760513
-#> 1100 0 -0.44566197 -0.38047100 15 sp_20 -0.090646571 0.82760513
-#> 1101 1 -0.44566197 -0.38047100 15 sp_21 -0.090646571 0.82760513
-#> 1102 0 -0.44566197 -0.38047100 16 sp_22 -0.090646571 0.82760513
-#> 1103 0 -0.44566197 -0.38047100 19 sp_23 -0.090646571 0.82760513
-#> 1104 0 -0.44566197 -0.38047100 8 sp_24 -0.090646571 0.82760513
-#> 1105 0 -0.44566197 -0.38047100 5 sp_25 -0.090646571 0.82760513
-#> 1106 0 -0.44566197 -0.38047100 7 sp_26 -0.090646571 0.82760513
-#> 1107 0 -0.44566197 -0.38047100 20 sp_27 -0.090646571 0.82760513
-#> 1108 0 -0.44566197 -0.38047100 16 sp_28 -0.090646571 0.82760513
-#> 1109 0 -0.44566197 -0.38047100 16 sp_29 -0.090646571 0.82760513
-#> 1110 0 -0.44566197 -0.38047100 9 sp_30 -0.090646571 0.82760513
-#> 1201 1 1.22408180 -0.69470698 11 sp_1 0.791847550 -1.27168186
-#> 1202 1 1.22408180 -0.69470698 11 sp_2 0.791847550 -1.27168186
-#> 1203 1 1.22408180 -0.69470698 19 sp_3 0.791847550 -1.27168186
-#> 1204 1 1.22408180 -0.69470698 10 sp_4 0.791847550 -1.27168186
-#> 1205 0 1.22408180 -0.69470698 2 sp_5 0.791847550 -1.27168186
-#> 1206 0 1.22408180 -0.69470698 6 sp_6 0.791847550 -1.27168186
-#> 1207 0 1.22408180 -0.69470698 20 sp_7 0.791847550 -1.27168186
-#> 1208 0 1.22408180 -0.69470698 14 sp_8 0.791847550 -1.27168186
-#> 1209 0 1.22408180 -0.69470698 14 sp_9 0.791847550 -1.27168186
-#> 1210 1 1.22408180 -0.69470698 6 sp_10 0.791847550 -1.27168186
-#> 1211 0 1.22408180 -0.69470698 18 sp_11 0.791847550 -1.27168186
-#> 1212 0 1.22408180 -0.69470698 2 sp_12 0.791847550 -1.27168186
-#> 1213 1 1.22408180 -0.69470698 8 sp_13 0.791847550 -1.27168186
-#> 1214 1 1.22408180 -0.69470698 11 sp_14 0.791847550 -1.27168186
-#> 1215 1 1.22408180 -0.69470698 7 sp_15 0.791847550 -1.27168186
-#> 1216 1 1.22408180 -0.69470698 19 sp_16 0.791847550 -1.27168186
-#> 1217 0 1.22408180 -0.69470698 8 sp_17 0.791847550 -1.27168186
-#> 1218 1 1.22408180 -0.69470698 10 sp_18 0.791847550 -1.27168186
-#> 1219 1 1.22408180 -0.69470698 5 sp_19 0.791847550 -1.27168186
-#> 1220 1 1.22408180 -0.69470698 17 sp_20 0.791847550 -1.27168186
-#> 1221 1 1.22408180 -0.69470698 6 sp_21 0.791847550 -1.27168186
-#> 1222 1 1.22408180 -0.69470698 8 sp_22 0.791847550 -1.27168186
-#> 1223 0 1.22408180 -0.69470698 20 sp_23 0.791847550 -1.27168186
-#> 1224 1 1.22408180 -0.69470698 6 sp_24 0.791847550 -1.27168186
-#> 1225 1 1.22408180 -0.69470698 15 sp_25 0.791847550 -1.27168186
-#> 1226 0 1.22408180 -0.69470698 17 sp_26 0.791847550 -1.27168186
-#> 1227 0 1.22408180 -0.69470698 3 sp_27 0.791847550 -1.27168186
-#> 1228 0 1.22408180 -0.69470698 15 sp_28 0.791847550 -1.27168186
-#> 1229 1 1.22408180 -0.69470698 20 sp_29 0.791847550 -1.27168186
-#> 1230 1 1.22408180 -0.69470698 1 sp_30 0.791847550 -1.27168186
-#> 1321 0 0.35981383 -0.20791728 5 sp_1 0.068754653 0.07194716
-#> 1322 0 0.35981383 -0.20791728 11 sp_2 0.068754653 0.07194716
-#> 1323 0 0.35981383 -0.20791728 15 sp_3 0.068754653 0.07194716
-#> 1324 0 0.35981383 -0.20791728 20 sp_4 0.068754653 0.07194716
-#> 1325 0 0.35981383 -0.20791728 2 sp_5 0.068754653 0.07194716
-#> 1326 0 0.35981383 -0.20791728 16 sp_6 0.068754653 0.07194716
-#> 1327 0 0.35981383 -0.20791728 19 sp_7 0.068754653 0.07194716
-#> 1328 0 0.35981383 -0.20791728 10 sp_8 0.068754653 0.07194716
-#> 1329 0 0.35981383 -0.20791728 19 sp_9 0.068754653 0.07194716
-#> 1330 1 0.35981383 -0.20791728 17 sp_10 0.068754653 0.07194716
-#> 1331 0 0.35981383 -0.20791728 7 sp_11 0.068754653 0.07194716
-#> 1332 0 0.35981383 -0.20791728 6 sp_12 0.068754653 0.07194716
-#> 1333 0 0.35981383 -0.20791728 12 sp_13 0.068754653 0.07194716
-#> 1334 0 0.35981383 -0.20791728 4 sp_14 0.068754653 0.07194716
-#> 1335 0 0.35981383 -0.20791728 19 sp_15 0.068754653 0.07194716
-#> 1336 1 0.35981383 -0.20791728 2 sp_16 0.068754653 0.07194716
-#> 1337 0 0.35981383 -0.20791728 4 sp_17 0.068754653 0.07194716
-#> 1338 0 0.35981383 -0.20791728 11 sp_18 0.068754653 0.07194716
-#> 1339 0 0.35981383 -0.20791728 1 sp_19 0.068754653 0.07194716
-#> 1340 0 0.35981383 -0.20791728 19 sp_20 0.068754653 0.07194716
-#> 1341 1 0.35981383 -0.20791728 18 sp_21 0.068754653 0.07194716
-#> 1342 0 0.35981383 -0.20791728 16 sp_22 0.068754653 0.07194716
-#> 1343 0 0.35981383 -0.20791728 3 sp_23 0.068754653 0.07194716
-#> 1344 0 0.35981383 -0.20791728 1 sp_24 0.068754653 0.07194716
-#> 1345 1 0.35981383 -0.20791728 2 sp_25 0.068754653 0.07194716
-#> 1346 0 0.35981383 -0.20791728 2 sp_26 0.068754653 0.07194716
-#> 1347 0 0.35981383 -0.20791728 8 sp_27 0.068754653 0.07194716
-#> 1348 0 0.35981383 -0.20791728 20 sp_28 0.068754653 0.07194716
-#> 1349 0 0.35981383 -0.20791728 14 sp_29 0.068754653 0.07194716
-#> 1350 0 0.35981383 -0.20791728 13 sp_30 0.068754653 0.07194716
-#> 1441 0 0.40077145 -1.26539635 7 sp_1 -0.613966444 -1.18393872
-#> 1442 0 0.40077145 -1.26539635 8 sp_2 -0.613966444 -1.18393872
-#> 1443 1 0.40077145 -1.26539635 3 sp_3 -0.613966444 -1.18393872
-#> 1444 0 0.40077145 -1.26539635 16 sp_4 -0.613966444 -1.18393872
-#> 1445 1 0.40077145 -1.26539635 1 sp_5 -0.613966444 -1.18393872
-#> 1446 1 0.40077145 -1.26539635 12 sp_6 -0.613966444 -1.18393872
-#> 1447 0 0.40077145 -1.26539635 18 sp_7 -0.613966444 -1.18393872
-#> 1448 0 0.40077145 -1.26539635 14 sp_8 -0.613966444 -1.18393872
-#> 1449 0 0.40077145 -1.26539635 8 sp_9 -0.613966444 -1.18393872
-#> 1450 1 0.40077145 -1.26539635 5 sp_10 -0.613966444 -1.18393872
-#> 1451 0 0.40077145 -1.26539635 17 sp_11 -0.613966444 -1.18393872
-#> 1452 1 0.40077145 -1.26539635 11 sp_12 -0.613966444 -1.18393872
-#> 1453 0 0.40077145 -1.26539635 4 sp_13 -0.613966444 -1.18393872
-#> 1454 1 0.40077145 -1.26539635 13 sp_14 -0.613966444 -1.18393872
-#> 1455 1 0.40077145 -1.26539635 8 sp_15 -0.613966444 -1.18393872
-#> 1456 1 0.40077145 -1.26539635 15 sp_16 -0.613966444 -1.18393872
-#> 1457 1 0.40077145 -1.26539635 4 sp_17 -0.613966444 -1.18393872
-#> 1458 0 0.40077145 -1.26539635 13 sp_18 -0.613966444 -1.18393872
-#> 1459 1 0.40077145 -1.26539635 3 sp_19 -0.613966444 -1.18393872
-#> 1460 0 0.40077145 -1.26539635 7 sp_20 -0.613966444 -1.18393872
-#> 1461 1 0.40077145 -1.26539635 1 sp_21 -0.613966444 -1.18393872
-#> 1462 0 0.40077145 -1.26539635 6 sp_22 -0.613966444 -1.18393872
-#> 1463 1 0.40077145 -1.26539635 13 sp_23 -0.613966444 -1.18393872
-#> 1464 1 0.40077145 -1.26539635 17 sp_24 -0.613966444 -1.18393872
-#> 1465 0 0.40077145 -1.26539635 6 sp_25 -0.613966444 -1.18393872
-#> 1466 1 0.40077145 -1.26539635 10 sp_26 -0.613966444 -1.18393872
-#> 1467 0 0.40077145 -1.26539635 13 sp_27 -0.613966444 -1.18393872
-#> 1468 0 0.40077145 -1.26539635 6 sp_28 -0.613966444 -1.18393872
-#> 1469 0 0.40077145 -1.26539635 9 sp_29 -0.613966444 -1.18393872
-#> 1470 0 0.40077145 -1.26539635 8 sp_30 -0.613966444 -1.18393872
-#> 1561 0 0.11068272 2.16895597 1 sp_1 -0.714181239 0.13138207
-#> 1562 1 0.11068272 2.16895597 16 sp_2 -0.714181239 0.13138207
-#> 1563 0 0.11068272 2.16895597 2 sp_3 -0.714181239 0.13138207
-#> 1564 0 0.11068272 2.16895597 8 sp_4 -0.714181239 0.13138207
-#> 1565 0 0.11068272 2.16895597 14 sp_5 -0.714181239 0.13138207
-#> 1566 0 0.11068272 2.16895597 12 sp_6 -0.714181239 0.13138207
-#> 1567 0 0.11068272 2.16895597 8 sp_7 -0.714181239 0.13138207
-#> 1568 0 0.11068272 2.16895597 9 sp_8 -0.714181239 0.13138207
-#> 1569 0 0.11068272 2.16895597 8 sp_9 -0.714181239 0.13138207
-#> 1570 0 0.11068272 2.16895597 9 sp_10 -0.714181239 0.13138207
-#> 1571 0 0.11068272 2.16895597 20 sp_11 -0.714181239 0.13138207
-#> 1572 0 0.11068272 2.16895597 1 sp_12 -0.714181239 0.13138207
-#> 1573 0 0.11068272 2.16895597 3 sp_13 -0.714181239 0.13138207
-#> 1574 0 0.11068272 2.16895597 8 sp_14 -0.714181239 0.13138207
-#> 1575 0 0.11068272 2.16895597 2 sp_15 -0.714181239 0.13138207
-#> 1576 0 0.11068272 2.16895597 1 sp_16 -0.714181239 0.13138207
-#> 1577 0 0.11068272 2.16895597 9 sp_17 -0.714181239 0.13138207
-#> 1578 0 0.11068272 2.16895597 7 sp_18 -0.714181239 0.13138207
-#> 1579 0 0.11068272 2.16895597 13 sp_19 -0.714181239 0.13138207
-#> 1580 0 0.11068272 2.16895597 20 sp_20 -0.714181239 0.13138207
-#> 1581 0 0.11068272 2.16895597 14 sp_21 -0.714181239 0.13138207
-#> 1582 0 0.11068272 2.16895597 16 sp_22 -0.714181239 0.13138207
-#> 1583 0 0.11068272 2.16895597 7 sp_23 -0.714181239 0.13138207
-#> 1584 0 0.11068272 2.16895597 4 sp_24 -0.714181239 0.13138207
-#> 1585 0 0.11068272 2.16895597 13 sp_25 -0.714181239 0.13138207
-#> 1586 0 0.11068272 2.16895597 12 sp_26 -0.714181239 0.13138207
-#> 1587 0 0.11068272 2.16895597 13 sp_27 -0.714181239 0.13138207
-#> 1588 0 0.11068272 2.16895597 20 sp_28 -0.714181239 0.13138207
-#> 1589 0 0.11068272 2.16895597 10 sp_29 -0.714181239 0.13138207
-#> 1590 0 0.11068272 2.16895597 9 sp_30 -0.714181239 0.13138207
-#> 1681 0 -0.55584113 1.20796200 12 sp_1 0.324249513 -0.14985243
-#> 1682 0 -0.55584113 1.20796200 8 sp_2 0.324249513 -0.14985243
-#> 1683 0 -0.55584113 1.20796200 7 sp_3 0.324249513 -0.14985243
-#> 1684 0 -0.55584113 1.20796200 15 sp_4 0.324249513 -0.14985243
-#> 1685 0 -0.55584113 1.20796200 19 sp_5 0.324249513 -0.14985243
-#> 1686 0 -0.55584113 1.20796200 17 sp_6 0.324249513 -0.14985243
-#> 1687 0 -0.55584113 1.20796200 11 sp_7 0.324249513 -0.14985243
-#> 1688 0 -0.55584113 1.20796200 7 sp_8 0.324249513 -0.14985243
-#> 1689 0 -0.55584113 1.20796200 19 sp_9 0.324249513 -0.14985243
-#> 1690 0 -0.55584113 1.20796200 3 sp_10 0.324249513 -0.14985243
-#> 1691 0 -0.55584113 1.20796200 6 sp_11 0.324249513 -0.14985243
-#> 1692 0 -0.55584113 1.20796200 7 sp_12 0.324249513 -0.14985243
-#> 1693 0 -0.55584113 1.20796200 4 sp_13 0.324249513 -0.14985243
-#> 1694 1 -0.55584113 1.20796200 10 sp_14 0.324249513 -0.14985243
-#> 1695 0 -0.55584113 1.20796200 17 sp_15 0.324249513 -0.14985243
-#> 1696 0 -0.55584113 1.20796200 16 sp_16 0.324249513 -0.14985243
-#> 1697 0 -0.55584113 1.20796200 8 sp_17 0.324249513 -0.14985243
-#> 1698 0 -0.55584113 1.20796200 3 sp_18 0.324249513 -0.14985243
-#> 1699 0 -0.55584113 1.20796200 12 sp_19 0.324249513 -0.14985243
-#> 1700 0 -0.55584113 1.20796200 14 sp_20 0.324249513 -0.14985243
-#> 1701 0 -0.55584113 1.20796200 5 sp_21 0.324249513 -0.14985243
-#> 1702 0 -0.55584113 1.20796200 14 sp_22 0.324249513 -0.14985243
-#> 1703 0 -0.55584113 1.20796200 6 sp_23 0.324249513 -0.14985243
-#> 1704 0 -0.55584113 1.20796200 9 sp_24 0.324249513 -0.14985243
-#> 1705 0 -0.55584113 1.20796200 1 sp_25 0.324249513 -0.14985243
-#> 1706 0 -0.55584113 1.20796200 20 sp_26 0.324249513 -0.14985243
-#> 1707 0 -0.55584113 1.20796200 14 sp_27 0.324249513 -0.14985243
-#> 1708 0 -0.55584113 1.20796200 19 sp_28 0.324249513 -0.14985243
-#> 1709 0 -0.55584113 1.20796200 5 sp_29 0.324249513 -0.14985243
-#> 1710 0 -0.55584113 1.20796200 2 sp_30 0.324249513 -0.14985243
-#> 1801 0 1.78691314 -1.12310858 1 sp_1 0.343282350 1.41604345
-#> 1802 0 1.78691314 -1.12310858 20 sp_2 0.343282350 1.41604345
-#> 1803 0 1.78691314 -1.12310858 4 sp_3 0.343282350 1.41604345
-#> 1804 0 1.78691314 -1.12310858 11 sp_4 0.343282350 1.41604345
-#> 1805 1 1.78691314 -1.12310858 5 sp_5 0.343282350 1.41604345
-#> 1806 0 1.78691314 -1.12310858 4 sp_6 0.343282350 1.41604345
-#> 1807 0 1.78691314 -1.12310858 19 sp_7 0.343282350 1.41604345
-#> 1808 0 1.78691314 -1.12310858 3 sp_8 0.343282350 1.41604345
-#> 1809 0 1.78691314 -1.12310858 1 sp_9 0.343282350 1.41604345
-#> 1810 0 1.78691314 -1.12310858 7 sp_10 0.343282350 1.41604345
-#> 1811 1 1.78691314 -1.12310858 5 sp_11 0.343282350 1.41604345
-#> 1812 0 1.78691314 -1.12310858 9 sp_12 0.343282350 1.41604345
-#> 1813 0 1.78691314 -1.12310858 17 sp_13 0.343282350 1.41604345
-#> 1814 1 1.78691314 -1.12310858 5 sp_14 0.343282350 1.41604345
-#> 1815 0 1.78691314 -1.12310858 12 sp_15 0.343282350 1.41604345
-#> 1816 0 1.78691314 -1.12310858 2 sp_16 0.343282350 1.41604345
-#> 1817 1 1.78691314 -1.12310858 18 sp_17 0.343282350 1.41604345
-#> 1818 0 1.78691314 -1.12310858 4 sp_18 0.343282350 1.41604345
-#> 1819 1 1.78691314 -1.12310858 10 sp_19 0.343282350 1.41604345
-#> 1820 0 1.78691314 -1.12310858 15 sp_20 0.343282350 1.41604345
-#> 1821 0 1.78691314 -1.12310858 8 sp_21 0.343282350 1.41604345
-#> 1822 0 1.78691314 -1.12310858 1 sp_22 0.343282350 1.41604345
-#> 1823 0 1.78691314 -1.12310858 11 sp_23 0.343282350 1.41604345
-#> 1824 0 1.78691314 -1.12310858 5 sp_24 0.343282350 1.41604345
-#> 1825 1 1.78691314 -1.12310858 11 sp_25 0.343282350 1.41604345
-#> 1826 1 1.78691314 -1.12310858 15 sp_26 0.343282350 1.41604345
-#> 1827 0 1.78691314 -1.12310858 15 sp_27 0.343282350 1.41604345
-#> 1828 1 1.78691314 -1.12310858 10 sp_28 0.343282350 1.41604345
-#> 1829 0 1.78691314 -1.12310858 15 sp_29 0.343282350 1.41604345
-#> 1830 0 1.78691314 -1.12310858 15 sp_30 0.343282350 1.41604345
-#> 1921 0 0.49785048 -0.40288484 20 sp_1 -0.439619408 -0.09657875
-#> 1922 0 0.49785048 -0.40288484 12 sp_2 -0.439619408 -0.09657875
-#> 1923 0 0.49785048 -0.40288484 9 sp_3 -0.439619408 -0.09657875
-#> 1924 0 0.49785048 -0.40288484 4 sp_4 -0.439619408 -0.09657875
-#> 1925 0 0.49785048 -0.40288484 3 sp_5 -0.439619408 -0.09657875
-#> 1926 0 0.49785048 -0.40288484 7 sp_6 -0.439619408 -0.09657875
-#> 1927 0 0.49785048 -0.40288484 4 sp_7 -0.439619408 -0.09657875
-#> 1928 0 0.49785048 -0.40288484 8 sp_8 -0.439619408 -0.09657875
-#> 1929 0 0.49785048 -0.40288484 5 sp_9 -0.439619408 -0.09657875
-#> 1930 0 0.49785048 -0.40288484 6 sp_10 -0.439619408 -0.09657875
-#> 1931 1 0.49785048 -0.40288484 4 sp_11 -0.439619408 -0.09657875
-#> 1932 1 0.49785048 -0.40288484 3 sp_12 -0.439619408 -0.09657875
-#> 1933 0 0.49785048 -0.40288484 11 sp_13 -0.439619408 -0.09657875
-#> 1934 0 0.49785048 -0.40288484 10 sp_14 -0.439619408 -0.09657875
-#> 1935 0 0.49785048 -0.40288484 5 sp_15 -0.439619408 -0.09657875
-#> 1936 0 0.49785048 -0.40288484 11 sp_16 -0.439619408 -0.09657875
-#> 1937 0 0.49785048 -0.40288484 10 sp_17 -0.439619408 -0.09657875
-#> 1938 1 0.49785048 -0.40288484 15 sp_18 -0.439619408 -0.09657875
-#> 1939 1 0.49785048 -0.40288484 19 sp_19 -0.439619408 -0.09657875
-#> 1940 0 0.49785048 -0.40288484 10 sp_20 -0.439619408 -0.09657875
-#> 1941 0 0.49785048 -0.40288484 13 sp_21 -0.439619408 -0.09657875
-#> 1942 0 0.49785048 -0.40288484 3 sp_22 -0.439619408 -0.09657875
-#> 1943 0 0.49785048 -0.40288484 18 sp_23 -0.439619408 -0.09657875
-#> 1944 0 0.49785048 -0.40288484 10 sp_24 -0.439619408 -0.09657875
-#> 1945 0 0.49785048 -0.40288484 8 sp_25 -0.439619408 -0.09657875
-#> 1946 1 0.49785048 -0.40288484 12 sp_26 -0.439619408 -0.09657875
-#> 1947 0 0.49785048 -0.40288484 10 sp_27 -0.439619408 -0.09657875
-#> 1948 0 0.49785048 -0.40288484 7 sp_28 -0.439619408 -0.09657875
-#> 1949 0 0.49785048 -0.40288484 7 sp_29 -0.439619408 -0.09657875
-#> 1950 0 0.49785048 -0.40288484 6 sp_30 -0.439619408 -0.09657875
-#> 2041 0 -1.96661716 -0.46665535 17 sp_1 0.345096720 -0.55778849
-#> 2042 0 -1.96661716 -0.46665535 20 sp_2 0.345096720 -0.55778849
-#> 2043 0 -1.96661716 -0.46665535 1 sp_3 0.345096720 -0.55778849
-#> 2044 0 -1.96661716 -0.46665535 5 sp_4 0.345096720 -0.55778849
-#> 2045 0 -1.96661716 -0.46665535 10 sp_5 0.345096720 -0.55778849
-#> 2046 0 -1.96661716 -0.46665535 13 sp_6 0.345096720 -0.55778849
-#> 2047 0 -1.96661716 -0.46665535 10 sp_7 0.345096720 -0.55778849
-#> 2048 0 -1.96661716 -0.46665535 2 sp_8 0.345096720 -0.55778849
-#> 2049 1 -1.96661716 -0.46665535 15 sp_9 0.345096720 -0.55778849
-#> 2050 0 -1.96661716 -0.46665535 15 sp_10 0.345096720 -0.55778849
-#> 2051 0 -1.96661716 -0.46665535 8 sp_11 0.345096720 -0.55778849
-#> 2052 0 -1.96661716 -0.46665535 3 sp_12 0.345096720 -0.55778849
-#> 2053 0 -1.96661716 -0.46665535 2 sp_13 0.345096720 -0.55778849
-#> 2054 0 -1.96661716 -0.46665535 6 sp_14 0.345096720 -0.55778849
-#> 2055 0 -1.96661716 -0.46665535 14 sp_15 0.345096720 -0.55778849
-#> 2056 0 -1.96661716 -0.46665535 15 sp_16 0.345096720 -0.55778849
-#> 2057 0 -1.96661716 -0.46665535 19 sp_17 0.345096720 -0.55778849
-#> 2058 0 -1.96661716 -0.46665535 9 sp_18 0.345096720 -0.55778849
-#> 2059 0 -1.96661716 -0.46665535 15 sp_19 0.345096720 -0.55778849
-#> 2060 0 -1.96661716 -0.46665535 16 sp_20 0.345096720 -0.55778849
-#> 2061 0 -1.96661716 -0.46665535 8 sp_21 0.345096720 -0.55778849
-#> 2062 0 -1.96661716 -0.46665535 9 sp_22 0.345096720 -0.55778849
-#> 2063 0 -1.96661716 -0.46665535 16 sp_23 0.345096720 -0.55778849
-#> 2064 0 -1.96661716 -0.46665535 9 sp_24 0.345096720 -0.55778849
-#> 2065 0 -1.96661716 -0.46665535 2 sp_25 0.345096720 -0.55778849
-#> 2066 0 -1.96661716 -0.46665535 9 sp_26 0.345096720 -0.55778849
-#> 2067 0 -1.96661716 -0.46665535 11 sp_27 0.345096720 -0.55778849
-#> 2068 0 -1.96661716 -0.46665535 11 sp_28 0.345096720 -0.55778849
-#> 2069 0 -1.96661716 -0.46665535 4 sp_29 0.345096720 -0.55778849
-#> 2070 0 -1.96661716 -0.46665535 7 sp_30 0.345096720 -0.55778849
-#> 2161 0 0.70135590 0.77996512 18 sp_1 -0.919759738 -0.31845834
-#> 2162 0 0.70135590 0.77996512 11 sp_2 -0.919759738 -0.31845834
-#> 2163 0 0.70135590 0.77996512 1 sp_3 -0.919759738 -0.31845834
-#> 2164 0 0.70135590 0.77996512 11 sp_4 -0.919759738 -0.31845834
-#> 2165 0 0.70135590 0.77996512 6 sp_5 -0.919759738 -0.31845834
-#> 2166 0 0.70135590 0.77996512 10 sp_6 -0.919759738 -0.31845834
-#> 2167 0 0.70135590 0.77996512 18 sp_7 -0.919759738 -0.31845834
-#> 2168 0 0.70135590 0.77996512 3 sp_8 -0.919759738 -0.31845834
-#> 2169 0 0.70135590 0.77996512 3 sp_9 -0.919759738 -0.31845834
-#> 2170 0 0.70135590 0.77996512 2 sp_10 -0.919759738 -0.31845834
-#> 2171 1 0.70135590 0.77996512 8 sp_11 -0.919759738 -0.31845834
-#> 2172 0 0.70135590 0.77996512 13 sp_12 -0.919759738 -0.31845834
-#> 2173 0 0.70135590 0.77996512 8 sp_13 -0.919759738 -0.31845834
-#> 2174 1 0.70135590 0.77996512 2 sp_14 -0.919759738 -0.31845834
-#> 2175 0 0.70135590 0.77996512 6 sp_15 -0.919759738 -0.31845834
-#> 2176 0 0.70135590 0.77996512 17 sp_16 -0.919759738 -0.31845834
-#> 2177 0 0.70135590 0.77996512 14 sp_17 -0.919759738 -0.31845834
-#> 2178 0 0.70135590 0.77996512 7 sp_18 -0.919759738 -0.31845834
-#> 2179 0 0.70135590 0.77996512 13 sp_19 -0.919759738 -0.31845834
-#> 2180 0 0.70135590 0.77996512 8 sp_20 -0.919759738 -0.31845834
-#> 2181 0 0.70135590 0.77996512 6 sp_21 -0.919759738 -0.31845834
-#> 2182 0 0.70135590 0.77996512 11 sp_22 -0.919759738 -0.31845834
-#> 2183 0 0.70135590 0.77996512 10 sp_23 -0.919759738 -0.31845834
-#> 2184 0 0.70135590 0.77996512 17 sp_24 -0.919759738 -0.31845834
-#> 2185 0 0.70135590 0.77996512 7 sp_25 -0.919759738 -0.31845834
-#> 2186 0 0.70135590 0.77996512 12 sp_26 -0.919759738 -0.31845834
-#> 2187 0 0.70135590 0.77996512 19 sp_27 -0.919759738 -0.31845834
-#> 2188 0 0.70135590 0.77996512 17 sp_28 -0.919759738 -0.31845834
-#> 2189 0 0.70135590 0.77996512 8 sp_29 -0.919759738 -0.31845834
-#> 2190 0 0.70135590 0.77996512 15 sp_30 -0.919759738 -0.31845834
-#> 2281 1 -0.47279141 -0.08336907 14 sp_1 1.783110817 -0.22054191
-#> 2282 0 -0.47279141 -0.08336907 14 sp_2 1.783110817 -0.22054191
-#> 2283 0 -0.47279141 -0.08336907 17 sp_3 1.783110817 -0.22054191
-#> 2284 1 -0.47279141 -0.08336907 1 sp_4 1.783110817 -0.22054191
-#> 2285 0 -0.47279141 -0.08336907 18 sp_5 1.783110817 -0.22054191
-#> 2286 0 -0.47279141 -0.08336907 18 sp_6 1.783110817 -0.22054191
-#> 2287 0 -0.47279141 -0.08336907 20 sp_7 1.783110817 -0.22054191
-#> 2288 0 -0.47279141 -0.08336907 10 sp_8 1.783110817 -0.22054191
-#> 2289 1 -0.47279141 -0.08336907 10 sp_9 1.783110817 -0.22054191
-#> 2290 0 -0.47279141 -0.08336907 9 sp_10 1.783110817 -0.22054191
-#> 2291 1 -0.47279141 -0.08336907 19 sp_11 1.783110817 -0.22054191
-#> 2292 0 -0.47279141 -0.08336907 18 sp_12 1.783110817 -0.22054191
-#> 2293 0 -0.47279141 -0.08336907 18 sp_13 1.783110817 -0.22054191
-#> 2294 1 -0.47279141 -0.08336907 12 sp_14 1.783110817 -0.22054191
-#> 2295 1 -0.47279141 -0.08336907 12 sp_15 1.783110817 -0.22054191
-#> 2296 0 -0.47279141 -0.08336907 4 sp_16 1.783110817 -0.22054191
-#> 2297 0 -0.47279141 -0.08336907 20 sp_17 1.783110817 -0.22054191
-#> 2298 1 -0.47279141 -0.08336907 10 sp_18 1.783110817 -0.22054191
-#> 2299 0 -0.47279141 -0.08336907 5 sp_19 1.783110817 -0.22054191
-#> 2300 1 -0.47279141 -0.08336907 2 sp_20 1.783110817 -0.22054191
-#> 2301 0 -0.47279141 -0.08336907 18 sp_21 1.783110817 -0.22054191
-#> 2302 1 -0.47279141 -0.08336907 12 sp_22 1.783110817 -0.22054191
-#> 2303 0 -0.47279141 -0.08336907 13 sp_23 1.783110817 -0.22054191
-#> 2304 0 -0.47279141 -0.08336907 11 sp_24 1.783110817 -0.22054191
-#> 2305 0 -0.47279141 -0.08336907 19 sp_25 1.783110817 -0.22054191
-#> 2306 0 -0.47279141 -0.08336907 6 sp_26 1.783110817 -0.22054191
-#> 2307 0 -0.47279141 -0.08336907 18 sp_27 1.783110817 -0.22054191
-#> 2308 0 -0.47279141 -0.08336907 10 sp_28 1.783110817 -0.22054191
-#> 2309 0 -0.47279141 -0.08336907 9 sp_29 1.783110817 -0.22054191
-#> 2310 0 -0.47279141 -0.08336907 3 sp_30 1.783110817 -0.22054191
-#> 2401 0 -1.06782371 0.25331851 19 sp_1 -1.421711896 -0.57964814
-#> 2402 0 -1.06782371 0.25331851 8 sp_2 -1.421711896 -0.57964814
-#> 2403 0 -1.06782371 0.25331851 13 sp_3 -1.421711896 -0.57964814
-#> 2404 0 -1.06782371 0.25331851 1 sp_4 -1.421711896 -0.57964814
-#> 2405 0 -1.06782371 0.25331851 2 sp_5 -1.421711896 -0.57964814
-#> 2406 0 -1.06782371 0.25331851 11 sp_6 -1.421711896 -0.57964814
-#> 2407 0 -1.06782371 0.25331851 16 sp_7 -1.421711896 -0.57964814
-#> 2408 0 -1.06782371 0.25331851 5 sp_8 -1.421711896 -0.57964814
-#> 2409 0 -1.06782371 0.25331851 4 sp_9 -1.421711896 -0.57964814
-#> 2410 0 -1.06782371 0.25331851 3 sp_10 -1.421711896 -0.57964814
-#> 2411 0 -1.06782371 0.25331851 15 sp_11 -1.421711896 -0.57964814
-#> 2412 0 -1.06782371 0.25331851 10 sp_12 -1.421711896 -0.57964814
-#> 2413 0 -1.06782371 0.25331851 7 sp_13 -1.421711896 -0.57964814
-#> 2414 0 -1.06782371 0.25331851 7 sp_14 -1.421711896 -0.57964814
-#> 2415 0 -1.06782371 0.25331851 2 sp_15 -1.421711896 -0.57964814
-#> 2416 0 -1.06782371 0.25331851 18 sp_16 -1.421711896 -0.57964814
-#> 2417 0 -1.06782371 0.25331851 18 sp_17 -1.421711896 -0.57964814
-#> 2418 0 -1.06782371 0.25331851 3 sp_18 -1.421711896 -0.57964814
-#> 2419 0 -1.06782371 0.25331851 8 sp_19 -1.421711896 -0.57964814
-#> 2420 0 -1.06782371 0.25331851 14 sp_20 -1.421711896 -0.57964814
-#> 2421 0 -1.06782371 0.25331851 9 sp_21 -1.421711896 -0.57964814
-#> 2422 0 -1.06782371 0.25331851 15 sp_22 -1.421711896 -0.57964814
-#> 2423 0 -1.06782371 0.25331851 17 sp_23 -1.421711896 -0.57964814
-#> 2424 0 -1.06782371 0.25331851 7 sp_24 -1.421711896 -0.57964814
-#> 2425 0 -1.06782371 0.25331851 8 sp_25 -1.421711896 -0.57964814
-#> 2426 0 -1.06782371 0.25331851 1 sp_26 -1.421711896 -0.57964814
-#> 2427 0 -1.06782371 0.25331851 9 sp_27 -1.421711896 -0.57964814
-#> 2428 0 -1.06782371 0.25331851 3 sp_28 -1.421711896 -0.57964814
-#> 2429 1 -1.06782371 0.25331851 2 sp_29 -1.421711896 -0.57964814
-#> 2430 0 -1.06782371 0.25331851 11 sp_30 -1.421711896 -0.57964814
-#> 2521 1 -0.21797491 -0.02854676 4 sp_1 1.642183362 0.18891799
-#> 2522 0 -0.21797491 -0.02854676 8 sp_2 1.642183362 0.18891799
-#> 2523 0 -0.21797491 -0.02854676 20 sp_3 1.642183362 0.18891799
-#> 2524 1 -0.21797491 -0.02854676 11 sp_4 1.642183362 0.18891799
-#> 2525 0 -0.21797491 -0.02854676 18 sp_5 1.642183362 0.18891799
-#> 2526 0 -0.21797491 -0.02854676 14 sp_6 1.642183362 0.18891799
-#> 2527 0 -0.21797491 -0.02854676 3 sp_7 1.642183362 0.18891799
-#> 2528 0 -0.21797491 -0.02854676 3 sp_8 1.642183362 0.18891799
-#> 2529 0 -0.21797491 -0.02854676 14 sp_9 1.642183362 0.18891799
-#> 2530 0 -0.21797491 -0.02854676 7 sp_10 1.642183362 0.18891799
-#> 2531 0 -0.21797491 -0.02854676 15 sp_11 1.642183362 0.18891799
-#> 2532 0 -0.21797491 -0.02854676 8 sp_12 1.642183362 0.18891799
-#> 2533 0 -0.21797491 -0.02854676 1 sp_13 1.642183362 0.18891799
-#> 2534 0 -0.21797491 -0.02854676 5 sp_14 1.642183362 0.18891799
-#> 2535 1 -0.21797491 -0.02854676 17 sp_15 1.642183362 0.18891799
-#> 2536 0 -0.21797491 -0.02854676 6 sp_16 1.642183362 0.18891799
-#> 2537 0 -0.21797491 -0.02854676 10 sp_17 1.642183362 0.18891799
-#> 2538 1 -0.21797491 -0.02854676 12 sp_18 1.642183362 0.18891799
-#> 2539 0 -0.21797491 -0.02854676 8 sp_19 1.642183362 0.18891799
-#> 2540 0 -0.21797491 -0.02854676 16 sp_20 1.642183362 0.18891799
-#> 2541 0 -0.21797491 -0.02854676 7 sp_21 1.642183362 0.18891799
-#> 2542 0 -0.21797491 -0.02854676 7 sp_22 1.642183362 0.18891799
-#> 2543 0 -0.21797491 -0.02854676 1 sp_23 1.642183362 0.18891799
-#> 2544 0 -0.21797491 -0.02854676 11 sp_24 1.642183362 0.18891799
-#> 2545 0 -0.21797491 -0.02854676 3 sp_25 1.642183362 0.18891799
-#> 2546 0 -0.21797491 -0.02854676 17 sp_26 1.642183362 0.18891799
-#> 2547 0 -0.21797491 -0.02854676 20 sp_27 1.642183362 0.18891799
-#> 2548 1 -0.21797491 -0.02854676 3 sp_28 1.642183362 0.18891799
-#> 2549 0 -0.21797491 -0.02854676 14 sp_29 1.642183362 0.18891799
-#> 2550 0 -0.21797491 -0.02854676 5 sp_30 1.642183362 0.18891799
-#> 2641 0 -1.02600445 -0.04287046 18 sp_1 0.124236888 -0.35126512
-#> 2642 0 -1.02600445 -0.04287046 8 sp_2 0.124236888 -0.35126512
-#> 2643 0 -1.02600445 -0.04287046 20 sp_3 0.124236888 -0.35126512
-#> 2644 0 -1.02600445 -0.04287046 10 sp_4 0.124236888 -0.35126512
-#> 2645 1 -1.02600445 -0.04287046 18 sp_5 0.124236888 -0.35126512
-#> 2646 0 -1.02600445 -0.04287046 17 sp_6 0.124236888 -0.35126512
-#> 2647 0 -1.02600445 -0.04287046 9 sp_7 0.124236888 -0.35126512
-#> 2648 0 -1.02600445 -0.04287046 3 sp_8 0.124236888 -0.35126512
-#> 2649 0 -1.02600445 -0.04287046 5 sp_9 0.124236888 -0.35126512
-#> 2650 0 -1.02600445 -0.04287046 16 sp_10 0.124236888 -0.35126512
-#> 2651 0 -1.02600445 -0.04287046 20 sp_11 0.124236888 -0.35126512
-#> 2652 0 -1.02600445 -0.04287046 3 sp_12 0.124236888 -0.35126512
-#> 2653 0 -1.02600445 -0.04287046 3 sp_13 0.124236888 -0.35126512
-#> 2654 0 -1.02600445 -0.04287046 13 sp_14 0.124236888 -0.35126512
-#> 2655 0 -1.02600445 -0.04287046 4 sp_15 0.124236888 -0.35126512
-#> 2656 0 -1.02600445 -0.04287046 15 sp_16 0.124236888 -0.35126512
-#> 2657 0 -1.02600445 -0.04287046 19 sp_17 0.124236888 -0.35126512
-#> 2658 0 -1.02600445 -0.04287046 13 sp_18 0.124236888 -0.35126512
-#> 2659 1 -1.02600445 -0.04287046 12 sp_19 0.124236888 -0.35126512
-#> 2660 0 -1.02600445 -0.04287046 20 sp_20 0.124236888 -0.35126512
-#> 2661 0 -1.02600445 -0.04287046 13 sp_21 0.124236888 -0.35126512
-#> 2662 0 -1.02600445 -0.04287046 13 sp_22 0.124236888 -0.35126512
-#> 2663 0 -1.02600445 -0.04287046 3 sp_23 0.124236888 -0.35126512
-#> 2664 0 -1.02600445 -0.04287046 20 sp_24 0.124236888 -0.35126512
-#> 2665 0 -1.02600445 -0.04287046 5 sp_25 0.124236888 -0.35126512
-#> 2666 0 -1.02600445 -0.04287046 13 sp_26 0.124236888 -0.35126512
-#> 2667 1 -1.02600445 -0.04287046 12 sp_27 0.124236888 -0.35126512
-#> 2668 0 -1.02600445 -0.04287046 8 sp_28 0.124236888 -0.35126512
-#> 2669 0 -1.02600445 -0.04287046 6 sp_29 0.124236888 -0.35126512
-#> 2670 0 -1.02600445 -0.04287046 16 sp_30 0.124236888 -0.35126512
-#> 2761 0 -0.72889123 1.36860228 11 sp_1 0.001123313 -0.24455126
-#> 2762 0 -0.72889123 1.36860228 12 sp_2 0.001123313 -0.24455126
-#> 2763 0 -0.72889123 1.36860228 16 sp_3 0.001123313 -0.24455126
-#> 2764 0 -0.72889123 1.36860228 15 sp_4 0.001123313 -0.24455126
-#> 2765 0 -0.72889123 1.36860228 1 sp_5 0.001123313 -0.24455126
-#> 2766 0 -0.72889123 1.36860228 12 sp_6 0.001123313 -0.24455126
-#> 2767 0 -0.72889123 1.36860228 10 sp_7 0.001123313 -0.24455126
-#> 2768 0 -0.72889123 1.36860228 10 sp_8 0.001123313 -0.24455126
-#> 2769 0 -0.72889123 1.36860228 4 sp_9 0.001123313 -0.24455126
-#> 2770 0 -0.72889123 1.36860228 9 sp_10 0.001123313 -0.24455126
-#> 2771 0 -0.72889123 1.36860228 20 sp_11 0.001123313 -0.24455126
-#> 2772 0 -0.72889123 1.36860228 5 sp_12 0.001123313 -0.24455126
-#> 2773 0 -0.72889123 1.36860228 9 sp_13 0.001123313 -0.24455126
-#> 2774 0 -0.72889123 1.36860228 19 sp_14 0.001123313 -0.24455126
-#> 2775 0 -0.72889123 1.36860228 3 sp_15 0.001123313 -0.24455126
-#> 2776 0 -0.72889123 1.36860228 2 sp_16 0.001123313 -0.24455126
-#> 2777 0 -0.72889123 1.36860228 12 sp_17 0.001123313 -0.24455126
-#> 2778 0 -0.72889123 1.36860228 15 sp_18 0.001123313 -0.24455126
-#> 2779 0 -0.72889123 1.36860228 17 sp_19 0.001123313 -0.24455126
-#> 2780 0 -0.72889123 1.36860228 3 sp_20 0.001123313 -0.24455126
-#> 2781 0 -0.72889123 1.36860228 7 sp_21 0.001123313 -0.24455126
-#> 2782 0 -0.72889123 1.36860228 13 sp_22 0.001123313 -0.24455126
-#> 2783 0 -0.72889123 1.36860228 14 sp_23 0.001123313 -0.24455126
-#> 2784 0 -0.72889123 1.36860228 2 sp_24 0.001123313 -0.24455126
-#> 2785 0 -0.72889123 1.36860228 9 sp_25 0.001123313 -0.24455126
-#> 2786 0 -0.72889123 1.36860228 15 sp_26 0.001123313 -0.24455126
-#> 2787 0 -0.72889123 1.36860228 1 sp_27 0.001123313 -0.24455126
-#> 2788 0 -0.72889123 1.36860228 10 sp_28 0.001123313 -0.24455126
-#> 2789 0 -0.72889123 1.36860228 9 sp_29 0.001123313 -0.24455126
-#> 2790 0 -0.72889123 1.36860228 9 sp_30 0.001123313 -0.24455126
-#> 2881 0 -0.62503927 -0.22577099 7 sp_1 -1.328975923 1.09479379
-#> 2882 0 -0.62503927 -0.22577099 18 sp_2 -1.328975923 1.09479379
-#> 2883 1 -0.62503927 -0.22577099 12 sp_3 -1.328975923 1.09479379
-#> 2884 0 -0.62503927 -0.22577099 6 sp_4 -1.328975923 1.09479379
-#> 2885 0 -0.62503927 -0.22577099 7 sp_5 -1.328975923 1.09479379
-#> 2886 0 -0.62503927 -0.22577099 16 sp_6 -1.328975923 1.09479379
-#> 2887 0 -0.62503927 -0.22577099 16 sp_7 -1.328975923 1.09479379
-#> 2888 0 -0.62503927 -0.22577099 2 sp_8 -1.328975923 1.09479379
-#> 2889 0 -0.62503927 -0.22577099 2 sp_9 -1.328975923 1.09479379
-#> 2890 0 -0.62503927 -0.22577099 14 sp_10 -1.328975923 1.09479379
-#> 2891 0 -0.62503927 -0.22577099 7 sp_11 -1.328975923 1.09479379
-#> 2892 0 -0.62503927 -0.22577099 6 sp_12 -1.328975923 1.09479379
-#> 2893 0 -0.62503927 -0.22577099 4 sp_13 -1.328975923 1.09479379
-#> 2894 0 -0.62503927 -0.22577099 3 sp_14 -1.328975923 1.09479379
-#> 2895 0 -0.62503927 -0.22577099 14 sp_15 -1.328975923 1.09479379
-#> 2896 0 -0.62503927 -0.22577099 19 sp_16 -1.328975923 1.09479379
-#> 2897 0 -0.62503927 -0.22577099 14 sp_17 -1.328975923 1.09479379
-#> 2898 0 -0.62503927 -0.22577099 16 sp_18 -1.328975923 1.09479379
-#> 2899 0 -0.62503927 -0.22577099 10 sp_19 -1.328975923 1.09479379
-#> 2900 0 -0.62503927 -0.22577099 12 sp_20 -1.328975923 1.09479379
-#> 2901 0 -0.62503927 -0.22577099 18 sp_21 -1.328975923 1.09479379
-#> 2902 0 -0.62503927 -0.22577099 3 sp_22 -1.328975923 1.09479379
-#> 2903 0 -0.62503927 -0.22577099 1 sp_23 -1.328975923 1.09479379
-#> 2904 0 -0.62503927 -0.22577099 12 sp_24 -1.328975923 1.09479379
-#> 2905 0 -0.62503927 -0.22577099 17 sp_25 -1.328975923 1.09479379
-#> 2906 0 -0.62503927 -0.22577099 1 sp_26 -1.328975923 1.09479379
-#> 2907 0 -0.62503927 -0.22577099 4 sp_27 -1.328975923 1.09479379
-#> 2908 0 -0.62503927 -0.22577099 19 sp_28 -1.328975923 1.09479379
-#> 2909 0 -0.62503927 -0.22577099 13 sp_29 -1.328975923 1.09479379
-#> 2910 0 -0.62503927 -0.22577099 18 sp_30 -1.328975923 1.09479379
-#> 3001 0 -1.68669331 1.51647060 15 sp_1 0.779726615 -1.51078277
-#> 3002 0 -1.68669331 1.51647060 13 sp_2 0.779726615 -1.51078277
-#> 3003 0 -1.68669331 1.51647060 14 sp_3 0.779726615 -1.51078277
-#> 3004 0 -1.68669331 1.51647060 18 sp_4 0.779726615 -1.51078277
-#> 3005 0 -1.68669331 1.51647060 12 sp_5 0.779726615 -1.51078277
-#> 3006 0 -1.68669331 1.51647060 18 sp_6 0.779726615 -1.51078277
-#> 3007 0 -1.68669331 1.51647060 7 sp_7 0.779726615 -1.51078277
-#> 3008 0 -1.68669331 1.51647060 4 sp_8 0.779726615 -1.51078277
-#> 3009 0 -1.68669331 1.51647060 4 sp_9 0.779726615 -1.51078277
-#> 3010 0 -1.68669331 1.51647060 3 sp_10 0.779726615 -1.51078277
-#> 3011 0 -1.68669331 1.51647060 11 sp_11 0.779726615 -1.51078277
-#> 3012 0 -1.68669331 1.51647060 19 sp_12 0.779726615 -1.51078277
-#> 3013 0 -1.68669331 1.51647060 16 sp_13 0.779726615 -1.51078277
-#> 3014 0 -1.68669331 1.51647060 15 sp_14 0.779726615 -1.51078277
-#> 3015 0 -1.68669331 1.51647060 11 sp_15 0.779726615 -1.51078277
-#> 3016 0 -1.68669331 1.51647060 6 sp_16 0.779726615 -1.51078277
-#> 3017 0 -1.68669331 1.51647060 5 sp_17 0.779726615 -1.51078277
-#> 3018 0 -1.68669331 1.51647060 2 sp_18 0.779726615 -1.51078277
-#> 3019 0 -1.68669331 1.51647060 17 sp_19 0.779726615 -1.51078277
-#> 3020 0 -1.68669331 1.51647060 5 sp_20 0.779726615 -1.51078277
-#> 3021 0 -1.68669331 1.51647060 19 sp_21 0.779726615 -1.51078277
-#> 3022 0 -1.68669331 1.51647060 15 sp_22 0.779726615 -1.51078277
-#> 3023 0 -1.68669331 1.51647060 19 sp_23 0.779726615 -1.51078277
-#> 3024 0 -1.68669331 1.51647060 3 sp_24 0.779726615 -1.51078277
-#> 3025 0 -1.68669331 1.51647060 15 sp_25 0.779726615 -1.51078277
-#> 3026 0 -1.68669331 1.51647060 3 sp_26 0.779726615 -1.51078277
-#> 3027 0 -1.68669331 1.51647060 2 sp_27 0.779726615 -1.51078277
-#> 3028 0 -1.68669331 1.51647060 5 sp_28 0.779726615 -1.51078277
-#> 3029 0 -1.68669331 1.51647060 5 sp_29 0.779726615 -1.51078277
-#> 3030 0 -1.68669331 1.51647060 7 sp_30 0.779726615 -1.51078277
-#> 3121 1 0.83778704 -1.54875280 2 sp_1 1.290447486 -0.49645077
-#> 3122 1 0.83778704 -1.54875280 16 sp_2 1.290447486 -0.49645077
-#> 3123 1 0.83778704 -1.54875280 8 sp_3 1.290447486 -0.49645077
-#> 3124 0 0.83778704 -1.54875280 18 sp_4 1.290447486 -0.49645077
-#> 3125 1 0.83778704 -1.54875280 19 sp_5 1.290447486 -0.49645077
-#> 3126 0 0.83778704 -1.54875280 9 sp_6 1.290447486 -0.49645077
-#> 3127 1 0.83778704 -1.54875280 19 sp_7 1.290447486 -0.49645077
-#> 3128 1 0.83778704 -1.54875280 14 sp_8 1.290447486 -0.49645077
-#> 3129 1 0.83778704 -1.54875280 19 sp_9 1.290447486 -0.49645077
-#> 3130 0 0.83778704 -1.54875280 5 sp_10 1.290447486 -0.49645077
-#> 3131 0 0.83778704 -1.54875280 13 sp_11 1.290447486 -0.49645077
-#> 3132 0 0.83778704 -1.54875280 16 sp_12 1.290447486 -0.49645077
-#> 3133 0 0.83778704 -1.54875280 7 sp_13 1.290447486 -0.49645077
-#> 3134 0 0.83778704 -1.54875280 8 sp_14 1.290447486 -0.49645077
-#> 3135 0 0.83778704 -1.54875280 16 sp_15 1.290447486 -0.49645077
-#> 3136 0 0.83778704 -1.54875280 15 sp_16 1.290447486 -0.49645077
-#> 3137 1 0.83778704 -1.54875280 20 sp_17 1.290447486 -0.49645077
-#> 3138 0 0.83778704 -1.54875280 3 sp_18 1.290447486 -0.49645077
-#> 3139 1 0.83778704 -1.54875280 17 sp_19 1.290447486 -0.49645077
-#> 3140 1 0.83778704 -1.54875280 7 sp_20 1.290447486 -0.49645077
-#> 3141 0 0.83778704 -1.54875280 13 sp_21 1.290447486 -0.49645077
-#> 3142 1 0.83778704 -1.54875280 3 sp_22 1.290447486 -0.49645077
-#> 3143 0 0.83778704 -1.54875280 13 sp_23 1.290447486 -0.49645077
-#> 3144 1 0.83778704 -1.54875280 14 sp_24 1.290447486 -0.49645077
-#> 3145 0 0.83778704 -1.54875280 4 sp_25 1.290447486 -0.49645077
-#> 3146 0 0.83778704 -1.54875280 16 sp_26 1.290447486 -0.49645077
-#> 3147 1 0.83778704 -1.54875280 9 sp_27 1.290447486 -0.49645077
-#> 3148 0 0.83778704 -1.54875280 16 sp_28 1.290447486 -0.49645077
-#> 3149 0 0.83778704 -1.54875280 9 sp_29 1.290447486 -0.49645077
-#> 3150 1 0.83778704 -1.54875280 5 sp_30 1.290447486 -0.49645077
-#> 3241 0 0.15337312 0.58461375 14 sp_1 -1.020567780 0.61989576
-#> 3242 0 0.15337312 0.58461375 12 sp_2 -1.020567780 0.61989576
-#> 3243 0 0.15337312 0.58461375 14 sp_3 -1.020567780 0.61989576
-#> 3244 0 0.15337312 0.58461375 13 sp_4 -1.020567780 0.61989576
-#> 3245 1 0.15337312 0.58461375 20 sp_5 -1.020567780 0.61989576
-#> 3246 0 0.15337312 0.58461375 15 sp_6 -1.020567780 0.61989576
-#> 3247 0 0.15337312 0.58461375 8 sp_7 -1.020567780 0.61989576
-#> 3248 0 0.15337312 0.58461375 13 sp_8 -1.020567780 0.61989576
-#> 3249 1 0.15337312 0.58461375 7 sp_9 -1.020567780 0.61989576
-#> 3250 0 0.15337312 0.58461375 5 sp_10 -1.020567780 0.61989576
-#> 3251 0 0.15337312 0.58461375 8 sp_11 -1.020567780 0.61989576
-#> 3252 0 0.15337312 0.58461375 15 sp_12 -1.020567780 0.61989576
-#> 3253 0 0.15337312 0.58461375 14 sp_13 -1.020567780 0.61989576
-#> 3254 1 0.15337312 0.58461375 16 sp_14 -1.020567780 0.61989576
-#> 3255 0 0.15337312 0.58461375 1 sp_15 -1.020567780 0.61989576
-#> 3256 0 0.15337312 0.58461375 14 sp_16 -1.020567780 0.61989576
-#> 3257 0 0.15337312 0.58461375 17 sp_17 -1.020567780 0.61989576
-#> 3258 0 0.15337312 0.58461375 7 sp_18 -1.020567780 0.61989576
-#> 3259 0 0.15337312 0.58461375 7 sp_19 -1.020567780 0.61989576
-#> 3260 0 0.15337312 0.58461375 13 sp_20 -1.020567780 0.61989576
-#> 3261 0 0.15337312 0.58461375 15 sp_21 -1.020567780 0.61989576
-#> 3262 1 0.15337312 0.58461375 12 sp_22 -1.020567780 0.61989576
-#> 3263 0 0.15337312 0.58461375 14 sp_23 -1.020567780 0.61989576
-#> 3264 0 0.15337312 0.58461375 19 sp_24 -1.020567780 0.61989576
-#> 3265 0 0.15337312 0.58461375 19 sp_25 -1.020567780 0.61989576
-#> 3266 0 0.15337312 0.58461375 17 sp_26 -1.020567780 0.61989576
-#> 3267 0 0.15337312 0.58461375 9 sp_27 -1.020567780 0.61989576
-#> 3268 0 0.15337312 0.58461375 13 sp_28 -1.020567780 0.61989576
-#> 3269 0 0.15337312 0.58461375 14 sp_29 -1.020567780 0.61989576
-#> 3270 0 0.15337312 0.58461375 6 sp_30 -1.020567780 0.61989576
-#> 3361 0 -1.13813694 0.12385424 1 sp_1 0.704704540 2.00602552
-#> 3362 0 -1.13813694 0.12385424 16 sp_2 0.704704540 2.00602552
-#> 3363 0 -1.13813694 0.12385424 8 sp_3 0.704704540 2.00602552
-#> 3364 0 -1.13813694 0.12385424 5 sp_4 0.704704540 2.00602552
-#> 3365 0 -1.13813694 0.12385424 10 sp_5 0.704704540 2.00602552
-#> 3366 0 -1.13813694 0.12385424 9 sp_6 0.704704540 2.00602552
-#> 3367 0 -1.13813694 0.12385424 5 sp_7 0.704704540 2.00602552
-#> 3368 0 -1.13813694 0.12385424 14 sp_8 0.704704540 2.00602552
-#> 3369 0 -1.13813694 0.12385424 19 sp_9 0.704704540 2.00602552
-#> 3370 0 -1.13813694 0.12385424 1 sp_10 0.704704540 2.00602552
-#> 3371 0 -1.13813694 0.12385424 16 sp_11 0.704704540 2.00602552
-#> 3372 0 -1.13813694 0.12385424 6 sp_12 0.704704540 2.00602552
-#> 3373 0 -1.13813694 0.12385424 20 sp_13 0.704704540 2.00602552
-#> 3374 0 -1.13813694 0.12385424 8 sp_14 0.704704540 2.00602552
-#> 3375 0 -1.13813694 0.12385424 14 sp_15 0.704704540 2.00602552
-#> 3376 0 -1.13813694 0.12385424 14 sp_16 0.704704540 2.00602552
-#> 3377 0 -1.13813694 0.12385424 8 sp_17 0.704704540 2.00602552
-#> 3378 0 -1.13813694 0.12385424 11 sp_18 0.704704540 2.00602552
-#> 3379 0 -1.13813694 0.12385424 20 sp_19 0.704704540 2.00602552
-#> 3380 0 -1.13813694 0.12385424 5 sp_20 0.704704540 2.00602552
-#> 3381 0 -1.13813694 0.12385424 14 sp_21 0.704704540 2.00602552
-#> 3382 0 -1.13813694 0.12385424 1 sp_22 0.704704540 2.00602552
-#> 3383 0 -1.13813694 0.12385424 1 sp_23 0.704704540 2.00602552
-#> 3384 0 -1.13813694 0.12385424 5 sp_24 0.704704540 2.00602552
-#> 3385 0 -1.13813694 0.12385424 3 sp_25 0.704704540 2.00602552
-#> 3386 0 -1.13813694 0.12385424 4 sp_26 0.704704540 2.00602552
-#> 3387 0 -1.13813694 0.12385424 3 sp_27 0.704704540 2.00602552
-#> 3388 0 -1.13813694 0.12385424 14 sp_28 0.704704540 2.00602552
-#> 3389 0 -1.13813694 0.12385424 18 sp_29 0.704704540 2.00602552
-#> 3390 0 -1.13813694 0.12385424 10 sp_30 0.704704540 2.00602552
-#> 3481 1 1.25381492 0.21594157 12 sp_1 1.328751933 0.21194168
-#> 3482 1 1.25381492 0.21594157 16 sp_2 1.328751933 0.21194168
-#> 3483 0 1.25381492 0.21594157 3 sp_3 1.328751933 0.21194168
-#> 3484 0 1.25381492 0.21594157 12 sp_4 1.328751933 0.21194168
-#> 3485 0 1.25381492 0.21594157 5 sp_5 1.328751933 0.21194168
-#> 3486 0 1.25381492 0.21594157 13 sp_6 1.328751933 0.21194168
-#> 3487 0 1.25381492 0.21594157 8 sp_7 1.328751933 0.21194168
-#> 3488 1 1.25381492 0.21594157 17 sp_8 1.328751933 0.21194168
-#> 3489 0 1.25381492 0.21594157 5 sp_9 1.328751933 0.21194168
-#> 3490 0 1.25381492 0.21594157 19 sp_10 1.328751933 0.21194168
-#> 3491 0 1.25381492 0.21594157 6 sp_11 1.328751933 0.21194168
-#> 3492 1 1.25381492 0.21594157 2 sp_12 1.328751933 0.21194168
-#> 3493 1 1.25381492 0.21594157 17 sp_13 1.328751933 0.21194168
-#> 3494 1 1.25381492 0.21594157 17 sp_14 1.328751933 0.21194168
-#> 3495 0 1.25381492 0.21594157 8 sp_15 1.328751933 0.21194168
-#> 3496 0 1.25381492 0.21594157 19 sp_16 1.328751933 0.21194168
-#> 3497 1 1.25381492 0.21594157 18 sp_17 1.328751933 0.21194168
-#> 3498 0 1.25381492 0.21594157 19 sp_18 1.328751933 0.21194168
-#> 3499 1 1.25381492 0.21594157 5 sp_19 1.328751933 0.21194168
-#> 3500 0 1.25381492 0.21594157 14 sp_20 1.328751933 0.21194168
-#> 3501 1 1.25381492 0.21594157 12 sp_21 1.328751933 0.21194168
-#> 3502 0 1.25381492 0.21594157 1 sp_22 1.328751933 0.21194168
-#> 3503 1 1.25381492 0.21594157 16 sp_23 1.328751933 0.21194168
-#> 3504 0 1.25381492 0.21594157 18 sp_24 1.328751933 0.21194168
-#> 3505 1 1.25381492 0.21594157 20 sp_25 1.328751933 0.21194168
-#> 3506 0 1.25381492 0.21594157 7 sp_26 1.328751933 0.21194168
-#> 3507 1 1.25381492 0.21594157 5 sp_27 1.328751933 0.21194168
-#> 3508 0 1.25381492 0.21594157 10 sp_28 1.328751933 0.21194168
-#> 3509 0 1.25381492 0.21594157 4 sp_29 1.328751933 0.21194168
-#> 3510 0 1.25381492 0.21594157 8 sp_30 1.328751933 0.21194168
-#> 110 1 -0.56047565 0.42646422 7 sp_1 1.716649095 -2.35167507
-#> 210 0 -0.56047565 0.42646422 3 sp_2 1.716649095 -2.35167507
-#> 31 0 -0.56047565 0.42646422 15 sp_3 1.716649095 -2.35167507
-#> 41 0 -0.56047565 0.42646422 5 sp_4 1.716649095 -2.35167507
-#> 51 1 -0.56047565 0.42646422 8 sp_5 1.716649095 -2.35167507
-#> 61 0 -0.56047565 0.42646422 19 sp_6 1.716649095 -2.35167507
-#> 71 0 -0.56047565 0.42646422 10 sp_7 1.716649095 -2.35167507
-#> 81 0 -0.56047565 0.42646422 18 sp_8 1.716649095 -2.35167507
-#> 91 0 -0.56047565 0.42646422 10 sp_9 1.716649095 -2.35167507
-#> 101 0 -0.56047565 0.42646422 12 sp_10 1.716649095 -2.35167507
-#> 111 1 -0.56047565 0.42646422 2 sp_11 1.716649095 -2.35167507
-#> 1231 0 -0.56047565 0.42646422 10 sp_12 1.716649095 -2.35167507
-#> 1310 1 -0.56047565 0.42646422 12 sp_13 1.716649095 -2.35167507
-#> 1410 0 -0.56047565 0.42646422 20 sp_14 1.716649095 -2.35167507
-#> 151 0 -0.56047565 0.42646422 14 sp_15 1.716649095 -2.35167507
-#> 161 0 -0.56047565 0.42646422 17 sp_16 1.716649095 -2.35167507
-#> 171 1 -0.56047565 0.42646422 14 sp_17 1.716649095 -2.35167507
-#> 181 0 -0.56047565 0.42646422 3 sp_18 1.716649095 -2.35167507
-#> 191 0 -0.56047565 0.42646422 8 sp_19 1.716649095 -2.35167507
-#> 201 1 -0.56047565 0.42646422 14 sp_20 1.716649095 -2.35167507
-#> 211 0 -0.56047565 0.42646422 19 sp_21 1.716649095 -2.35167507
-#> 221 0 -0.56047565 0.42646422 15 sp_22 1.716649095 -2.35167507
-#> 231 0 -0.56047565 0.42646422 17 sp_23 1.716649095 -2.35167507
-#> 2431 1 -0.56047565 0.42646422 11 sp_24 1.716649095 -2.35167507
-#> 2510 0 -0.56047565 0.42646422 7 sp_25 1.716649095 -2.35167507
-#> 2610 0 -0.56047565 0.42646422 15 sp_26 1.716649095 -2.35167507
-#> 271 1 -0.56047565 0.42646422 6 sp_27 1.716649095 -2.35167507
-#> 281 0 -0.56047565 0.42646422 14 sp_28 1.716649095 -2.35167507
-#> 291 0 -0.56047565 0.42646422 7 sp_29 1.716649095 -2.35167507
-#> 301 0 -0.56047565 0.42646422 10 sp_30 1.716649095 -2.35167507
-#> 12110 0 -0.23017749 -0.29507148 5 sp_1 -0.859586190 1.32733753
-#> 12210 0 -0.23017749 -0.29507148 6 sp_2 -0.859586190 1.32733753
-#> 1232 0 -0.23017749 -0.29507148 16 sp_3 -0.859586190 1.32733753
-#> 1241 0 -0.23017749 -0.29507148 11 sp_4 -0.859586190 1.32733753
-#> 1251 0 -0.23017749 -0.29507148 4 sp_5 -0.859586190 1.32733753
-#> 1261 0 -0.23017749 -0.29507148 12 sp_6 -0.859586190 1.32733753
-#> 1271 0 -0.23017749 -0.29507148 14 sp_7 -0.859586190 1.32733753
-#> 1281 0 -0.23017749 -0.29507148 19 sp_8 -0.859586190 1.32733753
-#> 1291 0 -0.23017749 -0.29507148 7 sp_9 -0.859586190 1.32733753
-#> 1301 0 -0.23017749 -0.29507148 9 sp_10 -0.859586190 1.32733753
-#> 1311 0 -0.23017749 -0.29507148 7 sp_11 -0.859586190 1.32733753
-#> 13210 0 -0.23017749 -0.29507148 2 sp_12 -0.859586190 1.32733753
-#> 13310 0 -0.23017749 -0.29507148 16 sp_13 -0.859586190 1.32733753
-#> 13410 0 -0.23017749 -0.29507148 13 sp_14 -0.859586190 1.32733753
-#> 1351 0 -0.23017749 -0.29507148 19 sp_15 -0.859586190 1.32733753
-#> 1361 0 -0.23017749 -0.29507148 20 sp_16 -0.859586190 1.32733753
-#> 1371 0 -0.23017749 -0.29507148 15 sp_17 -0.859586190 1.32733753
-#> 1381 0 -0.23017749 -0.29507148 7 sp_18 -0.859586190 1.32733753
-#> 1391 0 -0.23017749 -0.29507148 4 sp_19 -0.859586190 1.32733753
-#> 1401 0 -0.23017749 -0.29507148 1 sp_20 -0.859586190 1.32733753
-#> 1411 0 -0.23017749 -0.29507148 8 sp_21 -0.859586190 1.32733753
-#> 1421 0 -0.23017749 -0.29507148 20 sp_22 -0.859586190 1.32733753
-#> 1431 0 -0.23017749 -0.29507148 16 sp_23 -0.859586190 1.32733753
-#> 14410 0 -0.23017749 -0.29507148 11 sp_24 -0.859586190 1.32733753
-#> 14510 0 -0.23017749 -0.29507148 16 sp_25 -0.859586190 1.32733753
-#> 14610 0 -0.23017749 -0.29507148 20 sp_26 -0.859586190 1.32733753
-#> 1471 0 -0.23017749 -0.29507148 8 sp_27 -0.859586190 1.32733753
-#> 1481 0 -0.23017749 -0.29507148 3 sp_28 -0.859586190 1.32733753
-#> 1491 0 -0.23017749 -0.29507148 4 sp_29 -0.859586190 1.32733753
-#> 1501 0 -0.23017749 -0.29507148 20 sp_30 -0.859586190 1.32733753
-#> 24110 0 1.55870831 0.89512566 12 sp_1 -1.013550294 -0.08577912
-#> 24210 1 1.55870831 0.89512566 17 sp_2 -1.013550294 -0.08577912
-#> 2432 0 1.55870831 0.89512566 10 sp_3 -1.013550294 -0.08577912
-#> 2441 1 1.55870831 0.89512566 20 sp_4 -1.013550294 -0.08577912
-#> 2451 0 1.55870831 0.89512566 11 sp_5 -1.013550294 -0.08577912
-#> 2461 0 1.55870831 0.89512566 8 sp_6 -1.013550294 -0.08577912
-#> 2471 0 1.55870831 0.89512566 14 sp_7 -1.013550294 -0.08577912
-#> 2481 0 1.55870831 0.89512566 13 sp_8 -1.013550294 -0.08577912
-#> 2491 0 1.55870831 0.89512566 2 sp_9 -1.013550294 -0.08577912
-#> 2501 1 1.55870831 0.89512566 11 sp_10 -1.013550294 -0.08577912
-#> 2511 0 1.55870831 0.89512566 13 sp_11 -1.013550294 -0.08577912
-#> 25210 0 1.55870831 0.89512566 14 sp_12 -1.013550294 -0.08577912
-#> 25310 0 1.55870831 0.89512566 6 sp_13 -1.013550294 -0.08577912
-#> 25410 0 1.55870831 0.89512566 8 sp_14 -1.013550294 -0.08577912
-#> 2551 0 1.55870831 0.89512566 12 sp_15 -1.013550294 -0.08577912
-#> 2561 1 1.55870831 0.89512566 4 sp_16 -1.013550294 -0.08577912
-#> 2571 0 1.55870831 0.89512566 13 sp_17 -1.013550294 -0.08577912
-#> 2581 0 1.55870831 0.89512566 14 sp_18 -1.013550294 -0.08577912
-#> 2591 0 1.55870831 0.89512566 16 sp_19 -1.013550294 -0.08577912
-#> 2601 0 1.55870831 0.89512566 1 sp_20 -1.013550294 -0.08577912
-#> 2611 0 1.55870831 0.89512566 8 sp_21 -1.013550294 -0.08577912
-#> 2621 0 1.55870831 0.89512566 8 sp_22 -1.013550294 -0.08577912
-#> 2631 0 1.55870831 0.89512566 10 sp_23 -1.013550294 -0.08577912
-#> 26410 0 1.55870831 0.89512566 8 sp_24 -1.013550294 -0.08577912
-#> 26510 0 1.55870831 0.89512566 18 sp_25 -1.013550294 -0.08577912
-#> 26610 0 1.55870831 0.89512566 9 sp_26 -1.013550294 -0.08577912
-#> 2671 0 1.55870831 0.89512566 7 sp_27 -1.013550294 -0.08577912
-#> 2681 0 1.55870831 0.89512566 7 sp_28 -1.013550294 -0.08577912
-#> 2691 1 1.55870831 0.89512566 10 sp_29 -1.013550294 -0.08577912
-#> 2701 0 1.55870831 0.89512566 11 sp_30 -1.013550294 -0.08577912
-#> 3611 0 0.07050839 0.87813349 1 sp_1 -0.220246237 -0.08670636
-#> 3621 0 0.07050839 0.87813349 19 sp_2 -0.220246237 -0.08670636
-#> 3631 0 0.07050839 0.87813349 10 sp_3 -0.220246237 -0.08670636
-#> 3641 0 0.07050839 0.87813349 13 sp_4 -0.220246237 -0.08670636
-#> 3651 1 0.07050839 0.87813349 11 sp_5 -0.220246237 -0.08670636
-#> 3661 0 0.07050839 0.87813349 11 sp_6 -0.220246237 -0.08670636
-#> 3671 0 0.07050839 0.87813349 20 sp_7 -0.220246237 -0.08670636
-#> 3681 0 0.07050839 0.87813349 7 sp_8 -0.220246237 -0.08670636
-#> 3691 0 0.07050839 0.87813349 20 sp_9 -0.220246237 -0.08670636
-#> 3701 0 0.07050839 0.87813349 9 sp_10 -0.220246237 -0.08670636
-#> 3711 0 0.07050839 0.87813349 9 sp_11 -0.220246237 -0.08670636
-#> 3721 0 0.07050839 0.87813349 5 sp_12 -0.220246237 -0.08670636
-#> 3731 0 0.07050839 0.87813349 14 sp_13 -0.220246237 -0.08670636
-#> 3741 0 0.07050839 0.87813349 14 sp_14 -0.220246237 -0.08670636
-#> 3751 0 0.07050839 0.87813349 6 sp_15 -0.220246237 -0.08670636
-#> 3761 0 0.07050839 0.87813349 1 sp_16 -0.220246237 -0.08670636
-#> 3771 1 0.07050839 0.87813349 10 sp_17 -0.220246237 -0.08670636
-#> 3781 0 0.07050839 0.87813349 17 sp_18 -0.220246237 -0.08670636
-#> 3791 1 0.07050839 0.87813349 17 sp_19 -0.220246237 -0.08670636
-#> 3801 0 0.07050839 0.87813349 7 sp_20 -0.220246237 -0.08670636
-#> 3811 0 0.07050839 0.87813349 9 sp_21 -0.220246237 -0.08670636
-#> 3821 0 0.07050839 0.87813349 20 sp_22 -0.220246237 -0.08670636
-#> 3831 0 0.07050839 0.87813349 6 sp_23 -0.220246237 -0.08670636
-#> 3841 0 0.07050839 0.87813349 18 sp_24 -0.220246237 -0.08670636
-#> 3851 0 0.07050839 0.87813349 17 sp_25 -0.220246237 -0.08670636
-#> 3861 0 0.07050839 0.87813349 5 sp_26 -0.220246237 -0.08670636
-#> 3871 0 0.07050839 0.87813349 20 sp_27 -0.220246237 -0.08670636
-#> 3881 0 0.07050839 0.87813349 3 sp_28 -0.220246237 -0.08670636
-#> 3891 0 0.07050839 0.87813349 14 sp_29 -0.220246237 -0.08670636
-#> 3901 0 0.07050839 0.87813349 1 sp_30 -0.220246237 -0.08670636
-#> 4811 0 0.12928774 0.82158108 2 sp_1 0.158823107 -0.25053832
-#> 4821 0 0.12928774 0.82158108 4 sp_2 0.158823107 -0.25053832
-#> 4831 0 0.12928774 0.82158108 10 sp_3 0.158823107 -0.25053832
-#> 4841 0 0.12928774 0.82158108 1 sp_4 0.158823107 -0.25053832
-#> 4851 0 0.12928774 0.82158108 5 sp_5 0.158823107 -0.25053832
-#> 4861 0 0.12928774 0.82158108 8 sp_6 0.158823107 -0.25053832
-#> 4871 0 0.12928774 0.82158108 13 sp_7 0.158823107 -0.25053832
-#> 4881 0 0.12928774 0.82158108 18 sp_8 0.158823107 -0.25053832
-#> 4891 1 0.12928774 0.82158108 10 sp_9 0.158823107 -0.25053832
-#> 4901 0 0.12928774 0.82158108 6 sp_10 0.158823107 -0.25053832
-#> 4911 0 0.12928774 0.82158108 7 sp_11 0.158823107 -0.25053832
-#> 4921 0 0.12928774 0.82158108 9 sp_12 0.158823107 -0.25053832
-#> 4931 0 0.12928774 0.82158108 16 sp_13 0.158823107 -0.25053832
-#> 4941 1 0.12928774 0.82158108 17 sp_14 0.158823107 -0.25053832
-#> 4951 0 0.12928774 0.82158108 13 sp_15 0.158823107 -0.25053832
-#> 4961 0 0.12928774 0.82158108 8 sp_16 0.158823107 -0.25053832
-#> 4971 0 0.12928774 0.82158108 7 sp_17 0.158823107 -0.25053832
-#> 4981 0 0.12928774 0.82158108 20 sp_18 0.158823107 -0.25053832
-#> 4991 0 0.12928774 0.82158108 18 sp_19 0.158823107 -0.25053832
-#> 5001 0 0.12928774 0.82158108 17 sp_20 0.158823107 -0.25053832
-#> 5011 0 0.12928774 0.82158108 1 sp_21 0.158823107 -0.25053832
-#> 5021 0 0.12928774 0.82158108 2 sp_22 0.158823107 -0.25053832
-#> 5031 0 0.12928774 0.82158108 17 sp_23 0.158823107 -0.25053832
-#> 5041 0 0.12928774 0.82158108 2 sp_24 0.158823107 -0.25053832
-#> 5051 0 0.12928774 0.82158108 13 sp_25 0.158823107 -0.25053832
-#> 5061 0 0.12928774 0.82158108 17 sp_26 0.158823107 -0.25053832
-#> 5071 0 0.12928774 0.82158108 3 sp_27 0.158823107 -0.25053832
-#> 5081 0 0.12928774 0.82158108 18 sp_28 0.158823107 -0.25053832
-#> 5091 1 0.12928774 0.82158108 2 sp_29 0.158823107 -0.25053832
-#> 5101 0 0.12928774 0.82158108 5 sp_30 0.158823107 -0.25053832
-#> 6011 0 1.71506499 0.68864025 12 sp_1 -0.869274055 0.39534471
-#> 6021 0 1.71506499 0.68864025 13 sp_2 -0.869274055 0.39534471
-#> 6031 0 1.71506499 0.68864025 10 sp_3 -0.869274055 0.39534471
-#> 6041 0 1.71506499 0.68864025 6 sp_4 -0.869274055 0.39534471
-#> 6051 0 1.71506499 0.68864025 10 sp_5 -0.869274055 0.39534471
-#> 6061 0 1.71506499 0.68864025 10 sp_6 -0.869274055 0.39534471
-#> 6071 0 1.71506499 0.68864025 6 sp_7 -0.869274055 0.39534471
-#> 6081 1 1.71506499 0.68864025 16 sp_8 -0.869274055 0.39534471
-#> 6091 0 1.71506499 0.68864025 16 sp_9 -0.869274055 0.39534471
-#> 6101 1 1.71506499 0.68864025 3 sp_10 -0.869274055 0.39534471
-#> 6111 0 1.71506499 0.68864025 4 sp_11 -0.869274055 0.39534471
-#> 6121 0 1.71506499 0.68864025 3 sp_12 -0.869274055 0.39534471
-#> 6131 0 1.71506499 0.68864025 3 sp_13 -0.869274055 0.39534471
-#> 6141 0 1.71506499 0.68864025 16 sp_14 -0.869274055 0.39534471
-#> 6151 1 1.71506499 0.68864025 2 sp_15 -0.869274055 0.39534471
-#> 6161 0 1.71506499 0.68864025 15 sp_16 -0.869274055 0.39534471
-#> 6171 0 1.71506499 0.68864025 3 sp_17 -0.869274055 0.39534471
-#> 6181 0 1.71506499 0.68864025 9 sp_18 -0.869274055 0.39534471
-#> 6191 0 1.71506499 0.68864025 7 sp_19 -0.869274055 0.39534471
-#> 6201 0 1.71506499 0.68864025 9 sp_20 -0.869274055 0.39534471
-#> 6211 0 1.71506499 0.68864025 4 sp_21 -0.869274055 0.39534471
-#> 6221 0 1.71506499 0.68864025 2 sp_22 -0.869274055 0.39534471
-#> 6231 0 1.71506499 0.68864025 12 sp_23 -0.869274055 0.39534471
-#> 6241 0 1.71506499 0.68864025 9 sp_24 -0.869274055 0.39534471
-#> 6251 0 1.71506499 0.68864025 11 sp_25 -0.869274055 0.39534471
-#> 6261 0 1.71506499 0.68864025 7 sp_26 -0.869274055 0.39534471
-#> 6271 0 1.71506499 0.68864025 13 sp_27 -0.869274055 0.39534471
-#> 6281 1 1.71506499 0.68864025 5 sp_28 -0.869274055 0.39534471
-#> 6291 0 1.71506499 0.68864025 11 sp_29 -0.869274055 0.39534471
-#> 6301 0 1.71506499 0.68864025 1 sp_30 -0.869274055 0.39534471
-#> 7211 0 0.46091621 0.55391765 19 sp_1 -0.730637689 1.23693746
-#> 7221 1 0.46091621 0.55391765 12 sp_2 -0.730637689 1.23693746
-#> 7231 0 0.46091621 0.55391765 2 sp_3 -0.730637689 1.23693746
-#> 7241 1 0.46091621 0.55391765 17 sp_4 -0.730637689 1.23693746
-#> 7251 0 0.46091621 0.55391765 12 sp_5 -0.730637689 1.23693746
-#> 7261 0 0.46091621 0.55391765 3 sp_6 -0.730637689 1.23693746
-#> 7271 0 0.46091621 0.55391765 18 sp_7 -0.730637689 1.23693746
-#> 7281 0 0.46091621 0.55391765 15 sp_8 -0.730637689 1.23693746
-#> 7291 0 0.46091621 0.55391765 3 sp_9 -0.730637689 1.23693746
-#> 7301 0 0.46091621 0.55391765 19 sp_10 -0.730637689 1.23693746
-#> 7311 0 0.46091621 0.55391765 18 sp_11 -0.730637689 1.23693746
-#> 7321 0 0.46091621 0.55391765 17 sp_12 -0.730637689 1.23693746
-#> 7331 0 0.46091621 0.55391765 6 sp_13 -0.730637689 1.23693746
-#> 7341 0 0.46091621 0.55391765 10 sp_14 -0.730637689 1.23693746
-#> 7351 0 0.46091621 0.55391765 8 sp_15 -0.730637689 1.23693746
-#> 7361 0 0.46091621 0.55391765 10 sp_16 -0.730637689 1.23693746
-#> 7371 0 0.46091621 0.55391765 13 sp_17 -0.730637689 1.23693746
-#> 7381 0 0.46091621 0.55391765 20 sp_18 -0.730637689 1.23693746
-#> 7391 0 0.46091621 0.55391765 6 sp_19 -0.730637689 1.23693746
-#> 7401 0 0.46091621 0.55391765 20 sp_20 -0.730637689 1.23693746
-#> 7411 1 0.46091621 0.55391765 20 sp_21 -0.730637689 1.23693746
-#> 7421 0 0.46091621 0.55391765 9 sp_22 -0.730637689 1.23693746
-#> 7431 0 0.46091621 0.55391765 16 sp_23 -0.730637689 1.23693746
-#> 7441 0 0.46091621 0.55391765 8 sp_24 -0.730637689 1.23693746
-#> 7451 0 0.46091621 0.55391765 7 sp_25 -0.730637689 1.23693746
-#> 7461 0 0.46091621 0.55391765 10 sp_26 -0.730637689 1.23693746
-#> 7471 1 0.46091621 0.55391765 17 sp_27 -0.730637689 1.23693746
-#> 7481 0 0.46091621 0.55391765 18 sp_28 -0.730637689 1.23693746
-#> 7491 0 0.46091621 0.55391765 8 sp_29 -0.730637689 1.23693746
-#> 7501 0 0.46091621 0.55391765 19 sp_30 -0.730637689 1.23693746
-#> 8411 0 -1.26506123 -0.06191171 10 sp_1 1.111633173 0.14385911
-#> 8421 0 -1.26506123 -0.06191171 11 sp_2 1.111633173 0.14385911
-#> 8431 0 -1.26506123 -0.06191171 17 sp_3 1.111633173 0.14385911
-#> 8441 0 -1.26506123 -0.06191171 12 sp_4 1.111633173 0.14385911
-#> 8451 0 -1.26506123 -0.06191171 2 sp_5 1.111633173 0.14385911
-#> 8461 0 -1.26506123 -0.06191171 19 sp_6 1.111633173 0.14385911
-#> 8471 0 -1.26506123 -0.06191171 13 sp_7 1.111633173 0.14385911
-#> 8481 0 -1.26506123 -0.06191171 13 sp_8 1.111633173 0.14385911
-#> 8491 0 -1.26506123 -0.06191171 19 sp_9 1.111633173 0.14385911
-#> 8501 1 -1.26506123 -0.06191171 10 sp_10 1.111633173 0.14385911
-#> 8511 0 -1.26506123 -0.06191171 16 sp_11 1.111633173 0.14385911
-#> 8521 0 -1.26506123 -0.06191171 5 sp_12 1.111633173 0.14385911
-#> 8531 0 -1.26506123 -0.06191171 4 sp_13 1.111633173 0.14385911
-#> 8541 0 -1.26506123 -0.06191171 18 sp_14 1.111633173 0.14385911
-#> 8551 0 -1.26506123 -0.06191171 1 sp_15 1.111633173 0.14385911
-#> 8561 0 -1.26506123 -0.06191171 16 sp_16 1.111633173 0.14385911
-#> 8571 0 -1.26506123 -0.06191171 17 sp_17 1.111633173 0.14385911
-#> 8581 0 -1.26506123 -0.06191171 12 sp_18 1.111633173 0.14385911
-#> 8591 1 -1.26506123 -0.06191171 2 sp_19 1.111633173 0.14385911
-#> 8601 0 -1.26506123 -0.06191171 18 sp_20 1.111633173 0.14385911
-#> 8611 0 -1.26506123 -0.06191171 12 sp_21 1.111633173 0.14385911
-#> 8621 0 -1.26506123 -0.06191171 15 sp_22 1.111633173 0.14385911
-#> 8631 0 -1.26506123 -0.06191171 19 sp_23 1.111633173 0.14385911
-#> 8641 0 -1.26506123 -0.06191171 6 sp_24 1.111633173 0.14385911
-#> 8651 0 -1.26506123 -0.06191171 16 sp_25 1.111633173 0.14385911
-#> 8661 0 -1.26506123 -0.06191171 15 sp_26 1.111633173 0.14385911
-#> 8671 0 -1.26506123 -0.06191171 19 sp_27 1.111633173 0.14385911
-#> 8681 0 -1.26506123 -0.06191171 3 sp_28 1.111633173 0.14385911
-#> 8691 0 -1.26506123 -0.06191171 14 sp_29 1.111633173 0.14385911
-#> 8701 0 -1.26506123 -0.06191171 1 sp_30 1.111633173 0.14385911
-#> 9611 1 -0.68685285 -0.30596266 1 sp_1 -0.166381366 -1.44944857
-#> 9621 0 -0.68685285 -0.30596266 16 sp_2 -0.166381366 -1.44944857
-#> 9631 0 -0.68685285 -0.30596266 11 sp_3 -0.166381366 -1.44944857
-#> 9641 0 -0.68685285 -0.30596266 4 sp_4 -0.166381366 -1.44944857
-#> 9651 1 -0.68685285 -0.30596266 12 sp_5 -0.166381366 -1.44944857
-#> 9661 1 -0.68685285 -0.30596266 13 sp_6 -0.166381366 -1.44944857
-#> 9671 0 -0.68685285 -0.30596266 10 sp_7 -0.166381366 -1.44944857
-#> 9681 0 -0.68685285 -0.30596266 10 sp_8 -0.166381366 -1.44944857
-#> 9691 1 -0.68685285 -0.30596266 7 sp_9 -0.166381366 -1.44944857
-#> 9701 0 -0.68685285 -0.30596266 18 sp_10 -0.166381366 -1.44944857
-#> 9711 0 -0.68685285 -0.30596266 17 sp_11 -0.166381366 -1.44944857
-#> 9721 0 -0.68685285 -0.30596266 20 sp_12 -0.166381366 -1.44944857
-#> 9731 1 -0.68685285 -0.30596266 9 sp_13 -0.166381366 -1.44944857
-#> 9741 0 -0.68685285 -0.30596266 11 sp_14 -0.166381366 -1.44944857
-#> 9751 1 -0.68685285 -0.30596266 12 sp_15 -0.166381366 -1.44944857
-#> 9761 0 -0.68685285 -0.30596266 8 sp_16 -0.166381366 -1.44944857
-#> 9771 0 -0.68685285 -0.30596266 18 sp_17 -0.166381366 -1.44944857
-#> 9781 0 -0.68685285 -0.30596266 5 sp_18 -0.166381366 -1.44944857
-#> 9791 0 -0.68685285 -0.30596266 18 sp_19 -0.166381366 -1.44944857
-#> 9801 0 -0.68685285 -0.30596266 6 sp_20 -0.166381366 -1.44944857
-#> 9811 0 -0.68685285 -0.30596266 10 sp_21 -0.166381366 -1.44944857
-#> 9821 0 -0.68685285 -0.30596266 9 sp_22 -0.166381366 -1.44944857
-#> 9831 0 -0.68685285 -0.30596266 11 sp_23 -0.166381366 -1.44944857
-#> 9841 0 -0.68685285 -0.30596266 6 sp_24 -0.166381366 -1.44944857
-#> 9851 0 -0.68685285 -0.30596266 12 sp_25 -0.166381366 -1.44944857
-#> 9861 0 -0.68685285 -0.30596266 19 sp_26 -0.166381366 -1.44944857
-#> 9871 0 -0.68685285 -0.30596266 4 sp_27 -0.166381366 -1.44944857
-#> 9881 0 -0.68685285 -0.30596266 3 sp_28 -0.166381366 -1.44944857
-#> 9891 0 -0.68685285 -0.30596266 14 sp_29 -0.166381366 -1.44944857
-#> 9901 0 -0.68685285 -0.30596266 8 sp_30 -0.166381366 -1.44944857
-#> 10811 0 -0.44566197 -0.38047100 6 sp_1 0.967695272 0.26986716
-#> 10821 0 -0.44566197 -0.38047100 4 sp_2 0.967695272 0.26986716
-#> 10831 1 -0.44566197 -0.38047100 10 sp_3 0.967695272 0.26986716
-#> 10841 0 -0.44566197 -0.38047100 16 sp_4 0.967695272 0.26986716
-#> 10851 0 -0.44566197 -0.38047100 16 sp_5 0.967695272 0.26986716
-#> 10861 0 -0.44566197 -0.38047100 20 sp_6 0.967695272 0.26986716
-#> 10871 1 -0.44566197 -0.38047100 10 sp_7 0.967695272 0.26986716
-#> 10881 0 -0.44566197 -0.38047100 6 sp_8 0.967695272 0.26986716
-#> 10891 0 -0.44566197 -0.38047100 19 sp_9 0.967695272 0.26986716
-#> 10901 0 -0.44566197 -0.38047100 4 sp_10 0.967695272 0.26986716
-#> 10911 0 -0.44566197 -0.38047100 9 sp_11 0.967695272 0.26986716
-#> 10921 0 -0.44566197 -0.38047100 4 sp_12 0.967695272 0.26986716
-#> 10931 0 -0.44566197 -0.38047100 15 sp_13 0.967695272 0.26986716
-#> 10941 1 -0.44566197 -0.38047100 20 sp_14 0.967695272 0.26986716
-#> 10951 0 -0.44566197 -0.38047100 17 sp_15 0.967695272 0.26986716
-#> 10961 0 -0.44566197 -0.38047100 7 sp_16 0.967695272 0.26986716
-#> 10971 0 -0.44566197 -0.38047100 15 sp_17 0.967695272 0.26986716
-#> 10981 0 -0.44566197 -0.38047100 5 sp_18 0.967695272 0.26986716
-#> 10991 0 -0.44566197 -0.38047100 14 sp_19 0.967695272 0.26986716
-#> 11001 0 -0.44566197 -0.38047100 15 sp_20 0.967695272 0.26986716
-#> 11011 1 -0.44566197 -0.38047100 15 sp_21 0.967695272 0.26986716
-#> 11021 0 -0.44566197 -0.38047100 16 sp_22 0.967695272 0.26986716
-#> 11031 0 -0.44566197 -0.38047100 19 sp_23 0.967695272 0.26986716
-#> 11041 0 -0.44566197 -0.38047100 8 sp_24 0.967695272 0.26986716
-#> 11051 0 -0.44566197 -0.38047100 5 sp_25 0.967695272 0.26986716
-#> 11061 0 -0.44566197 -0.38047100 7 sp_26 0.967695272 0.26986716
-#> 11071 0 -0.44566197 -0.38047100 20 sp_27 0.967695272 0.26986716
-#> 11081 0 -0.44566197 -0.38047100 16 sp_28 0.967695272 0.26986716
-#> 11091 0 -0.44566197 -0.38047100 16 sp_29 0.967695272 0.26986716
-#> 11101 0 -0.44566197 -0.38047100 9 sp_30 0.967695272 0.26986716
-#> 12011 0 1.22408180 -0.69470698 11 sp_1 -0.498319395 1.33868649
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-#> 12031 0 1.22408180 -0.69470698 19 sp_3 -0.498319395 1.33868649
-#> 12041 0 1.22408180 -0.69470698 10 sp_4 -0.498319395 1.33868649
-#> 12051 0 1.22408180 -0.69470698 2 sp_5 -0.498319395 1.33868649
-#> 12061 0 1.22408180 -0.69470698 6 sp_6 -0.498319395 1.33868649
-#> 12071 0 1.22408180 -0.69470698 20 sp_7 -0.498319395 1.33868649
-#> 12081 0 1.22408180 -0.69470698 14 sp_8 -0.498319395 1.33868649
-#> 12091 0 1.22408180 -0.69470698 14 sp_9 -0.498319395 1.33868649
-#> 12101 0 1.22408180 -0.69470698 6 sp_10 -0.498319395 1.33868649
-#> 12111 0 1.22408180 -0.69470698 18 sp_11 -0.498319395 1.33868649
-#> 12121 0 1.22408180 -0.69470698 2 sp_12 -0.498319395 1.33868649
-#> 12131 0 1.22408180 -0.69470698 8 sp_13 -0.498319395 1.33868649
-#> 12141 0 1.22408180 -0.69470698 11 sp_14 -0.498319395 1.33868649
-#> 12151 0 1.22408180 -0.69470698 7 sp_15 -0.498319395 1.33868649
-#> 12161 0 1.22408180 -0.69470698 19 sp_16 -0.498319395 1.33868649
-#> 12171 0 1.22408180 -0.69470698 8 sp_17 -0.498319395 1.33868649
-#> 12181 1 1.22408180 -0.69470698 10 sp_18 -0.498319395 1.33868649
-#> 12191 0 1.22408180 -0.69470698 5 sp_19 -0.498319395 1.33868649
-#> 12201 0 1.22408180 -0.69470698 17 sp_20 -0.498319395 1.33868649
-#> 12211 1 1.22408180 -0.69470698 6 sp_21 -0.498319395 1.33868649
-#> 12221 0 1.22408180 -0.69470698 8 sp_22 -0.498319395 1.33868649
-#> 12231 1 1.22408180 -0.69470698 20 sp_23 -0.498319395 1.33868649
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-#> 12251 0 1.22408180 -0.69470698 15 sp_25 -0.498319395 1.33868649
-#> 12261 1 1.22408180 -0.69470698 17 sp_26 -0.498319395 1.33868649
-#> 12271 0 1.22408180 -0.69470698 3 sp_27 -0.498319395 1.33868649
-#> 12281 0 1.22408180 -0.69470698 15 sp_28 -0.498319395 1.33868649
-#> 12291 1 1.22408180 -0.69470698 20 sp_29 -0.498319395 1.33868649
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-#> 13221 1 0.35981383 -0.20791728 11 sp_2 0.926885841 1.61114313
-#> 13231 0 0.35981383 -0.20791728 15 sp_3 0.926885841 1.61114313
-#> 13241 0 0.35981383 -0.20791728 20 sp_4 0.926885841 1.61114313
-#> 13251 0 0.35981383 -0.20791728 2 sp_5 0.926885841 1.61114313
-#> 13261 0 0.35981383 -0.20791728 16 sp_6 0.926885841 1.61114313
-#> 13271 0 0.35981383 -0.20791728 19 sp_7 0.926885841 1.61114313
-#> 13281 0 0.35981383 -0.20791728 10 sp_8 0.926885841 1.61114313
-#> 13291 0 0.35981383 -0.20791728 19 sp_9 0.926885841 1.61114313
-#> 13301 0 0.35981383 -0.20791728 17 sp_10 0.926885841 1.61114313
-#> 13311 0 0.35981383 -0.20791728 7 sp_11 0.926885841 1.61114313
-#> 13321 0 0.35981383 -0.20791728 6 sp_12 0.926885841 1.61114313
-#> 13331 0 0.35981383 -0.20791728 12 sp_13 0.926885841 1.61114313
-#> 13341 0 0.35981383 -0.20791728 4 sp_14 0.926885841 1.61114313
-#> 13351 0 0.35981383 -0.20791728 19 sp_15 0.926885841 1.61114313
-#> 13361 0 0.35981383 -0.20791728 2 sp_16 0.926885841 1.61114313
-#> 13371 0 0.35981383 -0.20791728 4 sp_17 0.926885841 1.61114313
-#> 13381 1 0.35981383 -0.20791728 11 sp_18 0.926885841 1.61114313
-#> 13391 0 0.35981383 -0.20791728 1 sp_19 0.926885841 1.61114313
-#> 13401 0 0.35981383 -0.20791728 19 sp_20 0.926885841 1.61114313
-#> 13411 1 0.35981383 -0.20791728 18 sp_21 0.926885841 1.61114313
-#> 13421 0 0.35981383 -0.20791728 16 sp_22 0.926885841 1.61114313
-#> 13431 1 0.35981383 -0.20791728 3 sp_23 0.926885841 1.61114313
-#> 13441 0 0.35981383 -0.20791728 1 sp_24 0.926885841 1.61114313
-#> 13451 0 0.35981383 -0.20791728 2 sp_25 0.926885841 1.61114313
-#> 13461 0 0.35981383 -0.20791728 2 sp_26 0.926885841 1.61114313
-#> 13471 0 0.35981383 -0.20791728 8 sp_27 0.926885841 1.61114313
-#> 13481 0 0.35981383 -0.20791728 20 sp_28 0.926885841 1.61114313
-#> 13491 0 0.35981383 -0.20791728 14 sp_29 0.926885841 1.61114313
-#> 13501 0 0.35981383 -0.20791728 13 sp_30 0.926885841 1.61114313
-#> 14411 1 0.40077145 -1.26539635 7 sp_1 0.081143100 -0.28723019
-#> 14421 0 0.40077145 -1.26539635 8 sp_2 0.081143100 -0.28723019
-#> 14431 0 0.40077145 -1.26539635 3 sp_3 0.081143100 -0.28723019
-#> 14441 0 0.40077145 -1.26539635 16 sp_4 0.081143100 -0.28723019
-#> 14451 0 0.40077145 -1.26539635 1 sp_5 0.081143100 -0.28723019
-#> 14461 1 0.40077145 -1.26539635 12 sp_6 0.081143100 -0.28723019
-#> 14471 1 0.40077145 -1.26539635 18 sp_7 0.081143100 -0.28723019
-#> 14481 0 0.40077145 -1.26539635 14 sp_8 0.081143100 -0.28723019
-#> 14491 1 0.40077145 -1.26539635 8 sp_9 0.081143100 -0.28723019
-#> 14501 1 0.40077145 -1.26539635 5 sp_10 0.081143100 -0.28723019
-#> 14511 1 0.40077145 -1.26539635 17 sp_11 0.081143100 -0.28723019
-#> 14521 0 0.40077145 -1.26539635 11 sp_12 0.081143100 -0.28723019
-#> 14531 0 0.40077145 -1.26539635 4 sp_13 0.081143100 -0.28723019
-#> 14541 1 0.40077145 -1.26539635 13 sp_14 0.081143100 -0.28723019
-#> 14551 1 0.40077145 -1.26539635 8 sp_15 0.081143100 -0.28723019
-#> 14561 0 0.40077145 -1.26539635 15 sp_16 0.081143100 -0.28723019
-#> 14571 1 0.40077145 -1.26539635 4 sp_17 0.081143100 -0.28723019
-#> 14581 0 0.40077145 -1.26539635 13 sp_18 0.081143100 -0.28723019
-#> 14591 0 0.40077145 -1.26539635 3 sp_19 0.081143100 -0.28723019
-#> 14601 1 0.40077145 -1.26539635 7 sp_20 0.081143100 -0.28723019
-#> 14611 0 0.40077145 -1.26539635 1 sp_21 0.081143100 -0.28723019
-#> 14621 0 0.40077145 -1.26539635 6 sp_22 0.081143100 -0.28723019
-#> 14631 1 0.40077145 -1.26539635 13 sp_23 0.081143100 -0.28723019
-#> 14641 1 0.40077145 -1.26539635 17 sp_24 0.081143100 -0.28723019
-#> 14651 0 0.40077145 -1.26539635 6 sp_25 0.081143100 -0.28723019
-#> 14661 1 0.40077145 -1.26539635 10 sp_26 0.081143100 -0.28723019
-#> 14671 0 0.40077145 -1.26539635 13 sp_27 0.081143100 -0.28723019
-#> 14681 0 0.40077145 -1.26539635 6 sp_28 0.081143100 -0.28723019
-#> 14691 1 0.40077145 -1.26539635 9 sp_29 0.081143100 -0.28723019
-#> 14701 0 0.40077145 -1.26539635 8 sp_30 0.081143100 -0.28723019
-#> 15611 0 0.11068272 2.16895597 1 sp_1 -0.114458510 0.94373342
-#> 15621 0 0.11068272 2.16895597 16 sp_2 -0.114458510 0.94373342
-#> 15631 0 0.11068272 2.16895597 2 sp_3 -0.114458510 0.94373342
-#> 15641 0 0.11068272 2.16895597 8 sp_4 -0.114458510 0.94373342
-#> 15651 0 0.11068272 2.16895597 14 sp_5 -0.114458510 0.94373342
-#> 15661 0 0.11068272 2.16895597 12 sp_6 -0.114458510 0.94373342
-#> 15671 0 0.11068272 2.16895597 8 sp_7 -0.114458510 0.94373342
-#> 15681 0 0.11068272 2.16895597 9 sp_8 -0.114458510 0.94373342
-#> 15691 0 0.11068272 2.16895597 8 sp_9 -0.114458510 0.94373342
-#> 15701 0 0.11068272 2.16895597 9 sp_10 -0.114458510 0.94373342
-#> 15711 0 0.11068272 2.16895597 20 sp_11 -0.114458510 0.94373342
-#> 15721 0 0.11068272 2.16895597 1 sp_12 -0.114458510 0.94373342
-#> 15731 0 0.11068272 2.16895597 3 sp_13 -0.114458510 0.94373342
-#> 15741 0 0.11068272 2.16895597 8 sp_14 -0.114458510 0.94373342
-#> 15751 0 0.11068272 2.16895597 2 sp_15 -0.114458510 0.94373342
-#> 15761 0 0.11068272 2.16895597 1 sp_16 -0.114458510 0.94373342
-#> 15771 0 0.11068272 2.16895597 9 sp_17 -0.114458510 0.94373342
-#> 15781 0 0.11068272 2.16895597 7 sp_18 -0.114458510 0.94373342
-#> 15791 0 0.11068272 2.16895597 13 sp_19 -0.114458510 0.94373342
-#> 15801 0 0.11068272 2.16895597 20 sp_20 -0.114458510 0.94373342
-#> 15811 0 0.11068272 2.16895597 14 sp_21 -0.114458510 0.94373342
-#> 15821 0 0.11068272 2.16895597 16 sp_22 -0.114458510 0.94373342
-#> 15831 0 0.11068272 2.16895597 7 sp_23 -0.114458510 0.94373342
-#> 15841 0 0.11068272 2.16895597 4 sp_24 -0.114458510 0.94373342
-#> 15851 0 0.11068272 2.16895597 13 sp_25 -0.114458510 0.94373342
-#> 15861 0 0.11068272 2.16895597 12 sp_26 -0.114458510 0.94373342
-#> 15871 0 0.11068272 2.16895597 13 sp_27 -0.114458510 0.94373342
-#> 15881 0 0.11068272 2.16895597 20 sp_28 -0.114458510 0.94373342
-#> 15891 0 0.11068272 2.16895597 10 sp_29 -0.114458510 0.94373342
-#> 15901 0 0.11068272 2.16895597 9 sp_30 -0.114458510 0.94373342
-#> 16811 0 -0.55584113 1.20796200 12 sp_1 -1.864998020 -1.12347081
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-#> 16831 0 -0.55584113 1.20796200 7 sp_3 -1.864998020 -1.12347081
-#> 16841 0 -0.55584113 1.20796200 15 sp_4 -1.864998020 -1.12347081
-#> 16851 0 -0.55584113 1.20796200 19 sp_5 -1.864998020 -1.12347081
-#> 16861 0 -0.55584113 1.20796200 17 sp_6 -1.864998020 -1.12347081
-#> 16871 0 -0.55584113 1.20796200 11 sp_7 -1.864998020 -1.12347081
-#> 16881 0 -0.55584113 1.20796200 7 sp_8 -1.864998020 -1.12347081
-#> 16891 0 -0.55584113 1.20796200 19 sp_9 -1.864998020 -1.12347081
-#> 16901 0 -0.55584113 1.20796200 3 sp_10 -1.864998020 -1.12347081
-#> 16911 0 -0.55584113 1.20796200 6 sp_11 -1.864998020 -1.12347081
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-#> 16941 1 -0.55584113 1.20796200 10 sp_14 -1.864998020 -1.12347081
-#> 16951 0 -0.55584113 1.20796200 17 sp_15 -1.864998020 -1.12347081
-#> 16961 0 -0.55584113 1.20796200 16 sp_16 -1.864998020 -1.12347081
-#> 16971 0 -0.55584113 1.20796200 8 sp_17 -1.864998020 -1.12347081
-#> 16981 0 -0.55584113 1.20796200 3 sp_18 -1.864998020 -1.12347081
-#> 16991 0 -0.55584113 1.20796200 12 sp_19 -1.864998020 -1.12347081
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-#> 17021 0 -0.55584113 1.20796200 14 sp_22 -1.864998020 -1.12347081
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-#> 17071 0 -0.55584113 1.20796200 14 sp_27 -1.864998020 -1.12347081
-#> 17081 0 -0.55584113 1.20796200 19 sp_28 -1.864998020 -1.12347081
-#> 17091 0 -0.55584113 1.20796200 5 sp_29 -1.864998020 -1.12347081
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-#> 19231 0 0.49785048 -0.40288484 9 sp_3 0.710841370 0.55646477
-#> 19241 0 0.49785048 -0.40288484 4 sp_4 0.710841370 0.55646477
-#> 19251 1 0.49785048 -0.40288484 3 sp_5 0.710841370 0.55646477
-#> 19261 1 0.49785048 -0.40288484 7 sp_6 0.710841370 0.55646477
-#> 19271 0 0.49785048 -0.40288484 4 sp_7 0.710841370 0.55646477
-#> 19281 0 0.49785048 -0.40288484 8 sp_8 0.710841370 0.55646477
-#> 19291 0 0.49785048 -0.40288484 5 sp_9 0.710841370 0.55646477
-#> 19301 0 0.49785048 -0.40288484 6 sp_10 0.710841370 0.55646477
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-#> 19331 0 0.49785048 -0.40288484 11 sp_13 0.710841370 0.55646477
-#> 19341 0 0.49785048 -0.40288484 10 sp_14 0.710841370 0.55646477
-#> 19351 0 0.49785048 -0.40288484 5 sp_15 0.710841370 0.55646477
-#> 19361 1 0.49785048 -0.40288484 11 sp_16 0.710841370 0.55646477
-#> 19371 0 0.49785048 -0.40288484 10 sp_17 0.710841370 0.55646477
-#> 19381 0 0.49785048 -0.40288484 15 sp_18 0.710841370 0.55646477
-#> 19391 0 0.49785048 -0.40288484 19 sp_19 0.710841370 0.55646477
-#> 19401 0 0.49785048 -0.40288484 10 sp_20 0.710841370 0.55646477
-#> 19411 1 0.49785048 -0.40288484 13 sp_21 0.710841370 0.55646477
-#> 19421 0 0.49785048 -0.40288484 3 sp_22 0.710841370 0.55646477
-#> 19431 0 0.49785048 -0.40288484 18 sp_23 0.710841370 0.55646477
-#> 19441 0 0.49785048 -0.40288484 10 sp_24 0.710841370 0.55646477
-#> 19451 1 0.49785048 -0.40288484 8 sp_25 0.710841370 0.55646477
-#> 19461 1 0.49785048 -0.40288484 12 sp_26 0.710841370 0.55646477
-#> 19471 0 0.49785048 -0.40288484 10 sp_27 0.710841370 0.55646477
-#> 19481 0 0.49785048 -0.40288484 7 sp_28 0.710841370 0.55646477
-#> 19491 0 0.49785048 -0.40288484 7 sp_29 0.710841370 0.55646477
-#> 19501 0 0.49785048 -0.40288484 6 sp_30 0.710841370 0.55646477
-#> 20411 0 -1.96661716 -0.46665535 17 sp_1 -1.294813968 -0.28740457
-#> 20421 0 -1.96661716 -0.46665535 20 sp_2 -1.294813968 -0.28740457
-#> 20431 0 -1.96661716 -0.46665535 1 sp_3 -1.294813968 -0.28740457
-#> 20441 0 -1.96661716 -0.46665535 5 sp_4 -1.294813968 -0.28740457
-#> 20451 0 -1.96661716 -0.46665535 10 sp_5 -1.294813968 -0.28740457
-#> 20461 0 -1.96661716 -0.46665535 13 sp_6 -1.294813968 -0.28740457
-#> 20471 0 -1.96661716 -0.46665535 10 sp_7 -1.294813968 -0.28740457
-#> 20481 0 -1.96661716 -0.46665535 2 sp_8 -1.294813968 -0.28740457
-#> 20491 0 -1.96661716 -0.46665535 15 sp_9 -1.294813968 -0.28740457
-#> 20501 0 -1.96661716 -0.46665535 15 sp_10 -1.294813968 -0.28740457
-#> 20511 0 -1.96661716 -0.46665535 8 sp_11 -1.294813968 -0.28740457
-#> 20521 0 -1.96661716 -0.46665535 3 sp_12 -1.294813968 -0.28740457
-#> 20531 0 -1.96661716 -0.46665535 2 sp_13 -1.294813968 -0.28740457
-#> 20541 0 -1.96661716 -0.46665535 6 sp_14 -1.294813968 -0.28740457
-#> 20551 0 -1.96661716 -0.46665535 14 sp_15 -1.294813968 -0.28740457
-#> 20561 0 -1.96661716 -0.46665535 15 sp_16 -1.294813968 -0.28740457
-#> 20571 0 -1.96661716 -0.46665535 19 sp_17 -1.294813968 -0.28740457
-#> 20581 0 -1.96661716 -0.46665535 9 sp_18 -1.294813968 -0.28740457
-#> 20591 0 -1.96661716 -0.46665535 15 sp_19 -1.294813968 -0.28740457
-#> 20601 0 -1.96661716 -0.46665535 16 sp_20 -1.294813968 -0.28740457
-#> 20611 0 -1.96661716 -0.46665535 8 sp_21 -1.294813968 -0.28740457
-#> 20621 0 -1.96661716 -0.46665535 9 sp_22 -1.294813968 -0.28740457
-#> 20631 0 -1.96661716 -0.46665535 16 sp_23 -1.294813968 -0.28740457
-#> 20641 0 -1.96661716 -0.46665535 9 sp_24 -1.294813968 -0.28740457
-#> 20651 0 -1.96661716 -0.46665535 2 sp_25 -1.294813968 -0.28740457
-#> 20661 0 -1.96661716 -0.46665535 9 sp_26 -1.294813968 -0.28740457
-#> 20671 0 -1.96661716 -0.46665535 11 sp_27 -1.294813968 -0.28740457
-#> 20681 0 -1.96661716 -0.46665535 11 sp_28 -1.294813968 -0.28740457
-#> 20691 0 -1.96661716 -0.46665535 4 sp_29 -1.294813968 -0.28740457
-#> 20701 0 -1.96661716 -0.46665535 7 sp_30 -1.294813968 -0.28740457
-#> 21611 0 0.70135590 0.77996512 18 sp_1 -1.066032692 1.17589068
-#> 21621 0 0.70135590 0.77996512 11 sp_2 -1.066032692 1.17589068
-#> 21631 0 0.70135590 0.77996512 1 sp_3 -1.066032692 1.17589068
-#> 21641 1 0.70135590 0.77996512 11 sp_4 -1.066032692 1.17589068
-#> 21651 0 0.70135590 0.77996512 6 sp_5 -1.066032692 1.17589068
-#> 21661 0 0.70135590 0.77996512 10 sp_6 -1.066032692 1.17589068
-#> 21671 0 0.70135590 0.77996512 18 sp_7 -1.066032692 1.17589068
-#> 21681 0 0.70135590 0.77996512 3 sp_8 -1.066032692 1.17589068
-#> 21691 0 0.70135590 0.77996512 3 sp_9 -1.066032692 1.17589068
-#> 21701 0 0.70135590 0.77996512 2 sp_10 -1.066032692 1.17589068
-#> 21711 0 0.70135590 0.77996512 8 sp_11 -1.066032692 1.17589068
-#> 21721 0 0.70135590 0.77996512 13 sp_12 -1.066032692 1.17589068
-#> 21731 0 0.70135590 0.77996512 8 sp_13 -1.066032692 1.17589068
-#> 21741 0 0.70135590 0.77996512 2 sp_14 -1.066032692 1.17589068
-#> 21751 0 0.70135590 0.77996512 6 sp_15 -1.066032692 1.17589068
-#> 21761 0 0.70135590 0.77996512 17 sp_16 -1.066032692 1.17589068
-#> 21771 0 0.70135590 0.77996512 14 sp_17 -1.066032692 1.17589068
-#> 21781 0 0.70135590 0.77996512 7 sp_18 -1.066032692 1.17589068
-#> 21791 0 0.70135590 0.77996512 13 sp_19 -1.066032692 1.17589068
-#> 21801 0 0.70135590 0.77996512 8 sp_20 -1.066032692 1.17589068
-#> 21811 0 0.70135590 0.77996512 6 sp_21 -1.066032692 1.17589068
-#> 21821 0 0.70135590 0.77996512 11 sp_22 -1.066032692 1.17589068
-#> 21831 0 0.70135590 0.77996512 10 sp_23 -1.066032692 1.17589068
-#> 21841 0 0.70135590 0.77996512 17 sp_24 -1.066032692 1.17589068
-#> 21851 0 0.70135590 0.77996512 7 sp_25 -1.066032692 1.17589068
-#> 21861 0 0.70135590 0.77996512 12 sp_26 -1.066032692 1.17589068
-#> 21871 0 0.70135590 0.77996512 19 sp_27 -1.066032692 1.17589068
-#> 21881 0 0.70135590 0.77996512 17 sp_28 -1.066032692 1.17589068
-#> 21891 0 0.70135590 0.77996512 8 sp_29 -1.066032692 1.17589068
-#> 21901 0 0.70135590 0.77996512 15 sp_30 -1.066032692 1.17589068
-#> 22811 1 -0.47279141 -0.08336907 14 sp_1 0.163432374 -0.33967076
-#> 22821 0 -0.47279141 -0.08336907 14 sp_2 0.163432374 -0.33967076
-#> 22831 0 -0.47279141 -0.08336907 17 sp_3 0.163432374 -0.33967076
-#> 22841 0 -0.47279141 -0.08336907 1 sp_4 0.163432374 -0.33967076
-#> 22851 0 -0.47279141 -0.08336907 18 sp_5 0.163432374 -0.33967076
-#> 22861 0 -0.47279141 -0.08336907 18 sp_6 0.163432374 -0.33967076
-#> 22871 0 -0.47279141 -0.08336907 20 sp_7 0.163432374 -0.33967076
-#> 22881 0 -0.47279141 -0.08336907 10 sp_8 0.163432374 -0.33967076
-#> 22891 1 -0.47279141 -0.08336907 10 sp_9 0.163432374 -0.33967076
-#> 22901 0 -0.47279141 -0.08336907 9 sp_10 0.163432374 -0.33967076
-#> 22911 0 -0.47279141 -0.08336907 19 sp_11 0.163432374 -0.33967076
-#> 22921 0 -0.47279141 -0.08336907 18 sp_12 0.163432374 -0.33967076
-#> 22931 0 -0.47279141 -0.08336907 18 sp_13 0.163432374 -0.33967076
-#> 22941 1 -0.47279141 -0.08336907 12 sp_14 0.163432374 -0.33967076
-#> 22951 1 -0.47279141 -0.08336907 12 sp_15 0.163432374 -0.33967076
-#> 22961 0 -0.47279141 -0.08336907 4 sp_16 0.163432374 -0.33967076
-#> 22971 0 -0.47279141 -0.08336907 20 sp_17 0.163432374 -0.33967076
-#> 22981 1 -0.47279141 -0.08336907 10 sp_18 0.163432374 -0.33967076
-#> 22991 0 -0.47279141 -0.08336907 5 sp_19 0.163432374 -0.33967076
-#> 23001 0 -0.47279141 -0.08336907 2 sp_20 0.163432374 -0.33967076
-#> 23011 0 -0.47279141 -0.08336907 18 sp_21 0.163432374 -0.33967076
-#> 23021 1 -0.47279141 -0.08336907 12 sp_22 0.163432374 -0.33967076
-#> 23031 0 -0.47279141 -0.08336907 13 sp_23 0.163432374 -0.33967076
-#> 23041 0 -0.47279141 -0.08336907 11 sp_24 0.163432374 -0.33967076
-#> 23051 0 -0.47279141 -0.08336907 19 sp_25 0.163432374 -0.33967076
-#> 23061 0 -0.47279141 -0.08336907 6 sp_26 0.163432374 -0.33967076
-#> 23071 0 -0.47279141 -0.08336907 18 sp_27 0.163432374 -0.33967076
-#> 23081 0 -0.47279141 -0.08336907 10 sp_28 0.163432374 -0.33967076
-#> 23091 0 -0.47279141 -0.08336907 9 sp_29 0.163432374 -0.33967076
-#> 23101 0 -0.47279141 -0.08336907 3 sp_30 0.163432374 -0.33967076
-#> 24011 0 -1.06782371 0.25331851 19 sp_1 0.915459490 -0.78713906
-#> 24021 0 -1.06782371 0.25331851 8 sp_2 0.915459490 -0.78713906
-#> 24031 0 -1.06782371 0.25331851 13 sp_3 0.915459490 -0.78713906
-#> 24041 0 -1.06782371 0.25331851 1 sp_4 0.915459490 -0.78713906
-#> 24051 1 -1.06782371 0.25331851 2 sp_5 0.915459490 -0.78713906
-#> 24061 0 -1.06782371 0.25331851 11 sp_6 0.915459490 -0.78713906
-#> 24071 0 -1.06782371 0.25331851 16 sp_7 0.915459490 -0.78713906
-#> 24081 0 -1.06782371 0.25331851 5 sp_8 0.915459490 -0.78713906
-#> 24091 0 -1.06782371 0.25331851 4 sp_9 0.915459490 -0.78713906
-#> 24101 0 -1.06782371 0.25331851 3 sp_10 0.915459490 -0.78713906
-#> 24111 0 -1.06782371 0.25331851 15 sp_11 0.915459490 -0.78713906
-#> 24121 0 -1.06782371 0.25331851 10 sp_12 0.915459490 -0.78713906
-#> 24131 1 -1.06782371 0.25331851 7 sp_13 0.915459490 -0.78713906
-#> 24141 0 -1.06782371 0.25331851 7 sp_14 0.915459490 -0.78713906
-#> 24151 0 -1.06782371 0.25331851 2 sp_15 0.915459490 -0.78713906
-#> 24161 0 -1.06782371 0.25331851 18 sp_16 0.915459490 -0.78713906
-#> 24171 0 -1.06782371 0.25331851 18 sp_17 0.915459490 -0.78713906
-#> 24181 0 -1.06782371 0.25331851 3 sp_18 0.915459490 -0.78713906
-#> 24191 0 -1.06782371 0.25331851 8 sp_19 0.915459490 -0.78713906
-#> 24201 0 -1.06782371 0.25331851 14 sp_20 0.915459490 -0.78713906
-#> 24211 0 -1.06782371 0.25331851 9 sp_21 0.915459490 -0.78713906
-#> 24221 0 -1.06782371 0.25331851 15 sp_22 0.915459490 -0.78713906
-#> 24231 0 -1.06782371 0.25331851 17 sp_23 0.915459490 -0.78713906
-#> 24241 1 -1.06782371 0.25331851 7 sp_24 0.915459490 -0.78713906
-#> 24251 0 -1.06782371 0.25331851 8 sp_25 0.915459490 -0.78713906
-#> 24261 0 -1.06782371 0.25331851 1 sp_26 0.915459490 -0.78713906
-#> 24271 0 -1.06782371 0.25331851 9 sp_27 0.915459490 -0.78713906
-#> 24281 0 -1.06782371 0.25331851 3 sp_28 0.915459490 -0.78713906
-#> 24291 1 -1.06782371 0.25331851 2 sp_29 0.915459490 -0.78713906
-#> 24301 0 -1.06782371 0.25331851 11 sp_30 0.915459490 -0.78713906
-#> 25211 0 -0.21797491 -0.02854676 4 sp_1 -0.293764363 -0.31146820
-#> 25221 0 -0.21797491 -0.02854676 8 sp_2 -0.293764363 -0.31146820
-#> 25231 0 -0.21797491 -0.02854676 20 sp_3 -0.293764363 -0.31146820
-#> 25241 1 -0.21797491 -0.02854676 11 sp_4 -0.293764363 -0.31146820
-#> 25251 0 -0.21797491 -0.02854676 18 sp_5 -0.293764363 -0.31146820
-#> 25261 0 -0.21797491 -0.02854676 14 sp_6 -0.293764363 -0.31146820
-#> 25271 0 -0.21797491 -0.02854676 3 sp_7 -0.293764363 -0.31146820
-#> 25281 0 -0.21797491 -0.02854676 3 sp_8 -0.293764363 -0.31146820
-#> 25291 0 -0.21797491 -0.02854676 14 sp_9 -0.293764363 -0.31146820
-#> 25301 0 -0.21797491 -0.02854676 7 sp_10 -0.293764363 -0.31146820
-#> 25311 0 -0.21797491 -0.02854676 15 sp_11 -0.293764363 -0.31146820
-#> 25321 0 -0.21797491 -0.02854676 8 sp_12 -0.293764363 -0.31146820
-#> 25331 0 -0.21797491 -0.02854676 1 sp_13 -0.293764363 -0.31146820
-#> 25341 0 -0.21797491 -0.02854676 5 sp_14 -0.293764363 -0.31146820
-#> 25351 1 -0.21797491 -0.02854676 17 sp_15 -0.293764363 -0.31146820
-#> 25361 0 -0.21797491 -0.02854676 6 sp_16 -0.293764363 -0.31146820
-#> 25371 0 -0.21797491 -0.02854676 10 sp_17 -0.293764363 -0.31146820
-#> 25381 0 -0.21797491 -0.02854676 12 sp_18 -0.293764363 -0.31146820
-#> 25391 0 -0.21797491 -0.02854676 8 sp_19 -0.293764363 -0.31146820
-#> 25401 0 -0.21797491 -0.02854676 16 sp_20 -0.293764363 -0.31146820
-#> 25411 1 -0.21797491 -0.02854676 7 sp_21 -0.293764363 -0.31146820
-#> 25421 0 -0.21797491 -0.02854676 7 sp_22 -0.293764363 -0.31146820
-#> 25431 0 -0.21797491 -0.02854676 1 sp_23 -0.293764363 -0.31146820
-#> 25441 0 -0.21797491 -0.02854676 11 sp_24 -0.293764363 -0.31146820
-#> 25451 0 -0.21797491 -0.02854676 3 sp_25 -0.293764363 -0.31146820
-#> 25461 0 -0.21797491 -0.02854676 17 sp_26 -0.293764363 -0.31146820
-#> 25471 0 -0.21797491 -0.02854676 20 sp_27 -0.293764363 -0.31146820
-#> 25481 0 -0.21797491 -0.02854676 3 sp_28 -0.293764363 -0.31146820
-#> 25491 0 -0.21797491 -0.02854676 14 sp_29 -0.293764363 -0.31146820
-#> 25501 0 -0.21797491 -0.02854676 5 sp_30 -0.293764363 -0.31146820
-#> 26411 0 -1.02600445 -0.04287046 18 sp_1 0.829990553 0.16243481
-#> 26421 0 -1.02600445 -0.04287046 8 sp_2 0.829990553 0.16243481
-#> 26431 0 -1.02600445 -0.04287046 20 sp_3 0.829990553 0.16243481
-#> 26441 1 -1.02600445 -0.04287046 10 sp_4 0.829990553 0.16243481
-#> 26451 1 -1.02600445 -0.04287046 18 sp_5 0.829990553 0.16243481
-#> 26461 0 -1.02600445 -0.04287046 17 sp_6 0.829990553 0.16243481
-#> 26471 0 -1.02600445 -0.04287046 9 sp_7 0.829990553 0.16243481
-#> 26481 0 -1.02600445 -0.04287046 3 sp_8 0.829990553 0.16243481
-#> 26491 0 -1.02600445 -0.04287046 5 sp_9 0.829990553 0.16243481
-#> 26501 0 -1.02600445 -0.04287046 16 sp_10 0.829990553 0.16243481
-#> 26511 0 -1.02600445 -0.04287046 20 sp_11 0.829990553 0.16243481
-#> 26521 0 -1.02600445 -0.04287046 3 sp_12 0.829990553 0.16243481
-#> 26531 0 -1.02600445 -0.04287046 3 sp_13 0.829990553 0.16243481
-#> 26541 0 -1.02600445 -0.04287046 13 sp_14 0.829990553 0.16243481
-#> 26551 0 -1.02600445 -0.04287046 4 sp_15 0.829990553 0.16243481
-#> 26561 0 -1.02600445 -0.04287046 15 sp_16 0.829990553 0.16243481
-#> 26571 0 -1.02600445 -0.04287046 19 sp_17 0.829990553 0.16243481
-#> 26581 0 -1.02600445 -0.04287046 13 sp_18 0.829990553 0.16243481
-#> 26591 0 -1.02600445 -0.04287046 12 sp_19 0.829990553 0.16243481
-#> 26601 0 -1.02600445 -0.04287046 20 sp_20 0.829990553 0.16243481
-#> 26611 0 -1.02600445 -0.04287046 13 sp_21 0.829990553 0.16243481
-#> 26621 0 -1.02600445 -0.04287046 13 sp_22 0.829990553 0.16243481
-#> 26631 0 -1.02600445 -0.04287046 3 sp_23 0.829990553 0.16243481
-#> 26641 0 -1.02600445 -0.04287046 20 sp_24 0.829990553 0.16243481
-#> 26651 0 -1.02600445 -0.04287046 5 sp_25 0.829990553 0.16243481
-#> 26661 0 -1.02600445 -0.04287046 13 sp_26 0.829990553 0.16243481
-#> 26671 0 -1.02600445 -0.04287046 12 sp_27 0.829990553 0.16243481
-#> 26681 0 -1.02600445 -0.04287046 8 sp_28 0.829990553 0.16243481
-#> 26691 0 -1.02600445 -0.04287046 6 sp_29 0.829990553 0.16243481
-#> 26701 1 -1.02600445 -0.04287046 16 sp_30 0.829990553 0.16243481
-#> 27611 0 -0.72889123 1.36860228 11 sp_1 -1.259322145 0.89326994
-#> 27621 0 -0.72889123 1.36860228 12 sp_2 -1.259322145 0.89326994
-#> 27631 0 -0.72889123 1.36860228 16 sp_3 -1.259322145 0.89326994
-#> 27641 0 -0.72889123 1.36860228 15 sp_4 -1.259322145 0.89326994
-#> 27651 0 -0.72889123 1.36860228 1 sp_5 -1.259322145 0.89326994
-#> 27661 0 -0.72889123 1.36860228 12 sp_6 -1.259322145 0.89326994
-#> 27671 0 -0.72889123 1.36860228 10 sp_7 -1.259322145 0.89326994
-#> 27681 0 -0.72889123 1.36860228 10 sp_8 -1.259322145 0.89326994
-#> 27691 0 -0.72889123 1.36860228 4 sp_9 -1.259322145 0.89326994
-#> 27701 0 -0.72889123 1.36860228 9 sp_10 -1.259322145 0.89326994
-#> 27711 0 -0.72889123 1.36860228 20 sp_11 -1.259322145 0.89326994
-#> 27721 0 -0.72889123 1.36860228 5 sp_12 -1.259322145 0.89326994
-#> 27731 0 -0.72889123 1.36860228 9 sp_13 -1.259322145 0.89326994
-#> 27741 0 -0.72889123 1.36860228 19 sp_14 -1.259322145 0.89326994
-#> 27751 0 -0.72889123 1.36860228 3 sp_15 -1.259322145 0.89326994
-#> 27761 0 -0.72889123 1.36860228 2 sp_16 -1.259322145 0.89326994
-#> 27771 0 -0.72889123 1.36860228 12 sp_17 -1.259322145 0.89326994
-#> 27781 0 -0.72889123 1.36860228 15 sp_18 -1.259322145 0.89326994
-#> 27791 0 -0.72889123 1.36860228 17 sp_19 -1.259322145 0.89326994
-#> 27801 0 -0.72889123 1.36860228 3 sp_20 -1.259322145 0.89326994
-#> 27811 0 -0.72889123 1.36860228 7 sp_21 -1.259322145 0.89326994
-#> 27821 0 -0.72889123 1.36860228 13 sp_22 -1.259322145 0.89326994
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-#> 27841 0 -0.72889123 1.36860228 2 sp_24 -1.259322145 0.89326994
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-#> 1272 1 -0.23017749 -0.29507148 14 sp_7 0.030148911 -0.84353812
-#> 1282 0 -0.23017749 -0.29507148 19 sp_8 0.030148911 -0.84353812
-#> 1292 0 -0.23017749 -0.29507148 7 sp_9 0.030148911 -0.84353812
-#> 1302 0 -0.23017749 -0.29507148 9 sp_10 0.030148911 -0.84353812
-#> 1313 0 -0.23017749 -0.29507148 7 sp_11 0.030148911 -0.84353812
-#> 13212 1 -0.23017749 -0.29507148 2 sp_12 0.030148911 -0.84353812
-#> 13312 0 -0.23017749 -0.29507148 16 sp_13 0.030148911 -0.84353812
-#> 13412 0 -0.23017749 -0.29507148 13 sp_14 0.030148911 -0.84353812
-#> 1352 0 -0.23017749 -0.29507148 19 sp_15 0.030148911 -0.84353812
-#> 1362 1 -0.23017749 -0.29507148 20 sp_16 0.030148911 -0.84353812
-#> 1372 0 -0.23017749 -0.29507148 15 sp_17 0.030148911 -0.84353812
-#> 1382 0 -0.23017749 -0.29507148 7 sp_18 0.030148911 -0.84353812
-#> 1392 0 -0.23017749 -0.29507148 4 sp_19 0.030148911 -0.84353812
-#> 1402 0 -0.23017749 -0.29507148 1 sp_20 0.030148911 -0.84353812
-#> 1413 0 -0.23017749 -0.29507148 8 sp_21 0.030148911 -0.84353812
-#> 1422 1 -0.23017749 -0.29507148 20 sp_22 0.030148911 -0.84353812
-#> 1432 1 -0.23017749 -0.29507148 16 sp_23 0.030148911 -0.84353812
-#> 14412 0 -0.23017749 -0.29507148 11 sp_24 0.030148911 -0.84353812
-#> 14512 0 -0.23017749 -0.29507148 16 sp_25 0.030148911 -0.84353812
-#> 14612 0 -0.23017749 -0.29507148 20 sp_26 0.030148911 -0.84353812
-#> 1472 0 -0.23017749 -0.29507148 8 sp_27 0.030148911 -0.84353812
-#> 1482 0 -0.23017749 -0.29507148 3 sp_28 0.030148911 -0.84353812
-#> 1492 0 -0.23017749 -0.29507148 4 sp_29 0.030148911 -0.84353812
-#> 1502 0 -0.23017749 -0.29507148 20 sp_30 0.030148911 -0.84353812
-#> 24112 0 1.55870831 0.89512566 12 sp_1 -0.421998576 -0.60935167
-#> 24212 1 1.55870831 0.89512566 17 sp_2 -0.421998576 -0.60935167
-#> 2434 0 1.55870831 0.89512566 10 sp_3 -0.421998576 -0.60935167
-#> 2442 1 1.55870831 0.89512566 20 sp_4 -0.421998576 -0.60935167
-#> 2452 1 1.55870831 0.89512566 11 sp_5 -0.421998576 -0.60935167
-#> 2462 1 1.55870831 0.89512566 8 sp_6 -0.421998576 -0.60935167
-#> 2472 1 1.55870831 0.89512566 14 sp_7 -0.421998576 -0.60935167
-#> 2482 0 1.55870831 0.89512566 13 sp_8 -0.421998576 -0.60935167
-#> 2492 1 1.55870831 0.89512566 2 sp_9 -0.421998576 -0.60935167
-#> 2502 0 1.55870831 0.89512566 11 sp_10 -0.421998576 -0.60935167
-#> 2513 0 1.55870831 0.89512566 13 sp_11 -0.421998576 -0.60935167
-#> 25212 1 1.55870831 0.89512566 14 sp_12 -0.421998576 -0.60935167
-#> 25312 0 1.55870831 0.89512566 6 sp_13 -0.421998576 -0.60935167
-#> 25412 0 1.55870831 0.89512566 8 sp_14 -0.421998576 -0.60935167
-#> 2552 1 1.55870831 0.89512566 12 sp_15 -0.421998576 -0.60935167
-#> 2562 0 1.55870831 0.89512566 4 sp_16 -0.421998576 -0.60935167
-#> 2572 0 1.55870831 0.89512566 13 sp_17 -0.421998576 -0.60935167
-#> 2582 0 1.55870831 0.89512566 14 sp_18 -0.421998576 -0.60935167
-#> 2592 0 1.55870831 0.89512566 16 sp_19 -0.421998576 -0.60935167
-#> 2602 0 1.55870831 0.89512566 1 sp_20 -0.421998576 -0.60935167
-#> 2613 0 1.55870831 0.89512566 8 sp_21 -0.421998576 -0.60935167
-#> 2622 0 1.55870831 0.89512566 8 sp_22 -0.421998576 -0.60935167
-#> 2632 0 1.55870831 0.89512566 10 sp_23 -0.421998576 -0.60935167
-#> 26412 0 1.55870831 0.89512566 8 sp_24 -0.421998576 -0.60935167
-#> 26512 0 1.55870831 0.89512566 18 sp_25 -0.421998576 -0.60935167
-#> 26612 0 1.55870831 0.89512566 9 sp_26 -0.421998576 -0.60935167
-#> 2672 1 1.55870831 0.89512566 7 sp_27 -0.421998576 -0.60935167
-#> 2682 0 1.55870831 0.89512566 7 sp_28 -0.421998576 -0.60935167
-#> 2692 1 1.55870831 0.89512566 10 sp_29 -0.421998576 -0.60935167
-#> 2702 0 1.55870831 0.89512566 11 sp_30 -0.421998576 -0.60935167
-#> 3612 0 0.07050839 0.87813349 1 sp_1 -0.247425100 -1.79048626
-#> 3622 0 0.07050839 0.87813349 19 sp_2 -0.247425100 -1.79048626
-#> 3632 0 0.07050839 0.87813349 10 sp_3 -0.247425100 -1.79048626
-#> 3642 0 0.07050839 0.87813349 13 sp_4 -0.247425100 -1.79048626
-#> 3652 1 0.07050839 0.87813349 11 sp_5 -0.247425100 -1.79048626
-#> 3662 0 0.07050839 0.87813349 11 sp_6 -0.247425100 -1.79048626
-#> 3672 0 0.07050839 0.87813349 20 sp_7 -0.247425100 -1.79048626
-#> 3682 0 0.07050839 0.87813349 7 sp_8 -0.247425100 -1.79048626
-#> 3692 0 0.07050839 0.87813349 20 sp_9 -0.247425100 -1.79048626
-#> 3702 0 0.07050839 0.87813349 9 sp_10 -0.247425100 -1.79048626
-#> 3712 0 0.07050839 0.87813349 9 sp_11 -0.247425100 -1.79048626
-#> 3722 0 0.07050839 0.87813349 5 sp_12 -0.247425100 -1.79048626
-#> 3732 1 0.07050839 0.87813349 14 sp_13 -0.247425100 -1.79048626
-#> 3742 0 0.07050839 0.87813349 14 sp_14 -0.247425100 -1.79048626
-#> 3752 0 0.07050839 0.87813349 6 sp_15 -0.247425100 -1.79048626
-#> 3762 0 0.07050839 0.87813349 1 sp_16 -0.247425100 -1.79048626
-#> 3772 0 0.07050839 0.87813349 10 sp_17 -0.247425100 -1.79048626
-#> 3782 1 0.07050839 0.87813349 17 sp_18 -0.247425100 -1.79048626
-#> 3792 1 0.07050839 0.87813349 17 sp_19 -0.247425100 -1.79048626
-#> 3802 0 0.07050839 0.87813349 7 sp_20 -0.247425100 -1.79048626
-#> 3812 0 0.07050839 0.87813349 9 sp_21 -0.247425100 -1.79048626
-#> 3822 0 0.07050839 0.87813349 20 sp_22 -0.247425100 -1.79048626
-#> 3832 0 0.07050839 0.87813349 6 sp_23 -0.247425100 -1.79048626
-#> 3842 0 0.07050839 0.87813349 18 sp_24 -0.247425100 -1.79048626
-#> 3852 0 0.07050839 0.87813349 17 sp_25 -0.247425100 -1.79048626
-#> 3862 0 0.07050839 0.87813349 5 sp_26 -0.247425100 -1.79048626
-#> 3872 1 0.07050839 0.87813349 20 sp_27 -0.247425100 -1.79048626
-#> 3882 0 0.07050839 0.87813349 3 sp_28 -0.247425100 -1.79048626
-#> 3892 0 0.07050839 0.87813349 14 sp_29 -0.247425100 -1.79048626
-#> 3902 0 0.07050839 0.87813349 1 sp_30 -0.247425100 -1.79048626
-#> 4812 1 0.12928774 0.82158108 2 sp_1 0.644151150 -0.23984666
-#> 4822 0 0.12928774 0.82158108 4 sp_2 0.644151150 -0.23984666
-#> 4832 0 0.12928774 0.82158108 10 sp_3 0.644151150 -0.23984666
-#> 4842 0 0.12928774 0.82158108 1 sp_4 0.644151150 -0.23984666
-#> 4852 0 0.12928774 0.82158108 5 sp_5 0.644151150 -0.23984666
-#> 4862 0 0.12928774 0.82158108 8 sp_6 0.644151150 -0.23984666
-#> 4872 0 0.12928774 0.82158108 13 sp_7 0.644151150 -0.23984666
-#> 4882 0 0.12928774 0.82158108 18 sp_8 0.644151150 -0.23984666
-#> 4892 0 0.12928774 0.82158108 10 sp_9 0.644151150 -0.23984666
-#> 4902 0 0.12928774 0.82158108 6 sp_10 0.644151150 -0.23984666
-#> 4912 1 0.12928774 0.82158108 7 sp_11 0.644151150 -0.23984666
-#> 4922 0 0.12928774 0.82158108 9 sp_12 0.644151150 -0.23984666
-#> 4932 0 0.12928774 0.82158108 16 sp_13 0.644151150 -0.23984666
-#> 4942 1 0.12928774 0.82158108 17 sp_14 0.644151150 -0.23984666
-#> 4952 0 0.12928774 0.82158108 13 sp_15 0.644151150 -0.23984666
-#> 4962 0 0.12928774 0.82158108 8 sp_16 0.644151150 -0.23984666
-#> 4972 0 0.12928774 0.82158108 7 sp_17 0.644151150 -0.23984666
-#> 4982 0 0.12928774 0.82158108 20 sp_18 0.644151150 -0.23984666
-#> 4992 0 0.12928774 0.82158108 18 sp_19 0.644151150 -0.23984666
-#> 5002 0 0.12928774 0.82158108 17 sp_20 0.644151150 -0.23984666
-#> 5012 0 0.12928774 0.82158108 1 sp_21 0.644151150 -0.23984666
-#> 5022 0 0.12928774 0.82158108 2 sp_22 0.644151150 -0.23984666
-#> 5032 0 0.12928774 0.82158108 17 sp_23 0.644151150 -0.23984666
-#> 5042 0 0.12928774 0.82158108 2 sp_24 0.644151150 -0.23984666
-#> 5052 0 0.12928774 0.82158108 13 sp_25 0.644151150 -0.23984666
-#> 5062 0 0.12928774 0.82158108 17 sp_26 0.644151150 -0.23984666
-#> 5072 0 0.12928774 0.82158108 3 sp_27 0.644151150 -0.23984666
-#> 5082 0 0.12928774 0.82158108 18 sp_28 0.644151150 -0.23984666
-#> 5092 1 0.12928774 0.82158108 2 sp_29 0.644151150 -0.23984666
-#> 5102 0 0.12928774 0.82158108 5 sp_30 0.644151150 -0.23984666
-#> 6012 0 1.71506499 0.68864025 12 sp_1 0.218513365 1.48442693
-#> 6022 0 1.71506499 0.68864025 13 sp_2 0.218513365 1.48442693
-#> 6032 0 1.71506499 0.68864025 10 sp_3 0.218513365 1.48442693
-#> 6042 1 1.71506499 0.68864025 6 sp_4 0.218513365 1.48442693
-#> 6052 0 1.71506499 0.68864025 10 sp_5 0.218513365 1.48442693
-#> 6062 0 1.71506499 0.68864025 10 sp_6 0.218513365 1.48442693
-#> 6072 0 1.71506499 0.68864025 6 sp_7 0.218513365 1.48442693
-#> 6082 0 1.71506499 0.68864025 16 sp_8 0.218513365 1.48442693
-#> 6092 0 1.71506499 0.68864025 16 sp_9 0.218513365 1.48442693
-#> 6102 0 1.71506499 0.68864025 3 sp_10 0.218513365 1.48442693
-#> 6112 0 1.71506499 0.68864025 4 sp_11 0.218513365 1.48442693
-#> 6122 1 1.71506499 0.68864025 3 sp_12 0.218513365 1.48442693
-#> 6132 0 1.71506499 0.68864025 3 sp_13 0.218513365 1.48442693
-#> 6142 0 1.71506499 0.68864025 16 sp_14 0.218513365 1.48442693
-#> 6152 0 1.71506499 0.68864025 2 sp_15 0.218513365 1.48442693
-#> 6162 0 1.71506499 0.68864025 15 sp_16 0.218513365 1.48442693
-#> 6172 0 1.71506499 0.68864025 3 sp_17 0.218513365 1.48442693
-#> 6182 0 1.71506499 0.68864025 9 sp_18 0.218513365 1.48442693
-#> 6192 0 1.71506499 0.68864025 7 sp_19 0.218513365 1.48442693
-#> 6202 0 1.71506499 0.68864025 9 sp_20 0.218513365 1.48442693
-#> 6212 0 1.71506499 0.68864025 4 sp_21 0.218513365 1.48442693
-#> 6222 0 1.71506499 0.68864025 2 sp_22 0.218513365 1.48442693
-#> 6232 0 1.71506499 0.68864025 12 sp_23 0.218513365 1.48442693
-#> 6242 0 1.71506499 0.68864025 9 sp_24 0.218513365 1.48442693
-#> 6252 0 1.71506499 0.68864025 11 sp_25 0.218513365 1.48442693
-#> 6262 0 1.71506499 0.68864025 7 sp_26 0.218513365 1.48442693
-#> 6272 0 1.71506499 0.68864025 13 sp_27 0.218513365 1.48442693
-#> 6282 1 1.71506499 0.68864025 5 sp_28 0.218513365 1.48442693
-#> 6292 0 1.71506499 0.68864025 11 sp_29 0.218513365 1.48442693
-#> 6302 0 1.71506499 0.68864025 1 sp_30 0.218513365 1.48442693
-#> 7212 0 0.46091621 0.55391765 19 sp_1 1.524904741 0.66138217
-#> 7222 1 0.46091621 0.55391765 12 sp_2 1.524904741 0.66138217
-#> 7232 0 0.46091621 0.55391765 2 sp_3 1.524904741 0.66138217
-#> 7242 0 0.46091621 0.55391765 17 sp_4 1.524904741 0.66138217
-#> 7252 1 0.46091621 0.55391765 12 sp_5 1.524904741 0.66138217
-#> 7262 0 0.46091621 0.55391765 3 sp_6 1.524904741 0.66138217
-#> 7272 0 0.46091621 0.55391765 18 sp_7 1.524904741 0.66138217
-#> 7282 0 0.46091621 0.55391765 15 sp_8 1.524904741 0.66138217
-#> 7292 0 0.46091621 0.55391765 3 sp_9 1.524904741 0.66138217
-#> 7302 0 0.46091621 0.55391765 19 sp_10 1.524904741 0.66138217
-#> 7312 0 0.46091621 0.55391765 18 sp_11 1.524904741 0.66138217
-#> 7322 0 0.46091621 0.55391765 17 sp_12 1.524904741 0.66138217
-#> 7332 0 0.46091621 0.55391765 6 sp_13 1.524904741 0.66138217
-#> 7342 0 0.46091621 0.55391765 10 sp_14 1.524904741 0.66138217
-#> 7352 0 0.46091621 0.55391765 8 sp_15 1.524904741 0.66138217
-#> 7362 0 0.46091621 0.55391765 10 sp_16 1.524904741 0.66138217
-#> 7372 0 0.46091621 0.55391765 13 sp_17 1.524904741 0.66138217
-#> 7382 1 0.46091621 0.55391765 20 sp_18 1.524904741 0.66138217
-#> 7392 0 0.46091621 0.55391765 6 sp_19 1.524904741 0.66138217
-#> 7402 0 0.46091621 0.55391765 20 sp_20 1.524904741 0.66138217
-#> 7412 0 0.46091621 0.55391765 20 sp_21 1.524904741 0.66138217
-#> 7422 0 0.46091621 0.55391765 9 sp_22 1.524904741 0.66138217
-#> 7432 1 0.46091621 0.55391765 16 sp_23 1.524904741 0.66138217
-#> 7442 0 0.46091621 0.55391765 8 sp_24 1.524904741 0.66138217
-#> 7452 0 0.46091621 0.55391765 7 sp_25 1.524904741 0.66138217
-#> 7462 0 0.46091621 0.55391765 10 sp_26 1.524904741 0.66138217
-#> 7472 0 0.46091621 0.55391765 17 sp_27 1.524904741 0.66138217
-#> 7482 0 0.46091621 0.55391765 18 sp_28 1.524904741 0.66138217
-#> 7492 0 0.46091621 0.55391765 8 sp_29 1.524904741 0.66138217
-#> 7502 0 0.46091621 0.55391765 19 sp_30 1.524904741 0.66138217
-#> 8412 1 -1.26506123 -0.06191171 10 sp_1 -1.024046710 -0.81527923
-#> 8422 0 -1.26506123 -0.06191171 11 sp_2 -1.024046710 -0.81527923
-#> 8432 0 -1.26506123 -0.06191171 17 sp_3 -1.024046710 -0.81527923
-#> 8442 0 -1.26506123 -0.06191171 12 sp_4 -1.024046710 -0.81527923
-#> 8452 0 -1.26506123 -0.06191171 2 sp_5 -1.024046710 -0.81527923
-#> 8462 0 -1.26506123 -0.06191171 19 sp_6 -1.024046710 -0.81527923
-#> 8472 0 -1.26506123 -0.06191171 13 sp_7 -1.024046710 -0.81527923
-#> 8482 0 -1.26506123 -0.06191171 13 sp_8 -1.024046710 -0.81527923
-#> 8492 0 -1.26506123 -0.06191171 19 sp_9 -1.024046710 -0.81527923
-#> 8502 1 -1.26506123 -0.06191171 10 sp_10 -1.024046710 -0.81527923
-#> 8512 0 -1.26506123 -0.06191171 16 sp_11 -1.024046710 -0.81527923
-#> 8522 0 -1.26506123 -0.06191171 5 sp_12 -1.024046710 -0.81527923
-#> 8532 0 -1.26506123 -0.06191171 4 sp_13 -1.024046710 -0.81527923
-#> 8542 0 -1.26506123 -0.06191171 18 sp_14 -1.024046710 -0.81527923
-#> 8552 0 -1.26506123 -0.06191171 1 sp_15 -1.024046710 -0.81527923
-#> 8562 0 -1.26506123 -0.06191171 16 sp_16 -1.024046710 -0.81527923
-#> 8572 0 -1.26506123 -0.06191171 17 sp_17 -1.024046710 -0.81527923
-#> 8582 0 -1.26506123 -0.06191171 12 sp_18 -1.024046710 -0.81527923
-#> 8592 1 -1.26506123 -0.06191171 2 sp_19 -1.024046710 -0.81527923
-#> 8602 0 -1.26506123 -0.06191171 18 sp_20 -1.024046710 -0.81527923
-#> 8612 0 -1.26506123 -0.06191171 12 sp_21 -1.024046710 -0.81527923
-#> 8622 0 -1.26506123 -0.06191171 15 sp_22 -1.024046710 -0.81527923
-#> 8632 0 -1.26506123 -0.06191171 19 sp_23 -1.024046710 -0.81527923
-#> 8642 0 -1.26506123 -0.06191171 6 sp_24 -1.024046710 -0.81527923
-#> 8652 0 -1.26506123 -0.06191171 16 sp_25 -1.024046710 -0.81527923
-#> 8662 0 -1.26506123 -0.06191171 15 sp_26 -1.024046710 -0.81527923
-#> 8672 0 -1.26506123 -0.06191171 19 sp_27 -1.024046710 -0.81527923
-#> 8682 0 -1.26506123 -0.06191171 3 sp_28 -1.024046710 -0.81527923
-#> 8692 0 -1.26506123 -0.06191171 14 sp_29 -1.024046710 -0.81527923
-#> 8702 0 -1.26506123 -0.06191171 1 sp_30 -1.024046710 -0.81527923
-#> 9612 0 -0.68685285 -0.30596266 1 sp_1 0.519500645 -0.43573685
-#> 9622 1 -0.68685285 -0.30596266 16 sp_2 0.519500645 -0.43573685
-#> 9632 0 -0.68685285 -0.30596266 11 sp_3 0.519500645 -0.43573685
-#> 9642 0 -0.68685285 -0.30596266 4 sp_4 0.519500645 -0.43573685
-#> 9652 1 -0.68685285 -0.30596266 12 sp_5 0.519500645 -0.43573685
-#> 9662 0 -0.68685285 -0.30596266 13 sp_6 0.519500645 -0.43573685
-#> 9672 0 -0.68685285 -0.30596266 10 sp_7 0.519500645 -0.43573685
-#> 9682 0 -0.68685285 -0.30596266 10 sp_8 0.519500645 -0.43573685
-#> 9692 0 -0.68685285 -0.30596266 7 sp_9 0.519500645 -0.43573685
-#> 9702 0 -0.68685285 -0.30596266 18 sp_10 0.519500645 -0.43573685
-#> 9712 0 -0.68685285 -0.30596266 17 sp_11 0.519500645 -0.43573685
-#> 9722 0 -0.68685285 -0.30596266 20 sp_12 0.519500645 -0.43573685
-#> 9732 0 -0.68685285 -0.30596266 9 sp_13 0.519500645 -0.43573685
-#> 9742 1 -0.68685285 -0.30596266 11 sp_14 0.519500645 -0.43573685
-#> 9752 1 -0.68685285 -0.30596266 12 sp_15 0.519500645 -0.43573685
-#> 9762 0 -0.68685285 -0.30596266 8 sp_16 0.519500645 -0.43573685
-#> 9772 0 -0.68685285 -0.30596266 18 sp_17 0.519500645 -0.43573685
-#> 9782 0 -0.68685285 -0.30596266 5 sp_18 0.519500645 -0.43573685
-#> 9792 0 -0.68685285 -0.30596266 18 sp_19 0.519500645 -0.43573685
-#> 9802 0 -0.68685285 -0.30596266 6 sp_20 0.519500645 -0.43573685
-#> 9812 0 -0.68685285 -0.30596266 10 sp_21 0.519500645 -0.43573685
-#> 9822 0 -0.68685285 -0.30596266 9 sp_22 0.519500645 -0.43573685
-#> 9832 0 -0.68685285 -0.30596266 11 sp_23 0.519500645 -0.43573685
-#> 9842 0 -0.68685285 -0.30596266 6 sp_24 0.519500645 -0.43573685
-#> 9852 0 -0.68685285 -0.30596266 12 sp_25 0.519500645 -0.43573685
-#> 9862 0 -0.68685285 -0.30596266 19 sp_26 0.519500645 -0.43573685
-#> 9872 0 -0.68685285 -0.30596266 4 sp_27 0.519500645 -0.43573685
-#> 9882 0 -0.68685285 -0.30596266 3 sp_28 0.519500645 -0.43573685
-#> 9892 0 -0.68685285 -0.30596266 14 sp_29 0.519500645 -0.43573685
-#> 9902 0 -0.68685285 -0.30596266 8 sp_30 0.519500645 -0.43573685
-#> 10812 0 -0.44566197 -0.38047100 6 sp_1 0.024742072 0.73153658
-#> 10822 0 -0.44566197 -0.38047100 4 sp_2 0.024742072 0.73153658
-#> 10832 0 -0.44566197 -0.38047100 10 sp_3 0.024742072 0.73153658
-#> 10842 0 -0.44566197 -0.38047100 16 sp_4 0.024742072 0.73153658
-#> 10852 0 -0.44566197 -0.38047100 16 sp_5 0.024742072 0.73153658
-#> 10862 0 -0.44566197 -0.38047100 20 sp_6 0.024742072 0.73153658
-#> 10872 1 -0.44566197 -0.38047100 10 sp_7 0.024742072 0.73153658
-#> 10882 0 -0.44566197 -0.38047100 6 sp_8 0.024742072 0.73153658
-#> 10892 0 -0.44566197 -0.38047100 19 sp_9 0.024742072 0.73153658
-#> 10902 0 -0.44566197 -0.38047100 4 sp_10 0.024742072 0.73153658
-#> 10912 0 -0.44566197 -0.38047100 9 sp_11 0.024742072 0.73153658
-#> 10922 0 -0.44566197 -0.38047100 4 sp_12 0.024742072 0.73153658
-#> 10932 0 -0.44566197 -0.38047100 15 sp_13 0.024742072 0.73153658
-#> 10942 0 -0.44566197 -0.38047100 20 sp_14 0.024742072 0.73153658
-#> 10952 1 -0.44566197 -0.38047100 17 sp_15 0.024742072 0.73153658
-#> 10962 0 -0.44566197 -0.38047100 7 sp_16 0.024742072 0.73153658
-#> 10972 0 -0.44566197 -0.38047100 15 sp_17 0.024742072 0.73153658
-#> 10982 0 -0.44566197 -0.38047100 5 sp_18 0.024742072 0.73153658
-#> 10992 1 -0.44566197 -0.38047100 14 sp_19 0.024742072 0.73153658
-#> 11002 0 -0.44566197 -0.38047100 15 sp_20 0.024742072 0.73153658
-#> 11012 0 -0.44566197 -0.38047100 15 sp_21 0.024742072 0.73153658
-#> 11022 0 -0.44566197 -0.38047100 16 sp_22 0.024742072 0.73153658
-#> 11032 0 -0.44566197 -0.38047100 19 sp_23 0.024742072 0.73153658
-#> 11042 0 -0.44566197 -0.38047100 8 sp_24 0.024742072 0.73153658
-#> 11052 0 -0.44566197 -0.38047100 5 sp_25 0.024742072 0.73153658
-#> 11062 0 -0.44566197 -0.38047100 7 sp_26 0.024742072 0.73153658
-#> 11072 1 -0.44566197 -0.38047100 20 sp_27 0.024742072 0.73153658
-#> 11082 0 -0.44566197 -0.38047100 16 sp_28 0.024742072 0.73153658
-#> 11092 0 -0.44566197 -0.38047100 16 sp_29 0.024742072 0.73153658
-#> 11102 0 -0.44566197 -0.38047100 9 sp_30 0.024742072 0.73153658
-#> 12012 0 1.22408180 -0.69470698 11 sp_1 -0.970649504 1.50473579
-#> 12022 0 1.22408180 -0.69470698 11 sp_2 -0.970649504 1.50473579
-#> 12032 0 1.22408180 -0.69470698 19 sp_3 -0.970649504 1.50473579
-#> 12042 0 1.22408180 -0.69470698 10 sp_4 -0.970649504 1.50473579
-#> 12052 0 1.22408180 -0.69470698 2 sp_5 -0.970649504 1.50473579
-#> 12062 0 1.22408180 -0.69470698 6 sp_6 -0.970649504 1.50473579
-#> 12072 0 1.22408180 -0.69470698 20 sp_7 -0.970649504 1.50473579
-#> 12082 0 1.22408180 -0.69470698 14 sp_8 -0.970649504 1.50473579
-#> 12092 0 1.22408180 -0.69470698 14 sp_9 -0.970649504 1.50473579
-#> 12102 0 1.22408180 -0.69470698 6 sp_10 -0.970649504 1.50473579
-#> 12113 0 1.22408180 -0.69470698 18 sp_11 -0.970649504 1.50473579
-#> 12122 0 1.22408180 -0.69470698 2 sp_12 -0.970649504 1.50473579
-#> 12132 1 1.22408180 -0.69470698 8 sp_13 -0.970649504 1.50473579
-#> 12142 0 1.22408180 -0.69470698 11 sp_14 -0.970649504 1.50473579
-#> 12152 0 1.22408180 -0.69470698 7 sp_15 -0.970649504 1.50473579
-#> 12162 0 1.22408180 -0.69470698 19 sp_16 -0.970649504 1.50473579
-#> 12172 0 1.22408180 -0.69470698 8 sp_17 -0.970649504 1.50473579
-#> 12182 0 1.22408180 -0.69470698 10 sp_18 -0.970649504 1.50473579
-#> 12192 0 1.22408180 -0.69470698 5 sp_19 -0.970649504 1.50473579
-#> 12202 0 1.22408180 -0.69470698 17 sp_20 -0.970649504 1.50473579
-#> 12213 0 1.22408180 -0.69470698 6 sp_21 -0.970649504 1.50473579
-#> 12222 0 1.22408180 -0.69470698 8 sp_22 -0.970649504 1.50473579
-#> 12232 0 1.22408180 -0.69470698 20 sp_23 -0.970649504 1.50473579
-#> 12242 0 1.22408180 -0.69470698 6 sp_24 -0.970649504 1.50473579
-#> 12252 0 1.22408180 -0.69470698 15 sp_25 -0.970649504 1.50473579
-#> 12262 0 1.22408180 -0.69470698 17 sp_26 -0.970649504 1.50473579
-#> 12272 1 1.22408180 -0.69470698 3 sp_27 -0.970649504 1.50473579
-#> 12282 0 1.22408180 -0.69470698 15 sp_28 -0.970649504 1.50473579
-#> 12292 0 1.22408180 -0.69470698 20 sp_29 -0.970649504 1.50473579
-#> 12302 0 1.22408180 -0.69470698 1 sp_30 -0.970649504 1.50473579
-#> 13213 0 0.35981383 -0.20791728 5 sp_1 -1.696019564 -0.30971435
-#> 13222 1 0.35981383 -0.20791728 11 sp_2 -1.696019564 -0.30971435
-#> 13232 0 0.35981383 -0.20791728 15 sp_3 -1.696019564 -0.30971435
-#> 13242 0 0.35981383 -0.20791728 20 sp_4 -1.696019564 -0.30971435
-#> 13252 0 0.35981383 -0.20791728 2 sp_5 -1.696019564 -0.30971435
-#> 13262 0 0.35981383 -0.20791728 16 sp_6 -1.696019564 -0.30971435
-#> 13272 0 0.35981383 -0.20791728 19 sp_7 -1.696019564 -0.30971435
-#> 13282 0 0.35981383 -0.20791728 10 sp_8 -1.696019564 -0.30971435
-#> 13292 0 0.35981383 -0.20791728 19 sp_9 -1.696019564 -0.30971435
-#> 13302 0 0.35981383 -0.20791728 17 sp_10 -1.696019564 -0.30971435
-#> 13313 0 0.35981383 -0.20791728 7 sp_11 -1.696019564 -0.30971435
-#> 13322 0 0.35981383 -0.20791728 6 sp_12 -1.696019564 -0.30971435
-#> 13332 0 0.35981383 -0.20791728 12 sp_13 -1.696019564 -0.30971435
-#> 13342 0 0.35981383 -0.20791728 4 sp_14 -1.696019564 -0.30971435
-#> 13352 0 0.35981383 -0.20791728 19 sp_15 -1.696019564 -0.30971435
-#> 13362 0 0.35981383 -0.20791728 2 sp_16 -1.696019564 -0.30971435
-#> 13372 0 0.35981383 -0.20791728 4 sp_17 -1.696019564 -0.30971435
-#> 13382 0 0.35981383 -0.20791728 11 sp_18 -1.696019564 -0.30971435
-#> 13392 1 0.35981383 -0.20791728 1 sp_19 -1.696019564 -0.30971435
-#> 13402 0 0.35981383 -0.20791728 19 sp_20 -1.696019564 -0.30971435
-#> 13413 0 0.35981383 -0.20791728 18 sp_21 -1.696019564 -0.30971435
-#> 13422 0 0.35981383 -0.20791728 16 sp_22 -1.696019564 -0.30971435
-#> 13432 1 0.35981383 -0.20791728 3 sp_23 -1.696019564 -0.30971435
-#> 13442 0 0.35981383 -0.20791728 1 sp_24 -1.696019564 -0.30971435
-#> 13452 0 0.35981383 -0.20791728 2 sp_25 -1.696019564 -0.30971435
-#> 13462 0 0.35981383 -0.20791728 2 sp_26 -1.696019564 -0.30971435
-#> 13472 0 0.35981383 -0.20791728 8 sp_27 -1.696019564 -0.30971435
-#> 13482 1 0.35981383 -0.20791728 20 sp_28 -1.696019564 -0.30971435
-#> 13492 0 0.35981383 -0.20791728 14 sp_29 -1.696019564 -0.30971435
-#> 13502 0 0.35981383 -0.20791728 13 sp_30 -1.696019564 -0.30971435
-#> 14413 0 0.40077145 -1.26539635 7 sp_1 0.662820286 -1.28685391
-#> 14422 0 0.40077145 -1.26539635 8 sp_2 0.662820286 -1.28685391
-#> 14432 1 0.40077145 -1.26539635 3 sp_3 0.662820286 -1.28685391
-#> 14442 0 0.40077145 -1.26539635 16 sp_4 0.662820286 -1.28685391
-#> 14452 1 0.40077145 -1.26539635 1 sp_5 0.662820286 -1.28685391
-#> 14462 1 0.40077145 -1.26539635 12 sp_6 0.662820286 -1.28685391
-#> 14472 0 0.40077145 -1.26539635 18 sp_7 0.662820286 -1.28685391
-#> 14482 1 0.40077145 -1.26539635 14 sp_8 0.662820286 -1.28685391
-#> 14492 1 0.40077145 -1.26539635 8 sp_9 0.662820286 -1.28685391
-#> 14502 1 0.40077145 -1.26539635 5 sp_10 0.662820286 -1.28685391
-#> 14513 1 0.40077145 -1.26539635 17 sp_11 0.662820286 -1.28685391
-#> 14522 1 0.40077145 -1.26539635 11 sp_12 0.662820286 -1.28685391
-#> 14532 1 0.40077145 -1.26539635 4 sp_13 0.662820286 -1.28685391
-#> 14542 1 0.40077145 -1.26539635 13 sp_14 0.662820286 -1.28685391
-#> 14552 1 0.40077145 -1.26539635 8 sp_15 0.662820286 -1.28685391
-#> 14562 0 0.40077145 -1.26539635 15 sp_16 0.662820286 -1.28685391
-#> 14572 0 0.40077145 -1.26539635 4 sp_17 0.662820286 -1.28685391
-#> 14582 0 0.40077145 -1.26539635 13 sp_18 0.662820286 -1.28685391
-#> 14592 0 0.40077145 -1.26539635 3 sp_19 0.662820286 -1.28685391
-#> 14602 1 0.40077145 -1.26539635 7 sp_20 0.662820286 -1.28685391
-#> 14613 1 0.40077145 -1.26539635 1 sp_21 0.662820286 -1.28685391
-#> 14622 0 0.40077145 -1.26539635 6 sp_22 0.662820286 -1.28685391
-#> 14632 1 0.40077145 -1.26539635 13 sp_23 0.662820286 -1.28685391
-#> 14642 0 0.40077145 -1.26539635 17 sp_24 0.662820286 -1.28685391
-#> 14652 0 0.40077145 -1.26539635 6 sp_25 0.662820286 -1.28685391
-#> 14662 1 0.40077145 -1.26539635 10 sp_26 0.662820286 -1.28685391
-#> 14672 0 0.40077145 -1.26539635 13 sp_27 0.662820286 -1.28685391
-#> 14682 0 0.40077145 -1.26539635 6 sp_28 0.662820286 -1.28685391
-#> 14692 1 0.40077145 -1.26539635 9 sp_29 0.662820286 -1.28685391
-#> 14702 0 0.40077145 -1.26539635 8 sp_30 0.662820286 -1.28685391
-#> 15612 0 0.11068272 2.16895597 1 sp_1 -0.082930960 -1.04260743
-#> 15622 0 0.11068272 2.16895597 16 sp_2 -0.082930960 -1.04260743
-#> 15632 0 0.11068272 2.16895597 2 sp_3 -0.082930960 -1.04260743
-#> 15642 0 0.11068272 2.16895597 8 sp_4 -0.082930960 -1.04260743
-#> 15652 0 0.11068272 2.16895597 14 sp_5 -0.082930960 -1.04260743
-#> 15662 0 0.11068272 2.16895597 12 sp_6 -0.082930960 -1.04260743
-#> 15672 0 0.11068272 2.16895597 8 sp_7 -0.082930960 -1.04260743
-#> 15682 0 0.11068272 2.16895597 9 sp_8 -0.082930960 -1.04260743
-#> 15692 0 0.11068272 2.16895597 8 sp_9 -0.082930960 -1.04260743
-#> 15702 0 0.11068272 2.16895597 9 sp_10 -0.082930960 -1.04260743
-#> 15712 0 0.11068272 2.16895597 20 sp_11 -0.082930960 -1.04260743
-#> 15722 0 0.11068272 2.16895597 1 sp_12 -0.082930960 -1.04260743
-#> 15732 0 0.11068272 2.16895597 3 sp_13 -0.082930960 -1.04260743
-#> 15742 0 0.11068272 2.16895597 8 sp_14 -0.082930960 -1.04260743
-#> 15752 0 0.11068272 2.16895597 2 sp_15 -0.082930960 -1.04260743
-#> 15762 0 0.11068272 2.16895597 1 sp_16 -0.082930960 -1.04260743
-#> 15772 0 0.11068272 2.16895597 9 sp_17 -0.082930960 -1.04260743
-#> 15782 0 0.11068272 2.16895597 7 sp_18 -0.082930960 -1.04260743
-#> 15792 0 0.11068272 2.16895597 13 sp_19 -0.082930960 -1.04260743
-#> 15802 0 0.11068272 2.16895597 20 sp_20 -0.082930960 -1.04260743
-#> 15812 0 0.11068272 2.16895597 14 sp_21 -0.082930960 -1.04260743
-#> 15822 0 0.11068272 2.16895597 16 sp_22 -0.082930960 -1.04260743
-#> 15832 0 0.11068272 2.16895597 7 sp_23 -0.082930960 -1.04260743
-#> 15842 0 0.11068272 2.16895597 4 sp_24 -0.082930960 -1.04260743
-#> 15852 0 0.11068272 2.16895597 13 sp_25 -0.082930960 -1.04260743
-#> 15862 0 0.11068272 2.16895597 12 sp_26 -0.082930960 -1.04260743
-#> 15872 0 0.11068272 2.16895597 13 sp_27 -0.082930960 -1.04260743
-#> 15882 0 0.11068272 2.16895597 20 sp_28 -0.082930960 -1.04260743
-#> 15892 0 0.11068272 2.16895597 10 sp_29 -0.082930960 -1.04260743
-#> 15902 0 0.11068272 2.16895597 9 sp_30 -0.082930960 -1.04260743
-#> 16812 0 -0.55584113 1.20796200 12 sp_1 -1.291495828 1.04828678
-#> 16822 0 -0.55584113 1.20796200 8 sp_2 -1.291495828 1.04828678
-#> 16832 0 -0.55584113 1.20796200 7 sp_3 -1.291495828 1.04828678
-#> 16842 0 -0.55584113 1.20796200 15 sp_4 -1.291495828 1.04828678
-#> 16852 0 -0.55584113 1.20796200 19 sp_5 -1.291495828 1.04828678
-#> 16862 0 -0.55584113 1.20796200 17 sp_6 -1.291495828 1.04828678
-#> 16872 0 -0.55584113 1.20796200 11 sp_7 -1.291495828 1.04828678
-#> 16882 0 -0.55584113 1.20796200 7 sp_8 -1.291495828 1.04828678
-#> 16892 0 -0.55584113 1.20796200 19 sp_9 -1.291495828 1.04828678
-#> 16902 0 -0.55584113 1.20796200 3 sp_10 -1.291495828 1.04828678
-#> 16912 0 -0.55584113 1.20796200 6 sp_11 -1.291495828 1.04828678
-#> 16922 0 -0.55584113 1.20796200 7 sp_12 -1.291495828 1.04828678
-#> 16932 0 -0.55584113 1.20796200 4 sp_13 -1.291495828 1.04828678
-#> 16942 1 -0.55584113 1.20796200 10 sp_14 -1.291495828 1.04828678
-#> 16952 0 -0.55584113 1.20796200 17 sp_15 -1.291495828 1.04828678
-#> 16962 0 -0.55584113 1.20796200 16 sp_16 -1.291495828 1.04828678
-#> 16972 0 -0.55584113 1.20796200 8 sp_17 -1.291495828 1.04828678
-#> 16982 0 -0.55584113 1.20796200 3 sp_18 -1.291495828 1.04828678
-#> 16992 0 -0.55584113 1.20796200 12 sp_19 -1.291495828 1.04828678
-#> 17002 0 -0.55584113 1.20796200 14 sp_20 -1.291495828 1.04828678
-#> 17012 0 -0.55584113 1.20796200 5 sp_21 -1.291495828 1.04828678
-#> 17022 0 -0.55584113 1.20796200 14 sp_22 -1.291495828 1.04828678
-#> 17032 0 -0.55584113 1.20796200 6 sp_23 -1.291495828 1.04828678
-#> 17042 0 -0.55584113 1.20796200 9 sp_24 -1.291495828 1.04828678
-#> 17052 0 -0.55584113 1.20796200 1 sp_25 -1.291495828 1.04828678
-#> 17062 0 -0.55584113 1.20796200 20 sp_26 -1.291495828 1.04828678
-#> 17072 0 -0.55584113 1.20796200 14 sp_27 -1.291495828 1.04828678
-#> 17082 0 -0.55584113 1.20796200 19 sp_28 -1.291495828 1.04828678
-#> 17092 0 -0.55584113 1.20796200 5 sp_29 -1.291495828 1.04828678
-#> 17102 0 -0.55584113 1.20796200 2 sp_30 -1.291495828 1.04828678
-#> 18012 0 1.78691314 -1.12310858 1 sp_1 0.292763360 -0.62291708
-#> 18022 1 1.78691314 -1.12310858 20 sp_2 0.292763360 -0.62291708
-#> 18032 1 1.78691314 -1.12310858 4 sp_3 0.292763360 -0.62291708
-#> 18042 1 1.78691314 -1.12310858 11 sp_4 0.292763360 -0.62291708
-#> 18052 1 1.78691314 -1.12310858 5 sp_5 0.292763360 -0.62291708
-#> 18062 0 1.78691314 -1.12310858 4 sp_6 0.292763360 -0.62291708
-#> 18072 1 1.78691314 -1.12310858 19 sp_7 0.292763360 -0.62291708
-#> 18082 0 1.78691314 -1.12310858 3 sp_8 0.292763360 -0.62291708
-#> 18092 0 1.78691314 -1.12310858 1 sp_9 0.292763360 -0.62291708
-#> 18102 1 1.78691314 -1.12310858 7 sp_10 0.292763360 -0.62291708
-#> 18112 1 1.78691314 -1.12310858 5 sp_11 0.292763360 -0.62291708
-#> 18122 1 1.78691314 -1.12310858 9 sp_12 0.292763360 -0.62291708
-#> 18132 1 1.78691314 -1.12310858 17 sp_13 0.292763360 -0.62291708
-#> 18142 1 1.78691314 -1.12310858 5 sp_14 0.292763360 -0.62291708
-#> 18152 1 1.78691314 -1.12310858 12 sp_15 0.292763360 -0.62291708
-#> 18162 1 1.78691314 -1.12310858 2 sp_16 0.292763360 -0.62291708
-#> 18172 1 1.78691314 -1.12310858 18 sp_17 0.292763360 -0.62291708
-#> 18182 1 1.78691314 -1.12310858 4 sp_18 0.292763360 -0.62291708
-#> 18192 1 1.78691314 -1.12310858 10 sp_19 0.292763360 -0.62291708
-#> 18202 0 1.78691314 -1.12310858 15 sp_20 0.292763360 -0.62291708
-#> 18212 1 1.78691314 -1.12310858 8 sp_21 0.292763360 -0.62291708
-#> 18222 1 1.78691314 -1.12310858 1 sp_22 0.292763360 -0.62291708
-#> 18232 1 1.78691314 -1.12310858 11 sp_23 0.292763360 -0.62291708
-#> 18242 1 1.78691314 -1.12310858 5 sp_24 0.292763360 -0.62291708
-#> 18252 1 1.78691314 -1.12310858 11 sp_25 0.292763360 -0.62291708
-#> 18262 1 1.78691314 -1.12310858 15 sp_26 0.292763360 -0.62291708
-#> 18272 0 1.78691314 -1.12310858 15 sp_27 0.292763360 -0.62291708
-#> 18282 1 1.78691314 -1.12310858 10 sp_28 0.292763360 -0.62291708
-#> 18292 0 1.78691314 -1.12310858 15 sp_29 0.292763360 -0.62291708
-#> 18302 1 1.78691314 -1.12310858 15 sp_30 0.292763360 -0.62291708
-#> 19212 1 0.49785048 -0.40288484 20 sp_1 -0.097909392 1.70873840
-#> 19222 1 0.49785048 -0.40288484 12 sp_2 -0.097909392 1.70873840
-#> 19232 0 0.49785048 -0.40288484 9 sp_3 -0.097909392 1.70873840
-#> 19242 0 0.49785048 -0.40288484 4 sp_4 -0.097909392 1.70873840
-#> 19252 0 0.49785048 -0.40288484 3 sp_5 -0.097909392 1.70873840
-#> 19262 0 0.49785048 -0.40288484 7 sp_6 -0.097909392 1.70873840
-#> 19272 0 0.49785048 -0.40288484 4 sp_7 -0.097909392 1.70873840
-#> 19282 0 0.49785048 -0.40288484 8 sp_8 -0.097909392 1.70873840
-#> 19292 0 0.49785048 -0.40288484 5 sp_9 -0.097909392 1.70873840
-#> 19302 0 0.49785048 -0.40288484 6 sp_10 -0.097909392 1.70873840
-#> 19312 0 0.49785048 -0.40288484 4 sp_11 -0.097909392 1.70873840
-#> 19322 1 0.49785048 -0.40288484 3 sp_12 -0.097909392 1.70873840
-#> 19332 0 0.49785048 -0.40288484 11 sp_13 -0.097909392 1.70873840
-#> 19342 0 0.49785048 -0.40288484 10 sp_14 -0.097909392 1.70873840
-#> 19352 0 0.49785048 -0.40288484 5 sp_15 -0.097909392 1.70873840
-#> 19362 0 0.49785048 -0.40288484 11 sp_16 -0.097909392 1.70873840
-#> 19372 0 0.49785048 -0.40288484 10 sp_17 -0.097909392 1.70873840
-#> 19382 0 0.49785048 -0.40288484 15 sp_18 -0.097909392 1.70873840
-#> 19392 0 0.49785048 -0.40288484 19 sp_19 -0.097909392 1.70873840
-#> 19402 0 0.49785048 -0.40288484 10 sp_20 -0.097909392 1.70873840
-#> 19412 0 0.49785048 -0.40288484 13 sp_21 -0.097909392 1.70873840
-#> 19422 0 0.49785048 -0.40288484 3 sp_22 -0.097909392 1.70873840
-#> 19432 0 0.49785048 -0.40288484 18 sp_23 -0.097909392 1.70873840
-#> 19442 0 0.49785048 -0.40288484 10 sp_24 -0.097909392 1.70873840
-#> 19452 0 0.49785048 -0.40288484 8 sp_25 -0.097909392 1.70873840
-#> 19462 1 0.49785048 -0.40288484 12 sp_26 -0.097909392 1.70873840
-#> 19472 0 0.49785048 -0.40288484 10 sp_27 -0.097909392 1.70873840
-#> 19482 0 0.49785048 -0.40288484 7 sp_28 -0.097909392 1.70873840
-#> 19492 0 0.49785048 -0.40288484 7 sp_29 -0.097909392 1.70873840
-#> 19502 0 0.49785048 -0.40288484 6 sp_30 -0.097909392 1.70873840
-#> 20412 0 -1.96661716 -0.46665535 17 sp_1 1.597746035 0.50850841
-#> 20422 0 -1.96661716 -0.46665535 20 sp_2 1.597746035 0.50850841
-#> 20432 0 -1.96661716 -0.46665535 1 sp_3 1.597746035 0.50850841
-#> 20442 0 -1.96661716 -0.46665535 5 sp_4 1.597746035 0.50850841
-#> 20452 0 -1.96661716 -0.46665535 10 sp_5 1.597746035 0.50850841
-#> 20462 0 -1.96661716 -0.46665535 13 sp_6 1.597746035 0.50850841
-#> 20472 1 -1.96661716 -0.46665535 10 sp_7 1.597746035 0.50850841
-#> 20482 0 -1.96661716 -0.46665535 2 sp_8 1.597746035 0.50850841
-#> 20492 0 -1.96661716 -0.46665535 15 sp_9 1.597746035 0.50850841
-#> 20502 0 -1.96661716 -0.46665535 15 sp_10 1.597746035 0.50850841
-#> 20512 0 -1.96661716 -0.46665535 8 sp_11 1.597746035 0.50850841
-#> 20522 0 -1.96661716 -0.46665535 3 sp_12 1.597746035 0.50850841
-#> 20532 0 -1.96661716 -0.46665535 2 sp_13 1.597746035 0.50850841
-#> 20542 0 -1.96661716 -0.46665535 6 sp_14 1.597746035 0.50850841
-#> 20552 0 -1.96661716 -0.46665535 14 sp_15 1.597746035 0.50850841
-#> 20562 0 -1.96661716 -0.46665535 15 sp_16 1.597746035 0.50850841
-#> 20572 0 -1.96661716 -0.46665535 19 sp_17 1.597746035 0.50850841
-#> 20582 0 -1.96661716 -0.46665535 9 sp_18 1.597746035 0.50850841
-#> 20592 0 -1.96661716 -0.46665535 15 sp_19 1.597746035 0.50850841
-#> 20602 0 -1.96661716 -0.46665535 16 sp_20 1.597746035 0.50850841
-#> 20612 0 -1.96661716 -0.46665535 8 sp_21 1.597746035 0.50850841
-#> 20622 0 -1.96661716 -0.46665535 9 sp_22 1.597746035 0.50850841
-#> 20632 0 -1.96661716 -0.46665535 16 sp_23 1.597746035 0.50850841
-#> 20642 0 -1.96661716 -0.46665535 9 sp_24 1.597746035 0.50850841
-#> 20652 0 -1.96661716 -0.46665535 2 sp_25 1.597746035 0.50850841
-#> 20662 0 -1.96661716 -0.46665535 9 sp_26 1.597746035 0.50850841
-#> 20672 0 -1.96661716 -0.46665535 11 sp_27 1.597746035 0.50850841
-#> 20682 0 -1.96661716 -0.46665535 11 sp_28 1.597746035 0.50850841
-#> 20692 0 -1.96661716 -0.46665535 4 sp_29 1.597746035 0.50850841
-#> 20702 0 -1.96661716 -0.46665535 7 sp_30 1.597746035 0.50850841
-#> 21612 0 0.70135590 0.77996512 18 sp_1 -0.925654688 0.27650993
-#> 21622 0 0.70135590 0.77996512 11 sp_2 -0.925654688 0.27650993
-#> 21632 0 0.70135590 0.77996512 1 sp_3 -0.925654688 0.27650993
-#> 21642 0 0.70135590 0.77996512 11 sp_4 -0.925654688 0.27650993
-#> 21652 0 0.70135590 0.77996512 6 sp_5 -0.925654688 0.27650993
-#> 21662 0 0.70135590 0.77996512 10 sp_6 -0.925654688 0.27650993
-#> 21672 0 0.70135590 0.77996512 18 sp_7 -0.925654688 0.27650993
-#> 21682 0 0.70135590 0.77996512 3 sp_8 -0.925654688 0.27650993
-#> 21692 0 0.70135590 0.77996512 3 sp_9 -0.925654688 0.27650993
-#> 21702 1 0.70135590 0.77996512 2 sp_10 -0.925654688 0.27650993
-#> 21712 0 0.70135590 0.77996512 8 sp_11 -0.925654688 0.27650993
-#> 21722 0 0.70135590 0.77996512 13 sp_12 -0.925654688 0.27650993
-#> 21732 0 0.70135590 0.77996512 8 sp_13 -0.925654688 0.27650993
-#> 21742 0 0.70135590 0.77996512 2 sp_14 -0.925654688 0.27650993
-#> 21752 0 0.70135590 0.77996512 6 sp_15 -0.925654688 0.27650993
-#> 21762 0 0.70135590 0.77996512 17 sp_16 -0.925654688 0.27650993
-#> 21772 0 0.70135590 0.77996512 14 sp_17 -0.925654688 0.27650993
-#> 21782 0 0.70135590 0.77996512 7 sp_18 -0.925654688 0.27650993
-#> 21792 0 0.70135590 0.77996512 13 sp_19 -0.925654688 0.27650993
-#> 21802 0 0.70135590 0.77996512 8 sp_20 -0.925654688 0.27650993
-#> 21812 0 0.70135590 0.77996512 6 sp_21 -0.925654688 0.27650993
-#> 21822 0 0.70135590 0.77996512 11 sp_22 -0.925654688 0.27650993
-#> 21832 0 0.70135590 0.77996512 10 sp_23 -0.925654688 0.27650993
-#> 21842 0 0.70135590 0.77996512 17 sp_24 -0.925654688 0.27650993
-#> 21852 0 0.70135590 0.77996512 7 sp_25 -0.925654688 0.27650993
-#> 21862 0 0.70135590 0.77996512 12 sp_26 -0.925654688 0.27650993
-#> 21872 0 0.70135590 0.77996512 19 sp_27 -0.925654688 0.27650993
-#> 21882 0 0.70135590 0.77996512 17 sp_28 -0.925654688 0.27650993
-#> 21892 0 0.70135590 0.77996512 8 sp_29 -0.925654688 0.27650993
-#> 21902 0 0.70135590 0.77996512 15 sp_30 -0.925654688 0.27650993
-#> 22812 0 -0.47279141 -0.08336907 14 sp_1 0.840684900 1.39791523
-#> 22822 0 -0.47279141 -0.08336907 14 sp_2 0.840684900 1.39791523
-#> 22832 0 -0.47279141 -0.08336907 17 sp_3 0.840684900 1.39791523
-#> 22842 0 -0.47279141 -0.08336907 1 sp_4 0.840684900 1.39791523
-#> 22852 0 -0.47279141 -0.08336907 18 sp_5 0.840684900 1.39791523
-#> 22862 0 -0.47279141 -0.08336907 18 sp_6 0.840684900 1.39791523
-#> 22872 1 -0.47279141 -0.08336907 20 sp_7 0.840684900 1.39791523
-#> 22882 0 -0.47279141 -0.08336907 10 sp_8 0.840684900 1.39791523
-#> 22892 0 -0.47279141 -0.08336907 10 sp_9 0.840684900 1.39791523
-#> 22902 0 -0.47279141 -0.08336907 9 sp_10 0.840684900 1.39791523
-#> 22912 0 -0.47279141 -0.08336907 19 sp_11 0.840684900 1.39791523
-#> 22922 0 -0.47279141 -0.08336907 18 sp_12 0.840684900 1.39791523
-#> 22932 0 -0.47279141 -0.08336907 18 sp_13 0.840684900 1.39791523
-#> 22942 0 -0.47279141 -0.08336907 12 sp_14 0.840684900 1.39791523
-#> 22952 0 -0.47279141 -0.08336907 12 sp_15 0.840684900 1.39791523
-#> 22962 0 -0.47279141 -0.08336907 4 sp_16 0.840684900 1.39791523
-#> 22972 0 -0.47279141 -0.08336907 20 sp_17 0.840684900 1.39791523
-#> 22982 0 -0.47279141 -0.08336907 10 sp_18 0.840684900 1.39791523
-#> 22992 0 -0.47279141 -0.08336907 5 sp_19 0.840684900 1.39791523
-#> 23002 1 -0.47279141 -0.08336907 2 sp_20 0.840684900 1.39791523
-#> 23012 0 -0.47279141 -0.08336907 18 sp_21 0.840684900 1.39791523
-#> 23022 1 -0.47279141 -0.08336907 12 sp_22 0.840684900 1.39791523
-#> 23032 0 -0.47279141 -0.08336907 13 sp_23 0.840684900 1.39791523
-#> 23042 0 -0.47279141 -0.08336907 11 sp_24 0.840684900 1.39791523
-#> 23052 0 -0.47279141 -0.08336907 19 sp_25 0.840684900 1.39791523
-#> 23062 0 -0.47279141 -0.08336907 6 sp_26 0.840684900 1.39791523
-#> 23072 0 -0.47279141 -0.08336907 18 sp_27 0.840684900 1.39791523
-#> 23082 0 -0.47279141 -0.08336907 10 sp_28 0.840684900 1.39791523
-#> 23092 0 -0.47279141 -0.08336907 9 sp_29 0.840684900 1.39791523
-#> 23102 0 -0.47279141 -0.08336907 3 sp_30 0.840684900 1.39791523
-#> 24012 0 -1.06782371 0.25331851 19 sp_1 -0.641055073 -1.70788764
-#> 24022 0 -1.06782371 0.25331851 8 sp_2 -0.641055073 -1.70788764
-#> 24032 0 -1.06782371 0.25331851 13 sp_3 -0.641055073 -1.70788764
-#> 24042 0 -1.06782371 0.25331851 1 sp_4 -0.641055073 -1.70788764
-#> 24052 1 -1.06782371 0.25331851 2 sp_5 -0.641055073 -1.70788764
-#> 24062 1 -1.06782371 0.25331851 11 sp_6 -0.641055073 -1.70788764
-#> 24072 0 -1.06782371 0.25331851 16 sp_7 -0.641055073 -1.70788764
-#> 24082 0 -1.06782371 0.25331851 5 sp_8 -0.641055073 -1.70788764
-#> 24092 0 -1.06782371 0.25331851 4 sp_9 -0.641055073 -1.70788764
-#> 24102 0 -1.06782371 0.25331851 3 sp_10 -0.641055073 -1.70788764
-#> 24113 0 -1.06782371 0.25331851 15 sp_11 -0.641055073 -1.70788764
-#> 24122 0 -1.06782371 0.25331851 10 sp_12 -0.641055073 -1.70788764
-#> 24132 0 -1.06782371 0.25331851 7 sp_13 -0.641055073 -1.70788764
-#> 24142 0 -1.06782371 0.25331851 7 sp_14 -0.641055073 -1.70788764
-#> 24152 0 -1.06782371 0.25331851 2 sp_15 -0.641055073 -1.70788764
-#> 24162 0 -1.06782371 0.25331851 18 sp_16 -0.641055073 -1.70788764
-#> 24172 0 -1.06782371 0.25331851 18 sp_17 -0.641055073 -1.70788764
-#> 24182 0 -1.06782371 0.25331851 3 sp_18 -0.641055073 -1.70788764
-#> 24192 0 -1.06782371 0.25331851 8 sp_19 -0.641055073 -1.70788764
-#> 24202 0 -1.06782371 0.25331851 14 sp_20 -0.641055073 -1.70788764
-#> 24213 0 -1.06782371 0.25331851 9 sp_21 -0.641055073 -1.70788764
-#> 24222 0 -1.06782371 0.25331851 15 sp_22 -0.641055073 -1.70788764
-#> 24232 0 -1.06782371 0.25331851 17 sp_23 -0.641055073 -1.70788764
-#> 24242 0 -1.06782371 0.25331851 7 sp_24 -0.641055073 -1.70788764
-#> 24252 0 -1.06782371 0.25331851 8 sp_25 -0.641055073 -1.70788764
-#> 24262 0 -1.06782371 0.25331851 1 sp_26 -0.641055073 -1.70788764
-#> 24272 0 -1.06782371 0.25331851 9 sp_27 -0.641055073 -1.70788764
-#> 24282 0 -1.06782371 0.25331851 3 sp_28 -0.641055073 -1.70788764
-#> 24292 0 -1.06782371 0.25331851 2 sp_29 -0.641055073 -1.70788764
-#> 24302 0 -1.06782371 0.25331851 11 sp_30 -0.641055073 -1.70788764
-#> 25213 0 -0.21797491 -0.02854676 4 sp_1 -1.458915620 1.04822440
-#> 25222 0 -0.21797491 -0.02854676 8 sp_2 -1.458915620 1.04822440
-#> 25232 0 -0.21797491 -0.02854676 20 sp_3 -1.458915620 1.04822440
-#> 25242 0 -0.21797491 -0.02854676 11 sp_4 -1.458915620 1.04822440
-#> 25252 0 -0.21797491 -0.02854676 18 sp_5 -1.458915620 1.04822440
-#> 25262 0 -0.21797491 -0.02854676 14 sp_6 -1.458915620 1.04822440
-#> 25272 0 -0.21797491 -0.02854676 3 sp_7 -1.458915620 1.04822440
-#> 25282 0 -0.21797491 -0.02854676 3 sp_8 -1.458915620 1.04822440
-#> 25292 0 -0.21797491 -0.02854676 14 sp_9 -1.458915620 1.04822440
-#> 25302 0 -0.21797491 -0.02854676 7 sp_10 -1.458915620 1.04822440
-#> 25313 0 -0.21797491 -0.02854676 15 sp_11 -1.458915620 1.04822440
-#> 25322 0 -0.21797491 -0.02854676 8 sp_12 -1.458915620 1.04822440
-#> 25332 0 -0.21797491 -0.02854676 1 sp_13 -1.458915620 1.04822440
-#> 25342 0 -0.21797491 -0.02854676 5 sp_14 -1.458915620 1.04822440
-#> 25352 0 -0.21797491 -0.02854676 17 sp_15 -1.458915620 1.04822440
-#> 25362 0 -0.21797491 -0.02854676 6 sp_16 -1.458915620 1.04822440
-#> 25372 0 -0.21797491 -0.02854676 10 sp_17 -1.458915620 1.04822440
-#> 25382 0 -0.21797491 -0.02854676 12 sp_18 -1.458915620 1.04822440
-#> 25392 0 -0.21797491 -0.02854676 8 sp_19 -1.458915620 1.04822440
-#> 25402 0 -0.21797491 -0.02854676 16 sp_20 -1.458915620 1.04822440
-#> 25413 0 -0.21797491 -0.02854676 7 sp_21 -1.458915620 1.04822440
-#> 25422 0 -0.21797491 -0.02854676 7 sp_22 -1.458915620 1.04822440
-#> 25432 0 -0.21797491 -0.02854676 1 sp_23 -1.458915620 1.04822440
-#> 25442 0 -0.21797491 -0.02854676 11 sp_24 -1.458915620 1.04822440
-#> 25452 0 -0.21797491 -0.02854676 3 sp_25 -1.458915620 1.04822440
-#> 25462 0 -0.21797491 -0.02854676 17 sp_26 -1.458915620 1.04822440
-#> 25472 0 -0.21797491 -0.02854676 20 sp_27 -1.458915620 1.04822440
-#> 25482 0 -0.21797491 -0.02854676 3 sp_28 -1.458915620 1.04822440
-#> 25492 0 -0.21797491 -0.02854676 14 sp_29 -1.458915620 1.04822440
-#> 25502 0 -0.21797491 -0.02854676 5 sp_30 -1.458915620 1.04822440
-#> 26413 0 -1.02600445 -0.04287046 18 sp_1 1.177817761 1.66494265
-#> 26422 0 -1.02600445 -0.04287046 8 sp_2 1.177817761 1.66494265
-#> 26432 0 -1.02600445 -0.04287046 20 sp_3 1.177817761 1.66494265
-#> 26442 0 -1.02600445 -0.04287046 10 sp_4 1.177817761 1.66494265
-#> 26452 0 -1.02600445 -0.04287046 18 sp_5 1.177817761 1.66494265
-#> 26462 0 -1.02600445 -0.04287046 17 sp_6 1.177817761 1.66494265
-#> 26472 0 -1.02600445 -0.04287046 9 sp_7 1.177817761 1.66494265
-#> 26482 0 -1.02600445 -0.04287046 3 sp_8 1.177817761 1.66494265
-#> 26492 0 -1.02600445 -0.04287046 5 sp_9 1.177817761 1.66494265
-#> 26502 0 -1.02600445 -0.04287046 16 sp_10 1.177817761 1.66494265
-#> 26513 0 -1.02600445 -0.04287046 20 sp_11 1.177817761 1.66494265
-#> 26522 0 -1.02600445 -0.04287046 3 sp_12 1.177817761 1.66494265
-#> 26532 0 -1.02600445 -0.04287046 3 sp_13 1.177817761 1.66494265
-#> 26542 0 -1.02600445 -0.04287046 13 sp_14 1.177817761 1.66494265
-#> 26552 0 -1.02600445 -0.04287046 4 sp_15 1.177817761 1.66494265
-#> 26562 0 -1.02600445 -0.04287046 15 sp_16 1.177817761 1.66494265
-#> 26572 0 -1.02600445 -0.04287046 19 sp_17 1.177817761 1.66494265
-#> 26582 0 -1.02600445 -0.04287046 13 sp_18 1.177817761 1.66494265
-#> 26592 1 -1.02600445 -0.04287046 12 sp_19 1.177817761 1.66494265
-#> 26602 0 -1.02600445 -0.04287046 20 sp_20 1.177817761 1.66494265
-#> 26613 0 -1.02600445 -0.04287046 13 sp_21 1.177817761 1.66494265
-#> 26622 0 -1.02600445 -0.04287046 13 sp_22 1.177817761 1.66494265
-#> 26632 0 -1.02600445 -0.04287046 3 sp_23 1.177817761 1.66494265
-#> 26642 0 -1.02600445 -0.04287046 20 sp_24 1.177817761 1.66494265
-#> 26652 0 -1.02600445 -0.04287046 5 sp_25 1.177817761 1.66494265
-#> 26662 0 -1.02600445 -0.04287046 13 sp_26 1.177817761 1.66494265
-#> 26672 0 -1.02600445 -0.04287046 12 sp_27 1.177817761 1.66494265
-#> 26682 0 -1.02600445 -0.04287046 8 sp_28 1.177817761 1.66494265
-#> 26692 0 -1.02600445 -0.04287046 6 sp_29 1.177817761 1.66494265
-#> 26702 0 -1.02600445 -0.04287046 16 sp_30 1.177817761 1.66494265
-#> 27612 0 -0.72889123 1.36860228 11 sp_1 -2.279219585 -0.95179699
-#> 27622 0 -0.72889123 1.36860228 12 sp_2 -2.279219585 -0.95179699
-#> 27632 0 -0.72889123 1.36860228 16 sp_3 -2.279219585 -0.95179699
-#> 27642 0 -0.72889123 1.36860228 15 sp_4 -2.279219585 -0.95179699
-#> 27652 0 -0.72889123 1.36860228 1 sp_5 -2.279219585 -0.95179699
-#> 27662 0 -0.72889123 1.36860228 12 sp_6 -2.279219585 -0.95179699
-#> 27672 0 -0.72889123 1.36860228 10 sp_7 -2.279219585 -0.95179699
-#> 27682 0 -0.72889123 1.36860228 10 sp_8 -2.279219585 -0.95179699
-#> 27692 0 -0.72889123 1.36860228 4 sp_9 -2.279219585 -0.95179699
-#> 27702 0 -0.72889123 1.36860228 9 sp_10 -2.279219585 -0.95179699
-#> 27712 0 -0.72889123 1.36860228 20 sp_11 -2.279219585 -0.95179699
-#> 27722 0 -0.72889123 1.36860228 5 sp_12 -2.279219585 -0.95179699
-#> 27732 0 -0.72889123 1.36860228 9 sp_13 -2.279219585 -0.95179699
-#> 27742 0 -0.72889123 1.36860228 19 sp_14 -2.279219585 -0.95179699
-#> 27752 0 -0.72889123 1.36860228 3 sp_15 -2.279219585 -0.95179699
-#> 27762 0 -0.72889123 1.36860228 2 sp_16 -2.279219585 -0.95179699
-#> 27772 0 -0.72889123 1.36860228 12 sp_17 -2.279219585 -0.95179699
-#> 27782 0 -0.72889123 1.36860228 15 sp_18 -2.279219585 -0.95179699
-#> 27792 0 -0.72889123 1.36860228 17 sp_19 -2.279219585 -0.95179699
-#> 27802 0 -0.72889123 1.36860228 3 sp_20 -2.279219585 -0.95179699
-#> 27812 0 -0.72889123 1.36860228 7 sp_21 -2.279219585 -0.95179699
-#> 27822 0 -0.72889123 1.36860228 13 sp_22 -2.279219585 -0.95179699
-#> 27832 0 -0.72889123 1.36860228 14 sp_23 -2.279219585 -0.95179699
-#> 27842 0 -0.72889123 1.36860228 2 sp_24 -2.279219585 -0.95179699
-#> 27852 0 -0.72889123 1.36860228 9 sp_25 -2.279219585 -0.95179699
-#> 27862 0 -0.72889123 1.36860228 15 sp_26 -2.279219585 -0.95179699
-#> 27872 0 -0.72889123 1.36860228 1 sp_27 -2.279219585 -0.95179699
-#> 27882 0 -0.72889123 1.36860228 10 sp_28 -2.279219585 -0.95179699
-#> 27892 0 -0.72889123 1.36860228 9 sp_29 -2.279219585 -0.95179699
-#> 27902 0 -0.72889123 1.36860228 9 sp_30 -2.279219585 -0.95179699
-#> 28812 0 -0.62503927 -0.22577099 7 sp_1 0.272207845 -0.27955386
-#> 28822 1 -0.62503927 -0.22577099 18 sp_2 0.272207845 -0.27955386
-#> 28832 1 -0.62503927 -0.22577099 12 sp_3 0.272207845 -0.27955386
-#> 28842 0 -0.62503927 -0.22577099 6 sp_4 0.272207845 -0.27955386
-#> 28852 0 -0.62503927 -0.22577099 7 sp_5 0.272207845 -0.27955386
-#> 28862 0 -0.62503927 -0.22577099 16 sp_6 0.272207845 -0.27955386
-#> 28872 0 -0.62503927 -0.22577099 16 sp_7 0.272207845 -0.27955386
-#> 28882 0 -0.62503927 -0.22577099 2 sp_8 0.272207845 -0.27955386
-#> 28892 0 -0.62503927 -0.22577099 2 sp_9 0.272207845 -0.27955386
-#> 28902 0 -0.62503927 -0.22577099 14 sp_10 0.272207845 -0.27955386
-#> 28912 0 -0.62503927 -0.22577099 7 sp_11 0.272207845 -0.27955386
-#> 28922 0 -0.62503927 -0.22577099 6 sp_12 0.272207845 -0.27955386
-#> 28932 0 -0.62503927 -0.22577099 4 sp_13 0.272207845 -0.27955386
-#> 28942 0 -0.62503927 -0.22577099 3 sp_14 0.272207845 -0.27955386
-#> 28952 0 -0.62503927 -0.22577099 14 sp_15 0.272207845 -0.27955386
-#> 28962 0 -0.62503927 -0.22577099 19 sp_16 0.272207845 -0.27955386
-#> 28972 1 -0.62503927 -0.22577099 14 sp_17 0.272207845 -0.27955386
-#> 28982 0 -0.62503927 -0.22577099 16 sp_18 0.272207845 -0.27955386
-#> 28992 0 -0.62503927 -0.22577099 10 sp_19 0.272207845 -0.27955386
-#> 29002 0 -0.62503927 -0.22577099 12 sp_20 0.272207845 -0.27955386
-#> 29012 0 -0.62503927 -0.22577099 18 sp_21 0.272207845 -0.27955386
-#> 29022 0 -0.62503927 -0.22577099 3 sp_22 0.272207845 -0.27955386
-#> 29032 0 -0.62503927 -0.22577099 1 sp_23 0.272207845 -0.27955386
-#> 29042 1 -0.62503927 -0.22577099 12 sp_24 0.272207845 -0.27955386
-#> 29052 0 -0.62503927 -0.22577099 17 sp_25 0.272207845 -0.27955386
-#> 29062 0 -0.62503927 -0.22577099 1 sp_26 0.272207845 -0.27955386
-#> 29072 0 -0.62503927 -0.22577099 4 sp_27 0.272207845 -0.27955386
-#> 29082 0 -0.62503927 -0.22577099 19 sp_28 0.272207845 -0.27955386
-#> 29092 0 -0.62503927 -0.22577099 13 sp_29 0.272207845 -0.27955386
-#> 29102 0 -0.62503927 -0.22577099 18 sp_30 0.272207845 -0.27955386
-#> 30012 1 -1.68669331 1.51647060 15 sp_1 0.551074369 0.40090658
-#> 30022 0 -1.68669331 1.51647060 13 sp_2 0.551074369 0.40090658
-#> 30032 0 -1.68669331 1.51647060 14 sp_3 0.551074369 0.40090658
-#> 30042 0 -1.68669331 1.51647060 18 sp_4 0.551074369 0.40090658
-#> 30052 0 -1.68669331 1.51647060 12 sp_5 0.551074369 0.40090658
-#> 30062 0 -1.68669331 1.51647060 18 sp_6 0.551074369 0.40090658
-#> 30072 0 -1.68669331 1.51647060 7 sp_7 0.551074369 0.40090658
-#> 30082 0 -1.68669331 1.51647060 4 sp_8 0.551074369 0.40090658
-#> 30092 0 -1.68669331 1.51647060 4 sp_9 0.551074369 0.40090658
-#> 30102 0 -1.68669331 1.51647060 3 sp_10 0.551074369 0.40090658
-#> 30112 0 -1.68669331 1.51647060 11 sp_11 0.551074369 0.40090658
-#> 30122 0 -1.68669331 1.51647060 19 sp_12 0.551074369 0.40090658
-#> 30132 0 -1.68669331 1.51647060 16 sp_13 0.551074369 0.40090658
-#> 30142 0 -1.68669331 1.51647060 15 sp_14 0.551074369 0.40090658
-#> 30152 0 -1.68669331 1.51647060 11 sp_15 0.551074369 0.40090658
-#> 30162 0 -1.68669331 1.51647060 6 sp_16 0.551074369 0.40090658
-#> 30172 0 -1.68669331 1.51647060 5 sp_17 0.551074369 0.40090658
-#> 30182 0 -1.68669331 1.51647060 2 sp_18 0.551074369 0.40090658
-#> 30192 0 -1.68669331 1.51647060 17 sp_19 0.551074369 0.40090658
-#> 30202 0 -1.68669331 1.51647060 5 sp_20 0.551074369 0.40090658
-#> 30212 0 -1.68669331 1.51647060 19 sp_21 0.551074369 0.40090658
-#> 30222 0 -1.68669331 1.51647060 15 sp_22 0.551074369 0.40090658
-#> 30232 0 -1.68669331 1.51647060 19 sp_23 0.551074369 0.40090658
-#> 30242 0 -1.68669331 1.51647060 3 sp_24 0.551074369 0.40090658
-#> 30252 0 -1.68669331 1.51647060 15 sp_25 0.551074369 0.40090658
-#> 30262 0 -1.68669331 1.51647060 3 sp_26 0.551074369 0.40090658
-#> 30272 1 -1.68669331 1.51647060 2 sp_27 0.551074369 0.40090658
-#> 30282 0 -1.68669331 1.51647060 5 sp_28 0.551074369 0.40090658
-#> 30292 0 -1.68669331 1.51647060 5 sp_29 0.551074369 0.40090658
-#> 30302 0 -1.68669331 1.51647060 7 sp_30 0.551074369 0.40090658
-#> 31212 1 0.83778704 -1.54875280 2 sp_1 0.404754544 -1.40022373
-#> 31222 1 0.83778704 -1.54875280 16 sp_2 0.404754544 -1.40022373
-#> 31232 0 0.83778704 -1.54875280 8 sp_3 0.404754544 -1.40022373
-#> 31242 0 0.83778704 -1.54875280 18 sp_4 0.404754544 -1.40022373
-#> 31252 1 0.83778704 -1.54875280 19 sp_5 0.404754544 -1.40022373
-#> 31262 1 0.83778704 -1.54875280 9 sp_6 0.404754544 -1.40022373
-#> 31272 1 0.83778704 -1.54875280 19 sp_7 0.404754544 -1.40022373
-#> 31282 1 0.83778704 -1.54875280 14 sp_8 0.404754544 -1.40022373
-#> 31292 1 0.83778704 -1.54875280 19 sp_9 0.404754544 -1.40022373
-#> 31302 0 0.83778704 -1.54875280 5 sp_10 0.404754544 -1.40022373
-#> 31312 0 0.83778704 -1.54875280 13 sp_11 0.404754544 -1.40022373
-#> 31322 0 0.83778704 -1.54875280 16 sp_12 0.404754544 -1.40022373
-#> 31332 0 0.83778704 -1.54875280 7 sp_13 0.404754544 -1.40022373
-#> 31342 1 0.83778704 -1.54875280 8 sp_14 0.404754544 -1.40022373
-#> 31352 0 0.83778704 -1.54875280 16 sp_15 0.404754544 -1.40022373
-#> 31362 0 0.83778704 -1.54875280 15 sp_16 0.404754544 -1.40022373
-#> 31372 1 0.83778704 -1.54875280 20 sp_17 0.404754544 -1.40022373
-#> 31382 0 0.83778704 -1.54875280 3 sp_18 0.404754544 -1.40022373
-#> 31392 1 0.83778704 -1.54875280 17 sp_19 0.404754544 -1.40022373
-#> 31402 1 0.83778704 -1.54875280 7 sp_20 0.404754544 -1.40022373
-#> 31412 0 0.83778704 -1.54875280 13 sp_21 0.404754544 -1.40022373
-#> 31422 1 0.83778704 -1.54875280 3 sp_22 0.404754544 -1.40022373
-#> 31432 0 0.83778704 -1.54875280 13 sp_23 0.404754544 -1.40022373
-#> 31442 1 0.83778704 -1.54875280 14 sp_24 0.404754544 -1.40022373
-#> 31452 0 0.83778704 -1.54875280 4 sp_25 0.404754544 -1.40022373
-#> 31462 1 0.83778704 -1.54875280 16 sp_26 0.404754544 -1.40022373
-#> 31472 1 0.83778704 -1.54875280 9 sp_27 0.404754544 -1.40022373
-#> 31482 0 0.83778704 -1.54875280 16 sp_28 0.404754544 -1.40022373
-#> 31492 0 0.83778704 -1.54875280 9 sp_29 0.404754544 -1.40022373
-#> 31502 1 0.83778704 -1.54875280 5 sp_30 0.404754544 -1.40022373
-#> 32412 0 0.15337312 0.58461375 14 sp_1 -0.603832898 0.15166108
-#> 32422 0 0.15337312 0.58461375 12 sp_2 -0.603832898 0.15166108
-#> 32432 0 0.15337312 0.58461375 14 sp_3 -0.603832898 0.15166108
-#> 32442 0 0.15337312 0.58461375 13 sp_4 -0.603832898 0.15166108
-#> 32452 1 0.15337312 0.58461375 20 sp_5 -0.603832898 0.15166108
-#> 32462 0 0.15337312 0.58461375 15 sp_6 -0.603832898 0.15166108
-#> 32472 0 0.15337312 0.58461375 8 sp_7 -0.603832898 0.15166108
-#> 32482 0 0.15337312 0.58461375 13 sp_8 -0.603832898 0.15166108
-#> 32492 0 0.15337312 0.58461375 7 sp_9 -0.603832898 0.15166108
-#> 32502 0 0.15337312 0.58461375 5 sp_10 -0.603832898 0.15166108
-#> 32512 0 0.15337312 0.58461375 8 sp_11 -0.603832898 0.15166108
-#> 32522 0 0.15337312 0.58461375 15 sp_12 -0.603832898 0.15166108
-#> 32532 0 0.15337312 0.58461375 14 sp_13 -0.603832898 0.15166108
-#> 32542 1 0.15337312 0.58461375 16 sp_14 -0.603832898 0.15166108
-#> 32552 1 0.15337312 0.58461375 1 sp_15 -0.603832898 0.15166108
-#> 32562 0 0.15337312 0.58461375 14 sp_16 -0.603832898 0.15166108
-#> 32572 0 0.15337312 0.58461375 17 sp_17 -0.603832898 0.15166108
-#> 32582 0 0.15337312 0.58461375 7 sp_18 -0.603832898 0.15166108
-#> 32592 0 0.15337312 0.58461375 7 sp_19 -0.603832898 0.15166108
-#> 32602 0 0.15337312 0.58461375 13 sp_20 -0.603832898 0.15166108
-#> 32612 0 0.15337312 0.58461375 15 sp_21 -0.603832898 0.15166108
-#> 32622 0 0.15337312 0.58461375 12 sp_22 -0.603832898 0.15166108
-#> 32632 0 0.15337312 0.58461375 14 sp_23 -0.603832898 0.15166108
-#> 32642 0 0.15337312 0.58461375 19 sp_24 -0.603832898 0.15166108
-#> 32652 0 0.15337312 0.58461375 19 sp_25 -0.603832898 0.15166108
-#> 32662 0 0.15337312 0.58461375 17 sp_26 -0.603832898 0.15166108
-#> 32672 0 0.15337312 0.58461375 9 sp_27 -0.603832898 0.15166108
-#> 32682 0 0.15337312 0.58461375 13 sp_28 -0.603832898 0.15166108
-#> 32692 0 0.15337312 0.58461375 14 sp_29 -0.603832898 0.15166108
-#> 32702 0 0.15337312 0.58461375 6 sp_30 -0.603832898 0.15166108
-#> 33612 0 -1.13813694 0.12385424 1 sp_1 -0.922031005 -0.57269753
-#> 33622 0 -1.13813694 0.12385424 16 sp_2 -0.922031005 -0.57269753
-#> 33632 0 -1.13813694 0.12385424 8 sp_3 -0.922031005 -0.57269753
-#> 33642 0 -1.13813694 0.12385424 5 sp_4 -0.922031005 -0.57269753
-#> 33652 0 -1.13813694 0.12385424 10 sp_5 -0.922031005 -0.57269753
-#> 33662 0 -1.13813694 0.12385424 9 sp_6 -0.922031005 -0.57269753
-#> 33672 0 -1.13813694 0.12385424 5 sp_7 -0.922031005 -0.57269753
-#> 33682 0 -1.13813694 0.12385424 14 sp_8 -0.922031005 -0.57269753
-#> 33692 0 -1.13813694 0.12385424 19 sp_9 -0.922031005 -0.57269753
-#> 33702 0 -1.13813694 0.12385424 1 sp_10 -0.922031005 -0.57269753
-#> 33712 0 -1.13813694 0.12385424 16 sp_11 -0.922031005 -0.57269753
-#> 33722 0 -1.13813694 0.12385424 6 sp_12 -0.922031005 -0.57269753
-#> 33732 0 -1.13813694 0.12385424 20 sp_13 -0.922031005 -0.57269753
-#> 33742 0 -1.13813694 0.12385424 8 sp_14 -0.922031005 -0.57269753
-#> 33752 0 -1.13813694 0.12385424 14 sp_15 -0.922031005 -0.57269753
-#> 33762 0 -1.13813694 0.12385424 14 sp_16 -0.922031005 -0.57269753
-#> 33772 0 -1.13813694 0.12385424 8 sp_17 -0.922031005 -0.57269753
-#> 33782 0 -1.13813694 0.12385424 11 sp_18 -0.922031005 -0.57269753
-#> 33792 0 -1.13813694 0.12385424 20 sp_19 -0.922031005 -0.57269753
-#> 33802 0 -1.13813694 0.12385424 5 sp_20 -0.922031005 -0.57269753
-#> 33812 0 -1.13813694 0.12385424 14 sp_21 -0.922031005 -0.57269753
-#> 33822 0 -1.13813694 0.12385424 1 sp_22 -0.922031005 -0.57269753
-#> 33832 0 -1.13813694 0.12385424 1 sp_23 -0.922031005 -0.57269753
-#> 33842 0 -1.13813694 0.12385424 5 sp_24 -0.922031005 -0.57269753
-#> 33852 0 -1.13813694 0.12385424 3 sp_25 -0.922031005 -0.57269753
-#> 33862 0 -1.13813694 0.12385424 4 sp_26 -0.922031005 -0.57269753
-#> 33872 0 -1.13813694 0.12385424 3 sp_27 -0.922031005 -0.57269753
-#> 33882 0 -1.13813694 0.12385424 14 sp_28 -0.922031005 -0.57269753
-#> 33892 1 -1.13813694 0.12385424 18 sp_29 -0.922031005 -0.57269753
-#> 33902 0 -1.13813694 0.12385424 10 sp_30 -0.922031005 -0.57269753
-#> 34812 1 1.25381492 0.21594157 12 sp_1 0.479910722 0.32978651
-#> 34822 0 1.25381492 0.21594157 16 sp_2 0.479910722 0.32978651
-#> 34832 0 1.25381492 0.21594157 3 sp_3 0.479910722 0.32978651
-#> 34842 0 1.25381492 0.21594157 12 sp_4 0.479910722 0.32978651
-#> 34852 0 1.25381492 0.21594157 5 sp_5 0.479910722 0.32978651
-#> 34862 0 1.25381492 0.21594157 13 sp_6 0.479910722 0.32978651
-#> 34872 0 1.25381492 0.21594157 8 sp_7 0.479910722 0.32978651
-#> 34882 1 1.25381492 0.21594157 17 sp_8 0.479910722 0.32978651
-#> 34892 1 1.25381492 0.21594157 5 sp_9 0.479910722 0.32978651
-#> 34902 0 1.25381492 0.21594157 19 sp_10 0.479910722 0.32978651
-#> 34912 0 1.25381492 0.21594157 6 sp_11 0.479910722 0.32978651
-#> 34922 0 1.25381492 0.21594157 2 sp_12 0.479910722 0.32978651
-#> 34932 0 1.25381492 0.21594157 17 sp_13 0.479910722 0.32978651
-#> 34942 1 1.25381492 0.21594157 17 sp_14 0.479910722 0.32978651
-#> 34952 1 1.25381492 0.21594157 8 sp_15 0.479910722 0.32978651
-#> 34962 0 1.25381492 0.21594157 19 sp_16 0.479910722 0.32978651
-#> 34972 1 1.25381492 0.21594157 18 sp_17 0.479910722 0.32978651
-#> 34982 0 1.25381492 0.21594157 19 sp_18 0.479910722 0.32978651
-#> 34992 0 1.25381492 0.21594157 5 sp_19 0.479910722 0.32978651
-#> 35002 0 1.25381492 0.21594157 14 sp_20 0.479910722 0.32978651
-#> 35012 1 1.25381492 0.21594157 12 sp_21 0.479910722 0.32978651
-#> 35022 0 1.25381492 0.21594157 1 sp_22 0.479910722 0.32978651
-#> 35032 1 1.25381492 0.21594157 16 sp_23 0.479910722 0.32978651
-#> 35042 0 1.25381492 0.21594157 18 sp_24 0.479910722 0.32978651
-#> 35052 0 1.25381492 0.21594157 20 sp_25 0.479910722 0.32978651
-#> 35062 0 1.25381492 0.21594157 7 sp_26 0.479910722 0.32978651
-#> 35072 1 1.25381492 0.21594157 5 sp_27 0.479910722 0.32978651
-#> 35082 0 1.25381492 0.21594157 10 sp_28 0.479910722 0.32978651
-#> 35092 0 1.25381492 0.21594157 4 sp_29 0.479910722 0.32978651
-#> 35102 0 1.25381492 0.21594157 8 sp_30 0.479910722 0.32978651
-#> 114 0 -0.56047565 0.42646422 7 sp_1 0.105881568 -0.26338952
-#> 214 0 -0.56047565 0.42646422 3 sp_2 0.105881568 -0.26338952
-#> 33 0 -0.56047565 0.42646422 15 sp_3 0.105881568 -0.26338952
-#> 43 0 -0.56047565 0.42646422 5 sp_4 0.105881568 -0.26338952
-#> 53 0 -0.56047565 0.42646422 8 sp_5 0.105881568 -0.26338952
-#> 63 0 -0.56047565 0.42646422 19 sp_6 0.105881568 -0.26338952
-#> 73 0 -0.56047565 0.42646422 10 sp_7 0.105881568 -0.26338952
-#> 83 0 -0.56047565 0.42646422 18 sp_8 0.105881568 -0.26338952
-#> 93 0 -0.56047565 0.42646422 10 sp_9 0.105881568 -0.26338952
-#> 103 0 -0.56047565 0.42646422 12 sp_10 0.105881568 -0.26338952
-#> 115 0 -0.56047565 0.42646422 2 sp_11 0.105881568 -0.26338952
-#> 1235 0 -0.56047565 0.42646422 10 sp_12 0.105881568 -0.26338952
-#> 1314 0 -0.56047565 0.42646422 12 sp_13 0.105881568 -0.26338952
-#> 1414 0 -0.56047565 0.42646422 20 sp_14 0.105881568 -0.26338952
-#> 153 0 -0.56047565 0.42646422 14 sp_15 0.105881568 -0.26338952
-#> 163 0 -0.56047565 0.42646422 17 sp_16 0.105881568 -0.26338952
-#> 173 0 -0.56047565 0.42646422 14 sp_17 0.105881568 -0.26338952
-#> 183 0 -0.56047565 0.42646422 3 sp_18 0.105881568 -0.26338952
-#> 193 0 -0.56047565 0.42646422 8 sp_19 0.105881568 -0.26338952
-#> 203 0 -0.56047565 0.42646422 14 sp_20 0.105881568 -0.26338952
-#> 215 0 -0.56047565 0.42646422 19 sp_21 0.105881568 -0.26338952
-#> 223 0 -0.56047565 0.42646422 15 sp_22 0.105881568 -0.26338952
-#> 233 0 -0.56047565 0.42646422 17 sp_23 0.105881568 -0.26338952
-#> 2435 0 -0.56047565 0.42646422 11 sp_24 0.105881568 -0.26338952
-#> 2514 0 -0.56047565 0.42646422 7 sp_25 0.105881568 -0.26338952
-#> 2614 0 -0.56047565 0.42646422 15 sp_26 0.105881568 -0.26338952
-#> 273 1 -0.56047565 0.42646422 6 sp_27 0.105881568 -0.26338952
-#> 283 0 -0.56047565 0.42646422 14 sp_28 0.105881568 -0.26338952
-#> 293 0 -0.56047565 0.42646422 7 sp_29 0.105881568 -0.26338952
-#> 303 0 -0.56047565 0.42646422 10 sp_30 0.105881568 -0.26338952
-#> 12114 0 -0.23017749 -0.29507148 5 sp_1 -1.140377953 0.61794489
-#> 12214 0 -0.23017749 -0.29507148 6 sp_2 -1.140377953 0.61794489
-#> 1236 0 -0.23017749 -0.29507148 16 sp_3 -1.140377953 0.61794489
-#> 1243 0 -0.23017749 -0.29507148 11 sp_4 -1.140377953 0.61794489
-#> 1253 0 -0.23017749 -0.29507148 4 sp_5 -1.140377953 0.61794489
-#> 1263 0 -0.23017749 -0.29507148 12 sp_6 -1.140377953 0.61794489
-#> 1273 0 -0.23017749 -0.29507148 14 sp_7 -1.140377953 0.61794489
-#> 1283 0 -0.23017749 -0.29507148 19 sp_8 -1.140377953 0.61794489
-#> 1293 0 -0.23017749 -0.29507148 7 sp_9 -1.140377953 0.61794489
-#> 1303 0 -0.23017749 -0.29507148 9 sp_10 -1.140377953 0.61794489
-#> 1315 0 -0.23017749 -0.29507148 7 sp_11 -1.140377953 0.61794489
-#> 13214 0 -0.23017749 -0.29507148 2 sp_12 -1.140377953 0.61794489
-#> 13314 0 -0.23017749 -0.29507148 16 sp_13 -1.140377953 0.61794489
-#> 13414 0 -0.23017749 -0.29507148 13 sp_14 -1.140377953 0.61794489
-#> 1353 0 -0.23017749 -0.29507148 19 sp_15 -1.140377953 0.61794489
-#> 1363 0 -0.23017749 -0.29507148 20 sp_16 -1.140377953 0.61794489
-#> 1373 0 -0.23017749 -0.29507148 15 sp_17 -1.140377953 0.61794489
-#> 1383 1 -0.23017749 -0.29507148 7 sp_18 -1.140377953 0.61794489
-#> 1393 0 -0.23017749 -0.29507148 4 sp_19 -1.140377953 0.61794489
-#> 1403 0 -0.23017749 -0.29507148 1 sp_20 -1.140377953 0.61794489
-#> 1415 0 -0.23017749 -0.29507148 8 sp_21 -1.140377953 0.61794489
-#> 1423 1 -0.23017749 -0.29507148 20 sp_22 -1.140377953 0.61794489
-#> 1433 0 -0.23017749 -0.29507148 16 sp_23 -1.140377953 0.61794489
-#> 14414 0 -0.23017749 -0.29507148 11 sp_24 -1.140377953 0.61794489
-#> 14514 0 -0.23017749 -0.29507148 16 sp_25 -1.140377953 0.61794489
-#> 14614 0 -0.23017749 -0.29507148 20 sp_26 -1.140377953 0.61794489
-#> 1473 0 -0.23017749 -0.29507148 8 sp_27 -1.140377953 0.61794489
-#> 1483 0 -0.23017749 -0.29507148 3 sp_28 -1.140377953 0.61794489
-#> 1493 0 -0.23017749 -0.29507148 4 sp_29 -1.140377953 0.61794489
-#> 1503 0 -0.23017749 -0.29507148 20 sp_30 -1.140377953 0.61794489
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-#> 24214 1 1.55870831 0.89512566 17 sp_2 -0.971485822 -0.16289598
-#> 2436 0 1.55870831 0.89512566 10 sp_3 -0.971485822 -0.16289598
-#> 2443 0 1.55870831 0.89512566 20 sp_4 -0.971485822 -0.16289598
-#> 2453 1 1.55870831 0.89512566 11 sp_5 -0.971485822 -0.16289598
-#> 2463 0 1.55870831 0.89512566 8 sp_6 -0.971485822 -0.16289598
-#> 2473 1 1.55870831 0.89512566 14 sp_7 -0.971485822 -0.16289598
-#> 2483 0 1.55870831 0.89512566 13 sp_8 -0.971485822 -0.16289598
-#> 2493 0 1.55870831 0.89512566 2 sp_9 -0.971485822 -0.16289598
-#> 2503 0 1.55870831 0.89512566 11 sp_10 -0.971485822 -0.16289598
-#> 2515 0 1.55870831 0.89512566 13 sp_11 -0.971485822 -0.16289598
-#> 25214 0 1.55870831 0.89512566 14 sp_12 -0.971485822 -0.16289598
-#> 25314 0 1.55870831 0.89512566 6 sp_13 -0.971485822 -0.16289598
-#> 25414 0 1.55870831 0.89512566 8 sp_14 -0.971485822 -0.16289598
-#> 2553 1 1.55870831 0.89512566 12 sp_15 -0.971485822 -0.16289598
-#> 2563 0 1.55870831 0.89512566 4 sp_16 -0.971485822 -0.16289598
-#> 2573 0 1.55870831 0.89512566 13 sp_17 -0.971485822 -0.16289598
-#> 2583 0 1.55870831 0.89512566 14 sp_18 -0.971485822 -0.16289598
-#> 2593 0 1.55870831 0.89512566 16 sp_19 -0.971485822 -0.16289598
-#> 2603 0 1.55870831 0.89512566 1 sp_20 -0.971485822 -0.16289598
-#> 2615 1 1.55870831 0.89512566 8 sp_21 -0.971485822 -0.16289598
-#> 2623 0 1.55870831 0.89512566 8 sp_22 -0.971485822 -0.16289598
-#> 2633 0 1.55870831 0.89512566 10 sp_23 -0.971485822 -0.16289598
-#> 26414 0 1.55870831 0.89512566 8 sp_24 -0.971485822 -0.16289598
-#> 26514 0 1.55870831 0.89512566 18 sp_25 -0.971485822 -0.16289598
-#> 26614 0 1.55870831 0.89512566 9 sp_26 -0.971485822 -0.16289598
-#> 2673 0 1.55870831 0.89512566 7 sp_27 -0.971485822 -0.16289598
-#> 2683 0 1.55870831 0.89512566 7 sp_28 -0.971485822 -0.16289598
-#> 2693 0 1.55870831 0.89512566 10 sp_29 -0.971485822 -0.16289598
-#> 2703 1 1.55870831 0.89512566 11 sp_30 -0.971485822 -0.16289598
-#> 3613 0 0.07050839 0.87813349 1 sp_1 -1.069651815 -0.50832407
-#> 3623 0 0.07050839 0.87813349 19 sp_2 -1.069651815 -0.50832407
-#> 3633 0 0.07050839 0.87813349 10 sp_3 -1.069651815 -0.50832407
-#> 3643 0 0.07050839 0.87813349 13 sp_4 -1.069651815 -0.50832407
-#> 3653 1 0.07050839 0.87813349 11 sp_5 -1.069651815 -0.50832407
-#> 3663 0 0.07050839 0.87813349 11 sp_6 -1.069651815 -0.50832407
-#> 3673 0 0.07050839 0.87813349 20 sp_7 -1.069651815 -0.50832407
-#> 3683 0 0.07050839 0.87813349 7 sp_8 -1.069651815 -0.50832407
-#> 3693 0 0.07050839 0.87813349 20 sp_9 -1.069651815 -0.50832407
-#> 3703 0 0.07050839 0.87813349 9 sp_10 -1.069651815 -0.50832407
-#> 3713 0 0.07050839 0.87813349 9 sp_11 -1.069651815 -0.50832407
-#> 3723 0 0.07050839 0.87813349 5 sp_12 -1.069651815 -0.50832407
-#> 3733 1 0.07050839 0.87813349 14 sp_13 -1.069651815 -0.50832407
-#> 3743 0 0.07050839 0.87813349 14 sp_14 -1.069651815 -0.50832407
-#> 3753 0 0.07050839 0.87813349 6 sp_15 -1.069651815 -0.50832407
-#> 3763 0 0.07050839 0.87813349 1 sp_16 -1.069651815 -0.50832407
-#> 3773 1 0.07050839 0.87813349 10 sp_17 -1.069651815 -0.50832407
-#> 3783 1 0.07050839 0.87813349 17 sp_18 -1.069651815 -0.50832407
-#> 3793 0 0.07050839 0.87813349 17 sp_19 -1.069651815 -0.50832407
-#> 3803 0 0.07050839 0.87813349 7 sp_20 -1.069651815 -0.50832407
-#> 3813 0 0.07050839 0.87813349 9 sp_21 -1.069651815 -0.50832407
-#> 3823 0 0.07050839 0.87813349 20 sp_22 -1.069651815 -0.50832407
-#> 3833 0 0.07050839 0.87813349 6 sp_23 -1.069651815 -0.50832407
-#> 3843 0 0.07050839 0.87813349 18 sp_24 -1.069651815 -0.50832407
-#> 3853 0 0.07050839 0.87813349 17 sp_25 -1.069651815 -0.50832407
-#> 3863 0 0.07050839 0.87813349 5 sp_26 -1.069651815 -0.50832407
-#> 3873 1 0.07050839 0.87813349 20 sp_27 -1.069651815 -0.50832407
-#> 3883 0 0.07050839 0.87813349 3 sp_28 -1.069651815 -0.50832407
-#> 3893 0 0.07050839 0.87813349 14 sp_29 -1.069651815 -0.50832407
-#> 3903 0 0.07050839 0.87813349 1 sp_30 -1.069651815 -0.50832407
-#> 4813 0 0.12928774 0.82158108 2 sp_1 -1.902177022 0.33140152
-#> 4823 0 0.12928774 0.82158108 4 sp_2 -1.902177022 0.33140152
-#> 4833 0 0.12928774 0.82158108 10 sp_3 -1.902177022 0.33140152
-#> 4843 0 0.12928774 0.82158108 1 sp_4 -1.902177022 0.33140152
-#> 4853 0 0.12928774 0.82158108 5 sp_5 -1.902177022 0.33140152
-#> 4863 0 0.12928774 0.82158108 8 sp_6 -1.902177022 0.33140152
-#> 4873 0 0.12928774 0.82158108 13 sp_7 -1.902177022 0.33140152
-#> 4883 0 0.12928774 0.82158108 18 sp_8 -1.902177022 0.33140152
-#> 4893 0 0.12928774 0.82158108 10 sp_9 -1.902177022 0.33140152
-#> 4903 0 0.12928774 0.82158108 6 sp_10 -1.902177022 0.33140152
-#> 4913 0 0.12928774 0.82158108 7 sp_11 -1.902177022 0.33140152
-#> 4923 0 0.12928774 0.82158108 9 sp_12 -1.902177022 0.33140152
-#> 4933 0 0.12928774 0.82158108 16 sp_13 -1.902177022 0.33140152
-#> 4943 1 0.12928774 0.82158108 17 sp_14 -1.902177022 0.33140152
-#> 4953 0 0.12928774 0.82158108 13 sp_15 -1.902177022 0.33140152
-#> 4963 0 0.12928774 0.82158108 8 sp_16 -1.902177022 0.33140152
-#> 4973 0 0.12928774 0.82158108 7 sp_17 -1.902177022 0.33140152
-#> 4983 0 0.12928774 0.82158108 20 sp_18 -1.902177022 0.33140152
-#> 4993 0 0.12928774 0.82158108 18 sp_19 -1.902177022 0.33140152
-#> 5003 0 0.12928774 0.82158108 17 sp_20 -1.902177022 0.33140152
-#> 5013 0 0.12928774 0.82158108 1 sp_21 -1.902177022 0.33140152
-#> 5023 0 0.12928774 0.82158108 2 sp_22 -1.902177022 0.33140152
-#> 5033 0 0.12928774 0.82158108 17 sp_23 -1.902177022 0.33140152
-#> 5043 0 0.12928774 0.82158108 2 sp_24 -1.902177022 0.33140152
-#> 5053 0 0.12928774 0.82158108 13 sp_25 -1.902177022 0.33140152
-#> 5063 0 0.12928774 0.82158108 17 sp_26 -1.902177022 0.33140152
-#> 5073 0 0.12928774 0.82158108 3 sp_27 -1.902177022 0.33140152
-#> 5083 0 0.12928774 0.82158108 18 sp_28 -1.902177022 0.33140152
-#> 5093 0 0.12928774 0.82158108 2 sp_29 -1.902177022 0.33140152
-#> 5103 0 0.12928774 0.82158108 5 sp_30 -1.902177022 0.33140152
-#> 6013 1 1.71506499 0.68864025 12 sp_1 1.053866739 0.57437773
-#> 6023 0 1.71506499 0.68864025 13 sp_2 1.053866739 0.57437773
-#> 6033 0 1.71506499 0.68864025 10 sp_3 1.053866739 0.57437773
-#> 6043 1 1.71506499 0.68864025 6 sp_4 1.053866739 0.57437773
-#> 6053 0 1.71506499 0.68864025 10 sp_5 1.053866739 0.57437773
-#> 6063 0 1.71506499 0.68864025 10 sp_6 1.053866739 0.57437773
-#> 6073 0 1.71506499 0.68864025 6 sp_7 1.053866739 0.57437773
-#> 6083 0 1.71506499 0.68864025 16 sp_8 1.053866739 0.57437773
-#> 6093 0 1.71506499 0.68864025 16 sp_9 1.053866739 0.57437773
-#> 6103 0 1.71506499 0.68864025 3 sp_10 1.053866739 0.57437773
-#> 6113 0 1.71506499 0.68864025 4 sp_11 1.053866739 0.57437773
-#> 6123 1 1.71506499 0.68864025 3 sp_12 1.053866739 0.57437773
-#> 6133 0 1.71506499 0.68864025 3 sp_13 1.053866739 0.57437773
-#> 6143 0 1.71506499 0.68864025 16 sp_14 1.053866739 0.57437773
-#> 6153 0 1.71506499 0.68864025 2 sp_15 1.053866739 0.57437773
-#> 6163 0 1.71506499 0.68864025 15 sp_16 1.053866739 0.57437773
-#> 6173 0 1.71506499 0.68864025 3 sp_17 1.053866739 0.57437773
-#> 6183 0 1.71506499 0.68864025 9 sp_18 1.053866739 0.57437773
-#> 6193 0 1.71506499 0.68864025 7 sp_19 1.053866739 0.57437773
-#> 6203 0 1.71506499 0.68864025 9 sp_20 1.053866739 0.57437773
-#> 6213 0 1.71506499 0.68864025 4 sp_21 1.053866739 0.57437773
-#> 6223 1 1.71506499 0.68864025 2 sp_22 1.053866739 0.57437773
-#> 6233 0 1.71506499 0.68864025 12 sp_23 1.053866739 0.57437773
-#> 6243 0 1.71506499 0.68864025 9 sp_24 1.053866739 0.57437773
-#> 6253 0 1.71506499 0.68864025 11 sp_25 1.053866739 0.57437773
-#> 6263 0 1.71506499 0.68864025 7 sp_26 1.053866739 0.57437773
-#> 6273 0 1.71506499 0.68864025 13 sp_27 1.053866739 0.57437773
-#> 6283 1 1.71506499 0.68864025 5 sp_28 1.053866739 0.57437773
-#> 6293 0 1.71506499 0.68864025 11 sp_29 1.053866739 0.57437773
-#> 6303 0 1.71506499 0.68864025 1 sp_30 1.053866739 0.57437773
-#> 7213 0 0.46091621 0.55391765 19 sp_1 -0.139730368 0.53331433
-#> 7223 0 0.46091621 0.55391765 12 sp_2 -0.139730368 0.53331433
-#> 7233 0 0.46091621 0.55391765 2 sp_3 -0.139730368 0.53331433
-#> 7243 1 0.46091621 0.55391765 17 sp_4 -0.139730368 0.53331433
-#> 7253 1 0.46091621 0.55391765 12 sp_5 -0.139730368 0.53331433
-#> 7263 0 0.46091621 0.55391765 3 sp_6 -0.139730368 0.53331433
-#> 7273 0 0.46091621 0.55391765 18 sp_7 -0.139730368 0.53331433
-#> 7283 0 0.46091621 0.55391765 15 sp_8 -0.139730368 0.53331433
-#> 7293 0 0.46091621 0.55391765 3 sp_9 -0.139730368 0.53331433
-#> 7303 0 0.46091621 0.55391765 19 sp_10 -0.139730368 0.53331433
-#> 7313 0 0.46091621 0.55391765 18 sp_11 -0.139730368 0.53331433
-#> 7323 0 0.46091621 0.55391765 17 sp_12 -0.139730368 0.53331433
-#> 7333 0 0.46091621 0.55391765 6 sp_13 -0.139730368 0.53331433
-#> 7343 0 0.46091621 0.55391765 10 sp_14 -0.139730368 0.53331433
-#> 7353 0 0.46091621 0.55391765 8 sp_15 -0.139730368 0.53331433
-#> 7363 0 0.46091621 0.55391765 10 sp_16 -0.139730368 0.53331433
-#> 7373 0 0.46091621 0.55391765 13 sp_17 -0.139730368 0.53331433
-#> 7383 1 0.46091621 0.55391765 20 sp_18 -0.139730368 0.53331433
-#> 7393 0 0.46091621 0.55391765 6 sp_19 -0.139730368 0.53331433
-#> 7403 0 0.46091621 0.55391765 20 sp_20 -0.139730368 0.53331433
-#> 7413 0 0.46091621 0.55391765 20 sp_21 -0.139730368 0.53331433
-#> 7423 0 0.46091621 0.55391765 9 sp_22 -0.139730368 0.53331433
-#> 7433 0 0.46091621 0.55391765 16 sp_23 -0.139730368 0.53331433
-#> 7443 0 0.46091621 0.55391765 8 sp_24 -0.139730368 0.53331433
-#> 7453 0 0.46091621 0.55391765 7 sp_25 -0.139730368 0.53331433
-#> 7463 0 0.46091621 0.55391765 10 sp_26 -0.139730368 0.53331433
-#> 7473 1 0.46091621 0.55391765 17 sp_27 -0.139730368 0.53331433
-#> 7483 0 0.46091621 0.55391765 18 sp_28 -0.139730368 0.53331433
-#> 7493 0 0.46091621 0.55391765 8 sp_29 -0.139730368 0.53331433
-#> 7503 0 0.46091621 0.55391765 19 sp_30 -0.139730368 0.53331433
-#> 8413 1 -1.26506123 -0.06191171 10 sp_1 -0.380597979 0.24837592
-#> 8423 0 -1.26506123 -0.06191171 11 sp_2 -0.380597979 0.24837592
-#> 8433 0 -1.26506123 -0.06191171 17 sp_3 -0.380597979 0.24837592
-#> 8443 0 -1.26506123 -0.06191171 12 sp_4 -0.380597979 0.24837592
-#> 8453 0 -1.26506123 -0.06191171 2 sp_5 -0.380597979 0.24837592
-#> 8463 0 -1.26506123 -0.06191171 19 sp_6 -0.380597979 0.24837592
-#> 8473 0 -1.26506123 -0.06191171 13 sp_7 -0.380597979 0.24837592
-#> 8483 0 -1.26506123 -0.06191171 13 sp_8 -0.380597979 0.24837592
-#> 8493 0 -1.26506123 -0.06191171 19 sp_9 -0.380597979 0.24837592
-#> 8503 1 -1.26506123 -0.06191171 10 sp_10 -0.380597979 0.24837592
-#> 8513 0 -1.26506123 -0.06191171 16 sp_11 -0.380597979 0.24837592
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-#> 8533 0 -1.26506123 -0.06191171 4 sp_13 -0.380597979 0.24837592
-#> 8543 0 -1.26506123 -0.06191171 18 sp_14 -0.380597979 0.24837592
-#> 8553 0 -1.26506123 -0.06191171 1 sp_15 -0.380597979 0.24837592
-#> 8563 0 -1.26506123 -0.06191171 16 sp_16 -0.380597979 0.24837592
-#> 8573 0 -1.26506123 -0.06191171 17 sp_17 -0.380597979 0.24837592
-#> 8583 0 -1.26506123 -0.06191171 12 sp_18 -0.380597979 0.24837592
-#> 8593 0 -1.26506123 -0.06191171 2 sp_19 -0.380597979 0.24837592
-#> 8603 0 -1.26506123 -0.06191171 18 sp_20 -0.380597979 0.24837592
-#> 8613 0 -1.26506123 -0.06191171 12 sp_21 -0.380597979 0.24837592
-#> 8623 0 -1.26506123 -0.06191171 15 sp_22 -0.380597979 0.24837592
-#> 8633 0 -1.26506123 -0.06191171 19 sp_23 -0.380597979 0.24837592
-#> 8643 0 -1.26506123 -0.06191171 6 sp_24 -0.380597979 0.24837592
-#> 8653 0 -1.26506123 -0.06191171 16 sp_25 -0.380597979 0.24837592
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-#> 8673 0 -1.26506123 -0.06191171 19 sp_27 -0.380597979 0.24837592
-#> 8683 0 -1.26506123 -0.06191171 3 sp_28 -0.380597979 0.24837592
-#> 8693 0 -1.26506123 -0.06191171 14 sp_29 -0.380597979 0.24837592
-#> 8703 0 -1.26506123 -0.06191171 1 sp_30 -0.380597979 0.24837592
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-#> 9623 0 -0.68685285 -0.30596266 16 sp_2 1.476197464 -0.71800879
-#> 9633 0 -0.68685285 -0.30596266 11 sp_3 1.476197464 -0.71800879
-#> 9643 1 -0.68685285 -0.30596266 4 sp_4 1.476197464 -0.71800879
-#> 9653 0 -0.68685285 -0.30596266 12 sp_5 1.476197464 -0.71800879
-#> 9663 1 -0.68685285 -0.30596266 13 sp_6 1.476197464 -0.71800879
-#> 9673 0 -0.68685285 -0.30596266 10 sp_7 1.476197464 -0.71800879
-#> 9683 0 -0.68685285 -0.30596266 10 sp_8 1.476197464 -0.71800879
-#> 9693 0 -0.68685285 -0.30596266 7 sp_9 1.476197464 -0.71800879
-#> 9703 0 -0.68685285 -0.30596266 18 sp_10 1.476197464 -0.71800879
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-#> 9723 1 -0.68685285 -0.30596266 20 sp_12 1.476197464 -0.71800879
-#> 9733 1 -0.68685285 -0.30596266 9 sp_13 1.476197464 -0.71800879
-#> 9743 0 -0.68685285 -0.30596266 11 sp_14 1.476197464 -0.71800879
-#> 9753 1 -0.68685285 -0.30596266 12 sp_15 1.476197464 -0.71800879
-#> 9763 0 -0.68685285 -0.30596266 8 sp_16 1.476197464 -0.71800879
-#> 9773 0 -0.68685285 -0.30596266 18 sp_17 1.476197464 -0.71800879
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-#> 9793 0 -0.68685285 -0.30596266 18 sp_19 1.476197464 -0.71800879
-#> 9803 0 -0.68685285 -0.30596266 6 sp_20 1.476197464 -0.71800879
-#> 9813 0 -0.68685285 -0.30596266 10 sp_21 1.476197464 -0.71800879
-#> 9823 0 -0.68685285 -0.30596266 9 sp_22 1.476197464 -0.71800879
-#> 9833 1 -0.68685285 -0.30596266 11 sp_23 1.476197464 -0.71800879
-#> 9843 0 -0.68685285 -0.30596266 6 sp_24 1.476197464 -0.71800879
-#> 9853 0 -0.68685285 -0.30596266 12 sp_25 1.476197464 -0.71800879
-#> 9863 0 -0.68685285 -0.30596266 19 sp_26 1.476197464 -0.71800879
-#> 9873 0 -0.68685285 -0.30596266 4 sp_27 1.476197464 -0.71800879
-#> 9883 0 -0.68685285 -0.30596266 3 sp_28 1.476197464 -0.71800879
-#> 9893 0 -0.68685285 -0.30596266 14 sp_29 1.476197464 -0.71800879
-#> 9903 0 -0.68685285 -0.30596266 8 sp_30 1.476197464 -0.71800879
-#> 10813 0 -0.44566197 -0.38047100 6 sp_1 0.610727338 -1.32709228
-#> 10823 0 -0.44566197 -0.38047100 4 sp_2 0.610727338 -1.32709228
-#> 10833 1 -0.44566197 -0.38047100 10 sp_3 0.610727338 -1.32709228
-#> 10843 0 -0.44566197 -0.38047100 16 sp_4 0.610727338 -1.32709228
-#> 10853 0 -0.44566197 -0.38047100 16 sp_5 0.610727338 -1.32709228
-#> 10863 1 -0.44566197 -0.38047100 20 sp_6 0.610727338 -1.32709228
-#> 10873 1 -0.44566197 -0.38047100 10 sp_7 0.610727338 -1.32709228
-#> 10883 0 -0.44566197 -0.38047100 6 sp_8 0.610727338 -1.32709228
-#> 10893 0 -0.44566197 -0.38047100 19 sp_9 0.610727338 -1.32709228
-#> 10903 0 -0.44566197 -0.38047100 4 sp_10 0.610727338 -1.32709228
-#> 10913 0 -0.44566197 -0.38047100 9 sp_11 0.610727338 -1.32709228
-#> 10923 0 -0.44566197 -0.38047100 4 sp_12 0.610727338 -1.32709228
-#> 10933 0 -0.44566197 -0.38047100 15 sp_13 0.610727338 -1.32709228
-#> 10943 1 -0.44566197 -0.38047100 20 sp_14 0.610727338 -1.32709228
-#> 10953 1 -0.44566197 -0.38047100 17 sp_15 0.610727338 -1.32709228
-#> 10963 0 -0.44566197 -0.38047100 7 sp_16 0.610727338 -1.32709228
-#> 10973 1 -0.44566197 -0.38047100 15 sp_17 0.610727338 -1.32709228
-#> 10983 0 -0.44566197 -0.38047100 5 sp_18 0.610727338 -1.32709228
-#> 10993 1 -0.44566197 -0.38047100 14 sp_19 0.610727338 -1.32709228
-#> 11003 0 -0.44566197 -0.38047100 15 sp_20 0.610727338 -1.32709228
-#> 11013 0 -0.44566197 -0.38047100 15 sp_21 0.610727338 -1.32709228
-#> 11023 1 -0.44566197 -0.38047100 16 sp_22 0.610727338 -1.32709228
-#> 11033 0 -0.44566197 -0.38047100 19 sp_23 0.610727338 -1.32709228
-#> 11043 1 -0.44566197 -0.38047100 8 sp_24 0.610727338 -1.32709228
-#> 11053 0 -0.44566197 -0.38047100 5 sp_25 0.610727338 -1.32709228
-#> 11063 0 -0.44566197 -0.38047100 7 sp_26 0.610727338 -1.32709228
-#> 11073 1 -0.44566197 -0.38047100 20 sp_27 0.610727338 -1.32709228
-#> 11083 0 -0.44566197 -0.38047100 16 sp_28 0.610727338 -1.32709228
-#> 11093 0 -0.44566197 -0.38047100 16 sp_29 0.610727338 -1.32709228
-#> 11103 0 -0.44566197 -0.38047100 9 sp_30 0.610727338 -1.32709228
-#> 12013 0 1.22408180 -0.69470698 11 sp_1 1.556856957 1.59533274
-#> 12023 0 1.22408180 -0.69470698 11 sp_2 1.556856957 1.59533274
-#> 12033 0 1.22408180 -0.69470698 19 sp_3 1.556856957 1.59533274
-#> 12043 1 1.22408180 -0.69470698 10 sp_4 1.556856957 1.59533274
-#> 12053 0 1.22408180 -0.69470698 2 sp_5 1.556856957 1.59533274
-#> 12063 0 1.22408180 -0.69470698 6 sp_6 1.556856957 1.59533274
-#> 12073 1 1.22408180 -0.69470698 20 sp_7 1.556856957 1.59533274
-#> 12083 0 1.22408180 -0.69470698 14 sp_8 1.556856957 1.59533274
-#> 12093 0 1.22408180 -0.69470698 14 sp_9 1.556856957 1.59533274
-#> 12103 1 1.22408180 -0.69470698 6 sp_10 1.556856957 1.59533274
-#> 12115 0 1.22408180 -0.69470698 18 sp_11 1.556856957 1.59533274
-#> 12123 0 1.22408180 -0.69470698 2 sp_12 1.556856957 1.59533274
-#> 12133 0 1.22408180 -0.69470698 8 sp_13 1.556856957 1.59533274
-#> 12143 0 1.22408180 -0.69470698 11 sp_14 1.556856957 1.59533274
-#> 12153 0 1.22408180 -0.69470698 7 sp_15 1.556856957 1.59533274
-#> 12163 0 1.22408180 -0.69470698 19 sp_16 1.556856957 1.59533274
-#> 12173 0 1.22408180 -0.69470698 8 sp_17 1.556856957 1.59533274
-#> 12183 1 1.22408180 -0.69470698 10 sp_18 1.556856957 1.59533274
-#> 12193 0 1.22408180 -0.69470698 5 sp_19 1.556856957 1.59533274
-#> 12203 0 1.22408180 -0.69470698 17 sp_20 1.556856957 1.59533274
-#> 12215 0 1.22408180 -0.69470698 6 sp_21 1.556856957 1.59533274
-#> 12223 0 1.22408180 -0.69470698 8 sp_22 1.556856957 1.59533274
-#> 12233 1 1.22408180 -0.69470698 20 sp_23 1.556856957 1.59533274
-#> 12243 0 1.22408180 -0.69470698 6 sp_24 1.556856957 1.59533274
-#> 12253 0 1.22408180 -0.69470698 15 sp_25 1.556856957 1.59533274
-#> 12263 0 1.22408180 -0.69470698 17 sp_26 1.556856957 1.59533274
-#> 12273 0 1.22408180 -0.69470698 3 sp_27 1.556856957 1.59533274
-#> 12283 0 1.22408180 -0.69470698 15 sp_28 1.556856957 1.59533274
-#> 12293 1 1.22408180 -0.69470698 20 sp_29 1.556856957 1.59533274
-#> 12303 0 1.22408180 -0.69470698 1 sp_30 1.556856957 1.59533274
-#> 13215 0 0.35981383 -0.20791728 5 sp_1 2.279082282 0.43278793
-#> 13223 1 0.35981383 -0.20791728 11 sp_2 2.279082282 0.43278793
-#> 13233 0 0.35981383 -0.20791728 15 sp_3 2.279082282 0.43278793
-#> 13243 0 0.35981383 -0.20791728 20 sp_4 2.279082282 0.43278793
-#> 13253 1 0.35981383 -0.20791728 2 sp_5 2.279082282 0.43278793
-#> 13263 0 0.35981383 -0.20791728 16 sp_6 2.279082282 0.43278793
-#> 13273 0 0.35981383 -0.20791728 19 sp_7 2.279082282 0.43278793
-#> 13283 0 0.35981383 -0.20791728 10 sp_8 2.279082282 0.43278793
-#> 13293 0 0.35981383 -0.20791728 19 sp_9 2.279082282 0.43278793
-#> 13303 1 0.35981383 -0.20791728 17 sp_10 2.279082282 0.43278793
-#> 13315 0 0.35981383 -0.20791728 7 sp_11 2.279082282 0.43278793
-#> 13323 1 0.35981383 -0.20791728 6 sp_12 2.279082282 0.43278793
-#> 13333 0 0.35981383 -0.20791728 12 sp_13 2.279082282 0.43278793
-#> 13343 1 0.35981383 -0.20791728 4 sp_14 2.279082282 0.43278793
-#> 13353 0 0.35981383 -0.20791728 19 sp_15 2.279082282 0.43278793
-#> 13363 1 0.35981383 -0.20791728 2 sp_16 2.279082282 0.43278793
-#> 13373 0 0.35981383 -0.20791728 4 sp_17 2.279082282 0.43278793
-#> 13383 0 0.35981383 -0.20791728 11 sp_18 2.279082282 0.43278793
-#> 13393 0 0.35981383 -0.20791728 1 sp_19 2.279082282 0.43278793
-#> 13403 0 0.35981383 -0.20791728 19 sp_20 2.279082282 0.43278793
-#> 13415 1 0.35981383 -0.20791728 18 sp_21 2.279082282 0.43278793
-#> 13423 0 0.35981383 -0.20791728 16 sp_22 2.279082282 0.43278793
-#> 13433 1 0.35981383 -0.20791728 3 sp_23 2.279082282 0.43278793
-#> 13443 0 0.35981383 -0.20791728 1 sp_24 2.279082282 0.43278793
-#> 13453 1 0.35981383 -0.20791728 2 sp_25 2.279082282 0.43278793
-#> 13463 1 0.35981383 -0.20791728 2 sp_26 2.279082282 0.43278793
-#> 13473 0 0.35981383 -0.20791728 8 sp_27 2.279082282 0.43278793
-#> 13483 1 0.35981383 -0.20791728 20 sp_28 2.279082282 0.43278793
-#> 13493 0 0.35981383 -0.20791728 14 sp_29 2.279082282 0.43278793
-#> 13503 0 0.35981383 -0.20791728 13 sp_30 2.279082282 0.43278793
-#> 14415 1 0.40077145 -1.26539635 7 sp_1 -0.471806570 -1.08949913
-#> 14423 0 0.40077145 -1.26539635 8 sp_2 -0.471806570 -1.08949913
-#> 14433 0 0.40077145 -1.26539635 3 sp_3 -0.471806570 -1.08949913
-#> 14443 0 0.40077145 -1.26539635 16 sp_4 -0.471806570 -1.08949913
-#> 14453 0 0.40077145 -1.26539635 1 sp_5 -0.471806570 -1.08949913
-#> 14463 0 0.40077145 -1.26539635 12 sp_6 -0.471806570 -1.08949913
-#> 14473 1 0.40077145 -1.26539635 18 sp_7 -0.471806570 -1.08949913
-#> 14483 0 0.40077145 -1.26539635 14 sp_8 -0.471806570 -1.08949913
-#> 14493 0 0.40077145 -1.26539635 8 sp_9 -0.471806570 -1.08949913
-#> 14503 0 0.40077145 -1.26539635 5 sp_10 -0.471806570 -1.08949913
-#> 14515 1 0.40077145 -1.26539635 17 sp_11 -0.471806570 -1.08949913
-#> 14523 1 0.40077145 -1.26539635 11 sp_12 -0.471806570 -1.08949913
-#> 14533 1 0.40077145 -1.26539635 4 sp_13 -0.471806570 -1.08949913
-#> 14543 1 0.40077145 -1.26539635 13 sp_14 -0.471806570 -1.08949913
-#> 14553 1 0.40077145 -1.26539635 8 sp_15 -0.471806570 -1.08949913
-#> 14563 0 0.40077145 -1.26539635 15 sp_16 -0.471806570 -1.08949913
-#> 14573 0 0.40077145 -1.26539635 4 sp_17 -0.471806570 -1.08949913
-#> 14583 0 0.40077145 -1.26539635 13 sp_18 -0.471806570 -1.08949913
-#> 14593 1 0.40077145 -1.26539635 3 sp_19 -0.471806570 -1.08949913
-#> 14603 0 0.40077145 -1.26539635 7 sp_20 -0.471806570 -1.08949913
-#> 14615 0 0.40077145 -1.26539635 1 sp_21 -0.471806570 -1.08949913
-#> 14623 0 0.40077145 -1.26539635 6 sp_22 -0.471806570 -1.08949913
-#> 14633 1 0.40077145 -1.26539635 13 sp_23 -0.471806570 -1.08949913
-#> 14643 1 0.40077145 -1.26539635 17 sp_24 -0.471806570 -1.08949913
-#> 14653 0 0.40077145 -1.26539635 6 sp_25 -0.471806570 -1.08949913
-#> 14663 1 0.40077145 -1.26539635 10 sp_26 -0.471806570 -1.08949913
-#> 14673 0 0.40077145 -1.26539635 13 sp_27 -0.471806570 -1.08949913
-#> 14683 0 0.40077145 -1.26539635 6 sp_28 -0.471806570 -1.08949913
-#> 14693 1 0.40077145 -1.26539635 9 sp_29 -0.471806570 -1.08949913
-#> 14703 0 0.40077145 -1.26539635 8 sp_30 -0.471806570 -1.08949913
-#> 15613 0 0.11068272 2.16895597 1 sp_1 0.212686484 -1.31798554
-#> 15623 0 0.11068272 2.16895597 16 sp_2 0.212686484 -1.31798554
-#> 15633 0 0.11068272 2.16895597 2 sp_3 0.212686484 -1.31798554
-#> 15643 0 0.11068272 2.16895597 8 sp_4 0.212686484 -1.31798554
-#> 15653 0 0.11068272 2.16895597 14 sp_5 0.212686484 -1.31798554
-#> 15663 0 0.11068272 2.16895597 12 sp_6 0.212686484 -1.31798554
-#> 15673 0 0.11068272 2.16895597 8 sp_7 0.212686484 -1.31798554
-#> 15683 0 0.11068272 2.16895597 9 sp_8 0.212686484 -1.31798554
-#> 15693 0 0.11068272 2.16895597 8 sp_9 0.212686484 -1.31798554
-#> 15703 0 0.11068272 2.16895597 9 sp_10 0.212686484 -1.31798554
-#> 15713 0 0.11068272 2.16895597 20 sp_11 0.212686484 -1.31798554
-#> 15723 0 0.11068272 2.16895597 1 sp_12 0.212686484 -1.31798554
-#> 15733 0 0.11068272 2.16895597 3 sp_13 0.212686484 -1.31798554
-#> 15743 0 0.11068272 2.16895597 8 sp_14 0.212686484 -1.31798554
-#> 15753 0 0.11068272 2.16895597 2 sp_15 0.212686484 -1.31798554
-#> 15763 0 0.11068272 2.16895597 1 sp_16 0.212686484 -1.31798554
-#> 15773 0 0.11068272 2.16895597 9 sp_17 0.212686484 -1.31798554
-#> 15783 1 0.11068272 2.16895597 7 sp_18 0.212686484 -1.31798554
-#> 15793 0 0.11068272 2.16895597 13 sp_19 0.212686484 -1.31798554
-#> 15803 0 0.11068272 2.16895597 20 sp_20 0.212686484 -1.31798554
-#> 15813 0 0.11068272 2.16895597 14 sp_21 0.212686484 -1.31798554
-#> 15823 0 0.11068272 2.16895597 16 sp_22 0.212686484 -1.31798554
-#> 15833 1 0.11068272 2.16895597 7 sp_23 0.212686484 -1.31798554
-#> 15843 0 0.11068272 2.16895597 4 sp_24 0.212686484 -1.31798554
-#> 15853 0 0.11068272 2.16895597 13 sp_25 0.212686484 -1.31798554
-#> 15863 0 0.11068272 2.16895597 12 sp_26 0.212686484 -1.31798554
-#> 15873 0 0.11068272 2.16895597 13 sp_27 0.212686484 -1.31798554
-#> 15883 0 0.11068272 2.16895597 20 sp_28 0.212686484 -1.31798554
-#> 15893 0 0.11068272 2.16895597 10 sp_29 0.212686484 -1.31798554
-#> 15903 0 0.11068272 2.16895597 9 sp_30 0.212686484 -1.31798554
-#> 16813 0 -0.55584113 1.20796200 12 sp_1 2.666263607 -0.34159485
-#> 16823 0 -0.55584113 1.20796200 8 sp_2 2.666263607 -0.34159485
-#> 16833 0 -0.55584113 1.20796200 7 sp_3 2.666263607 -0.34159485
-#> 16843 1 -0.55584113 1.20796200 15 sp_4 2.666263607 -0.34159485
-#> 16853 0 -0.55584113 1.20796200 19 sp_5 2.666263607 -0.34159485
-#> 16863 0 -0.55584113 1.20796200 17 sp_6 2.666263607 -0.34159485
-#> 16873 0 -0.55584113 1.20796200 11 sp_7 2.666263607 -0.34159485
-#> 16883 0 -0.55584113 1.20796200 7 sp_8 2.666263607 -0.34159485
-#> 16893 0 -0.55584113 1.20796200 19 sp_9 2.666263607 -0.34159485
-#> 16903 0 -0.55584113 1.20796200 3 sp_10 2.666263607 -0.34159485
-#> 16913 0 -0.55584113 1.20796200 6 sp_11 2.666263607 -0.34159485
-#> 16923 1 -0.55584113 1.20796200 7 sp_12 2.666263607 -0.34159485
-#> 16933 0 -0.55584113 1.20796200 4 sp_13 2.666263607 -0.34159485
-#> 16943 1 -0.55584113 1.20796200 10 sp_14 2.666263607 -0.34159485
-#> 16953 0 -0.55584113 1.20796200 17 sp_15 2.666263607 -0.34159485
-#> 16963 0 -0.55584113 1.20796200 16 sp_16 2.666263607 -0.34159485
-#> 16973 0 -0.55584113 1.20796200 8 sp_17 2.666263607 -0.34159485
-#> 16983 0 -0.55584113 1.20796200 3 sp_18 2.666263607 -0.34159485
-#> 16993 0 -0.55584113 1.20796200 12 sp_19 2.666263607 -0.34159485
-#> 17003 0 -0.55584113 1.20796200 14 sp_20 2.666263607 -0.34159485
-#> 17013 0 -0.55584113 1.20796200 5 sp_21 2.666263607 -0.34159485
-#> 17023 0 -0.55584113 1.20796200 14 sp_22 2.666263607 -0.34159485
-#> 17033 0 -0.55584113 1.20796200 6 sp_23 2.666263607 -0.34159485
-#> 17043 0 -0.55584113 1.20796200 9 sp_24 2.666263607 -0.34159485
-#> 17053 0 -0.55584113 1.20796200 1 sp_25 2.666263607 -0.34159485
-#> 17063 0 -0.55584113 1.20796200 20 sp_26 2.666263607 -0.34159485
-#> 17073 0 -0.55584113 1.20796200 14 sp_27 2.666263607 -0.34159485
-#> 17083 0 -0.55584113 1.20796200 19 sp_28 2.666263607 -0.34159485
-#> 17093 0 -0.55584113 1.20796200 5 sp_29 2.666263607 -0.34159485
-#> 17103 0 -0.55584113 1.20796200 2 sp_30 2.666263607 -0.34159485
-#> 18013 0 1.78691314 -1.12310858 1 sp_1 0.902094706 -0.29755526
-#> 18023 1 1.78691314 -1.12310858 20 sp_2 0.902094706 -0.29755526
-#> 18033 0 1.78691314 -1.12310858 4 sp_3 0.902094706 -0.29755526
-#> 18043 1 1.78691314 -1.12310858 11 sp_4 0.902094706 -0.29755526
-#> 18053 1 1.78691314 -1.12310858 5 sp_5 0.902094706 -0.29755526
-#> 18063 1 1.78691314 -1.12310858 4 sp_6 0.902094706 -0.29755526
-#> 18073 1 1.78691314 -1.12310858 19 sp_7 0.902094706 -0.29755526
-#> 18083 0 1.78691314 -1.12310858 3 sp_8 0.902094706 -0.29755526
-#> 18093 0 1.78691314 -1.12310858 1 sp_9 0.902094706 -0.29755526
-#> 18103 1 1.78691314 -1.12310858 7 sp_10 0.902094706 -0.29755526
-#> 18113 0 1.78691314 -1.12310858 5 sp_11 0.902094706 -0.29755526
-#> 18123 1 1.78691314 -1.12310858 9 sp_12 0.902094706 -0.29755526
-#> 18133 1 1.78691314 -1.12310858 17 sp_13 0.902094706 -0.29755526
-#> 18143 0 1.78691314 -1.12310858 5 sp_14 0.902094706 -0.29755526
-#> 18153 1 1.78691314 -1.12310858 12 sp_15 0.902094706 -0.29755526
-#> 18163 1 1.78691314 -1.12310858 2 sp_16 0.902094706 -0.29755526
-#> 18173 1 1.78691314 -1.12310858 18 sp_17 0.902094706 -0.29755526
-#> 18183 1 1.78691314 -1.12310858 4 sp_18 0.902094706 -0.29755526
-#> 18193 1 1.78691314 -1.12310858 10 sp_19 0.902094706 -0.29755526
-#> 18203 1 1.78691314 -1.12310858 15 sp_20 0.902094706 -0.29755526
-#> 18213 0 1.78691314 -1.12310858 8 sp_21 0.902094706 -0.29755526
-#> 18223 1 1.78691314 -1.12310858 1 sp_22 0.902094706 -0.29755526
-#> 18233 0 1.78691314 -1.12310858 11 sp_23 0.902094706 -0.29755526
-#> 18243 0 1.78691314 -1.12310858 5 sp_24 0.902094706 -0.29755526
-#> 18253 1 1.78691314 -1.12310858 11 sp_25 0.902094706 -0.29755526
-#> 18263 1 1.78691314 -1.12310858 15 sp_26 0.902094706 -0.29755526
-#> 18273 0 1.78691314 -1.12310858 15 sp_27 0.902094706 -0.29755526
-#> 18283 1 1.78691314 -1.12310858 10 sp_28 0.902094706 -0.29755526
-#> 18293 1 1.78691314 -1.12310858 15 sp_29 0.902094706 -0.29755526
-#> 18303 0 1.78691314 -1.12310858 15 sp_30 0.902094706 -0.29755526
-#> 19213 1 0.49785048 -0.40288484 20 sp_1 2.186407733 0.08851264
-#> 19223 1 0.49785048 -0.40288484 12 sp_2 2.186407733 0.08851264
-#> 19233 0 0.49785048 -0.40288484 9 sp_3 2.186407733 0.08851264
-#> 19243 0 0.49785048 -0.40288484 4 sp_4 2.186407733 0.08851264
-#> 19253 1 0.49785048 -0.40288484 3 sp_5 2.186407733 0.08851264
-#> 19263 0 0.49785048 -0.40288484 7 sp_6 2.186407733 0.08851264
-#> 19273 1 0.49785048 -0.40288484 4 sp_7 2.186407733 0.08851264
-#> 19283 0 0.49785048 -0.40288484 8 sp_8 2.186407733 0.08851264
-#> 19293 0 0.49785048 -0.40288484 5 sp_9 2.186407733 0.08851264
-#> 19303 1 0.49785048 -0.40288484 6 sp_10 2.186407733 0.08851264
-#> 19313 1 0.49785048 -0.40288484 4 sp_11 2.186407733 0.08851264
-#> 19323 1 0.49785048 -0.40288484 3 sp_12 2.186407733 0.08851264
-#> 19333 1 0.49785048 -0.40288484 11 sp_13 2.186407733 0.08851264
-#> 19343 0 0.49785048 -0.40288484 10 sp_14 2.186407733 0.08851264
-#> 19353 0 0.49785048 -0.40288484 5 sp_15 2.186407733 0.08851264
-#> 19363 0 0.49785048 -0.40288484 11 sp_16 2.186407733 0.08851264
-#> 19373 0 0.49785048 -0.40288484 10 sp_17 2.186407733 0.08851264
-#> 19383 0 0.49785048 -0.40288484 15 sp_18 2.186407733 0.08851264
-#> 19393 1 0.49785048 -0.40288484 19 sp_19 2.186407733 0.08851264
-#> 19403 0 0.49785048 -0.40288484 10 sp_20 2.186407733 0.08851264
-#> 19413 0 0.49785048 -0.40288484 13 sp_21 2.186407733 0.08851264
-#> 19423 1 0.49785048 -0.40288484 3 sp_22 2.186407733 0.08851264
-#> 19433 0 0.49785048 -0.40288484 18 sp_23 2.186407733 0.08851264
-#> 19443 0 0.49785048 -0.40288484 10 sp_24 2.186407733 0.08851264
-#> 19453 0 0.49785048 -0.40288484 8 sp_25 2.186407733 0.08851264
-#> 19463 1 0.49785048 -0.40288484 12 sp_26 2.186407733 0.08851264
-#> 19473 0 0.49785048 -0.40288484 10 sp_27 2.186407733 0.08851264
-#> 19483 0 0.49785048 -0.40288484 7 sp_28 2.186407733 0.08851264
-#> 19493 0 0.49785048 -0.40288484 7 sp_29 2.186407733 0.08851264
-#> 19503 0 0.49785048 -0.40288484 6 sp_30 2.186407733 0.08851264
-#> 20413 0 -1.96661716 -0.46665535 17 sp_1 0.595320049 1.09064461
-#> 20423 0 -1.96661716 -0.46665535 20 sp_2 0.595320049 1.09064461
-#> 20433 0 -1.96661716 -0.46665535 1 sp_3 0.595320049 1.09064461
-#> 20443 0 -1.96661716 -0.46665535 5 sp_4 0.595320049 1.09064461
-#> 20453 0 -1.96661716 -0.46665535 10 sp_5 0.595320049 1.09064461
-#> 20463 0 -1.96661716 -0.46665535 13 sp_6 0.595320049 1.09064461
-#> 20473 0 -1.96661716 -0.46665535 10 sp_7 0.595320049 1.09064461
-#> 20483 0 -1.96661716 -0.46665535 2 sp_8 0.595320049 1.09064461
-#> 20493 0 -1.96661716 -0.46665535 15 sp_9 0.595320049 1.09064461
-#> 20503 0 -1.96661716 -0.46665535 15 sp_10 0.595320049 1.09064461
-#> 20513 0 -1.96661716 -0.46665535 8 sp_11 0.595320049 1.09064461
-#> 20523 0 -1.96661716 -0.46665535 3 sp_12 0.595320049 1.09064461
-#> 20533 0 -1.96661716 -0.46665535 2 sp_13 0.595320049 1.09064461
-#> 20543 0 -1.96661716 -0.46665535 6 sp_14 0.595320049 1.09064461
-#> 20553 0 -1.96661716 -0.46665535 14 sp_15 0.595320049 1.09064461
-#> 20563 0 -1.96661716 -0.46665535 15 sp_16 0.595320049 1.09064461
-#> 20573 0 -1.96661716 -0.46665535 19 sp_17 0.595320049 1.09064461
-#> 20583 0 -1.96661716 -0.46665535 9 sp_18 0.595320049 1.09064461
-#> 20593 0 -1.96661716 -0.46665535 15 sp_19 0.595320049 1.09064461
-#> 20603 0 -1.96661716 -0.46665535 16 sp_20 0.595320049 1.09064461
-#> 20613 0 -1.96661716 -0.46665535 8 sp_21 0.595320049 1.09064461
-#> 20623 0 -1.96661716 -0.46665535 9 sp_22 0.595320049 1.09064461
-#> 20633 0 -1.96661716 -0.46665535 16 sp_23 0.595320049 1.09064461
-#> 20643 0 -1.96661716 -0.46665535 9 sp_24 0.595320049 1.09064461
-#> 20653 0 -1.96661716 -0.46665535 2 sp_25 0.595320049 1.09064461
-#> 20663 0 -1.96661716 -0.46665535 9 sp_26 0.595320049 1.09064461
-#> 20673 0 -1.96661716 -0.46665535 11 sp_27 0.595320049 1.09064461
-#> 20683 0 -1.96661716 -0.46665535 11 sp_28 0.595320049 1.09064461
-#> 20693 0 -1.96661716 -0.46665535 4 sp_29 0.595320049 1.09064461
-#> 20703 0 -1.96661716 -0.46665535 7 sp_30 0.595320049 1.09064461
-#> 21613 0 0.70135590 0.77996512 18 sp_1 0.332761273 -1.52645307
-#> 21623 1 0.70135590 0.77996512 11 sp_2 0.332761273 -1.52645307
-#> 21633 1 0.70135590 0.77996512 1 sp_3 0.332761273 -1.52645307
-#> 21643 0 0.70135590 0.77996512 11 sp_4 0.332761273 -1.52645307
-#> 21653 0 0.70135590 0.77996512 6 sp_5 0.332761273 -1.52645307
-#> 21663 0 0.70135590 0.77996512 10 sp_6 0.332761273 -1.52645307
-#> 21673 0 0.70135590 0.77996512 18 sp_7 0.332761273 -1.52645307
-#> 21683 0 0.70135590 0.77996512 3 sp_8 0.332761273 -1.52645307
-#> 21693 0 0.70135590 0.77996512 3 sp_9 0.332761273 -1.52645307
-#> 21703 1 0.70135590 0.77996512 2 sp_10 0.332761273 -1.52645307
-#> 21713 1 0.70135590 0.77996512 8 sp_11 0.332761273 -1.52645307
-#> 21723 1 0.70135590 0.77996512 13 sp_12 0.332761273 -1.52645307
-#> 21733 0 0.70135590 0.77996512 8 sp_13 0.332761273 -1.52645307
-#> 21743 1 0.70135590 0.77996512 2 sp_14 0.332761273 -1.52645307
-#> 21753 0 0.70135590 0.77996512 6 sp_15 0.332761273 -1.52645307
-#> 21763 0 0.70135590 0.77996512 17 sp_16 0.332761273 -1.52645307
-#> 21773 0 0.70135590 0.77996512 14 sp_17 0.332761273 -1.52645307
-#> 21783 1 0.70135590 0.77996512 7 sp_18 0.332761273 -1.52645307
-#> 21793 0 0.70135590 0.77996512 13 sp_19 0.332761273 -1.52645307
-#> 21803 0 0.70135590 0.77996512 8 sp_20 0.332761273 -1.52645307
-#> 21813 0 0.70135590 0.77996512 6 sp_21 0.332761273 -1.52645307
-#> 21823 1 0.70135590 0.77996512 11 sp_22 0.332761273 -1.52645307
-#> 21833 0 0.70135590 0.77996512 10 sp_23 0.332761273 -1.52645307
-#> 21843 0 0.70135590 0.77996512 17 sp_24 0.332761273 -1.52645307
-#> 21853 0 0.70135590 0.77996512 7 sp_25 0.332761273 -1.52645307
-#> 21863 1 0.70135590 0.77996512 12 sp_26 0.332761273 -1.52645307
-#> 21873 0 0.70135590 0.77996512 19 sp_27 0.332761273 -1.52645307
-#> 21883 0 0.70135590 0.77996512 17 sp_28 0.332761273 -1.52645307
-#> 21893 0 0.70135590 0.77996512 8 sp_29 0.332761273 -1.52645307
-#> 21903 0 0.70135590 0.77996512 15 sp_30 0.332761273 -1.52645307
-#> 22813 0 -0.47279141 -0.08336907 14 sp_1 1.399227090 1.51928992
-#> 22823 0 -0.47279141 -0.08336907 14 sp_2 1.399227090 1.51928992
-#> 22833 0 -0.47279141 -0.08336907 17 sp_3 1.399227090 1.51928992
-#> 22843 0 -0.47279141 -0.08336907 1 sp_4 1.399227090 1.51928992
-#> 22853 0 -0.47279141 -0.08336907 18 sp_5 1.399227090 1.51928992
-#> 22863 0 -0.47279141 -0.08336907 18 sp_6 1.399227090 1.51928992
-#> 22873 0 -0.47279141 -0.08336907 20 sp_7 1.399227090 1.51928992
-#> 22883 0 -0.47279141 -0.08336907 10 sp_8 1.399227090 1.51928992
-#> 22893 0 -0.47279141 -0.08336907 10 sp_9 1.399227090 1.51928992
-#> 22903 0 -0.47279141 -0.08336907 9 sp_10 1.399227090 1.51928992
-#> 22913 1 -0.47279141 -0.08336907 19 sp_11 1.399227090 1.51928992
-#> 22923 0 -0.47279141 -0.08336907 18 sp_12 1.399227090 1.51928992
-#> 22933 0 -0.47279141 -0.08336907 18 sp_13 1.399227090 1.51928992
-#> 22943 0 -0.47279141 -0.08336907 12 sp_14 1.399227090 1.51928992
-#> 22953 0 -0.47279141 -0.08336907 12 sp_15 1.399227090 1.51928992
-#> 22963 0 -0.47279141 -0.08336907 4 sp_16 1.399227090 1.51928992
-#> 22973 0 -0.47279141 -0.08336907 20 sp_17 1.399227090 1.51928992
-#> 22983 0 -0.47279141 -0.08336907 10 sp_18 1.399227090 1.51928992
-#> 22993 0 -0.47279141 -0.08336907 5 sp_19 1.399227090 1.51928992
-#> 23003 0 -0.47279141 -0.08336907 2 sp_20 1.399227090 1.51928992
-#> 23013 0 -0.47279141 -0.08336907 18 sp_21 1.399227090 1.51928992
-#> 23023 0 -0.47279141 -0.08336907 12 sp_22 1.399227090 1.51928992
-#> 23033 0 -0.47279141 -0.08336907 13 sp_23 1.399227090 1.51928992
-#> 23043 0 -0.47279141 -0.08336907 11 sp_24 1.399227090 1.51928992
-#> 23053 0 -0.47279141 -0.08336907 19 sp_25 1.399227090 1.51928992
-#> 23063 0 -0.47279141 -0.08336907 6 sp_26 1.399227090 1.51928992
-#> 23073 0 -0.47279141 -0.08336907 18 sp_27 1.399227090 1.51928992
-#> 23083 0 -0.47279141 -0.08336907 10 sp_28 1.399227090 1.51928992
-#> 23093 0 -0.47279141 -0.08336907 9 sp_29 1.399227090 1.51928992
-#> 23103 0 -0.47279141 -0.08336907 3 sp_30 1.399227090 1.51928992
-#> 24013 0 -1.06782371 0.25331851 19 sp_1 1.063030449 0.45208542
-#> 24023 0 -1.06782371 0.25331851 8 sp_2 1.063030449 0.45208542
-#> 24033 0 -1.06782371 0.25331851 13 sp_3 1.063030449 0.45208542
-#> 24043 0 -1.06782371 0.25331851 1 sp_4 1.063030449 0.45208542
-#> 24053 1 -1.06782371 0.25331851 2 sp_5 1.063030449 0.45208542
-#> 24063 0 -1.06782371 0.25331851 11 sp_6 1.063030449 0.45208542
-#> 24073 0 -1.06782371 0.25331851 16 sp_7 1.063030449 0.45208542
-#> 24083 0 -1.06782371 0.25331851 5 sp_8 1.063030449 0.45208542
-#> 24093 0 -1.06782371 0.25331851 4 sp_9 1.063030449 0.45208542
-#> 24103 0 -1.06782371 0.25331851 3 sp_10 1.063030449 0.45208542
-#> 24115 0 -1.06782371 0.25331851 15 sp_11 1.063030449 0.45208542
-#> 24123 0 -1.06782371 0.25331851 10 sp_12 1.063030449 0.45208542
-#> 24133 0 -1.06782371 0.25331851 7 sp_13 1.063030449 0.45208542
-#> 24143 0 -1.06782371 0.25331851 7 sp_14 1.063030449 0.45208542
-#> 24153 0 -1.06782371 0.25331851 2 sp_15 1.063030449 0.45208542
-#> 24163 0 -1.06782371 0.25331851 18 sp_16 1.063030449 0.45208542
-#> 24173 0 -1.06782371 0.25331851 18 sp_17 1.063030449 0.45208542
-#> 24183 0 -1.06782371 0.25331851 3 sp_18 1.063030449 0.45208542
-#> 24193 0 -1.06782371 0.25331851 8 sp_19 1.063030449 0.45208542
-#> 24203 0 -1.06782371 0.25331851 14 sp_20 1.063030449 0.45208542
-#> 24215 0 -1.06782371 0.25331851 9 sp_21 1.063030449 0.45208542
-#> 24223 0 -1.06782371 0.25331851 15 sp_22 1.063030449 0.45208542
-#> 24233 0 -1.06782371 0.25331851 17 sp_23 1.063030449 0.45208542
-#> 24243 0 -1.06782371 0.25331851 7 sp_24 1.063030449 0.45208542
-#> 24253 0 -1.06782371 0.25331851 8 sp_25 1.063030449 0.45208542
-#> 24263 0 -1.06782371 0.25331851 1 sp_26 1.063030449 0.45208542
-#> 24273 0 -1.06782371 0.25331851 9 sp_27 1.063030449 0.45208542
-#> 24283 0 -1.06782371 0.25331851 3 sp_28 1.063030449 0.45208542
-#> 24293 0 -1.06782371 0.25331851 2 sp_29 1.063030449 0.45208542
-#> 24303 0 -1.06782371 0.25331851 11 sp_30 1.063030449 0.45208542
-#> 25215 0 -0.21797491 -0.02854676 4 sp_1 -0.209313656 -0.07923944
-#> 25223 0 -0.21797491 -0.02854676 8 sp_2 -0.209313656 -0.07923944
-#> 25233 0 -0.21797491 -0.02854676 20 sp_3 -0.209313656 -0.07923944
-#> 25243 0 -0.21797491 -0.02854676 11 sp_4 -0.209313656 -0.07923944
-#> 25253 0 -0.21797491 -0.02854676 18 sp_5 -0.209313656 -0.07923944
-#> 25263 1 -0.21797491 -0.02854676 14 sp_6 -0.209313656 -0.07923944
-#> 25273 0 -0.21797491 -0.02854676 3 sp_7 -0.209313656 -0.07923944
-#> 25283 1 -0.21797491 -0.02854676 3 sp_8 -0.209313656 -0.07923944
-#> 25293 0 -0.21797491 -0.02854676 14 sp_9 -0.209313656 -0.07923944
-#> 25303 0 -0.21797491 -0.02854676 7 sp_10 -0.209313656 -0.07923944
-#> 25315 0 -0.21797491 -0.02854676 15 sp_11 -0.209313656 -0.07923944
-#> 25323 0 -0.21797491 -0.02854676 8 sp_12 -0.209313656 -0.07923944
-#> 25333 0 -0.21797491 -0.02854676 1 sp_13 -0.209313656 -0.07923944
-#> 25343 0 -0.21797491 -0.02854676 5 sp_14 -0.209313656 -0.07923944
-#> 25353 1 -0.21797491 -0.02854676 17 sp_15 -0.209313656 -0.07923944
-#> 25363 0 -0.21797491 -0.02854676 6 sp_16 -0.209313656 -0.07923944
-#> 25373 0 -0.21797491 -0.02854676 10 sp_17 -0.209313656 -0.07923944
-#> 25383 0 -0.21797491 -0.02854676 12 sp_18 -0.209313656 -0.07923944
-#> 25393 0 -0.21797491 -0.02854676 8 sp_19 -0.209313656 -0.07923944
-#> 25403 0 -0.21797491 -0.02854676 16 sp_20 -0.209313656 -0.07923944
-#> 25415 0 -0.21797491 -0.02854676 7 sp_21 -0.209313656 -0.07923944
-#> 25423 0 -0.21797491 -0.02854676 7 sp_22 -0.209313656 -0.07923944
-#> 25433 0 -0.21797491 -0.02854676 1 sp_23 -0.209313656 -0.07923944
-#> 25443 0 -0.21797491 -0.02854676 11 sp_24 -0.209313656 -0.07923944
-#> 25453 0 -0.21797491 -0.02854676 3 sp_25 -0.209313656 -0.07923944
-#> 25463 0 -0.21797491 -0.02854676 17 sp_26 -0.209313656 -0.07923944
-#> 25473 0 -0.21797491 -0.02854676 20 sp_27 -0.209313656 -0.07923944
-#> 25483 0 -0.21797491 -0.02854676 3 sp_28 -0.209313656 -0.07923944
-#> 25493 0 -0.21797491 -0.02854676 14 sp_29 -0.209313656 -0.07923944
-#> 25503 0 -0.21797491 -0.02854676 5 sp_30 -0.209313656 -0.07923944
-#> 26415 0 -1.02600445 -0.04287046 18 sp_1 -0.001595076 0.30556929
-#> 26423 0 -1.02600445 -0.04287046 8 sp_2 -0.001595076 0.30556929
-#> 26433 0 -1.02600445 -0.04287046 20 sp_3 -0.001595076 0.30556929
-#> 26443 0 -1.02600445 -0.04287046 10 sp_4 -0.001595076 0.30556929
-#> 26453 1 -1.02600445 -0.04287046 18 sp_5 -0.001595076 0.30556929
-#> 26463 0 -1.02600445 -0.04287046 17 sp_6 -0.001595076 0.30556929
-#> 26473 0 -1.02600445 -0.04287046 9 sp_7 -0.001595076 0.30556929
-#> 26483 0 -1.02600445 -0.04287046 3 sp_8 -0.001595076 0.30556929
-#> 26493 0 -1.02600445 -0.04287046 5 sp_9 -0.001595076 0.30556929
-#> 26503 0 -1.02600445 -0.04287046 16 sp_10 -0.001595076 0.30556929
-#> 26515 0 -1.02600445 -0.04287046 20 sp_11 -0.001595076 0.30556929
-#> 26523 0 -1.02600445 -0.04287046 3 sp_12 -0.001595076 0.30556929
-#> 26533 0 -1.02600445 -0.04287046 3 sp_13 -0.001595076 0.30556929
-#> 26543 0 -1.02600445 -0.04287046 13 sp_14 -0.001595076 0.30556929
-#> 26553 0 -1.02600445 -0.04287046 4 sp_15 -0.001595076 0.30556929
-#> 26563 0 -1.02600445 -0.04287046 15 sp_16 -0.001595076 0.30556929
-#> 26573 0 -1.02600445 -0.04287046 19 sp_17 -0.001595076 0.30556929
-#> 26583 0 -1.02600445 -0.04287046 13 sp_18 -0.001595076 0.30556929
-#> 26593 0 -1.02600445 -0.04287046 12 sp_19 -0.001595076 0.30556929
-#> 26603 0 -1.02600445 -0.04287046 20 sp_20 -0.001595076 0.30556929
-#> 26615 0 -1.02600445 -0.04287046 13 sp_21 -0.001595076 0.30556929
-#> 26623 0 -1.02600445 -0.04287046 13 sp_22 -0.001595076 0.30556929
-#> 26633 0 -1.02600445 -0.04287046 3 sp_23 -0.001595076 0.30556929
-#> 26643 0 -1.02600445 -0.04287046 20 sp_24 -0.001595076 0.30556929
-#> 26653 0 -1.02600445 -0.04287046 5 sp_25 -0.001595076 0.30556929
-#> 26663 0 -1.02600445 -0.04287046 13 sp_26 -0.001595076 0.30556929
-#> 26673 0 -1.02600445 -0.04287046 12 sp_27 -0.001595076 0.30556929
-#> 26683 0 -1.02600445 -0.04287046 8 sp_28 -0.001595076 0.30556929
-#> 26693 0 -1.02600445 -0.04287046 6 sp_29 -0.001595076 0.30556929
-#> 26703 0 -1.02600445 -0.04287046 16 sp_30 -0.001595076 0.30556929
-#> 27613 0 -0.72889123 1.36860228 11 sp_1 -0.403005062 -0.85646918
-#> 27623 0 -0.72889123 1.36860228 12 sp_2 -0.403005062 -0.85646918
-#> 27633 0 -0.72889123 1.36860228 16 sp_3 -0.403005062 -0.85646918
-#> 27643 0 -0.72889123 1.36860228 15 sp_4 -0.403005062 -0.85646918
-#> 27653 0 -0.72889123 1.36860228 1 sp_5 -0.403005062 -0.85646918
-#> 27663 0 -0.72889123 1.36860228 12 sp_6 -0.403005062 -0.85646918
-#> 27673 0 -0.72889123 1.36860228 10 sp_7 -0.403005062 -0.85646918
-#> 27683 0 -0.72889123 1.36860228 10 sp_8 -0.403005062 -0.85646918
-#> 27693 0 -0.72889123 1.36860228 4 sp_9 -0.403005062 -0.85646918
-#> 27703 0 -0.72889123 1.36860228 9 sp_10 -0.403005062 -0.85646918
-#> 27713 0 -0.72889123 1.36860228 20 sp_11 -0.403005062 -0.85646918
-#> 27723 0 -0.72889123 1.36860228 5 sp_12 -0.403005062 -0.85646918
-#> 27733 0 -0.72889123 1.36860228 9 sp_13 -0.403005062 -0.85646918
-#> 27743 0 -0.72889123 1.36860228 19 sp_14 -0.403005062 -0.85646918
-#> 27753 0 -0.72889123 1.36860228 3 sp_15 -0.403005062 -0.85646918
-#> 27763 0 -0.72889123 1.36860228 2 sp_16 -0.403005062 -0.85646918
-#> 27773 0 -0.72889123 1.36860228 12 sp_17 -0.403005062 -0.85646918
-#> 27783 1 -0.72889123 1.36860228 15 sp_18 -0.403005062 -0.85646918
-#> 27793 0 -0.72889123 1.36860228 17 sp_19 -0.403005062 -0.85646918
-#> 27803 0 -0.72889123 1.36860228 3 sp_20 -0.403005062 -0.85646918
-#> 27813 0 -0.72889123 1.36860228 7 sp_21 -0.403005062 -0.85646918
-#> 27823 0 -0.72889123 1.36860228 13 sp_22 -0.403005062 -0.85646918
-#> 27833 0 -0.72889123 1.36860228 14 sp_23 -0.403005062 -0.85646918
-#> 27843 0 -0.72889123 1.36860228 2 sp_24 -0.403005062 -0.85646918
-#> 27853 0 -0.72889123 1.36860228 9 sp_25 -0.403005062 -0.85646918
-#> 27863 0 -0.72889123 1.36860228 15 sp_26 -0.403005062 -0.85646918
-#> 27873 0 -0.72889123 1.36860228 1 sp_27 -0.403005062 -0.85646918
-#> 27883 0 -0.72889123 1.36860228 10 sp_28 -0.403005062 -0.85646918
-#> 27893 0 -0.72889123 1.36860228 9 sp_29 -0.403005062 -0.85646918
-#> 27903 0 -0.72889123 1.36860228 9 sp_30 -0.403005062 -0.85646918
-#> 28813 0 -0.62503927 -0.22577099 7 sp_1 1.324704070 1.10392464
-#> 28823 0 -0.62503927 -0.22577099 18 sp_2 1.324704070 1.10392464
-#> 28833 0 -0.62503927 -0.22577099 12 sp_3 1.324704070 1.10392464
-#> 28843 0 -0.62503927 -0.22577099 6 sp_4 1.324704070 1.10392464
-#> 28853 0 -0.62503927 -0.22577099 7 sp_5 1.324704070 1.10392464
-#> 28863 0 -0.62503927 -0.22577099 16 sp_6 1.324704070 1.10392464
-#> 28873 0 -0.62503927 -0.22577099 16 sp_7 1.324704070 1.10392464
-#> 28883 0 -0.62503927 -0.22577099 2 sp_8 1.324704070 1.10392464
-#> 28893 0 -0.62503927 -0.22577099 2 sp_9 1.324704070 1.10392464
-#> 28903 0 -0.62503927 -0.22577099 14 sp_10 1.324704070 1.10392464
-#> 28913 0 -0.62503927 -0.22577099 7 sp_11 1.324704070 1.10392464
-#> 28923 0 -0.62503927 -0.22577099 6 sp_12 1.324704070 1.10392464
-#> 28933 0 -0.62503927 -0.22577099 4 sp_13 1.324704070 1.10392464
-#> 28943 0 -0.62503927 -0.22577099 3 sp_14 1.324704070 1.10392464
-#> 28953 0 -0.62503927 -0.22577099 14 sp_15 1.324704070 1.10392464
-#> 28963 0 -0.62503927 -0.22577099 19 sp_16 1.324704070 1.10392464
-#> 28973 0 -0.62503927 -0.22577099 14 sp_17 1.324704070 1.10392464
-#> 28983 0 -0.62503927 -0.22577099 16 sp_18 1.324704070 1.10392464
-#> 28993 0 -0.62503927 -0.22577099 10 sp_19 1.324704070 1.10392464
-#> 29003 0 -0.62503927 -0.22577099 12 sp_20 1.324704070 1.10392464
-#> 29013 0 -0.62503927 -0.22577099 18 sp_21 1.324704070 1.10392464
-#> 29023 0 -0.62503927 -0.22577099 3 sp_22 1.324704070 1.10392464
-#> 29033 0 -0.62503927 -0.22577099 1 sp_23 1.324704070 1.10392464
-#> 29043 0 -0.62503927 -0.22577099 12 sp_24 1.324704070 1.10392464
-#> 29053 0 -0.62503927 -0.22577099 17 sp_25 1.324704070 1.10392464
-#> 29063 0 -0.62503927 -0.22577099 1 sp_26 1.324704070 1.10392464
-#> 29073 0 -0.62503927 -0.22577099 4 sp_27 1.324704070 1.10392464
-#> 29083 0 -0.62503927 -0.22577099 19 sp_28 1.324704070 1.10392464
-#> 29093 0 -0.62503927 -0.22577099 13 sp_29 1.324704070 1.10392464
-#> 29103 0 -0.62503927 -0.22577099 18 sp_30 1.324704070 1.10392464
-#> 30013 0 -1.68669331 1.51647060 15 sp_1 -0.531131309 0.78017265
-#> 30023 0 -1.68669331 1.51647060 13 sp_2 -0.531131309 0.78017265
-#> 30033 0 -1.68669331 1.51647060 14 sp_3 -0.531131309 0.78017265
-#> 30043 0 -1.68669331 1.51647060 18 sp_4 -0.531131309 0.78017265
-#> 30053 0 -1.68669331 1.51647060 12 sp_5 -0.531131309 0.78017265
-#> 30063 0 -1.68669331 1.51647060 18 sp_6 -0.531131309 0.78017265
-#> 30073 0 -1.68669331 1.51647060 7 sp_7 -0.531131309 0.78017265
-#> 30083 0 -1.68669331 1.51647060 4 sp_8 -0.531131309 0.78017265
-#> 30093 0 -1.68669331 1.51647060 4 sp_9 -0.531131309 0.78017265
-#> 30103 0 -1.68669331 1.51647060 3 sp_10 -0.531131309 0.78017265
-#> 30113 0 -1.68669331 1.51647060 11 sp_11 -0.531131309 0.78017265
-#> 30123 0 -1.68669331 1.51647060 19 sp_12 -0.531131309 0.78017265
-#> 30133 0 -1.68669331 1.51647060 16 sp_13 -0.531131309 0.78017265
-#> 30143 0 -1.68669331 1.51647060 15 sp_14 -0.531131309 0.78017265
-#> 30153 0 -1.68669331 1.51647060 11 sp_15 -0.531131309 0.78017265
-#> 30163 0 -1.68669331 1.51647060 6 sp_16 -0.531131309 0.78017265
-#> 30173 0 -1.68669331 1.51647060 5 sp_17 -0.531131309 0.78017265
-#> 30183 0 -1.68669331 1.51647060 2 sp_18 -0.531131309 0.78017265
-#> 30193 0 -1.68669331 1.51647060 17 sp_19 -0.531131309 0.78017265
-#> 30203 0 -1.68669331 1.51647060 5 sp_20 -0.531131309 0.78017265
-#> 30213 0 -1.68669331 1.51647060 19 sp_21 -0.531131309 0.78017265
-#> 30223 0 -1.68669331 1.51647060 15 sp_22 -0.531131309 0.78017265
-#> 30233 0 -1.68669331 1.51647060 19 sp_23 -0.531131309 0.78017265
-#> 30243 0 -1.68669331 1.51647060 3 sp_24 -0.531131309 0.78017265
-#> 30253 0 -1.68669331 1.51647060 15 sp_25 -0.531131309 0.78017265
-#> 30263 0 -1.68669331 1.51647060 3 sp_26 -0.531131309 0.78017265
-#> 30273 1 -1.68669331 1.51647060 2 sp_27 -0.531131309 0.78017265
-#> 30283 0 -1.68669331 1.51647060 5 sp_28 -0.531131309 0.78017265
-#> 30293 0 -1.68669331 1.51647060 5 sp_29 -0.531131309 0.78017265
-#> 30303 0 -1.68669331 1.51647060 7 sp_30 -0.531131309 0.78017265
-#> 31213 0 0.83778704 -1.54875280 2 sp_1 0.167775141 -1.40425215
-#> 31223 1 0.83778704 -1.54875280 16 sp_2 0.167775141 -1.40425215
-#> 31233 0 0.83778704 -1.54875280 8 sp_3 0.167775141 -1.40425215
-#> 31243 0 0.83778704 -1.54875280 18 sp_4 0.167775141 -1.40425215
-#> 31253 1 0.83778704 -1.54875280 19 sp_5 0.167775141 -1.40425215
-#> 31263 1 0.83778704 -1.54875280 9 sp_6 0.167775141 -1.40425215
-#> 31273 1 0.83778704 -1.54875280 19 sp_7 0.167775141 -1.40425215
-#> 31283 0 0.83778704 -1.54875280 14 sp_8 0.167775141 -1.40425215
-#> 31293 1 0.83778704 -1.54875280 19 sp_9 0.167775141 -1.40425215
-#> 31303 0 0.83778704 -1.54875280 5 sp_10 0.167775141 -1.40425215
-#> 31313 1 0.83778704 -1.54875280 13 sp_11 0.167775141 -1.40425215
-#> 31323 0 0.83778704 -1.54875280 16 sp_12 0.167775141 -1.40425215
-#> 31333 0 0.83778704 -1.54875280 7 sp_13 0.167775141 -1.40425215
-#> 31343 1 0.83778704 -1.54875280 8 sp_14 0.167775141 -1.40425215
-#> 31353 1 0.83778704 -1.54875280 16 sp_15 0.167775141 -1.40425215
-#> 31363 0 0.83778704 -1.54875280 15 sp_16 0.167775141 -1.40425215
-#> 31373 1 0.83778704 -1.54875280 20 sp_17 0.167775141 -1.40425215
-#> 31383 0 0.83778704 -1.54875280 3 sp_18 0.167775141 -1.40425215
-#> 31393 1 0.83778704 -1.54875280 17 sp_19 0.167775141 -1.40425215
-#> 31403 0 0.83778704 -1.54875280 7 sp_20 0.167775141 -1.40425215
-#> 31413 0 0.83778704 -1.54875280 13 sp_21 0.167775141 -1.40425215
-#> 31423 1 0.83778704 -1.54875280 3 sp_22 0.167775141 -1.40425215
-#> 31433 0 0.83778704 -1.54875280 13 sp_23 0.167775141 -1.40425215
-#> 31443 0 0.83778704 -1.54875280 14 sp_24 0.167775141 -1.40425215
-#> 31453 1 0.83778704 -1.54875280 4 sp_25 0.167775141 -1.40425215
-#> 31463 0 0.83778704 -1.54875280 16 sp_26 0.167775141 -1.40425215
-#> 31473 0 0.83778704 -1.54875280 9 sp_27 0.167775141 -1.40425215
-#> 31483 0 0.83778704 -1.54875280 16 sp_28 0.167775141 -1.40425215
-#> 31493 0 0.83778704 -1.54875280 9 sp_29 0.167775141 -1.40425215
-#> 31503 1 0.83778704 -1.54875280 5 sp_30 0.167775141 -1.40425215
-#> 32413 0 0.15337312 0.58461375 14 sp_1 -1.253938223 -0.88156275
-#> 32423 1 0.15337312 0.58461375 12 sp_2 -1.253938223 -0.88156275
-#> 32433 1 0.15337312 0.58461375 14 sp_3 -1.253938223 -0.88156275
-#> 32443 0 0.15337312 0.58461375 13 sp_4 -1.253938223 -0.88156275
-#> 32453 1 0.15337312 0.58461375 20 sp_5 -1.253938223 -0.88156275
-#> 32463 0 0.15337312 0.58461375 15 sp_6 -1.253938223 -0.88156275
-#> 32473 1 0.15337312 0.58461375 8 sp_7 -1.253938223 -0.88156275
-#> 32483 0 0.15337312 0.58461375 13 sp_8 -1.253938223 -0.88156275
-#> 32493 0 0.15337312 0.58461375 7 sp_9 -1.253938223 -0.88156275
-#> 32503 0 0.15337312 0.58461375 5 sp_10 -1.253938223 -0.88156275
-#> 32513 0 0.15337312 0.58461375 8 sp_11 -1.253938223 -0.88156275
-#> 32523 0 0.15337312 0.58461375 15 sp_12 -1.253938223 -0.88156275
-#> 32533 0 0.15337312 0.58461375 14 sp_13 -1.253938223 -0.88156275
-#> 32543 0 0.15337312 0.58461375 16 sp_14 -1.253938223 -0.88156275
-#> 32553 1 0.15337312 0.58461375 1 sp_15 -1.253938223 -0.88156275
-#> 32563 0 0.15337312 0.58461375 14 sp_16 -1.253938223 -0.88156275
-#> 32573 0 0.15337312 0.58461375 17 sp_17 -1.253938223 -0.88156275
-#> 32583 0 0.15337312 0.58461375 7 sp_18 -1.253938223 -0.88156275
-#> 32593 0 0.15337312 0.58461375 7 sp_19 -1.253938223 -0.88156275
-#> 32603 0 0.15337312 0.58461375 13 sp_20 -1.253938223 -0.88156275
-#> 32613 0 0.15337312 0.58461375 15 sp_21 -1.253938223 -0.88156275
-#> 32623 0 0.15337312 0.58461375 12 sp_22 -1.253938223 -0.88156275
-#> 32633 0 0.15337312 0.58461375 14 sp_23 -1.253938223 -0.88156275
-#> 32643 0 0.15337312 0.58461375 19 sp_24 -1.253938223 -0.88156275
-#> 32653 0 0.15337312 0.58461375 19 sp_25 -1.253938223 -0.88156275
-#> 32663 0 0.15337312 0.58461375 17 sp_26 -1.253938223 -0.88156275
-#> 32673 0 0.15337312 0.58461375 9 sp_27 -1.253938223 -0.88156275
-#> 32683 0 0.15337312 0.58461375 13 sp_28 -1.253938223 -0.88156275
-#> 32693 0 0.15337312 0.58461375 14 sp_29 -1.253938223 -0.88156275
-#> 32703 0 0.15337312 0.58461375 6 sp_30 -1.253938223 -0.88156275
-#> 33613 0 -1.13813694 0.12385424 1 sp_1 1.374599253 -0.17239352
-#> 33623 0 -1.13813694 0.12385424 16 sp_2 1.374599253 -0.17239352
-#> 33633 0 -1.13813694 0.12385424 8 sp_3 1.374599253 -0.17239352
-#> 33643 0 -1.13813694 0.12385424 5 sp_4 1.374599253 -0.17239352
-#> 33653 0 -1.13813694 0.12385424 10 sp_5 1.374599253 -0.17239352
-#> 33663 0 -1.13813694 0.12385424 9 sp_6 1.374599253 -0.17239352
-#> 33673 0 -1.13813694 0.12385424 5 sp_7 1.374599253 -0.17239352
-#> 33683 0 -1.13813694 0.12385424 14 sp_8 1.374599253 -0.17239352
-#> 33693 0 -1.13813694 0.12385424 19 sp_9 1.374599253 -0.17239352
-#> 33703 0 -1.13813694 0.12385424 1 sp_10 1.374599253 -0.17239352
-#> 33713 0 -1.13813694 0.12385424 16 sp_11 1.374599253 -0.17239352
-#> 33723 0 -1.13813694 0.12385424 6 sp_12 1.374599253 -0.17239352
-#> 33733 1 -1.13813694 0.12385424 20 sp_13 1.374599253 -0.17239352
-#> 33743 0 -1.13813694 0.12385424 8 sp_14 1.374599253 -0.17239352
-#> 33753 0 -1.13813694 0.12385424 14 sp_15 1.374599253 -0.17239352
-#> 33763 0 -1.13813694 0.12385424 14 sp_16 1.374599253 -0.17239352
-#> 33773 0 -1.13813694 0.12385424 8 sp_17 1.374599253 -0.17239352
-#> 33783 0 -1.13813694 0.12385424 11 sp_18 1.374599253 -0.17239352
-#> 33793 0 -1.13813694 0.12385424 20 sp_19 1.374599253 -0.17239352
-#> 33803 0 -1.13813694 0.12385424 5 sp_20 1.374599253 -0.17239352
-#> 33813 0 -1.13813694 0.12385424 14 sp_21 1.374599253 -0.17239352
-#> 33823 0 -1.13813694 0.12385424 1 sp_22 1.374599253 -0.17239352
-#> 33833 0 -1.13813694 0.12385424 1 sp_23 1.374599253 -0.17239352
-#> 33843 0 -1.13813694 0.12385424 5 sp_24 1.374599253 -0.17239352
-#> 33853 0 -1.13813694 0.12385424 3 sp_25 1.374599253 -0.17239352
-#> 33863 0 -1.13813694 0.12385424 4 sp_26 1.374599253 -0.17239352
-#> 33873 0 -1.13813694 0.12385424 3 sp_27 1.374599253 -0.17239352
-#> 33883 1 -1.13813694 0.12385424 14 sp_28 1.374599253 -0.17239352
-#> 33893 0 -1.13813694 0.12385424 18 sp_29 1.374599253 -0.17239352
-#> 33903 0 -1.13813694 0.12385424 10 sp_30 1.374599253 -0.17239352
-#> 34813 0 1.25381492 0.21594157 12 sp_1 1.307855946 -0.88732783
-#> 34823 1 1.25381492 0.21594157 16 sp_2 1.307855946 -0.88732783
-#> 34833 0 1.25381492 0.21594157 3 sp_3 1.307855946 -0.88732783
-#> 34843 1 1.25381492 0.21594157 12 sp_4 1.307855946 -0.88732783
-#> 34853 1 1.25381492 0.21594157 5 sp_5 1.307855946 -0.88732783
-#> 34863 1 1.25381492 0.21594157 13 sp_6 1.307855946 -0.88732783
-#> 34873 1 1.25381492 0.21594157 8 sp_7 1.307855946 -0.88732783
-#> 34883 1 1.25381492 0.21594157 17 sp_8 1.307855946 -0.88732783
-#> 34893 1 1.25381492 0.21594157 5 sp_9 1.307855946 -0.88732783
-#> 34903 0 1.25381492 0.21594157 19 sp_10 1.307855946 -0.88732783
-#> 34913 1 1.25381492 0.21594157 6 sp_11 1.307855946 -0.88732783
-#> 34923 1 1.25381492 0.21594157 2 sp_12 1.307855946 -0.88732783
-#> 34933 1 1.25381492 0.21594157 17 sp_13 1.307855946 -0.88732783
-#> 34943 1 1.25381492 0.21594157 17 sp_14 1.307855946 -0.88732783
-#> 34953 1 1.25381492 0.21594157 8 sp_15 1.307855946 -0.88732783
-#> 34963 0 1.25381492 0.21594157 19 sp_16 1.307855946 -0.88732783
-#> 34973 1 1.25381492 0.21594157 18 sp_17 1.307855946 -0.88732783
-#> 34983 0 1.25381492 0.21594157 19 sp_18 1.307855946 -0.88732783
-#> 34993 1 1.25381492 0.21594157 5 sp_19 1.307855946 -0.88732783
-#> 35003 0 1.25381492 0.21594157 14 sp_20 1.307855946 -0.88732783
-#> 35013 1 1.25381492 0.21594157 12 sp_21 1.307855946 -0.88732783
-#> 35023 0 1.25381492 0.21594157 1 sp_22 1.307855946 -0.88732783
-#> 35033 1 1.25381492 0.21594157 16 sp_23 1.307855946 -0.88732783
-#> 35043 0 1.25381492 0.21594157 18 sp_24 1.307855946 -0.88732783
-#> 35053 1 1.25381492 0.21594157 20 sp_25 1.307855946 -0.88732783
-#> 35063 1 1.25381492 0.21594157 7 sp_26 1.307855946 -0.88732783
-#> 35073 1 1.25381492 0.21594157 5 sp_27 1.307855946 -0.88732783
-#> 35083 0 1.25381492 0.21594157 10 sp_28 1.307855946 -0.88732783
-#> 35093 1 1.25381492 0.21594157 4 sp_29 1.307855946 -0.88732783
-#> 35103 1 1.25381492 0.21594157 8 sp_30 1.307855946 -0.88732783
-#> ff_n_unit ff_n_rep ff_Q ff_unit ff_rep_index1 ff_rep_index2 ff_rep_index3
-#> 1 900 4 1 1 1 901 1801
-#> 2 -99 4 0 2 2 902 1802
-#> 3 -99 4 0 3 3 903 1803
-#> 4 -99 4 0 4 4 904 1804
-#> 5 -99 4 1 5 5 905 1805
-#> 6 -99 4 0 6 6 906 1806
-#> 7 -99 4 0 7 7 907 1807
-#> 8 -99 4 0 8 8 908 1808
-#> 9 -99 4 0 9 9 909 1809
-#> 10 -99 4 0 10 10 910 1810
-#> 11 -99 4 1 11 11 911 1811
-#> 12 -99 4 0 12 12 912 1812
-#> 13 -99 4 1 13 13 913 1813
-#> 14 -99 4 0 14 14 914 1814
-#> 15 -99 4 0 15 15 915 1815
-#> 16 -99 4 0 16 16 916 1816
-#> 17 -99 4 1 17 17 917 1817
-#> 18 -99 4 0 18 18 918 1818
-#> 19 -99 4 0 19 19 919 1819
-#> 20 -99 4 1 20 20 920 1820
-#> 21 -99 4 0 21 21 921 1821
-#> 22 -99 4 0 22 22 922 1822
-#> 23 -99 4 0 23 23 923 1823
-#> 24 -99 4 1 24 24 924 1824
-#> 25 -99 4 0 25 25 925 1825
-#> 26 -99 4 0 26 26 926 1826
-#> 27 -99 4 1 27 27 927 1827
-#> 28 -99 4 0 28 28 928 1828
-#> 29 -99 4 0 29 29 929 1829
-#> 30 -99 4 0 30 30 930 1830
-#> 121 -99 4 0 31 31 931 1831
-#> 122 -99 4 0 32 32 932 1832
-#> 123 -99 4 0 33 33 933 1833
-#> 124 -99 4 0 34 34 934 1834
-#> 125 -99 4 0 35 35 935 1835
-#> 126 -99 4 1 36 36 936 1836
-#> 127 -99 4 1 37 37 937 1837
-#> 128 -99 4 0 38 38 938 1838
-#> 129 -99 4 0 39 39 939 1839
-#> 130 -99 4 0 40 40 940 1840
-#> 131 -99 4 1 41 41 941 1841
-#> 132 -99 4 1 42 42 942 1842
-#> 133 -99 4 0 43 43 943 1843
-#> 134 -99 4 0 44 44 944 1844
-#> 135 -99 4 0 45 45 945 1845
-#> 136 -99 4 1 46 46 946 1846
-#> 137 -99 4 0 47 47 947 1847
-#> 138 -99 4 1 48 48 948 1848
-#> 139 -99 4 1 49 49 949 1849
-#> 140 -99 4 0 50 50 950 1850
-#> 141 -99 4 0 51 51 951 1851
-#> 142 -99 4 1 52 52 952 1852
-#> 143 -99 4 1 53 53 953 1853
-#> 144 -99 4 0 54 54 954 1854
-#> 145 -99 4 0 55 55 955 1855
-#> 146 -99 4 0 56 56 956 1856
-#> 147 -99 4 0 57 57 957 1857
-#> 148 -99 4 0 58 58 958 1858
-#> 149 -99 4 1 59 59 959 1859
-#> 150 -99 4 0 60 60 960 1860
-#> 241 -99 4 0 61 61 961 1861
-#> 242 -99 4 1 62 62 962 1862
-#> 243 -99 4 0 63 63 963 1863
-#> 244 -99 4 1 64 64 964 1864
-#> 245 -99 4 1 65 65 965 1865
-#> 246 -99 4 1 66 66 966 1866
-#> 247 -99 4 1 67 67 967 1867
-#> 248 -99 4 0 68 68 968 1868
-#> 249 -99 4 1 69 69 969 1869
-#> 250 -99 4 1 70 70 970 1870
-#> 251 -99 4 0 71 71 971 1871
-#> 252 -99 4 1 72 72 972 1872
-#> 253 -99 4 0 73 73 973 1873
-#> 254 -99 4 0 74 74 974 1874
-#> 255 -99 4 1 75 75 975 1875
-#> 256 -99 4 1 76 76 976 1876
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-#> 260 -99 4 0 80 80 980 1880
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-#> 484 -99 4 0 124 124 1024 1924
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-#> 486 -99 4 0 126 126 1026 1926
-#> 487 -99 4 0 127 127 1027 1927
-#> 488 -99 4 0 128 128 1028 1928
-#> 489 -99 4 1 129 129 1029 1929
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-#> 491 -99 4 1 131 131 1031 1931
-#> 492 -99 4 0 132 132 1032 1932
-#> 493 -99 4 0 133 133 1033 1933
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-#> 501 -99 4 0 141 141 1041 1941
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-#> 614 -99 4 0 164 164 1064 1964
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-#> 1828 -99 4 1 478 478 1378 2278
-#> 1829 -99 4 1 479 479 1379 2279
-#> 1830 -99 4 1 480 480 1380 2280
-#> 1921 -99 4 1 481 481 1381 2281
-#> 1922 -99 4 1 482 482 1382 2282
-#> 1923 -99 4 0 483 483 1383 2283
-#> 1924 -99 4 0 484 484 1384 2284
-#> 1925 -99 4 1 485 485 1385 2285
-#> 1926 -99 4 1 486 486 1386 2286
-#> 1927 -99 4 1 487 487 1387 2287
-#> 1928 -99 4 0 488 488 1388 2288
-#> 1929 -99 4 0 489 489 1389 2289
-#> 1930 -99 4 1 490 490 1390 2290
-#> 1931 -99 4 1 491 491 1391 2291
-#> 1932 -99 4 1 492 492 1392 2292
-#> 1933 -99 4 1 493 493 1393 2293
-#> 1934 -99 4 0 494 494 1394 2294
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-#> 1939 -99 4 1 499 499 1399 2299
-#> 1940 -99 4 0 500 500 1400 2300
-#> 1941 -99 4 1 501 501 1401 2301
-#> 1942 -99 4 1 502 502 1402 2302
-#> 1943 -99 4 0 503 503 1403 2303
-#> 1944 -99 4 0 504 504 1404 2304
-#> 1945 -99 4 1 505 505 1405 2305
-#> 1946 -99 4 1 506 506 1406 2306
-#> 1947 -99 4 0 507 507 1407 2307
-#> 1948 -99 4 0 508 508 1408 2308
-#> 1949 -99 4 0 509 509 1409 2309
-#> 1950 -99 4 0 510 510 1410 2310
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-#> 1 2701
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-#> 1940 3200
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-#> 1942 3202
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-#>
-#> $n_rep
-#> [1] 4
-#>
-#> $type
-#> [1] "single"
-#>
-#> $unit_covs
-#> [1] "uc1" "uc2" "grp" "species"
-#>
-#> $event_covs
-#> [1] "ec1" "ec2"
-#>
-#> attr(,"class")
-#> [1] "list" "flocker_data"
-
flock()
.R/make_flocker_data.R
- make_flocker_data_augmented.Rd
#' Format data for data-augmented occupancy model, to be passed to
- flock()
.
make_flocker_data_augmented(
- obs,
- n_aug,
- site_covs = NULL,
- event_covs = NULL,
- quiet = FALSE
-)
An I x J x K array where rows I are sites, columns J are -repeat sampling events, and slices K are species. Allowable values are 1 -(detection), 0 (no detection), and NA (no sampling event). - The data must be formatted so that all NAs are trailing within their rows.
Number of pseudospecies to augment
A dataframe of covariates for each site that are constant -across repeated sampling events.
A named list of I x J matrices, each one corresponding to a -covariate that varies across repeated sampling events within sites
Hide progress bars and informational messages?
A flocker_data list that can be passed as data to flocker()
.
flock()
.R/make_flocker_data.R
- make_flocker_data_dynamic.Rd
Format data for dynamic (multi-season) occupancy model, to be passed to
- flock()
.
make_flocker_data_dynamic(
- obs,
- unit_covs = NULL,
- event_covs = NULL,
- quiet = FALSE
-)
An I x J x K array where closure is assumed across rows, columns -are repeated sampling events, and slices along the third dimension are -seasons. Allowable values are 1 (detection), 0 (no detection), and NA (no -sampling event). -The data must be formatted so that all NAs are trailing within their rows -across repeat visits, but not necessarily across seasons.
A list of dataframes (one per season) of covariates for -each closure-unit that are constant across repeated sampling events within -units. All dataframes must have identical column names and types, and all -dataframes must have I rows.
A named list of I x J x K arrays, each one corresponding to -a covariate that varies across repeated sampling events within closure-units
Hide progress bars and informational messages?
A flocker_data list that can be passed as data to flock()
.
flock()
.R/make_flocker_data.R
- make_flocker_data_static.Rd
Format data for single-season occupancy model, to be passed to
- flock()
.
make_flocker_data_static(
- obs,
- unit_covs = NULL,
- event_covs = NULL,
- quiet = FALSE
-)
An I x J matrix-like object where closure is assumed across rows -and columns are repeated sampling events. Allowable values are 1 (detection), -0 (no detection), and NA (no sampling event).
A dataframe of covariates for each unit that are constant -across repeated sampling events within closure-units.
A named list of I x J matrices, each one corresponding to a covariate -that varies across repeated sampling events within closure-units
Hide progress bars and informational messages?
A flocker_data list that can be passed as data to flock()
.
make_flocker_data(
- example_flocker_data$obs,
- example_flocker_data$unit_covs,
- example_flocker_data$event_covs
-)
-#> Formatting data for a single-season occupancy model. For details, see make_flocker_data_static. All warnings and error messages should be interpreted in the context of make_flocker_data_static
-#> $data
-#> ff_y uc1 uc2 grp species ec1 ec2
-#> 1 0 -0.56047565 0.42646422 7 sp_1 0.321519971 -0.96540472
-#> 2 0 -0.56047565 0.42646422 3 sp_2 0.321519971 -0.96540472
-#> 3 0 -0.56047565 0.42646422 15 sp_3 0.321519971 -0.96540472
-#> 4 0 -0.56047565 0.42646422 5 sp_4 0.321519971 -0.96540472
-#> 5 1 -0.56047565 0.42646422 8 sp_5 0.321519971 -0.96540472
-#> 6 0 -0.56047565 0.42646422 19 sp_6 0.321519971 -0.96540472
-#> 7 0 -0.56047565 0.42646422 10 sp_7 0.321519971 -0.96540472
-#> 8 0 -0.56047565 0.42646422 18 sp_8 0.321519971 -0.96540472
-#> 9 0 -0.56047565 0.42646422 10 sp_9 0.321519971 -0.96540472
-#> 10 0 -0.56047565 0.42646422 12 sp_10 0.321519971 -0.96540472
-#> 11 1 -0.56047565 0.42646422 2 sp_11 0.321519971 -0.96540472
-#> 12 0 -0.56047565 0.42646422 10 sp_12 0.321519971 -0.96540472
-#> 13 0 -0.56047565 0.42646422 12 sp_13 0.321519971 -0.96540472
-#> 14 0 -0.56047565 0.42646422 20 sp_14 0.321519971 -0.96540472
-#> 15 0 -0.56047565 0.42646422 14 sp_15 0.321519971 -0.96540472
-#> 16 0 -0.56047565 0.42646422 17 sp_16 0.321519971 -0.96540472
-#> 17 1 -0.56047565 0.42646422 14 sp_17 0.321519971 -0.96540472
-#> 18 0 -0.56047565 0.42646422 3 sp_18 0.321519971 -0.96540472
-#> 19 0 -0.56047565 0.42646422 8 sp_19 0.321519971 -0.96540472
-#> 20 1 -0.56047565 0.42646422 14 sp_20 0.321519971 -0.96540472
-#> 21 0 -0.56047565 0.42646422 19 sp_21 0.321519971 -0.96540472
-#> 22 0 -0.56047565 0.42646422 15 sp_22 0.321519971 -0.96540472
-#> 23 0 -0.56047565 0.42646422 17 sp_23 0.321519971 -0.96540472
-#> 24 0 -0.56047565 0.42646422 11 sp_24 0.321519971 -0.96540472
-#> 25 0 -0.56047565 0.42646422 7 sp_25 0.321519971 -0.96540472
-#> 26 0 -0.56047565 0.42646422 15 sp_26 0.321519971 -0.96540472
-#> 27 1 -0.56047565 0.42646422 6 sp_27 0.321519971 -0.96540472
-#> 28 0 -0.56047565 0.42646422 14 sp_28 0.321519971 -0.96540472
-#> 29 0 -0.56047565 0.42646422 7 sp_29 0.321519971 -0.96540472
-#> 30 0 -0.56047565 0.42646422 10 sp_30 0.321519971 -0.96540472
-#> 121 0 -0.23017749 -0.29507148 5 sp_1 0.545146877 -1.18355753
-#> 122 0 -0.23017749 -0.29507148 6 sp_2 0.545146877 -1.18355753
-#> 123 0 -0.23017749 -0.29507148 16 sp_3 0.545146877 -1.18355753
-#> 124 0 -0.23017749 -0.29507148 11 sp_4 0.545146877 -1.18355753
-#> 125 0 -0.23017749 -0.29507148 4 sp_5 0.545146877 -1.18355753
-#> 126 1 -0.23017749 -0.29507148 12 sp_6 0.545146877 -1.18355753
-#> 127 0 -0.23017749 -0.29507148 14 sp_7 0.545146877 -1.18355753
-#> 128 0 -0.23017749 -0.29507148 19 sp_8 0.545146877 -1.18355753
-#> 129 0 -0.23017749 -0.29507148 7 sp_9 0.545146877 -1.18355753
-#> 130 0 -0.23017749 -0.29507148 9 sp_10 0.545146877 -1.18355753
-#> 131 1 -0.23017749 -0.29507148 7 sp_11 0.545146877 -1.18355753
-#> 132 0 -0.23017749 -0.29507148 2 sp_12 0.545146877 -1.18355753
-#> 133 0 -0.23017749 -0.29507148 16 sp_13 0.545146877 -1.18355753
-#> 134 0 -0.23017749 -0.29507148 13 sp_14 0.545146877 -1.18355753
-#> 135 0 -0.23017749 -0.29507148 19 sp_15 0.545146877 -1.18355753
-#> 136 1 -0.23017749 -0.29507148 20 sp_16 0.545146877 -1.18355753
-#> 137 0 -0.23017749 -0.29507148 15 sp_17 0.545146877 -1.18355753
-#> 138 0 -0.23017749 -0.29507148 7 sp_18 0.545146877 -1.18355753
-#> 139 1 -0.23017749 -0.29507148 4 sp_19 0.545146877 -1.18355753
-#> 140 0 -0.23017749 -0.29507148 1 sp_20 0.545146877 -1.18355753
-#> 141 0 -0.23017749 -0.29507148 8 sp_21 0.545146877 -1.18355753
-#> 142 1 -0.23017749 -0.29507148 20 sp_22 0.545146877 -1.18355753
-#> 143 1 -0.23017749 -0.29507148 16 sp_23 0.545146877 -1.18355753
-#> 144 0 -0.23017749 -0.29507148 11 sp_24 0.545146877 -1.18355753
-#> 145 0 -0.23017749 -0.29507148 16 sp_25 0.545146877 -1.18355753
-#> 146 0 -0.23017749 -0.29507148 20 sp_26 0.545146877 -1.18355753
-#> 147 0 -0.23017749 -0.29507148 8 sp_27 0.545146877 -1.18355753
-#> 148 0 -0.23017749 -0.29507148 3 sp_28 0.545146877 -1.18355753
-#> 149 1 -0.23017749 -0.29507148 4 sp_29 0.545146877 -1.18355753
-#> 150 0 -0.23017749 -0.29507148 20 sp_30 0.545146877 -1.18355753
-#> 241 0 1.55870831 0.89512566 12 sp_1 -0.636097623 0.76339802
-#> 242 1 1.55870831 0.89512566 17 sp_2 -0.636097623 0.76339802
-#> 243 0 1.55870831 0.89512566 10 sp_3 -0.636097623 0.76339802
-#> 244 0 1.55870831 0.89512566 20 sp_4 -0.636097623 0.76339802
-#> 245 1 1.55870831 0.89512566 11 sp_5 -0.636097623 0.76339802
-#> 246 0 1.55870831 0.89512566 8 sp_6 -0.636097623 0.76339802
-#> 247 0 1.55870831 0.89512566 14 sp_7 -0.636097623 0.76339802
-#> 248 0 1.55870831 0.89512566 13 sp_8 -0.636097623 0.76339802
-#> 249 0 1.55870831 0.89512566 2 sp_9 -0.636097623 0.76339802
-#> 250 1 1.55870831 0.89512566 11 sp_10 -0.636097623 0.76339802
-#> 251 0 1.55870831 0.89512566 13 sp_11 -0.636097623 0.76339802
-#> 252 0 1.55870831 0.89512566 14 sp_12 -0.636097623 0.76339802
-#> 253 0 1.55870831 0.89512566 6 sp_13 -0.636097623 0.76339802
-#> 254 0 1.55870831 0.89512566 8 sp_14 -0.636097623 0.76339802
-#> 255 1 1.55870831 0.89512566 12 sp_15 -0.636097623 0.76339802
-#> 256 0 1.55870831 0.89512566 4 sp_16 -0.636097623 0.76339802
-#> 257 0 1.55870831 0.89512566 13 sp_17 -0.636097623 0.76339802
-#> 258 0 1.55870831 0.89512566 14 sp_18 -0.636097623 0.76339802
-#> 259 0 1.55870831 0.89512566 16 sp_19 -0.636097623 0.76339802
-#> 260 0 1.55870831 0.89512566 1 sp_20 -0.636097623 0.76339802
-#> 261 0 1.55870831 0.89512566 8 sp_21 -0.636097623 0.76339802
-#> 262 0 1.55870831 0.89512566 8 sp_22 -0.636097623 0.76339802
-#> 263 0 1.55870831 0.89512566 10 sp_23 -0.636097623 0.76339802
-#> 264 0 1.55870831 0.89512566 8 sp_24 -0.636097623 0.76339802
-#> 265 0 1.55870831 0.89512566 18 sp_25 -0.636097623 0.76339802
-#> 266 0 1.55870831 0.89512566 9 sp_26 -0.636097623 0.76339802
-#> 267 0 1.55870831 0.89512566 7 sp_27 -0.636097623 0.76339802
-#> 268 0 1.55870831 0.89512566 7 sp_28 -0.636097623 0.76339802
-#> 269 0 1.55870831 0.89512566 10 sp_29 -0.636097623 0.76339802
-#> 270 1 1.55870831 0.89512566 11 sp_30 -0.636097623 0.76339802
-#> 361 0 0.07050839 0.87813349 1 sp_1 1.376384123 -0.18537799
-#> 362 0 0.07050839 0.87813349 19 sp_2 1.376384123 -0.18537799
-#> 363 0 0.07050839 0.87813349 10 sp_3 1.376384123 -0.18537799
-#> 364 0 0.07050839 0.87813349 13 sp_4 1.376384123 -0.18537799
-#> 365 1 0.07050839 0.87813349 11 sp_5 1.376384123 -0.18537799
-#> 366 0 0.07050839 0.87813349 11 sp_6 1.376384123 -0.18537799
-#> 367 0 0.07050839 0.87813349 20 sp_7 1.376384123 -0.18537799
-#> 368 0 0.07050839 0.87813349 7 sp_8 1.376384123 -0.18537799
-#> 369 0 0.07050839 0.87813349 20 sp_9 1.376384123 -0.18537799
-#> 370 0 0.07050839 0.87813349 9 sp_10 1.376384123 -0.18537799
-#> 371 0 0.07050839 0.87813349 9 sp_11 1.376384123 -0.18537799
-#> 372 0 0.07050839 0.87813349 5 sp_12 1.376384123 -0.18537799
-#> 373 0 0.07050839 0.87813349 14 sp_13 1.376384123 -0.18537799
-#> 374 0 0.07050839 0.87813349 14 sp_14 1.376384123 -0.18537799
-#> 375 0 0.07050839 0.87813349 6 sp_15 1.376384123 -0.18537799
-#> 376 0 0.07050839 0.87813349 1 sp_16 1.376384123 -0.18537799
-#> 377 1 0.07050839 0.87813349 10 sp_17 1.376384123 -0.18537799
-#> 378 1 0.07050839 0.87813349 17 sp_18 1.376384123 -0.18537799
-#> 379 1 0.07050839 0.87813349 17 sp_19 1.376384123 -0.18537799
-#> 380 0 0.07050839 0.87813349 7 sp_20 1.376384123 -0.18537799
-#> 381 0 0.07050839 0.87813349 9 sp_21 1.376384123 -0.18537799
-#> 382 0 0.07050839 0.87813349 20 sp_22 1.376384123 -0.18537799
-#> 383 0 0.07050839 0.87813349 6 sp_23 1.376384123 -0.18537799
-#> 384 0 0.07050839 0.87813349 18 sp_24 1.376384123 -0.18537799
-#> 385 0 0.07050839 0.87813349 17 sp_25 1.376384123 -0.18537799
-#> 386 0 0.07050839 0.87813349 5 sp_26 1.376384123 -0.18537799
-#> 387 1 0.07050839 0.87813349 20 sp_27 1.376384123 -0.18537799
-#> 388 0 0.07050839 0.87813349 3 sp_28 1.376384123 -0.18537799
-#> 389 0 0.07050839 0.87813349 14 sp_29 1.376384123 -0.18537799
-#> 390 0 0.07050839 0.87813349 1 sp_30 1.376384123 -0.18537799
-#> 481 0 0.12928774 0.82158108 2 sp_1 1.012519248 -0.07935506
-#> 482 0 0.12928774 0.82158108 4 sp_2 1.012519248 -0.07935506
-#> 483 0 0.12928774 0.82158108 10 sp_3 1.012519248 -0.07935506
-#> 484 0 0.12928774 0.82158108 1 sp_4 1.012519248 -0.07935506
-#> 485 0 0.12928774 0.82158108 5 sp_5 1.012519248 -0.07935506
-#> 486 0 0.12928774 0.82158108 8 sp_6 1.012519248 -0.07935506
-#> 487 0 0.12928774 0.82158108 13 sp_7 1.012519248 -0.07935506
-#> 488 0 0.12928774 0.82158108 18 sp_8 1.012519248 -0.07935506
-#> 489 1 0.12928774 0.82158108 10 sp_9 1.012519248 -0.07935506
-#> 490 0 0.12928774 0.82158108 6 sp_10 1.012519248 -0.07935506
-#> 491 0 0.12928774 0.82158108 7 sp_11 1.012519248 -0.07935506
-#> 492 0 0.12928774 0.82158108 9 sp_12 1.012519248 -0.07935506
-#> 493 0 0.12928774 0.82158108 16 sp_13 1.012519248 -0.07935506
-#> 494 1 0.12928774 0.82158108 17 sp_14 1.012519248 -0.07935506
-#> 495 0 0.12928774 0.82158108 13 sp_15 1.012519248 -0.07935506
-#> 496 0 0.12928774 0.82158108 8 sp_16 1.012519248 -0.07935506
-#> 497 0 0.12928774 0.82158108 7 sp_17 1.012519248 -0.07935506
-#> 498 0 0.12928774 0.82158108 20 sp_18 1.012519248 -0.07935506
-#> 499 0 0.12928774 0.82158108 18 sp_19 1.012519248 -0.07935506
-#> 500 0 0.12928774 0.82158108 17 sp_20 1.012519248 -0.07935506
-#> 501 0 0.12928774 0.82158108 1 sp_21 1.012519248 -0.07935506
-#> 502 0 0.12928774 0.82158108 2 sp_22 1.012519248 -0.07935506
-#> 503 0 0.12928774 0.82158108 17 sp_23 1.012519248 -0.07935506
-#> 504 0 0.12928774 0.82158108 2 sp_24 1.012519248 -0.07935506
-#> 505 0 0.12928774 0.82158108 13 sp_25 1.012519248 -0.07935506
-#> 506 0 0.12928774 0.82158108 17 sp_26 1.012519248 -0.07935506
-#> 507 0 0.12928774 0.82158108 3 sp_27 1.012519248 -0.07935506
-#> 508 0 0.12928774 0.82158108 18 sp_28 1.012519248 -0.07935506
-#> 509 0 0.12928774 0.82158108 2 sp_29 1.012519248 -0.07935506
-#> 510 0 0.12928774 0.82158108 5 sp_30 1.012519248 -0.07935506
-#> 601 1 1.71506499 0.68864025 12 sp_1 -0.539895140 0.70220997
-#> 602 0 1.71506499 0.68864025 13 sp_2 -0.539895140 0.70220997
-#> 603 0 1.71506499 0.68864025 10 sp_3 -0.539895140 0.70220997
-#> 604 1 1.71506499 0.68864025 6 sp_4 -0.539895140 0.70220997
-#> 605 0 1.71506499 0.68864025 10 sp_5 -0.539895140 0.70220997
-#> 606 0 1.71506499 0.68864025 10 sp_6 -0.539895140 0.70220997
-#> 607 1 1.71506499 0.68864025 6 sp_7 -0.539895140 0.70220997
-#> 608 0 1.71506499 0.68864025 16 sp_8 -0.539895140 0.70220997
-#> 609 0 1.71506499 0.68864025 16 sp_9 -0.539895140 0.70220997
-#> 610 0 1.71506499 0.68864025 3 sp_10 -0.539895140 0.70220997
-#> 611 0 1.71506499 0.68864025 4 sp_11 -0.539895140 0.70220997
-#> 612 0 1.71506499 0.68864025 3 sp_12 -0.539895140 0.70220997
-#> 613 0 1.71506499 0.68864025 3 sp_13 -0.539895140 0.70220997
-#> 614 0 1.71506499 0.68864025 16 sp_14 -0.539895140 0.70220997
-#> 615 0 1.71506499 0.68864025 2 sp_15 -0.539895140 0.70220997
-#> 616 1 1.71506499 0.68864025 15 sp_16 -0.539895140 0.70220997
-#> 617 0 1.71506499 0.68864025 3 sp_17 -0.539895140 0.70220997
-#> 618 0 1.71506499 0.68864025 9 sp_18 -0.539895140 0.70220997
-#> 619 0 1.71506499 0.68864025 7 sp_19 -0.539895140 0.70220997
-#> 620 0 1.71506499 0.68864025 9 sp_20 -0.539895140 0.70220997
-#> 621 0 1.71506499 0.68864025 4 sp_21 -0.539895140 0.70220997
-#> 622 0 1.71506499 0.68864025 2 sp_22 -0.539895140 0.70220997
-#> 623 0 1.71506499 0.68864025 12 sp_23 -0.539895140 0.70220997
-#> 624 0 1.71506499 0.68864025 9 sp_24 -0.539895140 0.70220997
-#> 625 0 1.71506499 0.68864025 11 sp_25 -0.539895140 0.70220997
-#> 626 0 1.71506499 0.68864025 7 sp_26 -0.539895140 0.70220997
-#> 627 0 1.71506499 0.68864025 13 sp_27 -0.539895140 0.70220997
-#> 628 0 1.71506499 0.68864025 5 sp_28 -0.539895140 0.70220997
-#> 629 0 1.71506499 0.68864025 11 sp_29 -0.539895140 0.70220997
-#> 630 0 1.71506499 0.68864025 1 sp_30 -0.539895140 0.70220997
-#> 721 0 0.46091621 0.55391765 19 sp_1 -1.072417884 1.02610781
-#> 722 0 0.46091621 0.55391765 12 sp_2 -1.072417884 1.02610781
-#> 723 0 0.46091621 0.55391765 2 sp_3 -1.072417884 1.02610781
-#> 724 1 0.46091621 0.55391765 17 sp_4 -1.072417884 1.02610781
-#> 725 0 0.46091621 0.55391765 12 sp_5 -1.072417884 1.02610781
-#> 726 0 0.46091621 0.55391765 3 sp_6 -1.072417884 1.02610781
-#> 727 0 0.46091621 0.55391765 18 sp_7 -1.072417884 1.02610781
-#> 728 0 0.46091621 0.55391765 15 sp_8 -1.072417884 1.02610781
-#> 729 0 0.46091621 0.55391765 3 sp_9 -1.072417884 1.02610781
-#> 730 0 0.46091621 0.55391765 19 sp_10 -1.072417884 1.02610781
-#> 731 0 0.46091621 0.55391765 18 sp_11 -1.072417884 1.02610781
-#> 732 0 0.46091621 0.55391765 17 sp_12 -1.072417884 1.02610781
-#> 733 0 0.46091621 0.55391765 6 sp_13 -1.072417884 1.02610781
-#> 734 0 0.46091621 0.55391765 10 sp_14 -1.072417884 1.02610781
-#> 735 0 0.46091621 0.55391765 8 sp_15 -1.072417884 1.02610781
-#> 736 0 0.46091621 0.55391765 10 sp_16 -1.072417884 1.02610781
-#> 737 0 0.46091621 0.55391765 13 sp_17 -1.072417884 1.02610781
-#> 738 0 0.46091621 0.55391765 20 sp_18 -1.072417884 1.02610781
-#> 739 0 0.46091621 0.55391765 6 sp_19 -1.072417884 1.02610781
-#> 740 0 0.46091621 0.55391765 20 sp_20 -1.072417884 1.02610781
-#> 741 0 0.46091621 0.55391765 20 sp_21 -1.072417884 1.02610781
-#> 742 0 0.46091621 0.55391765 9 sp_22 -1.072417884 1.02610781
-#> 743 0 0.46091621 0.55391765 16 sp_23 -1.072417884 1.02610781
-#> 744 0 0.46091621 0.55391765 8 sp_24 -1.072417884 1.02610781
-#> 745 0 0.46091621 0.55391765 7 sp_25 -1.072417884 1.02610781
-#> 746 0 0.46091621 0.55391765 10 sp_26 -1.072417884 1.02610781
-#> 747 0 0.46091621 0.55391765 17 sp_27 -1.072417884 1.02610781
-#> 748 0 0.46091621 0.55391765 18 sp_28 -1.072417884 1.02610781
-#> 749 0 0.46091621 0.55391765 8 sp_29 -1.072417884 1.02610781
-#> 750 0 0.46091621 0.55391765 19 sp_30 -1.072417884 1.02610781
-#> 841 1 -1.26506123 -0.06191171 10 sp_1 0.428912684 -0.90487124
-#> 842 0 -1.26506123 -0.06191171 11 sp_2 0.428912684 -0.90487124
-#> 843 0 -1.26506123 -0.06191171 17 sp_3 0.428912684 -0.90487124
-#> 844 0 -1.26506123 -0.06191171 12 sp_4 0.428912684 -0.90487124
-#> 845 0 -1.26506123 -0.06191171 2 sp_5 0.428912684 -0.90487124
-#> 846 0 -1.26506123 -0.06191171 19 sp_6 0.428912684 -0.90487124
-#> 847 0 -1.26506123 -0.06191171 13 sp_7 0.428912684 -0.90487124
-#> 848 0 -1.26506123 -0.06191171 13 sp_8 0.428912684 -0.90487124
-#> 849 0 -1.26506123 -0.06191171 19 sp_9 0.428912684 -0.90487124
-#> 850 1 -1.26506123 -0.06191171 10 sp_10 0.428912684 -0.90487124
-#> 851 0 -1.26506123 -0.06191171 16 sp_11 0.428912684 -0.90487124
-#> 852 1 -1.26506123 -0.06191171 5 sp_12 0.428912684 -0.90487124
-#> 853 0 -1.26506123 -0.06191171 4 sp_13 0.428912684 -0.90487124
-#> 854 0 -1.26506123 -0.06191171 18 sp_14 0.428912684 -0.90487124
-#> 855 0 -1.26506123 -0.06191171 1 sp_15 0.428912684 -0.90487124
-#> 856 0 -1.26506123 -0.06191171 16 sp_16 0.428912684 -0.90487124
-#> 857 0 -1.26506123 -0.06191171 17 sp_17 0.428912684 -0.90487124
-#> 858 0 -1.26506123 -0.06191171 12 sp_18 0.428912684 -0.90487124
-#> 859 0 -1.26506123 -0.06191171 2 sp_19 0.428912684 -0.90487124
-#> 860 0 -1.26506123 -0.06191171 18 sp_20 0.428912684 -0.90487124
-#> 861 0 -1.26506123 -0.06191171 12 sp_21 0.428912684 -0.90487124
-#> 862 0 -1.26506123 -0.06191171 15 sp_22 0.428912684 -0.90487124
-#> 863 0 -1.26506123 -0.06191171 19 sp_23 0.428912684 -0.90487124
-#> 864 1 -1.26506123 -0.06191171 6 sp_24 0.428912684 -0.90487124
-#> 865 0 -1.26506123 -0.06191171 16 sp_25 0.428912684 -0.90487124
-#> 866 0 -1.26506123 -0.06191171 15 sp_26 0.428912684 -0.90487124
-#> 867 0 -1.26506123 -0.06191171 19 sp_27 0.428912684 -0.90487124
-#> 868 0 -1.26506123 -0.06191171 3 sp_28 0.428912684 -0.90487124
-#> 869 0 -1.26506123 -0.06191171 14 sp_29 0.428912684 -0.90487124
-#> 870 0 -1.26506123 -0.06191171 1 sp_30 0.428912684 -0.90487124
-#> 961 1 -0.68685285 -0.30596266 1 sp_1 -0.482457898 -2.17554647
-#> 962 0 -0.68685285 -0.30596266 16 sp_2 -0.482457898 -2.17554647
-#> 963 0 -0.68685285 -0.30596266 11 sp_3 -0.482457898 -2.17554647
-#> 964 1 -0.68685285 -0.30596266 4 sp_4 -0.482457898 -2.17554647
-#> 965 1 -0.68685285 -0.30596266 12 sp_5 -0.482457898 -2.17554647
-#> 966 1 -0.68685285 -0.30596266 13 sp_6 -0.482457898 -2.17554647
-#> 967 0 -0.68685285 -0.30596266 10 sp_7 -0.482457898 -2.17554647
-#> 968 0 -0.68685285 -0.30596266 10 sp_8 -0.482457898 -2.17554647
-#> 969 0 -0.68685285 -0.30596266 7 sp_9 -0.482457898 -2.17554647
-#> 970 0 -0.68685285 -0.30596266 18 sp_10 -0.482457898 -2.17554647
-#> 971 0 -0.68685285 -0.30596266 17 sp_11 -0.482457898 -2.17554647
-#> 972 1 -0.68685285 -0.30596266 20 sp_12 -0.482457898 -2.17554647
-#> 973 1 -0.68685285 -0.30596266 9 sp_13 -0.482457898 -2.17554647
-#> 974 1 -0.68685285 -0.30596266 11 sp_14 -0.482457898 -2.17554647
-#> 975 1 -0.68685285 -0.30596266 12 sp_15 -0.482457898 -2.17554647
-#> 976 0 -0.68685285 -0.30596266 8 sp_16 -0.482457898 -2.17554647
-#> 977 0 -0.68685285 -0.30596266 18 sp_17 -0.482457898 -2.17554647
-#> 978 0 -0.68685285 -0.30596266 5 sp_18 -0.482457898 -2.17554647
-#> 979 0 -0.68685285 -0.30596266 18 sp_19 -0.482457898 -2.17554647
-#> 980 0 -0.68685285 -0.30596266 6 sp_20 -0.482457898 -2.17554647
-#> 981 0 -0.68685285 -0.30596266 10 sp_21 -0.482457898 -2.17554647
-#> 982 0 -0.68685285 -0.30596266 9 sp_22 -0.482457898 -2.17554647
-#> 983 1 -0.68685285 -0.30596266 11 sp_23 -0.482457898 -2.17554647
-#> 984 0 -0.68685285 -0.30596266 6 sp_24 -0.482457898 -2.17554647
-#> 985 0 -0.68685285 -0.30596266 12 sp_25 -0.482457898 -2.17554647
-#> 986 0 -0.68685285 -0.30596266 19 sp_26 -0.482457898 -2.17554647
-#> 987 0 -0.68685285 -0.30596266 4 sp_27 -0.482457898 -2.17554647
-#> 988 0 -0.68685285 -0.30596266 3 sp_28 -0.482457898 -2.17554647
-#> 989 0 -0.68685285 -0.30596266 14 sp_29 -0.482457898 -2.17554647
-#> 990 1 -0.68685285 -0.30596266 8 sp_30 -0.482457898 -2.17554647
-#> 1081 0 -0.44566197 -0.38047100 6 sp_1 -0.090646571 0.82760513
-#> 1082 0 -0.44566197 -0.38047100 4 sp_2 -0.090646571 0.82760513
-#> 1083 1 -0.44566197 -0.38047100 10 sp_3 -0.090646571 0.82760513
-#> 1084 0 -0.44566197 -0.38047100 16 sp_4 -0.090646571 0.82760513
-#> 1085 0 -0.44566197 -0.38047100 16 sp_5 -0.090646571 0.82760513
-#> 1086 0 -0.44566197 -0.38047100 20 sp_6 -0.090646571 0.82760513
-#> 1087 0 -0.44566197 -0.38047100 10 sp_7 -0.090646571 0.82760513
-#> 1088 0 -0.44566197 -0.38047100 6 sp_8 -0.090646571 0.82760513
-#> 1089 0 -0.44566197 -0.38047100 19 sp_9 -0.090646571 0.82760513
-#> 1090 0 -0.44566197 -0.38047100 4 sp_10 -0.090646571 0.82760513
-#> 1091 0 -0.44566197 -0.38047100 9 sp_11 -0.090646571 0.82760513
-#> 1092 0 -0.44566197 -0.38047100 4 sp_12 -0.090646571 0.82760513
-#> 1093 0 -0.44566197 -0.38047100 15 sp_13 -0.090646571 0.82760513
-#> 1094 0 -0.44566197 -0.38047100 20 sp_14 -0.090646571 0.82760513
-#> 1095 0 -0.44566197 -0.38047100 17 sp_15 -0.090646571 0.82760513
-#> 1096 0 -0.44566197 -0.38047100 7 sp_16 -0.090646571 0.82760513
-#> 1097 0 -0.44566197 -0.38047100 15 sp_17 -0.090646571 0.82760513
-#> 1098 0 -0.44566197 -0.38047100 5 sp_18 -0.090646571 0.82760513
-#> 1099 0 -0.44566197 -0.38047100 14 sp_19 -0.090646571 0.82760513
-#> 1100 0 -0.44566197 -0.38047100 15 sp_20 -0.090646571 0.82760513
-#> 1101 1 -0.44566197 -0.38047100 15 sp_21 -0.090646571 0.82760513
-#> 1102 0 -0.44566197 -0.38047100 16 sp_22 -0.090646571 0.82760513
-#> 1103 0 -0.44566197 -0.38047100 19 sp_23 -0.090646571 0.82760513
-#> 1104 0 -0.44566197 -0.38047100 8 sp_24 -0.090646571 0.82760513
-#> 1105 0 -0.44566197 -0.38047100 5 sp_25 -0.090646571 0.82760513
-#> 1106 0 -0.44566197 -0.38047100 7 sp_26 -0.090646571 0.82760513
-#> 1107 0 -0.44566197 -0.38047100 20 sp_27 -0.090646571 0.82760513
-#> 1108 0 -0.44566197 -0.38047100 16 sp_28 -0.090646571 0.82760513
-#> 1109 0 -0.44566197 -0.38047100 16 sp_29 -0.090646571 0.82760513
-#> 1110 0 -0.44566197 -0.38047100 9 sp_30 -0.090646571 0.82760513
-#> 1201 1 1.22408180 -0.69470698 11 sp_1 0.791847550 -1.27168186
-#> 1202 1 1.22408180 -0.69470698 11 sp_2 0.791847550 -1.27168186
-#> 1203 1 1.22408180 -0.69470698 19 sp_3 0.791847550 -1.27168186
-#> 1204 1 1.22408180 -0.69470698 10 sp_4 0.791847550 -1.27168186
-#> 1205 0 1.22408180 -0.69470698 2 sp_5 0.791847550 -1.27168186
-#> 1206 0 1.22408180 -0.69470698 6 sp_6 0.791847550 -1.27168186
-#> 1207 0 1.22408180 -0.69470698 20 sp_7 0.791847550 -1.27168186
-#> 1208 0 1.22408180 -0.69470698 14 sp_8 0.791847550 -1.27168186
-#> 1209 0 1.22408180 -0.69470698 14 sp_9 0.791847550 -1.27168186
-#> 1210 1 1.22408180 -0.69470698 6 sp_10 0.791847550 -1.27168186
-#> 1211 0 1.22408180 -0.69470698 18 sp_11 0.791847550 -1.27168186
-#> 1212 0 1.22408180 -0.69470698 2 sp_12 0.791847550 -1.27168186
-#> 1213 1 1.22408180 -0.69470698 8 sp_13 0.791847550 -1.27168186
-#> 1214 1 1.22408180 -0.69470698 11 sp_14 0.791847550 -1.27168186
-#> 1215 1 1.22408180 -0.69470698 7 sp_15 0.791847550 -1.27168186
-#> 1216 1 1.22408180 -0.69470698 19 sp_16 0.791847550 -1.27168186
-#> 1217 0 1.22408180 -0.69470698 8 sp_17 0.791847550 -1.27168186
-#> 1218 1 1.22408180 -0.69470698 10 sp_18 0.791847550 -1.27168186
-#> 1219 1 1.22408180 -0.69470698 5 sp_19 0.791847550 -1.27168186
-#> 1220 1 1.22408180 -0.69470698 17 sp_20 0.791847550 -1.27168186
-#> 1221 1 1.22408180 -0.69470698 6 sp_21 0.791847550 -1.27168186
-#> 1222 1 1.22408180 -0.69470698 8 sp_22 0.791847550 -1.27168186
-#> 1223 0 1.22408180 -0.69470698 20 sp_23 0.791847550 -1.27168186
-#> 1224 1 1.22408180 -0.69470698 6 sp_24 0.791847550 -1.27168186
-#> 1225 1 1.22408180 -0.69470698 15 sp_25 0.791847550 -1.27168186
-#> 1226 0 1.22408180 -0.69470698 17 sp_26 0.791847550 -1.27168186
-#> 1227 0 1.22408180 -0.69470698 3 sp_27 0.791847550 -1.27168186
-#> 1228 0 1.22408180 -0.69470698 15 sp_28 0.791847550 -1.27168186
-#> 1229 1 1.22408180 -0.69470698 20 sp_29 0.791847550 -1.27168186
-#> 1230 1 1.22408180 -0.69470698 1 sp_30 0.791847550 -1.27168186
-#> 1321 0 0.35981383 -0.20791728 5 sp_1 0.068754653 0.07194716
-#> 1322 0 0.35981383 -0.20791728 11 sp_2 0.068754653 0.07194716
-#> 1323 0 0.35981383 -0.20791728 15 sp_3 0.068754653 0.07194716
-#> 1324 0 0.35981383 -0.20791728 20 sp_4 0.068754653 0.07194716
-#> 1325 0 0.35981383 -0.20791728 2 sp_5 0.068754653 0.07194716
-#> 1326 0 0.35981383 -0.20791728 16 sp_6 0.068754653 0.07194716
-#> 1327 0 0.35981383 -0.20791728 19 sp_7 0.068754653 0.07194716
-#> 1328 0 0.35981383 -0.20791728 10 sp_8 0.068754653 0.07194716
-#> 1329 0 0.35981383 -0.20791728 19 sp_9 0.068754653 0.07194716
-#> 1330 1 0.35981383 -0.20791728 17 sp_10 0.068754653 0.07194716
-#> 1331 0 0.35981383 -0.20791728 7 sp_11 0.068754653 0.07194716
-#> 1332 0 0.35981383 -0.20791728 6 sp_12 0.068754653 0.07194716
-#> 1333 0 0.35981383 -0.20791728 12 sp_13 0.068754653 0.07194716
-#> 1334 0 0.35981383 -0.20791728 4 sp_14 0.068754653 0.07194716
-#> 1335 0 0.35981383 -0.20791728 19 sp_15 0.068754653 0.07194716
-#> 1336 1 0.35981383 -0.20791728 2 sp_16 0.068754653 0.07194716
-#> 1337 0 0.35981383 -0.20791728 4 sp_17 0.068754653 0.07194716
-#> 1338 0 0.35981383 -0.20791728 11 sp_18 0.068754653 0.07194716
-#> 1339 0 0.35981383 -0.20791728 1 sp_19 0.068754653 0.07194716
-#> 1340 0 0.35981383 -0.20791728 19 sp_20 0.068754653 0.07194716
-#> 1341 1 0.35981383 -0.20791728 18 sp_21 0.068754653 0.07194716
-#> 1342 0 0.35981383 -0.20791728 16 sp_22 0.068754653 0.07194716
-#> 1343 0 0.35981383 -0.20791728 3 sp_23 0.068754653 0.07194716
-#> 1344 0 0.35981383 -0.20791728 1 sp_24 0.068754653 0.07194716
-#> 1345 1 0.35981383 -0.20791728 2 sp_25 0.068754653 0.07194716
-#> 1346 0 0.35981383 -0.20791728 2 sp_26 0.068754653 0.07194716
-#> 1347 0 0.35981383 -0.20791728 8 sp_27 0.068754653 0.07194716
-#> 1348 0 0.35981383 -0.20791728 20 sp_28 0.068754653 0.07194716
-#> 1349 0 0.35981383 -0.20791728 14 sp_29 0.068754653 0.07194716
-#> 1350 0 0.35981383 -0.20791728 13 sp_30 0.068754653 0.07194716
-#> 1441 0 0.40077145 -1.26539635 7 sp_1 -0.613966444 -1.18393872
-#> 1442 0 0.40077145 -1.26539635 8 sp_2 -0.613966444 -1.18393872
-#> 1443 1 0.40077145 -1.26539635 3 sp_3 -0.613966444 -1.18393872
-#> 1444 0 0.40077145 -1.26539635 16 sp_4 -0.613966444 -1.18393872
-#> 1445 1 0.40077145 -1.26539635 1 sp_5 -0.613966444 -1.18393872
-#> 1446 1 0.40077145 -1.26539635 12 sp_6 -0.613966444 -1.18393872
-#> 1447 0 0.40077145 -1.26539635 18 sp_7 -0.613966444 -1.18393872
-#> 1448 0 0.40077145 -1.26539635 14 sp_8 -0.613966444 -1.18393872
-#> 1449 0 0.40077145 -1.26539635 8 sp_9 -0.613966444 -1.18393872
-#> 1450 1 0.40077145 -1.26539635 5 sp_10 -0.613966444 -1.18393872
-#> 1451 0 0.40077145 -1.26539635 17 sp_11 -0.613966444 -1.18393872
-#> 1452 1 0.40077145 -1.26539635 11 sp_12 -0.613966444 -1.18393872
-#> 1453 0 0.40077145 -1.26539635 4 sp_13 -0.613966444 -1.18393872
-#> 1454 1 0.40077145 -1.26539635 13 sp_14 -0.613966444 -1.18393872
-#> 1455 1 0.40077145 -1.26539635 8 sp_15 -0.613966444 -1.18393872
-#> 1456 1 0.40077145 -1.26539635 15 sp_16 -0.613966444 -1.18393872
-#> 1457 1 0.40077145 -1.26539635 4 sp_17 -0.613966444 -1.18393872
-#> 1458 0 0.40077145 -1.26539635 13 sp_18 -0.613966444 -1.18393872
-#> 1459 1 0.40077145 -1.26539635 3 sp_19 -0.613966444 -1.18393872
-#> 1460 0 0.40077145 -1.26539635 7 sp_20 -0.613966444 -1.18393872
-#> 1461 1 0.40077145 -1.26539635 1 sp_21 -0.613966444 -1.18393872
-#> 1462 0 0.40077145 -1.26539635 6 sp_22 -0.613966444 -1.18393872
-#> 1463 1 0.40077145 -1.26539635 13 sp_23 -0.613966444 -1.18393872
-#> 1464 1 0.40077145 -1.26539635 17 sp_24 -0.613966444 -1.18393872
-#> 1465 0 0.40077145 -1.26539635 6 sp_25 -0.613966444 -1.18393872
-#> 1466 1 0.40077145 -1.26539635 10 sp_26 -0.613966444 -1.18393872
-#> 1467 0 0.40077145 -1.26539635 13 sp_27 -0.613966444 -1.18393872
-#> 1468 0 0.40077145 -1.26539635 6 sp_28 -0.613966444 -1.18393872
-#> 1469 0 0.40077145 -1.26539635 9 sp_29 -0.613966444 -1.18393872
-#> 1470 0 0.40077145 -1.26539635 8 sp_30 -0.613966444 -1.18393872
-#> 1561 0 0.11068272 2.16895597 1 sp_1 -0.714181239 0.13138207
-#> 1562 1 0.11068272 2.16895597 16 sp_2 -0.714181239 0.13138207
-#> 1563 0 0.11068272 2.16895597 2 sp_3 -0.714181239 0.13138207
-#> 1564 0 0.11068272 2.16895597 8 sp_4 -0.714181239 0.13138207
-#> 1565 0 0.11068272 2.16895597 14 sp_5 -0.714181239 0.13138207
-#> 1566 0 0.11068272 2.16895597 12 sp_6 -0.714181239 0.13138207
-#> 1567 0 0.11068272 2.16895597 8 sp_7 -0.714181239 0.13138207
-#> 1568 0 0.11068272 2.16895597 9 sp_8 -0.714181239 0.13138207
-#> 1569 0 0.11068272 2.16895597 8 sp_9 -0.714181239 0.13138207
-#> 1570 0 0.11068272 2.16895597 9 sp_10 -0.714181239 0.13138207
-#> 1571 0 0.11068272 2.16895597 20 sp_11 -0.714181239 0.13138207
-#> 1572 0 0.11068272 2.16895597 1 sp_12 -0.714181239 0.13138207
-#> 1573 0 0.11068272 2.16895597 3 sp_13 -0.714181239 0.13138207
-#> 1574 0 0.11068272 2.16895597 8 sp_14 -0.714181239 0.13138207
-#> 1575 0 0.11068272 2.16895597 2 sp_15 -0.714181239 0.13138207
-#> 1576 0 0.11068272 2.16895597 1 sp_16 -0.714181239 0.13138207
-#> 1577 0 0.11068272 2.16895597 9 sp_17 -0.714181239 0.13138207
-#> 1578 0 0.11068272 2.16895597 7 sp_18 -0.714181239 0.13138207
-#> 1579 0 0.11068272 2.16895597 13 sp_19 -0.714181239 0.13138207
-#> 1580 0 0.11068272 2.16895597 20 sp_20 -0.714181239 0.13138207
-#> 1581 0 0.11068272 2.16895597 14 sp_21 -0.714181239 0.13138207
-#> 1582 0 0.11068272 2.16895597 16 sp_22 -0.714181239 0.13138207
-#> 1583 0 0.11068272 2.16895597 7 sp_23 -0.714181239 0.13138207
-#> 1584 0 0.11068272 2.16895597 4 sp_24 -0.714181239 0.13138207
-#> 1585 0 0.11068272 2.16895597 13 sp_25 -0.714181239 0.13138207
-#> 1586 0 0.11068272 2.16895597 12 sp_26 -0.714181239 0.13138207
-#> 1587 0 0.11068272 2.16895597 13 sp_27 -0.714181239 0.13138207
-#> 1588 0 0.11068272 2.16895597 20 sp_28 -0.714181239 0.13138207
-#> 1589 0 0.11068272 2.16895597 10 sp_29 -0.714181239 0.13138207
-#> 1590 0 0.11068272 2.16895597 9 sp_30 -0.714181239 0.13138207
-#> 1681 0 -0.55584113 1.20796200 12 sp_1 0.324249513 -0.14985243
-#> 1682 0 -0.55584113 1.20796200 8 sp_2 0.324249513 -0.14985243
-#> 1683 0 -0.55584113 1.20796200 7 sp_3 0.324249513 -0.14985243
-#> 1684 0 -0.55584113 1.20796200 15 sp_4 0.324249513 -0.14985243
-#> 1685 0 -0.55584113 1.20796200 19 sp_5 0.324249513 -0.14985243
-#> 1686 0 -0.55584113 1.20796200 17 sp_6 0.324249513 -0.14985243
-#> 1687 0 -0.55584113 1.20796200 11 sp_7 0.324249513 -0.14985243
-#> 1688 0 -0.55584113 1.20796200 7 sp_8 0.324249513 -0.14985243
-#> 1689 0 -0.55584113 1.20796200 19 sp_9 0.324249513 -0.14985243
-#> 1690 0 -0.55584113 1.20796200 3 sp_10 0.324249513 -0.14985243
-#> 1691 0 -0.55584113 1.20796200 6 sp_11 0.324249513 -0.14985243
-#> 1692 0 -0.55584113 1.20796200 7 sp_12 0.324249513 -0.14985243
-#> 1693 0 -0.55584113 1.20796200 4 sp_13 0.324249513 -0.14985243
-#> 1694 1 -0.55584113 1.20796200 10 sp_14 0.324249513 -0.14985243
-#> 1695 0 -0.55584113 1.20796200 17 sp_15 0.324249513 -0.14985243
-#> 1696 0 -0.55584113 1.20796200 16 sp_16 0.324249513 -0.14985243
-#> 1697 0 -0.55584113 1.20796200 8 sp_17 0.324249513 -0.14985243
-#> 1698 0 -0.55584113 1.20796200 3 sp_18 0.324249513 -0.14985243
-#> 1699 0 -0.55584113 1.20796200 12 sp_19 0.324249513 -0.14985243
-#> 1700 0 -0.55584113 1.20796200 14 sp_20 0.324249513 -0.14985243
-#> 1701 0 -0.55584113 1.20796200 5 sp_21 0.324249513 -0.14985243
-#> 1702 0 -0.55584113 1.20796200 14 sp_22 0.324249513 -0.14985243
-#> 1703 0 -0.55584113 1.20796200 6 sp_23 0.324249513 -0.14985243
-#> 1704 0 -0.55584113 1.20796200 9 sp_24 0.324249513 -0.14985243
-#> 1705 0 -0.55584113 1.20796200 1 sp_25 0.324249513 -0.14985243
-#> 1706 0 -0.55584113 1.20796200 20 sp_26 0.324249513 -0.14985243
-#> 1707 0 -0.55584113 1.20796200 14 sp_27 0.324249513 -0.14985243
-#> 1708 0 -0.55584113 1.20796200 19 sp_28 0.324249513 -0.14985243
-#> 1709 0 -0.55584113 1.20796200 5 sp_29 0.324249513 -0.14985243
-#> 1710 0 -0.55584113 1.20796200 2 sp_30 0.324249513 -0.14985243
-#> 1801 0 1.78691314 -1.12310858 1 sp_1 0.343282350 1.41604345
-#> 1802 0 1.78691314 -1.12310858 20 sp_2 0.343282350 1.41604345
-#> 1803 0 1.78691314 -1.12310858 4 sp_3 0.343282350 1.41604345
-#> 1804 0 1.78691314 -1.12310858 11 sp_4 0.343282350 1.41604345
-#> 1805 1 1.78691314 -1.12310858 5 sp_5 0.343282350 1.41604345
-#> 1806 0 1.78691314 -1.12310858 4 sp_6 0.343282350 1.41604345
-#> 1807 0 1.78691314 -1.12310858 19 sp_7 0.343282350 1.41604345
-#> 1808 0 1.78691314 -1.12310858 3 sp_8 0.343282350 1.41604345
-#> 1809 0 1.78691314 -1.12310858 1 sp_9 0.343282350 1.41604345
-#> 1810 0 1.78691314 -1.12310858 7 sp_10 0.343282350 1.41604345
-#> 1811 1 1.78691314 -1.12310858 5 sp_11 0.343282350 1.41604345
-#> 1812 0 1.78691314 -1.12310858 9 sp_12 0.343282350 1.41604345
-#> 1813 0 1.78691314 -1.12310858 17 sp_13 0.343282350 1.41604345
-#> 1814 1 1.78691314 -1.12310858 5 sp_14 0.343282350 1.41604345
-#> 1815 0 1.78691314 -1.12310858 12 sp_15 0.343282350 1.41604345
-#> 1816 0 1.78691314 -1.12310858 2 sp_16 0.343282350 1.41604345
-#> 1817 1 1.78691314 -1.12310858 18 sp_17 0.343282350 1.41604345
-#> 1818 0 1.78691314 -1.12310858 4 sp_18 0.343282350 1.41604345
-#> 1819 1 1.78691314 -1.12310858 10 sp_19 0.343282350 1.41604345
-#> 1820 0 1.78691314 -1.12310858 15 sp_20 0.343282350 1.41604345
-#> 1821 0 1.78691314 -1.12310858 8 sp_21 0.343282350 1.41604345
-#> 1822 0 1.78691314 -1.12310858 1 sp_22 0.343282350 1.41604345
-#> 1823 0 1.78691314 -1.12310858 11 sp_23 0.343282350 1.41604345
-#> 1824 0 1.78691314 -1.12310858 5 sp_24 0.343282350 1.41604345
-#> 1825 1 1.78691314 -1.12310858 11 sp_25 0.343282350 1.41604345
-#> 1826 1 1.78691314 -1.12310858 15 sp_26 0.343282350 1.41604345
-#> 1827 0 1.78691314 -1.12310858 15 sp_27 0.343282350 1.41604345
-#> 1828 1 1.78691314 -1.12310858 10 sp_28 0.343282350 1.41604345
-#> 1829 0 1.78691314 -1.12310858 15 sp_29 0.343282350 1.41604345
-#> 1830 0 1.78691314 -1.12310858 15 sp_30 0.343282350 1.41604345
-#> 1921 0 0.49785048 -0.40288484 20 sp_1 -0.439619408 -0.09657875
-#> 1922 0 0.49785048 -0.40288484 12 sp_2 -0.439619408 -0.09657875
-#> 1923 0 0.49785048 -0.40288484 9 sp_3 -0.439619408 -0.09657875
-#> 1924 0 0.49785048 -0.40288484 4 sp_4 -0.439619408 -0.09657875
-#> 1925 0 0.49785048 -0.40288484 3 sp_5 -0.439619408 -0.09657875
-#> 1926 0 0.49785048 -0.40288484 7 sp_6 -0.439619408 -0.09657875
-#> 1927 0 0.49785048 -0.40288484 4 sp_7 -0.439619408 -0.09657875
-#> 1928 0 0.49785048 -0.40288484 8 sp_8 -0.439619408 -0.09657875
-#> 1929 0 0.49785048 -0.40288484 5 sp_9 -0.439619408 -0.09657875
-#> 1930 0 0.49785048 -0.40288484 6 sp_10 -0.439619408 -0.09657875
-#> 1931 1 0.49785048 -0.40288484 4 sp_11 -0.439619408 -0.09657875
-#> 1932 1 0.49785048 -0.40288484 3 sp_12 -0.439619408 -0.09657875
-#> 1933 0 0.49785048 -0.40288484 11 sp_13 -0.439619408 -0.09657875
-#> 1934 0 0.49785048 -0.40288484 10 sp_14 -0.439619408 -0.09657875
-#> 1935 0 0.49785048 -0.40288484 5 sp_15 -0.439619408 -0.09657875
-#> 1936 0 0.49785048 -0.40288484 11 sp_16 -0.439619408 -0.09657875
-#> 1937 0 0.49785048 -0.40288484 10 sp_17 -0.439619408 -0.09657875
-#> 1938 1 0.49785048 -0.40288484 15 sp_18 -0.439619408 -0.09657875
-#> 1939 1 0.49785048 -0.40288484 19 sp_19 -0.439619408 -0.09657875
-#> 1940 0 0.49785048 -0.40288484 10 sp_20 -0.439619408 -0.09657875
-#> 1941 0 0.49785048 -0.40288484 13 sp_21 -0.439619408 -0.09657875
-#> 1942 0 0.49785048 -0.40288484 3 sp_22 -0.439619408 -0.09657875
-#> 1943 0 0.49785048 -0.40288484 18 sp_23 -0.439619408 -0.09657875
-#> 1944 0 0.49785048 -0.40288484 10 sp_24 -0.439619408 -0.09657875
-#> 1945 0 0.49785048 -0.40288484 8 sp_25 -0.439619408 -0.09657875
-#> 1946 1 0.49785048 -0.40288484 12 sp_26 -0.439619408 -0.09657875
-#> 1947 0 0.49785048 -0.40288484 10 sp_27 -0.439619408 -0.09657875
-#> 1948 0 0.49785048 -0.40288484 7 sp_28 -0.439619408 -0.09657875
-#> 1949 0 0.49785048 -0.40288484 7 sp_29 -0.439619408 -0.09657875
-#> 1950 0 0.49785048 -0.40288484 6 sp_30 -0.439619408 -0.09657875
-#> 2041 0 -1.96661716 -0.46665535 17 sp_1 0.345096720 -0.55778849
-#> 2042 0 -1.96661716 -0.46665535 20 sp_2 0.345096720 -0.55778849
-#> 2043 0 -1.96661716 -0.46665535 1 sp_3 0.345096720 -0.55778849
-#> 2044 0 -1.96661716 -0.46665535 5 sp_4 0.345096720 -0.55778849
-#> 2045 0 -1.96661716 -0.46665535 10 sp_5 0.345096720 -0.55778849
-#> 2046 0 -1.96661716 -0.46665535 13 sp_6 0.345096720 -0.55778849
-#> 2047 0 -1.96661716 -0.46665535 10 sp_7 0.345096720 -0.55778849
-#> 2048 0 -1.96661716 -0.46665535 2 sp_8 0.345096720 -0.55778849
-#> 2049 1 -1.96661716 -0.46665535 15 sp_9 0.345096720 -0.55778849
-#> 2050 0 -1.96661716 -0.46665535 15 sp_10 0.345096720 -0.55778849
-#> 2051 0 -1.96661716 -0.46665535 8 sp_11 0.345096720 -0.55778849
-#> 2052 0 -1.96661716 -0.46665535 3 sp_12 0.345096720 -0.55778849
-#> 2053 0 -1.96661716 -0.46665535 2 sp_13 0.345096720 -0.55778849
-#> 2054 0 -1.96661716 -0.46665535 6 sp_14 0.345096720 -0.55778849
-#> 2055 0 -1.96661716 -0.46665535 14 sp_15 0.345096720 -0.55778849
-#> 2056 0 -1.96661716 -0.46665535 15 sp_16 0.345096720 -0.55778849
-#> 2057 0 -1.96661716 -0.46665535 19 sp_17 0.345096720 -0.55778849
-#> 2058 0 -1.96661716 -0.46665535 9 sp_18 0.345096720 -0.55778849
-#> 2059 0 -1.96661716 -0.46665535 15 sp_19 0.345096720 -0.55778849
-#> 2060 0 -1.96661716 -0.46665535 16 sp_20 0.345096720 -0.55778849
-#> 2061 0 -1.96661716 -0.46665535 8 sp_21 0.345096720 -0.55778849
-#> 2062 0 -1.96661716 -0.46665535 9 sp_22 0.345096720 -0.55778849
-#> 2063 0 -1.96661716 -0.46665535 16 sp_23 0.345096720 -0.55778849
-#> 2064 0 -1.96661716 -0.46665535 9 sp_24 0.345096720 -0.55778849
-#> 2065 0 -1.96661716 -0.46665535 2 sp_25 0.345096720 -0.55778849
-#> 2066 0 -1.96661716 -0.46665535 9 sp_26 0.345096720 -0.55778849
-#> 2067 0 -1.96661716 -0.46665535 11 sp_27 0.345096720 -0.55778849
-#> 2068 0 -1.96661716 -0.46665535 11 sp_28 0.345096720 -0.55778849
-#> 2069 0 -1.96661716 -0.46665535 4 sp_29 0.345096720 -0.55778849
-#> 2070 0 -1.96661716 -0.46665535 7 sp_30 0.345096720 -0.55778849
-#> 2161 0 0.70135590 0.77996512 18 sp_1 -0.919759738 -0.31845834
-#> 2162 0 0.70135590 0.77996512 11 sp_2 -0.919759738 -0.31845834
-#> 2163 0 0.70135590 0.77996512 1 sp_3 -0.919759738 -0.31845834
-#> 2164 0 0.70135590 0.77996512 11 sp_4 -0.919759738 -0.31845834
-#> 2165 0 0.70135590 0.77996512 6 sp_5 -0.919759738 -0.31845834
-#> 2166 0 0.70135590 0.77996512 10 sp_6 -0.919759738 -0.31845834
-#> 2167 0 0.70135590 0.77996512 18 sp_7 -0.919759738 -0.31845834
-#> 2168 0 0.70135590 0.77996512 3 sp_8 -0.919759738 -0.31845834
-#> 2169 0 0.70135590 0.77996512 3 sp_9 -0.919759738 -0.31845834
-#> 2170 0 0.70135590 0.77996512 2 sp_10 -0.919759738 -0.31845834
-#> 2171 1 0.70135590 0.77996512 8 sp_11 -0.919759738 -0.31845834
-#> 2172 0 0.70135590 0.77996512 13 sp_12 -0.919759738 -0.31845834
-#> 2173 0 0.70135590 0.77996512 8 sp_13 -0.919759738 -0.31845834
-#> 2174 1 0.70135590 0.77996512 2 sp_14 -0.919759738 -0.31845834
-#> 2175 0 0.70135590 0.77996512 6 sp_15 -0.919759738 -0.31845834
-#> 2176 0 0.70135590 0.77996512 17 sp_16 -0.919759738 -0.31845834
-#> 2177 0 0.70135590 0.77996512 14 sp_17 -0.919759738 -0.31845834
-#> 2178 0 0.70135590 0.77996512 7 sp_18 -0.919759738 -0.31845834
-#> 2179 0 0.70135590 0.77996512 13 sp_19 -0.919759738 -0.31845834
-#> 2180 0 0.70135590 0.77996512 8 sp_20 -0.919759738 -0.31845834
-#> 2181 0 0.70135590 0.77996512 6 sp_21 -0.919759738 -0.31845834
-#> 2182 0 0.70135590 0.77996512 11 sp_22 -0.919759738 -0.31845834
-#> 2183 0 0.70135590 0.77996512 10 sp_23 -0.919759738 -0.31845834
-#> 2184 0 0.70135590 0.77996512 17 sp_24 -0.919759738 -0.31845834
-#> 2185 0 0.70135590 0.77996512 7 sp_25 -0.919759738 -0.31845834
-#> 2186 0 0.70135590 0.77996512 12 sp_26 -0.919759738 -0.31845834
-#> 2187 0 0.70135590 0.77996512 19 sp_27 -0.919759738 -0.31845834
-#> 2188 0 0.70135590 0.77996512 17 sp_28 -0.919759738 -0.31845834
-#> 2189 0 0.70135590 0.77996512 8 sp_29 -0.919759738 -0.31845834
-#> 2190 0 0.70135590 0.77996512 15 sp_30 -0.919759738 -0.31845834
-#> 2281 1 -0.47279141 -0.08336907 14 sp_1 1.783110817 -0.22054191
-#> 2282 0 -0.47279141 -0.08336907 14 sp_2 1.783110817 -0.22054191
-#> 2283 0 -0.47279141 -0.08336907 17 sp_3 1.783110817 -0.22054191
-#> 2284 1 -0.47279141 -0.08336907 1 sp_4 1.783110817 -0.22054191
-#> 2285 0 -0.47279141 -0.08336907 18 sp_5 1.783110817 -0.22054191
-#> 2286 0 -0.47279141 -0.08336907 18 sp_6 1.783110817 -0.22054191
-#> 2287 0 -0.47279141 -0.08336907 20 sp_7 1.783110817 -0.22054191
-#> 2288 0 -0.47279141 -0.08336907 10 sp_8 1.783110817 -0.22054191
-#> 2289 1 -0.47279141 -0.08336907 10 sp_9 1.783110817 -0.22054191
-#> 2290 0 -0.47279141 -0.08336907 9 sp_10 1.783110817 -0.22054191
-#> 2291 1 -0.47279141 -0.08336907 19 sp_11 1.783110817 -0.22054191
-#> 2292 0 -0.47279141 -0.08336907 18 sp_12 1.783110817 -0.22054191
-#> 2293 0 -0.47279141 -0.08336907 18 sp_13 1.783110817 -0.22054191
-#> 2294 1 -0.47279141 -0.08336907 12 sp_14 1.783110817 -0.22054191
-#> 2295 1 -0.47279141 -0.08336907 12 sp_15 1.783110817 -0.22054191
-#> 2296 0 -0.47279141 -0.08336907 4 sp_16 1.783110817 -0.22054191
-#> 2297 0 -0.47279141 -0.08336907 20 sp_17 1.783110817 -0.22054191
-#> 2298 1 -0.47279141 -0.08336907 10 sp_18 1.783110817 -0.22054191
-#> 2299 0 -0.47279141 -0.08336907 5 sp_19 1.783110817 -0.22054191
-#> 2300 1 -0.47279141 -0.08336907 2 sp_20 1.783110817 -0.22054191
-#> 2301 0 -0.47279141 -0.08336907 18 sp_21 1.783110817 -0.22054191
-#> 2302 1 -0.47279141 -0.08336907 12 sp_22 1.783110817 -0.22054191
-#> 2303 0 -0.47279141 -0.08336907 13 sp_23 1.783110817 -0.22054191
-#> 2304 0 -0.47279141 -0.08336907 11 sp_24 1.783110817 -0.22054191
-#> 2305 0 -0.47279141 -0.08336907 19 sp_25 1.783110817 -0.22054191
-#> 2306 0 -0.47279141 -0.08336907 6 sp_26 1.783110817 -0.22054191
-#> 2307 0 -0.47279141 -0.08336907 18 sp_27 1.783110817 -0.22054191
-#> 2308 0 -0.47279141 -0.08336907 10 sp_28 1.783110817 -0.22054191
-#> 2309 0 -0.47279141 -0.08336907 9 sp_29 1.783110817 -0.22054191
-#> 2310 0 -0.47279141 -0.08336907 3 sp_30 1.783110817 -0.22054191
-#> 2401 0 -1.06782371 0.25331851 19 sp_1 -1.421711896 -0.57964814
-#> 2402 0 -1.06782371 0.25331851 8 sp_2 -1.421711896 -0.57964814
-#> 2403 0 -1.06782371 0.25331851 13 sp_3 -1.421711896 -0.57964814
-#> 2404 0 -1.06782371 0.25331851 1 sp_4 -1.421711896 -0.57964814
-#> 2405 0 -1.06782371 0.25331851 2 sp_5 -1.421711896 -0.57964814
-#> 2406 0 -1.06782371 0.25331851 11 sp_6 -1.421711896 -0.57964814
-#> 2407 0 -1.06782371 0.25331851 16 sp_7 -1.421711896 -0.57964814
-#> 2408 0 -1.06782371 0.25331851 5 sp_8 -1.421711896 -0.57964814
-#> 2409 0 -1.06782371 0.25331851 4 sp_9 -1.421711896 -0.57964814
-#> 2410 0 -1.06782371 0.25331851 3 sp_10 -1.421711896 -0.57964814
-#> 2411 0 -1.06782371 0.25331851 15 sp_11 -1.421711896 -0.57964814
-#> 2412 0 -1.06782371 0.25331851 10 sp_12 -1.421711896 -0.57964814
-#> 2413 0 -1.06782371 0.25331851 7 sp_13 -1.421711896 -0.57964814
-#> 2414 0 -1.06782371 0.25331851 7 sp_14 -1.421711896 -0.57964814
-#> 2415 0 -1.06782371 0.25331851 2 sp_15 -1.421711896 -0.57964814
-#> 2416 0 -1.06782371 0.25331851 18 sp_16 -1.421711896 -0.57964814
-#> 2417 0 -1.06782371 0.25331851 18 sp_17 -1.421711896 -0.57964814
-#> 2418 0 -1.06782371 0.25331851 3 sp_18 -1.421711896 -0.57964814
-#> 2419 0 -1.06782371 0.25331851 8 sp_19 -1.421711896 -0.57964814
-#> 2420 0 -1.06782371 0.25331851 14 sp_20 -1.421711896 -0.57964814
-#> 2421 0 -1.06782371 0.25331851 9 sp_21 -1.421711896 -0.57964814
-#> 2422 0 -1.06782371 0.25331851 15 sp_22 -1.421711896 -0.57964814
-#> 2423 0 -1.06782371 0.25331851 17 sp_23 -1.421711896 -0.57964814
-#> 2424 0 -1.06782371 0.25331851 7 sp_24 -1.421711896 -0.57964814
-#> 2425 0 -1.06782371 0.25331851 8 sp_25 -1.421711896 -0.57964814
-#> 2426 0 -1.06782371 0.25331851 1 sp_26 -1.421711896 -0.57964814
-#> 2427 0 -1.06782371 0.25331851 9 sp_27 -1.421711896 -0.57964814
-#> 2428 0 -1.06782371 0.25331851 3 sp_28 -1.421711896 -0.57964814
-#> 2429 1 -1.06782371 0.25331851 2 sp_29 -1.421711896 -0.57964814
-#> 2430 0 -1.06782371 0.25331851 11 sp_30 -1.421711896 -0.57964814
-#> 2521 1 -0.21797491 -0.02854676 4 sp_1 1.642183362 0.18891799
-#> 2522 0 -0.21797491 -0.02854676 8 sp_2 1.642183362 0.18891799
-#> 2523 0 -0.21797491 -0.02854676 20 sp_3 1.642183362 0.18891799
-#> 2524 1 -0.21797491 -0.02854676 11 sp_4 1.642183362 0.18891799
-#> 2525 0 -0.21797491 -0.02854676 18 sp_5 1.642183362 0.18891799
-#> 2526 0 -0.21797491 -0.02854676 14 sp_6 1.642183362 0.18891799
-#> 2527 0 -0.21797491 -0.02854676 3 sp_7 1.642183362 0.18891799
-#> 2528 0 -0.21797491 -0.02854676 3 sp_8 1.642183362 0.18891799
-#> 2529 0 -0.21797491 -0.02854676 14 sp_9 1.642183362 0.18891799
-#> 2530 0 -0.21797491 -0.02854676 7 sp_10 1.642183362 0.18891799
-#> 2531 0 -0.21797491 -0.02854676 15 sp_11 1.642183362 0.18891799
-#> 2532 0 -0.21797491 -0.02854676 8 sp_12 1.642183362 0.18891799
-#> 2533 0 -0.21797491 -0.02854676 1 sp_13 1.642183362 0.18891799
-#> 2534 0 -0.21797491 -0.02854676 5 sp_14 1.642183362 0.18891799
-#> 2535 1 -0.21797491 -0.02854676 17 sp_15 1.642183362 0.18891799
-#> 2536 0 -0.21797491 -0.02854676 6 sp_16 1.642183362 0.18891799
-#> 2537 0 -0.21797491 -0.02854676 10 sp_17 1.642183362 0.18891799
-#> 2538 1 -0.21797491 -0.02854676 12 sp_18 1.642183362 0.18891799
-#> 2539 0 -0.21797491 -0.02854676 8 sp_19 1.642183362 0.18891799
-#> 2540 0 -0.21797491 -0.02854676 16 sp_20 1.642183362 0.18891799
-#> 2541 0 -0.21797491 -0.02854676 7 sp_21 1.642183362 0.18891799
-#> 2542 0 -0.21797491 -0.02854676 7 sp_22 1.642183362 0.18891799
-#> 2543 0 -0.21797491 -0.02854676 1 sp_23 1.642183362 0.18891799
-#> 2544 0 -0.21797491 -0.02854676 11 sp_24 1.642183362 0.18891799
-#> 2545 0 -0.21797491 -0.02854676 3 sp_25 1.642183362 0.18891799
-#> 2546 0 -0.21797491 -0.02854676 17 sp_26 1.642183362 0.18891799
-#> 2547 0 -0.21797491 -0.02854676 20 sp_27 1.642183362 0.18891799
-#> 2548 1 -0.21797491 -0.02854676 3 sp_28 1.642183362 0.18891799
-#> 2549 0 -0.21797491 -0.02854676 14 sp_29 1.642183362 0.18891799
-#> 2550 0 -0.21797491 -0.02854676 5 sp_30 1.642183362 0.18891799
-#> 2641 0 -1.02600445 -0.04287046 18 sp_1 0.124236888 -0.35126512
-#> 2642 0 -1.02600445 -0.04287046 8 sp_2 0.124236888 -0.35126512
-#> 2643 0 -1.02600445 -0.04287046 20 sp_3 0.124236888 -0.35126512
-#> 2644 0 -1.02600445 -0.04287046 10 sp_4 0.124236888 -0.35126512
-#> 2645 1 -1.02600445 -0.04287046 18 sp_5 0.124236888 -0.35126512
-#> 2646 0 -1.02600445 -0.04287046 17 sp_6 0.124236888 -0.35126512
-#> 2647 0 -1.02600445 -0.04287046 9 sp_7 0.124236888 -0.35126512
-#> 2648 0 -1.02600445 -0.04287046 3 sp_8 0.124236888 -0.35126512
-#> 2649 0 -1.02600445 -0.04287046 5 sp_9 0.124236888 -0.35126512
-#> 2650 0 -1.02600445 -0.04287046 16 sp_10 0.124236888 -0.35126512
-#> 2651 0 -1.02600445 -0.04287046 20 sp_11 0.124236888 -0.35126512
-#> 2652 0 -1.02600445 -0.04287046 3 sp_12 0.124236888 -0.35126512
-#> 2653 0 -1.02600445 -0.04287046 3 sp_13 0.124236888 -0.35126512
-#> 2654 0 -1.02600445 -0.04287046 13 sp_14 0.124236888 -0.35126512
-#> 2655 0 -1.02600445 -0.04287046 4 sp_15 0.124236888 -0.35126512
-#> 2656 0 -1.02600445 -0.04287046 15 sp_16 0.124236888 -0.35126512
-#> 2657 0 -1.02600445 -0.04287046 19 sp_17 0.124236888 -0.35126512
-#> 2658 0 -1.02600445 -0.04287046 13 sp_18 0.124236888 -0.35126512
-#> 2659 1 -1.02600445 -0.04287046 12 sp_19 0.124236888 -0.35126512
-#> 2660 0 -1.02600445 -0.04287046 20 sp_20 0.124236888 -0.35126512
-#> 2661 0 -1.02600445 -0.04287046 13 sp_21 0.124236888 -0.35126512
-#> 2662 0 -1.02600445 -0.04287046 13 sp_22 0.124236888 -0.35126512
-#> 2663 0 -1.02600445 -0.04287046 3 sp_23 0.124236888 -0.35126512
-#> 2664 0 -1.02600445 -0.04287046 20 sp_24 0.124236888 -0.35126512
-#> 2665 0 -1.02600445 -0.04287046 5 sp_25 0.124236888 -0.35126512
-#> 2666 0 -1.02600445 -0.04287046 13 sp_26 0.124236888 -0.35126512
-#> 2667 1 -1.02600445 -0.04287046 12 sp_27 0.124236888 -0.35126512
-#> 2668 0 -1.02600445 -0.04287046 8 sp_28 0.124236888 -0.35126512
-#> 2669 0 -1.02600445 -0.04287046 6 sp_29 0.124236888 -0.35126512
-#> 2670 0 -1.02600445 -0.04287046 16 sp_30 0.124236888 -0.35126512
-#> 2761 0 -0.72889123 1.36860228 11 sp_1 0.001123313 -0.24455126
-#> 2762 0 -0.72889123 1.36860228 12 sp_2 0.001123313 -0.24455126
-#> 2763 0 -0.72889123 1.36860228 16 sp_3 0.001123313 -0.24455126
-#> 2764 0 -0.72889123 1.36860228 15 sp_4 0.001123313 -0.24455126
-#> 2765 0 -0.72889123 1.36860228 1 sp_5 0.001123313 -0.24455126
-#> 2766 0 -0.72889123 1.36860228 12 sp_6 0.001123313 -0.24455126
-#> 2767 0 -0.72889123 1.36860228 10 sp_7 0.001123313 -0.24455126
-#> 2768 0 -0.72889123 1.36860228 10 sp_8 0.001123313 -0.24455126
-#> 2769 0 -0.72889123 1.36860228 4 sp_9 0.001123313 -0.24455126
-#> 2770 0 -0.72889123 1.36860228 9 sp_10 0.001123313 -0.24455126
-#> 2771 0 -0.72889123 1.36860228 20 sp_11 0.001123313 -0.24455126
-#> 2772 0 -0.72889123 1.36860228 5 sp_12 0.001123313 -0.24455126
-#> 2773 0 -0.72889123 1.36860228 9 sp_13 0.001123313 -0.24455126
-#> 2774 0 -0.72889123 1.36860228 19 sp_14 0.001123313 -0.24455126
-#> 2775 0 -0.72889123 1.36860228 3 sp_15 0.001123313 -0.24455126
-#> 2776 0 -0.72889123 1.36860228 2 sp_16 0.001123313 -0.24455126
-#> 2777 0 -0.72889123 1.36860228 12 sp_17 0.001123313 -0.24455126
-#> 2778 0 -0.72889123 1.36860228 15 sp_18 0.001123313 -0.24455126
-#> 2779 0 -0.72889123 1.36860228 17 sp_19 0.001123313 -0.24455126
-#> 2780 0 -0.72889123 1.36860228 3 sp_20 0.001123313 -0.24455126
-#> 2781 0 -0.72889123 1.36860228 7 sp_21 0.001123313 -0.24455126
-#> 2782 0 -0.72889123 1.36860228 13 sp_22 0.001123313 -0.24455126
-#> 2783 0 -0.72889123 1.36860228 14 sp_23 0.001123313 -0.24455126
-#> 2784 0 -0.72889123 1.36860228 2 sp_24 0.001123313 -0.24455126
-#> 2785 0 -0.72889123 1.36860228 9 sp_25 0.001123313 -0.24455126
-#> 2786 0 -0.72889123 1.36860228 15 sp_26 0.001123313 -0.24455126
-#> 2787 0 -0.72889123 1.36860228 1 sp_27 0.001123313 -0.24455126
-#> 2788 0 -0.72889123 1.36860228 10 sp_28 0.001123313 -0.24455126
-#> 2789 0 -0.72889123 1.36860228 9 sp_29 0.001123313 -0.24455126
-#> 2790 0 -0.72889123 1.36860228 9 sp_30 0.001123313 -0.24455126
-#> 2881 0 -0.62503927 -0.22577099 7 sp_1 -1.328975923 1.09479379
-#> 2882 0 -0.62503927 -0.22577099 18 sp_2 -1.328975923 1.09479379
-#> 2883 1 -0.62503927 -0.22577099 12 sp_3 -1.328975923 1.09479379
-#> 2884 0 -0.62503927 -0.22577099 6 sp_4 -1.328975923 1.09479379
-#> 2885 0 -0.62503927 -0.22577099 7 sp_5 -1.328975923 1.09479379
-#> 2886 0 -0.62503927 -0.22577099 16 sp_6 -1.328975923 1.09479379
-#> 2887 0 -0.62503927 -0.22577099 16 sp_7 -1.328975923 1.09479379
-#> 2888 0 -0.62503927 -0.22577099 2 sp_8 -1.328975923 1.09479379
-#> 2889 0 -0.62503927 -0.22577099 2 sp_9 -1.328975923 1.09479379
-#> 2890 0 -0.62503927 -0.22577099 14 sp_10 -1.328975923 1.09479379
-#> 2891 0 -0.62503927 -0.22577099 7 sp_11 -1.328975923 1.09479379
-#> 2892 0 -0.62503927 -0.22577099 6 sp_12 -1.328975923 1.09479379
-#> 2893 0 -0.62503927 -0.22577099 4 sp_13 -1.328975923 1.09479379
-#> 2894 0 -0.62503927 -0.22577099 3 sp_14 -1.328975923 1.09479379
-#> 2895 0 -0.62503927 -0.22577099 14 sp_15 -1.328975923 1.09479379
-#> 2896 0 -0.62503927 -0.22577099 19 sp_16 -1.328975923 1.09479379
-#> 2897 0 -0.62503927 -0.22577099 14 sp_17 -1.328975923 1.09479379
-#> 2898 0 -0.62503927 -0.22577099 16 sp_18 -1.328975923 1.09479379
-#> 2899 0 -0.62503927 -0.22577099 10 sp_19 -1.328975923 1.09479379
-#> 2900 0 -0.62503927 -0.22577099 12 sp_20 -1.328975923 1.09479379
-#> 2901 0 -0.62503927 -0.22577099 18 sp_21 -1.328975923 1.09479379
-#> 2902 0 -0.62503927 -0.22577099 3 sp_22 -1.328975923 1.09479379
-#> 2903 0 -0.62503927 -0.22577099 1 sp_23 -1.328975923 1.09479379
-#> 2904 0 -0.62503927 -0.22577099 12 sp_24 -1.328975923 1.09479379
-#> 2905 0 -0.62503927 -0.22577099 17 sp_25 -1.328975923 1.09479379
-#> 2906 0 -0.62503927 -0.22577099 1 sp_26 -1.328975923 1.09479379
-#> 2907 0 -0.62503927 -0.22577099 4 sp_27 -1.328975923 1.09479379
-#> 2908 0 -0.62503927 -0.22577099 19 sp_28 -1.328975923 1.09479379
-#> 2909 0 -0.62503927 -0.22577099 13 sp_29 -1.328975923 1.09479379
-#> 2910 0 -0.62503927 -0.22577099 18 sp_30 -1.328975923 1.09479379
-#> 3001 0 -1.68669331 1.51647060 15 sp_1 0.779726615 -1.51078277
-#> 3002 0 -1.68669331 1.51647060 13 sp_2 0.779726615 -1.51078277
-#> 3003 0 -1.68669331 1.51647060 14 sp_3 0.779726615 -1.51078277
-#> 3004 0 -1.68669331 1.51647060 18 sp_4 0.779726615 -1.51078277
-#> 3005 0 -1.68669331 1.51647060 12 sp_5 0.779726615 -1.51078277
-#> 3006 0 -1.68669331 1.51647060 18 sp_6 0.779726615 -1.51078277
-#> 3007 0 -1.68669331 1.51647060 7 sp_7 0.779726615 -1.51078277
-#> 3008 0 -1.68669331 1.51647060 4 sp_8 0.779726615 -1.51078277
-#> 3009 0 -1.68669331 1.51647060 4 sp_9 0.779726615 -1.51078277
-#> 3010 0 -1.68669331 1.51647060 3 sp_10 0.779726615 -1.51078277
-#> 3011 0 -1.68669331 1.51647060 11 sp_11 0.779726615 -1.51078277
-#> 3012 0 -1.68669331 1.51647060 19 sp_12 0.779726615 -1.51078277
-#> 3013 0 -1.68669331 1.51647060 16 sp_13 0.779726615 -1.51078277
-#> 3014 0 -1.68669331 1.51647060 15 sp_14 0.779726615 -1.51078277
-#> 3015 0 -1.68669331 1.51647060 11 sp_15 0.779726615 -1.51078277
-#> 3016 0 -1.68669331 1.51647060 6 sp_16 0.779726615 -1.51078277
-#> 3017 0 -1.68669331 1.51647060 5 sp_17 0.779726615 -1.51078277
-#> 3018 0 -1.68669331 1.51647060 2 sp_18 0.779726615 -1.51078277
-#> 3019 0 -1.68669331 1.51647060 17 sp_19 0.779726615 -1.51078277
-#> 3020 0 -1.68669331 1.51647060 5 sp_20 0.779726615 -1.51078277
-#> 3021 0 -1.68669331 1.51647060 19 sp_21 0.779726615 -1.51078277
-#> 3022 0 -1.68669331 1.51647060 15 sp_22 0.779726615 -1.51078277
-#> 3023 0 -1.68669331 1.51647060 19 sp_23 0.779726615 -1.51078277
-#> 3024 0 -1.68669331 1.51647060 3 sp_24 0.779726615 -1.51078277
-#> 3025 0 -1.68669331 1.51647060 15 sp_25 0.779726615 -1.51078277
-#> 3026 0 -1.68669331 1.51647060 3 sp_26 0.779726615 -1.51078277
-#> 3027 0 -1.68669331 1.51647060 2 sp_27 0.779726615 -1.51078277
-#> 3028 0 -1.68669331 1.51647060 5 sp_28 0.779726615 -1.51078277
-#> 3029 0 -1.68669331 1.51647060 5 sp_29 0.779726615 -1.51078277
-#> 3030 0 -1.68669331 1.51647060 7 sp_30 0.779726615 -1.51078277
-#> 3121 1 0.83778704 -1.54875280 2 sp_1 1.290447486 -0.49645077
-#> 3122 1 0.83778704 -1.54875280 16 sp_2 1.290447486 -0.49645077
-#> 3123 1 0.83778704 -1.54875280 8 sp_3 1.290447486 -0.49645077
-#> 3124 0 0.83778704 -1.54875280 18 sp_4 1.290447486 -0.49645077
-#> 3125 1 0.83778704 -1.54875280 19 sp_5 1.290447486 -0.49645077
-#> 3126 0 0.83778704 -1.54875280 9 sp_6 1.290447486 -0.49645077
-#> 3127 1 0.83778704 -1.54875280 19 sp_7 1.290447486 -0.49645077
-#> 3128 1 0.83778704 -1.54875280 14 sp_8 1.290447486 -0.49645077
-#> 3129 1 0.83778704 -1.54875280 19 sp_9 1.290447486 -0.49645077
-#> 3130 0 0.83778704 -1.54875280 5 sp_10 1.290447486 -0.49645077
-#> 3131 0 0.83778704 -1.54875280 13 sp_11 1.290447486 -0.49645077
-#> 3132 0 0.83778704 -1.54875280 16 sp_12 1.290447486 -0.49645077
-#> 3133 0 0.83778704 -1.54875280 7 sp_13 1.290447486 -0.49645077
-#> 3134 0 0.83778704 -1.54875280 8 sp_14 1.290447486 -0.49645077
-#> 3135 0 0.83778704 -1.54875280 16 sp_15 1.290447486 -0.49645077
-#> 3136 0 0.83778704 -1.54875280 15 sp_16 1.290447486 -0.49645077
-#> 3137 1 0.83778704 -1.54875280 20 sp_17 1.290447486 -0.49645077
-#> 3138 0 0.83778704 -1.54875280 3 sp_18 1.290447486 -0.49645077
-#> 3139 1 0.83778704 -1.54875280 17 sp_19 1.290447486 -0.49645077
-#> 3140 1 0.83778704 -1.54875280 7 sp_20 1.290447486 -0.49645077
-#> 3141 0 0.83778704 -1.54875280 13 sp_21 1.290447486 -0.49645077
-#> 3142 1 0.83778704 -1.54875280 3 sp_22 1.290447486 -0.49645077
-#> 3143 0 0.83778704 -1.54875280 13 sp_23 1.290447486 -0.49645077
-#> 3144 1 0.83778704 -1.54875280 14 sp_24 1.290447486 -0.49645077
-#> 3145 0 0.83778704 -1.54875280 4 sp_25 1.290447486 -0.49645077
-#> 3146 0 0.83778704 -1.54875280 16 sp_26 1.290447486 -0.49645077
-#> 3147 1 0.83778704 -1.54875280 9 sp_27 1.290447486 -0.49645077
-#> 3148 0 0.83778704 -1.54875280 16 sp_28 1.290447486 -0.49645077
-#> 3149 0 0.83778704 -1.54875280 9 sp_29 1.290447486 -0.49645077
-#> 3150 1 0.83778704 -1.54875280 5 sp_30 1.290447486 -0.49645077
-#> 3241 0 0.15337312 0.58461375 14 sp_1 -1.020567780 0.61989576
-#> 3242 0 0.15337312 0.58461375 12 sp_2 -1.020567780 0.61989576
-#> 3243 0 0.15337312 0.58461375 14 sp_3 -1.020567780 0.61989576
-#> 3244 0 0.15337312 0.58461375 13 sp_4 -1.020567780 0.61989576
-#> 3245 1 0.15337312 0.58461375 20 sp_5 -1.020567780 0.61989576
-#> 3246 0 0.15337312 0.58461375 15 sp_6 -1.020567780 0.61989576
-#> 3247 0 0.15337312 0.58461375 8 sp_7 -1.020567780 0.61989576
-#> 3248 0 0.15337312 0.58461375 13 sp_8 -1.020567780 0.61989576
-#> 3249 1 0.15337312 0.58461375 7 sp_9 -1.020567780 0.61989576
-#> 3250 0 0.15337312 0.58461375 5 sp_10 -1.020567780 0.61989576
-#> 3251 0 0.15337312 0.58461375 8 sp_11 -1.020567780 0.61989576
-#> 3252 0 0.15337312 0.58461375 15 sp_12 -1.020567780 0.61989576
-#> 3253 0 0.15337312 0.58461375 14 sp_13 -1.020567780 0.61989576
-#> 3254 1 0.15337312 0.58461375 16 sp_14 -1.020567780 0.61989576
-#> 3255 0 0.15337312 0.58461375 1 sp_15 -1.020567780 0.61989576
-#> 3256 0 0.15337312 0.58461375 14 sp_16 -1.020567780 0.61989576
-#> 3257 0 0.15337312 0.58461375 17 sp_17 -1.020567780 0.61989576
-#> 3258 0 0.15337312 0.58461375 7 sp_18 -1.020567780 0.61989576
-#> 3259 0 0.15337312 0.58461375 7 sp_19 -1.020567780 0.61989576
-#> 3260 0 0.15337312 0.58461375 13 sp_20 -1.020567780 0.61989576
-#> 3261 0 0.15337312 0.58461375 15 sp_21 -1.020567780 0.61989576
-#> 3262 1 0.15337312 0.58461375 12 sp_22 -1.020567780 0.61989576
-#> 3263 0 0.15337312 0.58461375 14 sp_23 -1.020567780 0.61989576
-#> 3264 0 0.15337312 0.58461375 19 sp_24 -1.020567780 0.61989576
-#> 3265 0 0.15337312 0.58461375 19 sp_25 -1.020567780 0.61989576
-#> 3266 0 0.15337312 0.58461375 17 sp_26 -1.020567780 0.61989576
-#> 3267 0 0.15337312 0.58461375 9 sp_27 -1.020567780 0.61989576
-#> 3268 0 0.15337312 0.58461375 13 sp_28 -1.020567780 0.61989576
-#> 3269 0 0.15337312 0.58461375 14 sp_29 -1.020567780 0.61989576
-#> 3270 0 0.15337312 0.58461375 6 sp_30 -1.020567780 0.61989576
-#> 3361 0 -1.13813694 0.12385424 1 sp_1 0.704704540 2.00602552
-#> 3362 0 -1.13813694 0.12385424 16 sp_2 0.704704540 2.00602552
-#> 3363 0 -1.13813694 0.12385424 8 sp_3 0.704704540 2.00602552
-#> 3364 0 -1.13813694 0.12385424 5 sp_4 0.704704540 2.00602552
-#> 3365 0 -1.13813694 0.12385424 10 sp_5 0.704704540 2.00602552
-#> 3366 0 -1.13813694 0.12385424 9 sp_6 0.704704540 2.00602552
-#> 3367 0 -1.13813694 0.12385424 5 sp_7 0.704704540 2.00602552
-#> 3368 0 -1.13813694 0.12385424 14 sp_8 0.704704540 2.00602552
-#> 3369 0 -1.13813694 0.12385424 19 sp_9 0.704704540 2.00602552
-#> 3370 0 -1.13813694 0.12385424 1 sp_10 0.704704540 2.00602552
-#> 3371 0 -1.13813694 0.12385424 16 sp_11 0.704704540 2.00602552
-#> 3372 0 -1.13813694 0.12385424 6 sp_12 0.704704540 2.00602552
-#> 3373 0 -1.13813694 0.12385424 20 sp_13 0.704704540 2.00602552
-#> 3374 0 -1.13813694 0.12385424 8 sp_14 0.704704540 2.00602552
-#> 3375 0 -1.13813694 0.12385424 14 sp_15 0.704704540 2.00602552
-#> 3376 0 -1.13813694 0.12385424 14 sp_16 0.704704540 2.00602552
-#> 3377 0 -1.13813694 0.12385424 8 sp_17 0.704704540 2.00602552
-#> 3378 0 -1.13813694 0.12385424 11 sp_18 0.704704540 2.00602552
-#> 3379 0 -1.13813694 0.12385424 20 sp_19 0.704704540 2.00602552
-#> 3380 0 -1.13813694 0.12385424 5 sp_20 0.704704540 2.00602552
-#> 3381 0 -1.13813694 0.12385424 14 sp_21 0.704704540 2.00602552
-#> 3382 0 -1.13813694 0.12385424 1 sp_22 0.704704540 2.00602552
-#> 3383 0 -1.13813694 0.12385424 1 sp_23 0.704704540 2.00602552
-#> 3384 0 -1.13813694 0.12385424 5 sp_24 0.704704540 2.00602552
-#> 3385 0 -1.13813694 0.12385424 3 sp_25 0.704704540 2.00602552
-#> 3386 0 -1.13813694 0.12385424 4 sp_26 0.704704540 2.00602552
-#> 3387 0 -1.13813694 0.12385424 3 sp_27 0.704704540 2.00602552
-#> 3388 0 -1.13813694 0.12385424 14 sp_28 0.704704540 2.00602552
-#> 3389 0 -1.13813694 0.12385424 18 sp_29 0.704704540 2.00602552
-#> 3390 0 -1.13813694 0.12385424 10 sp_30 0.704704540 2.00602552
-#> 3481 1 1.25381492 0.21594157 12 sp_1 1.328751933 0.21194168
-#> 3482 1 1.25381492 0.21594157 16 sp_2 1.328751933 0.21194168
-#> 3483 0 1.25381492 0.21594157 3 sp_3 1.328751933 0.21194168
-#> 3484 0 1.25381492 0.21594157 12 sp_4 1.328751933 0.21194168
-#> 3485 0 1.25381492 0.21594157 5 sp_5 1.328751933 0.21194168
-#> 3486 0 1.25381492 0.21594157 13 sp_6 1.328751933 0.21194168
-#> 3487 0 1.25381492 0.21594157 8 sp_7 1.328751933 0.21194168
-#> 3488 1 1.25381492 0.21594157 17 sp_8 1.328751933 0.21194168
-#> 3489 0 1.25381492 0.21594157 5 sp_9 1.328751933 0.21194168
-#> 3490 0 1.25381492 0.21594157 19 sp_10 1.328751933 0.21194168
-#> 3491 0 1.25381492 0.21594157 6 sp_11 1.328751933 0.21194168
-#> 3492 1 1.25381492 0.21594157 2 sp_12 1.328751933 0.21194168
-#> 3493 1 1.25381492 0.21594157 17 sp_13 1.328751933 0.21194168
-#> 3494 1 1.25381492 0.21594157 17 sp_14 1.328751933 0.21194168
-#> 3495 0 1.25381492 0.21594157 8 sp_15 1.328751933 0.21194168
-#> 3496 0 1.25381492 0.21594157 19 sp_16 1.328751933 0.21194168
-#> 3497 1 1.25381492 0.21594157 18 sp_17 1.328751933 0.21194168
-#> 3498 0 1.25381492 0.21594157 19 sp_18 1.328751933 0.21194168
-#> 3499 1 1.25381492 0.21594157 5 sp_19 1.328751933 0.21194168
-#> 3500 0 1.25381492 0.21594157 14 sp_20 1.328751933 0.21194168
-#> 3501 1 1.25381492 0.21594157 12 sp_21 1.328751933 0.21194168
-#> 3502 0 1.25381492 0.21594157 1 sp_22 1.328751933 0.21194168
-#> 3503 1 1.25381492 0.21594157 16 sp_23 1.328751933 0.21194168
-#> 3504 0 1.25381492 0.21594157 18 sp_24 1.328751933 0.21194168
-#> 3505 1 1.25381492 0.21594157 20 sp_25 1.328751933 0.21194168
-#> 3506 0 1.25381492 0.21594157 7 sp_26 1.328751933 0.21194168
-#> 3507 1 1.25381492 0.21594157 5 sp_27 1.328751933 0.21194168
-#> 3508 0 1.25381492 0.21594157 10 sp_28 1.328751933 0.21194168
-#> 3509 0 1.25381492 0.21594157 4 sp_29 1.328751933 0.21194168
-#> 3510 0 1.25381492 0.21594157 8 sp_30 1.328751933 0.21194168
-#> 110 1 -0.56047565 0.42646422 7 sp_1 1.716649095 -2.35167507
-#> 210 0 -0.56047565 0.42646422 3 sp_2 1.716649095 -2.35167507
-#> 31 0 -0.56047565 0.42646422 15 sp_3 1.716649095 -2.35167507
-#> 41 0 -0.56047565 0.42646422 5 sp_4 1.716649095 -2.35167507
-#> 51 1 -0.56047565 0.42646422 8 sp_5 1.716649095 -2.35167507
-#> 61 0 -0.56047565 0.42646422 19 sp_6 1.716649095 -2.35167507
-#> 71 0 -0.56047565 0.42646422 10 sp_7 1.716649095 -2.35167507
-#> 81 0 -0.56047565 0.42646422 18 sp_8 1.716649095 -2.35167507
-#> 91 0 -0.56047565 0.42646422 10 sp_9 1.716649095 -2.35167507
-#> 101 0 -0.56047565 0.42646422 12 sp_10 1.716649095 -2.35167507
-#> 111 1 -0.56047565 0.42646422 2 sp_11 1.716649095 -2.35167507
-#> 1231 0 -0.56047565 0.42646422 10 sp_12 1.716649095 -2.35167507
-#> 1310 1 -0.56047565 0.42646422 12 sp_13 1.716649095 -2.35167507
-#> 1410 0 -0.56047565 0.42646422 20 sp_14 1.716649095 -2.35167507
-#> 151 0 -0.56047565 0.42646422 14 sp_15 1.716649095 -2.35167507
-#> 161 0 -0.56047565 0.42646422 17 sp_16 1.716649095 -2.35167507
-#> 171 1 -0.56047565 0.42646422 14 sp_17 1.716649095 -2.35167507
-#> 181 0 -0.56047565 0.42646422 3 sp_18 1.716649095 -2.35167507
-#> 191 0 -0.56047565 0.42646422 8 sp_19 1.716649095 -2.35167507
-#> 201 1 -0.56047565 0.42646422 14 sp_20 1.716649095 -2.35167507
-#> 211 0 -0.56047565 0.42646422 19 sp_21 1.716649095 -2.35167507
-#> 221 0 -0.56047565 0.42646422 15 sp_22 1.716649095 -2.35167507
-#> 231 0 -0.56047565 0.42646422 17 sp_23 1.716649095 -2.35167507
-#> 2431 1 -0.56047565 0.42646422 11 sp_24 1.716649095 -2.35167507
-#> 2510 0 -0.56047565 0.42646422 7 sp_25 1.716649095 -2.35167507
-#> 2610 0 -0.56047565 0.42646422 15 sp_26 1.716649095 -2.35167507
-#> 271 1 -0.56047565 0.42646422 6 sp_27 1.716649095 -2.35167507
-#> 281 0 -0.56047565 0.42646422 14 sp_28 1.716649095 -2.35167507
-#> 291 0 -0.56047565 0.42646422 7 sp_29 1.716649095 -2.35167507
-#> 301 0 -0.56047565 0.42646422 10 sp_30 1.716649095 -2.35167507
-#> 12110 0 -0.23017749 -0.29507148 5 sp_1 -0.859586190 1.32733753
-#> 12210 0 -0.23017749 -0.29507148 6 sp_2 -0.859586190 1.32733753
-#> 1232 0 -0.23017749 -0.29507148 16 sp_3 -0.859586190 1.32733753
-#> 1241 0 -0.23017749 -0.29507148 11 sp_4 -0.859586190 1.32733753
-#> 1251 0 -0.23017749 -0.29507148 4 sp_5 -0.859586190 1.32733753
-#> 1261 0 -0.23017749 -0.29507148 12 sp_6 -0.859586190 1.32733753
-#> 1271 0 -0.23017749 -0.29507148 14 sp_7 -0.859586190 1.32733753
-#> 1281 0 -0.23017749 -0.29507148 19 sp_8 -0.859586190 1.32733753
-#> 1291 0 -0.23017749 -0.29507148 7 sp_9 -0.859586190 1.32733753
-#> 1301 0 -0.23017749 -0.29507148 9 sp_10 -0.859586190 1.32733753
-#> 1311 0 -0.23017749 -0.29507148 7 sp_11 -0.859586190 1.32733753
-#> 13210 0 -0.23017749 -0.29507148 2 sp_12 -0.859586190 1.32733753
-#> 13310 0 -0.23017749 -0.29507148 16 sp_13 -0.859586190 1.32733753
-#> 13410 0 -0.23017749 -0.29507148 13 sp_14 -0.859586190 1.32733753
-#> 1351 0 -0.23017749 -0.29507148 19 sp_15 -0.859586190 1.32733753
-#> 1361 0 -0.23017749 -0.29507148 20 sp_16 -0.859586190 1.32733753
-#> 1371 0 -0.23017749 -0.29507148 15 sp_17 -0.859586190 1.32733753
-#> 1381 0 -0.23017749 -0.29507148 7 sp_18 -0.859586190 1.32733753
-#> 1391 0 -0.23017749 -0.29507148 4 sp_19 -0.859586190 1.32733753
-#> 1401 0 -0.23017749 -0.29507148 1 sp_20 -0.859586190 1.32733753
-#> 1411 0 -0.23017749 -0.29507148 8 sp_21 -0.859586190 1.32733753
-#> 1421 0 -0.23017749 -0.29507148 20 sp_22 -0.859586190 1.32733753
-#> 1431 0 -0.23017749 -0.29507148 16 sp_23 -0.859586190 1.32733753
-#> 14410 0 -0.23017749 -0.29507148 11 sp_24 -0.859586190 1.32733753
-#> 14510 0 -0.23017749 -0.29507148 16 sp_25 -0.859586190 1.32733753
-#> 14610 0 -0.23017749 -0.29507148 20 sp_26 -0.859586190 1.32733753
-#> 1471 0 -0.23017749 -0.29507148 8 sp_27 -0.859586190 1.32733753
-#> 1481 0 -0.23017749 -0.29507148 3 sp_28 -0.859586190 1.32733753
-#> 1491 0 -0.23017749 -0.29507148 4 sp_29 -0.859586190 1.32733753
-#> 1501 0 -0.23017749 -0.29507148 20 sp_30 -0.859586190 1.32733753
-#> 24110 0 1.55870831 0.89512566 12 sp_1 -1.013550294 -0.08577912
-#> 24210 1 1.55870831 0.89512566 17 sp_2 -1.013550294 -0.08577912
-#> 2432 0 1.55870831 0.89512566 10 sp_3 -1.013550294 -0.08577912
-#> 2441 1 1.55870831 0.89512566 20 sp_4 -1.013550294 -0.08577912
-#> 2451 0 1.55870831 0.89512566 11 sp_5 -1.013550294 -0.08577912
-#> 2461 0 1.55870831 0.89512566 8 sp_6 -1.013550294 -0.08577912
-#> 2471 0 1.55870831 0.89512566 14 sp_7 -1.013550294 -0.08577912
-#> 2481 0 1.55870831 0.89512566 13 sp_8 -1.013550294 -0.08577912
-#> 2491 0 1.55870831 0.89512566 2 sp_9 -1.013550294 -0.08577912
-#> 2501 1 1.55870831 0.89512566 11 sp_10 -1.013550294 -0.08577912
-#> 2511 0 1.55870831 0.89512566 13 sp_11 -1.013550294 -0.08577912
-#> 25210 0 1.55870831 0.89512566 14 sp_12 -1.013550294 -0.08577912
-#> 25310 0 1.55870831 0.89512566 6 sp_13 -1.013550294 -0.08577912
-#> 25410 0 1.55870831 0.89512566 8 sp_14 -1.013550294 -0.08577912
-#> 2551 0 1.55870831 0.89512566 12 sp_15 -1.013550294 -0.08577912
-#> 2561 1 1.55870831 0.89512566 4 sp_16 -1.013550294 -0.08577912
-#> 2571 0 1.55870831 0.89512566 13 sp_17 -1.013550294 -0.08577912
-#> 2581 0 1.55870831 0.89512566 14 sp_18 -1.013550294 -0.08577912
-#> 2591 0 1.55870831 0.89512566 16 sp_19 -1.013550294 -0.08577912
-#> 2601 0 1.55870831 0.89512566 1 sp_20 -1.013550294 -0.08577912
-#> 2611 0 1.55870831 0.89512566 8 sp_21 -1.013550294 -0.08577912
-#> 2621 0 1.55870831 0.89512566 8 sp_22 -1.013550294 -0.08577912
-#> 2631 0 1.55870831 0.89512566 10 sp_23 -1.013550294 -0.08577912
-#> 26410 0 1.55870831 0.89512566 8 sp_24 -1.013550294 -0.08577912
-#> 26510 0 1.55870831 0.89512566 18 sp_25 -1.013550294 -0.08577912
-#> 26610 0 1.55870831 0.89512566 9 sp_26 -1.013550294 -0.08577912
-#> 2671 0 1.55870831 0.89512566 7 sp_27 -1.013550294 -0.08577912
-#> 2681 0 1.55870831 0.89512566 7 sp_28 -1.013550294 -0.08577912
-#> 2691 1 1.55870831 0.89512566 10 sp_29 -1.013550294 -0.08577912
-#> 2701 0 1.55870831 0.89512566 11 sp_30 -1.013550294 -0.08577912
-#> 3611 0 0.07050839 0.87813349 1 sp_1 -0.220246237 -0.08670636
-#> 3621 0 0.07050839 0.87813349 19 sp_2 -0.220246237 -0.08670636
-#> 3631 0 0.07050839 0.87813349 10 sp_3 -0.220246237 -0.08670636
-#> 3641 0 0.07050839 0.87813349 13 sp_4 -0.220246237 -0.08670636
-#> 3651 1 0.07050839 0.87813349 11 sp_5 -0.220246237 -0.08670636
-#> 3661 0 0.07050839 0.87813349 11 sp_6 -0.220246237 -0.08670636
-#> 3671 0 0.07050839 0.87813349 20 sp_7 -0.220246237 -0.08670636
-#> 3681 0 0.07050839 0.87813349 7 sp_8 -0.220246237 -0.08670636
-#> 3691 0 0.07050839 0.87813349 20 sp_9 -0.220246237 -0.08670636
-#> 3701 0 0.07050839 0.87813349 9 sp_10 -0.220246237 -0.08670636
-#> 3711 0 0.07050839 0.87813349 9 sp_11 -0.220246237 -0.08670636
-#> 3721 0 0.07050839 0.87813349 5 sp_12 -0.220246237 -0.08670636
-#> 3731 0 0.07050839 0.87813349 14 sp_13 -0.220246237 -0.08670636
-#> 3741 0 0.07050839 0.87813349 14 sp_14 -0.220246237 -0.08670636
-#> 3751 0 0.07050839 0.87813349 6 sp_15 -0.220246237 -0.08670636
-#> 3761 0 0.07050839 0.87813349 1 sp_16 -0.220246237 -0.08670636
-#> 3771 1 0.07050839 0.87813349 10 sp_17 -0.220246237 -0.08670636
-#> 3781 0 0.07050839 0.87813349 17 sp_18 -0.220246237 -0.08670636
-#> 3791 1 0.07050839 0.87813349 17 sp_19 -0.220246237 -0.08670636
-#> 3801 0 0.07050839 0.87813349 7 sp_20 -0.220246237 -0.08670636
-#> 3811 0 0.07050839 0.87813349 9 sp_21 -0.220246237 -0.08670636
-#> 3821 0 0.07050839 0.87813349 20 sp_22 -0.220246237 -0.08670636
-#> 3831 0 0.07050839 0.87813349 6 sp_23 -0.220246237 -0.08670636
-#> 3841 0 0.07050839 0.87813349 18 sp_24 -0.220246237 -0.08670636
-#> 3851 0 0.07050839 0.87813349 17 sp_25 -0.220246237 -0.08670636
-#> 3861 0 0.07050839 0.87813349 5 sp_26 -0.220246237 -0.08670636
-#> 3871 0 0.07050839 0.87813349 20 sp_27 -0.220246237 -0.08670636
-#> 3881 0 0.07050839 0.87813349 3 sp_28 -0.220246237 -0.08670636
-#> 3891 0 0.07050839 0.87813349 14 sp_29 -0.220246237 -0.08670636
-#> 3901 0 0.07050839 0.87813349 1 sp_30 -0.220246237 -0.08670636
-#> 4811 0 0.12928774 0.82158108 2 sp_1 0.158823107 -0.25053832
-#> 4821 0 0.12928774 0.82158108 4 sp_2 0.158823107 -0.25053832
-#> 4831 0 0.12928774 0.82158108 10 sp_3 0.158823107 -0.25053832
-#> 4841 0 0.12928774 0.82158108 1 sp_4 0.158823107 -0.25053832
-#> 4851 0 0.12928774 0.82158108 5 sp_5 0.158823107 -0.25053832
-#> 4861 0 0.12928774 0.82158108 8 sp_6 0.158823107 -0.25053832
-#> 4871 0 0.12928774 0.82158108 13 sp_7 0.158823107 -0.25053832
-#> 4881 0 0.12928774 0.82158108 18 sp_8 0.158823107 -0.25053832
-#> 4891 1 0.12928774 0.82158108 10 sp_9 0.158823107 -0.25053832
-#> 4901 0 0.12928774 0.82158108 6 sp_10 0.158823107 -0.25053832
-#> 4911 0 0.12928774 0.82158108 7 sp_11 0.158823107 -0.25053832
-#> 4921 0 0.12928774 0.82158108 9 sp_12 0.158823107 -0.25053832
-#> 4931 0 0.12928774 0.82158108 16 sp_13 0.158823107 -0.25053832
-#> 4941 1 0.12928774 0.82158108 17 sp_14 0.158823107 -0.25053832
-#> 4951 0 0.12928774 0.82158108 13 sp_15 0.158823107 -0.25053832
-#> 4961 0 0.12928774 0.82158108 8 sp_16 0.158823107 -0.25053832
-#> 4971 0 0.12928774 0.82158108 7 sp_17 0.158823107 -0.25053832
-#> 4981 0 0.12928774 0.82158108 20 sp_18 0.158823107 -0.25053832
-#> 4991 0 0.12928774 0.82158108 18 sp_19 0.158823107 -0.25053832
-#> 5001 0 0.12928774 0.82158108 17 sp_20 0.158823107 -0.25053832
-#> 5011 0 0.12928774 0.82158108 1 sp_21 0.158823107 -0.25053832
-#> 5021 0 0.12928774 0.82158108 2 sp_22 0.158823107 -0.25053832
-#> 5031 0 0.12928774 0.82158108 17 sp_23 0.158823107 -0.25053832
-#> 5041 0 0.12928774 0.82158108 2 sp_24 0.158823107 -0.25053832
-#> 5051 0 0.12928774 0.82158108 13 sp_25 0.158823107 -0.25053832
-#> 5061 0 0.12928774 0.82158108 17 sp_26 0.158823107 -0.25053832
-#> 5071 0 0.12928774 0.82158108 3 sp_27 0.158823107 -0.25053832
-#> 5081 0 0.12928774 0.82158108 18 sp_28 0.158823107 -0.25053832
-#> 5091 1 0.12928774 0.82158108 2 sp_29 0.158823107 -0.25053832
-#> 5101 0 0.12928774 0.82158108 5 sp_30 0.158823107 -0.25053832
-#> 6011 0 1.71506499 0.68864025 12 sp_1 -0.869274055 0.39534471
-#> 6021 0 1.71506499 0.68864025 13 sp_2 -0.869274055 0.39534471
-#> 6031 0 1.71506499 0.68864025 10 sp_3 -0.869274055 0.39534471
-#> 6041 0 1.71506499 0.68864025 6 sp_4 -0.869274055 0.39534471
-#> 6051 0 1.71506499 0.68864025 10 sp_5 -0.869274055 0.39534471
-#> 6061 0 1.71506499 0.68864025 10 sp_6 -0.869274055 0.39534471
-#> 6071 0 1.71506499 0.68864025 6 sp_7 -0.869274055 0.39534471
-#> 6081 1 1.71506499 0.68864025 16 sp_8 -0.869274055 0.39534471
-#> 6091 0 1.71506499 0.68864025 16 sp_9 -0.869274055 0.39534471
-#> 6101 1 1.71506499 0.68864025 3 sp_10 -0.869274055 0.39534471
-#> 6111 0 1.71506499 0.68864025 4 sp_11 -0.869274055 0.39534471
-#> 6121 0 1.71506499 0.68864025 3 sp_12 -0.869274055 0.39534471
-#> 6131 0 1.71506499 0.68864025 3 sp_13 -0.869274055 0.39534471
-#> 6141 0 1.71506499 0.68864025 16 sp_14 -0.869274055 0.39534471
-#> 6151 1 1.71506499 0.68864025 2 sp_15 -0.869274055 0.39534471
-#> 6161 0 1.71506499 0.68864025 15 sp_16 -0.869274055 0.39534471
-#> 6171 0 1.71506499 0.68864025 3 sp_17 -0.869274055 0.39534471
-#> 6181 0 1.71506499 0.68864025 9 sp_18 -0.869274055 0.39534471
-#> 6191 0 1.71506499 0.68864025 7 sp_19 -0.869274055 0.39534471
-#> 6201 0 1.71506499 0.68864025 9 sp_20 -0.869274055 0.39534471
-#> 6211 0 1.71506499 0.68864025 4 sp_21 -0.869274055 0.39534471
-#> 6221 0 1.71506499 0.68864025 2 sp_22 -0.869274055 0.39534471
-#> 6231 0 1.71506499 0.68864025 12 sp_23 -0.869274055 0.39534471
-#> 6241 0 1.71506499 0.68864025 9 sp_24 -0.869274055 0.39534471
-#> 6251 0 1.71506499 0.68864025 11 sp_25 -0.869274055 0.39534471
-#> 6261 0 1.71506499 0.68864025 7 sp_26 -0.869274055 0.39534471
-#> 6271 0 1.71506499 0.68864025 13 sp_27 -0.869274055 0.39534471
-#> 6281 1 1.71506499 0.68864025 5 sp_28 -0.869274055 0.39534471
-#> 6291 0 1.71506499 0.68864025 11 sp_29 -0.869274055 0.39534471
-#> 6301 0 1.71506499 0.68864025 1 sp_30 -0.869274055 0.39534471
-#> 7211 0 0.46091621 0.55391765 19 sp_1 -0.730637689 1.23693746
-#> 7221 1 0.46091621 0.55391765 12 sp_2 -0.730637689 1.23693746
-#> 7231 0 0.46091621 0.55391765 2 sp_3 -0.730637689 1.23693746
-#> 7241 1 0.46091621 0.55391765 17 sp_4 -0.730637689 1.23693746
-#> 7251 0 0.46091621 0.55391765 12 sp_5 -0.730637689 1.23693746
-#> 7261 0 0.46091621 0.55391765 3 sp_6 -0.730637689 1.23693746
-#> 7271 0 0.46091621 0.55391765 18 sp_7 -0.730637689 1.23693746
-#> 7281 0 0.46091621 0.55391765 15 sp_8 -0.730637689 1.23693746
-#> 7291 0 0.46091621 0.55391765 3 sp_9 -0.730637689 1.23693746
-#> 7301 0 0.46091621 0.55391765 19 sp_10 -0.730637689 1.23693746
-#> 7311 0 0.46091621 0.55391765 18 sp_11 -0.730637689 1.23693746
-#> 7321 0 0.46091621 0.55391765 17 sp_12 -0.730637689 1.23693746
-#> 7331 0 0.46091621 0.55391765 6 sp_13 -0.730637689 1.23693746
-#> 7341 0 0.46091621 0.55391765 10 sp_14 -0.730637689 1.23693746
-#> 7351 0 0.46091621 0.55391765 8 sp_15 -0.730637689 1.23693746
-#> 7361 0 0.46091621 0.55391765 10 sp_16 -0.730637689 1.23693746
-#> 7371 0 0.46091621 0.55391765 13 sp_17 -0.730637689 1.23693746
-#> 7381 0 0.46091621 0.55391765 20 sp_18 -0.730637689 1.23693746
-#> 7391 0 0.46091621 0.55391765 6 sp_19 -0.730637689 1.23693746
-#> 7401 0 0.46091621 0.55391765 20 sp_20 -0.730637689 1.23693746
-#> 7411 1 0.46091621 0.55391765 20 sp_21 -0.730637689 1.23693746
-#> 7421 0 0.46091621 0.55391765 9 sp_22 -0.730637689 1.23693746
-#> 7431 0 0.46091621 0.55391765 16 sp_23 -0.730637689 1.23693746
-#> 7441 0 0.46091621 0.55391765 8 sp_24 -0.730637689 1.23693746
-#> 7451 0 0.46091621 0.55391765 7 sp_25 -0.730637689 1.23693746
-#> 7461 0 0.46091621 0.55391765 10 sp_26 -0.730637689 1.23693746
-#> 7471 1 0.46091621 0.55391765 17 sp_27 -0.730637689 1.23693746
-#> 7481 0 0.46091621 0.55391765 18 sp_28 -0.730637689 1.23693746
-#> 7491 0 0.46091621 0.55391765 8 sp_29 -0.730637689 1.23693746
-#> 7501 0 0.46091621 0.55391765 19 sp_30 -0.730637689 1.23693746
-#> 8411 0 -1.26506123 -0.06191171 10 sp_1 1.111633173 0.14385911
-#> 8421 0 -1.26506123 -0.06191171 11 sp_2 1.111633173 0.14385911
-#> 8431 0 -1.26506123 -0.06191171 17 sp_3 1.111633173 0.14385911
-#> 8441 0 -1.26506123 -0.06191171 12 sp_4 1.111633173 0.14385911
-#> 8451 0 -1.26506123 -0.06191171 2 sp_5 1.111633173 0.14385911
-#> 8461 0 -1.26506123 -0.06191171 19 sp_6 1.111633173 0.14385911
-#> 8471 0 -1.26506123 -0.06191171 13 sp_7 1.111633173 0.14385911
-#> 8481 0 -1.26506123 -0.06191171 13 sp_8 1.111633173 0.14385911
-#> 8491 0 -1.26506123 -0.06191171 19 sp_9 1.111633173 0.14385911
-#> 8501 1 -1.26506123 -0.06191171 10 sp_10 1.111633173 0.14385911
-#> 8511 0 -1.26506123 -0.06191171 16 sp_11 1.111633173 0.14385911
-#> 8521 0 -1.26506123 -0.06191171 5 sp_12 1.111633173 0.14385911
-#> 8531 0 -1.26506123 -0.06191171 4 sp_13 1.111633173 0.14385911
-#> 8541 0 -1.26506123 -0.06191171 18 sp_14 1.111633173 0.14385911
-#> 8551 0 -1.26506123 -0.06191171 1 sp_15 1.111633173 0.14385911
-#> 8561 0 -1.26506123 -0.06191171 16 sp_16 1.111633173 0.14385911
-#> 8571 0 -1.26506123 -0.06191171 17 sp_17 1.111633173 0.14385911
-#> 8581 0 -1.26506123 -0.06191171 12 sp_18 1.111633173 0.14385911
-#> 8591 1 -1.26506123 -0.06191171 2 sp_19 1.111633173 0.14385911
-#> 8601 0 -1.26506123 -0.06191171 18 sp_20 1.111633173 0.14385911
-#> 8611 0 -1.26506123 -0.06191171 12 sp_21 1.111633173 0.14385911
-#> 8621 0 -1.26506123 -0.06191171 15 sp_22 1.111633173 0.14385911
-#> 8631 0 -1.26506123 -0.06191171 19 sp_23 1.111633173 0.14385911
-#> 8641 0 -1.26506123 -0.06191171 6 sp_24 1.111633173 0.14385911
-#> 8651 0 -1.26506123 -0.06191171 16 sp_25 1.111633173 0.14385911
-#> 8661 0 -1.26506123 -0.06191171 15 sp_26 1.111633173 0.14385911
-#> 8671 0 -1.26506123 -0.06191171 19 sp_27 1.111633173 0.14385911
-#> 8681 0 -1.26506123 -0.06191171 3 sp_28 1.111633173 0.14385911
-#> 8691 0 -1.26506123 -0.06191171 14 sp_29 1.111633173 0.14385911
-#> 8701 0 -1.26506123 -0.06191171 1 sp_30 1.111633173 0.14385911
-#> 9611 1 -0.68685285 -0.30596266 1 sp_1 -0.166381366 -1.44944857
-#> 9621 0 -0.68685285 -0.30596266 16 sp_2 -0.166381366 -1.44944857
-#> 9631 0 -0.68685285 -0.30596266 11 sp_3 -0.166381366 -1.44944857
-#> 9641 0 -0.68685285 -0.30596266 4 sp_4 -0.166381366 -1.44944857
-#> 9651 1 -0.68685285 -0.30596266 12 sp_5 -0.166381366 -1.44944857
-#> 9661 1 -0.68685285 -0.30596266 13 sp_6 -0.166381366 -1.44944857
-#> 9671 0 -0.68685285 -0.30596266 10 sp_7 -0.166381366 -1.44944857
-#> 9681 0 -0.68685285 -0.30596266 10 sp_8 -0.166381366 -1.44944857
-#> 9691 1 -0.68685285 -0.30596266 7 sp_9 -0.166381366 -1.44944857
-#> 9701 0 -0.68685285 -0.30596266 18 sp_10 -0.166381366 -1.44944857
-#> 9711 0 -0.68685285 -0.30596266 17 sp_11 -0.166381366 -1.44944857
-#> 9721 0 -0.68685285 -0.30596266 20 sp_12 -0.166381366 -1.44944857
-#> 9731 1 -0.68685285 -0.30596266 9 sp_13 -0.166381366 -1.44944857
-#> 9741 0 -0.68685285 -0.30596266 11 sp_14 -0.166381366 -1.44944857
-#> 9751 1 -0.68685285 -0.30596266 12 sp_15 -0.166381366 -1.44944857
-#> 9761 0 -0.68685285 -0.30596266 8 sp_16 -0.166381366 -1.44944857
-#> 9771 0 -0.68685285 -0.30596266 18 sp_17 -0.166381366 -1.44944857
-#> 9781 0 -0.68685285 -0.30596266 5 sp_18 -0.166381366 -1.44944857
-#> 9791 0 -0.68685285 -0.30596266 18 sp_19 -0.166381366 -1.44944857
-#> 9801 0 -0.68685285 -0.30596266 6 sp_20 -0.166381366 -1.44944857
-#> 9811 0 -0.68685285 -0.30596266 10 sp_21 -0.166381366 -1.44944857
-#> 9821 0 -0.68685285 -0.30596266 9 sp_22 -0.166381366 -1.44944857
-#> 9831 0 -0.68685285 -0.30596266 11 sp_23 -0.166381366 -1.44944857
-#> 9841 0 -0.68685285 -0.30596266 6 sp_24 -0.166381366 -1.44944857
-#> 9851 0 -0.68685285 -0.30596266 12 sp_25 -0.166381366 -1.44944857
-#> 9861 0 -0.68685285 -0.30596266 19 sp_26 -0.166381366 -1.44944857
-#> 9871 0 -0.68685285 -0.30596266 4 sp_27 -0.166381366 -1.44944857
-#> 9881 0 -0.68685285 -0.30596266 3 sp_28 -0.166381366 -1.44944857
-#> 9891 0 -0.68685285 -0.30596266 14 sp_29 -0.166381366 -1.44944857
-#> 9901 0 -0.68685285 -0.30596266 8 sp_30 -0.166381366 -1.44944857
-#> 10811 0 -0.44566197 -0.38047100 6 sp_1 0.967695272 0.26986716
-#> 10821 0 -0.44566197 -0.38047100 4 sp_2 0.967695272 0.26986716
-#> 10831 1 -0.44566197 -0.38047100 10 sp_3 0.967695272 0.26986716
-#> 10841 0 -0.44566197 -0.38047100 16 sp_4 0.967695272 0.26986716
-#> 10851 0 -0.44566197 -0.38047100 16 sp_5 0.967695272 0.26986716
-#> 10861 0 -0.44566197 -0.38047100 20 sp_6 0.967695272 0.26986716
-#> 10871 1 -0.44566197 -0.38047100 10 sp_7 0.967695272 0.26986716
-#> 10881 0 -0.44566197 -0.38047100 6 sp_8 0.967695272 0.26986716
-#> 10891 0 -0.44566197 -0.38047100 19 sp_9 0.967695272 0.26986716
-#> 10901 0 -0.44566197 -0.38047100 4 sp_10 0.967695272 0.26986716
-#> 10911 0 -0.44566197 -0.38047100 9 sp_11 0.967695272 0.26986716
-#> 10921 0 -0.44566197 -0.38047100 4 sp_12 0.967695272 0.26986716
-#> 10931 0 -0.44566197 -0.38047100 15 sp_13 0.967695272 0.26986716
-#> 10941 1 -0.44566197 -0.38047100 20 sp_14 0.967695272 0.26986716
-#> 10951 0 -0.44566197 -0.38047100 17 sp_15 0.967695272 0.26986716
-#> 10961 0 -0.44566197 -0.38047100 7 sp_16 0.967695272 0.26986716
-#> 10971 0 -0.44566197 -0.38047100 15 sp_17 0.967695272 0.26986716
-#> 10981 0 -0.44566197 -0.38047100 5 sp_18 0.967695272 0.26986716
-#> 10991 0 -0.44566197 -0.38047100 14 sp_19 0.967695272 0.26986716
-#> 11001 0 -0.44566197 -0.38047100 15 sp_20 0.967695272 0.26986716
-#> 11011 1 -0.44566197 -0.38047100 15 sp_21 0.967695272 0.26986716
-#> 11021 0 -0.44566197 -0.38047100 16 sp_22 0.967695272 0.26986716
-#> 11031 0 -0.44566197 -0.38047100 19 sp_23 0.967695272 0.26986716
-#> 11041 0 -0.44566197 -0.38047100 8 sp_24 0.967695272 0.26986716
-#> 11051 0 -0.44566197 -0.38047100 5 sp_25 0.967695272 0.26986716
-#> 11061 0 -0.44566197 -0.38047100 7 sp_26 0.967695272 0.26986716
-#> 11071 0 -0.44566197 -0.38047100 20 sp_27 0.967695272 0.26986716
-#> 11081 0 -0.44566197 -0.38047100 16 sp_28 0.967695272 0.26986716
-#> 11091 0 -0.44566197 -0.38047100 16 sp_29 0.967695272 0.26986716
-#> 11101 0 -0.44566197 -0.38047100 9 sp_30 0.967695272 0.26986716
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-#> 12031 0 1.22408180 -0.69470698 19 sp_3 -0.498319395 1.33868649
-#> 12041 0 1.22408180 -0.69470698 10 sp_4 -0.498319395 1.33868649
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-#> 12061 0 1.22408180 -0.69470698 6 sp_6 -0.498319395 1.33868649
-#> 12071 0 1.22408180 -0.69470698 20 sp_7 -0.498319395 1.33868649
-#> 12081 0 1.22408180 -0.69470698 14 sp_8 -0.498319395 1.33868649
-#> 12091 0 1.22408180 -0.69470698 14 sp_9 -0.498319395 1.33868649
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-#> 12141 0 1.22408180 -0.69470698 11 sp_14 -0.498319395 1.33868649
-#> 12151 0 1.22408180 -0.69470698 7 sp_15 -0.498319395 1.33868649
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-#> 12171 0 1.22408180 -0.69470698 8 sp_17 -0.498319395 1.33868649
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-#> 12201 0 1.22408180 -0.69470698 17 sp_20 -0.498319395 1.33868649
-#> 12211 1 1.22408180 -0.69470698 6 sp_21 -0.498319395 1.33868649
-#> 12221 0 1.22408180 -0.69470698 8 sp_22 -0.498319395 1.33868649
-#> 12231 1 1.22408180 -0.69470698 20 sp_23 -0.498319395 1.33868649
-#> 12241 0 1.22408180 -0.69470698 6 sp_24 -0.498319395 1.33868649
-#> 12251 0 1.22408180 -0.69470698 15 sp_25 -0.498319395 1.33868649
-#> 12261 1 1.22408180 -0.69470698 17 sp_26 -0.498319395 1.33868649
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-#> 12281 0 1.22408180 -0.69470698 15 sp_28 -0.498319395 1.33868649
-#> 12291 1 1.22408180 -0.69470698 20 sp_29 -0.498319395 1.33868649
-#> 12301 0 1.22408180 -0.69470698 1 sp_30 -0.498319395 1.33868649
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-#> 13221 1 0.35981383 -0.20791728 11 sp_2 0.926885841 1.61114313
-#> 13231 0 0.35981383 -0.20791728 15 sp_3 0.926885841 1.61114313
-#> 13241 0 0.35981383 -0.20791728 20 sp_4 0.926885841 1.61114313
-#> 13251 0 0.35981383 -0.20791728 2 sp_5 0.926885841 1.61114313
-#> 13261 0 0.35981383 -0.20791728 16 sp_6 0.926885841 1.61114313
-#> 13271 0 0.35981383 -0.20791728 19 sp_7 0.926885841 1.61114313
-#> 13281 0 0.35981383 -0.20791728 10 sp_8 0.926885841 1.61114313
-#> 13291 0 0.35981383 -0.20791728 19 sp_9 0.926885841 1.61114313
-#> 13301 0 0.35981383 -0.20791728 17 sp_10 0.926885841 1.61114313
-#> 13311 0 0.35981383 -0.20791728 7 sp_11 0.926885841 1.61114313
-#> 13321 0 0.35981383 -0.20791728 6 sp_12 0.926885841 1.61114313
-#> 13331 0 0.35981383 -0.20791728 12 sp_13 0.926885841 1.61114313
-#> 13341 0 0.35981383 -0.20791728 4 sp_14 0.926885841 1.61114313
-#> 13351 0 0.35981383 -0.20791728 19 sp_15 0.926885841 1.61114313
-#> 13361 0 0.35981383 -0.20791728 2 sp_16 0.926885841 1.61114313
-#> 13371 0 0.35981383 -0.20791728 4 sp_17 0.926885841 1.61114313
-#> 13381 1 0.35981383 -0.20791728 11 sp_18 0.926885841 1.61114313
-#> 13391 0 0.35981383 -0.20791728 1 sp_19 0.926885841 1.61114313
-#> 13401 0 0.35981383 -0.20791728 19 sp_20 0.926885841 1.61114313
-#> 13411 1 0.35981383 -0.20791728 18 sp_21 0.926885841 1.61114313
-#> 13421 0 0.35981383 -0.20791728 16 sp_22 0.926885841 1.61114313
-#> 13431 1 0.35981383 -0.20791728 3 sp_23 0.926885841 1.61114313
-#> 13441 0 0.35981383 -0.20791728 1 sp_24 0.926885841 1.61114313
-#> 13451 0 0.35981383 -0.20791728 2 sp_25 0.926885841 1.61114313
-#> 13461 0 0.35981383 -0.20791728 2 sp_26 0.926885841 1.61114313
-#> 13471 0 0.35981383 -0.20791728 8 sp_27 0.926885841 1.61114313
-#> 13481 0 0.35981383 -0.20791728 20 sp_28 0.926885841 1.61114313
-#> 13491 0 0.35981383 -0.20791728 14 sp_29 0.926885841 1.61114313
-#> 13501 0 0.35981383 -0.20791728 13 sp_30 0.926885841 1.61114313
-#> 14411 1 0.40077145 -1.26539635 7 sp_1 0.081143100 -0.28723019
-#> 14421 0 0.40077145 -1.26539635 8 sp_2 0.081143100 -0.28723019
-#> 14431 0 0.40077145 -1.26539635 3 sp_3 0.081143100 -0.28723019
-#> 14441 0 0.40077145 -1.26539635 16 sp_4 0.081143100 -0.28723019
-#> 14451 0 0.40077145 -1.26539635 1 sp_5 0.081143100 -0.28723019
-#> 14461 1 0.40077145 -1.26539635 12 sp_6 0.081143100 -0.28723019
-#> 14471 1 0.40077145 -1.26539635 18 sp_7 0.081143100 -0.28723019
-#> 14481 0 0.40077145 -1.26539635 14 sp_8 0.081143100 -0.28723019
-#> 14491 1 0.40077145 -1.26539635 8 sp_9 0.081143100 -0.28723019
-#> 14501 1 0.40077145 -1.26539635 5 sp_10 0.081143100 -0.28723019
-#> 14511 1 0.40077145 -1.26539635 17 sp_11 0.081143100 -0.28723019
-#> 14521 0 0.40077145 -1.26539635 11 sp_12 0.081143100 -0.28723019
-#> 14531 0 0.40077145 -1.26539635 4 sp_13 0.081143100 -0.28723019
-#> 14541 1 0.40077145 -1.26539635 13 sp_14 0.081143100 -0.28723019
-#> 14551 1 0.40077145 -1.26539635 8 sp_15 0.081143100 -0.28723019
-#> 14561 0 0.40077145 -1.26539635 15 sp_16 0.081143100 -0.28723019
-#> 14571 1 0.40077145 -1.26539635 4 sp_17 0.081143100 -0.28723019
-#> 14581 0 0.40077145 -1.26539635 13 sp_18 0.081143100 -0.28723019
-#> 14591 0 0.40077145 -1.26539635 3 sp_19 0.081143100 -0.28723019
-#> 14601 1 0.40077145 -1.26539635 7 sp_20 0.081143100 -0.28723019
-#> 14611 0 0.40077145 -1.26539635 1 sp_21 0.081143100 -0.28723019
-#> 14621 0 0.40077145 -1.26539635 6 sp_22 0.081143100 -0.28723019
-#> 14631 1 0.40077145 -1.26539635 13 sp_23 0.081143100 -0.28723019
-#> 14641 1 0.40077145 -1.26539635 17 sp_24 0.081143100 -0.28723019
-#> 14651 0 0.40077145 -1.26539635 6 sp_25 0.081143100 -0.28723019
-#> 14661 1 0.40077145 -1.26539635 10 sp_26 0.081143100 -0.28723019
-#> 14671 0 0.40077145 -1.26539635 13 sp_27 0.081143100 -0.28723019
-#> 14681 0 0.40077145 -1.26539635 6 sp_28 0.081143100 -0.28723019
-#> 14691 1 0.40077145 -1.26539635 9 sp_29 0.081143100 -0.28723019
-#> 14701 0 0.40077145 -1.26539635 8 sp_30 0.081143100 -0.28723019
-#> 15611 0 0.11068272 2.16895597 1 sp_1 -0.114458510 0.94373342
-#> 15621 0 0.11068272 2.16895597 16 sp_2 -0.114458510 0.94373342
-#> 15631 0 0.11068272 2.16895597 2 sp_3 -0.114458510 0.94373342
-#> 15641 0 0.11068272 2.16895597 8 sp_4 -0.114458510 0.94373342
-#> 15651 0 0.11068272 2.16895597 14 sp_5 -0.114458510 0.94373342
-#> 15661 0 0.11068272 2.16895597 12 sp_6 -0.114458510 0.94373342
-#> 15671 0 0.11068272 2.16895597 8 sp_7 -0.114458510 0.94373342
-#> 15681 0 0.11068272 2.16895597 9 sp_8 -0.114458510 0.94373342
-#> 15691 0 0.11068272 2.16895597 8 sp_9 -0.114458510 0.94373342
-#> 15701 0 0.11068272 2.16895597 9 sp_10 -0.114458510 0.94373342
-#> 15711 0 0.11068272 2.16895597 20 sp_11 -0.114458510 0.94373342
-#> 15721 0 0.11068272 2.16895597 1 sp_12 -0.114458510 0.94373342
-#> 15731 0 0.11068272 2.16895597 3 sp_13 -0.114458510 0.94373342
-#> 15741 0 0.11068272 2.16895597 8 sp_14 -0.114458510 0.94373342
-#> 15751 0 0.11068272 2.16895597 2 sp_15 -0.114458510 0.94373342
-#> 15761 0 0.11068272 2.16895597 1 sp_16 -0.114458510 0.94373342
-#> 15771 0 0.11068272 2.16895597 9 sp_17 -0.114458510 0.94373342
-#> 15781 0 0.11068272 2.16895597 7 sp_18 -0.114458510 0.94373342
-#> 15791 0 0.11068272 2.16895597 13 sp_19 -0.114458510 0.94373342
-#> 15801 0 0.11068272 2.16895597 20 sp_20 -0.114458510 0.94373342
-#> 15811 0 0.11068272 2.16895597 14 sp_21 -0.114458510 0.94373342
-#> 15821 0 0.11068272 2.16895597 16 sp_22 -0.114458510 0.94373342
-#> 15831 0 0.11068272 2.16895597 7 sp_23 -0.114458510 0.94373342
-#> 15841 0 0.11068272 2.16895597 4 sp_24 -0.114458510 0.94373342
-#> 15851 0 0.11068272 2.16895597 13 sp_25 -0.114458510 0.94373342
-#> 15861 0 0.11068272 2.16895597 12 sp_26 -0.114458510 0.94373342
-#> 15871 0 0.11068272 2.16895597 13 sp_27 -0.114458510 0.94373342
-#> 15881 0 0.11068272 2.16895597 20 sp_28 -0.114458510 0.94373342
-#> 15891 0 0.11068272 2.16895597 10 sp_29 -0.114458510 0.94373342
-#> 15901 0 0.11068272 2.16895597 9 sp_30 -0.114458510 0.94373342
-#> 16811 0 -0.55584113 1.20796200 12 sp_1 -1.864998020 -1.12347081
-#> 16821 0 -0.55584113 1.20796200 8 sp_2 -1.864998020 -1.12347081
-#> 16831 0 -0.55584113 1.20796200 7 sp_3 -1.864998020 -1.12347081
-#> 16841 0 -0.55584113 1.20796200 15 sp_4 -1.864998020 -1.12347081
-#> 16851 0 -0.55584113 1.20796200 19 sp_5 -1.864998020 -1.12347081
-#> 16861 0 -0.55584113 1.20796200 17 sp_6 -1.864998020 -1.12347081
-#> 16871 0 -0.55584113 1.20796200 11 sp_7 -1.864998020 -1.12347081
-#> 16881 0 -0.55584113 1.20796200 7 sp_8 -1.864998020 -1.12347081
-#> 16891 0 -0.55584113 1.20796200 19 sp_9 -1.864998020 -1.12347081
-#> 16901 0 -0.55584113 1.20796200 3 sp_10 -1.864998020 -1.12347081
-#> 16911 0 -0.55584113 1.20796200 6 sp_11 -1.864998020 -1.12347081
-#> 16921 0 -0.55584113 1.20796200 7 sp_12 -1.864998020 -1.12347081
-#> 16931 0 -0.55584113 1.20796200 4 sp_13 -1.864998020 -1.12347081
-#> 16941 1 -0.55584113 1.20796200 10 sp_14 -1.864998020 -1.12347081
-#> 16951 0 -0.55584113 1.20796200 17 sp_15 -1.864998020 -1.12347081
-#> 16961 0 -0.55584113 1.20796200 16 sp_16 -1.864998020 -1.12347081
-#> 16971 0 -0.55584113 1.20796200 8 sp_17 -1.864998020 -1.12347081
-#> 16981 0 -0.55584113 1.20796200 3 sp_18 -1.864998020 -1.12347081
-#> 16991 0 -0.55584113 1.20796200 12 sp_19 -1.864998020 -1.12347081
-#> 17001 0 -0.55584113 1.20796200 14 sp_20 -1.864998020 -1.12347081
-#> 17011 0 -0.55584113 1.20796200 5 sp_21 -1.864998020 -1.12347081
-#> 17021 0 -0.55584113 1.20796200 14 sp_22 -1.864998020 -1.12347081
-#> 17031 0 -0.55584113 1.20796200 6 sp_23 -1.864998020 -1.12347081
-#> 17041 0 -0.55584113 1.20796200 9 sp_24 -1.864998020 -1.12347081
-#> 17051 0 -0.55584113 1.20796200 1 sp_25 -1.864998020 -1.12347081
-#> 17061 0 -0.55584113 1.20796200 20 sp_26 -1.864998020 -1.12347081
-#> 17071 0 -0.55584113 1.20796200 14 sp_27 -1.864998020 -1.12347081
-#> 17081 0 -0.55584113 1.20796200 19 sp_28 -1.864998020 -1.12347081
-#> 17091 0 -0.55584113 1.20796200 5 sp_29 -1.864998020 -1.12347081
-#> 17101 0 -0.55584113 1.20796200 2 sp_30 -1.864998020 -1.12347081
-#> 18011 0 1.78691314 -1.12310858 1 sp_1 -1.421957153 2.26468095
-#> 18021 0 1.78691314 -1.12310858 20 sp_2 -1.421957153 2.26468095
-#> 18031 0 1.78691314 -1.12310858 4 sp_3 -1.421957153 2.26468095
-#> 18041 0 1.78691314 -1.12310858 11 sp_4 -1.421957153 2.26468095
-#> 18051 0 1.78691314 -1.12310858 5 sp_5 -1.421957153 2.26468095
-#> 18061 0 1.78691314 -1.12310858 4 sp_6 -1.421957153 2.26468095
-#> 18071 0 1.78691314 -1.12310858 19 sp_7 -1.421957153 2.26468095
-#> 18081 0 1.78691314 -1.12310858 3 sp_8 -1.421957153 2.26468095
-#> 18091 0 1.78691314 -1.12310858 1 sp_9 -1.421957153 2.26468095
-#> 18101 0 1.78691314 -1.12310858 7 sp_10 -1.421957153 2.26468095
-#> 18111 0 1.78691314 -1.12310858 5 sp_11 -1.421957153 2.26468095
-#> 18121 0 1.78691314 -1.12310858 9 sp_12 -1.421957153 2.26468095
-#> 18131 0 1.78691314 -1.12310858 17 sp_13 -1.421957153 2.26468095
-#> 18141 0 1.78691314 -1.12310858 5 sp_14 -1.421957153 2.26468095
-#> 18151 0 1.78691314 -1.12310858 12 sp_15 -1.421957153 2.26468095
-#> 18161 0 1.78691314 -1.12310858 2 sp_16 -1.421957153 2.26468095
-#> 18171 1 1.78691314 -1.12310858 18 sp_17 -1.421957153 2.26468095
-#> 18181 0 1.78691314 -1.12310858 4 sp_18 -1.421957153 2.26468095
-#> 18191 1 1.78691314 -1.12310858 10 sp_19 -1.421957153 2.26468095
-#> 18201 0 1.78691314 -1.12310858 15 sp_20 -1.421957153 2.26468095
-#> 18211 0 1.78691314 -1.12310858 8 sp_21 -1.421957153 2.26468095
-#> 18221 0 1.78691314 -1.12310858 1 sp_22 -1.421957153 2.26468095
-#> 18231 0 1.78691314 -1.12310858 11 sp_23 -1.421957153 2.26468095
-#> 18241 0 1.78691314 -1.12310858 5 sp_24 -1.421957153 2.26468095
-#> 18251 0 1.78691314 -1.12310858 11 sp_25 -1.421957153 2.26468095
-#> 18261 0 1.78691314 -1.12310858 15 sp_26 -1.421957153 2.26468095
-#> 18271 0 1.78691314 -1.12310858 15 sp_27 -1.421957153 2.26468095
-#> 18281 1 1.78691314 -1.12310858 10 sp_28 -1.421957153 2.26468095
-#> 18291 0 1.78691314 -1.12310858 15 sp_29 -1.421957153 2.26468095
-#> 18301 0 1.78691314 -1.12310858 15 sp_30 -1.421957153 2.26468095
-#> 19211 1 0.49785048 -0.40288484 20 sp_1 0.710841370 0.55646477
-#> 19221 0 0.49785048 -0.40288484 12 sp_2 0.710841370 0.55646477
-#> 19231 0 0.49785048 -0.40288484 9 sp_3 0.710841370 0.55646477
-#> 19241 0 0.49785048 -0.40288484 4 sp_4 0.710841370 0.55646477
-#> 19251 1 0.49785048 -0.40288484 3 sp_5 0.710841370 0.55646477
-#> 19261 1 0.49785048 -0.40288484 7 sp_6 0.710841370 0.55646477
-#> 19271 0 0.49785048 -0.40288484 4 sp_7 0.710841370 0.55646477
-#> 19281 0 0.49785048 -0.40288484 8 sp_8 0.710841370 0.55646477
-#> 19291 0 0.49785048 -0.40288484 5 sp_9 0.710841370 0.55646477
-#> 19301 0 0.49785048 -0.40288484 6 sp_10 0.710841370 0.55646477
-#> 19311 0 0.49785048 -0.40288484 4 sp_11 0.710841370 0.55646477
-#> 19321 0 0.49785048 -0.40288484 3 sp_12 0.710841370 0.55646477
-#> 19331 0 0.49785048 -0.40288484 11 sp_13 0.710841370 0.55646477
-#> 19341 0 0.49785048 -0.40288484 10 sp_14 0.710841370 0.55646477
-#> 19351 0 0.49785048 -0.40288484 5 sp_15 0.710841370 0.55646477
-#> 19361 1 0.49785048 -0.40288484 11 sp_16 0.710841370 0.55646477
-#> 19371 0 0.49785048 -0.40288484 10 sp_17 0.710841370 0.55646477
-#> 19381 0 0.49785048 -0.40288484 15 sp_18 0.710841370 0.55646477
-#> 19391 0 0.49785048 -0.40288484 19 sp_19 0.710841370 0.55646477
-#> 19401 0 0.49785048 -0.40288484 10 sp_20 0.710841370 0.55646477
-#> 19411 1 0.49785048 -0.40288484 13 sp_21 0.710841370 0.55646477
-#> 19421 0 0.49785048 -0.40288484 3 sp_22 0.710841370 0.55646477
-#> 19431 0 0.49785048 -0.40288484 18 sp_23 0.710841370 0.55646477
-#> 19441 0 0.49785048 -0.40288484 10 sp_24 0.710841370 0.55646477
-#> 19451 1 0.49785048 -0.40288484 8 sp_25 0.710841370 0.55646477
-#> 19461 1 0.49785048 -0.40288484 12 sp_26 0.710841370 0.55646477
-#> 19471 0 0.49785048 -0.40288484 10 sp_27 0.710841370 0.55646477
-#> 19481 0 0.49785048 -0.40288484 7 sp_28 0.710841370 0.55646477
-#> 19491 0 0.49785048 -0.40288484 7 sp_29 0.710841370 0.55646477
-#> 19501 0 0.49785048 -0.40288484 6 sp_30 0.710841370 0.55646477
-#> 20411 0 -1.96661716 -0.46665535 17 sp_1 -1.294813968 -0.28740457
-#> 20421 0 -1.96661716 -0.46665535 20 sp_2 -1.294813968 -0.28740457
-#> 20431 0 -1.96661716 -0.46665535 1 sp_3 -1.294813968 -0.28740457
-#> 20441 0 -1.96661716 -0.46665535 5 sp_4 -1.294813968 -0.28740457
-#> 20451 0 -1.96661716 -0.46665535 10 sp_5 -1.294813968 -0.28740457
-#> 20461 0 -1.96661716 -0.46665535 13 sp_6 -1.294813968 -0.28740457
-#> 20471 0 -1.96661716 -0.46665535 10 sp_7 -1.294813968 -0.28740457
-#> 20481 0 -1.96661716 -0.46665535 2 sp_8 -1.294813968 -0.28740457
-#> 20491 0 -1.96661716 -0.46665535 15 sp_9 -1.294813968 -0.28740457
-#> 20501 0 -1.96661716 -0.46665535 15 sp_10 -1.294813968 -0.28740457
-#> 20511 0 -1.96661716 -0.46665535 8 sp_11 -1.294813968 -0.28740457
-#> 20521 0 -1.96661716 -0.46665535 3 sp_12 -1.294813968 -0.28740457
-#> 20531 0 -1.96661716 -0.46665535 2 sp_13 -1.294813968 -0.28740457
-#> 20541 0 -1.96661716 -0.46665535 6 sp_14 -1.294813968 -0.28740457
-#> 20551 0 -1.96661716 -0.46665535 14 sp_15 -1.294813968 -0.28740457
-#> 20561 0 -1.96661716 -0.46665535 15 sp_16 -1.294813968 -0.28740457
-#> 20571 0 -1.96661716 -0.46665535 19 sp_17 -1.294813968 -0.28740457
-#> 20581 0 -1.96661716 -0.46665535 9 sp_18 -1.294813968 -0.28740457
-#> 20591 0 -1.96661716 -0.46665535 15 sp_19 -1.294813968 -0.28740457
-#> 20601 0 -1.96661716 -0.46665535 16 sp_20 -1.294813968 -0.28740457
-#> 20611 0 -1.96661716 -0.46665535 8 sp_21 -1.294813968 -0.28740457
-#> 20621 0 -1.96661716 -0.46665535 9 sp_22 -1.294813968 -0.28740457
-#> 20631 0 -1.96661716 -0.46665535 16 sp_23 -1.294813968 -0.28740457
-#> 20641 0 -1.96661716 -0.46665535 9 sp_24 -1.294813968 -0.28740457
-#> 20651 0 -1.96661716 -0.46665535 2 sp_25 -1.294813968 -0.28740457
-#> 20661 0 -1.96661716 -0.46665535 9 sp_26 -1.294813968 -0.28740457
-#> 20671 0 -1.96661716 -0.46665535 11 sp_27 -1.294813968 -0.28740457
-#> 20681 0 -1.96661716 -0.46665535 11 sp_28 -1.294813968 -0.28740457
-#> 20691 0 -1.96661716 -0.46665535 4 sp_29 -1.294813968 -0.28740457
-#> 20701 0 -1.96661716 -0.46665535 7 sp_30 -1.294813968 -0.28740457
-#> 21611 0 0.70135590 0.77996512 18 sp_1 -1.066032692 1.17589068
-#> 21621 0 0.70135590 0.77996512 11 sp_2 -1.066032692 1.17589068
-#> 21631 0 0.70135590 0.77996512 1 sp_3 -1.066032692 1.17589068
-#> 21641 1 0.70135590 0.77996512 11 sp_4 -1.066032692 1.17589068
-#> 21651 0 0.70135590 0.77996512 6 sp_5 -1.066032692 1.17589068
-#> 21661 0 0.70135590 0.77996512 10 sp_6 -1.066032692 1.17589068
-#> 21671 0 0.70135590 0.77996512 18 sp_7 -1.066032692 1.17589068
-#> 21681 0 0.70135590 0.77996512 3 sp_8 -1.066032692 1.17589068
-#> 21691 0 0.70135590 0.77996512 3 sp_9 -1.066032692 1.17589068
-#> 21701 0 0.70135590 0.77996512 2 sp_10 -1.066032692 1.17589068
-#> 21711 0 0.70135590 0.77996512 8 sp_11 -1.066032692 1.17589068
-#> 21721 0 0.70135590 0.77996512 13 sp_12 -1.066032692 1.17589068
-#> 21731 0 0.70135590 0.77996512 8 sp_13 -1.066032692 1.17589068
-#> 21741 0 0.70135590 0.77996512 2 sp_14 -1.066032692 1.17589068
-#> 21751 0 0.70135590 0.77996512 6 sp_15 -1.066032692 1.17589068
-#> 21761 0 0.70135590 0.77996512 17 sp_16 -1.066032692 1.17589068
-#> 21771 0 0.70135590 0.77996512 14 sp_17 -1.066032692 1.17589068
-#> 21781 0 0.70135590 0.77996512 7 sp_18 -1.066032692 1.17589068
-#> 21791 0 0.70135590 0.77996512 13 sp_19 -1.066032692 1.17589068
-#> 21801 0 0.70135590 0.77996512 8 sp_20 -1.066032692 1.17589068
-#> 21811 0 0.70135590 0.77996512 6 sp_21 -1.066032692 1.17589068
-#> 21821 0 0.70135590 0.77996512 11 sp_22 -1.066032692 1.17589068
-#> 21831 0 0.70135590 0.77996512 10 sp_23 -1.066032692 1.17589068
-#> 21841 0 0.70135590 0.77996512 17 sp_24 -1.066032692 1.17589068
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-#> 21861 0 0.70135590 0.77996512 12 sp_26 -1.066032692 1.17589068
-#> 21871 0 0.70135590 0.77996512 19 sp_27 -1.066032692 1.17589068
-#> 21881 0 0.70135590 0.77996512 17 sp_28 -1.066032692 1.17589068
-#> 21891 0 0.70135590 0.77996512 8 sp_29 -1.066032692 1.17589068
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-#> 23071 0 -0.47279141 -0.08336907 18 sp_27 0.163432374 -0.33967076
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-#> 23091 0 -0.47279141 -0.08336907 9 sp_29 0.163432374 -0.33967076
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-#> 24171 0 -1.06782371 0.25331851 18 sp_17 0.915459490 -0.78713906
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-#> 24201 0 -1.06782371 0.25331851 14 sp_20 0.915459490 -0.78713906
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-#> 24221 0 -1.06782371 0.25331851 15 sp_22 0.915459490 -0.78713906
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-#> 24251 0 -1.06782371 0.25331851 8 sp_25 0.915459490 -0.78713906
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-#> 24281 0 -1.06782371 0.25331851 3 sp_28 0.915459490 -0.78713906
-#> 24291 1 -1.06782371 0.25331851 2 sp_29 0.915459490 -0.78713906
-#> 24301 0 -1.06782371 0.25331851 11 sp_30 0.915459490 -0.78713906
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-#> 25231 0 -0.21797491 -0.02854676 20 sp_3 -0.293764363 -0.31146820
-#> 25241 1 -0.21797491 -0.02854676 11 sp_4 -0.293764363 -0.31146820
-#> 25251 0 -0.21797491 -0.02854676 18 sp_5 -0.293764363 -0.31146820
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-#> 25291 0 -0.21797491 -0.02854676 14 sp_9 -0.293764363 -0.31146820
-#> 25301 0 -0.21797491 -0.02854676 7 sp_10 -0.293764363 -0.31146820
-#> 25311 0 -0.21797491 -0.02854676 15 sp_11 -0.293764363 -0.31146820
-#> 25321 0 -0.21797491 -0.02854676 8 sp_12 -0.293764363 -0.31146820
-#> 25331 0 -0.21797491 -0.02854676 1 sp_13 -0.293764363 -0.31146820
-#> 25341 0 -0.21797491 -0.02854676 5 sp_14 -0.293764363 -0.31146820
-#> 25351 1 -0.21797491 -0.02854676 17 sp_15 -0.293764363 -0.31146820
-#> 25361 0 -0.21797491 -0.02854676 6 sp_16 -0.293764363 -0.31146820
-#> 25371 0 -0.21797491 -0.02854676 10 sp_17 -0.293764363 -0.31146820
-#> 25381 0 -0.21797491 -0.02854676 12 sp_18 -0.293764363 -0.31146820
-#> 25391 0 -0.21797491 -0.02854676 8 sp_19 -0.293764363 -0.31146820
-#> 25401 0 -0.21797491 -0.02854676 16 sp_20 -0.293764363 -0.31146820
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-#> 25461 0 -0.21797491 -0.02854676 17 sp_26 -0.293764363 -0.31146820
-#> 25471 0 -0.21797491 -0.02854676 20 sp_27 -0.293764363 -0.31146820
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-#> 25491 0 -0.21797491 -0.02854676 14 sp_29 -0.293764363 -0.31146820
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-#> 26431 0 -1.02600445 -0.04287046 20 sp_3 0.829990553 0.16243481
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-#> 27781 0 -0.72889123 1.36860228 15 sp_18 -1.259322145 0.89326994
-#> 27791 0 -0.72889123 1.36860228 17 sp_19 -1.259322145 0.89326994
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-#> 27861 0 -0.72889123 1.36860228 15 sp_26 -1.259322145 0.89326994
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-#> 27881 0 -0.72889123 1.36860228 10 sp_28 -1.259322145 0.89326994
-#> 27891 0 -0.72889123 1.36860228 9 sp_29 -1.259322145 0.89326994
-#> 27901 0 -0.72889123 1.36860228 9 sp_30 -1.259322145 0.89326994
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-#> 30211 0 -1.68669331 1.51647060 19 sp_21 0.762974146 0.03164965
-#> 30221 0 -1.68669331 1.51647060 15 sp_22 0.762974146 0.03164965
-#> 30231 0 -1.68669331 1.51647060 19 sp_23 0.762974146 0.03164965
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-#> 30251 0 -1.68669331 1.51647060 15 sp_25 0.762974146 0.03164965
-#> 30261 0 -1.68669331 1.51647060 3 sp_26 0.762974146 0.03164965
-#> 30271 0 -1.68669331 1.51647060 2 sp_27 0.762974146 0.03164965
-#> 30281 0 -1.68669331 1.51647060 5 sp_28 0.762974146 0.03164965
-#> 30291 0 -1.68669331 1.51647060 5 sp_29 0.762974146 0.03164965
-#> 30301 0 -1.68669331 1.51647060 7 sp_30 0.762974146 0.03164965
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-#> 31231 1 0.83778704 -1.54875280 8 sp_3 -0.533239399 1.03360032
-#> 31241 0 0.83778704 -1.54875280 18 sp_4 -0.533239399 1.03360032
-#> 31251 0 0.83778704 -1.54875280 19 sp_5 -0.533239399 1.03360032
-#> 31261 0 0.83778704 -1.54875280 9 sp_6 -0.533239399 1.03360032
-#> 31271 0 0.83778704 -1.54875280 19 sp_7 -0.533239399 1.03360032
-#> 31281 0 0.83778704 -1.54875280 14 sp_8 -0.533239399 1.03360032
-#> 31291 0 0.83778704 -1.54875280 19 sp_9 -0.533239399 1.03360032
-#> 31301 0 0.83778704 -1.54875280 5 sp_10 -0.533239399 1.03360032
-#> 31311 0 0.83778704 -1.54875280 13 sp_11 -0.533239399 1.03360032
-#> 31321 0 0.83778704 -1.54875280 16 sp_12 -0.533239399 1.03360032
-#> 31331 0 0.83778704 -1.54875280 7 sp_13 -0.533239399 1.03360032
-#> 31341 0 0.83778704 -1.54875280 8 sp_14 -0.533239399 1.03360032
-#> 31351 0 0.83778704 -1.54875280 16 sp_15 -0.533239399 1.03360032
-#> 31361 0 0.83778704 -1.54875280 15 sp_16 -0.533239399 1.03360032
-#> 31371 0 0.83778704 -1.54875280 20 sp_17 -0.533239399 1.03360032
-#> 31381 0 0.83778704 -1.54875280 3 sp_18 -0.533239399 1.03360032
-#> 31391 0 0.83778704 -1.54875280 17 sp_19 -0.533239399 1.03360032
-#> 31401 0 0.83778704 -1.54875280 7 sp_20 -0.533239399 1.03360032
-#> 31411 0 0.83778704 -1.54875280 13 sp_21 -0.533239399 1.03360032
-#> 31421 0 0.83778704 -1.54875280 3 sp_22 -0.533239399 1.03360032
-#> 31431 0 0.83778704 -1.54875280 13 sp_23 -0.533239399 1.03360032
-#> 31441 0 0.83778704 -1.54875280 14 sp_24 -0.533239399 1.03360032
-#> 31451 0 0.83778704 -1.54875280 4 sp_25 -0.533239399 1.03360032
-#> 31461 0 0.83778704 -1.54875280 16 sp_26 -0.533239399 1.03360032
-#> 31471 0 0.83778704 -1.54875280 9 sp_27 -0.533239399 1.03360032
-#> 31481 0 0.83778704 -1.54875280 16 sp_28 -0.533239399 1.03360032
-#> 31491 0 0.83778704 -1.54875280 9 sp_29 -0.533239399 1.03360032
-#> 31501 0 0.83778704 -1.54875280 5 sp_30 -0.533239399 1.03360032
-#> 32411 0 0.15337312 0.58461375 14 sp_1 0.306420867 -0.23808313
-#> 32421 0 0.15337312 0.58461375 12 sp_2 0.306420867 -0.23808313
-#> 32431 1 0.15337312 0.58461375 14 sp_3 0.306420867 -0.23808313
-#> 32441 0 0.15337312 0.58461375 13 sp_4 0.306420867 -0.23808313
-#> 32451 0 0.15337312 0.58461375 20 sp_5 0.306420867 -0.23808313
-#> 32461 0 0.15337312 0.58461375 15 sp_6 0.306420867 -0.23808313
-#> 32471 0 0.15337312 0.58461375 8 sp_7 0.306420867 -0.23808313
-#> 32481 0 0.15337312 0.58461375 13 sp_8 0.306420867 -0.23808313
-#> 32491 0 0.15337312 0.58461375 7 sp_9 0.306420867 -0.23808313
-#> 32501 0 0.15337312 0.58461375 5 sp_10 0.306420867 -0.23808313
-#> 32511 0 0.15337312 0.58461375 8 sp_11 0.306420867 -0.23808313
-#> 32521 0 0.15337312 0.58461375 15 sp_12 0.306420867 -0.23808313
-#> 32531 0 0.15337312 0.58461375 14 sp_13 0.306420867 -0.23808313
-#> 32541 0 0.15337312 0.58461375 16 sp_14 0.306420867 -0.23808313
-#> 32551 0 0.15337312 0.58461375 1 sp_15 0.306420867 -0.23808313
-#> 32561 0 0.15337312 0.58461375 14 sp_16 0.306420867 -0.23808313
-#> 32571 0 0.15337312 0.58461375 17 sp_17 0.306420867 -0.23808313
-#> 32581 1 0.15337312 0.58461375 7 sp_18 0.306420867 -0.23808313
-#> 32591 0 0.15337312 0.58461375 7 sp_19 0.306420867 -0.23808313
-#> 32601 0 0.15337312 0.58461375 13 sp_20 0.306420867 -0.23808313
-#> 32611 0 0.15337312 0.58461375 15 sp_21 0.306420867 -0.23808313
-#> 32621 0 0.15337312 0.58461375 12 sp_22 0.306420867 -0.23808313
-#> 32631 0 0.15337312 0.58461375 14 sp_23 0.306420867 -0.23808313
-#> 32641 0 0.15337312 0.58461375 19 sp_24 0.306420867 -0.23808313
-#> 32651 0 0.15337312 0.58461375 19 sp_25 0.306420867 -0.23808313
-#> 32661 0 0.15337312 0.58461375 17 sp_26 0.306420867 -0.23808313
-#> 32671 0 0.15337312 0.58461375 9 sp_27 0.306420867 -0.23808313
-#> 32681 0 0.15337312 0.58461375 13 sp_28 0.306420867 -0.23808313
-#> 32691 0 0.15337312 0.58461375 14 sp_29 0.306420867 -0.23808313
-#> 32701 0 0.15337312 0.58461375 6 sp_30 0.306420867 -0.23808313
-#> 33611 0 -1.13813694 0.12385424 1 sp_1 1.205383826 0.60383887
-#> 33621 0 -1.13813694 0.12385424 16 sp_2 1.205383826 0.60383887
-#> 33631 0 -1.13813694 0.12385424 8 sp_3 1.205383826 0.60383887
-#> 33641 0 -1.13813694 0.12385424 5 sp_4 1.205383826 0.60383887
-#> 33651 0 -1.13813694 0.12385424 10 sp_5 1.205383826 0.60383887
-#> 33661 0 -1.13813694 0.12385424 9 sp_6 1.205383826 0.60383887
-#> 33671 0 -1.13813694 0.12385424 5 sp_7 1.205383826 0.60383887
-#> 33681 0 -1.13813694 0.12385424 14 sp_8 1.205383826 0.60383887
-#> 33691 0 -1.13813694 0.12385424 19 sp_9 1.205383826 0.60383887
-#> 33701 0 -1.13813694 0.12385424 1 sp_10 1.205383826 0.60383887
-#> 33711 0 -1.13813694 0.12385424 16 sp_11 1.205383826 0.60383887
-#> 33721 0 -1.13813694 0.12385424 6 sp_12 1.205383826 0.60383887
-#> 33731 0 -1.13813694 0.12385424 20 sp_13 1.205383826 0.60383887
-#> 33741 0 -1.13813694 0.12385424 8 sp_14 1.205383826 0.60383887
-#> 33751 0 -1.13813694 0.12385424 14 sp_15 1.205383826 0.60383887
-#> 33761 0 -1.13813694 0.12385424 14 sp_16 1.205383826 0.60383887
-#> 33771 0 -1.13813694 0.12385424 8 sp_17 1.205383826 0.60383887
-#> 33781 0 -1.13813694 0.12385424 11 sp_18 1.205383826 0.60383887
-#> 33791 1 -1.13813694 0.12385424 20 sp_19 1.205383826 0.60383887
-#> 33801 0 -1.13813694 0.12385424 5 sp_20 1.205383826 0.60383887
-#> 33811 0 -1.13813694 0.12385424 14 sp_21 1.205383826 0.60383887
-#> 33821 0 -1.13813694 0.12385424 1 sp_22 1.205383826 0.60383887
-#> 33831 0 -1.13813694 0.12385424 1 sp_23 1.205383826 0.60383887
-#> 33841 0 -1.13813694 0.12385424 5 sp_24 1.205383826 0.60383887
-#> 33851 0 -1.13813694 0.12385424 3 sp_25 1.205383826 0.60383887
-#> 33861 0 -1.13813694 0.12385424 4 sp_26 1.205383826 0.60383887
-#> 33871 0 -1.13813694 0.12385424 3 sp_27 1.205383826 0.60383887
-#> 33881 0 -1.13813694 0.12385424 14 sp_28 1.205383826 0.60383887
-#> 33891 1 -1.13813694 0.12385424 18 sp_29 1.205383826 0.60383887
-#> 33901 0 -1.13813694 0.12385424 10 sp_30 1.205383826 0.60383887
-#> 34811 1 1.25381492 0.21594157 12 sp_1 -1.002725787 0.52440358
-#> 34821 0 1.25381492 0.21594157 16 sp_2 -1.002725787 0.52440358
-#> 34831 0 1.25381492 0.21594157 3 sp_3 -1.002725787 0.52440358
-#> 34841 0 1.25381492 0.21594157 12 sp_4 -1.002725787 0.52440358
-#> 34851 0 1.25381492 0.21594157 5 sp_5 -1.002725787 0.52440358
-#> 34861 0 1.25381492 0.21594157 13 sp_6 -1.002725787 0.52440358
-#> 34871 0 1.25381492 0.21594157 8 sp_7 -1.002725787 0.52440358
-#> 34881 0 1.25381492 0.21594157 17 sp_8 -1.002725787 0.52440358
-#> 34891 0 1.25381492 0.21594157 5 sp_9 -1.002725787 0.52440358
-#> 34901 0 1.25381492 0.21594157 19 sp_10 -1.002725787 0.52440358
-#> 34911 0 1.25381492 0.21594157 6 sp_11 -1.002725787 0.52440358
-#> 34921 0 1.25381492 0.21594157 2 sp_12 -1.002725787 0.52440358
-#> 34931 0 1.25381492 0.21594157 17 sp_13 -1.002725787 0.52440358
-#> 34941 0 1.25381492 0.21594157 17 sp_14 -1.002725787 0.52440358
-#> 34951 0 1.25381492 0.21594157 8 sp_15 -1.002725787 0.52440358
-#> 34961 0 1.25381492 0.21594157 19 sp_16 -1.002725787 0.52440358
-#> 34971 1 1.25381492 0.21594157 18 sp_17 -1.002725787 0.52440358
-#> 34981 0 1.25381492 0.21594157 19 sp_18 -1.002725787 0.52440358
-#> 34991 0 1.25381492 0.21594157 5 sp_19 -1.002725787 0.52440358
-#> 35001 0 1.25381492 0.21594157 14 sp_20 -1.002725787 0.52440358
-#> 35011 0 1.25381492 0.21594157 12 sp_21 -1.002725787 0.52440358
-#> 35021 0 1.25381492 0.21594157 1 sp_22 -1.002725787 0.52440358
-#> 35031 0 1.25381492 0.21594157 16 sp_23 -1.002725787 0.52440358
-#> 35041 0 1.25381492 0.21594157 18 sp_24 -1.002725787 0.52440358
-#> 35051 0 1.25381492 0.21594157 20 sp_25 -1.002725787 0.52440358
-#> 35061 0 1.25381492 0.21594157 7 sp_26 -1.002725787 0.52440358
-#> 35071 1 1.25381492 0.21594157 5 sp_27 -1.002725787 0.52440358
-#> 35081 0 1.25381492 0.21594157 10 sp_28 -1.002725787 0.52440358
-#> 35091 0 1.25381492 0.21594157 4 sp_29 -1.002725787 0.52440358
-#> 35101 0 1.25381492 0.21594157 8 sp_30 -1.002725787 0.52440358
-#> 112 0 -0.56047565 0.42646422 7 sp_1 -0.892245924 -0.63765962
-#> 212 0 -0.56047565 0.42646422 3 sp_2 -0.892245924 -0.63765962
-#> 32 0 -0.56047565 0.42646422 15 sp_3 -0.892245924 -0.63765962
-#> 42 0 -0.56047565 0.42646422 5 sp_4 -0.892245924 -0.63765962
-#> 52 0 -0.56047565 0.42646422 8 sp_5 -0.892245924 -0.63765962
-#> 62 0 -0.56047565 0.42646422 19 sp_6 -0.892245924 -0.63765962
-#> 72 0 -0.56047565 0.42646422 10 sp_7 -0.892245924 -0.63765962
-#> 82 0 -0.56047565 0.42646422 18 sp_8 -0.892245924 -0.63765962
-#> 92 0 -0.56047565 0.42646422 10 sp_9 -0.892245924 -0.63765962
-#> 102 0 -0.56047565 0.42646422 12 sp_10 -0.892245924 -0.63765962
-#> 113 0 -0.56047565 0.42646422 2 sp_11 -0.892245924 -0.63765962
-#> 1233 0 -0.56047565 0.42646422 10 sp_12 -0.892245924 -0.63765962
-#> 1312 1 -0.56047565 0.42646422 12 sp_13 -0.892245924 -0.63765962
-#> 1412 0 -0.56047565 0.42646422 20 sp_14 -0.892245924 -0.63765962
-#> 152 0 -0.56047565 0.42646422 14 sp_15 -0.892245924 -0.63765962
-#> 162 0 -0.56047565 0.42646422 17 sp_16 -0.892245924 -0.63765962
-#> 172 0 -0.56047565 0.42646422 14 sp_17 -0.892245924 -0.63765962
-#> 182 0 -0.56047565 0.42646422 3 sp_18 -0.892245924 -0.63765962
-#> 192 0 -0.56047565 0.42646422 8 sp_19 -0.892245924 -0.63765962
-#> 202 0 -0.56047565 0.42646422 14 sp_20 -0.892245924 -0.63765962
-#> 213 0 -0.56047565 0.42646422 19 sp_21 -0.892245924 -0.63765962
-#> 222 0 -0.56047565 0.42646422 15 sp_22 -0.892245924 -0.63765962
-#> 232 0 -0.56047565 0.42646422 17 sp_23 -0.892245924 -0.63765962
-#> 2433 0 -0.56047565 0.42646422 11 sp_24 -0.892245924 -0.63765962
-#> 2512 0 -0.56047565 0.42646422 7 sp_25 -0.892245924 -0.63765962
-#> 2612 0 -0.56047565 0.42646422 15 sp_26 -0.892245924 -0.63765962
-#> 272 0 -0.56047565 0.42646422 6 sp_27 -0.892245924 -0.63765962
-#> 282 0 -0.56047565 0.42646422 14 sp_28 -0.892245924 -0.63765962
-#> 292 0 -0.56047565 0.42646422 7 sp_29 -0.892245924 -0.63765962
-#> 302 0 -0.56047565 0.42646422 10 sp_30 -0.892245924 -0.63765962
-#> 12112 0 -0.23017749 -0.29507148 5 sp_1 0.030148911 -0.84353812
-#> 12212 0 -0.23017749 -0.29507148 6 sp_2 0.030148911 -0.84353812
-#> 1234 0 -0.23017749 -0.29507148 16 sp_3 0.030148911 -0.84353812
-#> 1242 0 -0.23017749 -0.29507148 11 sp_4 0.030148911 -0.84353812
-#> 1252 0 -0.23017749 -0.29507148 4 sp_5 0.030148911 -0.84353812
-#> 1262 0 -0.23017749 -0.29507148 12 sp_6 0.030148911 -0.84353812
-#> 1272 1 -0.23017749 -0.29507148 14 sp_7 0.030148911 -0.84353812
-#> 1282 0 -0.23017749 -0.29507148 19 sp_8 0.030148911 -0.84353812
-#> 1292 0 -0.23017749 -0.29507148 7 sp_9 0.030148911 -0.84353812
-#> 1302 0 -0.23017749 -0.29507148 9 sp_10 0.030148911 -0.84353812
-#> 1313 0 -0.23017749 -0.29507148 7 sp_11 0.030148911 -0.84353812
-#> 13212 1 -0.23017749 -0.29507148 2 sp_12 0.030148911 -0.84353812
-#> 13312 0 -0.23017749 -0.29507148 16 sp_13 0.030148911 -0.84353812
-#> 13412 0 -0.23017749 -0.29507148 13 sp_14 0.030148911 -0.84353812
-#> 1352 0 -0.23017749 -0.29507148 19 sp_15 0.030148911 -0.84353812
-#> 1362 1 -0.23017749 -0.29507148 20 sp_16 0.030148911 -0.84353812
-#> 1372 0 -0.23017749 -0.29507148 15 sp_17 0.030148911 -0.84353812
-#> 1382 0 -0.23017749 -0.29507148 7 sp_18 0.030148911 -0.84353812
-#> 1392 0 -0.23017749 -0.29507148 4 sp_19 0.030148911 -0.84353812
-#> 1402 0 -0.23017749 -0.29507148 1 sp_20 0.030148911 -0.84353812
-#> 1413 0 -0.23017749 -0.29507148 8 sp_21 0.030148911 -0.84353812
-#> 1422 1 -0.23017749 -0.29507148 20 sp_22 0.030148911 -0.84353812
-#> 1432 1 -0.23017749 -0.29507148 16 sp_23 0.030148911 -0.84353812
-#> 14412 0 -0.23017749 -0.29507148 11 sp_24 0.030148911 -0.84353812
-#> 14512 0 -0.23017749 -0.29507148 16 sp_25 0.030148911 -0.84353812
-#> 14612 0 -0.23017749 -0.29507148 20 sp_26 0.030148911 -0.84353812
-#> 1472 0 -0.23017749 -0.29507148 8 sp_27 0.030148911 -0.84353812
-#> 1482 0 -0.23017749 -0.29507148 3 sp_28 0.030148911 -0.84353812
-#> 1492 0 -0.23017749 -0.29507148 4 sp_29 0.030148911 -0.84353812
-#> 1502 0 -0.23017749 -0.29507148 20 sp_30 0.030148911 -0.84353812
-#> 24112 0 1.55870831 0.89512566 12 sp_1 -0.421998576 -0.60935167
-#> 24212 1 1.55870831 0.89512566 17 sp_2 -0.421998576 -0.60935167
-#> 2434 0 1.55870831 0.89512566 10 sp_3 -0.421998576 -0.60935167
-#> 2442 1 1.55870831 0.89512566 20 sp_4 -0.421998576 -0.60935167
-#> 2452 1 1.55870831 0.89512566 11 sp_5 -0.421998576 -0.60935167
-#> 2462 1 1.55870831 0.89512566 8 sp_6 -0.421998576 -0.60935167
-#> 2472 1 1.55870831 0.89512566 14 sp_7 -0.421998576 -0.60935167
-#> 2482 0 1.55870831 0.89512566 13 sp_8 -0.421998576 -0.60935167
-#> 2492 1 1.55870831 0.89512566 2 sp_9 -0.421998576 -0.60935167
-#> 2502 0 1.55870831 0.89512566 11 sp_10 -0.421998576 -0.60935167
-#> 2513 0 1.55870831 0.89512566 13 sp_11 -0.421998576 -0.60935167
-#> 25212 1 1.55870831 0.89512566 14 sp_12 -0.421998576 -0.60935167
-#> 25312 0 1.55870831 0.89512566 6 sp_13 -0.421998576 -0.60935167
-#> 25412 0 1.55870831 0.89512566 8 sp_14 -0.421998576 -0.60935167
-#> 2552 1 1.55870831 0.89512566 12 sp_15 -0.421998576 -0.60935167
-#> 2562 0 1.55870831 0.89512566 4 sp_16 -0.421998576 -0.60935167
-#> 2572 0 1.55870831 0.89512566 13 sp_17 -0.421998576 -0.60935167
-#> 2582 0 1.55870831 0.89512566 14 sp_18 -0.421998576 -0.60935167
-#> 2592 0 1.55870831 0.89512566 16 sp_19 -0.421998576 -0.60935167
-#> 2602 0 1.55870831 0.89512566 1 sp_20 -0.421998576 -0.60935167
-#> 2613 0 1.55870831 0.89512566 8 sp_21 -0.421998576 -0.60935167
-#> 2622 0 1.55870831 0.89512566 8 sp_22 -0.421998576 -0.60935167
-#> 2632 0 1.55870831 0.89512566 10 sp_23 -0.421998576 -0.60935167
-#> 26412 0 1.55870831 0.89512566 8 sp_24 -0.421998576 -0.60935167
-#> 26512 0 1.55870831 0.89512566 18 sp_25 -0.421998576 -0.60935167
-#> 26612 0 1.55870831 0.89512566 9 sp_26 -0.421998576 -0.60935167
-#> 2672 1 1.55870831 0.89512566 7 sp_27 -0.421998576 -0.60935167
-#> 2682 0 1.55870831 0.89512566 7 sp_28 -0.421998576 -0.60935167
-#> 2692 1 1.55870831 0.89512566 10 sp_29 -0.421998576 -0.60935167
-#> 2702 0 1.55870831 0.89512566 11 sp_30 -0.421998576 -0.60935167
-#> 3612 0 0.07050839 0.87813349 1 sp_1 -0.247425100 -1.79048626
-#> 3622 0 0.07050839 0.87813349 19 sp_2 -0.247425100 -1.79048626
-#> 3632 0 0.07050839 0.87813349 10 sp_3 -0.247425100 -1.79048626
-#> 3642 0 0.07050839 0.87813349 13 sp_4 -0.247425100 -1.79048626
-#> 3652 1 0.07050839 0.87813349 11 sp_5 -0.247425100 -1.79048626
-#> 3662 0 0.07050839 0.87813349 11 sp_6 -0.247425100 -1.79048626
-#> 3672 0 0.07050839 0.87813349 20 sp_7 -0.247425100 -1.79048626
-#> 3682 0 0.07050839 0.87813349 7 sp_8 -0.247425100 -1.79048626
-#> 3692 0 0.07050839 0.87813349 20 sp_9 -0.247425100 -1.79048626
-#> 3702 0 0.07050839 0.87813349 9 sp_10 -0.247425100 -1.79048626
-#> 3712 0 0.07050839 0.87813349 9 sp_11 -0.247425100 -1.79048626
-#> 3722 0 0.07050839 0.87813349 5 sp_12 -0.247425100 -1.79048626
-#> 3732 1 0.07050839 0.87813349 14 sp_13 -0.247425100 -1.79048626
-#> 3742 0 0.07050839 0.87813349 14 sp_14 -0.247425100 -1.79048626
-#> 3752 0 0.07050839 0.87813349 6 sp_15 -0.247425100 -1.79048626
-#> 3762 0 0.07050839 0.87813349 1 sp_16 -0.247425100 -1.79048626
-#> 3772 0 0.07050839 0.87813349 10 sp_17 -0.247425100 -1.79048626
-#> 3782 1 0.07050839 0.87813349 17 sp_18 -0.247425100 -1.79048626
-#> 3792 1 0.07050839 0.87813349 17 sp_19 -0.247425100 -1.79048626
-#> 3802 0 0.07050839 0.87813349 7 sp_20 -0.247425100 -1.79048626
-#> 3812 0 0.07050839 0.87813349 9 sp_21 -0.247425100 -1.79048626
-#> 3822 0 0.07050839 0.87813349 20 sp_22 -0.247425100 -1.79048626
-#> 3832 0 0.07050839 0.87813349 6 sp_23 -0.247425100 -1.79048626
-#> 3842 0 0.07050839 0.87813349 18 sp_24 -0.247425100 -1.79048626
-#> 3852 0 0.07050839 0.87813349 17 sp_25 -0.247425100 -1.79048626
-#> 3862 0 0.07050839 0.87813349 5 sp_26 -0.247425100 -1.79048626
-#> 3872 1 0.07050839 0.87813349 20 sp_27 -0.247425100 -1.79048626
-#> 3882 0 0.07050839 0.87813349 3 sp_28 -0.247425100 -1.79048626
-#> 3892 0 0.07050839 0.87813349 14 sp_29 -0.247425100 -1.79048626
-#> 3902 0 0.07050839 0.87813349 1 sp_30 -0.247425100 -1.79048626
-#> 4812 1 0.12928774 0.82158108 2 sp_1 0.644151150 -0.23984666
-#> 4822 0 0.12928774 0.82158108 4 sp_2 0.644151150 -0.23984666
-#> 4832 0 0.12928774 0.82158108 10 sp_3 0.644151150 -0.23984666
-#> 4842 0 0.12928774 0.82158108 1 sp_4 0.644151150 -0.23984666
-#> 4852 0 0.12928774 0.82158108 5 sp_5 0.644151150 -0.23984666
-#> 4862 0 0.12928774 0.82158108 8 sp_6 0.644151150 -0.23984666
-#> 4872 0 0.12928774 0.82158108 13 sp_7 0.644151150 -0.23984666
-#> 4882 0 0.12928774 0.82158108 18 sp_8 0.644151150 -0.23984666
-#> 4892 0 0.12928774 0.82158108 10 sp_9 0.644151150 -0.23984666
-#> 4902 0 0.12928774 0.82158108 6 sp_10 0.644151150 -0.23984666
-#> 4912 1 0.12928774 0.82158108 7 sp_11 0.644151150 -0.23984666
-#> 4922 0 0.12928774 0.82158108 9 sp_12 0.644151150 -0.23984666
-#> 4932 0 0.12928774 0.82158108 16 sp_13 0.644151150 -0.23984666
-#> 4942 1 0.12928774 0.82158108 17 sp_14 0.644151150 -0.23984666
-#> 4952 0 0.12928774 0.82158108 13 sp_15 0.644151150 -0.23984666
-#> 4962 0 0.12928774 0.82158108 8 sp_16 0.644151150 -0.23984666
-#> 4972 0 0.12928774 0.82158108 7 sp_17 0.644151150 -0.23984666
-#> 4982 0 0.12928774 0.82158108 20 sp_18 0.644151150 -0.23984666
-#> 4992 0 0.12928774 0.82158108 18 sp_19 0.644151150 -0.23984666
-#> 5002 0 0.12928774 0.82158108 17 sp_20 0.644151150 -0.23984666
-#> 5012 0 0.12928774 0.82158108 1 sp_21 0.644151150 -0.23984666
-#> 5022 0 0.12928774 0.82158108 2 sp_22 0.644151150 -0.23984666
-#> 5032 0 0.12928774 0.82158108 17 sp_23 0.644151150 -0.23984666
-#> 5042 0 0.12928774 0.82158108 2 sp_24 0.644151150 -0.23984666
-#> 5052 0 0.12928774 0.82158108 13 sp_25 0.644151150 -0.23984666
-#> 5062 0 0.12928774 0.82158108 17 sp_26 0.644151150 -0.23984666
-#> 5072 0 0.12928774 0.82158108 3 sp_27 0.644151150 -0.23984666
-#> 5082 0 0.12928774 0.82158108 18 sp_28 0.644151150 -0.23984666
-#> 5092 1 0.12928774 0.82158108 2 sp_29 0.644151150 -0.23984666
-#> 5102 0 0.12928774 0.82158108 5 sp_30 0.644151150 -0.23984666
-#> 6012 0 1.71506499 0.68864025 12 sp_1 0.218513365 1.48442693
-#> 6022 0 1.71506499 0.68864025 13 sp_2 0.218513365 1.48442693
-#> 6032 0 1.71506499 0.68864025 10 sp_3 0.218513365 1.48442693
-#> 6042 1 1.71506499 0.68864025 6 sp_4 0.218513365 1.48442693
-#> 6052 0 1.71506499 0.68864025 10 sp_5 0.218513365 1.48442693
-#> 6062 0 1.71506499 0.68864025 10 sp_6 0.218513365 1.48442693
-#> 6072 0 1.71506499 0.68864025 6 sp_7 0.218513365 1.48442693
-#> 6082 0 1.71506499 0.68864025 16 sp_8 0.218513365 1.48442693
-#> 6092 0 1.71506499 0.68864025 16 sp_9 0.218513365 1.48442693
-#> 6102 0 1.71506499 0.68864025 3 sp_10 0.218513365 1.48442693
-#> 6112 0 1.71506499 0.68864025 4 sp_11 0.218513365 1.48442693
-#> 6122 1 1.71506499 0.68864025 3 sp_12 0.218513365 1.48442693
-#> 6132 0 1.71506499 0.68864025 3 sp_13 0.218513365 1.48442693
-#> 6142 0 1.71506499 0.68864025 16 sp_14 0.218513365 1.48442693
-#> 6152 0 1.71506499 0.68864025 2 sp_15 0.218513365 1.48442693
-#> 6162 0 1.71506499 0.68864025 15 sp_16 0.218513365 1.48442693
-#> 6172 0 1.71506499 0.68864025 3 sp_17 0.218513365 1.48442693
-#> 6182 0 1.71506499 0.68864025 9 sp_18 0.218513365 1.48442693
-#> 6192 0 1.71506499 0.68864025 7 sp_19 0.218513365 1.48442693
-#> 6202 0 1.71506499 0.68864025 9 sp_20 0.218513365 1.48442693
-#> 6212 0 1.71506499 0.68864025 4 sp_21 0.218513365 1.48442693
-#> 6222 0 1.71506499 0.68864025 2 sp_22 0.218513365 1.48442693
-#> 6232 0 1.71506499 0.68864025 12 sp_23 0.218513365 1.48442693
-#> 6242 0 1.71506499 0.68864025 9 sp_24 0.218513365 1.48442693
-#> 6252 0 1.71506499 0.68864025 11 sp_25 0.218513365 1.48442693
-#> 6262 0 1.71506499 0.68864025 7 sp_26 0.218513365 1.48442693
-#> 6272 0 1.71506499 0.68864025 13 sp_27 0.218513365 1.48442693
-#> 6282 1 1.71506499 0.68864025 5 sp_28 0.218513365 1.48442693
-#> 6292 0 1.71506499 0.68864025 11 sp_29 0.218513365 1.48442693
-#> 6302 0 1.71506499 0.68864025 1 sp_30 0.218513365 1.48442693
-#> 7212 0 0.46091621 0.55391765 19 sp_1 1.524904741 0.66138217
-#> 7222 1 0.46091621 0.55391765 12 sp_2 1.524904741 0.66138217
-#> 7232 0 0.46091621 0.55391765 2 sp_3 1.524904741 0.66138217
-#> 7242 0 0.46091621 0.55391765 17 sp_4 1.524904741 0.66138217
-#> 7252 1 0.46091621 0.55391765 12 sp_5 1.524904741 0.66138217
-#> 7262 0 0.46091621 0.55391765 3 sp_6 1.524904741 0.66138217
-#> 7272 0 0.46091621 0.55391765 18 sp_7 1.524904741 0.66138217
-#> 7282 0 0.46091621 0.55391765 15 sp_8 1.524904741 0.66138217
-#> 7292 0 0.46091621 0.55391765 3 sp_9 1.524904741 0.66138217
-#> 7302 0 0.46091621 0.55391765 19 sp_10 1.524904741 0.66138217
-#> 7312 0 0.46091621 0.55391765 18 sp_11 1.524904741 0.66138217
-#> 7322 0 0.46091621 0.55391765 17 sp_12 1.524904741 0.66138217
-#> 7332 0 0.46091621 0.55391765 6 sp_13 1.524904741 0.66138217
-#> 7342 0 0.46091621 0.55391765 10 sp_14 1.524904741 0.66138217
-#> 7352 0 0.46091621 0.55391765 8 sp_15 1.524904741 0.66138217
-#> 7362 0 0.46091621 0.55391765 10 sp_16 1.524904741 0.66138217
-#> 7372 0 0.46091621 0.55391765 13 sp_17 1.524904741 0.66138217
-#> 7382 1 0.46091621 0.55391765 20 sp_18 1.524904741 0.66138217
-#> 7392 0 0.46091621 0.55391765 6 sp_19 1.524904741 0.66138217
-#> 7402 0 0.46091621 0.55391765 20 sp_20 1.524904741 0.66138217
-#> 7412 0 0.46091621 0.55391765 20 sp_21 1.524904741 0.66138217
-#> 7422 0 0.46091621 0.55391765 9 sp_22 1.524904741 0.66138217
-#> 7432 1 0.46091621 0.55391765 16 sp_23 1.524904741 0.66138217
-#> 7442 0 0.46091621 0.55391765 8 sp_24 1.524904741 0.66138217
-#> 7452 0 0.46091621 0.55391765 7 sp_25 1.524904741 0.66138217
-#> 7462 0 0.46091621 0.55391765 10 sp_26 1.524904741 0.66138217
-#> 7472 0 0.46091621 0.55391765 17 sp_27 1.524904741 0.66138217
-#> 7482 0 0.46091621 0.55391765 18 sp_28 1.524904741 0.66138217
-#> 7492 0 0.46091621 0.55391765 8 sp_29 1.524904741 0.66138217
-#> 7502 0 0.46091621 0.55391765 19 sp_30 1.524904741 0.66138217
-#> 8412 1 -1.26506123 -0.06191171 10 sp_1 -1.024046710 -0.81527923
-#> 8422 0 -1.26506123 -0.06191171 11 sp_2 -1.024046710 -0.81527923
-#> 8432 0 -1.26506123 -0.06191171 17 sp_3 -1.024046710 -0.81527923
-#> 8442 0 -1.26506123 -0.06191171 12 sp_4 -1.024046710 -0.81527923
-#> 8452 0 -1.26506123 -0.06191171 2 sp_5 -1.024046710 -0.81527923
-#> 8462 0 -1.26506123 -0.06191171 19 sp_6 -1.024046710 -0.81527923
-#> 8472 0 -1.26506123 -0.06191171 13 sp_7 -1.024046710 -0.81527923
-#> 8482 0 -1.26506123 -0.06191171 13 sp_8 -1.024046710 -0.81527923
-#> 8492 0 -1.26506123 -0.06191171 19 sp_9 -1.024046710 -0.81527923
-#> 8502 1 -1.26506123 -0.06191171 10 sp_10 -1.024046710 -0.81527923
-#> 8512 0 -1.26506123 -0.06191171 16 sp_11 -1.024046710 -0.81527923
-#> 8522 0 -1.26506123 -0.06191171 5 sp_12 -1.024046710 -0.81527923
-#> 8532 0 -1.26506123 -0.06191171 4 sp_13 -1.024046710 -0.81527923
-#> 8542 0 -1.26506123 -0.06191171 18 sp_14 -1.024046710 -0.81527923
-#> 8552 0 -1.26506123 -0.06191171 1 sp_15 -1.024046710 -0.81527923
-#> 8562 0 -1.26506123 -0.06191171 16 sp_16 -1.024046710 -0.81527923
-#> 8572 0 -1.26506123 -0.06191171 17 sp_17 -1.024046710 -0.81527923
-#> 8582 0 -1.26506123 -0.06191171 12 sp_18 -1.024046710 -0.81527923
-#> 8592 1 -1.26506123 -0.06191171 2 sp_19 -1.024046710 -0.81527923
-#> 8602 0 -1.26506123 -0.06191171 18 sp_20 -1.024046710 -0.81527923
-#> 8612 0 -1.26506123 -0.06191171 12 sp_21 -1.024046710 -0.81527923
-#> 8622 0 -1.26506123 -0.06191171 15 sp_22 -1.024046710 -0.81527923
-#> 8632 0 -1.26506123 -0.06191171 19 sp_23 -1.024046710 -0.81527923
-#> 8642 0 -1.26506123 -0.06191171 6 sp_24 -1.024046710 -0.81527923
-#> 8652 0 -1.26506123 -0.06191171 16 sp_25 -1.024046710 -0.81527923
-#> 8662 0 -1.26506123 -0.06191171 15 sp_26 -1.024046710 -0.81527923
-#> 8672 0 -1.26506123 -0.06191171 19 sp_27 -1.024046710 -0.81527923
-#> 8682 0 -1.26506123 -0.06191171 3 sp_28 -1.024046710 -0.81527923
-#> 8692 0 -1.26506123 -0.06191171 14 sp_29 -1.024046710 -0.81527923
-#> 8702 0 -1.26506123 -0.06191171 1 sp_30 -1.024046710 -0.81527923
-#> 9612 0 -0.68685285 -0.30596266 1 sp_1 0.519500645 -0.43573685
-#> 9622 1 -0.68685285 -0.30596266 16 sp_2 0.519500645 -0.43573685
-#> 9632 0 -0.68685285 -0.30596266 11 sp_3 0.519500645 -0.43573685
-#> 9642 0 -0.68685285 -0.30596266 4 sp_4 0.519500645 -0.43573685
-#> 9652 1 -0.68685285 -0.30596266 12 sp_5 0.519500645 -0.43573685
-#> 9662 0 -0.68685285 -0.30596266 13 sp_6 0.519500645 -0.43573685
-#> 9672 0 -0.68685285 -0.30596266 10 sp_7 0.519500645 -0.43573685
-#> 9682 0 -0.68685285 -0.30596266 10 sp_8 0.519500645 -0.43573685
-#> 9692 0 -0.68685285 -0.30596266 7 sp_9 0.519500645 -0.43573685
-#> 9702 0 -0.68685285 -0.30596266 18 sp_10 0.519500645 -0.43573685
-#> 9712 0 -0.68685285 -0.30596266 17 sp_11 0.519500645 -0.43573685
-#> 9722 0 -0.68685285 -0.30596266 20 sp_12 0.519500645 -0.43573685
-#> 9732 0 -0.68685285 -0.30596266 9 sp_13 0.519500645 -0.43573685
-#> 9742 1 -0.68685285 -0.30596266 11 sp_14 0.519500645 -0.43573685
-#> 9752 1 -0.68685285 -0.30596266 12 sp_15 0.519500645 -0.43573685
-#> 9762 0 -0.68685285 -0.30596266 8 sp_16 0.519500645 -0.43573685
-#> 9772 0 -0.68685285 -0.30596266 18 sp_17 0.519500645 -0.43573685
-#> 9782 0 -0.68685285 -0.30596266 5 sp_18 0.519500645 -0.43573685
-#> 9792 0 -0.68685285 -0.30596266 18 sp_19 0.519500645 -0.43573685
-#> 9802 0 -0.68685285 -0.30596266 6 sp_20 0.519500645 -0.43573685
-#> 9812 0 -0.68685285 -0.30596266 10 sp_21 0.519500645 -0.43573685
-#> 9822 0 -0.68685285 -0.30596266 9 sp_22 0.519500645 -0.43573685
-#> 9832 0 -0.68685285 -0.30596266 11 sp_23 0.519500645 -0.43573685
-#> 9842 0 -0.68685285 -0.30596266 6 sp_24 0.519500645 -0.43573685
-#> 9852 0 -0.68685285 -0.30596266 12 sp_25 0.519500645 -0.43573685
-#> 9862 0 -0.68685285 -0.30596266 19 sp_26 0.519500645 -0.43573685
-#> 9872 0 -0.68685285 -0.30596266 4 sp_27 0.519500645 -0.43573685
-#> 9882 0 -0.68685285 -0.30596266 3 sp_28 0.519500645 -0.43573685
-#> 9892 0 -0.68685285 -0.30596266 14 sp_29 0.519500645 -0.43573685
-#> 9902 0 -0.68685285 -0.30596266 8 sp_30 0.519500645 -0.43573685
-#> 10812 0 -0.44566197 -0.38047100 6 sp_1 0.024742072 0.73153658
-#> 10822 0 -0.44566197 -0.38047100 4 sp_2 0.024742072 0.73153658
-#> 10832 0 -0.44566197 -0.38047100 10 sp_3 0.024742072 0.73153658
-#> 10842 0 -0.44566197 -0.38047100 16 sp_4 0.024742072 0.73153658
-#> 10852 0 -0.44566197 -0.38047100 16 sp_5 0.024742072 0.73153658
-#> 10862 0 -0.44566197 -0.38047100 20 sp_6 0.024742072 0.73153658
-#> 10872 1 -0.44566197 -0.38047100 10 sp_7 0.024742072 0.73153658
-#> 10882 0 -0.44566197 -0.38047100 6 sp_8 0.024742072 0.73153658
-#> 10892 0 -0.44566197 -0.38047100 19 sp_9 0.024742072 0.73153658
-#> 10902 0 -0.44566197 -0.38047100 4 sp_10 0.024742072 0.73153658
-#> 10912 0 -0.44566197 -0.38047100 9 sp_11 0.024742072 0.73153658
-#> 10922 0 -0.44566197 -0.38047100 4 sp_12 0.024742072 0.73153658
-#> 10932 0 -0.44566197 -0.38047100 15 sp_13 0.024742072 0.73153658
-#> 10942 0 -0.44566197 -0.38047100 20 sp_14 0.024742072 0.73153658
-#> 10952 1 -0.44566197 -0.38047100 17 sp_15 0.024742072 0.73153658
-#> 10962 0 -0.44566197 -0.38047100 7 sp_16 0.024742072 0.73153658
-#> 10972 0 -0.44566197 -0.38047100 15 sp_17 0.024742072 0.73153658
-#> 10982 0 -0.44566197 -0.38047100 5 sp_18 0.024742072 0.73153658
-#> 10992 1 -0.44566197 -0.38047100 14 sp_19 0.024742072 0.73153658
-#> 11002 0 -0.44566197 -0.38047100 15 sp_20 0.024742072 0.73153658
-#> 11012 0 -0.44566197 -0.38047100 15 sp_21 0.024742072 0.73153658
-#> 11022 0 -0.44566197 -0.38047100 16 sp_22 0.024742072 0.73153658
-#> 11032 0 -0.44566197 -0.38047100 19 sp_23 0.024742072 0.73153658
-#> 11042 0 -0.44566197 -0.38047100 8 sp_24 0.024742072 0.73153658
-#> 11052 0 -0.44566197 -0.38047100 5 sp_25 0.024742072 0.73153658
-#> 11062 0 -0.44566197 -0.38047100 7 sp_26 0.024742072 0.73153658
-#> 11072 1 -0.44566197 -0.38047100 20 sp_27 0.024742072 0.73153658
-#> 11082 0 -0.44566197 -0.38047100 16 sp_28 0.024742072 0.73153658
-#> 11092 0 -0.44566197 -0.38047100 16 sp_29 0.024742072 0.73153658
-#> 11102 0 -0.44566197 -0.38047100 9 sp_30 0.024742072 0.73153658
-#> 12012 0 1.22408180 -0.69470698 11 sp_1 -0.970649504 1.50473579
-#> 12022 0 1.22408180 -0.69470698 11 sp_2 -0.970649504 1.50473579
-#> 12032 0 1.22408180 -0.69470698 19 sp_3 -0.970649504 1.50473579
-#> 12042 0 1.22408180 -0.69470698 10 sp_4 -0.970649504 1.50473579
-#> 12052 0 1.22408180 -0.69470698 2 sp_5 -0.970649504 1.50473579
-#> 12062 0 1.22408180 -0.69470698 6 sp_6 -0.970649504 1.50473579
-#> 12072 0 1.22408180 -0.69470698 20 sp_7 -0.970649504 1.50473579
-#> 12082 0 1.22408180 -0.69470698 14 sp_8 -0.970649504 1.50473579
-#> 12092 0 1.22408180 -0.69470698 14 sp_9 -0.970649504 1.50473579
-#> 12102 0 1.22408180 -0.69470698 6 sp_10 -0.970649504 1.50473579
-#> 12113 0 1.22408180 -0.69470698 18 sp_11 -0.970649504 1.50473579
-#> 12122 0 1.22408180 -0.69470698 2 sp_12 -0.970649504 1.50473579
-#> 12132 1 1.22408180 -0.69470698 8 sp_13 -0.970649504 1.50473579
-#> 12142 0 1.22408180 -0.69470698 11 sp_14 -0.970649504 1.50473579
-#> 12152 0 1.22408180 -0.69470698 7 sp_15 -0.970649504 1.50473579
-#> 12162 0 1.22408180 -0.69470698 19 sp_16 -0.970649504 1.50473579
-#> 12172 0 1.22408180 -0.69470698 8 sp_17 -0.970649504 1.50473579
-#> 12182 0 1.22408180 -0.69470698 10 sp_18 -0.970649504 1.50473579
-#> 12192 0 1.22408180 -0.69470698 5 sp_19 -0.970649504 1.50473579
-#> 12202 0 1.22408180 -0.69470698 17 sp_20 -0.970649504 1.50473579
-#> 12213 0 1.22408180 -0.69470698 6 sp_21 -0.970649504 1.50473579
-#> 12222 0 1.22408180 -0.69470698 8 sp_22 -0.970649504 1.50473579
-#> 12232 0 1.22408180 -0.69470698 20 sp_23 -0.970649504 1.50473579
-#> 12242 0 1.22408180 -0.69470698 6 sp_24 -0.970649504 1.50473579
-#> 12252 0 1.22408180 -0.69470698 15 sp_25 -0.970649504 1.50473579
-#> 12262 0 1.22408180 -0.69470698 17 sp_26 -0.970649504 1.50473579
-#> 12272 1 1.22408180 -0.69470698 3 sp_27 -0.970649504 1.50473579
-#> 12282 0 1.22408180 -0.69470698 15 sp_28 -0.970649504 1.50473579
-#> 12292 0 1.22408180 -0.69470698 20 sp_29 -0.970649504 1.50473579
-#> 12302 0 1.22408180 -0.69470698 1 sp_30 -0.970649504 1.50473579
-#> 13213 0 0.35981383 -0.20791728 5 sp_1 -1.696019564 -0.30971435
-#> 13222 1 0.35981383 -0.20791728 11 sp_2 -1.696019564 -0.30971435
-#> 13232 0 0.35981383 -0.20791728 15 sp_3 -1.696019564 -0.30971435
-#> 13242 0 0.35981383 -0.20791728 20 sp_4 -1.696019564 -0.30971435
-#> 13252 0 0.35981383 -0.20791728 2 sp_5 -1.696019564 -0.30971435
-#> 13262 0 0.35981383 -0.20791728 16 sp_6 -1.696019564 -0.30971435
-#> 13272 0 0.35981383 -0.20791728 19 sp_7 -1.696019564 -0.30971435
-#> 13282 0 0.35981383 -0.20791728 10 sp_8 -1.696019564 -0.30971435
-#> 13292 0 0.35981383 -0.20791728 19 sp_9 -1.696019564 -0.30971435
-#> 13302 0 0.35981383 -0.20791728 17 sp_10 -1.696019564 -0.30971435
-#> 13313 0 0.35981383 -0.20791728 7 sp_11 -1.696019564 -0.30971435
-#> 13322 0 0.35981383 -0.20791728 6 sp_12 -1.696019564 -0.30971435
-#> 13332 0 0.35981383 -0.20791728 12 sp_13 -1.696019564 -0.30971435
-#> 13342 0 0.35981383 -0.20791728 4 sp_14 -1.696019564 -0.30971435
-#> 13352 0 0.35981383 -0.20791728 19 sp_15 -1.696019564 -0.30971435
-#> 13362 0 0.35981383 -0.20791728 2 sp_16 -1.696019564 -0.30971435
-#> 13372 0 0.35981383 -0.20791728 4 sp_17 -1.696019564 -0.30971435
-#> 13382 0 0.35981383 -0.20791728 11 sp_18 -1.696019564 -0.30971435
-#> 13392 1 0.35981383 -0.20791728 1 sp_19 -1.696019564 -0.30971435
-#> 13402 0 0.35981383 -0.20791728 19 sp_20 -1.696019564 -0.30971435
-#> 13413 0 0.35981383 -0.20791728 18 sp_21 -1.696019564 -0.30971435
-#> 13422 0 0.35981383 -0.20791728 16 sp_22 -1.696019564 -0.30971435
-#> 13432 1 0.35981383 -0.20791728 3 sp_23 -1.696019564 -0.30971435
-#> 13442 0 0.35981383 -0.20791728 1 sp_24 -1.696019564 -0.30971435
-#> 13452 0 0.35981383 -0.20791728 2 sp_25 -1.696019564 -0.30971435
-#> 13462 0 0.35981383 -0.20791728 2 sp_26 -1.696019564 -0.30971435
-#> 13472 0 0.35981383 -0.20791728 8 sp_27 -1.696019564 -0.30971435
-#> 13482 1 0.35981383 -0.20791728 20 sp_28 -1.696019564 -0.30971435
-#> 13492 0 0.35981383 -0.20791728 14 sp_29 -1.696019564 -0.30971435
-#> 13502 0 0.35981383 -0.20791728 13 sp_30 -1.696019564 -0.30971435
-#> 14413 0 0.40077145 -1.26539635 7 sp_1 0.662820286 -1.28685391
-#> 14422 0 0.40077145 -1.26539635 8 sp_2 0.662820286 -1.28685391
-#> 14432 1 0.40077145 -1.26539635 3 sp_3 0.662820286 -1.28685391
-#> 14442 0 0.40077145 -1.26539635 16 sp_4 0.662820286 -1.28685391
-#> 14452 1 0.40077145 -1.26539635 1 sp_5 0.662820286 -1.28685391
-#> 14462 1 0.40077145 -1.26539635 12 sp_6 0.662820286 -1.28685391
-#> 14472 0 0.40077145 -1.26539635 18 sp_7 0.662820286 -1.28685391
-#> 14482 1 0.40077145 -1.26539635 14 sp_8 0.662820286 -1.28685391
-#> 14492 1 0.40077145 -1.26539635 8 sp_9 0.662820286 -1.28685391
-#> 14502 1 0.40077145 -1.26539635 5 sp_10 0.662820286 -1.28685391
-#> 14513 1 0.40077145 -1.26539635 17 sp_11 0.662820286 -1.28685391
-#> 14522 1 0.40077145 -1.26539635 11 sp_12 0.662820286 -1.28685391
-#> 14532 1 0.40077145 -1.26539635 4 sp_13 0.662820286 -1.28685391
-#> 14542 1 0.40077145 -1.26539635 13 sp_14 0.662820286 -1.28685391
-#> 14552 1 0.40077145 -1.26539635 8 sp_15 0.662820286 -1.28685391
-#> 14562 0 0.40077145 -1.26539635 15 sp_16 0.662820286 -1.28685391
-#> 14572 0 0.40077145 -1.26539635 4 sp_17 0.662820286 -1.28685391
-#> 14582 0 0.40077145 -1.26539635 13 sp_18 0.662820286 -1.28685391
-#> 14592 0 0.40077145 -1.26539635 3 sp_19 0.662820286 -1.28685391
-#> 14602 1 0.40077145 -1.26539635 7 sp_20 0.662820286 -1.28685391
-#> 14613 1 0.40077145 -1.26539635 1 sp_21 0.662820286 -1.28685391
-#> 14622 0 0.40077145 -1.26539635 6 sp_22 0.662820286 -1.28685391
-#> 14632 1 0.40077145 -1.26539635 13 sp_23 0.662820286 -1.28685391
-#> 14642 0 0.40077145 -1.26539635 17 sp_24 0.662820286 -1.28685391
-#> 14652 0 0.40077145 -1.26539635 6 sp_25 0.662820286 -1.28685391
-#> 14662 1 0.40077145 -1.26539635 10 sp_26 0.662820286 -1.28685391
-#> 14672 0 0.40077145 -1.26539635 13 sp_27 0.662820286 -1.28685391
-#> 14682 0 0.40077145 -1.26539635 6 sp_28 0.662820286 -1.28685391
-#> 14692 1 0.40077145 -1.26539635 9 sp_29 0.662820286 -1.28685391
-#> 14702 0 0.40077145 -1.26539635 8 sp_30 0.662820286 -1.28685391
-#> 15612 0 0.11068272 2.16895597 1 sp_1 -0.082930960 -1.04260743
-#> 15622 0 0.11068272 2.16895597 16 sp_2 -0.082930960 -1.04260743
-#> 15632 0 0.11068272 2.16895597 2 sp_3 -0.082930960 -1.04260743
-#> 15642 0 0.11068272 2.16895597 8 sp_4 -0.082930960 -1.04260743
-#> 15652 0 0.11068272 2.16895597 14 sp_5 -0.082930960 -1.04260743
-#> 15662 0 0.11068272 2.16895597 12 sp_6 -0.082930960 -1.04260743
-#> 15672 0 0.11068272 2.16895597 8 sp_7 -0.082930960 -1.04260743
-#> 15682 0 0.11068272 2.16895597 9 sp_8 -0.082930960 -1.04260743
-#> 15692 0 0.11068272 2.16895597 8 sp_9 -0.082930960 -1.04260743
-#> 15702 0 0.11068272 2.16895597 9 sp_10 -0.082930960 -1.04260743
-#> 15712 0 0.11068272 2.16895597 20 sp_11 -0.082930960 -1.04260743
-#> 15722 0 0.11068272 2.16895597 1 sp_12 -0.082930960 -1.04260743
-#> 15732 0 0.11068272 2.16895597 3 sp_13 -0.082930960 -1.04260743
-#> 15742 0 0.11068272 2.16895597 8 sp_14 -0.082930960 -1.04260743
-#> 15752 0 0.11068272 2.16895597 2 sp_15 -0.082930960 -1.04260743
-#> 15762 0 0.11068272 2.16895597 1 sp_16 -0.082930960 -1.04260743
-#> 15772 0 0.11068272 2.16895597 9 sp_17 -0.082930960 -1.04260743
-#> 15782 0 0.11068272 2.16895597 7 sp_18 -0.082930960 -1.04260743
-#> 15792 0 0.11068272 2.16895597 13 sp_19 -0.082930960 -1.04260743
-#> 15802 0 0.11068272 2.16895597 20 sp_20 -0.082930960 -1.04260743
-#> 15812 0 0.11068272 2.16895597 14 sp_21 -0.082930960 -1.04260743
-#> 15822 0 0.11068272 2.16895597 16 sp_22 -0.082930960 -1.04260743
-#> 15832 0 0.11068272 2.16895597 7 sp_23 -0.082930960 -1.04260743
-#> 15842 0 0.11068272 2.16895597 4 sp_24 -0.082930960 -1.04260743
-#> 15852 0 0.11068272 2.16895597 13 sp_25 -0.082930960 -1.04260743
-#> 15862 0 0.11068272 2.16895597 12 sp_26 -0.082930960 -1.04260743
-#> 15872 0 0.11068272 2.16895597 13 sp_27 -0.082930960 -1.04260743
-#> 15882 0 0.11068272 2.16895597 20 sp_28 -0.082930960 -1.04260743
-#> 15892 0 0.11068272 2.16895597 10 sp_29 -0.082930960 -1.04260743
-#> 15902 0 0.11068272 2.16895597 9 sp_30 -0.082930960 -1.04260743
-#> 16812 0 -0.55584113 1.20796200 12 sp_1 -1.291495828 1.04828678
-#> 16822 0 -0.55584113 1.20796200 8 sp_2 -1.291495828 1.04828678
-#> 16832 0 -0.55584113 1.20796200 7 sp_3 -1.291495828 1.04828678
-#> 16842 0 -0.55584113 1.20796200 15 sp_4 -1.291495828 1.04828678
-#> 16852 0 -0.55584113 1.20796200 19 sp_5 -1.291495828 1.04828678
-#> 16862 0 -0.55584113 1.20796200 17 sp_6 -1.291495828 1.04828678
-#> 16872 0 -0.55584113 1.20796200 11 sp_7 -1.291495828 1.04828678
-#> 16882 0 -0.55584113 1.20796200 7 sp_8 -1.291495828 1.04828678
-#> 16892 0 -0.55584113 1.20796200 19 sp_9 -1.291495828 1.04828678
-#> 16902 0 -0.55584113 1.20796200 3 sp_10 -1.291495828 1.04828678
-#> 16912 0 -0.55584113 1.20796200 6 sp_11 -1.291495828 1.04828678
-#> 16922 0 -0.55584113 1.20796200 7 sp_12 -1.291495828 1.04828678
-#> 16932 0 -0.55584113 1.20796200 4 sp_13 -1.291495828 1.04828678
-#> 16942 1 -0.55584113 1.20796200 10 sp_14 -1.291495828 1.04828678
-#> 16952 0 -0.55584113 1.20796200 17 sp_15 -1.291495828 1.04828678
-#> 16962 0 -0.55584113 1.20796200 16 sp_16 -1.291495828 1.04828678
-#> 16972 0 -0.55584113 1.20796200 8 sp_17 -1.291495828 1.04828678
-#> 16982 0 -0.55584113 1.20796200 3 sp_18 -1.291495828 1.04828678
-#> 16992 0 -0.55584113 1.20796200 12 sp_19 -1.291495828 1.04828678
-#> 17002 0 -0.55584113 1.20796200 14 sp_20 -1.291495828 1.04828678
-#> 17012 0 -0.55584113 1.20796200 5 sp_21 -1.291495828 1.04828678
-#> 17022 0 -0.55584113 1.20796200 14 sp_22 -1.291495828 1.04828678
-#> 17032 0 -0.55584113 1.20796200 6 sp_23 -1.291495828 1.04828678
-#> 17042 0 -0.55584113 1.20796200 9 sp_24 -1.291495828 1.04828678
-#> 17052 0 -0.55584113 1.20796200 1 sp_25 -1.291495828 1.04828678
-#> 17062 0 -0.55584113 1.20796200 20 sp_26 -1.291495828 1.04828678
-#> 17072 0 -0.55584113 1.20796200 14 sp_27 -1.291495828 1.04828678
-#> 17082 0 -0.55584113 1.20796200 19 sp_28 -1.291495828 1.04828678
-#> 17092 0 -0.55584113 1.20796200 5 sp_29 -1.291495828 1.04828678
-#> 17102 0 -0.55584113 1.20796200 2 sp_30 -1.291495828 1.04828678
-#> 18012 0 1.78691314 -1.12310858 1 sp_1 0.292763360 -0.62291708
-#> 18022 1 1.78691314 -1.12310858 20 sp_2 0.292763360 -0.62291708
-#> 18032 1 1.78691314 -1.12310858 4 sp_3 0.292763360 -0.62291708
-#> 18042 1 1.78691314 -1.12310858 11 sp_4 0.292763360 -0.62291708
-#> 18052 1 1.78691314 -1.12310858 5 sp_5 0.292763360 -0.62291708
-#> 18062 0 1.78691314 -1.12310858 4 sp_6 0.292763360 -0.62291708
-#> 18072 1 1.78691314 -1.12310858 19 sp_7 0.292763360 -0.62291708
-#> 18082 0 1.78691314 -1.12310858 3 sp_8 0.292763360 -0.62291708
-#> 18092 0 1.78691314 -1.12310858 1 sp_9 0.292763360 -0.62291708
-#> 18102 1 1.78691314 -1.12310858 7 sp_10 0.292763360 -0.62291708
-#> 18112 1 1.78691314 -1.12310858 5 sp_11 0.292763360 -0.62291708
-#> 18122 1 1.78691314 -1.12310858 9 sp_12 0.292763360 -0.62291708
-#> 18132 1 1.78691314 -1.12310858 17 sp_13 0.292763360 -0.62291708
-#> 18142 1 1.78691314 -1.12310858 5 sp_14 0.292763360 -0.62291708
-#> 18152 1 1.78691314 -1.12310858 12 sp_15 0.292763360 -0.62291708
-#> 18162 1 1.78691314 -1.12310858 2 sp_16 0.292763360 -0.62291708
-#> 18172 1 1.78691314 -1.12310858 18 sp_17 0.292763360 -0.62291708
-#> 18182 1 1.78691314 -1.12310858 4 sp_18 0.292763360 -0.62291708
-#> 18192 1 1.78691314 -1.12310858 10 sp_19 0.292763360 -0.62291708
-#> 18202 0 1.78691314 -1.12310858 15 sp_20 0.292763360 -0.62291708
-#> 18212 1 1.78691314 -1.12310858 8 sp_21 0.292763360 -0.62291708
-#> 18222 1 1.78691314 -1.12310858 1 sp_22 0.292763360 -0.62291708
-#> 18232 1 1.78691314 -1.12310858 11 sp_23 0.292763360 -0.62291708
-#> 18242 1 1.78691314 -1.12310858 5 sp_24 0.292763360 -0.62291708
-#> 18252 1 1.78691314 -1.12310858 11 sp_25 0.292763360 -0.62291708
-#> 18262 1 1.78691314 -1.12310858 15 sp_26 0.292763360 -0.62291708
-#> 18272 0 1.78691314 -1.12310858 15 sp_27 0.292763360 -0.62291708
-#> 18282 1 1.78691314 -1.12310858 10 sp_28 0.292763360 -0.62291708
-#> 18292 0 1.78691314 -1.12310858 15 sp_29 0.292763360 -0.62291708
-#> 18302 1 1.78691314 -1.12310858 15 sp_30 0.292763360 -0.62291708
-#> 19212 1 0.49785048 -0.40288484 20 sp_1 -0.097909392 1.70873840
-#> 19222 1 0.49785048 -0.40288484 12 sp_2 -0.097909392 1.70873840
-#> 19232 0 0.49785048 -0.40288484 9 sp_3 -0.097909392 1.70873840
-#> 19242 0 0.49785048 -0.40288484 4 sp_4 -0.097909392 1.70873840
-#> 19252 0 0.49785048 -0.40288484 3 sp_5 -0.097909392 1.70873840
-#> 19262 0 0.49785048 -0.40288484 7 sp_6 -0.097909392 1.70873840
-#> 19272 0 0.49785048 -0.40288484 4 sp_7 -0.097909392 1.70873840
-#> 19282 0 0.49785048 -0.40288484 8 sp_8 -0.097909392 1.70873840
-#> 19292 0 0.49785048 -0.40288484 5 sp_9 -0.097909392 1.70873840
-#> 19302 0 0.49785048 -0.40288484 6 sp_10 -0.097909392 1.70873840
-#> 19312 0 0.49785048 -0.40288484 4 sp_11 -0.097909392 1.70873840
-#> 19322 1 0.49785048 -0.40288484 3 sp_12 -0.097909392 1.70873840
-#> 19332 0 0.49785048 -0.40288484 11 sp_13 -0.097909392 1.70873840
-#> 19342 0 0.49785048 -0.40288484 10 sp_14 -0.097909392 1.70873840
-#> 19352 0 0.49785048 -0.40288484 5 sp_15 -0.097909392 1.70873840
-#> 19362 0 0.49785048 -0.40288484 11 sp_16 -0.097909392 1.70873840
-#> 19372 0 0.49785048 -0.40288484 10 sp_17 -0.097909392 1.70873840
-#> 19382 0 0.49785048 -0.40288484 15 sp_18 -0.097909392 1.70873840
-#> 19392 0 0.49785048 -0.40288484 19 sp_19 -0.097909392 1.70873840
-#> 19402 0 0.49785048 -0.40288484 10 sp_20 -0.097909392 1.70873840
-#> 19412 0 0.49785048 -0.40288484 13 sp_21 -0.097909392 1.70873840
-#> 19422 0 0.49785048 -0.40288484 3 sp_22 -0.097909392 1.70873840
-#> 19432 0 0.49785048 -0.40288484 18 sp_23 -0.097909392 1.70873840
-#> 19442 0 0.49785048 -0.40288484 10 sp_24 -0.097909392 1.70873840
-#> 19452 0 0.49785048 -0.40288484 8 sp_25 -0.097909392 1.70873840
-#> 19462 1 0.49785048 -0.40288484 12 sp_26 -0.097909392 1.70873840
-#> 19472 0 0.49785048 -0.40288484 10 sp_27 -0.097909392 1.70873840
-#> 19482 0 0.49785048 -0.40288484 7 sp_28 -0.097909392 1.70873840
-#> 19492 0 0.49785048 -0.40288484 7 sp_29 -0.097909392 1.70873840
-#> 19502 0 0.49785048 -0.40288484 6 sp_30 -0.097909392 1.70873840
-#> 20412 0 -1.96661716 -0.46665535 17 sp_1 1.597746035 0.50850841
-#> 20422 0 -1.96661716 -0.46665535 20 sp_2 1.597746035 0.50850841
-#> 20432 0 -1.96661716 -0.46665535 1 sp_3 1.597746035 0.50850841
-#> 20442 0 -1.96661716 -0.46665535 5 sp_4 1.597746035 0.50850841
-#> 20452 0 -1.96661716 -0.46665535 10 sp_5 1.597746035 0.50850841
-#> 20462 0 -1.96661716 -0.46665535 13 sp_6 1.597746035 0.50850841
-#> 20472 1 -1.96661716 -0.46665535 10 sp_7 1.597746035 0.50850841
-#> 20482 0 -1.96661716 -0.46665535 2 sp_8 1.597746035 0.50850841
-#> 20492 0 -1.96661716 -0.46665535 15 sp_9 1.597746035 0.50850841
-#> 20502 0 -1.96661716 -0.46665535 15 sp_10 1.597746035 0.50850841
-#> 20512 0 -1.96661716 -0.46665535 8 sp_11 1.597746035 0.50850841
-#> 20522 0 -1.96661716 -0.46665535 3 sp_12 1.597746035 0.50850841
-#> 20532 0 -1.96661716 -0.46665535 2 sp_13 1.597746035 0.50850841
-#> 20542 0 -1.96661716 -0.46665535 6 sp_14 1.597746035 0.50850841
-#> 20552 0 -1.96661716 -0.46665535 14 sp_15 1.597746035 0.50850841
-#> 20562 0 -1.96661716 -0.46665535 15 sp_16 1.597746035 0.50850841
-#> 20572 0 -1.96661716 -0.46665535 19 sp_17 1.597746035 0.50850841
-#> 20582 0 -1.96661716 -0.46665535 9 sp_18 1.597746035 0.50850841
-#> 20592 0 -1.96661716 -0.46665535 15 sp_19 1.597746035 0.50850841
-#> 20602 0 -1.96661716 -0.46665535 16 sp_20 1.597746035 0.50850841
-#> 20612 0 -1.96661716 -0.46665535 8 sp_21 1.597746035 0.50850841
-#> 20622 0 -1.96661716 -0.46665535 9 sp_22 1.597746035 0.50850841
-#> 20632 0 -1.96661716 -0.46665535 16 sp_23 1.597746035 0.50850841
-#> 20642 0 -1.96661716 -0.46665535 9 sp_24 1.597746035 0.50850841
-#> 20652 0 -1.96661716 -0.46665535 2 sp_25 1.597746035 0.50850841
-#> 20662 0 -1.96661716 -0.46665535 9 sp_26 1.597746035 0.50850841
-#> 20672 0 -1.96661716 -0.46665535 11 sp_27 1.597746035 0.50850841
-#> 20682 0 -1.96661716 -0.46665535 11 sp_28 1.597746035 0.50850841
-#> 20692 0 -1.96661716 -0.46665535 4 sp_29 1.597746035 0.50850841
-#> 20702 0 -1.96661716 -0.46665535 7 sp_30 1.597746035 0.50850841
-#> 21612 0 0.70135590 0.77996512 18 sp_1 -0.925654688 0.27650993
-#> 21622 0 0.70135590 0.77996512 11 sp_2 -0.925654688 0.27650993
-#> 21632 0 0.70135590 0.77996512 1 sp_3 -0.925654688 0.27650993
-#> 21642 0 0.70135590 0.77996512 11 sp_4 -0.925654688 0.27650993
-#> 21652 0 0.70135590 0.77996512 6 sp_5 -0.925654688 0.27650993
-#> 21662 0 0.70135590 0.77996512 10 sp_6 -0.925654688 0.27650993
-#> 21672 0 0.70135590 0.77996512 18 sp_7 -0.925654688 0.27650993
-#> 21682 0 0.70135590 0.77996512 3 sp_8 -0.925654688 0.27650993
-#> 21692 0 0.70135590 0.77996512 3 sp_9 -0.925654688 0.27650993
-#> 21702 1 0.70135590 0.77996512 2 sp_10 -0.925654688 0.27650993
-#> 21712 0 0.70135590 0.77996512 8 sp_11 -0.925654688 0.27650993
-#> 21722 0 0.70135590 0.77996512 13 sp_12 -0.925654688 0.27650993
-#> 21732 0 0.70135590 0.77996512 8 sp_13 -0.925654688 0.27650993
-#> 21742 0 0.70135590 0.77996512 2 sp_14 -0.925654688 0.27650993
-#> 21752 0 0.70135590 0.77996512 6 sp_15 -0.925654688 0.27650993
-#> 21762 0 0.70135590 0.77996512 17 sp_16 -0.925654688 0.27650993
-#> 21772 0 0.70135590 0.77996512 14 sp_17 -0.925654688 0.27650993
-#> 21782 0 0.70135590 0.77996512 7 sp_18 -0.925654688 0.27650993
-#> 21792 0 0.70135590 0.77996512 13 sp_19 -0.925654688 0.27650993
-#> 21802 0 0.70135590 0.77996512 8 sp_20 -0.925654688 0.27650993
-#> 21812 0 0.70135590 0.77996512 6 sp_21 -0.925654688 0.27650993
-#> 21822 0 0.70135590 0.77996512 11 sp_22 -0.925654688 0.27650993
-#> 21832 0 0.70135590 0.77996512 10 sp_23 -0.925654688 0.27650993
-#> 21842 0 0.70135590 0.77996512 17 sp_24 -0.925654688 0.27650993
-#> 21852 0 0.70135590 0.77996512 7 sp_25 -0.925654688 0.27650993
-#> 21862 0 0.70135590 0.77996512 12 sp_26 -0.925654688 0.27650993
-#> 21872 0 0.70135590 0.77996512 19 sp_27 -0.925654688 0.27650993
-#> 21882 0 0.70135590 0.77996512 17 sp_28 -0.925654688 0.27650993
-#> 21892 0 0.70135590 0.77996512 8 sp_29 -0.925654688 0.27650993
-#> 21902 0 0.70135590 0.77996512 15 sp_30 -0.925654688 0.27650993
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-#> 22832 0 -0.47279141 -0.08336907 17 sp_3 0.840684900 1.39791523
-#> 22842 0 -0.47279141 -0.08336907 1 sp_4 0.840684900 1.39791523
-#> 22852 0 -0.47279141 -0.08336907 18 sp_5 0.840684900 1.39791523
-#> 22862 0 -0.47279141 -0.08336907 18 sp_6 0.840684900 1.39791523
-#> 22872 1 -0.47279141 -0.08336907 20 sp_7 0.840684900 1.39791523
-#> 22882 0 -0.47279141 -0.08336907 10 sp_8 0.840684900 1.39791523
-#> 22892 0 -0.47279141 -0.08336907 10 sp_9 0.840684900 1.39791523
-#> 22902 0 -0.47279141 -0.08336907 9 sp_10 0.840684900 1.39791523
-#> 22912 0 -0.47279141 -0.08336907 19 sp_11 0.840684900 1.39791523
-#> 22922 0 -0.47279141 -0.08336907 18 sp_12 0.840684900 1.39791523
-#> 22932 0 -0.47279141 -0.08336907 18 sp_13 0.840684900 1.39791523
-#> 22942 0 -0.47279141 -0.08336907 12 sp_14 0.840684900 1.39791523
-#> 22952 0 -0.47279141 -0.08336907 12 sp_15 0.840684900 1.39791523
-#> 22962 0 -0.47279141 -0.08336907 4 sp_16 0.840684900 1.39791523
-#> 22972 0 -0.47279141 -0.08336907 20 sp_17 0.840684900 1.39791523
-#> 22982 0 -0.47279141 -0.08336907 10 sp_18 0.840684900 1.39791523
-#> 22992 0 -0.47279141 -0.08336907 5 sp_19 0.840684900 1.39791523
-#> 23002 1 -0.47279141 -0.08336907 2 sp_20 0.840684900 1.39791523
-#> 23012 0 -0.47279141 -0.08336907 18 sp_21 0.840684900 1.39791523
-#> 23022 1 -0.47279141 -0.08336907 12 sp_22 0.840684900 1.39791523
-#> 23032 0 -0.47279141 -0.08336907 13 sp_23 0.840684900 1.39791523
-#> 23042 0 -0.47279141 -0.08336907 11 sp_24 0.840684900 1.39791523
-#> 23052 0 -0.47279141 -0.08336907 19 sp_25 0.840684900 1.39791523
-#> 23062 0 -0.47279141 -0.08336907 6 sp_26 0.840684900 1.39791523
-#> 23072 0 -0.47279141 -0.08336907 18 sp_27 0.840684900 1.39791523
-#> 23082 0 -0.47279141 -0.08336907 10 sp_28 0.840684900 1.39791523
-#> 23092 0 -0.47279141 -0.08336907 9 sp_29 0.840684900 1.39791523
-#> 23102 0 -0.47279141 -0.08336907 3 sp_30 0.840684900 1.39791523
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-#> 24032 0 -1.06782371 0.25331851 13 sp_3 -0.641055073 -1.70788764
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-#> 24052 1 -1.06782371 0.25331851 2 sp_5 -0.641055073 -1.70788764
-#> 24062 1 -1.06782371 0.25331851 11 sp_6 -0.641055073 -1.70788764
-#> 24072 0 -1.06782371 0.25331851 16 sp_7 -0.641055073 -1.70788764
-#> 24082 0 -1.06782371 0.25331851 5 sp_8 -0.641055073 -1.70788764
-#> 24092 0 -1.06782371 0.25331851 4 sp_9 -0.641055073 -1.70788764
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-#> 24113 0 -1.06782371 0.25331851 15 sp_11 -0.641055073 -1.70788764
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-#> 24132 0 -1.06782371 0.25331851 7 sp_13 -0.641055073 -1.70788764
-#> 24142 0 -1.06782371 0.25331851 7 sp_14 -0.641055073 -1.70788764
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-#> 24162 0 -1.06782371 0.25331851 18 sp_16 -0.641055073 -1.70788764
-#> 24172 0 -1.06782371 0.25331851 18 sp_17 -0.641055073 -1.70788764
-#> 24182 0 -1.06782371 0.25331851 3 sp_18 -0.641055073 -1.70788764
-#> 24192 0 -1.06782371 0.25331851 8 sp_19 -0.641055073 -1.70788764
-#> 24202 0 -1.06782371 0.25331851 14 sp_20 -0.641055073 -1.70788764
-#> 24213 0 -1.06782371 0.25331851 9 sp_21 -0.641055073 -1.70788764
-#> 24222 0 -1.06782371 0.25331851 15 sp_22 -0.641055073 -1.70788764
-#> 24232 0 -1.06782371 0.25331851 17 sp_23 -0.641055073 -1.70788764
-#> 24242 0 -1.06782371 0.25331851 7 sp_24 -0.641055073 -1.70788764
-#> 24252 0 -1.06782371 0.25331851 8 sp_25 -0.641055073 -1.70788764
-#> 24262 0 -1.06782371 0.25331851 1 sp_26 -0.641055073 -1.70788764
-#> 24272 0 -1.06782371 0.25331851 9 sp_27 -0.641055073 -1.70788764
-#> 24282 0 -1.06782371 0.25331851 3 sp_28 -0.641055073 -1.70788764
-#> 24292 0 -1.06782371 0.25331851 2 sp_29 -0.641055073 -1.70788764
-#> 24302 0 -1.06782371 0.25331851 11 sp_30 -0.641055073 -1.70788764
-#> 25213 0 -0.21797491 -0.02854676 4 sp_1 -1.458915620 1.04822440
-#> 25222 0 -0.21797491 -0.02854676 8 sp_2 -1.458915620 1.04822440
-#> 25232 0 -0.21797491 -0.02854676 20 sp_3 -1.458915620 1.04822440
-#> 25242 0 -0.21797491 -0.02854676 11 sp_4 -1.458915620 1.04822440
-#> 25252 0 -0.21797491 -0.02854676 18 sp_5 -1.458915620 1.04822440
-#> 25262 0 -0.21797491 -0.02854676 14 sp_6 -1.458915620 1.04822440
-#> 25272 0 -0.21797491 -0.02854676 3 sp_7 -1.458915620 1.04822440
-#> 25282 0 -0.21797491 -0.02854676 3 sp_8 -1.458915620 1.04822440
-#> 25292 0 -0.21797491 -0.02854676 14 sp_9 -1.458915620 1.04822440
-#> 25302 0 -0.21797491 -0.02854676 7 sp_10 -1.458915620 1.04822440
-#> 25313 0 -0.21797491 -0.02854676 15 sp_11 -1.458915620 1.04822440
-#> 25322 0 -0.21797491 -0.02854676 8 sp_12 -1.458915620 1.04822440
-#> 25332 0 -0.21797491 -0.02854676 1 sp_13 -1.458915620 1.04822440
-#> 25342 0 -0.21797491 -0.02854676 5 sp_14 -1.458915620 1.04822440
-#> 25352 0 -0.21797491 -0.02854676 17 sp_15 -1.458915620 1.04822440
-#> 25362 0 -0.21797491 -0.02854676 6 sp_16 -1.458915620 1.04822440
-#> 25372 0 -0.21797491 -0.02854676 10 sp_17 -1.458915620 1.04822440
-#> 25382 0 -0.21797491 -0.02854676 12 sp_18 -1.458915620 1.04822440
-#> 25392 0 -0.21797491 -0.02854676 8 sp_19 -1.458915620 1.04822440
-#> 25402 0 -0.21797491 -0.02854676 16 sp_20 -1.458915620 1.04822440
-#> 25413 0 -0.21797491 -0.02854676 7 sp_21 -1.458915620 1.04822440
-#> 25422 0 -0.21797491 -0.02854676 7 sp_22 -1.458915620 1.04822440
-#> 25432 0 -0.21797491 -0.02854676 1 sp_23 -1.458915620 1.04822440
-#> 25442 0 -0.21797491 -0.02854676 11 sp_24 -1.458915620 1.04822440
-#> 25452 0 -0.21797491 -0.02854676 3 sp_25 -1.458915620 1.04822440
-#> 25462 0 -0.21797491 -0.02854676 17 sp_26 -1.458915620 1.04822440
-#> 25472 0 -0.21797491 -0.02854676 20 sp_27 -1.458915620 1.04822440
-#> 25482 0 -0.21797491 -0.02854676 3 sp_28 -1.458915620 1.04822440
-#> 25492 0 -0.21797491 -0.02854676 14 sp_29 -1.458915620 1.04822440
-#> 25502 0 -0.21797491 -0.02854676 5 sp_30 -1.458915620 1.04822440
-#> 26413 0 -1.02600445 -0.04287046 18 sp_1 1.177817761 1.66494265
-#> 26422 0 -1.02600445 -0.04287046 8 sp_2 1.177817761 1.66494265
-#> 26432 0 -1.02600445 -0.04287046 20 sp_3 1.177817761 1.66494265
-#> 26442 0 -1.02600445 -0.04287046 10 sp_4 1.177817761 1.66494265
-#> 26452 0 -1.02600445 -0.04287046 18 sp_5 1.177817761 1.66494265
-#> 26462 0 -1.02600445 -0.04287046 17 sp_6 1.177817761 1.66494265
-#> 26472 0 -1.02600445 -0.04287046 9 sp_7 1.177817761 1.66494265
-#> 26482 0 -1.02600445 -0.04287046 3 sp_8 1.177817761 1.66494265
-#> 26492 0 -1.02600445 -0.04287046 5 sp_9 1.177817761 1.66494265
-#> 26502 0 -1.02600445 -0.04287046 16 sp_10 1.177817761 1.66494265
-#> 26513 0 -1.02600445 -0.04287046 20 sp_11 1.177817761 1.66494265
-#> 26522 0 -1.02600445 -0.04287046 3 sp_12 1.177817761 1.66494265
-#> 26532 0 -1.02600445 -0.04287046 3 sp_13 1.177817761 1.66494265
-#> 26542 0 -1.02600445 -0.04287046 13 sp_14 1.177817761 1.66494265
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-#> 26562 0 -1.02600445 -0.04287046 15 sp_16 1.177817761 1.66494265
-#> 26572 0 -1.02600445 -0.04287046 19 sp_17 1.177817761 1.66494265
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-#> 26592 1 -1.02600445 -0.04287046 12 sp_19 1.177817761 1.66494265
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-#> 26662 0 -1.02600445 -0.04287046 13 sp_26 1.177817761 1.66494265
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-#> 26702 0 -1.02600445 -0.04287046 16 sp_30 1.177817761 1.66494265
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-#> 27702 0 -0.72889123 1.36860228 9 sp_10 -2.279219585 -0.95179699
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-#> 27792 0 -0.72889123 1.36860228 17 sp_19 -2.279219585 -0.95179699
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-#> 27862 0 -0.72889123 1.36860228 15 sp_26 -2.279219585 -0.95179699
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-#> 27892 0 -0.72889123 1.36860228 9 sp_29 -2.279219585 -0.95179699
-#> 27902 0 -0.72889123 1.36860228 9 sp_30 -2.279219585 -0.95179699
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-#> 28842 0 -0.62503927 -0.22577099 6 sp_4 0.272207845 -0.27955386
-#> 28852 0 -0.62503927 -0.22577099 7 sp_5 0.272207845 -0.27955386
-#> 28862 0 -0.62503927 -0.22577099 16 sp_6 0.272207845 -0.27955386
-#> 28872 0 -0.62503927 -0.22577099 16 sp_7 0.272207845 -0.27955386
-#> 28882 0 -0.62503927 -0.22577099 2 sp_8 0.272207845 -0.27955386
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-#> 28902 0 -0.62503927 -0.22577099 14 sp_10 0.272207845 -0.27955386
-#> 28912 0 -0.62503927 -0.22577099 7 sp_11 0.272207845 -0.27955386
-#> 28922 0 -0.62503927 -0.22577099 6 sp_12 0.272207845 -0.27955386
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-#> 28952 0 -0.62503927 -0.22577099 14 sp_15 0.272207845 -0.27955386
-#> 28962 0 -0.62503927 -0.22577099 19 sp_16 0.272207845 -0.27955386
-#> 28972 1 -0.62503927 -0.22577099 14 sp_17 0.272207845 -0.27955386
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-#> 29012 0 -0.62503927 -0.22577099 18 sp_21 0.272207845 -0.27955386
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-#> 29102 0 -0.62503927 -0.22577099 18 sp_30 0.272207845 -0.27955386
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-#> 30032 0 -1.68669331 1.51647060 14 sp_3 0.551074369 0.40090658
-#> 30042 0 -1.68669331 1.51647060 18 sp_4 0.551074369 0.40090658
-#> 30052 0 -1.68669331 1.51647060 12 sp_5 0.551074369 0.40090658
-#> 30062 0 -1.68669331 1.51647060 18 sp_6 0.551074369 0.40090658
-#> 30072 0 -1.68669331 1.51647060 7 sp_7 0.551074369 0.40090658
-#> 30082 0 -1.68669331 1.51647060 4 sp_8 0.551074369 0.40090658
-#> 30092 0 -1.68669331 1.51647060 4 sp_9 0.551074369 0.40090658
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-#> 30132 0 -1.68669331 1.51647060 16 sp_13 0.551074369 0.40090658
-#> 30142 0 -1.68669331 1.51647060 15 sp_14 0.551074369 0.40090658
-#> 30152 0 -1.68669331 1.51647060 11 sp_15 0.551074369 0.40090658
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-#> 30172 0 -1.68669331 1.51647060 5 sp_17 0.551074369 0.40090658
-#> 30182 0 -1.68669331 1.51647060 2 sp_18 0.551074369 0.40090658
-#> 30192 0 -1.68669331 1.51647060 17 sp_19 0.551074369 0.40090658
-#> 30202 0 -1.68669331 1.51647060 5 sp_20 0.551074369 0.40090658
-#> 30212 0 -1.68669331 1.51647060 19 sp_21 0.551074369 0.40090658
-#> 30222 0 -1.68669331 1.51647060 15 sp_22 0.551074369 0.40090658
-#> 30232 0 -1.68669331 1.51647060 19 sp_23 0.551074369 0.40090658
-#> 30242 0 -1.68669331 1.51647060 3 sp_24 0.551074369 0.40090658
-#> 30252 0 -1.68669331 1.51647060 15 sp_25 0.551074369 0.40090658
-#> 30262 0 -1.68669331 1.51647060 3 sp_26 0.551074369 0.40090658
-#> 30272 1 -1.68669331 1.51647060 2 sp_27 0.551074369 0.40090658
-#> 30282 0 -1.68669331 1.51647060 5 sp_28 0.551074369 0.40090658
-#> 30292 0 -1.68669331 1.51647060 5 sp_29 0.551074369 0.40090658
-#> 30302 0 -1.68669331 1.51647060 7 sp_30 0.551074369 0.40090658
-#> 31212 1 0.83778704 -1.54875280 2 sp_1 0.404754544 -1.40022373
-#> 31222 1 0.83778704 -1.54875280 16 sp_2 0.404754544 -1.40022373
-#> 31232 0 0.83778704 -1.54875280 8 sp_3 0.404754544 -1.40022373
-#> 31242 0 0.83778704 -1.54875280 18 sp_4 0.404754544 -1.40022373
-#> 31252 1 0.83778704 -1.54875280 19 sp_5 0.404754544 -1.40022373
-#> 31262 1 0.83778704 -1.54875280 9 sp_6 0.404754544 -1.40022373
-#> 31272 1 0.83778704 -1.54875280 19 sp_7 0.404754544 -1.40022373
-#> 31282 1 0.83778704 -1.54875280 14 sp_8 0.404754544 -1.40022373
-#> 31292 1 0.83778704 -1.54875280 19 sp_9 0.404754544 -1.40022373
-#> 31302 0 0.83778704 -1.54875280 5 sp_10 0.404754544 -1.40022373
-#> 31312 0 0.83778704 -1.54875280 13 sp_11 0.404754544 -1.40022373
-#> 31322 0 0.83778704 -1.54875280 16 sp_12 0.404754544 -1.40022373
-#> 31332 0 0.83778704 -1.54875280 7 sp_13 0.404754544 -1.40022373
-#> 31342 1 0.83778704 -1.54875280 8 sp_14 0.404754544 -1.40022373
-#> 31352 0 0.83778704 -1.54875280 16 sp_15 0.404754544 -1.40022373
-#> 31362 0 0.83778704 -1.54875280 15 sp_16 0.404754544 -1.40022373
-#> 31372 1 0.83778704 -1.54875280 20 sp_17 0.404754544 -1.40022373
-#> 31382 0 0.83778704 -1.54875280 3 sp_18 0.404754544 -1.40022373
-#> 31392 1 0.83778704 -1.54875280 17 sp_19 0.404754544 -1.40022373
-#> 31402 1 0.83778704 -1.54875280 7 sp_20 0.404754544 -1.40022373
-#> 31412 0 0.83778704 -1.54875280 13 sp_21 0.404754544 -1.40022373
-#> 31422 1 0.83778704 -1.54875280 3 sp_22 0.404754544 -1.40022373
-#> 31432 0 0.83778704 -1.54875280 13 sp_23 0.404754544 -1.40022373
-#> 31442 1 0.83778704 -1.54875280 14 sp_24 0.404754544 -1.40022373
-#> 31452 0 0.83778704 -1.54875280 4 sp_25 0.404754544 -1.40022373
-#> 31462 1 0.83778704 -1.54875280 16 sp_26 0.404754544 -1.40022373
-#> 31472 1 0.83778704 -1.54875280 9 sp_27 0.404754544 -1.40022373
-#> 31482 0 0.83778704 -1.54875280 16 sp_28 0.404754544 -1.40022373
-#> 31492 0 0.83778704 -1.54875280 9 sp_29 0.404754544 -1.40022373
-#> 31502 1 0.83778704 -1.54875280 5 sp_30 0.404754544 -1.40022373
-#> 32412 0 0.15337312 0.58461375 14 sp_1 -0.603832898 0.15166108
-#> 32422 0 0.15337312 0.58461375 12 sp_2 -0.603832898 0.15166108
-#> 32432 0 0.15337312 0.58461375 14 sp_3 -0.603832898 0.15166108
-#> 32442 0 0.15337312 0.58461375 13 sp_4 -0.603832898 0.15166108
-#> 32452 1 0.15337312 0.58461375 20 sp_5 -0.603832898 0.15166108
-#> 32462 0 0.15337312 0.58461375 15 sp_6 -0.603832898 0.15166108
-#> 32472 0 0.15337312 0.58461375 8 sp_7 -0.603832898 0.15166108
-#> 32482 0 0.15337312 0.58461375 13 sp_8 -0.603832898 0.15166108
-#> 32492 0 0.15337312 0.58461375 7 sp_9 -0.603832898 0.15166108
-#> 32502 0 0.15337312 0.58461375 5 sp_10 -0.603832898 0.15166108
-#> 32512 0 0.15337312 0.58461375 8 sp_11 -0.603832898 0.15166108
-#> 32522 0 0.15337312 0.58461375 15 sp_12 -0.603832898 0.15166108
-#> 32532 0 0.15337312 0.58461375 14 sp_13 -0.603832898 0.15166108
-#> 32542 1 0.15337312 0.58461375 16 sp_14 -0.603832898 0.15166108
-#> 32552 1 0.15337312 0.58461375 1 sp_15 -0.603832898 0.15166108
-#> 32562 0 0.15337312 0.58461375 14 sp_16 -0.603832898 0.15166108
-#> 32572 0 0.15337312 0.58461375 17 sp_17 -0.603832898 0.15166108
-#> 32582 0 0.15337312 0.58461375 7 sp_18 -0.603832898 0.15166108
-#> 32592 0 0.15337312 0.58461375 7 sp_19 -0.603832898 0.15166108
-#> 32602 0 0.15337312 0.58461375 13 sp_20 -0.603832898 0.15166108
-#> 32612 0 0.15337312 0.58461375 15 sp_21 -0.603832898 0.15166108
-#> 32622 0 0.15337312 0.58461375 12 sp_22 -0.603832898 0.15166108
-#> 32632 0 0.15337312 0.58461375 14 sp_23 -0.603832898 0.15166108
-#> 32642 0 0.15337312 0.58461375 19 sp_24 -0.603832898 0.15166108
-#> 32652 0 0.15337312 0.58461375 19 sp_25 -0.603832898 0.15166108
-#> 32662 0 0.15337312 0.58461375 17 sp_26 -0.603832898 0.15166108
-#> 32672 0 0.15337312 0.58461375 9 sp_27 -0.603832898 0.15166108
-#> 32682 0 0.15337312 0.58461375 13 sp_28 -0.603832898 0.15166108
-#> 32692 0 0.15337312 0.58461375 14 sp_29 -0.603832898 0.15166108
-#> 32702 0 0.15337312 0.58461375 6 sp_30 -0.603832898 0.15166108
-#> 33612 0 -1.13813694 0.12385424 1 sp_1 -0.922031005 -0.57269753
-#> 33622 0 -1.13813694 0.12385424 16 sp_2 -0.922031005 -0.57269753
-#> 33632 0 -1.13813694 0.12385424 8 sp_3 -0.922031005 -0.57269753
-#> 33642 0 -1.13813694 0.12385424 5 sp_4 -0.922031005 -0.57269753
-#> 33652 0 -1.13813694 0.12385424 10 sp_5 -0.922031005 -0.57269753
-#> 33662 0 -1.13813694 0.12385424 9 sp_6 -0.922031005 -0.57269753
-#> 33672 0 -1.13813694 0.12385424 5 sp_7 -0.922031005 -0.57269753
-#> 33682 0 -1.13813694 0.12385424 14 sp_8 -0.922031005 -0.57269753
-#> 33692 0 -1.13813694 0.12385424 19 sp_9 -0.922031005 -0.57269753
-#> 33702 0 -1.13813694 0.12385424 1 sp_10 -0.922031005 -0.57269753
-#> 33712 0 -1.13813694 0.12385424 16 sp_11 -0.922031005 -0.57269753
-#> 33722 0 -1.13813694 0.12385424 6 sp_12 -0.922031005 -0.57269753
-#> 33732 0 -1.13813694 0.12385424 20 sp_13 -0.922031005 -0.57269753
-#> 33742 0 -1.13813694 0.12385424 8 sp_14 -0.922031005 -0.57269753
-#> 33752 0 -1.13813694 0.12385424 14 sp_15 -0.922031005 -0.57269753
-#> 33762 0 -1.13813694 0.12385424 14 sp_16 -0.922031005 -0.57269753
-#> 33772 0 -1.13813694 0.12385424 8 sp_17 -0.922031005 -0.57269753
-#> 33782 0 -1.13813694 0.12385424 11 sp_18 -0.922031005 -0.57269753
-#> 33792 0 -1.13813694 0.12385424 20 sp_19 -0.922031005 -0.57269753
-#> 33802 0 -1.13813694 0.12385424 5 sp_20 -0.922031005 -0.57269753
-#> 33812 0 -1.13813694 0.12385424 14 sp_21 -0.922031005 -0.57269753
-#> 33822 0 -1.13813694 0.12385424 1 sp_22 -0.922031005 -0.57269753
-#> 33832 0 -1.13813694 0.12385424 1 sp_23 -0.922031005 -0.57269753
-#> 33842 0 -1.13813694 0.12385424 5 sp_24 -0.922031005 -0.57269753
-#> 33852 0 -1.13813694 0.12385424 3 sp_25 -0.922031005 -0.57269753
-#> 33862 0 -1.13813694 0.12385424 4 sp_26 -0.922031005 -0.57269753
-#> 33872 0 -1.13813694 0.12385424 3 sp_27 -0.922031005 -0.57269753
-#> 33882 0 -1.13813694 0.12385424 14 sp_28 -0.922031005 -0.57269753
-#> 33892 1 -1.13813694 0.12385424 18 sp_29 -0.922031005 -0.57269753
-#> 33902 0 -1.13813694 0.12385424 10 sp_30 -0.922031005 -0.57269753
-#> 34812 1 1.25381492 0.21594157 12 sp_1 0.479910722 0.32978651
-#> 34822 0 1.25381492 0.21594157 16 sp_2 0.479910722 0.32978651
-#> 34832 0 1.25381492 0.21594157 3 sp_3 0.479910722 0.32978651
-#> 34842 0 1.25381492 0.21594157 12 sp_4 0.479910722 0.32978651
-#> 34852 0 1.25381492 0.21594157 5 sp_5 0.479910722 0.32978651
-#> 34862 0 1.25381492 0.21594157 13 sp_6 0.479910722 0.32978651
-#> 34872 0 1.25381492 0.21594157 8 sp_7 0.479910722 0.32978651
-#> 34882 1 1.25381492 0.21594157 17 sp_8 0.479910722 0.32978651
-#> 34892 1 1.25381492 0.21594157 5 sp_9 0.479910722 0.32978651
-#> 34902 0 1.25381492 0.21594157 19 sp_10 0.479910722 0.32978651
-#> 34912 0 1.25381492 0.21594157 6 sp_11 0.479910722 0.32978651
-#> 34922 0 1.25381492 0.21594157 2 sp_12 0.479910722 0.32978651
-#> 34932 0 1.25381492 0.21594157 17 sp_13 0.479910722 0.32978651
-#> 34942 1 1.25381492 0.21594157 17 sp_14 0.479910722 0.32978651
-#> 34952 1 1.25381492 0.21594157 8 sp_15 0.479910722 0.32978651
-#> 34962 0 1.25381492 0.21594157 19 sp_16 0.479910722 0.32978651
-#> 34972 1 1.25381492 0.21594157 18 sp_17 0.479910722 0.32978651
-#> 34982 0 1.25381492 0.21594157 19 sp_18 0.479910722 0.32978651
-#> 34992 0 1.25381492 0.21594157 5 sp_19 0.479910722 0.32978651
-#> 35002 0 1.25381492 0.21594157 14 sp_20 0.479910722 0.32978651
-#> 35012 1 1.25381492 0.21594157 12 sp_21 0.479910722 0.32978651
-#> 35022 0 1.25381492 0.21594157 1 sp_22 0.479910722 0.32978651
-#> 35032 1 1.25381492 0.21594157 16 sp_23 0.479910722 0.32978651
-#> 35042 0 1.25381492 0.21594157 18 sp_24 0.479910722 0.32978651
-#> 35052 0 1.25381492 0.21594157 20 sp_25 0.479910722 0.32978651
-#> 35062 0 1.25381492 0.21594157 7 sp_26 0.479910722 0.32978651
-#> 35072 1 1.25381492 0.21594157 5 sp_27 0.479910722 0.32978651
-#> 35082 0 1.25381492 0.21594157 10 sp_28 0.479910722 0.32978651
-#> 35092 0 1.25381492 0.21594157 4 sp_29 0.479910722 0.32978651
-#> 35102 0 1.25381492 0.21594157 8 sp_30 0.479910722 0.32978651
-#> 114 0 -0.56047565 0.42646422 7 sp_1 0.105881568 -0.26338952
-#> 214 0 -0.56047565 0.42646422 3 sp_2 0.105881568 -0.26338952
-#> 33 0 -0.56047565 0.42646422 15 sp_3 0.105881568 -0.26338952
-#> 43 0 -0.56047565 0.42646422 5 sp_4 0.105881568 -0.26338952
-#> 53 0 -0.56047565 0.42646422 8 sp_5 0.105881568 -0.26338952
-#> 63 0 -0.56047565 0.42646422 19 sp_6 0.105881568 -0.26338952
-#> 73 0 -0.56047565 0.42646422 10 sp_7 0.105881568 -0.26338952
-#> 83 0 -0.56047565 0.42646422 18 sp_8 0.105881568 -0.26338952
-#> 93 0 -0.56047565 0.42646422 10 sp_9 0.105881568 -0.26338952
-#> 103 0 -0.56047565 0.42646422 12 sp_10 0.105881568 -0.26338952
-#> 115 0 -0.56047565 0.42646422 2 sp_11 0.105881568 -0.26338952
-#> 1235 0 -0.56047565 0.42646422 10 sp_12 0.105881568 -0.26338952
-#> 1314 0 -0.56047565 0.42646422 12 sp_13 0.105881568 -0.26338952
-#> 1414 0 -0.56047565 0.42646422 20 sp_14 0.105881568 -0.26338952
-#> 153 0 -0.56047565 0.42646422 14 sp_15 0.105881568 -0.26338952
-#> 163 0 -0.56047565 0.42646422 17 sp_16 0.105881568 -0.26338952
-#> 173 0 -0.56047565 0.42646422 14 sp_17 0.105881568 -0.26338952
-#> 183 0 -0.56047565 0.42646422 3 sp_18 0.105881568 -0.26338952
-#> 193 0 -0.56047565 0.42646422 8 sp_19 0.105881568 -0.26338952
-#> 203 0 -0.56047565 0.42646422 14 sp_20 0.105881568 -0.26338952
-#> 215 0 -0.56047565 0.42646422 19 sp_21 0.105881568 -0.26338952
-#> 223 0 -0.56047565 0.42646422 15 sp_22 0.105881568 -0.26338952
-#> 233 0 -0.56047565 0.42646422 17 sp_23 0.105881568 -0.26338952
-#> 2435 0 -0.56047565 0.42646422 11 sp_24 0.105881568 -0.26338952
-#> 2514 0 -0.56047565 0.42646422 7 sp_25 0.105881568 -0.26338952
-#> 2614 0 -0.56047565 0.42646422 15 sp_26 0.105881568 -0.26338952
-#> 273 1 -0.56047565 0.42646422 6 sp_27 0.105881568 -0.26338952
-#> 283 0 -0.56047565 0.42646422 14 sp_28 0.105881568 -0.26338952
-#> 293 0 -0.56047565 0.42646422 7 sp_29 0.105881568 -0.26338952
-#> 303 0 -0.56047565 0.42646422 10 sp_30 0.105881568 -0.26338952
-#> 12114 0 -0.23017749 -0.29507148 5 sp_1 -1.140377953 0.61794489
-#> 12214 0 -0.23017749 -0.29507148 6 sp_2 -1.140377953 0.61794489
-#> 1236 0 -0.23017749 -0.29507148 16 sp_3 -1.140377953 0.61794489
-#> 1243 0 -0.23017749 -0.29507148 11 sp_4 -1.140377953 0.61794489
-#> 1253 0 -0.23017749 -0.29507148 4 sp_5 -1.140377953 0.61794489
-#> 1263 0 -0.23017749 -0.29507148 12 sp_6 -1.140377953 0.61794489
-#> 1273 0 -0.23017749 -0.29507148 14 sp_7 -1.140377953 0.61794489
-#> 1283 0 -0.23017749 -0.29507148 19 sp_8 -1.140377953 0.61794489
-#> 1293 0 -0.23017749 -0.29507148 7 sp_9 -1.140377953 0.61794489
-#> 1303 0 -0.23017749 -0.29507148 9 sp_10 -1.140377953 0.61794489
-#> 1315 0 -0.23017749 -0.29507148 7 sp_11 -1.140377953 0.61794489
-#> 13214 0 -0.23017749 -0.29507148 2 sp_12 -1.140377953 0.61794489
-#> 13314 0 -0.23017749 -0.29507148 16 sp_13 -1.140377953 0.61794489
-#> 13414 0 -0.23017749 -0.29507148 13 sp_14 -1.140377953 0.61794489
-#> 1353 0 -0.23017749 -0.29507148 19 sp_15 -1.140377953 0.61794489
-#> 1363 0 -0.23017749 -0.29507148 20 sp_16 -1.140377953 0.61794489
-#> 1373 0 -0.23017749 -0.29507148 15 sp_17 -1.140377953 0.61794489
-#> 1383 1 -0.23017749 -0.29507148 7 sp_18 -1.140377953 0.61794489
-#> 1393 0 -0.23017749 -0.29507148 4 sp_19 -1.140377953 0.61794489
-#> 1403 0 -0.23017749 -0.29507148 1 sp_20 -1.140377953 0.61794489
-#> 1415 0 -0.23017749 -0.29507148 8 sp_21 -1.140377953 0.61794489
-#> 1423 1 -0.23017749 -0.29507148 20 sp_22 -1.140377953 0.61794489
-#> 1433 0 -0.23017749 -0.29507148 16 sp_23 -1.140377953 0.61794489
-#> 14414 0 -0.23017749 -0.29507148 11 sp_24 -1.140377953 0.61794489
-#> 14514 0 -0.23017749 -0.29507148 16 sp_25 -1.140377953 0.61794489
-#> 14614 0 -0.23017749 -0.29507148 20 sp_26 -1.140377953 0.61794489
-#> 1473 0 -0.23017749 -0.29507148 8 sp_27 -1.140377953 0.61794489
-#> 1483 0 -0.23017749 -0.29507148 3 sp_28 -1.140377953 0.61794489
-#> 1493 0 -0.23017749 -0.29507148 4 sp_29 -1.140377953 0.61794489
-#> 1503 0 -0.23017749 -0.29507148 20 sp_30 -1.140377953 0.61794489
-#> 24114 0 1.55870831 0.89512566 12 sp_1 -0.971485822 -0.16289598
-#> 24214 1 1.55870831 0.89512566 17 sp_2 -0.971485822 -0.16289598
-#> 2436 0 1.55870831 0.89512566 10 sp_3 -0.971485822 -0.16289598
-#> 2443 0 1.55870831 0.89512566 20 sp_4 -0.971485822 -0.16289598
-#> 2453 1 1.55870831 0.89512566 11 sp_5 -0.971485822 -0.16289598
-#> 2463 0 1.55870831 0.89512566 8 sp_6 -0.971485822 -0.16289598
-#> 2473 1 1.55870831 0.89512566 14 sp_7 -0.971485822 -0.16289598
-#> 2483 0 1.55870831 0.89512566 13 sp_8 -0.971485822 -0.16289598
-#> 2493 0 1.55870831 0.89512566 2 sp_9 -0.971485822 -0.16289598
-#> 2503 0 1.55870831 0.89512566 11 sp_10 -0.971485822 -0.16289598
-#> 2515 0 1.55870831 0.89512566 13 sp_11 -0.971485822 -0.16289598
-#> 25214 0 1.55870831 0.89512566 14 sp_12 -0.971485822 -0.16289598
-#> 25314 0 1.55870831 0.89512566 6 sp_13 -0.971485822 -0.16289598
-#> 25414 0 1.55870831 0.89512566 8 sp_14 -0.971485822 -0.16289598
-#> 2553 1 1.55870831 0.89512566 12 sp_15 -0.971485822 -0.16289598
-#> 2563 0 1.55870831 0.89512566 4 sp_16 -0.971485822 -0.16289598
-#> 2573 0 1.55870831 0.89512566 13 sp_17 -0.971485822 -0.16289598
-#> 2583 0 1.55870831 0.89512566 14 sp_18 -0.971485822 -0.16289598
-#> 2593 0 1.55870831 0.89512566 16 sp_19 -0.971485822 -0.16289598
-#> 2603 0 1.55870831 0.89512566 1 sp_20 -0.971485822 -0.16289598
-#> 2615 1 1.55870831 0.89512566 8 sp_21 -0.971485822 -0.16289598
-#> 2623 0 1.55870831 0.89512566 8 sp_22 -0.971485822 -0.16289598
-#> 2633 0 1.55870831 0.89512566 10 sp_23 -0.971485822 -0.16289598
-#> 26414 0 1.55870831 0.89512566 8 sp_24 -0.971485822 -0.16289598
-#> 26514 0 1.55870831 0.89512566 18 sp_25 -0.971485822 -0.16289598
-#> 26614 0 1.55870831 0.89512566 9 sp_26 -0.971485822 -0.16289598
-#> 2673 0 1.55870831 0.89512566 7 sp_27 -0.971485822 -0.16289598
-#> 2683 0 1.55870831 0.89512566 7 sp_28 -0.971485822 -0.16289598
-#> 2693 0 1.55870831 0.89512566 10 sp_29 -0.971485822 -0.16289598
-#> 2703 1 1.55870831 0.89512566 11 sp_30 -0.971485822 -0.16289598
-#> 3613 0 0.07050839 0.87813349 1 sp_1 -1.069651815 -0.50832407
-#> 3623 0 0.07050839 0.87813349 19 sp_2 -1.069651815 -0.50832407
-#> 3633 0 0.07050839 0.87813349 10 sp_3 -1.069651815 -0.50832407
-#> 3643 0 0.07050839 0.87813349 13 sp_4 -1.069651815 -0.50832407
-#> 3653 1 0.07050839 0.87813349 11 sp_5 -1.069651815 -0.50832407
-#> 3663 0 0.07050839 0.87813349 11 sp_6 -1.069651815 -0.50832407
-#> 3673 0 0.07050839 0.87813349 20 sp_7 -1.069651815 -0.50832407
-#> 3683 0 0.07050839 0.87813349 7 sp_8 -1.069651815 -0.50832407
-#> 3693 0 0.07050839 0.87813349 20 sp_9 -1.069651815 -0.50832407
-#> 3703 0 0.07050839 0.87813349 9 sp_10 -1.069651815 -0.50832407
-#> 3713 0 0.07050839 0.87813349 9 sp_11 -1.069651815 -0.50832407
-#> 3723 0 0.07050839 0.87813349 5 sp_12 -1.069651815 -0.50832407
-#> 3733 1 0.07050839 0.87813349 14 sp_13 -1.069651815 -0.50832407
-#> 3743 0 0.07050839 0.87813349 14 sp_14 -1.069651815 -0.50832407
-#> 3753 0 0.07050839 0.87813349 6 sp_15 -1.069651815 -0.50832407
-#> 3763 0 0.07050839 0.87813349 1 sp_16 -1.069651815 -0.50832407
-#> 3773 1 0.07050839 0.87813349 10 sp_17 -1.069651815 -0.50832407
-#> 3783 1 0.07050839 0.87813349 17 sp_18 -1.069651815 -0.50832407
-#> 3793 0 0.07050839 0.87813349 17 sp_19 -1.069651815 -0.50832407
-#> 3803 0 0.07050839 0.87813349 7 sp_20 -1.069651815 -0.50832407
-#> 3813 0 0.07050839 0.87813349 9 sp_21 -1.069651815 -0.50832407
-#> 3823 0 0.07050839 0.87813349 20 sp_22 -1.069651815 -0.50832407
-#> 3833 0 0.07050839 0.87813349 6 sp_23 -1.069651815 -0.50832407
-#> 3843 0 0.07050839 0.87813349 18 sp_24 -1.069651815 -0.50832407
-#> 3853 0 0.07050839 0.87813349 17 sp_25 -1.069651815 -0.50832407
-#> 3863 0 0.07050839 0.87813349 5 sp_26 -1.069651815 -0.50832407
-#> 3873 1 0.07050839 0.87813349 20 sp_27 -1.069651815 -0.50832407
-#> 3883 0 0.07050839 0.87813349 3 sp_28 -1.069651815 -0.50832407
-#> 3893 0 0.07050839 0.87813349 14 sp_29 -1.069651815 -0.50832407
-#> 3903 0 0.07050839 0.87813349 1 sp_30 -1.069651815 -0.50832407
-#> 4813 0 0.12928774 0.82158108 2 sp_1 -1.902177022 0.33140152
-#> 4823 0 0.12928774 0.82158108 4 sp_2 -1.902177022 0.33140152
-#> 4833 0 0.12928774 0.82158108 10 sp_3 -1.902177022 0.33140152
-#> 4843 0 0.12928774 0.82158108 1 sp_4 -1.902177022 0.33140152
-#> 4853 0 0.12928774 0.82158108 5 sp_5 -1.902177022 0.33140152
-#> 4863 0 0.12928774 0.82158108 8 sp_6 -1.902177022 0.33140152
-#> 4873 0 0.12928774 0.82158108 13 sp_7 -1.902177022 0.33140152
-#> 4883 0 0.12928774 0.82158108 18 sp_8 -1.902177022 0.33140152
-#> 4893 0 0.12928774 0.82158108 10 sp_9 -1.902177022 0.33140152
-#> 4903 0 0.12928774 0.82158108 6 sp_10 -1.902177022 0.33140152
-#> 4913 0 0.12928774 0.82158108 7 sp_11 -1.902177022 0.33140152
-#> 4923 0 0.12928774 0.82158108 9 sp_12 -1.902177022 0.33140152
-#> 4933 0 0.12928774 0.82158108 16 sp_13 -1.902177022 0.33140152
-#> 4943 1 0.12928774 0.82158108 17 sp_14 -1.902177022 0.33140152
-#> 4953 0 0.12928774 0.82158108 13 sp_15 -1.902177022 0.33140152
-#> 4963 0 0.12928774 0.82158108 8 sp_16 -1.902177022 0.33140152
-#> 4973 0 0.12928774 0.82158108 7 sp_17 -1.902177022 0.33140152
-#> 4983 0 0.12928774 0.82158108 20 sp_18 -1.902177022 0.33140152
-#> 4993 0 0.12928774 0.82158108 18 sp_19 -1.902177022 0.33140152
-#> 5003 0 0.12928774 0.82158108 17 sp_20 -1.902177022 0.33140152
-#> 5013 0 0.12928774 0.82158108 1 sp_21 -1.902177022 0.33140152
-#> 5023 0 0.12928774 0.82158108 2 sp_22 -1.902177022 0.33140152
-#> 5033 0 0.12928774 0.82158108 17 sp_23 -1.902177022 0.33140152
-#> 5043 0 0.12928774 0.82158108 2 sp_24 -1.902177022 0.33140152
-#> 5053 0 0.12928774 0.82158108 13 sp_25 -1.902177022 0.33140152
-#> 5063 0 0.12928774 0.82158108 17 sp_26 -1.902177022 0.33140152
-#> 5073 0 0.12928774 0.82158108 3 sp_27 -1.902177022 0.33140152
-#> 5083 0 0.12928774 0.82158108 18 sp_28 -1.902177022 0.33140152
-#> 5093 0 0.12928774 0.82158108 2 sp_29 -1.902177022 0.33140152
-#> 5103 0 0.12928774 0.82158108 5 sp_30 -1.902177022 0.33140152
-#> 6013 1 1.71506499 0.68864025 12 sp_1 1.053866739 0.57437773
-#> 6023 0 1.71506499 0.68864025 13 sp_2 1.053866739 0.57437773
-#> 6033 0 1.71506499 0.68864025 10 sp_3 1.053866739 0.57437773
-#> 6043 1 1.71506499 0.68864025 6 sp_4 1.053866739 0.57437773
-#> 6053 0 1.71506499 0.68864025 10 sp_5 1.053866739 0.57437773
-#> 6063 0 1.71506499 0.68864025 10 sp_6 1.053866739 0.57437773
-#> 6073 0 1.71506499 0.68864025 6 sp_7 1.053866739 0.57437773
-#> 6083 0 1.71506499 0.68864025 16 sp_8 1.053866739 0.57437773
-#> 6093 0 1.71506499 0.68864025 16 sp_9 1.053866739 0.57437773
-#> 6103 0 1.71506499 0.68864025 3 sp_10 1.053866739 0.57437773
-#> 6113 0 1.71506499 0.68864025 4 sp_11 1.053866739 0.57437773
-#> 6123 1 1.71506499 0.68864025 3 sp_12 1.053866739 0.57437773
-#> 6133 0 1.71506499 0.68864025 3 sp_13 1.053866739 0.57437773
-#> 6143 0 1.71506499 0.68864025 16 sp_14 1.053866739 0.57437773
-#> 6153 0 1.71506499 0.68864025 2 sp_15 1.053866739 0.57437773
-#> 6163 0 1.71506499 0.68864025 15 sp_16 1.053866739 0.57437773
-#> 6173 0 1.71506499 0.68864025 3 sp_17 1.053866739 0.57437773
-#> 6183 0 1.71506499 0.68864025 9 sp_18 1.053866739 0.57437773
-#> 6193 0 1.71506499 0.68864025 7 sp_19 1.053866739 0.57437773
-#> 6203 0 1.71506499 0.68864025 9 sp_20 1.053866739 0.57437773
-#> 6213 0 1.71506499 0.68864025 4 sp_21 1.053866739 0.57437773
-#> 6223 1 1.71506499 0.68864025 2 sp_22 1.053866739 0.57437773
-#> 6233 0 1.71506499 0.68864025 12 sp_23 1.053866739 0.57437773
-#> 6243 0 1.71506499 0.68864025 9 sp_24 1.053866739 0.57437773
-#> 6253 0 1.71506499 0.68864025 11 sp_25 1.053866739 0.57437773
-#> 6263 0 1.71506499 0.68864025 7 sp_26 1.053866739 0.57437773
-#> 6273 0 1.71506499 0.68864025 13 sp_27 1.053866739 0.57437773
-#> 6283 1 1.71506499 0.68864025 5 sp_28 1.053866739 0.57437773
-#> 6293 0 1.71506499 0.68864025 11 sp_29 1.053866739 0.57437773
-#> 6303 0 1.71506499 0.68864025 1 sp_30 1.053866739 0.57437773
-#> 7213 0 0.46091621 0.55391765 19 sp_1 -0.139730368 0.53331433
-#> 7223 0 0.46091621 0.55391765 12 sp_2 -0.139730368 0.53331433
-#> 7233 0 0.46091621 0.55391765 2 sp_3 -0.139730368 0.53331433
-#> 7243 1 0.46091621 0.55391765 17 sp_4 -0.139730368 0.53331433
-#> 7253 1 0.46091621 0.55391765 12 sp_5 -0.139730368 0.53331433
-#> 7263 0 0.46091621 0.55391765 3 sp_6 -0.139730368 0.53331433
-#> 7273 0 0.46091621 0.55391765 18 sp_7 -0.139730368 0.53331433
-#> 7283 0 0.46091621 0.55391765 15 sp_8 -0.139730368 0.53331433
-#> 7293 0 0.46091621 0.55391765 3 sp_9 -0.139730368 0.53331433
-#> 7303 0 0.46091621 0.55391765 19 sp_10 -0.139730368 0.53331433
-#> 7313 0 0.46091621 0.55391765 18 sp_11 -0.139730368 0.53331433
-#> 7323 0 0.46091621 0.55391765 17 sp_12 -0.139730368 0.53331433
-#> 7333 0 0.46091621 0.55391765 6 sp_13 -0.139730368 0.53331433
-#> 7343 0 0.46091621 0.55391765 10 sp_14 -0.139730368 0.53331433
-#> 7353 0 0.46091621 0.55391765 8 sp_15 -0.139730368 0.53331433
-#> 7363 0 0.46091621 0.55391765 10 sp_16 -0.139730368 0.53331433
-#> 7373 0 0.46091621 0.55391765 13 sp_17 -0.139730368 0.53331433
-#> 7383 1 0.46091621 0.55391765 20 sp_18 -0.139730368 0.53331433
-#> 7393 0 0.46091621 0.55391765 6 sp_19 -0.139730368 0.53331433
-#> 7403 0 0.46091621 0.55391765 20 sp_20 -0.139730368 0.53331433
-#> 7413 0 0.46091621 0.55391765 20 sp_21 -0.139730368 0.53331433
-#> 7423 0 0.46091621 0.55391765 9 sp_22 -0.139730368 0.53331433
-#> 7433 0 0.46091621 0.55391765 16 sp_23 -0.139730368 0.53331433
-#> 7443 0 0.46091621 0.55391765 8 sp_24 -0.139730368 0.53331433
-#> 7453 0 0.46091621 0.55391765 7 sp_25 -0.139730368 0.53331433
-#> 7463 0 0.46091621 0.55391765 10 sp_26 -0.139730368 0.53331433
-#> 7473 1 0.46091621 0.55391765 17 sp_27 -0.139730368 0.53331433
-#> 7483 0 0.46091621 0.55391765 18 sp_28 -0.139730368 0.53331433
-#> 7493 0 0.46091621 0.55391765 8 sp_29 -0.139730368 0.53331433
-#> 7503 0 0.46091621 0.55391765 19 sp_30 -0.139730368 0.53331433
-#> 8413 1 -1.26506123 -0.06191171 10 sp_1 -0.380597979 0.24837592
-#> 8423 0 -1.26506123 -0.06191171 11 sp_2 -0.380597979 0.24837592
-#> 8433 0 -1.26506123 -0.06191171 17 sp_3 -0.380597979 0.24837592
-#> 8443 0 -1.26506123 -0.06191171 12 sp_4 -0.380597979 0.24837592
-#> 8453 0 -1.26506123 -0.06191171 2 sp_5 -0.380597979 0.24837592
-#> 8463 0 -1.26506123 -0.06191171 19 sp_6 -0.380597979 0.24837592
-#> 8473 0 -1.26506123 -0.06191171 13 sp_7 -0.380597979 0.24837592
-#> 8483 0 -1.26506123 -0.06191171 13 sp_8 -0.380597979 0.24837592
-#> 8493 0 -1.26506123 -0.06191171 19 sp_9 -0.380597979 0.24837592
-#> 8503 1 -1.26506123 -0.06191171 10 sp_10 -0.380597979 0.24837592
-#> 8513 0 -1.26506123 -0.06191171 16 sp_11 -0.380597979 0.24837592
-#> 8523 0 -1.26506123 -0.06191171 5 sp_12 -0.380597979 0.24837592
-#> 8533 0 -1.26506123 -0.06191171 4 sp_13 -0.380597979 0.24837592
-#> 8543 0 -1.26506123 -0.06191171 18 sp_14 -0.380597979 0.24837592
-#> 8553 0 -1.26506123 -0.06191171 1 sp_15 -0.380597979 0.24837592
-#> 8563 0 -1.26506123 -0.06191171 16 sp_16 -0.380597979 0.24837592
-#> 8573 0 -1.26506123 -0.06191171 17 sp_17 -0.380597979 0.24837592
-#> 8583 0 -1.26506123 -0.06191171 12 sp_18 -0.380597979 0.24837592
-#> 8593 0 -1.26506123 -0.06191171 2 sp_19 -0.380597979 0.24837592
-#> 8603 0 -1.26506123 -0.06191171 18 sp_20 -0.380597979 0.24837592
-#> 8613 0 -1.26506123 -0.06191171 12 sp_21 -0.380597979 0.24837592
-#> 8623 0 -1.26506123 -0.06191171 15 sp_22 -0.380597979 0.24837592
-#> 8633 0 -1.26506123 -0.06191171 19 sp_23 -0.380597979 0.24837592
-#> 8643 0 -1.26506123 -0.06191171 6 sp_24 -0.380597979 0.24837592
-#> 8653 0 -1.26506123 -0.06191171 16 sp_25 -0.380597979 0.24837592
-#> 8663 0 -1.26506123 -0.06191171 15 sp_26 -0.380597979 0.24837592
-#> 8673 0 -1.26506123 -0.06191171 19 sp_27 -0.380597979 0.24837592
-#> 8683 0 -1.26506123 -0.06191171 3 sp_28 -0.380597979 0.24837592
-#> 8693 0 -1.26506123 -0.06191171 14 sp_29 -0.380597979 0.24837592
-#> 8703 0 -1.26506123 -0.06191171 1 sp_30 -0.380597979 0.24837592
-#> 9613 0 -0.68685285 -0.30596266 1 sp_1 1.476197464 -0.71800879
-#> 9623 0 -0.68685285 -0.30596266 16 sp_2 1.476197464 -0.71800879
-#> 9633 0 -0.68685285 -0.30596266 11 sp_3 1.476197464 -0.71800879
-#> 9643 1 -0.68685285 -0.30596266 4 sp_4 1.476197464 -0.71800879
-#> 9653 0 -0.68685285 -0.30596266 12 sp_5 1.476197464 -0.71800879
-#> 9663 1 -0.68685285 -0.30596266 13 sp_6 1.476197464 -0.71800879
-#> 9673 0 -0.68685285 -0.30596266 10 sp_7 1.476197464 -0.71800879
-#> 9683 0 -0.68685285 -0.30596266 10 sp_8 1.476197464 -0.71800879
-#> 9693 0 -0.68685285 -0.30596266 7 sp_9 1.476197464 -0.71800879
-#> 9703 0 -0.68685285 -0.30596266 18 sp_10 1.476197464 -0.71800879
-#> 9713 0 -0.68685285 -0.30596266 17 sp_11 1.476197464 -0.71800879
-#> 9723 1 -0.68685285 -0.30596266 20 sp_12 1.476197464 -0.71800879
-#> 9733 1 -0.68685285 -0.30596266 9 sp_13 1.476197464 -0.71800879
-#> 9743 0 -0.68685285 -0.30596266 11 sp_14 1.476197464 -0.71800879
-#> 9753 1 -0.68685285 -0.30596266 12 sp_15 1.476197464 -0.71800879
-#> 9763 0 -0.68685285 -0.30596266 8 sp_16 1.476197464 -0.71800879
-#> 9773 0 -0.68685285 -0.30596266 18 sp_17 1.476197464 -0.71800879
-#> 9783 0 -0.68685285 -0.30596266 5 sp_18 1.476197464 -0.71800879
-#> 9793 0 -0.68685285 -0.30596266 18 sp_19 1.476197464 -0.71800879
-#> 9803 0 -0.68685285 -0.30596266 6 sp_20 1.476197464 -0.71800879
-#> 9813 0 -0.68685285 -0.30596266 10 sp_21 1.476197464 -0.71800879
-#> 9823 0 -0.68685285 -0.30596266 9 sp_22 1.476197464 -0.71800879
-#> 9833 1 -0.68685285 -0.30596266 11 sp_23 1.476197464 -0.71800879
-#> 9843 0 -0.68685285 -0.30596266 6 sp_24 1.476197464 -0.71800879
-#> 9853 0 -0.68685285 -0.30596266 12 sp_25 1.476197464 -0.71800879
-#> 9863 0 -0.68685285 -0.30596266 19 sp_26 1.476197464 -0.71800879
-#> 9873 0 -0.68685285 -0.30596266 4 sp_27 1.476197464 -0.71800879
-#> 9883 0 -0.68685285 -0.30596266 3 sp_28 1.476197464 -0.71800879
-#> 9893 0 -0.68685285 -0.30596266 14 sp_29 1.476197464 -0.71800879
-#> 9903 0 -0.68685285 -0.30596266 8 sp_30 1.476197464 -0.71800879
-#> 10813 0 -0.44566197 -0.38047100 6 sp_1 0.610727338 -1.32709228
-#> 10823 0 -0.44566197 -0.38047100 4 sp_2 0.610727338 -1.32709228
-#> 10833 1 -0.44566197 -0.38047100 10 sp_3 0.610727338 -1.32709228
-#> 10843 0 -0.44566197 -0.38047100 16 sp_4 0.610727338 -1.32709228
-#> 10853 0 -0.44566197 -0.38047100 16 sp_5 0.610727338 -1.32709228
-#> 10863 1 -0.44566197 -0.38047100 20 sp_6 0.610727338 -1.32709228
-#> 10873 1 -0.44566197 -0.38047100 10 sp_7 0.610727338 -1.32709228
-#> 10883 0 -0.44566197 -0.38047100 6 sp_8 0.610727338 -1.32709228
-#> 10893 0 -0.44566197 -0.38047100 19 sp_9 0.610727338 -1.32709228
-#> 10903 0 -0.44566197 -0.38047100 4 sp_10 0.610727338 -1.32709228
-#> 10913 0 -0.44566197 -0.38047100 9 sp_11 0.610727338 -1.32709228
-#> 10923 0 -0.44566197 -0.38047100 4 sp_12 0.610727338 -1.32709228
-#> 10933 0 -0.44566197 -0.38047100 15 sp_13 0.610727338 -1.32709228
-#> 10943 1 -0.44566197 -0.38047100 20 sp_14 0.610727338 -1.32709228
-#> 10953 1 -0.44566197 -0.38047100 17 sp_15 0.610727338 -1.32709228
-#> 10963 0 -0.44566197 -0.38047100 7 sp_16 0.610727338 -1.32709228
-#> 10973 1 -0.44566197 -0.38047100 15 sp_17 0.610727338 -1.32709228
-#> 10983 0 -0.44566197 -0.38047100 5 sp_18 0.610727338 -1.32709228
-#> 10993 1 -0.44566197 -0.38047100 14 sp_19 0.610727338 -1.32709228
-#> 11003 0 -0.44566197 -0.38047100 15 sp_20 0.610727338 -1.32709228
-#> 11013 0 -0.44566197 -0.38047100 15 sp_21 0.610727338 -1.32709228
-#> 11023 1 -0.44566197 -0.38047100 16 sp_22 0.610727338 -1.32709228
-#> 11033 0 -0.44566197 -0.38047100 19 sp_23 0.610727338 -1.32709228
-#> 11043 1 -0.44566197 -0.38047100 8 sp_24 0.610727338 -1.32709228
-#> 11053 0 -0.44566197 -0.38047100 5 sp_25 0.610727338 -1.32709228
-#> 11063 0 -0.44566197 -0.38047100 7 sp_26 0.610727338 -1.32709228
-#> 11073 1 -0.44566197 -0.38047100 20 sp_27 0.610727338 -1.32709228
-#> 11083 0 -0.44566197 -0.38047100 16 sp_28 0.610727338 -1.32709228
-#> 11093 0 -0.44566197 -0.38047100 16 sp_29 0.610727338 -1.32709228
-#> 11103 0 -0.44566197 -0.38047100 9 sp_30 0.610727338 -1.32709228
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-#> 12043 1 1.22408180 -0.69470698 10 sp_4 1.556856957 1.59533274
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-#> 12063 0 1.22408180 -0.69470698 6 sp_6 1.556856957 1.59533274
-#> 12073 1 1.22408180 -0.69470698 20 sp_7 1.556856957 1.59533274
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-#> 12143 0 1.22408180 -0.69470698 11 sp_14 1.556856957 1.59533274
-#> 12153 0 1.22408180 -0.69470698 7 sp_15 1.556856957 1.59533274
-#> 12163 0 1.22408180 -0.69470698 19 sp_16 1.556856957 1.59533274
-#> 12173 0 1.22408180 -0.69470698 8 sp_17 1.556856957 1.59533274
-#> 12183 1 1.22408180 -0.69470698 10 sp_18 1.556856957 1.59533274
-#> 12193 0 1.22408180 -0.69470698 5 sp_19 1.556856957 1.59533274
-#> 12203 0 1.22408180 -0.69470698 17 sp_20 1.556856957 1.59533274
-#> 12215 0 1.22408180 -0.69470698 6 sp_21 1.556856957 1.59533274
-#> 12223 0 1.22408180 -0.69470698 8 sp_22 1.556856957 1.59533274
-#> 12233 1 1.22408180 -0.69470698 20 sp_23 1.556856957 1.59533274
-#> 12243 0 1.22408180 -0.69470698 6 sp_24 1.556856957 1.59533274
-#> 12253 0 1.22408180 -0.69470698 15 sp_25 1.556856957 1.59533274
-#> 12263 0 1.22408180 -0.69470698 17 sp_26 1.556856957 1.59533274
-#> 12273 0 1.22408180 -0.69470698 3 sp_27 1.556856957 1.59533274
-#> 12283 0 1.22408180 -0.69470698 15 sp_28 1.556856957 1.59533274
-#> 12293 1 1.22408180 -0.69470698 20 sp_29 1.556856957 1.59533274
-#> 12303 0 1.22408180 -0.69470698 1 sp_30 1.556856957 1.59533274
-#> 13215 0 0.35981383 -0.20791728 5 sp_1 2.279082282 0.43278793
-#> 13223 1 0.35981383 -0.20791728 11 sp_2 2.279082282 0.43278793
-#> 13233 0 0.35981383 -0.20791728 15 sp_3 2.279082282 0.43278793
-#> 13243 0 0.35981383 -0.20791728 20 sp_4 2.279082282 0.43278793
-#> 13253 1 0.35981383 -0.20791728 2 sp_5 2.279082282 0.43278793
-#> 13263 0 0.35981383 -0.20791728 16 sp_6 2.279082282 0.43278793
-#> 13273 0 0.35981383 -0.20791728 19 sp_7 2.279082282 0.43278793
-#> 13283 0 0.35981383 -0.20791728 10 sp_8 2.279082282 0.43278793
-#> 13293 0 0.35981383 -0.20791728 19 sp_9 2.279082282 0.43278793
-#> 13303 1 0.35981383 -0.20791728 17 sp_10 2.279082282 0.43278793
-#> 13315 0 0.35981383 -0.20791728 7 sp_11 2.279082282 0.43278793
-#> 13323 1 0.35981383 -0.20791728 6 sp_12 2.279082282 0.43278793
-#> 13333 0 0.35981383 -0.20791728 12 sp_13 2.279082282 0.43278793
-#> 13343 1 0.35981383 -0.20791728 4 sp_14 2.279082282 0.43278793
-#> 13353 0 0.35981383 -0.20791728 19 sp_15 2.279082282 0.43278793
-#> 13363 1 0.35981383 -0.20791728 2 sp_16 2.279082282 0.43278793
-#> 13373 0 0.35981383 -0.20791728 4 sp_17 2.279082282 0.43278793
-#> 13383 0 0.35981383 -0.20791728 11 sp_18 2.279082282 0.43278793
-#> 13393 0 0.35981383 -0.20791728 1 sp_19 2.279082282 0.43278793
-#> 13403 0 0.35981383 -0.20791728 19 sp_20 2.279082282 0.43278793
-#> 13415 1 0.35981383 -0.20791728 18 sp_21 2.279082282 0.43278793
-#> 13423 0 0.35981383 -0.20791728 16 sp_22 2.279082282 0.43278793
-#> 13433 1 0.35981383 -0.20791728 3 sp_23 2.279082282 0.43278793
-#> 13443 0 0.35981383 -0.20791728 1 sp_24 2.279082282 0.43278793
-#> 13453 1 0.35981383 -0.20791728 2 sp_25 2.279082282 0.43278793
-#> 13463 1 0.35981383 -0.20791728 2 sp_26 2.279082282 0.43278793
-#> 13473 0 0.35981383 -0.20791728 8 sp_27 2.279082282 0.43278793
-#> 13483 1 0.35981383 -0.20791728 20 sp_28 2.279082282 0.43278793
-#> 13493 0 0.35981383 -0.20791728 14 sp_29 2.279082282 0.43278793
-#> 13503 0 0.35981383 -0.20791728 13 sp_30 2.279082282 0.43278793
-#> 14415 1 0.40077145 -1.26539635 7 sp_1 -0.471806570 -1.08949913
-#> 14423 0 0.40077145 -1.26539635 8 sp_2 -0.471806570 -1.08949913
-#> 14433 0 0.40077145 -1.26539635 3 sp_3 -0.471806570 -1.08949913
-#> 14443 0 0.40077145 -1.26539635 16 sp_4 -0.471806570 -1.08949913
-#> 14453 0 0.40077145 -1.26539635 1 sp_5 -0.471806570 -1.08949913
-#> 14463 0 0.40077145 -1.26539635 12 sp_6 -0.471806570 -1.08949913
-#> 14473 1 0.40077145 -1.26539635 18 sp_7 -0.471806570 -1.08949913
-#> 14483 0 0.40077145 -1.26539635 14 sp_8 -0.471806570 -1.08949913
-#> 14493 0 0.40077145 -1.26539635 8 sp_9 -0.471806570 -1.08949913
-#> 14503 0 0.40077145 -1.26539635 5 sp_10 -0.471806570 -1.08949913
-#> 14515 1 0.40077145 -1.26539635 17 sp_11 -0.471806570 -1.08949913
-#> 14523 1 0.40077145 -1.26539635 11 sp_12 -0.471806570 -1.08949913
-#> 14533 1 0.40077145 -1.26539635 4 sp_13 -0.471806570 -1.08949913
-#> 14543 1 0.40077145 -1.26539635 13 sp_14 -0.471806570 -1.08949913
-#> 14553 1 0.40077145 -1.26539635 8 sp_15 -0.471806570 -1.08949913
-#> 14563 0 0.40077145 -1.26539635 15 sp_16 -0.471806570 -1.08949913
-#> 14573 0 0.40077145 -1.26539635 4 sp_17 -0.471806570 -1.08949913
-#> 14583 0 0.40077145 -1.26539635 13 sp_18 -0.471806570 -1.08949913
-#> 14593 1 0.40077145 -1.26539635 3 sp_19 -0.471806570 -1.08949913
-#> 14603 0 0.40077145 -1.26539635 7 sp_20 -0.471806570 -1.08949913
-#> 14615 0 0.40077145 -1.26539635 1 sp_21 -0.471806570 -1.08949913
-#> 14623 0 0.40077145 -1.26539635 6 sp_22 -0.471806570 -1.08949913
-#> 14633 1 0.40077145 -1.26539635 13 sp_23 -0.471806570 -1.08949913
-#> 14643 1 0.40077145 -1.26539635 17 sp_24 -0.471806570 -1.08949913
-#> 14653 0 0.40077145 -1.26539635 6 sp_25 -0.471806570 -1.08949913
-#> 14663 1 0.40077145 -1.26539635 10 sp_26 -0.471806570 -1.08949913
-#> 14673 0 0.40077145 -1.26539635 13 sp_27 -0.471806570 -1.08949913
-#> 14683 0 0.40077145 -1.26539635 6 sp_28 -0.471806570 -1.08949913
-#> 14693 1 0.40077145 -1.26539635 9 sp_29 -0.471806570 -1.08949913
-#> 14703 0 0.40077145 -1.26539635 8 sp_30 -0.471806570 -1.08949913
-#> 15613 0 0.11068272 2.16895597 1 sp_1 0.212686484 -1.31798554
-#> 15623 0 0.11068272 2.16895597 16 sp_2 0.212686484 -1.31798554
-#> 15633 0 0.11068272 2.16895597 2 sp_3 0.212686484 -1.31798554
-#> 15643 0 0.11068272 2.16895597 8 sp_4 0.212686484 -1.31798554
-#> 15653 0 0.11068272 2.16895597 14 sp_5 0.212686484 -1.31798554
-#> 15663 0 0.11068272 2.16895597 12 sp_6 0.212686484 -1.31798554
-#> 15673 0 0.11068272 2.16895597 8 sp_7 0.212686484 -1.31798554
-#> 15683 0 0.11068272 2.16895597 9 sp_8 0.212686484 -1.31798554
-#> 15693 0 0.11068272 2.16895597 8 sp_9 0.212686484 -1.31798554
-#> 15703 0 0.11068272 2.16895597 9 sp_10 0.212686484 -1.31798554
-#> 15713 0 0.11068272 2.16895597 20 sp_11 0.212686484 -1.31798554
-#> 15723 0 0.11068272 2.16895597 1 sp_12 0.212686484 -1.31798554
-#> 15733 0 0.11068272 2.16895597 3 sp_13 0.212686484 -1.31798554
-#> 15743 0 0.11068272 2.16895597 8 sp_14 0.212686484 -1.31798554
-#> 15753 0 0.11068272 2.16895597 2 sp_15 0.212686484 -1.31798554
-#> 15763 0 0.11068272 2.16895597 1 sp_16 0.212686484 -1.31798554
-#> 15773 0 0.11068272 2.16895597 9 sp_17 0.212686484 -1.31798554
-#> 15783 1 0.11068272 2.16895597 7 sp_18 0.212686484 -1.31798554
-#> 15793 0 0.11068272 2.16895597 13 sp_19 0.212686484 -1.31798554
-#> 15803 0 0.11068272 2.16895597 20 sp_20 0.212686484 -1.31798554
-#> 15813 0 0.11068272 2.16895597 14 sp_21 0.212686484 -1.31798554
-#> 15823 0 0.11068272 2.16895597 16 sp_22 0.212686484 -1.31798554
-#> 15833 1 0.11068272 2.16895597 7 sp_23 0.212686484 -1.31798554
-#> 15843 0 0.11068272 2.16895597 4 sp_24 0.212686484 -1.31798554
-#> 15853 0 0.11068272 2.16895597 13 sp_25 0.212686484 -1.31798554
-#> 15863 0 0.11068272 2.16895597 12 sp_26 0.212686484 -1.31798554
-#> 15873 0 0.11068272 2.16895597 13 sp_27 0.212686484 -1.31798554
-#> 15883 0 0.11068272 2.16895597 20 sp_28 0.212686484 -1.31798554
-#> 15893 0 0.11068272 2.16895597 10 sp_29 0.212686484 -1.31798554
-#> 15903 0 0.11068272 2.16895597 9 sp_30 0.212686484 -1.31798554
-#> 16813 0 -0.55584113 1.20796200 12 sp_1 2.666263607 -0.34159485
-#> 16823 0 -0.55584113 1.20796200 8 sp_2 2.666263607 -0.34159485
-#> 16833 0 -0.55584113 1.20796200 7 sp_3 2.666263607 -0.34159485
-#> 16843 1 -0.55584113 1.20796200 15 sp_4 2.666263607 -0.34159485
-#> 16853 0 -0.55584113 1.20796200 19 sp_5 2.666263607 -0.34159485
-#> 16863 0 -0.55584113 1.20796200 17 sp_6 2.666263607 -0.34159485
-#> 16873 0 -0.55584113 1.20796200 11 sp_7 2.666263607 -0.34159485
-#> 16883 0 -0.55584113 1.20796200 7 sp_8 2.666263607 -0.34159485
-#> 16893 0 -0.55584113 1.20796200 19 sp_9 2.666263607 -0.34159485
-#> 16903 0 -0.55584113 1.20796200 3 sp_10 2.666263607 -0.34159485
-#> 16913 0 -0.55584113 1.20796200 6 sp_11 2.666263607 -0.34159485
-#> 16923 1 -0.55584113 1.20796200 7 sp_12 2.666263607 -0.34159485
-#> 16933 0 -0.55584113 1.20796200 4 sp_13 2.666263607 -0.34159485
-#> 16943 1 -0.55584113 1.20796200 10 sp_14 2.666263607 -0.34159485
-#> 16953 0 -0.55584113 1.20796200 17 sp_15 2.666263607 -0.34159485
-#> 16963 0 -0.55584113 1.20796200 16 sp_16 2.666263607 -0.34159485
-#> 16973 0 -0.55584113 1.20796200 8 sp_17 2.666263607 -0.34159485
-#> 16983 0 -0.55584113 1.20796200 3 sp_18 2.666263607 -0.34159485
-#> 16993 0 -0.55584113 1.20796200 12 sp_19 2.666263607 -0.34159485
-#> 17003 0 -0.55584113 1.20796200 14 sp_20 2.666263607 -0.34159485
-#> 17013 0 -0.55584113 1.20796200 5 sp_21 2.666263607 -0.34159485
-#> 17023 0 -0.55584113 1.20796200 14 sp_22 2.666263607 -0.34159485
-#> 17033 0 -0.55584113 1.20796200 6 sp_23 2.666263607 -0.34159485
-#> 17043 0 -0.55584113 1.20796200 9 sp_24 2.666263607 -0.34159485
-#> 17053 0 -0.55584113 1.20796200 1 sp_25 2.666263607 -0.34159485
-#> 17063 0 -0.55584113 1.20796200 20 sp_26 2.666263607 -0.34159485
-#> 17073 0 -0.55584113 1.20796200 14 sp_27 2.666263607 -0.34159485
-#> 17083 0 -0.55584113 1.20796200 19 sp_28 2.666263607 -0.34159485
-#> 17093 0 -0.55584113 1.20796200 5 sp_29 2.666263607 -0.34159485
-#> 17103 0 -0.55584113 1.20796200 2 sp_30 2.666263607 -0.34159485
-#> 18013 0 1.78691314 -1.12310858 1 sp_1 0.902094706 -0.29755526
-#> 18023 1 1.78691314 -1.12310858 20 sp_2 0.902094706 -0.29755526
-#> 18033 0 1.78691314 -1.12310858 4 sp_3 0.902094706 -0.29755526
-#> 18043 1 1.78691314 -1.12310858 11 sp_4 0.902094706 -0.29755526
-#> 18053 1 1.78691314 -1.12310858 5 sp_5 0.902094706 -0.29755526
-#> 18063 1 1.78691314 -1.12310858 4 sp_6 0.902094706 -0.29755526
-#> 18073 1 1.78691314 -1.12310858 19 sp_7 0.902094706 -0.29755526
-#> 18083 0 1.78691314 -1.12310858 3 sp_8 0.902094706 -0.29755526
-#> 18093 0 1.78691314 -1.12310858 1 sp_9 0.902094706 -0.29755526
-#> 18103 1 1.78691314 -1.12310858 7 sp_10 0.902094706 -0.29755526
-#> 18113 0 1.78691314 -1.12310858 5 sp_11 0.902094706 -0.29755526
-#> 18123 1 1.78691314 -1.12310858 9 sp_12 0.902094706 -0.29755526
-#> 18133 1 1.78691314 -1.12310858 17 sp_13 0.902094706 -0.29755526
-#> 18143 0 1.78691314 -1.12310858 5 sp_14 0.902094706 -0.29755526
-#> 18153 1 1.78691314 -1.12310858 12 sp_15 0.902094706 -0.29755526
-#> 18163 1 1.78691314 -1.12310858 2 sp_16 0.902094706 -0.29755526
-#> 18173 1 1.78691314 -1.12310858 18 sp_17 0.902094706 -0.29755526
-#> 18183 1 1.78691314 -1.12310858 4 sp_18 0.902094706 -0.29755526
-#> 18193 1 1.78691314 -1.12310858 10 sp_19 0.902094706 -0.29755526
-#> 18203 1 1.78691314 -1.12310858 15 sp_20 0.902094706 -0.29755526
-#> 18213 0 1.78691314 -1.12310858 8 sp_21 0.902094706 -0.29755526
-#> 18223 1 1.78691314 -1.12310858 1 sp_22 0.902094706 -0.29755526
-#> 18233 0 1.78691314 -1.12310858 11 sp_23 0.902094706 -0.29755526
-#> 18243 0 1.78691314 -1.12310858 5 sp_24 0.902094706 -0.29755526
-#> 18253 1 1.78691314 -1.12310858 11 sp_25 0.902094706 -0.29755526
-#> 18263 1 1.78691314 -1.12310858 15 sp_26 0.902094706 -0.29755526
-#> 18273 0 1.78691314 -1.12310858 15 sp_27 0.902094706 -0.29755526
-#> 18283 1 1.78691314 -1.12310858 10 sp_28 0.902094706 -0.29755526
-#> 18293 1 1.78691314 -1.12310858 15 sp_29 0.902094706 -0.29755526
-#> 18303 0 1.78691314 -1.12310858 15 sp_30 0.902094706 -0.29755526
-#> 19213 1 0.49785048 -0.40288484 20 sp_1 2.186407733 0.08851264
-#> 19223 1 0.49785048 -0.40288484 12 sp_2 2.186407733 0.08851264
-#> 19233 0 0.49785048 -0.40288484 9 sp_3 2.186407733 0.08851264
-#> 19243 0 0.49785048 -0.40288484 4 sp_4 2.186407733 0.08851264
-#> 19253 1 0.49785048 -0.40288484 3 sp_5 2.186407733 0.08851264
-#> 19263 0 0.49785048 -0.40288484 7 sp_6 2.186407733 0.08851264
-#> 19273 1 0.49785048 -0.40288484 4 sp_7 2.186407733 0.08851264
-#> 19283 0 0.49785048 -0.40288484 8 sp_8 2.186407733 0.08851264
-#> 19293 0 0.49785048 -0.40288484 5 sp_9 2.186407733 0.08851264
-#> 19303 1 0.49785048 -0.40288484 6 sp_10 2.186407733 0.08851264
-#> 19313 1 0.49785048 -0.40288484 4 sp_11 2.186407733 0.08851264
-#> 19323 1 0.49785048 -0.40288484 3 sp_12 2.186407733 0.08851264
-#> 19333 1 0.49785048 -0.40288484 11 sp_13 2.186407733 0.08851264
-#> 19343 0 0.49785048 -0.40288484 10 sp_14 2.186407733 0.08851264
-#> 19353 0 0.49785048 -0.40288484 5 sp_15 2.186407733 0.08851264
-#> 19363 0 0.49785048 -0.40288484 11 sp_16 2.186407733 0.08851264
-#> 19373 0 0.49785048 -0.40288484 10 sp_17 2.186407733 0.08851264
-#> 19383 0 0.49785048 -0.40288484 15 sp_18 2.186407733 0.08851264
-#> 19393 1 0.49785048 -0.40288484 19 sp_19 2.186407733 0.08851264
-#> 19403 0 0.49785048 -0.40288484 10 sp_20 2.186407733 0.08851264
-#> 19413 0 0.49785048 -0.40288484 13 sp_21 2.186407733 0.08851264
-#> 19423 1 0.49785048 -0.40288484 3 sp_22 2.186407733 0.08851264
-#> 19433 0 0.49785048 -0.40288484 18 sp_23 2.186407733 0.08851264
-#> 19443 0 0.49785048 -0.40288484 10 sp_24 2.186407733 0.08851264
-#> 19453 0 0.49785048 -0.40288484 8 sp_25 2.186407733 0.08851264
-#> 19463 1 0.49785048 -0.40288484 12 sp_26 2.186407733 0.08851264
-#> 19473 0 0.49785048 -0.40288484 10 sp_27 2.186407733 0.08851264
-#> 19483 0 0.49785048 -0.40288484 7 sp_28 2.186407733 0.08851264
-#> 19493 0 0.49785048 -0.40288484 7 sp_29 2.186407733 0.08851264
-#> 19503 0 0.49785048 -0.40288484 6 sp_30 2.186407733 0.08851264
-#> 20413 0 -1.96661716 -0.46665535 17 sp_1 0.595320049 1.09064461
-#> 20423 0 -1.96661716 -0.46665535 20 sp_2 0.595320049 1.09064461
-#> 20433 0 -1.96661716 -0.46665535 1 sp_3 0.595320049 1.09064461
-#> 20443 0 -1.96661716 -0.46665535 5 sp_4 0.595320049 1.09064461
-#> 20453 0 -1.96661716 -0.46665535 10 sp_5 0.595320049 1.09064461
-#> 20463 0 -1.96661716 -0.46665535 13 sp_6 0.595320049 1.09064461
-#> 20473 0 -1.96661716 -0.46665535 10 sp_7 0.595320049 1.09064461
-#> 20483 0 -1.96661716 -0.46665535 2 sp_8 0.595320049 1.09064461
-#> 20493 0 -1.96661716 -0.46665535 15 sp_9 0.595320049 1.09064461
-#> 20503 0 -1.96661716 -0.46665535 15 sp_10 0.595320049 1.09064461
-#> 20513 0 -1.96661716 -0.46665535 8 sp_11 0.595320049 1.09064461
-#> 20523 0 -1.96661716 -0.46665535 3 sp_12 0.595320049 1.09064461
-#> 20533 0 -1.96661716 -0.46665535 2 sp_13 0.595320049 1.09064461
-#> 20543 0 -1.96661716 -0.46665535 6 sp_14 0.595320049 1.09064461
-#> 20553 0 -1.96661716 -0.46665535 14 sp_15 0.595320049 1.09064461
-#> 20563 0 -1.96661716 -0.46665535 15 sp_16 0.595320049 1.09064461
-#> 20573 0 -1.96661716 -0.46665535 19 sp_17 0.595320049 1.09064461
-#> 20583 0 -1.96661716 -0.46665535 9 sp_18 0.595320049 1.09064461
-#> 20593 0 -1.96661716 -0.46665535 15 sp_19 0.595320049 1.09064461
-#> 20603 0 -1.96661716 -0.46665535 16 sp_20 0.595320049 1.09064461
-#> 20613 0 -1.96661716 -0.46665535 8 sp_21 0.595320049 1.09064461
-#> 20623 0 -1.96661716 -0.46665535 9 sp_22 0.595320049 1.09064461
-#> 20633 0 -1.96661716 -0.46665535 16 sp_23 0.595320049 1.09064461
-#> 20643 0 -1.96661716 -0.46665535 9 sp_24 0.595320049 1.09064461
-#> 20653 0 -1.96661716 -0.46665535 2 sp_25 0.595320049 1.09064461
-#> 20663 0 -1.96661716 -0.46665535 9 sp_26 0.595320049 1.09064461
-#> 20673 0 -1.96661716 -0.46665535 11 sp_27 0.595320049 1.09064461
-#> 20683 0 -1.96661716 -0.46665535 11 sp_28 0.595320049 1.09064461
-#> 20693 0 -1.96661716 -0.46665535 4 sp_29 0.595320049 1.09064461
-#> 20703 0 -1.96661716 -0.46665535 7 sp_30 0.595320049 1.09064461
-#> 21613 0 0.70135590 0.77996512 18 sp_1 0.332761273 -1.52645307
-#> 21623 1 0.70135590 0.77996512 11 sp_2 0.332761273 -1.52645307
-#> 21633 1 0.70135590 0.77996512 1 sp_3 0.332761273 -1.52645307
-#> 21643 0 0.70135590 0.77996512 11 sp_4 0.332761273 -1.52645307
-#> 21653 0 0.70135590 0.77996512 6 sp_5 0.332761273 -1.52645307
-#> 21663 0 0.70135590 0.77996512 10 sp_6 0.332761273 -1.52645307
-#> 21673 0 0.70135590 0.77996512 18 sp_7 0.332761273 -1.52645307
-#> 21683 0 0.70135590 0.77996512 3 sp_8 0.332761273 -1.52645307
-#> 21693 0 0.70135590 0.77996512 3 sp_9 0.332761273 -1.52645307
-#> 21703 1 0.70135590 0.77996512 2 sp_10 0.332761273 -1.52645307
-#> 21713 1 0.70135590 0.77996512 8 sp_11 0.332761273 -1.52645307
-#> 21723 1 0.70135590 0.77996512 13 sp_12 0.332761273 -1.52645307
-#> 21733 0 0.70135590 0.77996512 8 sp_13 0.332761273 -1.52645307
-#> 21743 1 0.70135590 0.77996512 2 sp_14 0.332761273 -1.52645307
-#> 21753 0 0.70135590 0.77996512 6 sp_15 0.332761273 -1.52645307
-#> 21763 0 0.70135590 0.77996512 17 sp_16 0.332761273 -1.52645307
-#> 21773 0 0.70135590 0.77996512 14 sp_17 0.332761273 -1.52645307
-#> 21783 1 0.70135590 0.77996512 7 sp_18 0.332761273 -1.52645307
-#> 21793 0 0.70135590 0.77996512 13 sp_19 0.332761273 -1.52645307
-#> 21803 0 0.70135590 0.77996512 8 sp_20 0.332761273 -1.52645307
-#> 21813 0 0.70135590 0.77996512 6 sp_21 0.332761273 -1.52645307
-#> 21823 1 0.70135590 0.77996512 11 sp_22 0.332761273 -1.52645307
-#> 21833 0 0.70135590 0.77996512 10 sp_23 0.332761273 -1.52645307
-#> 21843 0 0.70135590 0.77996512 17 sp_24 0.332761273 -1.52645307
-#> 21853 0 0.70135590 0.77996512 7 sp_25 0.332761273 -1.52645307
-#> 21863 1 0.70135590 0.77996512 12 sp_26 0.332761273 -1.52645307
-#> 21873 0 0.70135590 0.77996512 19 sp_27 0.332761273 -1.52645307
-#> 21883 0 0.70135590 0.77996512 17 sp_28 0.332761273 -1.52645307
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-#> 22853 0 -0.47279141 -0.08336907 18 sp_5 1.399227090 1.51928992
-#> 22863 0 -0.47279141 -0.08336907 18 sp_6 1.399227090 1.51928992
-#> 22873 0 -0.47279141 -0.08336907 20 sp_7 1.399227090 1.51928992
-#> 22883 0 -0.47279141 -0.08336907 10 sp_8 1.399227090 1.51928992
-#> 22893 0 -0.47279141 -0.08336907 10 sp_9 1.399227090 1.51928992
-#> 22903 0 -0.47279141 -0.08336907 9 sp_10 1.399227090 1.51928992
-#> 22913 1 -0.47279141 -0.08336907 19 sp_11 1.399227090 1.51928992
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-#> 22933 0 -0.47279141 -0.08336907 18 sp_13 1.399227090 1.51928992
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-#> 22953 0 -0.47279141 -0.08336907 12 sp_15 1.399227090 1.51928992
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-#> 22973 0 -0.47279141 -0.08336907 20 sp_17 1.399227090 1.51928992
-#> 22983 0 -0.47279141 -0.08336907 10 sp_18 1.399227090 1.51928992
-#> 22993 0 -0.47279141 -0.08336907 5 sp_19 1.399227090 1.51928992
-#> 23003 0 -0.47279141 -0.08336907 2 sp_20 1.399227090 1.51928992
-#> 23013 0 -0.47279141 -0.08336907 18 sp_21 1.399227090 1.51928992
-#> 23023 0 -0.47279141 -0.08336907 12 sp_22 1.399227090 1.51928992
-#> 23033 0 -0.47279141 -0.08336907 13 sp_23 1.399227090 1.51928992
-#> 23043 0 -0.47279141 -0.08336907 11 sp_24 1.399227090 1.51928992
-#> 23053 0 -0.47279141 -0.08336907 19 sp_25 1.399227090 1.51928992
-#> 23063 0 -0.47279141 -0.08336907 6 sp_26 1.399227090 1.51928992
-#> 23073 0 -0.47279141 -0.08336907 18 sp_27 1.399227090 1.51928992
-#> 23083 0 -0.47279141 -0.08336907 10 sp_28 1.399227090 1.51928992
-#> 23093 0 -0.47279141 -0.08336907 9 sp_29 1.399227090 1.51928992
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-#> 24033 0 -1.06782371 0.25331851 13 sp_3 1.063030449 0.45208542
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-#> 24063 0 -1.06782371 0.25331851 11 sp_6 1.063030449 0.45208542
-#> 24073 0 -1.06782371 0.25331851 16 sp_7 1.063030449 0.45208542
-#> 24083 0 -1.06782371 0.25331851 5 sp_8 1.063030449 0.45208542
-#> 24093 0 -1.06782371 0.25331851 4 sp_9 1.063030449 0.45208542
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-#> 24115 0 -1.06782371 0.25331851 15 sp_11 1.063030449 0.45208542
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-#> 24133 0 -1.06782371 0.25331851 7 sp_13 1.063030449 0.45208542
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-#> 24163 0 -1.06782371 0.25331851 18 sp_16 1.063030449 0.45208542
-#> 24173 0 -1.06782371 0.25331851 18 sp_17 1.063030449 0.45208542
-#> 24183 0 -1.06782371 0.25331851 3 sp_18 1.063030449 0.45208542
-#> 24193 0 -1.06782371 0.25331851 8 sp_19 1.063030449 0.45208542
-#> 24203 0 -1.06782371 0.25331851 14 sp_20 1.063030449 0.45208542
-#> 24215 0 -1.06782371 0.25331851 9 sp_21 1.063030449 0.45208542
-#> 24223 0 -1.06782371 0.25331851 15 sp_22 1.063030449 0.45208542
-#> 24233 0 -1.06782371 0.25331851 17 sp_23 1.063030449 0.45208542
-#> 24243 0 -1.06782371 0.25331851 7 sp_24 1.063030449 0.45208542
-#> 24253 0 -1.06782371 0.25331851 8 sp_25 1.063030449 0.45208542
-#> 24263 0 -1.06782371 0.25331851 1 sp_26 1.063030449 0.45208542
-#> 24273 0 -1.06782371 0.25331851 9 sp_27 1.063030449 0.45208542
-#> 24283 0 -1.06782371 0.25331851 3 sp_28 1.063030449 0.45208542
-#> 24293 0 -1.06782371 0.25331851 2 sp_29 1.063030449 0.45208542
-#> 24303 0 -1.06782371 0.25331851 11 sp_30 1.063030449 0.45208542
-#> 25215 0 -0.21797491 -0.02854676 4 sp_1 -0.209313656 -0.07923944
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-#> 25233 0 -0.21797491 -0.02854676 20 sp_3 -0.209313656 -0.07923944
-#> 25243 0 -0.21797491 -0.02854676 11 sp_4 -0.209313656 -0.07923944
-#> 25253 0 -0.21797491 -0.02854676 18 sp_5 -0.209313656 -0.07923944
-#> 25263 1 -0.21797491 -0.02854676 14 sp_6 -0.209313656 -0.07923944
-#> 25273 0 -0.21797491 -0.02854676 3 sp_7 -0.209313656 -0.07923944
-#> 25283 1 -0.21797491 -0.02854676 3 sp_8 -0.209313656 -0.07923944
-#> 25293 0 -0.21797491 -0.02854676 14 sp_9 -0.209313656 -0.07923944
-#> 25303 0 -0.21797491 -0.02854676 7 sp_10 -0.209313656 -0.07923944
-#> 25315 0 -0.21797491 -0.02854676 15 sp_11 -0.209313656 -0.07923944
-#> 25323 0 -0.21797491 -0.02854676 8 sp_12 -0.209313656 -0.07923944
-#> 25333 0 -0.21797491 -0.02854676 1 sp_13 -0.209313656 -0.07923944
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-#> 25353 1 -0.21797491 -0.02854676 17 sp_15 -0.209313656 -0.07923944
-#> 25363 0 -0.21797491 -0.02854676 6 sp_16 -0.209313656 -0.07923944
-#> 25373 0 -0.21797491 -0.02854676 10 sp_17 -0.209313656 -0.07923944
-#> 25383 0 -0.21797491 -0.02854676 12 sp_18 -0.209313656 -0.07923944
-#> 25393 0 -0.21797491 -0.02854676 8 sp_19 -0.209313656 -0.07923944
-#> 25403 0 -0.21797491 -0.02854676 16 sp_20 -0.209313656 -0.07923944
-#> 25415 0 -0.21797491 -0.02854676 7 sp_21 -0.209313656 -0.07923944
-#> 25423 0 -0.21797491 -0.02854676 7 sp_22 -0.209313656 -0.07923944
-#> 25433 0 -0.21797491 -0.02854676 1 sp_23 -0.209313656 -0.07923944
-#> 25443 0 -0.21797491 -0.02854676 11 sp_24 -0.209313656 -0.07923944
-#> 25453 0 -0.21797491 -0.02854676 3 sp_25 -0.209313656 -0.07923944
-#> 25463 0 -0.21797491 -0.02854676 17 sp_26 -0.209313656 -0.07923944
-#> 25473 0 -0.21797491 -0.02854676 20 sp_27 -0.209313656 -0.07923944
-#> 25483 0 -0.21797491 -0.02854676 3 sp_28 -0.209313656 -0.07923944
-#> 25493 0 -0.21797491 -0.02854676 14 sp_29 -0.209313656 -0.07923944
-#> 25503 0 -0.21797491 -0.02854676 5 sp_30 -0.209313656 -0.07923944
-#> 26415 0 -1.02600445 -0.04287046 18 sp_1 -0.001595076 0.30556929
-#> 26423 0 -1.02600445 -0.04287046 8 sp_2 -0.001595076 0.30556929
-#> 26433 0 -1.02600445 -0.04287046 20 sp_3 -0.001595076 0.30556929
-#> 26443 0 -1.02600445 -0.04287046 10 sp_4 -0.001595076 0.30556929
-#> 26453 1 -1.02600445 -0.04287046 18 sp_5 -0.001595076 0.30556929
-#> 26463 0 -1.02600445 -0.04287046 17 sp_6 -0.001595076 0.30556929
-#> 26473 0 -1.02600445 -0.04287046 9 sp_7 -0.001595076 0.30556929
-#> 26483 0 -1.02600445 -0.04287046 3 sp_8 -0.001595076 0.30556929
-#> 26493 0 -1.02600445 -0.04287046 5 sp_9 -0.001595076 0.30556929
-#> 26503 0 -1.02600445 -0.04287046 16 sp_10 -0.001595076 0.30556929
-#> 26515 0 -1.02600445 -0.04287046 20 sp_11 -0.001595076 0.30556929
-#> 26523 0 -1.02600445 -0.04287046 3 sp_12 -0.001595076 0.30556929
-#> 26533 0 -1.02600445 -0.04287046 3 sp_13 -0.001595076 0.30556929
-#> 26543 0 -1.02600445 -0.04287046 13 sp_14 -0.001595076 0.30556929
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-#> 26563 0 -1.02600445 -0.04287046 15 sp_16 -0.001595076 0.30556929
-#> 26573 0 -1.02600445 -0.04287046 19 sp_17 -0.001595076 0.30556929
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-#> 26593 0 -1.02600445 -0.04287046 12 sp_19 -0.001595076 0.30556929
-#> 26603 0 -1.02600445 -0.04287046 20 sp_20 -0.001595076 0.30556929
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-#> 26703 0 -1.02600445 -0.04287046 16 sp_30 -0.001595076 0.30556929
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-#> 27643 0 -0.72889123 1.36860228 15 sp_4 -0.403005062 -0.85646918
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-#> 27703 0 -0.72889123 1.36860228 9 sp_10 -0.403005062 -0.85646918
-#> 27713 0 -0.72889123 1.36860228 20 sp_11 -0.403005062 -0.85646918
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-#> 27743 0 -0.72889123 1.36860228 19 sp_14 -0.403005062 -0.85646918
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-#> 27783 1 -0.72889123 1.36860228 15 sp_18 -0.403005062 -0.85646918
-#> 27793 0 -0.72889123 1.36860228 17 sp_19 -0.403005062 -0.85646918
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-#> 27863 0 -0.72889123 1.36860228 15 sp_26 -0.403005062 -0.85646918
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-#> 27893 0 -0.72889123 1.36860228 9 sp_29 -0.403005062 -0.85646918
-#> 27903 0 -0.72889123 1.36860228 9 sp_30 -0.403005062 -0.85646918
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-#> 30253 0 -1.68669331 1.51647060 15 sp_25 -0.531131309 0.78017265
-#> 30263 0 -1.68669331 1.51647060 3 sp_26 -0.531131309 0.78017265
-#> 30273 1 -1.68669331 1.51647060 2 sp_27 -0.531131309 0.78017265
-#> 30283 0 -1.68669331 1.51647060 5 sp_28 -0.531131309 0.78017265
-#> 30293 0 -1.68669331 1.51647060 5 sp_29 -0.531131309 0.78017265
-#> 30303 0 -1.68669331 1.51647060 7 sp_30 -0.531131309 0.78017265
-#> 31213 0 0.83778704 -1.54875280 2 sp_1 0.167775141 -1.40425215
-#> 31223 1 0.83778704 -1.54875280 16 sp_2 0.167775141 -1.40425215
-#> 31233 0 0.83778704 -1.54875280 8 sp_3 0.167775141 -1.40425215
-#> 31243 0 0.83778704 -1.54875280 18 sp_4 0.167775141 -1.40425215
-#> 31253 1 0.83778704 -1.54875280 19 sp_5 0.167775141 -1.40425215
-#> 31263 1 0.83778704 -1.54875280 9 sp_6 0.167775141 -1.40425215
-#> 31273 1 0.83778704 -1.54875280 19 sp_7 0.167775141 -1.40425215
-#> 31283 0 0.83778704 -1.54875280 14 sp_8 0.167775141 -1.40425215
-#> 31293 1 0.83778704 -1.54875280 19 sp_9 0.167775141 -1.40425215
-#> 31303 0 0.83778704 -1.54875280 5 sp_10 0.167775141 -1.40425215
-#> 31313 1 0.83778704 -1.54875280 13 sp_11 0.167775141 -1.40425215
-#> 31323 0 0.83778704 -1.54875280 16 sp_12 0.167775141 -1.40425215
-#> 31333 0 0.83778704 -1.54875280 7 sp_13 0.167775141 -1.40425215
-#> 31343 1 0.83778704 -1.54875280 8 sp_14 0.167775141 -1.40425215
-#> 31353 1 0.83778704 -1.54875280 16 sp_15 0.167775141 -1.40425215
-#> 31363 0 0.83778704 -1.54875280 15 sp_16 0.167775141 -1.40425215
-#> 31373 1 0.83778704 -1.54875280 20 sp_17 0.167775141 -1.40425215
-#> 31383 0 0.83778704 -1.54875280 3 sp_18 0.167775141 -1.40425215
-#> 31393 1 0.83778704 -1.54875280 17 sp_19 0.167775141 -1.40425215
-#> 31403 0 0.83778704 -1.54875280 7 sp_20 0.167775141 -1.40425215
-#> 31413 0 0.83778704 -1.54875280 13 sp_21 0.167775141 -1.40425215
-#> 31423 1 0.83778704 -1.54875280 3 sp_22 0.167775141 -1.40425215
-#> 31433 0 0.83778704 -1.54875280 13 sp_23 0.167775141 -1.40425215
-#> 31443 0 0.83778704 -1.54875280 14 sp_24 0.167775141 -1.40425215
-#> 31453 1 0.83778704 -1.54875280 4 sp_25 0.167775141 -1.40425215
-#> 31463 0 0.83778704 -1.54875280 16 sp_26 0.167775141 -1.40425215
-#> 31473 0 0.83778704 -1.54875280 9 sp_27 0.167775141 -1.40425215
-#> 31483 0 0.83778704 -1.54875280 16 sp_28 0.167775141 -1.40425215
-#> 31493 0 0.83778704 -1.54875280 9 sp_29 0.167775141 -1.40425215
-#> 31503 1 0.83778704 -1.54875280 5 sp_30 0.167775141 -1.40425215
-#> 32413 0 0.15337312 0.58461375 14 sp_1 -1.253938223 -0.88156275
-#> 32423 1 0.15337312 0.58461375 12 sp_2 -1.253938223 -0.88156275
-#> 32433 1 0.15337312 0.58461375 14 sp_3 -1.253938223 -0.88156275
-#> 32443 0 0.15337312 0.58461375 13 sp_4 -1.253938223 -0.88156275
-#> 32453 1 0.15337312 0.58461375 20 sp_5 -1.253938223 -0.88156275
-#> 32463 0 0.15337312 0.58461375 15 sp_6 -1.253938223 -0.88156275
-#> 32473 1 0.15337312 0.58461375 8 sp_7 -1.253938223 -0.88156275
-#> 32483 0 0.15337312 0.58461375 13 sp_8 -1.253938223 -0.88156275
-#> 32493 0 0.15337312 0.58461375 7 sp_9 -1.253938223 -0.88156275
-#> 32503 0 0.15337312 0.58461375 5 sp_10 -1.253938223 -0.88156275
-#> 32513 0 0.15337312 0.58461375 8 sp_11 -1.253938223 -0.88156275
-#> 32523 0 0.15337312 0.58461375 15 sp_12 -1.253938223 -0.88156275
-#> 32533 0 0.15337312 0.58461375 14 sp_13 -1.253938223 -0.88156275
-#> 32543 0 0.15337312 0.58461375 16 sp_14 -1.253938223 -0.88156275
-#> 32553 1 0.15337312 0.58461375 1 sp_15 -1.253938223 -0.88156275
-#> 32563 0 0.15337312 0.58461375 14 sp_16 -1.253938223 -0.88156275
-#> 32573 0 0.15337312 0.58461375 17 sp_17 -1.253938223 -0.88156275
-#> 32583 0 0.15337312 0.58461375 7 sp_18 -1.253938223 -0.88156275
-#> 32593 0 0.15337312 0.58461375 7 sp_19 -1.253938223 -0.88156275
-#> 32603 0 0.15337312 0.58461375 13 sp_20 -1.253938223 -0.88156275
-#> 32613 0 0.15337312 0.58461375 15 sp_21 -1.253938223 -0.88156275
-#> 32623 0 0.15337312 0.58461375 12 sp_22 -1.253938223 -0.88156275
-#> 32633 0 0.15337312 0.58461375 14 sp_23 -1.253938223 -0.88156275
-#> 32643 0 0.15337312 0.58461375 19 sp_24 -1.253938223 -0.88156275
-#> 32653 0 0.15337312 0.58461375 19 sp_25 -1.253938223 -0.88156275
-#> 32663 0 0.15337312 0.58461375 17 sp_26 -1.253938223 -0.88156275
-#> 32673 0 0.15337312 0.58461375 9 sp_27 -1.253938223 -0.88156275
-#> 32683 0 0.15337312 0.58461375 13 sp_28 -1.253938223 -0.88156275
-#> 32693 0 0.15337312 0.58461375 14 sp_29 -1.253938223 -0.88156275
-#> 32703 0 0.15337312 0.58461375 6 sp_30 -1.253938223 -0.88156275
-#> 33613 0 -1.13813694 0.12385424 1 sp_1 1.374599253 -0.17239352
-#> 33623 0 -1.13813694 0.12385424 16 sp_2 1.374599253 -0.17239352
-#> 33633 0 -1.13813694 0.12385424 8 sp_3 1.374599253 -0.17239352
-#> 33643 0 -1.13813694 0.12385424 5 sp_4 1.374599253 -0.17239352
-#> 33653 0 -1.13813694 0.12385424 10 sp_5 1.374599253 -0.17239352
-#> 33663 0 -1.13813694 0.12385424 9 sp_6 1.374599253 -0.17239352
-#> 33673 0 -1.13813694 0.12385424 5 sp_7 1.374599253 -0.17239352
-#> 33683 0 -1.13813694 0.12385424 14 sp_8 1.374599253 -0.17239352
-#> 33693 0 -1.13813694 0.12385424 19 sp_9 1.374599253 -0.17239352
-#> 33703 0 -1.13813694 0.12385424 1 sp_10 1.374599253 -0.17239352
-#> 33713 0 -1.13813694 0.12385424 16 sp_11 1.374599253 -0.17239352
-#> 33723 0 -1.13813694 0.12385424 6 sp_12 1.374599253 -0.17239352
-#> 33733 1 -1.13813694 0.12385424 20 sp_13 1.374599253 -0.17239352
-#> 33743 0 -1.13813694 0.12385424 8 sp_14 1.374599253 -0.17239352
-#> 33753 0 -1.13813694 0.12385424 14 sp_15 1.374599253 -0.17239352
-#> 33763 0 -1.13813694 0.12385424 14 sp_16 1.374599253 -0.17239352
-#> 33773 0 -1.13813694 0.12385424 8 sp_17 1.374599253 -0.17239352
-#> 33783 0 -1.13813694 0.12385424 11 sp_18 1.374599253 -0.17239352
-#> 33793 0 -1.13813694 0.12385424 20 sp_19 1.374599253 -0.17239352
-#> 33803 0 -1.13813694 0.12385424 5 sp_20 1.374599253 -0.17239352
-#> 33813 0 -1.13813694 0.12385424 14 sp_21 1.374599253 -0.17239352
-#> 33823 0 -1.13813694 0.12385424 1 sp_22 1.374599253 -0.17239352
-#> 33833 0 -1.13813694 0.12385424 1 sp_23 1.374599253 -0.17239352
-#> 33843 0 -1.13813694 0.12385424 5 sp_24 1.374599253 -0.17239352
-#> 33853 0 -1.13813694 0.12385424 3 sp_25 1.374599253 -0.17239352
-#> 33863 0 -1.13813694 0.12385424 4 sp_26 1.374599253 -0.17239352
-#> 33873 0 -1.13813694 0.12385424 3 sp_27 1.374599253 -0.17239352
-#> 33883 1 -1.13813694 0.12385424 14 sp_28 1.374599253 -0.17239352
-#> 33893 0 -1.13813694 0.12385424 18 sp_29 1.374599253 -0.17239352
-#> 33903 0 -1.13813694 0.12385424 10 sp_30 1.374599253 -0.17239352
-#> 34813 0 1.25381492 0.21594157 12 sp_1 1.307855946 -0.88732783
-#> 34823 1 1.25381492 0.21594157 16 sp_2 1.307855946 -0.88732783
-#> 34833 0 1.25381492 0.21594157 3 sp_3 1.307855946 -0.88732783
-#> 34843 1 1.25381492 0.21594157 12 sp_4 1.307855946 -0.88732783
-#> 34853 1 1.25381492 0.21594157 5 sp_5 1.307855946 -0.88732783
-#> 34863 1 1.25381492 0.21594157 13 sp_6 1.307855946 -0.88732783
-#> 34873 1 1.25381492 0.21594157 8 sp_7 1.307855946 -0.88732783
-#> 34883 1 1.25381492 0.21594157 17 sp_8 1.307855946 -0.88732783
-#> 34893 1 1.25381492 0.21594157 5 sp_9 1.307855946 -0.88732783
-#> 34903 0 1.25381492 0.21594157 19 sp_10 1.307855946 -0.88732783
-#> 34913 1 1.25381492 0.21594157 6 sp_11 1.307855946 -0.88732783
-#> 34923 1 1.25381492 0.21594157 2 sp_12 1.307855946 -0.88732783
-#> 34933 1 1.25381492 0.21594157 17 sp_13 1.307855946 -0.88732783
-#> 34943 1 1.25381492 0.21594157 17 sp_14 1.307855946 -0.88732783
-#> 34953 1 1.25381492 0.21594157 8 sp_15 1.307855946 -0.88732783
-#> 34963 0 1.25381492 0.21594157 19 sp_16 1.307855946 -0.88732783
-#> 34973 1 1.25381492 0.21594157 18 sp_17 1.307855946 -0.88732783
-#> 34983 0 1.25381492 0.21594157 19 sp_18 1.307855946 -0.88732783
-#> 34993 1 1.25381492 0.21594157 5 sp_19 1.307855946 -0.88732783
-#> 35003 0 1.25381492 0.21594157 14 sp_20 1.307855946 -0.88732783
-#> 35013 1 1.25381492 0.21594157 12 sp_21 1.307855946 -0.88732783
-#> 35023 0 1.25381492 0.21594157 1 sp_22 1.307855946 -0.88732783
-#> 35033 1 1.25381492 0.21594157 16 sp_23 1.307855946 -0.88732783
-#> 35043 0 1.25381492 0.21594157 18 sp_24 1.307855946 -0.88732783
-#> 35053 1 1.25381492 0.21594157 20 sp_25 1.307855946 -0.88732783
-#> 35063 1 1.25381492 0.21594157 7 sp_26 1.307855946 -0.88732783
-#> 35073 1 1.25381492 0.21594157 5 sp_27 1.307855946 -0.88732783
-#> 35083 0 1.25381492 0.21594157 10 sp_28 1.307855946 -0.88732783
-#> 35093 1 1.25381492 0.21594157 4 sp_29 1.307855946 -0.88732783
-#> 35103 1 1.25381492 0.21594157 8 sp_30 1.307855946 -0.88732783
-#> ff_n_unit ff_n_rep ff_Q ff_unit ff_rep_index1 ff_rep_index2 ff_rep_index3
-#> 1 900 4 1 1 1 901 1801
-#> 2 -99 4 0 2 2 902 1802
-#> 3 -99 4 0 3 3 903 1803
-#> 4 -99 4 0 4 4 904 1804
-#> 5 -99 4 1 5 5 905 1805
-#> 6 -99 4 0 6 6 906 1806
-#> 7 -99 4 0 7 7 907 1807
-#> 8 -99 4 0 8 8 908 1808
-#> 9 -99 4 0 9 9 909 1809
-#> 10 -99 4 0 10 10 910 1810
-#> 11 -99 4 1 11 11 911 1811
-#> 12 -99 4 0 12 12 912 1812
-#> 13 -99 4 1 13 13 913 1813
-#> 14 -99 4 0 14 14 914 1814
-#> 15 -99 4 0 15 15 915 1815
-#> 16 -99 4 0 16 16 916 1816
-#> 17 -99 4 1 17 17 917 1817
-#> 18 -99 4 0 18 18 918 1818
-#> 19 -99 4 0 19 19 919 1819
-#> 20 -99 4 1 20 20 920 1820
-#> 21 -99 4 0 21 21 921 1821
-#> 22 -99 4 0 22 22 922 1822
-#> 23 -99 4 0 23 23 923 1823
-#> 24 -99 4 1 24 24 924 1824
-#> 25 -99 4 0 25 25 925 1825
-#> 26 -99 4 0 26 26 926 1826
-#> 27 -99 4 1 27 27 927 1827
-#> 28 -99 4 0 28 28 928 1828
-#> 29 -99 4 0 29 29 929 1829
-#> 30 -99 4 0 30 30 930 1830
-#> 121 -99 4 0 31 31 931 1831
-#> 122 -99 4 0 32 32 932 1832
-#> 123 -99 4 0 33 33 933 1833
-#> 124 -99 4 0 34 34 934 1834
-#> 125 -99 4 0 35 35 935 1835
-#> 126 -99 4 1 36 36 936 1836
-#> 127 -99 4 1 37 37 937 1837
-#> 128 -99 4 0 38 38 938 1838
-#> 129 -99 4 0 39 39 939 1839
-#> 130 -99 4 0 40 40 940 1840
-#> 131 -99 4 1 41 41 941 1841
-#> 132 -99 4 1 42 42 942 1842
-#> 133 -99 4 0 43 43 943 1843
-#> 134 -99 4 0 44 44 944 1844
-#> 135 -99 4 0 45 45 945 1845
-#> 136 -99 4 1 46 46 946 1846
-#> 137 -99 4 0 47 47 947 1847
-#> 138 -99 4 1 48 48 948 1848
-#> 139 -99 4 1 49 49 949 1849
-#> 140 -99 4 0 50 50 950 1850
-#> 141 -99 4 0 51 51 951 1851
-#> 142 -99 4 1 52 52 952 1852
-#> 143 -99 4 1 53 53 953 1853
-#> 144 -99 4 0 54 54 954 1854
-#> 145 -99 4 0 55 55 955 1855
-#> 146 -99 4 0 56 56 956 1856
-#> 147 -99 4 0 57 57 957 1857
-#> 148 -99 4 0 58 58 958 1858
-#> 149 -99 4 1 59 59 959 1859
-#> 150 -99 4 0 60 60 960 1860
-#> 241 -99 4 0 61 61 961 1861
-#> 242 -99 4 1 62 62 962 1862
-#> 243 -99 4 0 63 63 963 1863
-#> 244 -99 4 1 64 64 964 1864
-#> 245 -99 4 1 65 65 965 1865
-#> 246 -99 4 1 66 66 966 1866
-#> 247 -99 4 1 67 67 967 1867
-#> 248 -99 4 0 68 68 968 1868
-#> 249 -99 4 1 69 69 969 1869
-#> 250 -99 4 1 70 70 970 1870
-#> 251 -99 4 0 71 71 971 1871
-#> 252 -99 4 1 72 72 972 1872
-#> 253 -99 4 0 73 73 973 1873
-#> 254 -99 4 0 74 74 974 1874
-#> 255 -99 4 1 75 75 975 1875
-#> 256 -99 4 1 76 76 976 1876
-#> 257 -99 4 0 77 77 977 1877
-#> 258 -99 4 0 78 78 978 1878
-#> 259 -99 4 0 79 79 979 1879
-#> 260 -99 4 0 80 80 980 1880
-#> 261 -99 4 1 81 81 981 1881
-#> 262 -99 4 0 82 82 982 1882
-#> 263 -99 4 0 83 83 983 1883
-#> 264 -99 4 0 84 84 984 1884
-#> 265 -99 4 0 85 85 985 1885
-#> 266 -99 4 0 86 86 986 1886
-#> 267 -99 4 1 87 87 987 1887
-#> 268 -99 4 0 88 88 988 1888
-#> 269 -99 4 1 89 89 989 1889
-#> 270 -99 4 1 90 90 990 1890
-#> 361 -99 4 0 91 91 991 1891
-#> 362 -99 4 0 92 92 992 1892
-#> 363 -99 4 0 93 93 993 1893
-#> 364 -99 4 0 94 94 994 1894
-#> 365 -99 4 1 95 95 995 1895
-#> 366 -99 4 0 96 96 996 1896
-#> 367 -99 4 0 97 97 997 1897
-#> 368 -99 4 0 98 98 998 1898
-#> 369 -99 4 0 99 99 999 1899
-#> 370 -99 4 0 100 100 1000 1900
-#> 371 -99 4 0 101 101 1001 1901
-#> 372 -99 4 0 102 102 1002 1902
-#> 373 -99 4 1 103 103 1003 1903
-#> 374 -99 4 0 104 104 1004 1904
-#> 375 -99 4 0 105 105 1005 1905
-#> 376 -99 4 0 106 106 1006 1906
-#> 377 -99 4 1 107 107 1007 1907
-#> 378 -99 4 1 108 108 1008 1908
-#> 379 -99 4 1 109 109 1009 1909
-#> 380 -99 4 0 110 110 1010 1910
-#> 381 -99 4 0 111 111 1011 1911
-#> 382 -99 4 0 112 112 1012 1912
-#> 383 -99 4 0 113 113 1013 1913
-#> 384 -99 4 0 114 114 1014 1914
-#> 385 -99 4 0 115 115 1015 1915
-#> 386 -99 4 0 116 116 1016 1916
-#> 387 -99 4 1 117 117 1017 1917
-#> 388 -99 4 0 118 118 1018 1918
-#> 389 -99 4 0 119 119 1019 1919
-#> 390 -99 4 0 120 120 1020 1920
-#> 481 -99 4 1 121 121 1021 1921
-#> 482 -99 4 0 122 122 1022 1922
-#> 483 -99 4 0 123 123 1023 1923
-#> 484 -99 4 0 124 124 1024 1924
-#> 485 -99 4 0 125 125 1025 1925
-#> 486 -99 4 0 126 126 1026 1926
-#> 487 -99 4 0 127 127 1027 1927
-#> 488 -99 4 0 128 128 1028 1928
-#> 489 -99 4 1 129 129 1029 1929
-#> 490 -99 4 0 130 130 1030 1930
-#> 491 -99 4 1 131 131 1031 1931
-#> 492 -99 4 0 132 132 1032 1932
-#> 493 -99 4 0 133 133 1033 1933
-#> 494 -99 4 1 134 134 1034 1934
-#> 495 -99 4 0 135 135 1035 1935
-#> 496 -99 4 0 136 136 1036 1936
-#> 497 -99 4 0 137 137 1037 1937
-#> 498 -99 4 0 138 138 1038 1938
-#> 499 -99 4 0 139 139 1039 1939
-#> 500 -99 4 0 140 140 1040 1940
-#> 501 -99 4 0 141 141 1041 1941
-#> 502 -99 4 0 142 142 1042 1942
-#> 503 -99 4 0 143 143 1043 1943
-#> 504 -99 4 0 144 144 1044 1944
-#> 505 -99 4 0 145 145 1045 1945
-#> 506 -99 4 0 146 146 1046 1946
-#> 507 -99 4 0 147 147 1047 1947
-#> 508 -99 4 0 148 148 1048 1948
-#> 509 -99 4 1 149 149 1049 1949
-#> 510 -99 4 0 150 150 1050 1950
-#> 601 -99 4 1 151 151 1051 1951
-#> 602 -99 4 0 152 152 1052 1952
-#> 603 -99 4 0 153 153 1053 1953
-#> 604 -99 4 1 154 154 1054 1954
-#> 605 -99 4 0 155 155 1055 1955
-#> 606 -99 4 0 156 156 1056 1956
-#> 607 -99 4 1 157 157 1057 1957
-#> 608 -99 4 1 158 158 1058 1958
-#> 609 -99 4 0 159 159 1059 1959
-#> 610 -99 4 1 160 160 1060 1960
-#> 611 -99 4 0 161 161 1061 1961
-#> 612 -99 4 1 162 162 1062 1962
-#> 613 -99 4 0 163 163 1063 1963
-#> 614 -99 4 0 164 164 1064 1964
-#> 615 -99 4 1 165 165 1065 1965
-#> 616 -99 4 1 166 166 1066 1966
-#> 617 -99 4 0 167 167 1067 1967
-#> 618 -99 4 0 168 168 1068 1968
-#> 619 -99 4 0 169 169 1069 1969
-#> 620 -99 4 0 170 170 1070 1970
-#> 621 -99 4 0 171 171 1071 1971
-#> 622 -99 4 1 172 172 1072 1972
-#> 623 -99 4 0 173 173 1073 1973
-#> 624 -99 4 0 174 174 1074 1974
-#> 625 -99 4 0 175 175 1075 1975
-#> 626 -99 4 0 176 176 1076 1976
-#> 627 -99 4 0 177 177 1077 1977
-#> 628 -99 4 1 178 178 1078 1978
-#> 629 -99 4 0 179 179 1079 1979
-#> 630 -99 4 0 180 180 1080 1980
-#> 721 -99 4 0 181 181 1081 1981
-#> 722 -99 4 1 182 182 1082 1982
-#> 723 -99 4 0 183 183 1083 1983
-#> 724 -99 4 1 184 184 1084 1984
-#> 725 -99 4 1 185 185 1085 1985
-#> 726 -99 4 0 186 186 1086 1986
-#> 727 -99 4 0 187 187 1087 1987
-#> 728 -99 4 0 188 188 1088 1988
-#> 729 -99 4 0 189 189 1089 1989
-#> 730 -99 4 0 190 190 1090 1990
-#> 731 -99 4 0 191 191 1091 1991
-#> 732 -99 4 0 192 192 1092 1992
-#> 733 -99 4 0 193 193 1093 1993
-#> 734 -99 4 0 194 194 1094 1994
-#> 735 -99 4 0 195 195 1095 1995
-#> 736 -99 4 0 196 196 1096 1996
-#> 737 -99 4 0 197 197 1097 1997
-#> 738 -99 4 1 198 198 1098 1998
-#> 739 -99 4 0 199 199 1099 1999
-#> 740 -99 4 0 200 200 1100 2000
-#> 741 -99 4 1 201 201 1101 2001
-#> 742 -99 4 0 202 202 1102 2002
-#> 743 -99 4 1 203 203 1103 2003
-#> 744 -99 4 0 204 204 1104 2004
-#> 745 -99 4 0 205 205 1105 2005
-#> 746 -99 4 0 206 206 1106 2006
-#> 747 -99 4 1 207 207 1107 2007
-#> 748 -99 4 0 208 208 1108 2008
-#> 749 -99 4 0 209 209 1109 2009
-#> 750 -99 4 0 210 210 1110 2010
-#> 841 -99 4 1 211 211 1111 2011
-#> 842 -99 4 0 212 212 1112 2012
-#> 843 -99 4 0 213 213 1113 2013
-#> 844 -99 4 0 214 214 1114 2014
-#> 845 -99 4 0 215 215 1115 2015
-#> 846 -99 4 0 216 216 1116 2016
-#> 847 -99 4 0 217 217 1117 2017
-#> 848 -99 4 0 218 218 1118 2018
-#> 849 -99 4 0 219 219 1119 2019
-#> 850 -99 4 1 220 220 1120 2020
-#> 851 -99 4 0 221 221 1121 2021
-#> 852 -99 4 1 222 222 1122 2022
-#> 853 -99 4 0 223 223 1123 2023
-#> 854 -99 4 0 224 224 1124 2024
-#> 855 -99 4 0 225 225 1125 2025
-#> 856 -99 4 0 226 226 1126 2026
-#> 857 -99 4 0 227 227 1127 2027
-#> 858 -99 4 0 228 228 1128 2028
-#> 859 -99 4 1 229 229 1129 2029
-#> 860 -99 4 0 230 230 1130 2030
-#> 861 -99 4 0 231 231 1131 2031
-#> 862 -99 4 0 232 232 1132 2032
-#> 863 -99 4 0 233 233 1133 2033
-#> 864 -99 4 1 234 234 1134 2034
-#> 865 -99 4 0 235 235 1135 2035
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-#> 2424 -99 4 1 624 624 1524 2424
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-#> 2427 -99 4 0 627 627 1527 2427
-#> 2428 -99 4 0 628 628 1528 2428
-#> 2429 -99 4 1 629 629 1529 2429
-#> 2430 -99 4 0 630 630 1530 2430
-#> 2521 -99 4 1 631 631 1531 2431
-#> 2522 -99 4 0 632 632 1532 2432
-#> 2523 -99 4 0 633 633 1533 2433
-#> 2524 -99 4 1 634 634 1534 2434
-#> 2525 -99 4 0 635 635 1535 2435
-#> 2526 -99 4 1 636 636 1536 2436
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-#> 2528 -99 4 1 638 638 1538 2438
-#> 2529 -99 4 0 639 639 1539 2439
-#> 2530 -99 4 0 640 640 1540 2440
-#> 2531 -99 4 0 641 641 1541 2441
-#> 2532 -99 4 0 642 642 1542 2442
-#> 2533 -99 4 0 643 643 1543 2443
-#> 2534 -99 4 0 644 644 1544 2444
-#> 2535 -99 4 1 645 645 1545 2445
-#> 2536 -99 4 0 646 646 1546 2446
-#> 2537 -99 4 0 647 647 1547 2447
-#> 2538 -99 4 1 648 648 1548 2448
-#> 2539 -99 4 0 649 649 1549 2449
-#> 2540 -99 4 0 650 650 1550 2450
-#> 2541 -99 4 1 651 651 1551 2451
-#> 2542 -99 4 0 652 652 1552 2452
-#> 2543 -99 4 0 653 653 1553 2453
-#> 2544 -99 4 0 654 654 1554 2454
-#> 2545 -99 4 0 655 655 1555 2455
-#> 2546 -99 4 0 656 656 1556 2456
-#> 2547 -99 4 0 657 657 1557 2457
-#> 2548 -99 4 1 658 658 1558 2458
-#> 2549 -99 4 0 659 659 1559 2459
-#> 2550 -99 4 0 660 660 1560 2460
-#> 2641 -99 4 0 661 661 1561 2461
-#> 2642 -99 4 0 662 662 1562 2462
-#> 2643 -99 4 0 663 663 1563 2463
-#> 2644 -99 4 1 664 664 1564 2464
-#> 2645 -99 4 1 665 665 1565 2465
-#> 2646 -99 4 0 666 666 1566 2466
-#> 2647 -99 4 0 667 667 1567 2467
-#> 2648 -99 4 0 668 668 1568 2468
-#> 2649 -99 4 0 669 669 1569 2469
-#> 2650 -99 4 0 670 670 1570 2470
-#> 2651 -99 4 0 671 671 1571 2471
-#> 2652 -99 4 0 672 672 1572 2472
-#> 2653 -99 4 0 673 673 1573 2473
-#> 2654 -99 4 0 674 674 1574 2474
-#> 2655 -99 4 0 675 675 1575 2475
-#> 2656 -99 4 0 676 676 1576 2476
-#> 2657 -99 4 0 677 677 1577 2477
-#> 2658 -99 4 0 678 678 1578 2478
-#> 2659 -99 4 1 679 679 1579 2479
-#> 2660 -99 4 0 680 680 1580 2480
-#> 2661 -99 4 0 681 681 1581 2481
-#> 2662 -99 4 0 682 682 1582 2482
-#> 2663 -99 4 0 683 683 1583 2483
-#> 2664 -99 4 0 684 684 1584 2484
-#> 2665 -99 4 0 685 685 1585 2485
-#> 2666 -99 4 0 686 686 1586 2486
-#> 2667 -99 4 1 687 687 1587 2487
-#> 2668 -99 4 0 688 688 1588 2488
-#> 2669 -99 4 0 689 689 1589 2489
-#> 2670 -99 4 1 690 690 1590 2490
-#> 2761 -99 4 0 691 691 1591 2491
-#> 2762 -99 4 0 692 692 1592 2492
-#> 2763 -99 4 0 693 693 1593 2493
-#> 2764 -99 4 0 694 694 1594 2494
-#> 2765 -99 4 0 695 695 1595 2495
-#> 2766 -99 4 0 696 696 1596 2496
-#> 2767 -99 4 0 697 697 1597 2497
-#> 2768 -99 4 0 698 698 1598 2498
-#> 2769 -99 4 0 699 699 1599 2499
-#> 2770 -99 4 0 700 700 1600 2500
-#> 2771 -99 4 0 701 701 1601 2501
-#> 2772 -99 4 0 702 702 1602 2502
-#> 2773 -99 4 0 703 703 1603 2503
-#> 2774 -99 4 0 704 704 1604 2504
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-#> 32663 -99 -99 -99 836 -99 -99 -99
-#> 32673 -99 -99 -99 837 -99 -99 -99
-#> 32683 -99 -99 -99 838 -99 -99 -99
-#> 32693 -99 -99 -99 839 -99 -99 -99
-#> 32703 -99 -99 -99 840 -99 -99 -99
-#> 33613 -99 -99 -99 841 -99 -99 -99
-#> 33623 -99 -99 -99 842 -99 -99 -99
-#> 33633 -99 -99 -99 843 -99 -99 -99
-#> 33643 -99 -99 -99 844 -99 -99 -99
-#> 33653 -99 -99 -99 845 -99 -99 -99
-#> 33663 -99 -99 -99 846 -99 -99 -99
-#> 33673 -99 -99 -99 847 -99 -99 -99
-#> 33683 -99 -99 -99 848 -99 -99 -99
-#> 33693 -99 -99 -99 849 -99 -99 -99
-#> 33703 -99 -99 -99 850 -99 -99 -99
-#> 33713 -99 -99 -99 851 -99 -99 -99
-#> 33723 -99 -99 -99 852 -99 -99 -99
-#> 33733 -99 -99 -99 853 -99 -99 -99
-#> 33743 -99 -99 -99 854 -99 -99 -99
-#> 33753 -99 -99 -99 855 -99 -99 -99
-#> 33763 -99 -99 -99 856 -99 -99 -99
-#> 33773 -99 -99 -99 857 -99 -99 -99
-#> 33783 -99 -99 -99 858 -99 -99 -99
-#> 33793 -99 -99 -99 859 -99 -99 -99
-#> 33803 -99 -99 -99 860 -99 -99 -99
-#> 33813 -99 -99 -99 861 -99 -99 -99
-#> 33823 -99 -99 -99 862 -99 -99 -99
-#> 33833 -99 -99 -99 863 -99 -99 -99
-#> 33843 -99 -99 -99 864 -99 -99 -99
-#> 33853 -99 -99 -99 865 -99 -99 -99
-#> 33863 -99 -99 -99 866 -99 -99 -99
-#> 33873 -99 -99 -99 867 -99 -99 -99
-#> 33883 -99 -99 -99 868 -99 -99 -99
-#> 33893 -99 -99 -99 869 -99 -99 -99
-#> 33903 -99 -99 -99 870 -99 -99 -99
-#> 34813 -99 -99 -99 871 -99 -99 -99
-#> 34823 -99 -99 -99 872 -99 -99 -99
-#> 34833 -99 -99 -99 873 -99 -99 -99
-#> 34843 -99 -99 -99 874 -99 -99 -99
-#> 34853 -99 -99 -99 875 -99 -99 -99
-#> 34863 -99 -99 -99 876 -99 -99 -99
-#> 34873 -99 -99 -99 877 -99 -99 -99
-#> 34883 -99 -99 -99 878 -99 -99 -99
-#> 34893 -99 -99 -99 879 -99 -99 -99
-#> 34903 -99 -99 -99 880 -99 -99 -99
-#> 34913 -99 -99 -99 881 -99 -99 -99
-#> 34923 -99 -99 -99 882 -99 -99 -99
-#> 34933 -99 -99 -99 883 -99 -99 -99
-#> 34943 -99 -99 -99 884 -99 -99 -99
-#> 34953 -99 -99 -99 885 -99 -99 -99
-#> 34963 -99 -99 -99 886 -99 -99 -99
-#> 34973 -99 -99 -99 887 -99 -99 -99
-#> 34983 -99 -99 -99 888 -99 -99 -99
-#> 34993 -99 -99 -99 889 -99 -99 -99
-#> 35003 -99 -99 -99 890 -99 -99 -99
-#> 35013 -99 -99 -99 891 -99 -99 -99
-#> 35023 -99 -99 -99 892 -99 -99 -99
-#> 35033 -99 -99 -99 893 -99 -99 -99
-#> 35043 -99 -99 -99 894 -99 -99 -99
-#> 35053 -99 -99 -99 895 -99 -99 -99
-#> 35063 -99 -99 -99 896 -99 -99 -99
-#> 35073 -99 -99 -99 897 -99 -99 -99
-#> 35083 -99 -99 -99 898 -99 -99 -99
-#> 35093 -99 -99 -99 899 -99 -99 -99
-#> 35103 -99 -99 -99 900 -99 -99 -99
-#> ff_rep_index4
-#> 1 2701
-#> 2 2702
-#> 3 2703
-#> 4 2704
-#> 5 2705
-#> 6 2706
-#> 7 2707
-#> 8 2708
-#> 9 2709
-#> 10 2710
-#> 11 2711
-#> 12 2712
-#> 13 2713
-#> 14 2714
-#> 15 2715
-#> 16 2716
-#> 17 2717
-#> 18 2718
-#> 19 2719
-#> 20 2720
-#> 21 2721
-#> 22 2722
-#> 23 2723
-#> 24 2724
-#> 25 2725
-#> 26 2726
-#> 27 2727
-#> 28 2728
-#> 29 2729
-#> 30 2730
-#> 121 2731
-#> 122 2732
-#> 123 2733
-#> 124 2734
-#> 125 2735
-#> 126 2736
-#> 127 2737
-#> 128 2738
-#> 129 2739
-#> 130 2740
-#> 131 2741
-#> 132 2742
-#> 133 2743
-#> 134 2744
-#> 135 2745
-#> 136 2746
-#> 137 2747
-#> 138 2748
-#> 139 2749
-#> 140 2750
-#> 141 2751
-#> 142 2752
-#> 143 2753
-#> 144 2754
-#> 145 2755
-#> 146 2756
-#> 147 2757
-#> 148 2758
-#> 149 2759
-#> 150 2760
-#> 241 2761
-#> 242 2762
-#> 243 2763
-#> 244 2764
-#> 245 2765
-#> 246 2766
-#> 247 2767
-#> 248 2768
-#> 249 2769
-#> 250 2770
-#> 251 2771
-#> 252 2772
-#> 253 2773
-#> 254 2774
-#> 255 2775
-#> 256 2776
-#> 257 2777
-#> 258 2778
-#> 259 2779
-#> 260 2780
-#> 261 2781
-#> 262 2782
-#> 263 2783
-#> 264 2784
-#> 265 2785
-#> 266 2786
-#> 267 2787
-#> 268 2788
-#> 269 2789
-#> 270 2790
-#> 361 2791
-#> 362 2792
-#> 363 2793
-#> 364 2794
-#> 365 2795
-#> 366 2796
-#> 367 2797
-#> 368 2798
-#> 369 2799
-#> 370 2800
-#> 371 2801
-#> 372 2802
-#> 373 2803
-#> 374 2804
-#> 375 2805
-#> 376 2806
-#> 377 2807
-#> 378 2808
-#> 379 2809
-#> 380 2810
-#> 381 2811
-#> 382 2812
-#> 383 2813
-#> 384 2814
-#> 385 2815
-#> 386 2816
-#> 387 2817
-#> 388 2818
-#> 389 2819
-#> 390 2820
-#> 481 2821
-#> 482 2822
-#> 483 2823
-#> 484 2824
-#> 485 2825
-#> 486 2826
-#> 487 2827
-#> 488 2828
-#> 489 2829
-#> 490 2830
-#> 491 2831
-#> 492 2832
-#> 493 2833
-#> 494 2834
-#> 495 2835
-#> 496 2836
-#> 497 2837
-#> 498 2838
-#> 499 2839
-#> 500 2840
-#> 501 2841
-#> 502 2842
-#> 503 2843
-#> 504 2844
-#> 505 2845
-#> 506 2846
-#> 507 2847
-#> 508 2848
-#> 509 2849
-#> 510 2850
-#> 601 2851
-#> 602 2852
-#> 603 2853
-#> 604 2854
-#> 605 2855
-#> 606 2856
-#> 607 2857
-#> 608 2858
-#> 609 2859
-#> 610 2860
-#> 611 2861
-#> 612 2862
-#> 613 2863
-#> 614 2864
-#> 615 2865
-#> 616 2866
-#> 617 2867
-#> 618 2868
-#> 619 2869
-#> 620 2870
-#> 621 2871
-#> 622 2872
-#> 623 2873
-#> 624 2874
-#> 625 2875
-#> 626 2876
-#> 627 2877
-#> 628 2878
-#> 629 2879
-#> 630 2880
-#> 721 2881
-#> 722 2882
-#> 723 2883
-#> 724 2884
-#> 725 2885
-#> 726 2886
-#> 727 2887
-#> 728 2888
-#> 729 2889
-#> 730 2890
-#> 731 2891
-#> 732 2892
-#> 733 2893
-#> 734 2894
-#> 735 2895
-#> 736 2896
-#> 737 2897
-#> 738 2898
-#> 739 2899
-#> 740 2900
-#> 741 2901
-#> 742 2902
-#> 743 2903
-#> 744 2904
-#> 745 2905
-#> 746 2906
-#> 747 2907
-#> 748 2908
-#> 749 2909
-#> 750 2910
-#> 841 2911
-#> 842 2912
-#> 843 2913
-#> 844 2914
-#> 845 2915
-#> 846 2916
-#> 847 2917
-#> 848 2918
-#> 849 2919
-#> 850 2920
-#> 851 2921
-#> 852 2922
-#> 853 2923
-#> 854 2924
-#> 855 2925
-#> 856 2926
-#> 857 2927
-#> 858 2928
-#> 859 2929
-#> 860 2930
-#> 861 2931
-#> 862 2932
-#> 863 2933
-#> 864 2934
-#> 865 2935
-#> 866 2936
-#> 867 2937
-#> 868 2938
-#> 869 2939
-#> 870 2940
-#> 961 2941
-#> 962 2942
-#> 963 2943
-#> 964 2944
-#> 965 2945
-#> 966 2946
-#> 967 2947
-#> 968 2948
-#> 969 2949
-#> 970 2950
-#> 971 2951
-#> 972 2952
-#> 973 2953
-#> 974 2954
-#> 975 2955
-#> 976 2956
-#> 977 2957
-#> 978 2958
-#> 979 2959
-#> 980 2960
-#> 981 2961
-#> 982 2962
-#> 983 2963
-#> 984 2964
-#> 985 2965
-#> 986 2966
-#> 987 2967
-#> 988 2968
-#> 989 2969
-#> 990 2970
-#> 1081 2971
-#> 1082 2972
-#> 1083 2973
-#> 1084 2974
-#> 1085 2975
-#> 1086 2976
-#> 1087 2977
-#> 1088 2978
-#> 1089 2979
-#> 1090 2980
-#> 1091 2981
-#> 1092 2982
-#> 1093 2983
-#> 1094 2984
-#> 1095 2985
-#> 1096 2986
-#> 1097 2987
-#> 1098 2988
-#> 1099 2989
-#> 1100 2990
-#> 1101 2991
-#> 1102 2992
-#> 1103 2993
-#> 1104 2994
-#> 1105 2995
-#> 1106 2996
-#> 1107 2997
-#> 1108 2998
-#> 1109 2999
-#> 1110 3000
-#> 1201 3001
-#> 1202 3002
-#> 1203 3003
-#> 1204 3004
-#> 1205 3005
-#> 1206 3006
-#> 1207 3007
-#> 1208 3008
-#> 1209 3009
-#> 1210 3010
-#> 1211 3011
-#> 1212 3012
-#> 1213 3013
-#> 1214 3014
-#> 1215 3015
-#> 1216 3016
-#> 1217 3017
-#> 1218 3018
-#> 1219 3019
-#> 1220 3020
-#> 1221 3021
-#> 1222 3022
-#> 1223 3023
-#> 1224 3024
-#> 1225 3025
-#> 1226 3026
-#> 1227 3027
-#> 1228 3028
-#> 1229 3029
-#> 1230 3030
-#> 1321 3031
-#> 1322 3032
-#> 1323 3033
-#> 1324 3034
-#> 1325 3035
-#> 1326 3036
-#> 1327 3037
-#> 1328 3038
-#> 1329 3039
-#> 1330 3040
-#> 1331 3041
-#> 1332 3042
-#> 1333 3043
-#> 1334 3044
-#> 1335 3045
-#> 1336 3046
-#> 1337 3047
-#> 1338 3048
-#> 1339 3049
-#> 1340 3050
-#> 1341 3051
-#> 1342 3052
-#> 1343 3053
-#> 1344 3054
-#> 1345 3055
-#> 1346 3056
-#> 1347 3057
-#> 1348 3058
-#> 1349 3059
-#> 1350 3060
-#> 1441 3061
-#> 1442 3062
-#> 1443 3063
-#> 1444 3064
-#> 1445 3065
-#> 1446 3066
-#> 1447 3067
-#> 1448 3068
-#> 1449 3069
-#> 1450 3070
-#> 1451 3071
-#> 1452 3072
-#> 1453 3073
-#> 1454 3074
-#> 1455 3075
-#> 1456 3076
-#> 1457 3077
-#> 1458 3078
-#> 1459 3079
-#> 1460 3080
-#> 1461 3081
-#> 1462 3082
-#> 1463 3083
-#> 1464 3084
-#> 1465 3085
-#> 1466 3086
-#> 1467 3087
-#> 1468 3088
-#> 1469 3089
-#> 1470 3090
-#> 1561 3091
-#> 1562 3092
-#> 1563 3093
-#> 1564 3094
-#> 1565 3095
-#> 1566 3096
-#> 1567 3097
-#> 1568 3098
-#> 1569 3099
-#> 1570 3100
-#> 1571 3101
-#> 1572 3102
-#> 1573 3103
-#> 1574 3104
-#> 1575 3105
-#> 1576 3106
-#> 1577 3107
-#> 1578 3108
-#> 1579 3109
-#> 1580 3110
-#> 1581 3111
-#> 1582 3112
-#> 1583 3113
-#> 1584 3114
-#> 1585 3115
-#> 1586 3116
-#> 1587 3117
-#> 1588 3118
-#> 1589 3119
-#> 1590 3120
-#> 1681 3121
-#> 1682 3122
-#> 1683 3123
-#> 1684 3124
-#> 1685 3125
-#> 1686 3126
-#> 1687 3127
-#> 1688 3128
-#> 1689 3129
-#> 1690 3130
-#> 1691 3131
-#> 1692 3132
-#> 1693 3133
-#> 1694 3134
-#> 1695 3135
-#> 1696 3136
-#> 1697 3137
-#> 1698 3138
-#> 1699 3139
-#> 1700 3140
-#> 1701 3141
-#> 1702 3142
-#> 1703 3143
-#> 1704 3144
-#> 1705 3145
-#> 1706 3146
-#> 1707 3147
-#> 1708 3148
-#> 1709 3149
-#> 1710 3150
-#> 1801 3151
-#> 1802 3152
-#> 1803 3153
-#> 1804 3154
-#> 1805 3155
-#> 1806 3156
-#> 1807 3157
-#> 1808 3158
-#> 1809 3159
-#> 1810 3160
-#> 1811 3161
-#> 1812 3162
-#> 1813 3163
-#> 1814 3164
-#> 1815 3165
-#> 1816 3166
-#> 1817 3167
-#> 1818 3168
-#> 1819 3169
-#> 1820 3170
-#> 1821 3171
-#> 1822 3172
-#> 1823 3173
-#> 1824 3174
-#> 1825 3175
-#> 1826 3176
-#> 1827 3177
-#> 1828 3178
-#> 1829 3179
-#> 1830 3180
-#> 1921 3181
-#> 1922 3182
-#> 1923 3183
-#> 1924 3184
-#> 1925 3185
-#> 1926 3186
-#> 1927 3187
-#> 1928 3188
-#> 1929 3189
-#> 1930 3190
-#> 1931 3191
-#> 1932 3192
-#> 1933 3193
-#> 1934 3194
-#> 1935 3195
-#> 1936 3196
-#> 1937 3197
-#> 1938 3198
-#> 1939 3199
-#> 1940 3200
-#> 1941 3201
-#> 1942 3202
-#> 1943 3203
-#> 1944 3204
-#> 1945 3205
-#> 1946 3206
-#> 1947 3207
-#> 1948 3208
-#> 1949 3209
-#> 1950 3210
-#> 2041 3211
-#> 2042 3212
-#> 2043 3213
-#> 2044 3214
-#> 2045 3215
-#> 2046 3216
-#> 2047 3217
-#> 2048 3218
-#> 2049 3219
-#> 2050 3220
-#> 2051 3221
-#> 2052 3222
-#> 2053 3223
-#> 2054 3224
-#> 2055 3225
-#> 2056 3226
-#> 2057 3227
-#> 2058 3228
-#> 2059 3229
-#> 2060 3230
-#> 2061 3231
-#> 2062 3232
-#> 2063 3233
-#> 2064 3234
-#> 2065 3235
-#> 2066 3236
-#> 2067 3237
-#> 2068 3238
-#> 2069 3239
-#> 2070 3240
-#> 2161 3241
-#> 2162 3242
-#> 2163 3243
-#> 2164 3244
-#> 2165 3245
-#> 2166 3246
-#> 2167 3247
-#> 2168 3248
-#> 2169 3249
-#> 2170 3250
-#> 2171 3251
-#> 2172 3252
-#> 2173 3253
-#> 2174 3254
-#> 2175 3255
-#> 2176 3256
-#> 2177 3257
-#> 2178 3258
-#> 2179 3259
-#> 2180 3260
-#> 2181 3261
-#> 2182 3262
-#> 2183 3263
-#> 2184 3264
-#> 2185 3265
-#> 2186 3266
-#> 2187 3267
-#> 2188 3268
-#> 2189 3269
-#> 2190 3270
-#> 2281 3271
-#> 2282 3272
-#> 2283 3273
-#> 2284 3274
-#> 2285 3275
-#> 2286 3276
-#> 2287 3277
-#> 2288 3278
-#> 2289 3279
-#> 2290 3280
-#> 2291 3281
-#> 2292 3282
-#> 2293 3283
-#> 2294 3284
-#> 2295 3285
-#> 2296 3286
-#> 2297 3287
-#> 2298 3288
-#> 2299 3289
-#> 2300 3290
-#> 2301 3291
-#> 2302 3292
-#> 2303 3293
-#> 2304 3294
-#> 2305 3295
-#> 2306 3296
-#> 2307 3297
-#> 2308 3298
-#> 2309 3299
-#> 2310 3300
-#> 2401 3301
-#> 2402 3302
-#> 2403 3303
-#> 2404 3304
-#> 2405 3305
-#> 2406 3306
-#> 2407 3307
-#> 2408 3308
-#> 2409 3309
-#> 2410 3310
-#> 2411 3311
-#> 2412 3312
-#> 2413 3313
-#> 2414 3314
-#> 2415 3315
-#> 2416 3316
-#> 2417 3317
-#> 2418 3318
-#> 2419 3319
-#> 2420 3320
-#> 2421 3321
-#> 2422 3322
-#> 2423 3323
-#> 2424 3324
-#> 2425 3325
-#> 2426 3326
-#> 2427 3327
-#> 2428 3328
-#> 2429 3329
-#> 2430 3330
-#> 2521 3331
-#> 2522 3332
-#> 2523 3333
-#> 2524 3334
-#> 2525 3335
-#> 2526 3336
-#> 2527 3337
-#> 2528 3338
-#> 2529 3339
-#> 2530 3340
-#> 2531 3341
-#> 2532 3342
-#> 2533 3343
-#> 2534 3344
-#> 2535 3345
-#> 2536 3346
-#> 2537 3347
-#> 2538 3348
-#> 2539 3349
-#> 2540 3350
-#> 2541 3351
-#> 2542 3352
-#> 2543 3353
-#> 2544 3354
-#> 2545 3355
-#> 2546 3356
-#> 2547 3357
-#> 2548 3358
-#> 2549 3359
-#> 2550 3360
-#> 2641 3361
-#> 2642 3362
-#> 2643 3363
-#> 2644 3364
-#> 2645 3365
-#> 2646 3366
-#> 2647 3367
-#> 2648 3368
-#> 2649 3369
-#> 2650 3370
-#> 2651 3371
-#> 2652 3372
-#> 2653 3373
-#> 2654 3374
-#> 2655 3375
-#> 2656 3376
-#> 2657 3377
-#> 2658 3378
-#> 2659 3379
-#> 2660 3380
-#> 2661 3381
-#> 2662 3382
-#> 2663 3383
-#> 2664 3384
-#> 2665 3385
-#> 2666 3386
-#> 2667 3387
-#> 2668 3388
-#> 2669 3389
-#> 2670 3390
-#> 2761 3391
-#> 2762 3392
-#> 2763 3393
-#> 2764 3394
-#> 2765 3395
-#> 2766 3396
-#> 2767 3397
-#> 2768 3398
-#> 2769 3399
-#> 2770 3400
-#> 2771 3401
-#> 2772 3402
-#> 2773 3403
-#> 2774 3404
-#> 2775 3405
-#> 2776 3406
-#> 2777 3407
-#> 2778 3408
-#> 2779 3409
-#> 2780 3410
-#> 2781 3411
-#> 2782 3412
-#> 2783 3413
-#> 2784 3414
-#> 2785 3415
-#> 2786 3416
-#> 2787 3417
-#> 2788 3418
-#> 2789 3419
-#> 2790 3420
-#> 2881 3421
-#> 2882 3422
-#> 2883 3423
-#> 2884 3424
-#> 2885 3425
-#> 2886 3426
-#> 2887 3427
-#> 2888 3428
-#> 2889 3429
-#> 2890 3430
-#> 2891 3431
-#> 2892 3432
-#> 2893 3433
-#> 2894 3434
-#> 2895 3435
-#> 2896 3436
-#> 2897 3437
-#> 2898 3438
-#> 2899 3439
-#> 2900 3440
-#> 2901 3441
-#> 2902 3442
-#> 2903 3443
-#> 2904 3444
-#> 2905 3445
-#> 2906 3446
-#> 2907 3447
-#> 2908 3448
-#> 2909 3449
-#> 2910 3450
-#> 3001 3451
-#> 3002 3452
-#> 3003 3453
-#> 3004 3454
-#> 3005 3455
-#> 3006 3456
-#> 3007 3457
-#> 3008 3458
-#> 3009 3459
-#> 3010 3460
-#> 3011 3461
-#> 3012 3462
-#> 3013 3463
-#> 3014 3464
-#> 3015 3465
-#> 3016 3466
-#> 3017 3467
-#> 3018 3468
-#> 3019 3469
-#> 3020 3470
-#> 3021 3471
-#> 3022 3472
-#> 3023 3473
-#> 3024 3474
-#> 3025 3475
-#> 3026 3476
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-#> 3028 3478
-#> 3029 3479
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-#> 3121 3481
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-#> 3126 3486
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-#> 3140 3500
-#> 3141 3501
-#> 3142 3502
-#> 3143 3503
-#> 3144 3504
-#> 3145 3505
-#> 3146 3506
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-#> 3148 3508
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-#> 3150 3510
-#> 3241 3511
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-#> 3243 3513
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-#> 3248 3518
-#> 3249 3519
-#> 3250 3520
-#> 3251 3521
-#> 3252 3522
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-#> 3254 3524
-#> 3255 3525
-#> 3256 3526
-#> 3257 3527
-#> 3258 3528
-#> 3259 3529
-#> 3260 3530
-#> 3261 3531
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-#> 3265 3535
-#> 3266 3536
-#> 3267 3537
-#> 3268 3538
-#> 3269 3539
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-#> 3361 3541
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-#> 3365 3545
-#> 3366 3546
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-#> 3368 3548
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-#> 3385 3565
-#> 3386 3566
-#> 3387 3567
-#> 3388 3568
-#> 3389 3569
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-#> 3485 3575
-#> 3486 3576
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-#> 3489 3579
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-#> 31473 -99
-#> 31483 -99
-#> 31493 -99
-#> 31503 -99
-#> 32413 -99
-#> 32423 -99
-#> 32433 -99
-#> 32443 -99
-#> 32453 -99
-#> 32463 -99
-#> 32473 -99
-#> 32483 -99
-#> 32493 -99
-#> 32503 -99
-#> 32513 -99
-#> 32523 -99
-#> 32533 -99
-#> 32543 -99
-#> 32553 -99
-#> 32563 -99
-#> 32573 -99
-#> 32583 -99
-#> 32593 -99
-#> 32603 -99
-#> 32613 -99
-#> 32623 -99
-#> 32633 -99
-#> 32643 -99
-#> 32653 -99
-#> 32663 -99
-#> 32673 -99
-#> 32683 -99
-#> 32693 -99
-#> 32703 -99
-#> 33613 -99
-#> 33623 -99
-#> 33633 -99
-#> 33643 -99
-#> 33653 -99
-#> 33663 -99
-#> 33673 -99
-#> 33683 -99
-#> 33693 -99
-#> 33703 -99
-#> 33713 -99
-#> 33723 -99
-#> 33733 -99
-#> 33743 -99
-#> 33753 -99
-#> 33763 -99
-#> 33773 -99
-#> 33783 -99
-#> 33793 -99
-#> 33803 -99
-#> 33813 -99
-#> 33823 -99
-#> 33833 -99
-#> 33843 -99
-#> 33853 -99
-#> 33863 -99
-#> 33873 -99
-#> 33883 -99
-#> 33893 -99
-#> 33903 -99
-#> 34813 -99
-#> 34823 -99
-#> 34833 -99
-#> 34843 -99
-#> 34853 -99
-#> 34863 -99
-#> 34873 -99
-#> 34883 -99
-#> 34893 -99
-#> 34903 -99
-#> 34913 -99
-#> 34923 -99
-#> 34933 -99
-#> 34943 -99
-#> 34953 -99
-#> 34963 -99
-#> 34973 -99
-#> 34983 -99
-#> 34993 -99
-#> 35003 -99
-#> 35013 -99
-#> 35023 -99
-#> 35033 -99
-#> 35043 -99
-#> 35053 -99
-#> 35063 -99
-#> 35073 -99
-#> 35083 -99
-#> 35093 -99
-#> 35103 -99
-#>
-#> $n_rep
-#> [1] 4
-#>
-#> $type
-#> [1] "single"
-#>
-#> $unit_covs
-#> [1] "uc1" "uc2" "grp" "species"
-#>
-#> $event_covs
-#> [1] "ec1" "ec2"
-#>
-#> attr(,"class")
-#> [1] "list" "flocker_data"
-
R/make_occupancy_lpmf.R
- make_forward_colex.Rd
Create Stan code for forward_colex function, an implementation of the - forward algorithm for use in colex models.
-make_forward_colex()
Character string of Stan code corresponding to forward_colex
-R/make_occupancy_lpmf.R
- make_occupancy_augmented_lpmf.Rd
Create Stan code for likelihood function occupancy_augmented_lpmf for -rep-varying model.
-make_occupancy_augmented_lpmf(max_rep)
Literal integer maximum number of repeated sampling events at -any unit.
Character string of Stan code corresponding to occupancy_V_lpmf
-R/make_occupancy_lpmf.R
- make_occupancy_multi_autologistic_eq_lpmf.Rd
Create Stan code for likelihood function occupancy_multi_autologistic_eq_lpmf.
-make_occupancy_multi_autologistic_eq_lpmf(max_rep, max_year)
Literal integer maximum number of repeated sampling events at -any unit.
Literal integer maximum number of years (or seasons) visited -in any series
Character string of Stan code corresponding to occupancy_multi_autologistic_eq_lpmf
-R/make_occupancy_lpmf.R
- make_occupancy_multi_autologistic_lpmf.Rd
Create Stan code for likelihood function occupancy_multi_autologistic_lpmf.
-make_occupancy_multi_autologistic_lpmf(max_rep, max_year)
Literal integer maximum number of repeated sampling events at -any unit.
Literal integer maximum number of years (or seasons) visited -in any series
Character string of Stan code corresponding to occupancy_multi_autologistic_lpmf
-R/make_occupancy_lpmf.R
- make_occupancy_multi_colex_eq_lpmf.Rd
Create Stan code for likelihood function occupancy_multi_colex_eq_lpmf.
-make_occupancy_multi_colex_eq_lpmf(max_rep, max_year)
Literal integer maximum number of repeated sampling events at -any unit.
Literal integer maximum number of years (or seasons) visited -in any series
Character string of Stan code corresponding to occupancy_multi_colex_eq_lpmf
-R/make_occupancy_lpmf.R
- make_occupancy_multi_colex_lpmf.Rd
Create Stan code for likelihood function occupancy_multi_colex_lpmf.
-make_occupancy_multi_colex_lpmf(max_rep, max_year)
Literal integer maximum number of repeated sampling events at -any unit.
Literal integer maximum number of years (or seasons) visited -in any series
Character string of Stan code corresponding to occupancy_multi_colex_lpmf
-R/make_occupancy_lpmf.R
- make_occupancy_single_C_lpmf.Rd
Create Stan code for likelihood function occupancy_single_C_lpmf. -The purpose of defining this custom family, rather than using brms's zero-inflated -binomial, is to ensure that the occupancy parameters are interpretable with -values of 1 in the marginalized state reflecting occupancy rather than non- -occupancy.
-make_occupancy_single_C_lpmf()
Character string of Stan code corresponding to occupancy_single_C_lpmf
-R/make_occupancy_lpmf.R
- make_occupancy_single_lpmf.Rd
Create Stan code for likelihood function occupancy_single_lpmf.
-make_occupancy_single_lpmf(max_rep)
Literal integer maximum number of repeated sampling events at -any unit.
Character string of Stan code corresponding to occupancy_single_lpmf
-R/make_occupancy_lpmf.R
- make_occupancy_single_partial_sum.Rd
Create Stan code for likelihood function occupancy_single_lpmf.
-make_occupancy_single_partial_sum(max_rep)
Literal integer maximum number of repeated sampling events at -any unit.
Character string of Stan code corresponding to occupancy_single_lpmf
-get largest index in a vector that is not NA
-max_position_not_na(x, treat_m99_NA = FALSE)
vector to test
logical; should -99 be treated as NA?
0 if all elements are NA; otherwise the largest index that is not NA
-if `treat_m99_NA` is `TRUE`, then character `"-99"` will be treated - as `NA` just as numeric `-99` would be.
-R/utils.R
- multi_init_types.Rd
possible values for the `multi_init` parameter if not NULL
-multi_init_types()
character vector of options
-flocker_data_output_types valid for use with colex models
-multi_types()
character vector of data output types
-create a new array with the dimensions of an old array
-new_array(m, data = NA)
old array
passed to the data argument of array()
new array
-create a new matrix with the dimensions of an old matrix
-new_matrix(m, data = NA, byrow = FALSE)
old matrix
passed to the data argument of matrix()
passed to the byrow argument of matrix()
new matrix
-Get third dimension of a 3D array
-nslice(x)
3D array for which third dimension is desired
integer size of third dimension
-R/occupancy_families.R
- occupancy_augmented.Rd
Define the rep-varying augmented occupancy family
-occupancy_augmented(max_rep)
the maximum number of repeat sampling events at a unit
a "customfamily" "brmsfamily" object from brms
-R/occupancy_families.R
- occupancy_multi_autologistic.Rd
Define the autologistic family
-occupancy_multi_autologistic(max_year, max_rep)
the maximum number of seasons at a colex unit
the maximum number of repeat sampling events at a closure unit
a "customfamily" "brmsfamily" object from brms
-R/occupancy_families.R
- occupancy_multi_autologistic_eq.Rd
Define the autologistic_eq family
-occupancy_multi_autologistic_eq(max_year, max_rep)
the maximum number of seasons at a colex unit
the maximum number of repeat sampling events at a closure unit
a "customfamily" "brmsfamily" object from brms
-R/occupancy_families.R
- occupancy_multi_colex.Rd
Define the colonization-extinction family
-occupancy_multi_colex(max_year, max_rep)
the maximum number of seasons at a colex unit
the maximum number of repeat sampling events at a closure unit
a "customfamily" "brmsfamily" object from brms
-R/occupancy_families.R
- occupancy_multi_colex_eq.Rd
Define the colonization-extinction equilibrium family
-occupancy_multi_colex_eq(max_year, max_rep)
the maximum number of seasons at a colex unit
the maximum number of repeat sampling events at a closure unit
a "customfamily" "brmsfamily" object from brms
-Define the rep-varying occupancy family
-occupancy_single(max_rep)
the maximum number of repeat sampling events at a unit
a "customfamily" "brmsfamily" object from brms
-R/occupancy_families.R
- occupancy_single_C.Rd
Define the rep-constant occupancy family
-occupancy_single_C()
a "customfamily" "brmsfamily" object from brms
-R/log_lik_occupancy.R
- occupancy_single_C_lpmf.Rd
An R implementation of the rep constant lpmf without the binomial coefficient.
-occupancy_single_C_lpmf(y, mu, occ, trials)
number of detections
logit-scale detection probability
logit-scale occupancy probability
number of reps
The log-likelihood
-By omitting the binomial coefficient, the log-likelihood is directly - comparable to log-likelihoods from rep-varying models.
-R/log_lik_occupancy.R
- occupancy_single_C_lpmf_with_coef.Rd
An R implementation of occupancy_C_lpmf including the binomial coefficient. -Not currently in use.
-occupancy_single_C_lpmf_with_coef(y, mu, occ, trials)
number of detections
logit-scale detection probability
logit-scale occupancy probability
number of reps
The log-likelihood
-R/occupancy_families.R
- occupancy_single_threaded.Rd
Define the rep-varying occupancy family with threading
-occupancy_single_threaded(max_rep)
the maximum number of repeat sampling events at a unit
a "customfamily" "brmsfamily" object from brms
-A list of distributional parameters by model type
-params_by_type
An object of class list
of length 7.
A list of distributional parameters by model type
-R/predict_flocker.R
- predict_flocker.Rd
Get posterior predictions from a flocker model
-predict_flocker(
- flocker_fit,
- draw_ids = NULL,
- history_condition = FALSE,
- new_data = NULL,
- mixed = FALSE,
- allow_new_levels = FALSE,
- sample_new_levels = "uncertainty"
-)
A `flocker_fit` object
Vector of indices of the posterior draws to be -used. If `NULL` (the default) all draws are used in their native order.
Logical indicator of whether to directly condition the -posterior for the occupancy state on the observed detection histories. -For example, at sites with at least one detection, the true occupancy -state conditioned on the history is one with absolute certainty. Without -directly conditioning on the history, the occupancy state is controlled -exclusively by the posterior distribution for the occupancy probability -psi.
Optional new data at which to predict. If `NULL`, predictions -are given at the data points used for model fitting ("retrodictions")
When `new_data` is not provided, should random effect levels be -drawn from their posteriors (`FALSE`, the default) or re-sampled from -their fitted hyperparameters (`TRUE`). The latter can be useful for mixed -predictive checking. Note that setting to TRUE is not available for -grouping terms involved in phylogenetic random effects or other random -effects with specified covariance structures.
Should new_data be allowed to contain new levels for -random effects?
If new_data is provided and contains random effect -levels not present in the original data, how should predictions be -handled? Passed directly to brms::prepare_predictions, which see.
An array of posterior predictions. For a single-season rep-varying - model, a 3-dimensional array where the first dimension is the closure-unit, - the second dimension is the rep, the third dimension is the iteration, - and the value is 1, 0, or NA indicating detection, non-detection, or - non-existence of the sampling event.
-if (FALSE) {
-unconditioned_preds <- predict_flocker(example_flocker_model_single)
-conditioned_preds <- predict_flocker(
- example_flocker_model_single,
- history_condition = TRUE
-)
-}
-
remove rownames
-remove_rownames(m)
object whose rownames to remove
m with rownames removed
-R/utils.R
- rep_constant_types.Rd
flocker_data_output_types that yield rep-constant models
-rep_constant_types()
character vector of data output types
-R/fitted_flocker.R
- reshape_fun.Rd
reshape a matrix of values into a stack of arrays via get_positions
-reshape_fun(x, gp)
input_matrix
output of get_positions
Data will be simulated with one unit covariate that affects all -relevant terms, one event covariate that affects detection (unless -`rep_constant` is `TRUE`), and one grouping factor representing species -with correlated effects on all terms.
-sfd(
- n_rep,
- n_pt,
- n_sp,
- n_season,
- multiseason,
- multi_init,
- augmented,
- rep_constant,
- params,
- covariates,
- ragged_rep,
- missing_seasons
-)
number of replicate visits to simulate per closure unit
number of points to simulate. The number of units for single- -season models will be `n_pt*n_sp`. The number of units for multi-season -models will be `n_pt*n_sp*n_season`.
number of levels to include in random effect. For compatibility -with multispecies models where the random effect represents species, -the data get expanded such that there's a row (closure-unit) for each -combination of sampling point and effect level (i.e. species)
Number of seasons desired. 1 yields data for a single-season -model; all other positive integers yield data for multiseason models.
if n_season is NULL, must be NULL. Otherwise, one of -"colex" or "autologistic".
if n_season is NULL, must be NULL. Otherwise, one of -"explicit" or "equilibrium".
logical. If `TRUE` data will be formatted for an augmented -model, which requires that `n_season == 1`. All never-observed -species will be trimmed out of the data, and the default parameters will be -modified to increase random effect variances for the detection and occupancy, -intercepts and to decrease random effect variances for detection slopes, thus -encouraging the existence of never-observed species. Furthermore, the data will -be simulated without any covariate influence on occupancy.
logical: create data with unit covariates only (TRUE) -or data that includes event covariates (FALSE)
a named list containing of parameter values to use in simulation. -Any required parameters whose names are not in this list will be assigned their -default values. To see the parameter names and structures required, run with -`params = NULL` (the default) and examine the `$params` element of the output.
a dataframe of covariate values to use in simulation, or -NULL to simulate values. To see the covariate names and structures required, -run with `covariates = NULL` (the default) and examine the `$covariates` element -of the output.
logical: create data with variable (TRUE) or constant -(FALSE) numbers of visits per unit. If TRUE, approximately half of units -will be missing approximately half of `n_rep` visits. Intended primarily for -development purposes (bug-checking models with missing data).
logical; relevant only if n_season is greater than 1. -create data with variable (TRUE) or constant (FALSE) numbers of seasons per -series (TRUE). If TRUE, approximately half of series will be missing their -even-numbered seasons.
A named list with the observation matrix/array ($obs), the unit covariate - dataframe(s) ($unit_covs), the event covariate list ($event_covs), the parameters - used in simulation ($params) and the covariate list used in simulation ($covariates). - If rep_constant is TRUE, then $event_covs will be NULL.
-simulate_flocker_data()
-#> $obs
-#> [,1] [,2] [,3] [,4]
-#> [1,] 0 0 0 0
-#> [2,] 0 0 0 0
-#> [3,] 1 1 1 0
-#> [4,] 1 1 1 1
-#> [5,] 0 0 0 0
-#> [6,] 0 0 0 0
-#> [7,] 1 1 1 1
-#> [8,] 1 1 1 0
-#> [9,] 0 0 0 0
-#> [10,] 0 0 0 0
-#> [11,] 0 0 0 0
-#> [12,] 0 0 0 0
-#> [13,] 0 0 0 0
-#> [14,] 0 0 0 0
-#> [15,] 0 0 0 0
-#> [16,] 0 0 0 0
-#> [17,] 0 0 0 0
-#> [18,] 0 0 0 0
-#> [19,] 1 1 0 1
-#> [20,] 1 1 1 1
-#> [21,] 0 0 0 0
-#> [22,] 0 0 0 0
-#> [23,] 0 1 1 1
-#> [24,] 0 0 0 0
-#> [25,] 0 0 0 0
-#> [26,] 1 1 0 0
-#> [27,] 0 0 0 0
-#> [28,] 0 0 0 0
-#> [29,] 0 0 0 0
-#> [30,] 0 0 0 0
-#> [31,] 0 0 0 0
-#> [32,] 1 1 1 1
-#> [33,] 1 1 1 0
-#> [34,] 1 1 1 1
-#> [35,] 0 1 1 0
-#> [36,] 0 1 1 1
-#> [37,] 0 0 0 0
-#> [38,] 0 0 0 0
-#> [39,] 1 1 1 1
-#> [40,] 0 0 0 0
-#> [41,] 0 1 0 0
-#> [42,] 1 0 1 0
-#> [43,] 0 1 1 1
-#> [44,] 0 0 0 0
-#> [45,] 0 0 0 1
-#> [46,] 0 0 0 0
-#> [47,] 0 0 0 0
-#> [48,] 0 0 0 0
-#> [49,] 0 0 0 0
-#> [50,] 0 0 0 0
-#> [51,] 0 1 0 1
-#> [52,] 1 1 0 0
-#> [53,] 1 0 0 0
-#> [54,] 0 0 0 0
-#> [55,] 1 0 1 0
-#> [56,] 0 1 0 0
-#> [57,] 0 0 0 0
-#> [58,] 0 1 0 1
-#> [59,] 0 0 0 0
-#> [60,] 0 0 1 0
-#> [61,] 0 1 1 0
-#> [62,] 0 0 0 0
-#> [63,] 0 0 0 0
-#> [64,] 1 1 1 1
-#> [65,] 0 0 0 0
-#> [66,] 0 0 0 0
-#> [67,] 0 0 0 0
-#> [68,] 0 1 0 1
-#> [69,] 0 0 1 0
-#> [70,] 0 0 0 0
-#> [71,] 0 0 0 0
-#> [72,] 0 0 0 0
-#> [73,] 0 1 0 1
-#> [74,] 1 1 1 1
-#> [75,] 0 1 0 1
-#> [76,] 0 0 0 0
-#> [77,] 0 0 1 0
-#> [78,] 0 0 0 0
-#> [79,] 0 0 1 0
-#> [80,] 0 0 0 0
-#> [81,] 0 1 0 0
-#> [82,] 1 0 1 1
-#> [83,] 0 0 0 1
-#> [84,] 0 0 0 0
-#> [85,] 0 0 1 0
-#> [86,] 0 0 0 0
-#> [87,] 1 1 0 1
-#> [88,] 0 0 0 0
-#> [89,] 0 0 0 0
-#> [90,] 0 0 0 0
-#> [91,] 0 1 1 0
-#> [92,] 1 0 0 1
-#> [93,] 0 1 0 0
-#> [94,] 0 0 0 0
-#> [95,] 0 1 1 0
-#> [96,] 0 0 0 0
-#> [97,] 1 0 1 1
-#> [98,] 0 0 0 0
-#> [99,] 0 0 0 1
-#> [100,] 0 0 0 0
-#> [101,] 0 0 0 0
-#> [102,] 0 0 0 0
-#> [103,] 0 0 0 0
-#> [104,] 0 0 0 0
-#> [105,] 0 0 0 0
-#> [106,] 0 0 0 0
-#> [107,] 0 0 0 0
-#> [108,] 0 0 0 0
-#> [109,] 0 0 0 0
-#> [110,] 0 0 0 0
-#> [111,] 0 0 0 0
-#> [112,] 0 0 0 0
-#> [113,] 0 0 0 0
-#> [114,] 0 0 0 0
-#> [115,] 0 0 0 0
-#> [116,] 0 0 1 0
-#> [117,] 0 0 0 0
-#> [118,] 1 0 0 0
-#> [119,] 0 0 0 0
-#> [120,] 0 0 0 0
-#> [121,] 0 0 0 0
-#> [122,] 0 0 0 0
-#> [123,] 0 0 0 0
-#> [124,] 0 0 0 0
-#> [125,] 0 0 0 0
-#> [126,] 1 0 0 1
-#> [127,] 0 0 0 0
-#> [128,] 0 0 0 0
-#> [129,] 0 0 0 0
-#> [130,] 0 0 0 0
-#> [131,] 0 0 0 0
-#> [132,] 0 0 0 0
-#> [133,] 0 0 0 1
-#> [134,] 0 0 0 0
-#> [135,] 0 0 0 0
-#> [136,] 0 0 0 0
-#> [137,] 0 0 0 0
-#> [138,] 0 0 0 0
-#> [139,] 0 0 0 0
-#> [140,] 0 0 0 1
-#> [141,] 0 0 0 0
-#> [142,] 0 0 0 0
-#> [143,] 0 0 0 0
-#> [144,] 0 0 0 0
-#> [145,] 0 0 0 0
-#> [146,] 0 0 0 0
-#> [147,] 0 0 0 0
-#> [148,] 1 0 0 0
-#> [149,] 0 0 0 0
-#> [150,] 0 0 0 0
-#> [151,] 0 1 0 1
-#> [152,] 0 0 0 0
-#> [153,] 1 0 1 0
-#> [154,] 0 0 0 0
-#> [155,] 0 0 0 0
-#> [156,] 0 1 0 0
-#> [157,] 0 0 0 1
-#> [158,] 0 0 1 0
-#> [159,] 0 0 1 0
-#> [160,] 0 0 0 0
-#> [161,] 0 0 0 0
-#> [162,] 1 1 0 0
-#> [163,] 0 0 0 0
-#> [164,] 1 0 1 0
-#> [165,] 1 1 1 1
-#> [166,] 0 0 0 0
-#> [167,] 0 1 1 0
-#> [168,] 0 0 0 0
-#> [169,] 1 0 0 0
-#> [170,] 0 1 1 1
-#> [171,] 1 0 1 1
-#> [172,] 0 0 0 0
-#> [173,] 0 0 0 0
-#> [174,] 0 0 1 0
-#> [175,] 0 0 0 0
-#> [176,] 0 0 0 1
-#> [177,] 0 1 0 0
-#> [178,] 0 0 1 0
-#> [179,] 1 1 0 0
-#> [180,] 0 0 0 0
-#> [181,] 0 0 0 1
-#> [182,] 1 0 0 0
-#> [183,] 0 0 0 0
-#> [184,] 0 0 0 0
-#> [185,] 0 1 1 0
-#> [186,] 0 0 0 0
-#> [187,] 0 0 0 0
-#> [188,] 0 0 0 0
-#> [189,] 0 1 0 1
-#> [190,] 0 0 0 0
-#> [191,] 0 0 0 0
-#> [192,] 0 1 0 0
-#> [193,] 0 0 0 0
-#> [194,] 0 0 0 1
-#> [195,] 0 0 0 0
-#> [196,] 0 0 1 1
-#> [197,] 0 0 0 0
-#> [198,] 0 0 0 0
-#> [199,] 0 1 1 1
-#> [200,] 0 0 0 0
-#> [201,] 0 0 0 0
-#> [202,] 0 0 0 0
-#> [203,] 0 0 0 0
-#> [204,] 0 0 0 0
-#> [205,] 0 0 0 0
-#> [206,] 0 0 0 0
-#> [207,] 0 1 1 1
-#> [208,] 0 0 0 0
-#> [209,] 0 0 0 0
-#> [210,] 0 0 0 0
-#> [211,] 0 0 0 0
-#> [212,] 0 0 0 0
-#> [213,] 0 0 0 0
-#> [214,] 0 0 0 0
-#> [215,] 0 1 1 1
-#> [216,] 0 0 0 0
-#> [217,] 0 0 0 0
-#> [218,] 0 0 0 0
-#> [219,] 0 0 0 0
-#> [220,] 0 0 0 0
-#> [221,] 0 1 1 1
-#> [222,] 0 0 0 0
-#> [223,] 0 0 0 0
-#> [224,] 0 0 0 0
-#> [225,] 0 0 0 0
-#> [226,] 0 0 0 0
-#> [227,] 0 0 1 0
-#> [228,] 0 0 0 0
-#> [229,] 1 1 1 1
-#> [230,] 1 0 1 1
-#> [231,] 1 1 1 1
-#> [232,] 0 0 0 0
-#> [233,] 0 0 0 0
-#> [234,] 0 0 0 0
-#> [235,] 0 0 0 0
-#> [236,] 0 0 0 0
-#> [237,] 1 1 1 0
-#> [238,] 0 0 0 0
-#> [239,] 0 0 0 0
-#> [240,] 0 0 0 0
-#> [241,] 1 1 1 1
-#> [242,] 1 1 1 1
-#> [243,] 1 1 1 1
-#> [244,] 1 0 0 0
-#> [245,] 0 0 0 0
-#> [246,] 1 0 1 1
-#> [247,] 0 0 0 0
-#> [248,] 0 0 0 0
-#> [249,] 0 0 0 0
-#> [250,] 0 0 0 0
-#> [251,] 0 0 0 0
-#> [252,] 0 0 0 0
-#> [253,] 0 0 0 0
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-#> 1028 0.31048075 sp_21
-#> 1029 0.43652348 sp_21
-#> 1030 -0.45836533 sp_21
-#> 1031 -1.06332613 sp_21
-#> 1032 1.26318518 sp_21
-#> 1033 -0.34965039 sp_21
-#> 1034 -0.86551286 sp_21
-#> 1035 -0.23627957 sp_21
-#> 1036 -0.19717589 sp_21
-#> 1037 1.10992029 sp_21
-#> 1038 0.08473729 sp_21
-#> 1039 0.75405379 sp_21
-#> 1040 -0.49929202 sp_21
-#> 1041 0.21444531 sp_21
-#> 1042 -0.32468591 sp_21
-#> 1043 0.09458353 sp_21
-#> 1044 -0.89536336 sp_21
-#> 1045 -1.31080153 sp_21
-#> 1046 1.99721338 sp_21
-#> 1047 0.60070882 sp_21
-#> 1048 -1.25127136 sp_21
-#> 1049 -0.61116592 sp_21
-#> 1050 -1.18548008 sp_21
-#> 1051 0.78773885 sp_22
-#> 1052 0.76904224 sp_22
-#> 1053 0.33220258 sp_22
-#> 1054 -1.00837661 sp_22
-#> 1055 -0.11945261 sp_22
-#> 1056 -0.28039534 sp_22
-#> 1057 0.56298953 sp_22
-#> 1058 -0.37243876 sp_22
-#> 1059 0.97697339 sp_22
-#> 1060 -0.37458086 sp_22
-#> 1061 1.05271147 sp_22
-#> 1062 -1.04917701 sp_22
-#> 1063 -1.26015524 sp_22
-#> 1064 3.24103993 sp_22
-#> 1065 -0.41685759 sp_22
-#> 1066 0.29822759 sp_22
-#> 1067 0.63656967 sp_22
-#> 1068 -0.48378063 sp_22
-#> 1069 0.51686204 sp_22
-#> 1070 0.36896453 sp_22
-#> 1071 -0.21538051 sp_22
-#> 1072 0.06529303 sp_22
-#> 1073 -0.03406725 sp_22
-#> 1074 2.12845190 sp_22
-#> 1075 -0.74133610 sp_22
-#> 1076 -1.09599627 sp_22
-#> 1077 0.03778840 sp_22
-#> 1078 0.31048075 sp_22
-#> 1079 0.43652348 sp_22
-#> 1080 -0.45836533 sp_22
-#> 1081 -1.06332613 sp_22
-#> 1082 1.26318518 sp_22
-#> 1083 -0.34965039 sp_22
-#> 1084 -0.86551286 sp_22
-#> 1085 -0.23627957 sp_22
-#> 1086 -0.19717589 sp_22
-#> 1087 1.10992029 sp_22
-#> 1088 0.08473729 sp_22
-#> 1089 0.75405379 sp_22
-#> 1090 -0.49929202 sp_22
-#> 1091 0.21444531 sp_22
-#> 1092 -0.32468591 sp_22
-#> 1093 0.09458353 sp_22
-#> 1094 -0.89536336 sp_22
-#> 1095 -1.31080153 sp_22
-#> 1096 1.99721338 sp_22
-#> 1097 0.60070882 sp_22
-#> 1098 -1.25127136 sp_22
-#> 1099 -0.61116592 sp_22
-#> 1100 -1.18548008 sp_22
-#> 1101 0.78773885 sp_23
-#> 1102 0.76904224 sp_23
-#> 1103 0.33220258 sp_23
-#> 1104 -1.00837661 sp_23
-#> 1105 -0.11945261 sp_23
-#> 1106 -0.28039534 sp_23
-#> 1107 0.56298953 sp_23
-#> 1108 -0.37243876 sp_23
-#> 1109 0.97697339 sp_23
-#> 1110 -0.37458086 sp_23
-#> 1111 1.05271147 sp_23
-#> 1112 -1.04917701 sp_23
-#> 1113 -1.26015524 sp_23
-#> 1114 3.24103993 sp_23
-#> 1115 -0.41685759 sp_23
-#> 1116 0.29822759 sp_23
-#> 1117 0.63656967 sp_23
-#> 1118 -0.48378063 sp_23
-#> 1119 0.51686204 sp_23
-#> 1120 0.36896453 sp_23
-#> 1121 -0.21538051 sp_23
-#> 1122 0.06529303 sp_23
-#> 1123 -0.03406725 sp_23
-#> 1124 2.12845190 sp_23
-#> 1125 -0.74133610 sp_23
-#> 1126 -1.09599627 sp_23
-#> 1127 0.03778840 sp_23
-#> 1128 0.31048075 sp_23
-#> 1129 0.43652348 sp_23
-#> 1130 -0.45836533 sp_23
-#> 1131 -1.06332613 sp_23
-#> 1132 1.26318518 sp_23
-#> 1133 -0.34965039 sp_23
-#> 1134 -0.86551286 sp_23
-#> 1135 -0.23627957 sp_23
-#> 1136 -0.19717589 sp_23
-#> 1137 1.10992029 sp_23
-#> 1138 0.08473729 sp_23
-#> 1139 0.75405379 sp_23
-#> 1140 -0.49929202 sp_23
-#> 1141 0.21444531 sp_23
-#> 1142 -0.32468591 sp_23
-#> 1143 0.09458353 sp_23
-#> 1144 -0.89536336 sp_23
-#> 1145 -1.31080153 sp_23
-#> 1146 1.99721338 sp_23
-#> 1147 0.60070882 sp_23
-#> 1148 -1.25127136 sp_23
-#> 1149 -0.61116592 sp_23
-#> 1150 -1.18548008 sp_23
-#> 1151 0.78773885 sp_24
-#> 1152 0.76904224 sp_24
-#> 1153 0.33220258 sp_24
-#> 1154 -1.00837661 sp_24
-#> 1155 -0.11945261 sp_24
-#> 1156 -0.28039534 sp_24
-#> 1157 0.56298953 sp_24
-#> 1158 -0.37243876 sp_24
-#> 1159 0.97697339 sp_24
-#> 1160 -0.37458086 sp_24
-#> 1161 1.05271147 sp_24
-#> 1162 -1.04917701 sp_24
-#> 1163 -1.26015524 sp_24
-#> 1164 3.24103993 sp_24
-#> 1165 -0.41685759 sp_24
-#> 1166 0.29822759 sp_24
-#> 1167 0.63656967 sp_24
-#> 1168 -0.48378063 sp_24
-#> 1169 0.51686204 sp_24
-#> 1170 0.36896453 sp_24
-#> 1171 -0.21538051 sp_24
-#> 1172 0.06529303 sp_24
-#> 1173 -0.03406725 sp_24
-#> 1174 2.12845190 sp_24
-#> 1175 -0.74133610 sp_24
-#> 1176 -1.09599627 sp_24
-#> 1177 0.03778840 sp_24
-#> 1178 0.31048075 sp_24
-#> 1179 0.43652348 sp_24
-#> 1180 -0.45836533 sp_24
-#> 1181 -1.06332613 sp_24
-#> 1182 1.26318518 sp_24
-#> 1183 -0.34965039 sp_24
-#> 1184 -0.86551286 sp_24
-#> 1185 -0.23627957 sp_24
-#> 1186 -0.19717589 sp_24
-#> 1187 1.10992029 sp_24
-#> 1188 0.08473729 sp_24
-#> 1189 0.75405379 sp_24
-#> 1190 -0.49929202 sp_24
-#> 1191 0.21444531 sp_24
-#> 1192 -0.32468591 sp_24
-#> 1193 0.09458353 sp_24
-#> 1194 -0.89536336 sp_24
-#> 1195 -1.31080153 sp_24
-#> 1196 1.99721338 sp_24
-#> 1197 0.60070882 sp_24
-#> 1198 -1.25127136 sp_24
-#> 1199 -0.61116592 sp_24
-#> 1200 -1.18548008 sp_24
-#> 1201 0.78773885 sp_25
-#> 1202 0.76904224 sp_25
-#> 1203 0.33220258 sp_25
-#> 1204 -1.00837661 sp_25
-#> 1205 -0.11945261 sp_25
-#> 1206 -0.28039534 sp_25
-#> 1207 0.56298953 sp_25
-#> 1208 -0.37243876 sp_25
-#> 1209 0.97697339 sp_25
-#> 1210 -0.37458086 sp_25
-#> 1211 1.05271147 sp_25
-#> 1212 -1.04917701 sp_25
-#> 1213 -1.26015524 sp_25
-#> 1214 3.24103993 sp_25
-#> 1215 -0.41685759 sp_25
-#> 1216 0.29822759 sp_25
-#> 1217 0.63656967 sp_25
-#> 1218 -0.48378063 sp_25
-#> 1219 0.51686204 sp_25
-#> 1220 0.36896453 sp_25
-#> 1221 -0.21538051 sp_25
-#> 1222 0.06529303 sp_25
-#> 1223 -0.03406725 sp_25
-#> 1224 2.12845190 sp_25
-#> 1225 -0.74133610 sp_25
-#> 1226 -1.09599627 sp_25
-#> 1227 0.03778840 sp_25
-#> 1228 0.31048075 sp_25
-#> 1229 0.43652348 sp_25
-#> 1230 -0.45836533 sp_25
-#> 1231 -1.06332613 sp_25
-#> 1232 1.26318518 sp_25
-#> 1233 -0.34965039 sp_25
-#> 1234 -0.86551286 sp_25
-#> 1235 -0.23627957 sp_25
-#> 1236 -0.19717589 sp_25
-#> 1237 1.10992029 sp_25
-#> 1238 0.08473729 sp_25
-#> 1239 0.75405379 sp_25
-#> 1240 -0.49929202 sp_25
-#> 1241 0.21444531 sp_25
-#> 1242 -0.32468591 sp_25
-#> 1243 0.09458353 sp_25
-#> 1244 -0.89536336 sp_25
-#> 1245 -1.31080153 sp_25
-#> 1246 1.99721338 sp_25
-#> 1247 0.60070882 sp_25
-#> 1248 -1.25127136 sp_25
-#> 1249 -0.61116592 sp_25
-#> 1250 -1.18548008 sp_25
-#> 1251 0.78773885 sp_26
-#> 1252 0.76904224 sp_26
-#> 1253 0.33220258 sp_26
-#> 1254 -1.00837661 sp_26
-#> 1255 -0.11945261 sp_26
-#> 1256 -0.28039534 sp_26
-#> 1257 0.56298953 sp_26
-#> 1258 -0.37243876 sp_26
-#> 1259 0.97697339 sp_26
-#> 1260 -0.37458086 sp_26
-#> 1261 1.05271147 sp_26
-#> 1262 -1.04917701 sp_26
-#> 1263 -1.26015524 sp_26
-#> 1264 3.24103993 sp_26
-#> 1265 -0.41685759 sp_26
-#> 1266 0.29822759 sp_26
-#> 1267 0.63656967 sp_26
-#> 1268 -0.48378063 sp_26
-#> 1269 0.51686204 sp_26
-#> 1270 0.36896453 sp_26
-#> 1271 -0.21538051 sp_26
-#> 1272 0.06529303 sp_26
-#> 1273 -0.03406725 sp_26
-#> 1274 2.12845190 sp_26
-#> 1275 -0.74133610 sp_26
-#> 1276 -1.09599627 sp_26
-#> 1277 0.03778840 sp_26
-#> 1278 0.31048075 sp_26
-#> 1279 0.43652348 sp_26
-#> 1280 -0.45836533 sp_26
-#> 1281 -1.06332613 sp_26
-#> 1282 1.26318518 sp_26
-#> 1283 -0.34965039 sp_26
-#> 1284 -0.86551286 sp_26
-#> 1285 -0.23627957 sp_26
-#> 1286 -0.19717589 sp_26
-#> 1287 1.10992029 sp_26
-#> 1288 0.08473729 sp_26
-#> 1289 0.75405379 sp_26
-#> 1290 -0.49929202 sp_26
-#> 1291 0.21444531 sp_26
-#> 1292 -0.32468591 sp_26
-#> 1293 0.09458353 sp_26
-#> 1294 -0.89536336 sp_26
-#> 1295 -1.31080153 sp_26
-#> 1296 1.99721338 sp_26
-#> 1297 0.60070882 sp_26
-#> 1298 -1.25127136 sp_26
-#> 1299 -0.61116592 sp_26
-#> 1300 -1.18548008 sp_26
-#> 1301 0.78773885 sp_27
-#> 1302 0.76904224 sp_27
-#> 1303 0.33220258 sp_27
-#> 1304 -1.00837661 sp_27
-#> 1305 -0.11945261 sp_27
-#> 1306 -0.28039534 sp_27
-#> 1307 0.56298953 sp_27
-#> 1308 -0.37243876 sp_27
-#> 1309 0.97697339 sp_27
-#> 1310 -0.37458086 sp_27
-#> 1311 1.05271147 sp_27
-#> 1312 -1.04917701 sp_27
-#> 1313 -1.26015524 sp_27
-#> 1314 3.24103993 sp_27
-#> 1315 -0.41685759 sp_27
-#> 1316 0.29822759 sp_27
-#> 1317 0.63656967 sp_27
-#> 1318 -0.48378063 sp_27
-#> 1319 0.51686204 sp_27
-#> 1320 0.36896453 sp_27
-#> 1321 -0.21538051 sp_27
-#> 1322 0.06529303 sp_27
-#> 1323 -0.03406725 sp_27
-#> 1324 2.12845190 sp_27
-#> 1325 -0.74133610 sp_27
-#> 1326 -1.09599627 sp_27
-#> 1327 0.03778840 sp_27
-#> 1328 0.31048075 sp_27
-#> 1329 0.43652348 sp_27
-#> 1330 -0.45836533 sp_27
-#> 1331 -1.06332613 sp_27
-#> 1332 1.26318518 sp_27
-#> 1333 -0.34965039 sp_27
-#> 1334 -0.86551286 sp_27
-#> 1335 -0.23627957 sp_27
-#> 1336 -0.19717589 sp_27
-#> 1337 1.10992029 sp_27
-#> 1338 0.08473729 sp_27
-#> 1339 0.75405379 sp_27
-#> 1340 -0.49929202 sp_27
-#> 1341 0.21444531 sp_27
-#> 1342 -0.32468591 sp_27
-#> 1343 0.09458353 sp_27
-#> 1344 -0.89536336 sp_27
-#> 1345 -1.31080153 sp_27
-#> 1346 1.99721338 sp_27
-#> 1347 0.60070882 sp_27
-#> 1348 -1.25127136 sp_27
-#> 1349 -0.61116592 sp_27
-#> 1350 -1.18548008 sp_27
-#> 1351 0.78773885 sp_28
-#> 1352 0.76904224 sp_28
-#> 1353 0.33220258 sp_28
-#> 1354 -1.00837661 sp_28
-#> 1355 -0.11945261 sp_28
-#> 1356 -0.28039534 sp_28
-#> 1357 0.56298953 sp_28
-#> 1358 -0.37243876 sp_28
-#> 1359 0.97697339 sp_28
-#> 1360 -0.37458086 sp_28
-#> 1361 1.05271147 sp_28
-#> 1362 -1.04917701 sp_28
-#> 1363 -1.26015524 sp_28
-#> 1364 3.24103993 sp_28
-#> 1365 -0.41685759 sp_28
-#> 1366 0.29822759 sp_28
-#> 1367 0.63656967 sp_28
-#> 1368 -0.48378063 sp_28
-#> 1369 0.51686204 sp_28
-#> 1370 0.36896453 sp_28
-#> 1371 -0.21538051 sp_28
-#> 1372 0.06529303 sp_28
-#> 1373 -0.03406725 sp_28
-#> 1374 2.12845190 sp_28
-#> 1375 -0.74133610 sp_28
-#> 1376 -1.09599627 sp_28
-#> 1377 0.03778840 sp_28
-#> 1378 0.31048075 sp_28
-#> 1379 0.43652348 sp_28
-#> 1380 -0.45836533 sp_28
-#> 1381 -1.06332613 sp_28
-#> 1382 1.26318518 sp_28
-#> 1383 -0.34965039 sp_28
-#> 1384 -0.86551286 sp_28
-#> 1385 -0.23627957 sp_28
-#> 1386 -0.19717589 sp_28
-#> 1387 1.10992029 sp_28
-#> 1388 0.08473729 sp_28
-#> 1389 0.75405379 sp_28
-#> 1390 -0.49929202 sp_28
-#> 1391 0.21444531 sp_28
-#> 1392 -0.32468591 sp_28
-#> 1393 0.09458353 sp_28
-#> 1394 -0.89536336 sp_28
-#> 1395 -1.31080153 sp_28
-#> 1396 1.99721338 sp_28
-#> 1397 0.60070882 sp_28
-#> 1398 -1.25127136 sp_28
-#> 1399 -0.61116592 sp_28
-#> 1400 -1.18548008 sp_28
-#> 1401 0.78773885 sp_29
-#> 1402 0.76904224 sp_29
-#> 1403 0.33220258 sp_29
-#> 1404 -1.00837661 sp_29
-#> 1405 -0.11945261 sp_29
-#> 1406 -0.28039534 sp_29
-#> 1407 0.56298953 sp_29
-#> 1408 -0.37243876 sp_29
-#> 1409 0.97697339 sp_29
-#> 1410 -0.37458086 sp_29
-#> 1411 1.05271147 sp_29
-#> 1412 -1.04917701 sp_29
-#> 1413 -1.26015524 sp_29
-#> 1414 3.24103993 sp_29
-#> 1415 -0.41685759 sp_29
-#> 1416 0.29822759 sp_29
-#> 1417 0.63656967 sp_29
-#> 1418 -0.48378063 sp_29
-#> 1419 0.51686204 sp_29
-#> 1420 0.36896453 sp_29
-#> 1421 -0.21538051 sp_29
-#> 1422 0.06529303 sp_29
-#> 1423 -0.03406725 sp_29
-#> 1424 2.12845190 sp_29
-#> 1425 -0.74133610 sp_29
-#> 1426 -1.09599627 sp_29
-#> 1427 0.03778840 sp_29
-#> 1428 0.31048075 sp_29
-#> 1429 0.43652348 sp_29
-#> 1430 -0.45836533 sp_29
-#> 1431 -1.06332613 sp_29
-#> 1432 1.26318518 sp_29
-#> 1433 -0.34965039 sp_29
-#> 1434 -0.86551286 sp_29
-#> 1435 -0.23627957 sp_29
-#> 1436 -0.19717589 sp_29
-#> 1437 1.10992029 sp_29
-#> 1438 0.08473729 sp_29
-#> 1439 0.75405379 sp_29
-#> 1440 -0.49929202 sp_29
-#> 1441 0.21444531 sp_29
-#> 1442 -0.32468591 sp_29
-#> 1443 0.09458353 sp_29
-#> 1444 -0.89536336 sp_29
-#> 1445 -1.31080153 sp_29
-#> 1446 1.99721338 sp_29
-#> 1447 0.60070882 sp_29
-#> 1448 -1.25127136 sp_29
-#> 1449 -0.61116592 sp_29
-#> 1450 -1.18548008 sp_29
-#> 1451 0.78773885 sp_30
-#> 1452 0.76904224 sp_30
-#> 1453 0.33220258 sp_30
-#> 1454 -1.00837661 sp_30
-#> 1455 -0.11945261 sp_30
-#> 1456 -0.28039534 sp_30
-#> 1457 0.56298953 sp_30
-#> 1458 -0.37243876 sp_30
-#> 1459 0.97697339 sp_30
-#> 1460 -0.37458086 sp_30
-#> 1461 1.05271147 sp_30
-#> 1462 -1.04917701 sp_30
-#> 1463 -1.26015524 sp_30
-#> 1464 3.24103993 sp_30
-#> 1465 -0.41685759 sp_30
-#> 1466 0.29822759 sp_30
-#> 1467 0.63656967 sp_30
-#> 1468 -0.48378063 sp_30
-#> 1469 0.51686204 sp_30
-#> 1470 0.36896453 sp_30
-#> 1471 -0.21538051 sp_30
-#> 1472 0.06529303 sp_30
-#> 1473 -0.03406725 sp_30
-#> 1474 2.12845190 sp_30
-#> 1475 -0.74133610 sp_30
-#> 1476 -1.09599627 sp_30
-#> 1477 0.03778840 sp_30
-#> 1478 0.31048075 sp_30
-#> 1479 0.43652348 sp_30
-#> 1480 -0.45836533 sp_30
-#> 1481 -1.06332613 sp_30
-#> 1482 1.26318518 sp_30
-#> 1483 -0.34965039 sp_30
-#> 1484 -0.86551286 sp_30
-#> 1485 -0.23627957 sp_30
-#> 1486 -0.19717589 sp_30
-#> 1487 1.10992029 sp_30
-#> 1488 0.08473729 sp_30
-#> 1489 0.75405379 sp_30
-#> 1490 -0.49929202 sp_30
-#> 1491 0.21444531 sp_30
-#> 1492 -0.32468591 sp_30
-#> 1493 0.09458353 sp_30
-#> 1494 -0.89536336 sp_30
-#> 1495 -1.31080153 sp_30
-#> 1496 1.99721338 sp_30
-#> 1497 0.60070882 sp_30
-#> 1498 -1.25127136 sp_30
-#> 1499 -0.61116592 sp_30
-#> 1500 -1.18548008 sp_30
-#>
-#> $event_covs
-#> $event_covs$ec1
-#> [,1] [,2] [,3] [,4]
-#> [1,] 0.67576242 -1.07420661 0.45457781 -0.21330714
-#> [2,] 0.93560368 -1.13689311 0.26691825 0.42833204
-#> [3,] -0.10555991 -0.73050967 1.90504358 0.33262173
-#> [4,] 1.39531344 -0.19070343 -0.52467120 3.18404447
-#> [5,] 0.49030264 -0.09616320 0.46852512 -0.98237064
-#> [6,] -1.02298384 -0.69341466 -0.76798957 1.29904997
-#> [7,] 1.57914556 -0.15689195 -0.35893656 -0.32903883
-#> [8,] 0.06923648 0.09690423 0.29003439 -0.74667894
-#> [9,] -0.84689639 1.19707766 -0.54862736 0.30304570
-#> [10,] -0.14126176 -1.00537758 0.15615571 0.23363361
-#> [11,] 0.35558761 -1.62185826 0.22071129 0.31045008
-#> [12,] -1.42110845 0.95536564 0.78417088 2.29961936
-#> [13,] 0.15670299 0.04673353 0.09658583 0.06976623
-#> [14,] -1.84847278 -1.67112706 -0.07753897 -0.58106738
-#> [15,] 0.05473653 -2.11120837 -1.49869825 -1.10148344
-#> [16,] 0.98605822 -1.09849001 -0.79951395 0.07987382
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-#> [1484,] 1.15791047 0.58470526 -0.80645282 0.05455325
-#> [1485,] 0.71633162 0.55773098 1.48193402 -0.61298775
-#> [1486,] 1.11613662 1.03654801 -0.16248313 -0.97592669
-#> [1487,] -1.08914519 0.45778696 -0.07112673 1.77910267
-#> [1488,] 0.53513796 -0.37194488 -1.02554225 -0.58240167
-#> [1489,] 0.34288839 -0.45093465 0.51423012 -0.33433805
-#> [1490,] 0.23063364 -1.69186241 0.65979190 -1.02362359
-#> [1491,] -0.89152157 0.91834117 -0.45270065 -1.74837228
-#> [1492,] 1.76990411 -2.37740693 0.57281153 1.01724925
-#> [1493,] -0.63096787 0.44428705 0.43913039 1.04062315
-#> [1494,] 0.48409939 -0.24488378 0.91599206 0.80062236
-#> [1495,] -0.93656903 -1.40078743 0.16027754 -0.27396237
-#> [1496,] -0.98553911 0.08393068 -1.31999653 0.16122635
-#> [1497,] -0.62492839 0.95716427 2.42448914 -0.91597924
-#> [1498,] 1.05766417 0.82514973 -0.07019422 -0.45364637
-#> [1499,] 1.57530771 -2.00545782 -0.64319479 -1.43684344
-#> [1500,] -0.05003727 -0.44374931 0.29986525 -1.56842462
-#>
-#>
-#> $params
-#> $params$coef_means
-#> [1] 0 0 0 0 0
-#>
-#> $params$Sigma
-#> [,1] [,2] [,3] [,4] [,5]
-#> [1,] 1.0 0.5 0.5 0.5 0.5
-#> [2,] 0.5 1.0 0.5 0.5 0.5
-#> [3,] 0.5 0.5 1.0 0.5 0.5
-#> [4,] 0.5 0.5 0.5 1.0 0.5
-#> [5,] 0.5 0.5 0.5 0.5 1.0
-#>
-#> $params$coefs
-#> det_intercept det_slope_unit det_slope_visit occ_intercept occ_slope_unit
-#> 1 0.508548810 0.77807011 0.80482970 -0.17360000 0.25286423
-#> 2 -0.420940845 0.77990025 0.12350617 0.35203975 0.05696827
-#> 3 -1.517626038 -0.89263386 -1.28636204 -1.61767754 -0.72255187
-#> 4 -0.216582489 0.03204391 -0.71897615 -0.12384829 0.75428519
-#> 5 1.066014876 0.66757562 -0.79646966 -1.12971558 -0.30813450
-#> 6 -1.740812948 -1.63284467 -1.14658859 -1.40540609 -0.71676583
-#> 7 -0.208152618 0.54095837 0.23442360 -1.45313390 -0.89921624
-#> 8 1.029218989 1.71515102 1.25425367 0.48142456 0.41951285
-#> 9 -0.076297618 0.24019585 1.18828474 0.80697467 0.50101201
-#> 10 0.300109084 -0.88154177 1.39343691 0.64725408 0.26678308
-#> 11 -0.034555501 -1.35817078 -1.58431721 -0.53454897 -1.22925595
-#> 12 0.006845644 0.59475669 -1.66797651 -0.05963075 -0.26754803
-#> 13 -0.284358241 -0.79588393 0.23456607 0.27944565 -0.98595070
-#> 14 -0.352944922 0.05803719 -0.49475617 -0.90398219 1.26497378
-#> 15 -0.868034872 0.52263808 0.19118352 0.54950737 1.75746936
-#> 16 -0.668616485 -1.94812518 -0.96619798 -1.10731830 -2.23042688
-#> 17 -1.309423215 -0.44645562 -0.45330736 0.34195221 -0.06093262
-#> 18 1.991318996 1.00395704 0.40903399 2.33951041 1.87285506
-#> 19 0.664155168 -1.09933744 -0.80166071 -1.12973093 -0.34976581
-#> 20 -0.546975568 1.10312602 0.66584579 0.34624304 0.26287397
-#> 21 1.270980071 0.42645941 0.62367626 0.78061459 1.03393310
-#> 22 0.003014390 0.37806468 0.53865575 -0.02348742 -0.05203418
-#> 23 -0.199571642 0.36542420 0.55525681 1.64772961 1.60485916
-#> 24 -0.393363218 0.54848421 1.17452890 0.06236571 1.43096800
-#> 25 -0.528747078 1.07503581 0.69402335 0.70311279 0.47734180
-#> 26 0.970732254 1.42372476 1.63614734 0.49273008 2.00920068
-#> 27 -1.573442460 -0.75277626 0.24610808 0.19206408 -1.35668872
-#> 28 0.316274462 -0.70178439 -0.07792268 -0.35759633 0.22701742
-#> 29 2.209822598 0.23992275 0.21586628 0.80925977 0.93311401
-#> 30 -1.785190406 -1.68593270 -0.26145023 -0.66968627 -0.45374470
-#>
-#>
-#> $covariates
-#> $covariates$uc1
-#> [1] 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885
-#> [7] 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885
-#> [13] 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885
-#> [19] 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885
-#> [25] 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885
-#> [31] 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224
-#> [37] 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224
-#> [43] 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224
-#> [49] 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224
-#> [55] 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224
-#> [61] 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258
-#> [67] 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258
-#> [73] 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258
-#> [79] 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258
-#> [85] 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258
-#> [91] -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661
-#> [97] -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661
-#> [103] -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661
-#> [109] -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661
-#> [115] -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661
-#> [121] -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261
-#> [127] -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261
-#> [133] -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261
-#> [139] -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261
-#> [145] -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261
-#> [151] -0.28039534 -0.28039534 -0.28039534 -0.28039534 -0.28039534 -0.28039534
-#> [157] -0.28039534 -0.28039534 -0.28039534 -0.28039534 -0.28039534 -0.28039534
-#> [163] -0.28039534 -0.28039534 -0.28039534 -0.28039534 -0.28039534 -0.28039534
-#> [169] -0.28039534 -0.28039534 -0.28039534 -0.28039534 -0.28039534 -0.28039534
-#> [175] -0.28039534 -0.28039534 -0.28039534 -0.28039534 -0.28039534 -0.28039534
-#> [181] 0.56298953 0.56298953 0.56298953 0.56298953 0.56298953 0.56298953
-#> [187] 0.56298953 0.56298953 0.56298953 0.56298953 0.56298953 0.56298953
-#> [193] 0.56298953 0.56298953 0.56298953 0.56298953 0.56298953 0.56298953
-#> [199] 0.56298953 0.56298953 0.56298953 0.56298953 0.56298953 0.56298953
-#> [205] 0.56298953 0.56298953 0.56298953 0.56298953 0.56298953 0.56298953
-#> [211] -0.37243876 -0.37243876 -0.37243876 -0.37243876 -0.37243876 -0.37243876
-#> [217] -0.37243876 -0.37243876 -0.37243876 -0.37243876 -0.37243876 -0.37243876
-#> [223] -0.37243876 -0.37243876 -0.37243876 -0.37243876 -0.37243876 -0.37243876
-#> [229] -0.37243876 -0.37243876 -0.37243876 -0.37243876 -0.37243876 -0.37243876
-#> [235] -0.37243876 -0.37243876 -0.37243876 -0.37243876 -0.37243876 -0.37243876
-#> [241] 0.97697339 0.97697339 0.97697339 0.97697339 0.97697339 0.97697339
-#> [247] 0.97697339 0.97697339 0.97697339 0.97697339 0.97697339 0.97697339
-#> [253] 0.97697339 0.97697339 0.97697339 0.97697339 0.97697339 0.97697339
-#> [259] 0.97697339 0.97697339 0.97697339 0.97697339 0.97697339 0.97697339
-#> [265] 0.97697339 0.97697339 0.97697339 0.97697339 0.97697339 0.97697339
-#> [271] -0.37458086 -0.37458086 -0.37458086 -0.37458086 -0.37458086 -0.37458086
-#> [277] -0.37458086 -0.37458086 -0.37458086 -0.37458086 -0.37458086 -0.37458086
-#> [283] -0.37458086 -0.37458086 -0.37458086 -0.37458086 -0.37458086 -0.37458086
-#> [289] -0.37458086 -0.37458086 -0.37458086 -0.37458086 -0.37458086 -0.37458086
-#> [295] -0.37458086 -0.37458086 -0.37458086 -0.37458086 -0.37458086 -0.37458086
-#> [301] 1.05271147 1.05271147 1.05271147 1.05271147 1.05271147 1.05271147
-#> [307] 1.05271147 1.05271147 1.05271147 1.05271147 1.05271147 1.05271147
-#> [313] 1.05271147 1.05271147 1.05271147 1.05271147 1.05271147 1.05271147
-#> [319] 1.05271147 1.05271147 1.05271147 1.05271147 1.05271147 1.05271147
-#> [325] 1.05271147 1.05271147 1.05271147 1.05271147 1.05271147 1.05271147
-#> [331] -1.04917701 -1.04917701 -1.04917701 -1.04917701 -1.04917701 -1.04917701
-#> [337] -1.04917701 -1.04917701 -1.04917701 -1.04917701 -1.04917701 -1.04917701
-#> [343] -1.04917701 -1.04917701 -1.04917701 -1.04917701 -1.04917701 -1.04917701
-#> [349] -1.04917701 -1.04917701 -1.04917701 -1.04917701 -1.04917701 -1.04917701
-#> [355] -1.04917701 -1.04917701 -1.04917701 -1.04917701 -1.04917701 -1.04917701
-#> [361] -1.26015524 -1.26015524 -1.26015524 -1.26015524 -1.26015524 -1.26015524
-#> [367] -1.26015524 -1.26015524 -1.26015524 -1.26015524 -1.26015524 -1.26015524
-#> [373] -1.26015524 -1.26015524 -1.26015524 -1.26015524 -1.26015524 -1.26015524
-#> [379] -1.26015524 -1.26015524 -1.26015524 -1.26015524 -1.26015524 -1.26015524
-#> [385] -1.26015524 -1.26015524 -1.26015524 -1.26015524 -1.26015524 -1.26015524
-#> [391] 3.24103993 3.24103993 3.24103993 3.24103993 3.24103993 3.24103993
-#> [397] 3.24103993 3.24103993 3.24103993 3.24103993 3.24103993 3.24103993
-#> [403] 3.24103993 3.24103993 3.24103993 3.24103993 3.24103993 3.24103993
-#> [409] 3.24103993 3.24103993 3.24103993 3.24103993 3.24103993 3.24103993
-#> [415] 3.24103993 3.24103993 3.24103993 3.24103993 3.24103993 3.24103993
-#> [421] -0.41685759 -0.41685759 -0.41685759 -0.41685759 -0.41685759 -0.41685759
-#> [427] -0.41685759 -0.41685759 -0.41685759 -0.41685759 -0.41685759 -0.41685759
-#> [433] -0.41685759 -0.41685759 -0.41685759 -0.41685759 -0.41685759 -0.41685759
-#> [439] -0.41685759 -0.41685759 -0.41685759 -0.41685759 -0.41685759 -0.41685759
-#> [445] -0.41685759 -0.41685759 -0.41685759 -0.41685759 -0.41685759 -0.41685759
-#> [451] 0.29822759 0.29822759 0.29822759 0.29822759 0.29822759 0.29822759
-#> [457] 0.29822759 0.29822759 0.29822759 0.29822759 0.29822759 0.29822759
-#> [463] 0.29822759 0.29822759 0.29822759 0.29822759 0.29822759 0.29822759
-#> [469] 0.29822759 0.29822759 0.29822759 0.29822759 0.29822759 0.29822759
-#> [475] 0.29822759 0.29822759 0.29822759 0.29822759 0.29822759 0.29822759
-#> [481] 0.63656967 0.63656967 0.63656967 0.63656967 0.63656967 0.63656967
-#> [487] 0.63656967 0.63656967 0.63656967 0.63656967 0.63656967 0.63656967
-#> [493] 0.63656967 0.63656967 0.63656967 0.63656967 0.63656967 0.63656967
-#> [499] 0.63656967 0.63656967 0.63656967 0.63656967 0.63656967 0.63656967
-#> [505] 0.63656967 0.63656967 0.63656967 0.63656967 0.63656967 0.63656967
-#> [511] -0.48378063 -0.48378063 -0.48378063 -0.48378063 -0.48378063 -0.48378063
-#> [517] -0.48378063 -0.48378063 -0.48378063 -0.48378063 -0.48378063 -0.48378063
-#> [523] -0.48378063 -0.48378063 -0.48378063 -0.48378063 -0.48378063 -0.48378063
-#> [529] -0.48378063 -0.48378063 -0.48378063 -0.48378063 -0.48378063 -0.48378063
-#> [535] -0.48378063 -0.48378063 -0.48378063 -0.48378063 -0.48378063 -0.48378063
-#> [541] 0.51686204 0.51686204 0.51686204 0.51686204 0.51686204 0.51686204
-#> [547] 0.51686204 0.51686204 0.51686204 0.51686204 0.51686204 0.51686204
-#> [553] 0.51686204 0.51686204 0.51686204 0.51686204 0.51686204 0.51686204
-#> [559] 0.51686204 0.51686204 0.51686204 0.51686204 0.51686204 0.51686204
-#> [565] 0.51686204 0.51686204 0.51686204 0.51686204 0.51686204 0.51686204
-#> [571] 0.36896453 0.36896453 0.36896453 0.36896453 0.36896453 0.36896453
-#> [577] 0.36896453 0.36896453 0.36896453 0.36896453 0.36896453 0.36896453
-#> [583] 0.36896453 0.36896453 0.36896453 0.36896453 0.36896453 0.36896453
-#> [589] 0.36896453 0.36896453 0.36896453 0.36896453 0.36896453 0.36896453
-#> [595] 0.36896453 0.36896453 0.36896453 0.36896453 0.36896453 0.36896453
-#> [601] -0.21538051 -0.21538051 -0.21538051 -0.21538051 -0.21538051 -0.21538051
-#> [607] -0.21538051 -0.21538051 -0.21538051 -0.21538051 -0.21538051 -0.21538051
-#> [613] -0.21538051 -0.21538051 -0.21538051 -0.21538051 -0.21538051 -0.21538051
-#> [619] -0.21538051 -0.21538051 -0.21538051 -0.21538051 -0.21538051 -0.21538051
-#> [625] -0.21538051 -0.21538051 -0.21538051 -0.21538051 -0.21538051 -0.21538051
-#> [631] 0.06529303 0.06529303 0.06529303 0.06529303 0.06529303 0.06529303
-#> [637] 0.06529303 0.06529303 0.06529303 0.06529303 0.06529303 0.06529303
-#> [643] 0.06529303 0.06529303 0.06529303 0.06529303 0.06529303 0.06529303
-#> [649] 0.06529303 0.06529303 0.06529303 0.06529303 0.06529303 0.06529303
-#> [655] 0.06529303 0.06529303 0.06529303 0.06529303 0.06529303 0.06529303
-#> [661] -0.03406725 -0.03406725 -0.03406725 -0.03406725 -0.03406725 -0.03406725
-#> [667] -0.03406725 -0.03406725 -0.03406725 -0.03406725 -0.03406725 -0.03406725
-#> [673] -0.03406725 -0.03406725 -0.03406725 -0.03406725 -0.03406725 -0.03406725
-#> [679] -0.03406725 -0.03406725 -0.03406725 -0.03406725 -0.03406725 -0.03406725
-#> [685] -0.03406725 -0.03406725 -0.03406725 -0.03406725 -0.03406725 -0.03406725
-#> [691] 2.12845190 2.12845190 2.12845190 2.12845190 2.12845190 2.12845190
-#> [697] 2.12845190 2.12845190 2.12845190 2.12845190 2.12845190 2.12845190
-#> [703] 2.12845190 2.12845190 2.12845190 2.12845190 2.12845190 2.12845190
-#> [709] 2.12845190 2.12845190 2.12845190 2.12845190 2.12845190 2.12845190
-#> [715] 2.12845190 2.12845190 2.12845190 2.12845190 2.12845190 2.12845190
-#> [721] -0.74133610 -0.74133610 -0.74133610 -0.74133610 -0.74133610 -0.74133610
-#> [727] -0.74133610 -0.74133610 -0.74133610 -0.74133610 -0.74133610 -0.74133610
-#> [733] -0.74133610 -0.74133610 -0.74133610 -0.74133610 -0.74133610 -0.74133610
-#> [739] -0.74133610 -0.74133610 -0.74133610 -0.74133610 -0.74133610 -0.74133610
-#> [745] -0.74133610 -0.74133610 -0.74133610 -0.74133610 -0.74133610 -0.74133610
-#> [751] -1.09599627 -1.09599627 -1.09599627 -1.09599627 -1.09599627 -1.09599627
-#> [757] -1.09599627 -1.09599627 -1.09599627 -1.09599627 -1.09599627 -1.09599627
-#> [763] -1.09599627 -1.09599627 -1.09599627 -1.09599627 -1.09599627 -1.09599627
-#> [769] -1.09599627 -1.09599627 -1.09599627 -1.09599627 -1.09599627 -1.09599627
-#> [775] -1.09599627 -1.09599627 -1.09599627 -1.09599627 -1.09599627 -1.09599627
-#> [781] 0.03778840 0.03778840 0.03778840 0.03778840 0.03778840 0.03778840
-#> [787] 0.03778840 0.03778840 0.03778840 0.03778840 0.03778840 0.03778840
-#> [793] 0.03778840 0.03778840 0.03778840 0.03778840 0.03778840 0.03778840
-#> [799] 0.03778840 0.03778840 0.03778840 0.03778840 0.03778840 0.03778840
-#> [805] 0.03778840 0.03778840 0.03778840 0.03778840 0.03778840 0.03778840
-#> [811] 0.31048075 0.31048075 0.31048075 0.31048075 0.31048075 0.31048075
-#> [817] 0.31048075 0.31048075 0.31048075 0.31048075 0.31048075 0.31048075
-#> [823] 0.31048075 0.31048075 0.31048075 0.31048075 0.31048075 0.31048075
-#> [829] 0.31048075 0.31048075 0.31048075 0.31048075 0.31048075 0.31048075
-#> [835] 0.31048075 0.31048075 0.31048075 0.31048075 0.31048075 0.31048075
-#> [841] 0.43652348 0.43652348 0.43652348 0.43652348 0.43652348 0.43652348
-#> [847] 0.43652348 0.43652348 0.43652348 0.43652348 0.43652348 0.43652348
-#> [853] 0.43652348 0.43652348 0.43652348 0.43652348 0.43652348 0.43652348
-#> [859] 0.43652348 0.43652348 0.43652348 0.43652348 0.43652348 0.43652348
-#> [865] 0.43652348 0.43652348 0.43652348 0.43652348 0.43652348 0.43652348
-#> [871] -0.45836533 -0.45836533 -0.45836533 -0.45836533 -0.45836533 -0.45836533
-#> [877] -0.45836533 -0.45836533 -0.45836533 -0.45836533 -0.45836533 -0.45836533
-#> [883] -0.45836533 -0.45836533 -0.45836533 -0.45836533 -0.45836533 -0.45836533
-#> [889] -0.45836533 -0.45836533 -0.45836533 -0.45836533 -0.45836533 -0.45836533
-#> [895] -0.45836533 -0.45836533 -0.45836533 -0.45836533 -0.45836533 -0.45836533
-#> [901] -1.06332613 -1.06332613 -1.06332613 -1.06332613 -1.06332613 -1.06332613
-#> [907] -1.06332613 -1.06332613 -1.06332613 -1.06332613 -1.06332613 -1.06332613
-#> [913] -1.06332613 -1.06332613 -1.06332613 -1.06332613 -1.06332613 -1.06332613
-#> [919] -1.06332613 -1.06332613 -1.06332613 -1.06332613 -1.06332613 -1.06332613
-#> [925] -1.06332613 -1.06332613 -1.06332613 -1.06332613 -1.06332613 -1.06332613
-#> [931] 1.26318518 1.26318518 1.26318518 1.26318518 1.26318518 1.26318518
-#> [937] 1.26318518 1.26318518 1.26318518 1.26318518 1.26318518 1.26318518
-#> [943] 1.26318518 1.26318518 1.26318518 1.26318518 1.26318518 1.26318518
-#> [949] 1.26318518 1.26318518 1.26318518 1.26318518 1.26318518 1.26318518
-#> [955] 1.26318518 1.26318518 1.26318518 1.26318518 1.26318518 1.26318518
-#> [961] -0.34965039 -0.34965039 -0.34965039 -0.34965039 -0.34965039 -0.34965039
-#> [967] -0.34965039 -0.34965039 -0.34965039 -0.34965039 -0.34965039 -0.34965039
-#> [973] -0.34965039 -0.34965039 -0.34965039 -0.34965039 -0.34965039 -0.34965039
-#> [979] -0.34965039 -0.34965039 -0.34965039 -0.34965039 -0.34965039 -0.34965039
-#> [985] -0.34965039 -0.34965039 -0.34965039 -0.34965039 -0.34965039 -0.34965039
-#> [991] -0.86551286 -0.86551286 -0.86551286 -0.86551286 -0.86551286 -0.86551286
-#> [997] -0.86551286 -0.86551286 -0.86551286 -0.86551286 -0.86551286 -0.86551286
-#> [1003] -0.86551286 -0.86551286 -0.86551286 -0.86551286 -0.86551286 -0.86551286
-#> [1009] -0.86551286 -0.86551286 -0.86551286 -0.86551286 -0.86551286 -0.86551286
-#> [1015] -0.86551286 -0.86551286 -0.86551286 -0.86551286 -0.86551286 -0.86551286
-#> [1021] -0.23627957 -0.23627957 -0.23627957 -0.23627957 -0.23627957 -0.23627957
-#> [1027] -0.23627957 -0.23627957 -0.23627957 -0.23627957 -0.23627957 -0.23627957
-#> [1033] -0.23627957 -0.23627957 -0.23627957 -0.23627957 -0.23627957 -0.23627957
-#> [1039] -0.23627957 -0.23627957 -0.23627957 -0.23627957 -0.23627957 -0.23627957
-#> [1045] -0.23627957 -0.23627957 -0.23627957 -0.23627957 -0.23627957 -0.23627957
-#> [1051] -0.19717589 -0.19717589 -0.19717589 -0.19717589 -0.19717589 -0.19717589
-#> [1057] -0.19717589 -0.19717589 -0.19717589 -0.19717589 -0.19717589 -0.19717589
-#> [1063] -0.19717589 -0.19717589 -0.19717589 -0.19717589 -0.19717589 -0.19717589
-#> [1069] -0.19717589 -0.19717589 -0.19717589 -0.19717589 -0.19717589 -0.19717589
-#> [1075] -0.19717589 -0.19717589 -0.19717589 -0.19717589 -0.19717589 -0.19717589
-#> [1081] 1.10992029 1.10992029 1.10992029 1.10992029 1.10992029 1.10992029
-#> [1087] 1.10992029 1.10992029 1.10992029 1.10992029 1.10992029 1.10992029
-#> [1093] 1.10992029 1.10992029 1.10992029 1.10992029 1.10992029 1.10992029
-#> [1099] 1.10992029 1.10992029 1.10992029 1.10992029 1.10992029 1.10992029
-#> [1105] 1.10992029 1.10992029 1.10992029 1.10992029 1.10992029 1.10992029
-#> [1111] 0.08473729 0.08473729 0.08473729 0.08473729 0.08473729 0.08473729
-#> [1117] 0.08473729 0.08473729 0.08473729 0.08473729 0.08473729 0.08473729
-#> [1123] 0.08473729 0.08473729 0.08473729 0.08473729 0.08473729 0.08473729
-#> [1129] 0.08473729 0.08473729 0.08473729 0.08473729 0.08473729 0.08473729
-#> [1135] 0.08473729 0.08473729 0.08473729 0.08473729 0.08473729 0.08473729
-#> [1141] 0.75405379 0.75405379 0.75405379 0.75405379 0.75405379 0.75405379
-#> [1147] 0.75405379 0.75405379 0.75405379 0.75405379 0.75405379 0.75405379
-#> [1153] 0.75405379 0.75405379 0.75405379 0.75405379 0.75405379 0.75405379
-#> [1159] 0.75405379 0.75405379 0.75405379 0.75405379 0.75405379 0.75405379
-#> [1165] 0.75405379 0.75405379 0.75405379 0.75405379 0.75405379 0.75405379
-#> [1171] -0.49929202 -0.49929202 -0.49929202 -0.49929202 -0.49929202 -0.49929202
-#> [1177] -0.49929202 -0.49929202 -0.49929202 -0.49929202 -0.49929202 -0.49929202
-#> [1183] -0.49929202 -0.49929202 -0.49929202 -0.49929202 -0.49929202 -0.49929202
-#> [1189] -0.49929202 -0.49929202 -0.49929202 -0.49929202 -0.49929202 -0.49929202
-#> [1195] -0.49929202 -0.49929202 -0.49929202 -0.49929202 -0.49929202 -0.49929202
-#> [1201] 0.21444531 0.21444531 0.21444531 0.21444531 0.21444531 0.21444531
-#> [1207] 0.21444531 0.21444531 0.21444531 0.21444531 0.21444531 0.21444531
-#> [1213] 0.21444531 0.21444531 0.21444531 0.21444531 0.21444531 0.21444531
-#> [1219] 0.21444531 0.21444531 0.21444531 0.21444531 0.21444531 0.21444531
-#> [1225] 0.21444531 0.21444531 0.21444531 0.21444531 0.21444531 0.21444531
-#> [1231] -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591
-#> [1237] -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591
-#> [1243] -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591
-#> [1249] -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591
-#> [1255] -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591
-#> [1261] 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353
-#> [1267] 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353
-#> [1273] 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353
-#> [1279] 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353
-#> [1285] 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353
-#> [1291] -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336
-#> [1297] -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336
-#> [1303] -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336
-#> [1309] -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336
-#> [1315] -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336
-#> [1321] -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153
-#> [1327] -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153
-#> [1333] -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153
-#> [1339] -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153
-#> [1345] -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153
-#> [1351] 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338
-#> [1357] 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338
-#> [1363] 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338
-#> [1369] 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338
-#> [1375] 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338
-#> [1381] 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882
-#> [1387] 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882
-#> [1393] 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882
-#> [1399] 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882
-#> [1405] 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882
-#> [1411] -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136
-#> [1417] -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136
-#> [1423] -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136
-#> [1429] -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136
-#> [1435] -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136
-#> [1441] -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592
-#> [1447] -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592
-#> [1453] -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592
-#> [1459] -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592
-#> [1465] -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592
-#> [1471] -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008
-#> [1477] -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008
-#> [1483] -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008
-#> [1489] -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008
-#> [1495] -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008
-#>
-#> $covariates$ec1
-#> [1] 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242
-#> [7] 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242
-#> [13] 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242
-#> [19] 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242
-#> [25] 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242
-#> [31] 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368
-#> [37] 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368
-#> [43] 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368
-#> [49] 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368
-#> [55] 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368
-#> [61] -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991
-#> [67] -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991
-#> [73] -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991
-#> [79] -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991
-#> [85] -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991
-#> [91] 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344
-#> [97] 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344
-#> [103] 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344
-#> [109] 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344
-#> [115] 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344
-#> [121] 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264
-#> [127] 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264
-#> [133] 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264
-#> [139] 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264
-#> [145] 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264
-#> [151] -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384
-#> [157] -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384
-#> [163] -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384
-#> [169] -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384
-#> [175] -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384
-#> [181] 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556
-#> [187] 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556
-#> [193] 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556
-#> [199] 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556
-#> [205] 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556
-#> [211] 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648
-#> [217] 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648
-#> [223] 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648
-#> [229] 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648
-#> [235] 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648
-#> [241] -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639
-#> [247] -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639
-#> [253] -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639
-#> [259] -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639
-#> [265] -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639
-#> [271] -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176
-#> [277] -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176
-#> [283] -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176
-#> [289] -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176
-#> [295] -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176
-#> [301] 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761
-#> [307] 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761
-#> [313] 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761
-#> [319] 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761
-#> [325] 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761
-#> [331] -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845
-#> [337] -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845
-#> [343] -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845
-#> [349] -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845
-#> [355] -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845
-#> [361] 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299
-#> [367] 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299
-#> [373] 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299
-#> [379] 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299
-#> [385] 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299
-#> [391] -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278
-#> [397] -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278
-#> [403] -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278
-#> [409] -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278
-#> [415] -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278
-#> [421] 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653
-#> [427] 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653
-#> [433] 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653
-#> [439] 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653
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-#> [1597] -0.19070343 -0.19070343 -0.19070343 -0.19070343 -0.19070343 -0.19070343
-#> [1603] -0.19070343 -0.19070343 -0.19070343 -0.19070343 -0.19070343 -0.19070343
-#> [1609] -0.19070343 -0.19070343 -0.19070343 -0.19070343 -0.19070343 -0.19070343
-#> [1615] -0.19070343 -0.19070343 -0.19070343 -0.19070343 -0.19070343 -0.19070343
-#> [1621] -0.09616320 -0.09616320 -0.09616320 -0.09616320 -0.09616320 -0.09616320
-#> [1627] -0.09616320 -0.09616320 -0.09616320 -0.09616320 -0.09616320 -0.09616320
-#> [1633] -0.09616320 -0.09616320 -0.09616320 -0.09616320 -0.09616320 -0.09616320
-#> [1639] -0.09616320 -0.09616320 -0.09616320 -0.09616320 -0.09616320 -0.09616320
-#> [1645] -0.09616320 -0.09616320 -0.09616320 -0.09616320 -0.09616320 -0.09616320
-#> [1651] -0.69341466 -0.69341466 -0.69341466 -0.69341466 -0.69341466 -0.69341466
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-#> [1669] -0.69341466 -0.69341466 -0.69341466 -0.69341466 -0.69341466 -0.69341466
-#> [1675] -0.69341466 -0.69341466 -0.69341466 -0.69341466 -0.69341466 -0.69341466
-#> [1681] -0.15689195 -0.15689195 -0.15689195 -0.15689195 -0.15689195 -0.15689195
-#> [1687] -0.15689195 -0.15689195 -0.15689195 -0.15689195 -0.15689195 -0.15689195
-#> [1693] -0.15689195 -0.15689195 -0.15689195 -0.15689195 -0.15689195 -0.15689195
-#> [1699] -0.15689195 -0.15689195 -0.15689195 -0.15689195 -0.15689195 -0.15689195
-#> [1705] -0.15689195 -0.15689195 -0.15689195 -0.15689195 -0.15689195 -0.15689195
-#> [1711] 0.09690423 0.09690423 0.09690423 0.09690423 0.09690423 0.09690423
-#> [1717] 0.09690423 0.09690423 0.09690423 0.09690423 0.09690423 0.09690423
-#> [1723] 0.09690423 0.09690423 0.09690423 0.09690423 0.09690423 0.09690423
-#> [1729] 0.09690423 0.09690423 0.09690423 0.09690423 0.09690423 0.09690423
-#> [1735] 0.09690423 0.09690423 0.09690423 0.09690423 0.09690423 0.09690423
-#> [1741] 1.19707766 1.19707766 1.19707766 1.19707766 1.19707766 1.19707766
-#> [1747] 1.19707766 1.19707766 1.19707766 1.19707766 1.19707766 1.19707766
-#> [1753] 1.19707766 1.19707766 1.19707766 1.19707766 1.19707766 1.19707766
-#> [1759] 1.19707766 1.19707766 1.19707766 1.19707766 1.19707766 1.19707766
-#> [1765] 1.19707766 1.19707766 1.19707766 1.19707766 1.19707766 1.19707766
-#> [1771] -1.00537758 -1.00537758 -1.00537758 -1.00537758 -1.00537758 -1.00537758
-#> [1777] -1.00537758 -1.00537758 -1.00537758 -1.00537758 -1.00537758 -1.00537758
-#> [1783] -1.00537758 -1.00537758 -1.00537758 -1.00537758 -1.00537758 -1.00537758
-#> [1789] -1.00537758 -1.00537758 -1.00537758 -1.00537758 -1.00537758 -1.00537758
-#> [1795] -1.00537758 -1.00537758 -1.00537758 -1.00537758 -1.00537758 -1.00537758
-#> [1801] -1.62185826 -1.62185826 -1.62185826 -1.62185826 -1.62185826 -1.62185826
-#> [1807] -1.62185826 -1.62185826 -1.62185826 -1.62185826 -1.62185826 -1.62185826
-#> [1813] -1.62185826 -1.62185826 -1.62185826 -1.62185826 -1.62185826 -1.62185826
-#> [1819] -1.62185826 -1.62185826 -1.62185826 -1.62185826 -1.62185826 -1.62185826
-#> [1825] -1.62185826 -1.62185826 -1.62185826 -1.62185826 -1.62185826 -1.62185826
-#> [1831] 0.95536564 0.95536564 0.95536564 0.95536564 0.95536564 0.95536564
-#> [1837] 0.95536564 0.95536564 0.95536564 0.95536564 0.95536564 0.95536564
-#> [1843] 0.95536564 0.95536564 0.95536564 0.95536564 0.95536564 0.95536564
-#> [1849] 0.95536564 0.95536564 0.95536564 0.95536564 0.95536564 0.95536564
-#> [1855] 0.95536564 0.95536564 0.95536564 0.95536564 0.95536564 0.95536564
-#> [1861] 0.04673353 0.04673353 0.04673353 0.04673353 0.04673353 0.04673353
-#> [1867] 0.04673353 0.04673353 0.04673353 0.04673353 0.04673353 0.04673353
-#> [1873] 0.04673353 0.04673353 0.04673353 0.04673353 0.04673353 0.04673353
-#> [1879] 0.04673353 0.04673353 0.04673353 0.04673353 0.04673353 0.04673353
-#> [1885] 0.04673353 0.04673353 0.04673353 0.04673353 0.04673353 0.04673353
-#> [1891] -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706
-#> [1897] -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706
-#> [1903] -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706
-#> [1909] -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706
-#> [1915] -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706
-#> [1921] -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837
-#> [1927] -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837
-#> [1933] -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837
-#> [1939] -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837
-#> [1945] -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837
-#> [1951] -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001
-#> [1957] -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001
-#> [1963] -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001
-#> [1969] -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001
-#> [1975] -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001
-#> [1981] 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718
-#> [1987] 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718
-#> [1993] 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718
-#> [1999] 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718
-#> [2005] 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718
-#> [2011] -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945
-#> [2017] -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945
-#> [2023] -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945
-#> [2029] -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945
-#> [2035] -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945
-#> [2041] 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361
-#> [2047] 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361
-#> [2053] 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361
-#> [2059] 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361
-#> [2065] 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361
-#> [2071] -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520
-#> [2077] -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520
-#> [2083] -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520
-#> [2089] -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520
-#> [2095] -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520
-#> [2101] -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068
-#> [2107] -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068
-#> [2113] -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068
-#> [2119] -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068
-#> [2125] -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068
-#> [2131] -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513
-#> [2137] -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513
-#> [2143] -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513
-#> [2149] -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513
-#> [2155] -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513
-#> [2161] 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737
-#> [2167] 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737
-#> [2173] 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737
-#> [2179] 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737
-#> [2185] 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737
-#> [2191] 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602
-#> [2197] 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602
-#> [2203] 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602
-#> [2209] 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602
-#> [2215] 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602
-#> [2221] 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115
-#> [2227] 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115
-#> [2233] 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115
-#> [2239] 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115
-#> [2245] 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115
-#> [2251] 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736
-#> [2257] 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736
-#> [2263] 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736
-#> [2269] 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736
-#> [2275] 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736
-#> [2281] 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624
-#> [2287] 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624
-#> [2293] 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624
-#> [2299] 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624
-#> [2305] 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624
-#> [2311] 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635
-#> [2317] 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635
-#> [2323] 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635
-#> [2329] 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635
-#> [2335] 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635
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-#> [2353] 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157
-#> [2359] 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157
-#> [2365] 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157
-#> [2371] 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882
-#> [2377] 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882
-#> [2383] 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882
-#> [2389] 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882
-#> [2395] 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882
-#> [2401] -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224
-#> [2407] -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224
-#> [2413] -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224
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-#> [2425] -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224
-#> [2431] -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088
-#> [2437] -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088
-#> [2443] -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088
-#> [2449] -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088
-#> [2455] -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088
-#> [2461] -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664
-#> [2467] -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664
-#> [2473] -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664
-#> [2479] -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664
-#> [2485] -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664
-#> [2491] 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526
-#> [2497] 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526
-#> [2503] 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526
-#> [2509] 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526
-#> [2515] 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526
-#> [2521] 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098
-#> [2527] 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098
-#> [2533] 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098
-#> [2539] 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098
-#> [2545] 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098
-#> [2551] 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801
-#> [2557] 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801
-#> [2563] 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801
-#> [2569] 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801
-#> [2575] 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801
-#> [2581] 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696
-#> [2587] 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696
-#> [2593] 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696
-#> [2599] 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696
-#> [2605] 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696
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-#> [5881] -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924
-#> [5887] -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924
-#> [5893] -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924
-#> [5899] -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924
-#> [5905] -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924
-#> [5911] -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637
-#> [5917] -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637
-#> [5923] -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637
-#> [5929] -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637
-#> [5935] -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637
-#> [5941] -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344
-#> [5947] -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344
-#> [5953] -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344
-#> [5959] -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344
-#> [5965] -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344
-#> [5971] -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462
-#> [5977] -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462
-#> [5983] -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462
-#> [5989] -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462
-#> [5995] -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462
-#>
-#>
-
get shared elements between two vectors
-shared_elements(x, y)
vector
vector
all unique elements that occur at least once in both x and y
-make_flocker_data()
and downstream
-functions.R/simulate_flocker_data.R
- simulate_flocker_data.Rd
Data will be simulated with one unit covariate that affects all -relevant terms, one event covariate that affects detection (unless -`rep_constant` is `TRUE`), and one grouping factor representing species -with correlated effects on all terms.
-simulate_flocker_data(
- n_rep = 4,
- n_pt = 50,
- n_sp = 30,
- n_season = 1,
- multiseason = NULL,
- multi_init = NULL,
- augmented = FALSE,
- rep_constant = FALSE,
- params = NULL,
- covariates = NULL,
- seed = 123,
- ragged_rep = FALSE,
- missing_seasons = FALSE
-)
number of replicate visits to simulate per closure unit
number of points to simulate. The number of units for single- -season models will be `n_pt*n_sp`. The number of units for multi-season -models will be `n_pt*n_sp*n_season`.
number of levels to include in random effect. For compatibility -with multispecies models where the random effect represents species, -the data get expanded such that there's a row (closure-unit) for each -combination of sampling point and effect level (i.e. species)
Number of seasons desired. 1 yields data for a single-season -model; all other positive integers yield data for multiseason models.
if n_season is NULL, must be NULL. Otherwise, one of -"colex" or "autologistic".
if n_season is NULL, must be NULL. Otherwise, one of -"explicit" or "equilibrium".
logical. If `TRUE` data will be formatted for an augmented -model, which requires that `n_season == 1`. All never-observed -species will be trimmed out of the data, and the default parameters will be -modified to increase random effect variances for the detection and occupancy, -intercepts and to decrease random effect variances for detection slopes, thus -encouraging the existence of never-observed species. Furthermore, the data will -be simulated without any covariate influence on occupancy.
logical: create data with unit covariates only (TRUE) -or data that includes event covariates (FALSE)
a named list containing of parameter values to use in simulation. -Any required parameters whose names are not in this list will be assigned their -default values. To see the parameter names and structures required, run with -`params = NULL` (the default) and examine the `$params` element of the output.
a dataframe of covariate values to use in simulation, or -NULL to simulate values. To see the covariate names and structures required, -run with `covariates = NULL` (the default) and examine the `$covariates` element -of the output.
random seed. NULL uses (and updates) the existing RNG state. Other values -do not update the global RNG state.
logical: create data with variable (TRUE) or constant -(FALSE) numbers of visits per unit. If TRUE, approximately half of units -will be missing approximately half of `n_rep` visits. Intended primarily for -development purposes (bug-checking models with missing data).
logical; relevant only if n_season is greater than 1. -create data with variable (TRUE) or constant (FALSE) numbers of seasons per -series (TRUE). If TRUE, approximately half of series will be missing their -even-numbered seasons.
A named list with the observation matrix/array ($obs), the unit covariate - dataframe(s) ($unit_covs), the event covariate list ($event_covs), the parameters - used in simulation ($params) and the covariate list used in simulation ($covariates). - If rep_constant is TRUE, then $event_covs will be NULL.
-simulate_flocker_data()
-#> $obs
-#> [,1] [,2] [,3] [,4]
-#> [1,] 0 0 0 0
-#> [2,] 0 0 0 0
-#> [3,] 1 1 1 0
-#> [4,] 1 1 1 1
-#> [5,] 0 0 0 0
-#> [6,] 0 0 0 0
-#> [7,] 1 1 1 1
-#> [8,] 1 1 1 0
-#> [9,] 0 0 0 0
-#> [10,] 0 0 0 0
-#> [11,] 0 0 0 0
-#> [12,] 0 0 0 0
-#> [13,] 0 0 0 0
-#> [14,] 0 0 0 0
-#> [15,] 0 0 0 0
-#> [16,] 0 0 0 0
-#> [17,] 0 0 0 0
-#> [18,] 0 0 0 0
-#> [19,] 1 1 0 1
-#> [20,] 1 1 1 1
-#> [21,] 0 0 0 0
-#> [22,] 0 0 0 0
-#> [23,] 0 1 1 1
-#> [24,] 0 0 0 0
-#> [25,] 0 0 0 0
-#> [26,] 1 1 0 0
-#> [27,] 0 0 0 0
-#> [28,] 0 0 0 0
-#> [29,] 0 0 0 0
-#> [30,] 0 0 0 0
-#> [31,] 0 0 0 0
-#> [32,] 1 1 1 1
-#> [33,] 1 1 1 0
-#> [34,] 1 1 1 1
-#> [35,] 0 1 1 0
-#> [36,] 0 1 1 1
-#> [37,] 0 0 0 0
-#> [38,] 0 0 0 0
-#> [39,] 1 1 1 1
-#> [40,] 0 0 0 0
-#> [41,] 0 1 0 0
-#> [42,] 1 0 1 0
-#> [43,] 0 1 1 1
-#> [44,] 0 0 0 0
-#> [45,] 0 0 0 1
-#> [46,] 0 0 0 0
-#> [47,] 0 0 0 0
-#> [48,] 0 0 0 0
-#> [49,] 0 0 0 0
-#> [50,] 0 0 0 0
-#> [51,] 0 1 0 1
-#> [52,] 1 1 0 0
-#> [53,] 1 0 0 0
-#> [54,] 0 0 0 0
-#> [55,] 1 0 1 0
-#> [56,] 0 1 0 0
-#> [57,] 0 0 0 0
-#> [58,] 0 1 0 1
-#> [59,] 0 0 0 0
-#> [60,] 0 0 1 0
-#> [61,] 0 1 1 0
-#> [62,] 0 0 0 0
-#> [63,] 0 0 0 0
-#> [64,] 1 1 1 1
-#> [65,] 0 0 0 0
-#> [66,] 0 0 0 0
-#> [67,] 0 0 0 0
-#> [68,] 0 1 0 1
-#> [69,] 0 0 1 0
-#> [70,] 0 0 0 0
-#> [71,] 0 0 0 0
-#> [72,] 0 0 0 0
-#> [73,] 0 1 0 1
-#> [74,] 1 1 1 1
-#> [75,] 0 1 0 1
-#> [76,] 0 0 0 0
-#> [77,] 0 0 1 0
-#> [78,] 0 0 0 0
-#> [79,] 0 0 1 0
-#> [80,] 0 0 0 0
-#> [81,] 0 1 0 0
-#> [82,] 1 0 1 1
-#> [83,] 0 0 0 1
-#> [84,] 0 0 0 0
-#> [85,] 0 0 1 0
-#> [86,] 0 0 0 0
-#> [87,] 1 1 0 1
-#> [88,] 0 0 0 0
-#> [89,] 0 0 0 0
-#> [90,] 0 0 0 0
-#> [91,] 0 1 1 0
-#> [92,] 1 0 0 1
-#> [93,] 0 1 0 0
-#> [94,] 0 0 0 0
-#> [95,] 0 1 1 0
-#> [96,] 0 0 0 0
-#> [97,] 1 0 1 1
-#> [98,] 0 0 0 0
-#> [99,] 0 0 0 1
-#> [100,] 0 0 0 0
-#> [101,] 0 0 0 0
-#> [102,] 0 0 0 0
-#> [103,] 0 0 0 0
-#> [104,] 0 0 0 0
-#> [105,] 0 0 0 0
-#> [106,] 0 0 0 0
-#> [107,] 0 0 0 0
-#> [108,] 0 0 0 0
-#> [109,] 0 0 0 0
-#> [110,] 0 0 0 0
-#> [111,] 0 0 0 0
-#> [112,] 0 0 0 0
-#> [113,] 0 0 0 0
-#> [114,] 0 0 0 0
-#> [115,] 0 0 0 0
-#> [116,] 0 0 1 0
-#> [117,] 0 0 0 0
-#> [118,] 1 0 0 0
-#> [119,] 0 0 0 0
-#> [120,] 0 0 0 0
-#> [121,] 0 0 0 0
-#> [122,] 0 0 0 0
-#> [123,] 0 0 0 0
-#> [124,] 0 0 0 0
-#> [125,] 0 0 0 0
-#> [126,] 1 0 0 1
-#> [127,] 0 0 0 0
-#> [128,] 0 0 0 0
-#> [129,] 0 0 0 0
-#> [130,] 0 0 0 0
-#> [131,] 0 0 0 0
-#> [132,] 0 0 0 0
-#> [133,] 0 0 0 1
-#> [134,] 0 0 0 0
-#> [135,] 0 0 0 0
-#> [136,] 0 0 0 0
-#> [137,] 0 0 0 0
-#> [138,] 0 0 0 0
-#> [139,] 0 0 0 0
-#> [140,] 0 0 0 1
-#> [141,] 0 0 0 0
-#> [142,] 0 0 0 0
-#> [143,] 0 0 0 0
-#> [144,] 0 0 0 0
-#> [145,] 0 0 0 0
-#> [146,] 0 0 0 0
-#> [147,] 0 0 0 0
-#> [148,] 1 0 0 0
-#> [149,] 0 0 0 0
-#> [150,] 0 0 0 0
-#> [151,] 0 1 0 1
-#> [152,] 0 0 0 0
-#> [153,] 1 0 1 0
-#> [154,] 0 0 0 0
-#> [155,] 0 0 0 0
-#> [156,] 0 1 0 0
-#> [157,] 0 0 0 1
-#> [158,] 0 0 1 0
-#> [159,] 0 0 1 0
-#> [160,] 0 0 0 0
-#> [161,] 0 0 0 0
-#> [162,] 1 1 0 0
-#> [163,] 0 0 0 0
-#> [164,] 1 0 1 0
-#> [165,] 1 1 1 1
-#> [166,] 0 0 0 0
-#> [167,] 0 1 1 0
-#> [168,] 0 0 0 0
-#> [169,] 1 0 0 0
-#> [170,] 0 1 1 1
-#> [171,] 1 0 1 1
-#> [172,] 0 0 0 0
-#> [173,] 0 0 0 0
-#> [174,] 0 0 1 0
-#> [175,] 0 0 0 0
-#> [176,] 0 0 0 1
-#> [177,] 0 1 0 0
-#> [178,] 0 0 1 0
-#> [179,] 1 1 0 0
-#> [180,] 0 0 0 0
-#> [181,] 0 0 0 1
-#> [182,] 1 0 0 0
-#> [183,] 0 0 0 0
-#> [184,] 0 0 0 0
-#> [185,] 0 1 1 0
-#> [186,] 0 0 0 0
-#> [187,] 0 0 0 0
-#> [188,] 0 0 0 0
-#> [189,] 0 1 0 1
-#> [190,] 0 0 0 0
-#> [191,] 0 0 0 0
-#> [192,] 0 1 0 0
-#> [193,] 0 0 0 0
-#> [194,] 0 0 0 1
-#> [195,] 0 0 0 0
-#> [196,] 0 0 1 1
-#> [197,] 0 0 0 0
-#> [198,] 0 0 0 0
-#> [199,] 0 1 1 1
-#> [200,] 0 0 0 0
-#> [201,] 0 0 0 0
-#> [202,] 0 0 0 0
-#> [203,] 0 0 0 0
-#> [204,] 0 0 0 0
-#> [205,] 0 0 0 0
-#> [206,] 0 0 0 0
-#> [207,] 0 1 1 1
-#> [208,] 0 0 0 0
-#> [209,] 0 0 0 0
-#> [210,] 0 0 0 0
-#> [211,] 0 0 0 0
-#> [212,] 0 0 0 0
-#> [213,] 0 0 0 0
-#> [214,] 0 0 0 0
-#> [215,] 0 1 1 1
-#> [216,] 0 0 0 0
-#> [217,] 0 0 0 0
-#> [218,] 0 0 0 0
-#> [219,] 0 0 0 0
-#> [220,] 0 0 0 0
-#> [221,] 0 1 1 1
-#> [222,] 0 0 0 0
-#> [223,] 0 0 0 0
-#> [224,] 0 0 0 0
-#> [225,] 0 0 0 0
-#> [226,] 0 0 0 0
-#> [227,] 0 0 1 0
-#> [228,] 0 0 0 0
-#> [229,] 1 1 1 1
-#> [230,] 1 0 1 1
-#> [231,] 1 1 1 1
-#> [232,] 0 0 0 0
-#> [233,] 0 0 0 0
-#> [234,] 0 0 0 0
-#> [235,] 0 0 0 0
-#> [236,] 0 0 0 0
-#> [237,] 1 1 1 0
-#> [238,] 0 0 0 0
-#> [239,] 0 0 0 0
-#> [240,] 0 0 0 0
-#> [241,] 1 1 1 1
-#> [242,] 1 1 1 1
-#> [243,] 1 1 1 1
-#> [244,] 1 0 0 0
-#> [245,] 0 0 0 0
-#> [246,] 1 0 1 1
-#> [247,] 0 0 0 0
-#> [248,] 0 0 0 0
-#> [249,] 0 0 0 0
-#> [250,] 0 0 0 0
-#> [251,] 0 0 0 0
-#> [252,] 0 0 0 0
-#> [253,] 0 0 0 0
-#> [254,] 1 0 1 0
-#> [255,] 0 0 0 0
-#> [256,] 0 0 0 0
-#> [257,] 0 0 0 0
-#> [258,] 0 1 0 0
-#> [259,] 0 0 0 0
-#> [260,] 0 0 0 0
-#> [261,] 0 0 0 0
-#> [262,] 0 0 0 0
-#> [263,] 0 0 0 0
-#> [264,] 0 0 0 0
-#> [265,] 0 0 0 0
-#> [266,] 0 0 0 0
-#> [267,] 0 0 0 0
-#> [268,] 0 1 0 1
-#> [269,] 0 0 0 0
-#> [270,] 0 0 0 0
-#> [271,] 0 0 0 0
-#> [272,] 0 0 0 0
-#> [273,] 0 0 0 0
-#> [274,] 0 0 0 0
-#> [275,] 0 0 0 0
-#> [276,] 0 0 0 0
-#> [277,] 0 0 0 0
-#> [278,] 0 0 0 0
-#> [279,] 0 0 0 0
-#> [280,] 0 0 0 0
-#> [281,] 0 0 0 0
-#> [282,] 0 0 0 0
-#> [283,] 0 0 0 0
-#> [284,] 0 0 1 1
-#> [285,] 0 0 0 0
-#> [286,] 0 0 0 1
-#> [287,] 0 0 0 0
-#> [288,] 0 0 0 0
-#> [289,] 0 0 0 0
-#> [290,] 0 0 0 0
-#> [291,] 0 0 0 0
-#> [292,] 0 0 1 0
-#> [293,] 0 0 0 0
-#> [294,] 1 1 0 0
-#> [295,] 0 1 1 0
-#> [296,] 0 0 0 0
-#> [297,] 0 0 0 0
-#> [298,] 0 0 0 0
-#> [299,] 0 0 0 0
-#> [300,] 0 1 1 0
-#> [301,] 0 0 0 0
-#> [302,] 0 0 0 0
-#> [303,] 0 0 0 0
-#> [304,] 0 0 0 0
-#> [305,] 0 1 0 1
-#> [306,] 0 0 0 0
-#> [307,] 0 0 0 0
-#> [308,] 0 1 1 0
-#> [309,] 0 0 0 0
-#> [310,] 0 1 1 0
-#> [311,] 0 0 0 0
-#> [312,] 1 0 0 1
-#> [313,] 0 0 0 0
-#> [314,] 0 0 0 0
-#> [315,] 0 0 0 0
-#> [316,] 1 1 0 1
-#> [317,] 0 0 0 0
-#> [318,] 0 0 0 0
-#> [319,] 0 0 0 0
-#> [320,] 1 0 1 0
-#> [321,] 0 0 0 0
-#> [322,] 0 0 0 0
-#> [323,] 0 0 0 0
-#> [324,] 0 1 0 0
-#> [325,] 1 0 1 0
-#> [326,] 0 0 0 0
-#> [327,] 0 0 0 0
-#> [328,] 0 0 0 0
-#> [329,] 0 0 0 0
-#> [330,] 0 0 0 0
-#> [331,] 0 0 0 0
-#> [332,] 0 0 0 0
-#> [333,] 0 0 0 0
-#> [334,] 1 1 0 1
-#> [335,] 0 0 0 0
-#> [336,] 0 0 0 0
-#> [337,] 0 0 0 0
-#> [338,] 0 0 0 0
-#> [339,] 0 0 0 0
-#> [340,] 0 0 0 0
-#> [341,] 0 1 1 0
-#> [342,] 0 0 0 0
-#> [343,] 0 0 0 1
-#> [344,] 1 1 1 0
-#> [345,] 0 0 0 0
-#> [346,] 0 0 0 0
-#> [347,] 1 0 1 0
-#> [348,] 0 0 0 0
-#> [349,] 0 0 0 0
-#> [350,] 0 0 0 0
-#> [351,] 1 1 1 1
-#> [352,] 1 1 1 1
-#> [353,] 0 0 0 0
-#> [354,] 1 0 0 1
-#> [355,] 0 1 1 1
-#> [356,] 0 0 0 1
-#> [357,] 1 1 1 0
-#> [358,] 0 0 0 0
-#> [359,] 0 1 1 1
-#> [360,] 1 1 0 0
-#> [361,] 1 0 1 1
-#> [362,] 0 0 0 0
-#> [363,] 0 0 0 0
-#> [364,] 1 1 1 1
-#> [365,] 1 0 0 0
-#> [366,] 1 0 1 1
-#> [367,] 1 1 1 1
-#> [368,] 1 1 1 1
-#> [369,] 1 1 0 1
-#> [370,] 1 1 1 0
-#> [371,] 1 0 0 0
-#> [372,] 1 1 0 1
-#> [373,] 1 1 0 0
-#> [374,] 1 1 1 1
-#> [375,] 0 0 0 0
-#> [376,] 0 0 0 0
-#> [377,] 0 0 0 0
-#> [378,] 0 0 0 0
-#> [379,] 0 1 1 1
-#> [380,] 0 0 0 0
-#> [381,] 0 0 1 0
-#> [382,] 0 0 0 0
-#> [383,] 0 0 0 0
-#> [384,] 1 0 0 1
-#> [385,] 0 0 0 0
-#> [386,] 0 0 0 0
-#> [387,] 1 1 1 1
-#> [388,] 1 0 0 1
-#> [389,] 1 1 1 1
-#> [390,] 1 0 0 0
-#> [391,] 1 1 1 0
-#> [392,] 1 0 0 1
-#> [393,] 0 1 1 1
-#> [394,] 0 0 0 0
-#> [395,] 0 0 0 1
-#> [396,] 1 1 1 1
-#> [397,] 0 1 1 1
-#> [398,] 0 0 0 0
-#> [399,] 1 0 0 0
-#> [400,] 0 0 0 0
-#> [401,] 0 0 1 1
-#> [402,] 0 0 1 0
-#> [403,] 1 1 1 1
-#> [404,] 0 0 0 0
-#> [405,] 0 0 0 0
-#> [406,] 0 1 0 0
-#> [407,] 0 0 0 0
-#> [408,] 0 0 0 0
-#> [409,] 0 1 0 1
-#> [410,] 0 0 0 1
-#> [411,] 0 0 0 1
-#> [412,] 0 1 0 1
-#> [413,] 0 0 0 0
-#> [414,] 0 0 1 0
-#> [415,] 0 0 0 0
-#> [416,] 1 0 0 1
-#> [417,] 1 0 1 1
-#> [418,] 0 1 1 0
-#> [419,] 0 1 1 0
-#> [420,] 1 1 1 0
-#> [421,] 0 1 0 0
-#> [422,] 0 1 0 1
-#> [423,] 0 0 0 0
-#> [424,] 1 1 1 0
-#> [425,] 0 1 1 0
-#> [426,] 1 1 1 1
-#> [427,] 1 1 0 1
-#> [428,] 1 1 1 1
-#> [429,] 0 0 0 0
-#> [430,] 1 1 0 1
-#> [431,] 0 0 0 0
-#> [432,] 0 0 0 0
-#> [433,] 1 0 1 0
-#> [434,] 1 0 0 1
-#> [435,] 0 0 0 0
-#> [436,] 0 0 0 0
-#> [437,] 0 0 1 1
-#> [438,] 0 0 0 1
-#> [439,] 1 0 1 0
-#> [440,] 0 0 1 0
-#> [441,] 0 0 0 0
-#> [442,] 1 0 1 1
-#> [443,] 0 1 1 1
-#> [444,] 1 0 1 1
-#> [445,] 0 0 0 0
-#> [446,] 1 1 0 0
-#> [447,] 1 0 1 1
-#> [448,] 0 0 0 0
-#> [449,] 0 0 0 0
-#> [450,] 0 0 0 0
-#> [451,] 1 0 1 1
-#> [452,] 0 0 0 1
-#> [453,] 0 0 0 0
-#> [454,] 0 0 0 0
-#> [455,] 0 0 1 1
-#> [456,] 0 0 0 1
-#> [457,] 1 0 0 0
-#> [458,] 1 1 1 1
-#> [459,] 0 0 0 1
-#> [460,] 0 0 0 1
-#> [461,] 0 0 1 1
-#> [462,] 0 1 1 1
-#> [463,] 0 0 0 0
-#> [464,] 0 0 0 0
-#> [465,] 0 0 0 0
-#> [466,] 0 0 0 0
-#> [467,] 1 0 1 0
-#> [468,] 0 1 1 0
-#> [469,] 0 1 1 1
-#> [470,] 0 1 1 0
-#> [471,] 1 0 0 0
-#> [472,] 1 0 0 1
-#> [473,] 1 1 0 0
-#> [474,] 1 1 0 1
-#> [475,] 0 1 1 1
-#> [476,] 0 1 0 1
-#> [477,] 1 0 0 0
-#> [478,] 0 0 0 0
-#> [479,] 0 0 0 0
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-#> [1092,] 1 0 0 1
-#> [1093,] 0 0 1 1
-#> [1094,] 1 0 1 0
-#> [1095,] 0 0 0 0
-#> [1096,] 1 1 1 1
-#> [1097,] 0 1 0 0
-#> [1098,] 0 1 0 0
-#> [1099,] 0 0 0 0
-#> [1100,] 0 0 0 0
-#> [1101,] 1 0 1 1
-#> [1102,] 1 0 1 1
-#> [1103,] 1 0 0 1
-#> [1104,] 0 0 0 0
-#> [1105,] 0 0 0 0
-#> [1106,] 0 0 1 1
-#> [1107,] 0 1 0 0
-#> [1108,] 1 0 1 1
-#> [1109,] 0 1 1 1
-#> [1110,] 1 0 0 1
-#> [1111,] 1 0 1 1
-#> [1112,] 0 0 0 0
-#> [1113,] 0 0 0 0
-#> [1114,] 0 1 1 1
-#> [1115,] 0 0 0 0
-#> [1116,] 1 0 0 1
-#> [1117,] 0 0 1 1
-#> [1118,] 0 0 0 0
-#> [1119,] 0 1 0 1
-#> [1120,] 1 0 0 1
-#> [1121,] 1 1 0 1
-#> [1122,] 0 0 0 0
-#> [1123,] 0 1 1 0
-#> [1124,] 1 1 1 0
-#> [1125,] 0 0 0 0
-#> [1126,] 0 0 0 0
-#> [1127,] 1 1 1 1
-#> [1128,] 0 0 0 1
-#> [1129,] 1 0 1 1
-#> [1130,] 0 1 0 1
-#> [1131,] 1 1 0 0
-#> [1132,] 1 1 1 1
-#> [1133,] 0 0 0 0
-#> [1134,] 0 0 0 0
-#> [1135,] 0 1 1 0
-#> [1136,] 1 0 0 1
-#> [1137,] 0 0 1 1
-#> [1138,] 0 0 0 0
-#> [1139,] 1 0 0 0
-#> [1140,] 0 1 1 1
-#> [1141,] 0 0 1 1
-#> [1142,] 0 0 1 0
-#> [1143,] 0 0 0 0
-#> [1144,] 1 1 1 0
-#> [1145,] 0 0 0 0
-#> [1146,] 0 1 1 1
-#> [1147,] 1 1 0 1
-#> [1148,] 0 1 0 0
-#> [1149,] 1 0 0 0
-#> [1150,] 0 0 0 0
-#> [1151,] 0 0 1 1
-#> [1152,] 1 0 1 1
-#> [1153,] 0 0 0 0
-#> [1154,] 0 0 0 0
-#> [1155,] 0 0 0 0
-#> [1156,] 0 0 0 0
-#> [1157,] 1 1 0 1
-#> [1158,] 0 1 1 0
-#> [1159,] 0 1 0 1
-#> [1160,] 0 0 0 0
-#> [1161,] 0 0 0 0
-#> [1162,] 0 0 0 0
-#> [1163,] 0 0 0 0
-#> [1164,] 0 0 0 1
-#> [1165,] 0 0 0 0
-#> [1166,] 1 0 0 1
-#> [1167,] 0 0 1 1
-#> [1168,] 0 0 0 0
-#> [1169,] 0 1 0 1
-#> [1170,] 1 1 1 1
-#> [1171,] 0 0 0 0
-#> [1172,] 0 0 0 0
-#> [1173,] 0 0 1 0
-#> [1174,] 1 1 1 1
-#> [1175,] 0 0 0 0
-#> [1176,] 0 1 0 0
-#> [1177,] 0 0 0 0
-#> [1178,] 1 1 1 0
-#> [1179,] 0 1 1 0
-#> [1180,] 1 1 0 0
-#> [1181,] 0 0 0 0
-#> [1182,] 0 1 1 1
-#> [1183,] 0 0 0 0
-#> [1184,] 0 0 0 0
-#> [1185,] 0 0 0 0
-#> [1186,] 0 0 0 0
-#> [1187,] 0 0 0 1
-#> [1188,] 0 1 1 1
-#> [1189,] 1 0 0 0
-#> [1190,] 0 0 0 0
-#> [1191,] 0 0 0 0
-#> [1192,] 0 0 0 0
-#> [1193,] 1 1 0 1
-#> [1194,] 0 0 0 1
-#> [1195,] 0 0 0 0
-#> [1196,] 1 1 0 0
-#> [1197,] 0 1 1 1
-#> [1198,] 0 0 0 0
-#> [1199,] 0 0 0 0
-#> [1200,] 0 0 0 0
-#> [1201,] 0 0 0 0
-#> [1202,] 1 0 1 1
-#> [1203,] 0 0 0 0
-#> [1204,] 0 0 0 0
-#> [1205,] 0 0 0 0
-#> [1206,] 0 0 0 0
-#> [1207,] 1 0 1 0
-#> [1208,] 1 0 1 0
-#> [1209,] 0 1 0 0
-#> [1210,] 0 0 0 1
-#> [1211,] 0 1 0 0
-#> [1212,] 0 0 0 0
-#> [1213,] 0 0 0 0
-#> [1214,] 1 1 1 1
-#> [1215,] 1 0 0 0
-#> [1216,] 0 0 0 0
-#> [1217,] 1 0 0 1
-#> [1218,] 0 0 0 0
-#> [1219,] 0 0 0 0
-#> [1220,] 1 0 0 0
-#> [1221,] 0 0 0 0
-#> [1222,] 0 0 0 1
-#> [1223,] 0 0 0 0
-#> [1224,] 1 1 1 1
-#> [1225,] 0 1 1 0
-#> [1226,] 0 1 0 0
-#> [1227,] 1 1 0 1
-#> [1228,] 1 0 0 1
-#> [1229,] 0 1 0 0
-#> [1230,] 1 1 0 1
-#> [1231,] 0 0 0 0
-#> [1232,] 1 0 1 1
-#> [1233,] 0 0 0 0
-#> [1234,] 0 0 0 0
-#> [1235,] 0 0 0 0
-#> [1236,] 1 0 0 0
-#> [1237,] 0 1 1 1
-#> [1238,] 0 1 0 1
-#> [1239,] 0 0 1 0
-#> [1240,] 0 0 1 1
-#> [1241,] 0 0 0 0
-#> [1242,] 1 0 0 0
-#> [1243,] 1 0 0 0
-#> [1244,] 0 0 0 0
-#> [1245,] 0 0 0 0
-#> [1246,] 0 1 1 0
-#> [1247,] 1 1 1 0
-#> [1248,] 0 0 0 0
-#> [1249,] 1 0 0 0
-#> [1250,] 0 0 0 0
-#> [1251,] 1 0 1 1
-#> [1252,] 0 0 0 0
-#> [1253,] 1 1 1 1
-#> [1254,] 0 0 0 0
-#> [1255,] 0 0 0 0
-#> [1256,] 0 1 1 1
-#> [1257,] 1 1 1 0
-#> [1258,] 0 0 0 0
-#> [1259,] 0 1 1 1
-#> [1260,] 0 0 1 1
-#> [1261,] 1 1 1 1
-#> [1262,] 0 0 0 0
-#> [1263,] 0 0 0 0
-#> [1264,] 1 1 1 1
-#> [1265,] 0 0 0 0
-#> [1266,] 1 0 0 1
-#> [1267,] 1 1 1 1
-#> [1268,] 0 0 0 0
-#> [1269,] 1 1 1 1
-#> [1270,] 0 0 0 0
-#> [1271,] 0 0 0 1
-#> [1272,] 0 0 0 1
-#> [1273,] 0 1 0 0
-#> [1274,] 1 1 0 1
-#> [1275,] 0 0 0 0
-#> [1276,] 0 0 0 0
-#> [1277,] 0 0 0 0
-#> [1278,] 1 1 1 1
-#> [1279,] 1 1 0 0
-#> [1280,] 0 0 0 0
-#> [1281,] 0 0 0 0
-#> [1282,] 1 1 1 1
-#> [1283,] 0 0 0 0
-#> [1284,] 0 0 0 0
-#> [1285,] 0 0 0 0
-#> [1286,] 0 0 0 0
-#> [1287,] 1 1 1 1
-#> [1288,] 1 1 1 0
-#> [1289,] 1 1 1 1
-#> [1290,] 0 0 0 0
-#> [1291,] 0 0 0 0
-#> [1292,] 0 0 0 0
-#> [1293,] 1 1 1 1
-#> [1294,] 1 0 1 1
-#> [1295,] 0 0 0 0
-#> [1296,] 1 1 1 1
-#> [1297,] 0 1 1 1
-#> [1298,] 0 0 0 0
-#> [1299,] 0 0 0 0
-#> [1300,] 0 0 0 0
-#> [1301,] 0 0 0 0
-#> [1302,] 0 0 0 0
-#> [1303,] 0 0 0 0
-#> [1304,] 0 0 0 1
-#> [1305,] 0 1 0 1
-#> [1306,] 0 0 0 1
-#> [1307,] 0 0 0 0
-#> [1308,] 0 0 0 0
-#> [1309,] 0 0 0 0
-#> [1310,] 0 0 0 1
-#> [1311,] 0 0 0 0
-#> [1312,] 0 0 0 1
-#> [1313,] 0 0 0 0
-#> [1314,] 0 0 0 0
-#> [1315,] 0 0 0 0
-#> [1316,] 0 0 0 0
-#> [1317,] 0 1 0 0
-#> [1318,] 1 0 0 0
-#> [1319,] 0 0 0 0
-#> [1320,] 0 0 1 0
-#> [1321,] 0 1 1 1
-#> [1322,] 0 0 0 0
-#> [1323,] 1 0 0 0
-#> [1324,] 0 0 0 0
-#> [1325,] 0 0 0 0
-#> [1326,] 0 1 1 0
-#> [1327,] 1 0 0 0
-#> [1328,] 0 0 0 0
-#> [1329,] 0 0 0 0
-#> [1330,] 0 0 0 0
-#> [1331,] 0 0 0 0
-#> [1332,] 0 0 0 0
-#> [1333,] 1 0 0 0
-#> [1334,] 1 0 0 1
-#> [1335,] 0 0 1 0
-#> [1336,] 0 0 1 0
-#> [1337,] 0 0 0 0
-#> [1338,] 1 0 0 1
-#> [1339,] 0 0 0 0
-#> [1340,] 1 1 0 0
-#> [1341,] 0 0 0 0
-#> [1342,] 0 0 0 0
-#> [1343,] 0 0 0 0
-#> [1344,] 0 1 0 0
-#> [1345,] 0 0 1 1
-#> [1346,] 0 0 0 0
-#> [1347,] 0 0 0 0
-#> [1348,] 1 1 1 0
-#> [1349,] 0 0 0 1
-#> [1350,] 0 0 1 0
-#> [1351,] 0 0 0 0
-#> [1352,] 0 0 0 0
-#> [1353,] 0 1 1 0
-#> [1354,] 1 1 1 0
-#> [1355,] 1 0 1 1
-#> [1356,] 0 0 0 0
-#> [1357,] 1 0 0 0
-#> [1358,] 0 0 1 0
-#> [1359,] 0 0 0 0
-#> [1360,] 0 0 0 0
-#> [1361,] 0 1 0 1
-#> [1362,] 1 1 1 1
-#> [1363,] 0 0 0 0
-#> [1364,] 0 0 0 0
-#> [1365,] 0 0 0 0
-#> [1366,] 1 1 0 1
-#> [1367,] 1 0 0 0
-#> [1368,] 1 1 1 0
-#> [1369,] 0 0 0 0
-#> [1370,] 0 0 0 0
-#> [1371,] 0 0 0 0
-#> [1372,] 0 0 0 0
-#> [1373,] 0 0 0 0
-#> [1374,] 0 0 0 0
-#> [1375,] 0 0 0 0
-#> [1376,] 0 0 0 0
-#> [1377,] 0 0 0 0
-#> [1378,] 0 0 0 0
-#> [1379,] 1 1 1 1
-#> [1380,] 1 1 1 1
-#> [1381,] 0 0 0 0
-#> [1382,] 1 0 0 1
-#> [1383,] 1 0 1 1
-#> [1384,] 0 0 0 0
-#> [1385,] 0 0 0 0
-#> [1386,] 0 1 1 1
-#> [1387,] 0 0 0 0
-#> [1388,] 0 0 0 0
-#> [1389,] 0 0 1 1
-#> [1390,] 0 0 0 0
-#> [1391,] 0 0 0 0
-#> [1392,] 1 0 1 1
-#> [1393,] 0 1 1 0
-#> [1394,] 0 0 0 0
-#> [1395,] 1 1 0 1
-#> [1396,] 0 0 1 0
-#> [1397,] 0 1 1 0
-#> [1398,] 0 0 0 0
-#> [1399,] 0 1 1 1
-#> [1400,] 0 1 1 1
-#> [1401,] 1 1 1 1
-#> [1402,] 1 1 1 1
-#> [1403,] 1 1 1 1
-#> [1404,] 0 0 0 0
-#> [1405,] 0 0 0 0
-#> [1406,] 1 0 1 1
-#> [1407,] 1 1 1 1
-#> [1408,] 0 0 0 0
-#> [1409,] 1 1 1 0
-#> [1410,] 1 1 1 1
-#> [1411,] 1 1 1 1
-#> [1412,] 0 0 0 0
-#> [1413,] 0 0 0 0
-#> [1414,] 1 1 1 1
-#> [1415,] 1 0 1 1
-#> [1416,] 0 0 0 0
-#> [1417,] 0 0 0 0
-#> [1418,] 0 0 0 0
-#> [1419,] 1 1 1 1
-#> [1420,] 1 1 1 1
-#> [1421,] 1 1 1 1
-#> [1422,] 1 1 0 1
-#> [1423,] 0 0 0 0
-#> [1424,] 1 1 1 1
-#> [1425,] 1 1 1 1
-#> [1426,] 0 0 0 0
-#> [1427,] 0 0 0 0
-#> [1428,] 0 0 0 0
-#> [1429,] 1 1 1 0
-#> [1430,] 0 0 0 0
-#> [1431,] 0 0 0 0
-#> [1432,] 1 1 1 1
-#> [1433,] 1 1 1 1
-#> [1434,] 0 0 0 0
-#> [1435,] 1 0 1 1
-#> [1436,] 0 0 0 0
-#> [1437,] 0 1 1 1
-#> [1438,] 0 0 0 0
-#> [1439,] 1 1 1 1
-#> [1440,] 0 0 0 0
-#> [1441,] 0 1 1 1
-#> [1442,] 1 1 1 1
-#> [1443,] 0 0 0 0
-#> [1444,] 1 1 1 1
-#> [1445,] 1 1 1 1
-#> [1446,] 1 1 1 1
-#> [1447,] 0 0 0 0
-#> [1448,] 0 1 1 1
-#> [1449,] 1 0 1 1
-#> [1450,] 0 0 0 0
-#> [1451,] 0 0 0 0
-#> [1452,] 0 0 0 0
-#> [1453,] 0 0 0 0
-#> [1454,] 0 1 0 1
-#> [1455,] 0 0 0 0
-#> [1456,] 0 0 0 0
-#> [1457,] 0 0 0 0
-#> [1458,] 0 0 0 0
-#> [1459,] 0 0 0 0
-#> [1460,] 0 0 0 0
-#> [1461,] 0 0 0 0
-#> [1462,] 0 0 0 0
-#> [1463,] 0 0 0 0
-#> [1464,] 0 0 0 0
-#> [1465,] 0 0 0 0
-#> [1466,] 0 0 0 0
-#> [1467,] 0 0 0 0
-#> [1468,] 0 0 0 0
-#> [1469,] 0 0 0 0
-#> [1470,] 0 0 0 0
-#> [1471,] 0 0 0 0
-#> [1472,] 0 0 0 1
-#> [1473,] 0 0 0 0
-#> [1474,] 0 0 0 0
-#> [1475,] 0 0 0 0
-#> [1476,] 1 0 1 1
-#> [1477,] 0 0 0 0
-#> [1478,] 0 0 0 0
-#> [1479,] 0 0 0 0
-#> [1480,] 0 0 0 0
-#> [1481,] 0 0 0 1
-#> [1482,] 0 0 0 0
-#> [1483,] 0 0 0 0
-#> [1484,] 0 0 0 0
-#> [1485,] 0 0 0 0
-#> [1486,] 0 0 0 0
-#> [1487,] 0 0 0 0
-#> [1488,] 0 0 0 0
-#> [1489,] 0 0 0 0
-#> [1490,] 0 0 0 0
-#> [1491,] 0 0 0 0
-#> [1492,] 0 0 0 0
-#> [1493,] 0 0 0 1
-#> [1494,] 0 0 0 0
-#> [1495,] 0 0 0 0
-#> [1496,] 0 0 0 0
-#> [1497,] 0 0 0 0
-#> [1498,] 1 1 1 0
-#> [1499,] 0 0 0 1
-#> [1500,] 1 0 0 1
-#>
-#> $unit_covs
-#> uc1 species
-#> 1 0.78773885 sp_1
-#> 2 0.76904224 sp_1
-#> 3 0.33220258 sp_1
-#> 4 -1.00837661 sp_1
-#> 5 -0.11945261 sp_1
-#> 6 -0.28039534 sp_1
-#> 7 0.56298953 sp_1
-#> 8 -0.37243876 sp_1
-#> 9 0.97697339 sp_1
-#> 10 -0.37458086 sp_1
-#> 11 1.05271147 sp_1
-#> 12 -1.04917701 sp_1
-#> 13 -1.26015524 sp_1
-#> 14 3.24103993 sp_1
-#> 15 -0.41685759 sp_1
-#> 16 0.29822759 sp_1
-#> 17 0.63656967 sp_1
-#> 18 -0.48378063 sp_1
-#> 19 0.51686204 sp_1
-#> 20 0.36896453 sp_1
-#> 21 -0.21538051 sp_1
-#> 22 0.06529303 sp_1
-#> 23 -0.03406725 sp_1
-#> 24 2.12845190 sp_1
-#> 25 -0.74133610 sp_1
-#> 26 -1.09599627 sp_1
-#> 27 0.03778840 sp_1
-#> 28 0.31048075 sp_1
-#> 29 0.43652348 sp_1
-#> 30 -0.45836533 sp_1
-#> 31 -1.06332613 sp_1
-#> 32 1.26318518 sp_1
-#> 33 -0.34965039 sp_1
-#> 34 -0.86551286 sp_1
-#> 35 -0.23627957 sp_1
-#> 36 -0.19717589 sp_1
-#> 37 1.10992029 sp_1
-#> 38 0.08473729 sp_1
-#> 39 0.75405379 sp_1
-#> 40 -0.49929202 sp_1
-#> 41 0.21444531 sp_1
-#> 42 -0.32468591 sp_1
-#> 43 0.09458353 sp_1
-#> 44 -0.89536336 sp_1
-#> 45 -1.31080153 sp_1
-#> 46 1.99721338 sp_1
-#> 47 0.60070882 sp_1
-#> 48 -1.25127136 sp_1
-#> 49 -0.61116592 sp_1
-#> 50 -1.18548008 sp_1
-#> 51 0.78773885 sp_2
-#> 52 0.76904224 sp_2
-#> 53 0.33220258 sp_2
-#> 54 -1.00837661 sp_2
-#> 55 -0.11945261 sp_2
-#> 56 -0.28039534 sp_2
-#> 57 0.56298953 sp_2
-#> 58 -0.37243876 sp_2
-#> 59 0.97697339 sp_2
-#> 60 -0.37458086 sp_2
-#> 61 1.05271147 sp_2
-#> 62 -1.04917701 sp_2
-#> 63 -1.26015524 sp_2
-#> 64 3.24103993 sp_2
-#> 65 -0.41685759 sp_2
-#> 66 0.29822759 sp_2
-#> 67 0.63656967 sp_2
-#> 68 -0.48378063 sp_2
-#> 69 0.51686204 sp_2
-#> 70 0.36896453 sp_2
-#> 71 -0.21538051 sp_2
-#> 72 0.06529303 sp_2
-#> 73 -0.03406725 sp_2
-#> 74 2.12845190 sp_2
-#> 75 -0.74133610 sp_2
-#> 76 -1.09599627 sp_2
-#> 77 0.03778840 sp_2
-#> 78 0.31048075 sp_2
-#> 79 0.43652348 sp_2
-#> 80 -0.45836533 sp_2
-#> 81 -1.06332613 sp_2
-#> 82 1.26318518 sp_2
-#> 83 -0.34965039 sp_2
-#> 84 -0.86551286 sp_2
-#> 85 -0.23627957 sp_2
-#> 86 -0.19717589 sp_2
-#> 87 1.10992029 sp_2
-#> 88 0.08473729 sp_2
-#> 89 0.75405379 sp_2
-#> 90 -0.49929202 sp_2
-#> 91 0.21444531 sp_2
-#> 92 -0.32468591 sp_2
-#> 93 0.09458353 sp_2
-#> 94 -0.89536336 sp_2
-#> 95 -1.31080153 sp_2
-#> 96 1.99721338 sp_2
-#> 97 0.60070882 sp_2
-#> 98 -1.25127136 sp_2
-#> 99 -0.61116592 sp_2
-#> 100 -1.18548008 sp_2
-#> 101 0.78773885 sp_3
-#> 102 0.76904224 sp_3
-#> 103 0.33220258 sp_3
-#> 104 -1.00837661 sp_3
-#> 105 -0.11945261 sp_3
-#> 106 -0.28039534 sp_3
-#> 107 0.56298953 sp_3
-#> 108 -0.37243876 sp_3
-#> 109 0.97697339 sp_3
-#> 110 -0.37458086 sp_3
-#> 111 1.05271147 sp_3
-#> 112 -1.04917701 sp_3
-#> 113 -1.26015524 sp_3
-#> 114 3.24103993 sp_3
-#> 115 -0.41685759 sp_3
-#> 116 0.29822759 sp_3
-#> 117 0.63656967 sp_3
-#> 118 -0.48378063 sp_3
-#> 119 0.51686204 sp_3
-#> 120 0.36896453 sp_3
-#> 121 -0.21538051 sp_3
-#> 122 0.06529303 sp_3
-#> 123 -0.03406725 sp_3
-#> 124 2.12845190 sp_3
-#> 125 -0.74133610 sp_3
-#> 126 -1.09599627 sp_3
-#> 127 0.03778840 sp_3
-#> 128 0.31048075 sp_3
-#> 129 0.43652348 sp_3
-#> 130 -0.45836533 sp_3
-#> 131 -1.06332613 sp_3
-#> 132 1.26318518 sp_3
-#> 133 -0.34965039 sp_3
-#> 134 -0.86551286 sp_3
-#> 135 -0.23627957 sp_3
-#> 136 -0.19717589 sp_3
-#> 137 1.10992029 sp_3
-#> 138 0.08473729 sp_3
-#> 139 0.75405379 sp_3
-#> 140 -0.49929202 sp_3
-#> 141 0.21444531 sp_3
-#> 142 -0.32468591 sp_3
-#> 143 0.09458353 sp_3
-#> 144 -0.89536336 sp_3
-#> 145 -1.31080153 sp_3
-#> 146 1.99721338 sp_3
-#> 147 0.60070882 sp_3
-#> 148 -1.25127136 sp_3
-#> 149 -0.61116592 sp_3
-#> 150 -1.18548008 sp_3
-#> 151 0.78773885 sp_4
-#> 152 0.76904224 sp_4
-#> 153 0.33220258 sp_4
-#> 154 -1.00837661 sp_4
-#> 155 -0.11945261 sp_4
-#> 156 -0.28039534 sp_4
-#> 157 0.56298953 sp_4
-#> 158 -0.37243876 sp_4
-#> 159 0.97697339 sp_4
-#> 160 -0.37458086 sp_4
-#> 161 1.05271147 sp_4
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-#> 1210 -0.37458086 sp_25
-#> 1211 1.05271147 sp_25
-#> 1212 -1.04917701 sp_25
-#> 1213 -1.26015524 sp_25
-#> 1214 3.24103993 sp_25
-#> 1215 -0.41685759 sp_25
-#> 1216 0.29822759 sp_25
-#> 1217 0.63656967 sp_25
-#> 1218 -0.48378063 sp_25
-#> 1219 0.51686204 sp_25
-#> 1220 0.36896453 sp_25
-#> 1221 -0.21538051 sp_25
-#> 1222 0.06529303 sp_25
-#> 1223 -0.03406725 sp_25
-#> 1224 2.12845190 sp_25
-#> 1225 -0.74133610 sp_25
-#> 1226 -1.09599627 sp_25
-#> 1227 0.03778840 sp_25
-#> 1228 0.31048075 sp_25
-#> 1229 0.43652348 sp_25
-#> 1230 -0.45836533 sp_25
-#> 1231 -1.06332613 sp_25
-#> 1232 1.26318518 sp_25
-#> 1233 -0.34965039 sp_25
-#> 1234 -0.86551286 sp_25
-#> 1235 -0.23627957 sp_25
-#> 1236 -0.19717589 sp_25
-#> 1237 1.10992029 sp_25
-#> 1238 0.08473729 sp_25
-#> 1239 0.75405379 sp_25
-#> 1240 -0.49929202 sp_25
-#> 1241 0.21444531 sp_25
-#> 1242 -0.32468591 sp_25
-#> 1243 0.09458353 sp_25
-#> 1244 -0.89536336 sp_25
-#> 1245 -1.31080153 sp_25
-#> 1246 1.99721338 sp_25
-#> 1247 0.60070882 sp_25
-#> 1248 -1.25127136 sp_25
-#> 1249 -0.61116592 sp_25
-#> 1250 -1.18548008 sp_25
-#> 1251 0.78773885 sp_26
-#> 1252 0.76904224 sp_26
-#> 1253 0.33220258 sp_26
-#> 1254 -1.00837661 sp_26
-#> 1255 -0.11945261 sp_26
-#> 1256 -0.28039534 sp_26
-#> 1257 0.56298953 sp_26
-#> 1258 -0.37243876 sp_26
-#> 1259 0.97697339 sp_26
-#> 1260 -0.37458086 sp_26
-#> 1261 1.05271147 sp_26
-#> 1262 -1.04917701 sp_26
-#> 1263 -1.26015524 sp_26
-#> 1264 3.24103993 sp_26
-#> 1265 -0.41685759 sp_26
-#> 1266 0.29822759 sp_26
-#> 1267 0.63656967 sp_26
-#> 1268 -0.48378063 sp_26
-#> 1269 0.51686204 sp_26
-#> 1270 0.36896453 sp_26
-#> 1271 -0.21538051 sp_26
-#> 1272 0.06529303 sp_26
-#> 1273 -0.03406725 sp_26
-#> 1274 2.12845190 sp_26
-#> 1275 -0.74133610 sp_26
-#> 1276 -1.09599627 sp_26
-#> 1277 0.03778840 sp_26
-#> 1278 0.31048075 sp_26
-#> 1279 0.43652348 sp_26
-#> 1280 -0.45836533 sp_26
-#> 1281 -1.06332613 sp_26
-#> 1282 1.26318518 sp_26
-#> 1283 -0.34965039 sp_26
-#> 1284 -0.86551286 sp_26
-#> 1285 -0.23627957 sp_26
-#> 1286 -0.19717589 sp_26
-#> 1287 1.10992029 sp_26
-#> 1288 0.08473729 sp_26
-#> 1289 0.75405379 sp_26
-#> 1290 -0.49929202 sp_26
-#> 1291 0.21444531 sp_26
-#> 1292 -0.32468591 sp_26
-#> 1293 0.09458353 sp_26
-#> 1294 -0.89536336 sp_26
-#> 1295 -1.31080153 sp_26
-#> 1296 1.99721338 sp_26
-#> 1297 0.60070882 sp_26
-#> 1298 -1.25127136 sp_26
-#> 1299 -0.61116592 sp_26
-#> 1300 -1.18548008 sp_26
-#> 1301 0.78773885 sp_27
-#> 1302 0.76904224 sp_27
-#> 1303 0.33220258 sp_27
-#> 1304 -1.00837661 sp_27
-#> 1305 -0.11945261 sp_27
-#> 1306 -0.28039534 sp_27
-#> 1307 0.56298953 sp_27
-#> 1308 -0.37243876 sp_27
-#> 1309 0.97697339 sp_27
-#> 1310 -0.37458086 sp_27
-#> 1311 1.05271147 sp_27
-#> 1312 -1.04917701 sp_27
-#> 1313 -1.26015524 sp_27
-#> 1314 3.24103993 sp_27
-#> 1315 -0.41685759 sp_27
-#> 1316 0.29822759 sp_27
-#> 1317 0.63656967 sp_27
-#> 1318 -0.48378063 sp_27
-#> 1319 0.51686204 sp_27
-#> 1320 0.36896453 sp_27
-#> 1321 -0.21538051 sp_27
-#> 1322 0.06529303 sp_27
-#> 1323 -0.03406725 sp_27
-#> 1324 2.12845190 sp_27
-#> 1325 -0.74133610 sp_27
-#> 1326 -1.09599627 sp_27
-#> 1327 0.03778840 sp_27
-#> 1328 0.31048075 sp_27
-#> 1329 0.43652348 sp_27
-#> 1330 -0.45836533 sp_27
-#> 1331 -1.06332613 sp_27
-#> 1332 1.26318518 sp_27
-#> 1333 -0.34965039 sp_27
-#> 1334 -0.86551286 sp_27
-#> 1335 -0.23627957 sp_27
-#> 1336 -0.19717589 sp_27
-#> 1337 1.10992029 sp_27
-#> 1338 0.08473729 sp_27
-#> 1339 0.75405379 sp_27
-#> 1340 -0.49929202 sp_27
-#> 1341 0.21444531 sp_27
-#> 1342 -0.32468591 sp_27
-#> 1343 0.09458353 sp_27
-#> 1344 -0.89536336 sp_27
-#> 1345 -1.31080153 sp_27
-#> 1346 1.99721338 sp_27
-#> 1347 0.60070882 sp_27
-#> 1348 -1.25127136 sp_27
-#> 1349 -0.61116592 sp_27
-#> 1350 -1.18548008 sp_27
-#> 1351 0.78773885 sp_28
-#> 1352 0.76904224 sp_28
-#> 1353 0.33220258 sp_28
-#> 1354 -1.00837661 sp_28
-#> 1355 -0.11945261 sp_28
-#> 1356 -0.28039534 sp_28
-#> 1357 0.56298953 sp_28
-#> 1358 -0.37243876 sp_28
-#> 1359 0.97697339 sp_28
-#> 1360 -0.37458086 sp_28
-#> 1361 1.05271147 sp_28
-#> 1362 -1.04917701 sp_28
-#> 1363 -1.26015524 sp_28
-#> 1364 3.24103993 sp_28
-#> 1365 -0.41685759 sp_28
-#> 1366 0.29822759 sp_28
-#> 1367 0.63656967 sp_28
-#> 1368 -0.48378063 sp_28
-#> 1369 0.51686204 sp_28
-#> 1370 0.36896453 sp_28
-#> 1371 -0.21538051 sp_28
-#> 1372 0.06529303 sp_28
-#> 1373 -0.03406725 sp_28
-#> 1374 2.12845190 sp_28
-#> 1375 -0.74133610 sp_28
-#> 1376 -1.09599627 sp_28
-#> 1377 0.03778840 sp_28
-#> 1378 0.31048075 sp_28
-#> 1379 0.43652348 sp_28
-#> 1380 -0.45836533 sp_28
-#> 1381 -1.06332613 sp_28
-#> 1382 1.26318518 sp_28
-#> 1383 -0.34965039 sp_28
-#> 1384 -0.86551286 sp_28
-#> 1385 -0.23627957 sp_28
-#> 1386 -0.19717589 sp_28
-#> 1387 1.10992029 sp_28
-#> 1388 0.08473729 sp_28
-#> 1389 0.75405379 sp_28
-#> 1390 -0.49929202 sp_28
-#> 1391 0.21444531 sp_28
-#> 1392 -0.32468591 sp_28
-#> 1393 0.09458353 sp_28
-#> 1394 -0.89536336 sp_28
-#> 1395 -1.31080153 sp_28
-#> 1396 1.99721338 sp_28
-#> 1397 0.60070882 sp_28
-#> 1398 -1.25127136 sp_28
-#> 1399 -0.61116592 sp_28
-#> 1400 -1.18548008 sp_28
-#> 1401 0.78773885 sp_29
-#> 1402 0.76904224 sp_29
-#> 1403 0.33220258 sp_29
-#> 1404 -1.00837661 sp_29
-#> 1405 -0.11945261 sp_29
-#> 1406 -0.28039534 sp_29
-#> 1407 0.56298953 sp_29
-#> 1408 -0.37243876 sp_29
-#> 1409 0.97697339 sp_29
-#> 1410 -0.37458086 sp_29
-#> 1411 1.05271147 sp_29
-#> 1412 -1.04917701 sp_29
-#> 1413 -1.26015524 sp_29
-#> 1414 3.24103993 sp_29
-#> 1415 -0.41685759 sp_29
-#> 1416 0.29822759 sp_29
-#> 1417 0.63656967 sp_29
-#> 1418 -0.48378063 sp_29
-#> 1419 0.51686204 sp_29
-#> 1420 0.36896453 sp_29
-#> 1421 -0.21538051 sp_29
-#> 1422 0.06529303 sp_29
-#> 1423 -0.03406725 sp_29
-#> 1424 2.12845190 sp_29
-#> 1425 -0.74133610 sp_29
-#> 1426 -1.09599627 sp_29
-#> 1427 0.03778840 sp_29
-#> 1428 0.31048075 sp_29
-#> 1429 0.43652348 sp_29
-#> 1430 -0.45836533 sp_29
-#> 1431 -1.06332613 sp_29
-#> 1432 1.26318518 sp_29
-#> 1433 -0.34965039 sp_29
-#> 1434 -0.86551286 sp_29
-#> 1435 -0.23627957 sp_29
-#> 1436 -0.19717589 sp_29
-#> 1437 1.10992029 sp_29
-#> 1438 0.08473729 sp_29
-#> 1439 0.75405379 sp_29
-#> 1440 -0.49929202 sp_29
-#> 1441 0.21444531 sp_29
-#> 1442 -0.32468591 sp_29
-#> 1443 0.09458353 sp_29
-#> 1444 -0.89536336 sp_29
-#> 1445 -1.31080153 sp_29
-#> 1446 1.99721338 sp_29
-#> 1447 0.60070882 sp_29
-#> 1448 -1.25127136 sp_29
-#> 1449 -0.61116592 sp_29
-#> 1450 -1.18548008 sp_29
-#> 1451 0.78773885 sp_30
-#> 1452 0.76904224 sp_30
-#> 1453 0.33220258 sp_30
-#> 1454 -1.00837661 sp_30
-#> 1455 -0.11945261 sp_30
-#> 1456 -0.28039534 sp_30
-#> 1457 0.56298953 sp_30
-#> 1458 -0.37243876 sp_30
-#> 1459 0.97697339 sp_30
-#> 1460 -0.37458086 sp_30
-#> 1461 1.05271147 sp_30
-#> 1462 -1.04917701 sp_30
-#> 1463 -1.26015524 sp_30
-#> 1464 3.24103993 sp_30
-#> 1465 -0.41685759 sp_30
-#> 1466 0.29822759 sp_30
-#> 1467 0.63656967 sp_30
-#> 1468 -0.48378063 sp_30
-#> 1469 0.51686204 sp_30
-#> 1470 0.36896453 sp_30
-#> 1471 -0.21538051 sp_30
-#> 1472 0.06529303 sp_30
-#> 1473 -0.03406725 sp_30
-#> 1474 2.12845190 sp_30
-#> 1475 -0.74133610 sp_30
-#> 1476 -1.09599627 sp_30
-#> 1477 0.03778840 sp_30
-#> 1478 0.31048075 sp_30
-#> 1479 0.43652348 sp_30
-#> 1480 -0.45836533 sp_30
-#> 1481 -1.06332613 sp_30
-#> 1482 1.26318518 sp_30
-#> 1483 -0.34965039 sp_30
-#> 1484 -0.86551286 sp_30
-#> 1485 -0.23627957 sp_30
-#> 1486 -0.19717589 sp_30
-#> 1487 1.10992029 sp_30
-#> 1488 0.08473729 sp_30
-#> 1489 0.75405379 sp_30
-#> 1490 -0.49929202 sp_30
-#> 1491 0.21444531 sp_30
-#> 1492 -0.32468591 sp_30
-#> 1493 0.09458353 sp_30
-#> 1494 -0.89536336 sp_30
-#> 1495 -1.31080153 sp_30
-#> 1496 1.99721338 sp_30
-#> 1497 0.60070882 sp_30
-#> 1498 -1.25127136 sp_30
-#> 1499 -0.61116592 sp_30
-#> 1500 -1.18548008 sp_30
-#>
-#> $event_covs
-#> $event_covs$ec1
-#> [,1] [,2] [,3] [,4]
-#> [1,] 0.67576242 -1.07420661 0.45457781 -0.21330714
-#> [2,] 0.93560368 -1.13689311 0.26691825 0.42833204
-#> [3,] -0.10555991 -0.73050967 1.90504358 0.33262173
-#> [4,] 1.39531344 -0.19070343 -0.52467120 3.18404447
-#> [5,] 0.49030264 -0.09616320 0.46852512 -0.98237064
-#> [6,] -1.02298384 -0.69341466 -0.76798957 1.29904997
-#> [7,] 1.57914556 -0.15689195 -0.35893656 -0.32903883
-#> [8,] 0.06923648 0.09690423 0.29003439 -0.74667894
-#> [9,] -0.84689639 1.19707766 -0.54862736 0.30304570
-#> [10,] -0.14126176 -1.00537758 0.15615571 0.23363361
-#> [11,] 0.35558761 -1.62185826 0.22071129 0.31045008
-#> [12,] -1.42110845 0.95536564 0.78417088 2.29961936
-#> [13,] 0.15670299 0.04673353 0.09658583 0.06976623
-#> [14,] -1.84847278 -1.67112706 -0.07753897 -0.58106738
-#> [15,] 0.05473653 -2.11120837 -1.49869825 -1.10148344
-#> [16,] 0.98605822 -1.09849001 -0.79951395 0.07987382
-#> [17,] -0.32274636 0.14641718 2.30506198 -1.12460367
-#> [18,] -0.30546964 -0.51675945 1.51239543 -0.76948492
-#> [19,] -0.08208690 0.78713361 -1.05859054 1.65517582
-#> [20,] 0.31322877 -0.08997520 1.07051604 -1.35110039
-#> [21,] -0.52261670 -0.24919068 -0.99579872 -1.03995504
-#> [22,] -0.01798024 -0.13217513 -2.54934277 1.04057346
-#> [23,] 0.24972574 2.41620737 0.68519824 -0.44695931
-#> [24,] 2.79739115 2.83222602 -1.21871182 0.46903196
-#> [25,] -0.21124692 0.18705115 0.22754273 -1.26190046
-#> [26,] 0.28558958 1.74924736 -0.16409000 -0.16292671
-#> [27,] 1.39857201 0.89839624 -1.64849482 0.22855697
-#> [28,] 1.65354723 1.41527635 0.41995160 0.72122081
-#> [29,] -1.19693521 0.30013157 -0.95444894 -0.45801807
-#> [30,] 0.05491197 1.82218882 -1.02234733 0.60613026
-#> [31,] -0.08893057 -0.26083224 0.46409123 -1.02040059
-#> [32,] -1.31345092 -0.49448088 1.75175715 0.05576477
-#> [33,] 0.33143440 -0.18984664 0.47049273 -0.95167954
-#> [34,] 1.15791047 0.58470526 -0.80645282 0.05455325
-#> [35,] 0.71633162 0.55773098 1.48193402 -0.61298775
-#> [36,] 1.11613662 1.03654801 -0.16248313 -0.97592669
-#> [37,] -1.08914519 0.45778696 -0.07112673 1.77910267
-#> [38,] 0.53513796 -0.37194488 -1.02554225 -0.58240167
-#> [39,] 0.34288839 -0.45093465 0.51423012 -0.33433805
-#> [40,] 0.23063364 -1.69186241 0.65979190 -1.02362359
-#> [41,] -0.89152157 0.91834117 -0.45270065 -1.74837228
-#> [42,] 1.76990411 -2.37740693 0.57281153 1.01724925
-#> [43,] -0.63096787 0.44428705 0.43913039 1.04062315
-#> [44,] 0.48409939 -0.24488378 0.91599206 0.80062236
-#> [45,] -0.93656903 -1.40078743 0.16027754 -0.27396237
-#> [46,] -0.98553911 0.08393068 -1.31999653 0.16122635
-#> [47,] -0.62492839 0.95716427 2.42448914 -0.91597924
-#> [48,] 1.05766417 0.82514973 -0.07019422 -0.45364637
-#> [49,] 1.57530771 -2.00545782 -0.64319479 -1.43684344
-#> [50,] -0.05003727 -0.44374931 0.29986525 -1.56842462
-#> [51,] 0.67576242 -1.07420661 0.45457781 -0.21330714
-#> [52,] 0.93560368 -1.13689311 0.26691825 0.42833204
-#> [53,] -0.10555991 -0.73050967 1.90504358 0.33262173
-#> [54,] 1.39531344 -0.19070343 -0.52467120 3.18404447
-#> [55,] 0.49030264 -0.09616320 0.46852512 -0.98237064
-#> [56,] -1.02298384 -0.69341466 -0.76798957 1.29904997
-#> [57,] 1.57914556 -0.15689195 -0.35893656 -0.32903883
-#> [58,] 0.06923648 0.09690423 0.29003439 -0.74667894
-#> [59,] -0.84689639 1.19707766 -0.54862736 0.30304570
-#> [60,] -0.14126176 -1.00537758 0.15615571 0.23363361
-#> [61,] 0.35558761 -1.62185826 0.22071129 0.31045008
-#> [62,] -1.42110845 0.95536564 0.78417088 2.29961936
-#> [63,] 0.15670299 0.04673353 0.09658583 0.06976623
-#> [64,] -1.84847278 -1.67112706 -0.07753897 -0.58106738
-#> [65,] 0.05473653 -2.11120837 -1.49869825 -1.10148344
-#> [66,] 0.98605822 -1.09849001 -0.79951395 0.07987382
-#> [67,] -0.32274636 0.14641718 2.30506198 -1.12460367
-#> [68,] -0.30546964 -0.51675945 1.51239543 -0.76948492
-#> [69,] -0.08208690 0.78713361 -1.05859054 1.65517582
-#> [70,] 0.31322877 -0.08997520 1.07051604 -1.35110039
-#> [71,] -0.52261670 -0.24919068 -0.99579872 -1.03995504
-#> [72,] -0.01798024 -0.13217513 -2.54934277 1.04057346
-#> [73,] 0.24972574 2.41620737 0.68519824 -0.44695931
-#> [74,] 2.79739115 2.83222602 -1.21871182 0.46903196
-#> [75,] -0.21124692 0.18705115 0.22754273 -1.26190046
-#> [76,] 0.28558958 1.74924736 -0.16409000 -0.16292671
-#> [77,] 1.39857201 0.89839624 -1.64849482 0.22855697
-#> [78,] 1.65354723 1.41527635 0.41995160 0.72122081
-#> [79,] -1.19693521 0.30013157 -0.95444894 -0.45801807
-#> [80,] 0.05491197 1.82218882 -1.02234733 0.60613026
-#> [81,] -0.08893057 -0.26083224 0.46409123 -1.02040059
-#> [82,] -1.31345092 -0.49448088 1.75175715 0.05576477
-#> [83,] 0.33143440 -0.18984664 0.47049273 -0.95167954
-#> [84,] 1.15791047 0.58470526 -0.80645282 0.05455325
-#> [85,] 0.71633162 0.55773098 1.48193402 -0.61298775
-#> [86,] 1.11613662 1.03654801 -0.16248313 -0.97592669
-#> [87,] -1.08914519 0.45778696 -0.07112673 1.77910267
-#> [88,] 0.53513796 -0.37194488 -1.02554225 -0.58240167
-#> [89,] 0.34288839 -0.45093465 0.51423012 -0.33433805
-#> [90,] 0.23063364 -1.69186241 0.65979190 -1.02362359
-#> [91,] -0.89152157 0.91834117 -0.45270065 -1.74837228
-#> [92,] 1.76990411 -2.37740693 0.57281153 1.01724925
-#> [93,] -0.63096787 0.44428705 0.43913039 1.04062315
-#> [94,] 0.48409939 -0.24488378 0.91599206 0.80062236
-#> [95,] -0.93656903 -1.40078743 0.16027754 -0.27396237
-#> [96,] -0.98553911 0.08393068 -1.31999653 0.16122635
-#> [97,] -0.62492839 0.95716427 2.42448914 -0.91597924
-#> [98,] 1.05766417 0.82514973 -0.07019422 -0.45364637
-#> [99,] 1.57530771 -2.00545782 -0.64319479 -1.43684344
-#> [100,] -0.05003727 -0.44374931 0.29986525 -1.56842462
-#> [101,] 0.67576242 -1.07420661 0.45457781 -0.21330714
-#> [102,] 0.93560368 -1.13689311 0.26691825 0.42833204
-#> [103,] -0.10555991 -0.73050967 1.90504358 0.33262173
-#> [104,] 1.39531344 -0.19070343 -0.52467120 3.18404447
-#> [105,] 0.49030264 -0.09616320 0.46852512 -0.98237064
-#> [106,] -1.02298384 -0.69341466 -0.76798957 1.29904997
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-#> [1330,] 0.05491197 1.82218882 -1.02234733 0.60613026
-#> [1331,] -0.08893057 -0.26083224 0.46409123 -1.02040059
-#> [1332,] -1.31345092 -0.49448088 1.75175715 0.05576477
-#> [1333,] 0.33143440 -0.18984664 0.47049273 -0.95167954
-#> [1334,] 1.15791047 0.58470526 -0.80645282 0.05455325
-#> [1335,] 0.71633162 0.55773098 1.48193402 -0.61298775
-#> [1336,] 1.11613662 1.03654801 -0.16248313 -0.97592669
-#> [1337,] -1.08914519 0.45778696 -0.07112673 1.77910267
-#> [1338,] 0.53513796 -0.37194488 -1.02554225 -0.58240167
-#> [1339,] 0.34288839 -0.45093465 0.51423012 -0.33433805
-#> [1340,] 0.23063364 -1.69186241 0.65979190 -1.02362359
-#> [1341,] -0.89152157 0.91834117 -0.45270065 -1.74837228
-#> [1342,] 1.76990411 -2.37740693 0.57281153 1.01724925
-#> [1343,] -0.63096787 0.44428705 0.43913039 1.04062315
-#> [1344,] 0.48409939 -0.24488378 0.91599206 0.80062236
-#> [1345,] -0.93656903 -1.40078743 0.16027754 -0.27396237
-#> [1346,] -0.98553911 0.08393068 -1.31999653 0.16122635
-#> [1347,] -0.62492839 0.95716427 2.42448914 -0.91597924
-#> [1348,] 1.05766417 0.82514973 -0.07019422 -0.45364637
-#> [1349,] 1.57530771 -2.00545782 -0.64319479 -1.43684344
-#> [1350,] -0.05003727 -0.44374931 0.29986525 -1.56842462
-#> [1351,] 0.67576242 -1.07420661 0.45457781 -0.21330714
-#> [1352,] 0.93560368 -1.13689311 0.26691825 0.42833204
-#> [1353,] -0.10555991 -0.73050967 1.90504358 0.33262173
-#> [1354,] 1.39531344 -0.19070343 -0.52467120 3.18404447
-#> [1355,] 0.49030264 -0.09616320 0.46852512 -0.98237064
-#> [1356,] -1.02298384 -0.69341466 -0.76798957 1.29904997
-#> [1357,] 1.57914556 -0.15689195 -0.35893656 -0.32903883
-#> [1358,] 0.06923648 0.09690423 0.29003439 -0.74667894
-#> [1359,] -0.84689639 1.19707766 -0.54862736 0.30304570
-#> [1360,] -0.14126176 -1.00537758 0.15615571 0.23363361
-#> [1361,] 0.35558761 -1.62185826 0.22071129 0.31045008
-#> [1362,] -1.42110845 0.95536564 0.78417088 2.29961936
-#> [1363,] 0.15670299 0.04673353 0.09658583 0.06976623
-#> [1364,] -1.84847278 -1.67112706 -0.07753897 -0.58106738
-#> [1365,] 0.05473653 -2.11120837 -1.49869825 -1.10148344
-#> [1366,] 0.98605822 -1.09849001 -0.79951395 0.07987382
-#> [1367,] -0.32274636 0.14641718 2.30506198 -1.12460367
-#> [1368,] -0.30546964 -0.51675945 1.51239543 -0.76948492
-#> [1369,] -0.08208690 0.78713361 -1.05859054 1.65517582
-#> [1370,] 0.31322877 -0.08997520 1.07051604 -1.35110039
-#> [1371,] -0.52261670 -0.24919068 -0.99579872 -1.03995504
-#> [1372,] -0.01798024 -0.13217513 -2.54934277 1.04057346
-#> [1373,] 0.24972574 2.41620737 0.68519824 -0.44695931
-#> [1374,] 2.79739115 2.83222602 -1.21871182 0.46903196
-#> [1375,] -0.21124692 0.18705115 0.22754273 -1.26190046
-#> [1376,] 0.28558958 1.74924736 -0.16409000 -0.16292671
-#> [1377,] 1.39857201 0.89839624 -1.64849482 0.22855697
-#> [1378,] 1.65354723 1.41527635 0.41995160 0.72122081
-#> [1379,] -1.19693521 0.30013157 -0.95444894 -0.45801807
-#> [1380,] 0.05491197 1.82218882 -1.02234733 0.60613026
-#> [1381,] -0.08893057 -0.26083224 0.46409123 -1.02040059
-#> [1382,] -1.31345092 -0.49448088 1.75175715 0.05576477
-#> [1383,] 0.33143440 -0.18984664 0.47049273 -0.95167954
-#> [1384,] 1.15791047 0.58470526 -0.80645282 0.05455325
-#> [1385,] 0.71633162 0.55773098 1.48193402 -0.61298775
-#> [1386,] 1.11613662 1.03654801 -0.16248313 -0.97592669
-#> [1387,] -1.08914519 0.45778696 -0.07112673 1.77910267
-#> [1388,] 0.53513796 -0.37194488 -1.02554225 -0.58240167
-#> [1389,] 0.34288839 -0.45093465 0.51423012 -0.33433805
-#> [1390,] 0.23063364 -1.69186241 0.65979190 -1.02362359
-#> [1391,] -0.89152157 0.91834117 -0.45270065 -1.74837228
-#> [1392,] 1.76990411 -2.37740693 0.57281153 1.01724925
-#> [1393,] -0.63096787 0.44428705 0.43913039 1.04062315
-#> [1394,] 0.48409939 -0.24488378 0.91599206 0.80062236
-#> [1395,] -0.93656903 -1.40078743 0.16027754 -0.27396237
-#> [1396,] -0.98553911 0.08393068 -1.31999653 0.16122635
-#> [1397,] -0.62492839 0.95716427 2.42448914 -0.91597924
-#> [1398,] 1.05766417 0.82514973 -0.07019422 -0.45364637
-#> [1399,] 1.57530771 -2.00545782 -0.64319479 -1.43684344
-#> [1400,] -0.05003727 -0.44374931 0.29986525 -1.56842462
-#> [1401,] 0.67576242 -1.07420661 0.45457781 -0.21330714
-#> [1402,] 0.93560368 -1.13689311 0.26691825 0.42833204
-#> [1403,] -0.10555991 -0.73050967 1.90504358 0.33262173
-#> [1404,] 1.39531344 -0.19070343 -0.52467120 3.18404447
-#> [1405,] 0.49030264 -0.09616320 0.46852512 -0.98237064
-#> [1406,] -1.02298384 -0.69341466 -0.76798957 1.29904997
-#> [1407,] 1.57914556 -0.15689195 -0.35893656 -0.32903883
-#> [1408,] 0.06923648 0.09690423 0.29003439 -0.74667894
-#> [1409,] -0.84689639 1.19707766 -0.54862736 0.30304570
-#> [1410,] -0.14126176 -1.00537758 0.15615571 0.23363361
-#> [1411,] 0.35558761 -1.62185826 0.22071129 0.31045008
-#> [1412,] -1.42110845 0.95536564 0.78417088 2.29961936
-#> [1413,] 0.15670299 0.04673353 0.09658583 0.06976623
-#> [1414,] -1.84847278 -1.67112706 -0.07753897 -0.58106738
-#> [1415,] 0.05473653 -2.11120837 -1.49869825 -1.10148344
-#> [1416,] 0.98605822 -1.09849001 -0.79951395 0.07987382
-#> [1417,] -0.32274636 0.14641718 2.30506198 -1.12460367
-#> [1418,] -0.30546964 -0.51675945 1.51239543 -0.76948492
-#> [1419,] -0.08208690 0.78713361 -1.05859054 1.65517582
-#> [1420,] 0.31322877 -0.08997520 1.07051604 -1.35110039
-#> [1421,] -0.52261670 -0.24919068 -0.99579872 -1.03995504
-#> [1422,] -0.01798024 -0.13217513 -2.54934277 1.04057346
-#> [1423,] 0.24972574 2.41620737 0.68519824 -0.44695931
-#> [1424,] 2.79739115 2.83222602 -1.21871182 0.46903196
-#> [1425,] -0.21124692 0.18705115 0.22754273 -1.26190046
-#> [1426,] 0.28558958 1.74924736 -0.16409000 -0.16292671
-#> [1427,] 1.39857201 0.89839624 -1.64849482 0.22855697
-#> [1428,] 1.65354723 1.41527635 0.41995160 0.72122081
-#> [1429,] -1.19693521 0.30013157 -0.95444894 -0.45801807
-#> [1430,] 0.05491197 1.82218882 -1.02234733 0.60613026
-#> [1431,] -0.08893057 -0.26083224 0.46409123 -1.02040059
-#> [1432,] -1.31345092 -0.49448088 1.75175715 0.05576477
-#> [1433,] 0.33143440 -0.18984664 0.47049273 -0.95167954
-#> [1434,] 1.15791047 0.58470526 -0.80645282 0.05455325
-#> [1435,] 0.71633162 0.55773098 1.48193402 -0.61298775
-#> [1436,] 1.11613662 1.03654801 -0.16248313 -0.97592669
-#> [1437,] -1.08914519 0.45778696 -0.07112673 1.77910267
-#> [1438,] 0.53513796 -0.37194488 -1.02554225 -0.58240167
-#> [1439,] 0.34288839 -0.45093465 0.51423012 -0.33433805
-#> [1440,] 0.23063364 -1.69186241 0.65979190 -1.02362359
-#> [1441,] -0.89152157 0.91834117 -0.45270065 -1.74837228
-#> [1442,] 1.76990411 -2.37740693 0.57281153 1.01724925
-#> [1443,] -0.63096787 0.44428705 0.43913039 1.04062315
-#> [1444,] 0.48409939 -0.24488378 0.91599206 0.80062236
-#> [1445,] -0.93656903 -1.40078743 0.16027754 -0.27396237
-#> [1446,] -0.98553911 0.08393068 -1.31999653 0.16122635
-#> [1447,] -0.62492839 0.95716427 2.42448914 -0.91597924
-#> [1448,] 1.05766417 0.82514973 -0.07019422 -0.45364637
-#> [1449,] 1.57530771 -2.00545782 -0.64319479 -1.43684344
-#> [1450,] -0.05003727 -0.44374931 0.29986525 -1.56842462
-#> [1451,] 0.67576242 -1.07420661 0.45457781 -0.21330714
-#> [1452,] 0.93560368 -1.13689311 0.26691825 0.42833204
-#> [1453,] -0.10555991 -0.73050967 1.90504358 0.33262173
-#> [1454,] 1.39531344 -0.19070343 -0.52467120 3.18404447
-#> [1455,] 0.49030264 -0.09616320 0.46852512 -0.98237064
-#> [1456,] -1.02298384 -0.69341466 -0.76798957 1.29904997
-#> [1457,] 1.57914556 -0.15689195 -0.35893656 -0.32903883
-#> [1458,] 0.06923648 0.09690423 0.29003439 -0.74667894
-#> [1459,] -0.84689639 1.19707766 -0.54862736 0.30304570
-#> [1460,] -0.14126176 -1.00537758 0.15615571 0.23363361
-#> [1461,] 0.35558761 -1.62185826 0.22071129 0.31045008
-#> [1462,] -1.42110845 0.95536564 0.78417088 2.29961936
-#> [1463,] 0.15670299 0.04673353 0.09658583 0.06976623
-#> [1464,] -1.84847278 -1.67112706 -0.07753897 -0.58106738
-#> [1465,] 0.05473653 -2.11120837 -1.49869825 -1.10148344
-#> [1466,] 0.98605822 -1.09849001 -0.79951395 0.07987382
-#> [1467,] -0.32274636 0.14641718 2.30506198 -1.12460367
-#> [1468,] -0.30546964 -0.51675945 1.51239543 -0.76948492
-#> [1469,] -0.08208690 0.78713361 -1.05859054 1.65517582
-#> [1470,] 0.31322877 -0.08997520 1.07051604 -1.35110039
-#> [1471,] -0.52261670 -0.24919068 -0.99579872 -1.03995504
-#> [1472,] -0.01798024 -0.13217513 -2.54934277 1.04057346
-#> [1473,] 0.24972574 2.41620737 0.68519824 -0.44695931
-#> [1474,] 2.79739115 2.83222602 -1.21871182 0.46903196
-#> [1475,] -0.21124692 0.18705115 0.22754273 -1.26190046
-#> [1476,] 0.28558958 1.74924736 -0.16409000 -0.16292671
-#> [1477,] 1.39857201 0.89839624 -1.64849482 0.22855697
-#> [1478,] 1.65354723 1.41527635 0.41995160 0.72122081
-#> [1479,] -1.19693521 0.30013157 -0.95444894 -0.45801807
-#> [1480,] 0.05491197 1.82218882 -1.02234733 0.60613026
-#> [1481,] -0.08893057 -0.26083224 0.46409123 -1.02040059
-#> [1482,] -1.31345092 -0.49448088 1.75175715 0.05576477
-#> [1483,] 0.33143440 -0.18984664 0.47049273 -0.95167954
-#> [1484,] 1.15791047 0.58470526 -0.80645282 0.05455325
-#> [1485,] 0.71633162 0.55773098 1.48193402 -0.61298775
-#> [1486,] 1.11613662 1.03654801 -0.16248313 -0.97592669
-#> [1487,] -1.08914519 0.45778696 -0.07112673 1.77910267
-#> [1488,] 0.53513796 -0.37194488 -1.02554225 -0.58240167
-#> [1489,] 0.34288839 -0.45093465 0.51423012 -0.33433805
-#> [1490,] 0.23063364 -1.69186241 0.65979190 -1.02362359
-#> [1491,] -0.89152157 0.91834117 -0.45270065 -1.74837228
-#> [1492,] 1.76990411 -2.37740693 0.57281153 1.01724925
-#> [1493,] -0.63096787 0.44428705 0.43913039 1.04062315
-#> [1494,] 0.48409939 -0.24488378 0.91599206 0.80062236
-#> [1495,] -0.93656903 -1.40078743 0.16027754 -0.27396237
-#> [1496,] -0.98553911 0.08393068 -1.31999653 0.16122635
-#> [1497,] -0.62492839 0.95716427 2.42448914 -0.91597924
-#> [1498,] 1.05766417 0.82514973 -0.07019422 -0.45364637
-#> [1499,] 1.57530771 -2.00545782 -0.64319479 -1.43684344
-#> [1500,] -0.05003727 -0.44374931 0.29986525 -1.56842462
-#>
-#>
-#> $params
-#> $params$coef_means
-#> [1] 0 0 0 0 0
-#>
-#> $params$Sigma
-#> [,1] [,2] [,3] [,4] [,5]
-#> [1,] 1.0 0.5 0.5 0.5 0.5
-#> [2,] 0.5 1.0 0.5 0.5 0.5
-#> [3,] 0.5 0.5 1.0 0.5 0.5
-#> [4,] 0.5 0.5 0.5 1.0 0.5
-#> [5,] 0.5 0.5 0.5 0.5 1.0
-#>
-#> $params$coefs
-#> det_intercept det_slope_unit det_slope_visit occ_intercept occ_slope_unit
-#> 1 0.508548810 0.77807011 0.80482970 -0.17360000 0.25286423
-#> 2 -0.420940845 0.77990025 0.12350617 0.35203975 0.05696827
-#> 3 -1.517626038 -0.89263386 -1.28636204 -1.61767754 -0.72255187
-#> 4 -0.216582489 0.03204391 -0.71897615 -0.12384829 0.75428519
-#> 5 1.066014876 0.66757562 -0.79646966 -1.12971558 -0.30813450
-#> 6 -1.740812948 -1.63284467 -1.14658859 -1.40540609 -0.71676583
-#> 7 -0.208152618 0.54095837 0.23442360 -1.45313390 -0.89921624
-#> 8 1.029218989 1.71515102 1.25425367 0.48142456 0.41951285
-#> 9 -0.076297618 0.24019585 1.18828474 0.80697467 0.50101201
-#> 10 0.300109084 -0.88154177 1.39343691 0.64725408 0.26678308
-#> 11 -0.034555501 -1.35817078 -1.58431721 -0.53454897 -1.22925595
-#> 12 0.006845644 0.59475669 -1.66797651 -0.05963075 -0.26754803
-#> 13 -0.284358241 -0.79588393 0.23456607 0.27944565 -0.98595070
-#> 14 -0.352944922 0.05803719 -0.49475617 -0.90398219 1.26497378
-#> 15 -0.868034872 0.52263808 0.19118352 0.54950737 1.75746936
-#> 16 -0.668616485 -1.94812518 -0.96619798 -1.10731830 -2.23042688
-#> 17 -1.309423215 -0.44645562 -0.45330736 0.34195221 -0.06093262
-#> 18 1.991318996 1.00395704 0.40903399 2.33951041 1.87285506
-#> 19 0.664155168 -1.09933744 -0.80166071 -1.12973093 -0.34976581
-#> 20 -0.546975568 1.10312602 0.66584579 0.34624304 0.26287397
-#> 21 1.270980071 0.42645941 0.62367626 0.78061459 1.03393310
-#> 22 0.003014390 0.37806468 0.53865575 -0.02348742 -0.05203418
-#> 23 -0.199571642 0.36542420 0.55525681 1.64772961 1.60485916
-#> 24 -0.393363218 0.54848421 1.17452890 0.06236571 1.43096800
-#> 25 -0.528747078 1.07503581 0.69402335 0.70311279 0.47734180
-#> 26 0.970732254 1.42372476 1.63614734 0.49273008 2.00920068
-#> 27 -1.573442460 -0.75277626 0.24610808 0.19206408 -1.35668872
-#> 28 0.316274462 -0.70178439 -0.07792268 -0.35759633 0.22701742
-#> 29 2.209822598 0.23992275 0.21586628 0.80925977 0.93311401
-#> 30 -1.785190406 -1.68593270 -0.26145023 -0.66968627 -0.45374470
-#>
-#>
-#> $covariates
-#> $covariates$uc1
-#> [1] 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885
-#> [7] 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885
-#> [13] 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885
-#> [19] 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885
-#> [25] 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885 0.78773885
-#> [31] 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224
-#> [37] 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224
-#> [43] 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224
-#> [49] 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224
-#> [55] 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224 0.76904224
-#> [61] 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258
-#> [67] 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258
-#> [73] 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258
-#> [79] 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258
-#> [85] 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258 0.33220258
-#> [91] -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661
-#> [97] -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661
-#> [103] -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661
-#> [109] -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661
-#> [115] -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661 -1.00837661
-#> [121] -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261
-#> [127] -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261
-#> [133] -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261
-#> [139] -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261 -0.11945261
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-#> [1225] 0.21444531 0.21444531 0.21444531 0.21444531 0.21444531 0.21444531
-#> [1231] -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591
-#> [1237] -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591
-#> [1243] -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591
-#> [1249] -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591
-#> [1255] -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591 -0.32468591
-#> [1261] 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353
-#> [1267] 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353
-#> [1273] 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353
-#> [1279] 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353
-#> [1285] 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353 0.09458353
-#> [1291] -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336
-#> [1297] -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336
-#> [1303] -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336
-#> [1309] -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336
-#> [1315] -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336 -0.89536336
-#> [1321] -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153
-#> [1327] -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153
-#> [1333] -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153
-#> [1339] -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153
-#> [1345] -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153 -1.31080153
-#> [1351] 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338
-#> [1357] 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338
-#> [1363] 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338
-#> [1369] 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338
-#> [1375] 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338 1.99721338
-#> [1381] 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882
-#> [1387] 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882
-#> [1393] 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882
-#> [1399] 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882
-#> [1405] 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882 0.60070882
-#> [1411] -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136
-#> [1417] -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136
-#> [1423] -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136
-#> [1429] -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136
-#> [1435] -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136 -1.25127136
-#> [1441] -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592
-#> [1447] -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592
-#> [1453] -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592
-#> [1459] -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592
-#> [1465] -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592 -0.61116592
-#> [1471] -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008
-#> [1477] -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008
-#> [1483] -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008
-#> [1489] -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008
-#> [1495] -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008 -1.18548008
-#>
-#> $covariates$ec1
-#> [1] 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242
-#> [7] 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242
-#> [13] 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242
-#> [19] 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242
-#> [25] 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242 0.67576242
-#> [31] 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368
-#> [37] 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368
-#> [43] 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368
-#> [49] 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368
-#> [55] 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368 0.93560368
-#> [61] -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991
-#> [67] -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991
-#> [73] -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991
-#> [79] -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991
-#> [85] -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991 -0.10555991
-#> [91] 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344
-#> [97] 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344
-#> [103] 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344
-#> [109] 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344
-#> [115] 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344 1.39531344
-#> [121] 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264
-#> [127] 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264
-#> [133] 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264
-#> [139] 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264
-#> [145] 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264 0.49030264
-#> [151] -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384
-#> [157] -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384
-#> [163] -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384
-#> [169] -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384
-#> [175] -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384 -1.02298384
-#> [181] 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556
-#> [187] 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556
-#> [193] 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556
-#> [199] 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556
-#> [205] 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556 1.57914556
-#> [211] 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648
-#> [217] 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648
-#> [223] 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648
-#> [229] 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648
-#> [235] 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648 0.06923648
-#> [241] -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639
-#> [247] -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639
-#> [253] -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639
-#> [259] -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639
-#> [265] -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639 -0.84689639
-#> [271] -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176
-#> [277] -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176
-#> [283] -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176
-#> [289] -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176
-#> [295] -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176 -0.14126176
-#> [301] 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761
-#> [307] 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761
-#> [313] 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761
-#> [319] 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761
-#> [325] 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761 0.35558761
-#> [331] -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845
-#> [337] -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845
-#> [343] -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845
-#> [349] -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845
-#> [355] -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845 -1.42110845
-#> [361] 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299
-#> [367] 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299
-#> [373] 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299
-#> [379] 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299
-#> [385] 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299 0.15670299
-#> [391] -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278
-#> [397] -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278
-#> [403] -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278
-#> [409] -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278
-#> [415] -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278 -1.84847278
-#> [421] 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653
-#> [427] 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653
-#> [433] 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653
-#> [439] 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653
-#> [445] 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653 0.05473653
-#> [451] 0.98605822 0.98605822 0.98605822 0.98605822 0.98605822 0.98605822
-#> [457] 0.98605822 0.98605822 0.98605822 0.98605822 0.98605822 0.98605822
-#> [463] 0.98605822 0.98605822 0.98605822 0.98605822 0.98605822 0.98605822
-#> [469] 0.98605822 0.98605822 0.98605822 0.98605822 0.98605822 0.98605822
-#> [475] 0.98605822 0.98605822 0.98605822 0.98605822 0.98605822 0.98605822
-#> [481] -0.32274636 -0.32274636 -0.32274636 -0.32274636 -0.32274636 -0.32274636
-#> [487] -0.32274636 -0.32274636 -0.32274636 -0.32274636 -0.32274636 -0.32274636
-#> [493] -0.32274636 -0.32274636 -0.32274636 -0.32274636 -0.32274636 -0.32274636
-#> [499] -0.32274636 -0.32274636 -0.32274636 -0.32274636 -0.32274636 -0.32274636
-#> [505] -0.32274636 -0.32274636 -0.32274636 -0.32274636 -0.32274636 -0.32274636
-#> [511] -0.30546964 -0.30546964 -0.30546964 -0.30546964 -0.30546964 -0.30546964
-#> [517] -0.30546964 -0.30546964 -0.30546964 -0.30546964 -0.30546964 -0.30546964
-#> [523] -0.30546964 -0.30546964 -0.30546964 -0.30546964 -0.30546964 -0.30546964
-#> [529] -0.30546964 -0.30546964 -0.30546964 -0.30546964 -0.30546964 -0.30546964
-#> [535] -0.30546964 -0.30546964 -0.30546964 -0.30546964 -0.30546964 -0.30546964
-#> [541] -0.08208690 -0.08208690 -0.08208690 -0.08208690 -0.08208690 -0.08208690
-#> [547] -0.08208690 -0.08208690 -0.08208690 -0.08208690 -0.08208690 -0.08208690
-#> [553] -0.08208690 -0.08208690 -0.08208690 -0.08208690 -0.08208690 -0.08208690
-#> [559] -0.08208690 -0.08208690 -0.08208690 -0.08208690 -0.08208690 -0.08208690
-#> [565] -0.08208690 -0.08208690 -0.08208690 -0.08208690 -0.08208690 -0.08208690
-#> [571] 0.31322877 0.31322877 0.31322877 0.31322877 0.31322877 0.31322877
-#> [577] 0.31322877 0.31322877 0.31322877 0.31322877 0.31322877 0.31322877
-#> [583] 0.31322877 0.31322877 0.31322877 0.31322877 0.31322877 0.31322877
-#> [589] 0.31322877 0.31322877 0.31322877 0.31322877 0.31322877 0.31322877
-#> [595] 0.31322877 0.31322877 0.31322877 0.31322877 0.31322877 0.31322877
-#> [601] -0.52261670 -0.52261670 -0.52261670 -0.52261670 -0.52261670 -0.52261670
-#> [607] -0.52261670 -0.52261670 -0.52261670 -0.52261670 -0.52261670 -0.52261670
-#> [613] -0.52261670 -0.52261670 -0.52261670 -0.52261670 -0.52261670 -0.52261670
-#> [619] -0.52261670 -0.52261670 -0.52261670 -0.52261670 -0.52261670 -0.52261670
-#> [625] -0.52261670 -0.52261670 -0.52261670 -0.52261670 -0.52261670 -0.52261670
-#> [631] -0.01798024 -0.01798024 -0.01798024 -0.01798024 -0.01798024 -0.01798024
-#> [637] -0.01798024 -0.01798024 -0.01798024 -0.01798024 -0.01798024 -0.01798024
-#> [643] -0.01798024 -0.01798024 -0.01798024 -0.01798024 -0.01798024 -0.01798024
-#> [649] -0.01798024 -0.01798024 -0.01798024 -0.01798024 -0.01798024 -0.01798024
-#> [655] -0.01798024 -0.01798024 -0.01798024 -0.01798024 -0.01798024 -0.01798024
-#> [661] 0.24972574 0.24972574 0.24972574 0.24972574 0.24972574 0.24972574
-#> [667] 0.24972574 0.24972574 0.24972574 0.24972574 0.24972574 0.24972574
-#> [673] 0.24972574 0.24972574 0.24972574 0.24972574 0.24972574 0.24972574
-#> [679] 0.24972574 0.24972574 0.24972574 0.24972574 0.24972574 0.24972574
-#> [685] 0.24972574 0.24972574 0.24972574 0.24972574 0.24972574 0.24972574
-#> [691] 2.79739115 2.79739115 2.79739115 2.79739115 2.79739115 2.79739115
-#> [697] 2.79739115 2.79739115 2.79739115 2.79739115 2.79739115 2.79739115
-#> [703] 2.79739115 2.79739115 2.79739115 2.79739115 2.79739115 2.79739115
-#> [709] 2.79739115 2.79739115 2.79739115 2.79739115 2.79739115 2.79739115
-#> [715] 2.79739115 2.79739115 2.79739115 2.79739115 2.79739115 2.79739115
-#> [721] -0.21124692 -0.21124692 -0.21124692 -0.21124692 -0.21124692 -0.21124692
-#> [727] -0.21124692 -0.21124692 -0.21124692 -0.21124692 -0.21124692 -0.21124692
-#> [733] -0.21124692 -0.21124692 -0.21124692 -0.21124692 -0.21124692 -0.21124692
-#> [739] -0.21124692 -0.21124692 -0.21124692 -0.21124692 -0.21124692 -0.21124692
-#> [745] -0.21124692 -0.21124692 -0.21124692 -0.21124692 -0.21124692 -0.21124692
-#> [751] 0.28558958 0.28558958 0.28558958 0.28558958 0.28558958 0.28558958
-#> [757] 0.28558958 0.28558958 0.28558958 0.28558958 0.28558958 0.28558958
-#> [763] 0.28558958 0.28558958 0.28558958 0.28558958 0.28558958 0.28558958
-#> [769] 0.28558958 0.28558958 0.28558958 0.28558958 0.28558958 0.28558958
-#> [775] 0.28558958 0.28558958 0.28558958 0.28558958 0.28558958 0.28558958
-#> [781] 1.39857201 1.39857201 1.39857201 1.39857201 1.39857201 1.39857201
-#> [787] 1.39857201 1.39857201 1.39857201 1.39857201 1.39857201 1.39857201
-#> [793] 1.39857201 1.39857201 1.39857201 1.39857201 1.39857201 1.39857201
-#> [799] 1.39857201 1.39857201 1.39857201 1.39857201 1.39857201 1.39857201
-#> [805] 1.39857201 1.39857201 1.39857201 1.39857201 1.39857201 1.39857201
-#> [811] 1.65354723 1.65354723 1.65354723 1.65354723 1.65354723 1.65354723
-#> [817] 1.65354723 1.65354723 1.65354723 1.65354723 1.65354723 1.65354723
-#> [823] 1.65354723 1.65354723 1.65354723 1.65354723 1.65354723 1.65354723
-#> [829] 1.65354723 1.65354723 1.65354723 1.65354723 1.65354723 1.65354723
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-#> [1903] -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706
-#> [1909] -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706
-#> [1915] -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706 -1.67112706
-#> [1921] -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837
-#> [1927] -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837
-#> [1933] -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837
-#> [1939] -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837
-#> [1945] -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837 -2.11120837
-#> [1951] -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001
-#> [1957] -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001
-#> [1963] -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001
-#> [1969] -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001
-#> [1975] -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001 -1.09849001
-#> [1981] 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718
-#> [1987] 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718
-#> [1993] 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718
-#> [1999] 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718
-#> [2005] 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718 0.14641718
-#> [2011] -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945
-#> [2017] -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945
-#> [2023] -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945
-#> [2029] -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945
-#> [2035] -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945 -0.51675945
-#> [2041] 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361
-#> [2047] 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361
-#> [2053] 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361
-#> [2059] 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361
-#> [2065] 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361 0.78713361
-#> [2071] -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520
-#> [2077] -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520
-#> [2083] -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520
-#> [2089] -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520
-#> [2095] -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520 -0.08997520
-#> [2101] -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068
-#> [2107] -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068
-#> [2113] -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068
-#> [2119] -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068
-#> [2125] -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068 -0.24919068
-#> [2131] -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513
-#> [2137] -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513
-#> [2143] -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513
-#> [2149] -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513
-#> [2155] -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513 -0.13217513
-#> [2161] 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737
-#> [2167] 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737
-#> [2173] 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737
-#> [2179] 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737
-#> [2185] 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737 2.41620737
-#> [2191] 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602
-#> [2197] 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602
-#> [2203] 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602
-#> [2209] 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602
-#> [2215] 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602 2.83222602
-#> [2221] 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115
-#> [2227] 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115
-#> [2233] 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115
-#> [2239] 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115
-#> [2245] 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115 0.18705115
-#> [2251] 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736
-#> [2257] 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736
-#> [2263] 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736
-#> [2269] 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736
-#> [2275] 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736 1.74924736
-#> [2281] 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624
-#> [2287] 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624
-#> [2293] 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624
-#> [2299] 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624
-#> [2305] 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624 0.89839624
-#> [2311] 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635
-#> [2317] 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635
-#> [2323] 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635
-#> [2329] 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635
-#> [2335] 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635 1.41527635
-#> [2341] 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157
-#> [2347] 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157
-#> [2353] 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157
-#> [2359] 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157
-#> [2365] 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157 0.30013157
-#> [2371] 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882
-#> [2377] 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882
-#> [2383] 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882
-#> [2389] 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882
-#> [2395] 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882 1.82218882
-#> [2401] -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224
-#> [2407] -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224
-#> [2413] -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224
-#> [2419] -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224
-#> [2425] -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224 -0.26083224
-#> [2431] -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088
-#> [2437] -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088
-#> [2443] -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088
-#> [2449] -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088
-#> [2455] -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088 -0.49448088
-#> [2461] -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664
-#> [2467] -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664
-#> [2473] -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664
-#> [2479] -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664
-#> [2485] -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664 -0.18984664
-#> [2491] 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526
-#> [2497] 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526
-#> [2503] 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526
-#> [2509] 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526
-#> [2515] 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526 0.58470526
-#> [2521] 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098
-#> [2527] 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098
-#> [2533] 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098
-#> [2539] 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098
-#> [2545] 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098 0.55773098
-#> [2551] 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801
-#> [2557] 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801
-#> [2563] 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801
-#> [2569] 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801
-#> [2575] 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801 1.03654801
-#> [2581] 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696
-#> [2587] 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696
-#> [2593] 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696
-#> [2599] 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696
-#> [2605] 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696 0.45778696
-#> [2611] -0.37194488 -0.37194488 -0.37194488 -0.37194488 -0.37194488 -0.37194488
-#> [2617] -0.37194488 -0.37194488 -0.37194488 -0.37194488 -0.37194488 -0.37194488
-#> [2623] -0.37194488 -0.37194488 -0.37194488 -0.37194488 -0.37194488 -0.37194488
-#> [2629] -0.37194488 -0.37194488 -0.37194488 -0.37194488 -0.37194488 -0.37194488
-#> [2635] -0.37194488 -0.37194488 -0.37194488 -0.37194488 -0.37194488 -0.37194488
-#> [2641] -0.45093465 -0.45093465 -0.45093465 -0.45093465 -0.45093465 -0.45093465
-#> [2647] -0.45093465 -0.45093465 -0.45093465 -0.45093465 -0.45093465 -0.45093465
-#> [2653] -0.45093465 -0.45093465 -0.45093465 -0.45093465 -0.45093465 -0.45093465
-#> [2659] -0.45093465 -0.45093465 -0.45093465 -0.45093465 -0.45093465 -0.45093465
-#> [2665] -0.45093465 -0.45093465 -0.45093465 -0.45093465 -0.45093465 -0.45093465
-#> [2671] -1.69186241 -1.69186241 -1.69186241 -1.69186241 -1.69186241 -1.69186241
-#> [2677] -1.69186241 -1.69186241 -1.69186241 -1.69186241 -1.69186241 -1.69186241
-#> [2683] -1.69186241 -1.69186241 -1.69186241 -1.69186241 -1.69186241 -1.69186241
-#> [2689] -1.69186241 -1.69186241 -1.69186241 -1.69186241 -1.69186241 -1.69186241
-#> [2695] -1.69186241 -1.69186241 -1.69186241 -1.69186241 -1.69186241 -1.69186241
-#> [2701] 0.91834117 0.91834117 0.91834117 0.91834117 0.91834117 0.91834117
-#> [2707] 0.91834117 0.91834117 0.91834117 0.91834117 0.91834117 0.91834117
-#> [2713] 0.91834117 0.91834117 0.91834117 0.91834117 0.91834117 0.91834117
-#> [2719] 0.91834117 0.91834117 0.91834117 0.91834117 0.91834117 0.91834117
-#> [2725] 0.91834117 0.91834117 0.91834117 0.91834117 0.91834117 0.91834117
-#> [2731] -2.37740693 -2.37740693 -2.37740693 -2.37740693 -2.37740693 -2.37740693
-#> [2737] -2.37740693 -2.37740693 -2.37740693 -2.37740693 -2.37740693 -2.37740693
-#> [2743] -2.37740693 -2.37740693 -2.37740693 -2.37740693 -2.37740693 -2.37740693
-#> [2749] -2.37740693 -2.37740693 -2.37740693 -2.37740693 -2.37740693 -2.37740693
-#> [2755] -2.37740693 -2.37740693 -2.37740693 -2.37740693 -2.37740693 -2.37740693
-#> [2761] 0.44428705 0.44428705 0.44428705 0.44428705 0.44428705 0.44428705
-#> [2767] 0.44428705 0.44428705 0.44428705 0.44428705 0.44428705 0.44428705
-#> [2773] 0.44428705 0.44428705 0.44428705 0.44428705 0.44428705 0.44428705
-#> [2779] 0.44428705 0.44428705 0.44428705 0.44428705 0.44428705 0.44428705
-#> [2785] 0.44428705 0.44428705 0.44428705 0.44428705 0.44428705 0.44428705
-#> [2791] -0.24488378 -0.24488378 -0.24488378 -0.24488378 -0.24488378 -0.24488378
-#> [2797] -0.24488378 -0.24488378 -0.24488378 -0.24488378 -0.24488378 -0.24488378
-#> [2803] -0.24488378 -0.24488378 -0.24488378 -0.24488378 -0.24488378 -0.24488378
-#> [2809] -0.24488378 -0.24488378 -0.24488378 -0.24488378 -0.24488378 -0.24488378
-#> [2815] -0.24488378 -0.24488378 -0.24488378 -0.24488378 -0.24488378 -0.24488378
-#> [2821] -1.40078743 -1.40078743 -1.40078743 -1.40078743 -1.40078743 -1.40078743
-#> [2827] -1.40078743 -1.40078743 -1.40078743 -1.40078743 -1.40078743 -1.40078743
-#> [2833] -1.40078743 -1.40078743 -1.40078743 -1.40078743 -1.40078743 -1.40078743
-#> [2839] -1.40078743 -1.40078743 -1.40078743 -1.40078743 -1.40078743 -1.40078743
-#> [2845] -1.40078743 -1.40078743 -1.40078743 -1.40078743 -1.40078743 -1.40078743
-#> [2851] 0.08393068 0.08393068 0.08393068 0.08393068 0.08393068 0.08393068
-#> [2857] 0.08393068 0.08393068 0.08393068 0.08393068 0.08393068 0.08393068
-#> [2863] 0.08393068 0.08393068 0.08393068 0.08393068 0.08393068 0.08393068
-#> [2869] 0.08393068 0.08393068 0.08393068 0.08393068 0.08393068 0.08393068
-#> [2875] 0.08393068 0.08393068 0.08393068 0.08393068 0.08393068 0.08393068
-#> [2881] 0.95716427 0.95716427 0.95716427 0.95716427 0.95716427 0.95716427
-#> [2887] 0.95716427 0.95716427 0.95716427 0.95716427 0.95716427 0.95716427
-#> [2893] 0.95716427 0.95716427 0.95716427 0.95716427 0.95716427 0.95716427
-#> [2899] 0.95716427 0.95716427 0.95716427 0.95716427 0.95716427 0.95716427
-#> [2905] 0.95716427 0.95716427 0.95716427 0.95716427 0.95716427 0.95716427
-#> [2911] 0.82514973 0.82514973 0.82514973 0.82514973 0.82514973 0.82514973
-#> [2917] 0.82514973 0.82514973 0.82514973 0.82514973 0.82514973 0.82514973
-#> [2923] 0.82514973 0.82514973 0.82514973 0.82514973 0.82514973 0.82514973
-#> [2929] 0.82514973 0.82514973 0.82514973 0.82514973 0.82514973 0.82514973
-#> [2935] 0.82514973 0.82514973 0.82514973 0.82514973 0.82514973 0.82514973
-#> [2941] -2.00545782 -2.00545782 -2.00545782 -2.00545782 -2.00545782 -2.00545782
-#> [2947] -2.00545782 -2.00545782 -2.00545782 -2.00545782 -2.00545782 -2.00545782
-#> [2953] -2.00545782 -2.00545782 -2.00545782 -2.00545782 -2.00545782 -2.00545782
-#> [2959] -2.00545782 -2.00545782 -2.00545782 -2.00545782 -2.00545782 -2.00545782
-#> [2965] -2.00545782 -2.00545782 -2.00545782 -2.00545782 -2.00545782 -2.00545782
-#> [2971] -0.44374931 -0.44374931 -0.44374931 -0.44374931 -0.44374931 -0.44374931
-#> [2977] -0.44374931 -0.44374931 -0.44374931 -0.44374931 -0.44374931 -0.44374931
-#> [2983] -0.44374931 -0.44374931 -0.44374931 -0.44374931 -0.44374931 -0.44374931
-#> [2989] -0.44374931 -0.44374931 -0.44374931 -0.44374931 -0.44374931 -0.44374931
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-#> [5197] 0.46903196 0.46903196 0.46903196 0.46903196 0.46903196 0.46903196
-#> [5203] 0.46903196 0.46903196 0.46903196 0.46903196 0.46903196 0.46903196
-#> [5209] 0.46903196 0.46903196 0.46903196 0.46903196 0.46903196 0.46903196
-#> [5215] 0.46903196 0.46903196 0.46903196 0.46903196 0.46903196 0.46903196
-#> [5221] -1.26190046 -1.26190046 -1.26190046 -1.26190046 -1.26190046 -1.26190046
-#> [5227] -1.26190046 -1.26190046 -1.26190046 -1.26190046 -1.26190046 -1.26190046
-#> [5233] -1.26190046 -1.26190046 -1.26190046 -1.26190046 -1.26190046 -1.26190046
-#> [5239] -1.26190046 -1.26190046 -1.26190046 -1.26190046 -1.26190046 -1.26190046
-#> [5245] -1.26190046 -1.26190046 -1.26190046 -1.26190046 -1.26190046 -1.26190046
-#> [5251] -0.16292671 -0.16292671 -0.16292671 -0.16292671 -0.16292671 -0.16292671
-#> [5257] -0.16292671 -0.16292671 -0.16292671 -0.16292671 -0.16292671 -0.16292671
-#> [5263] -0.16292671 -0.16292671 -0.16292671 -0.16292671 -0.16292671 -0.16292671
-#> [5269] -0.16292671 -0.16292671 -0.16292671 -0.16292671 -0.16292671 -0.16292671
-#> [5275] -0.16292671 -0.16292671 -0.16292671 -0.16292671 -0.16292671 -0.16292671
-#> [5281] 0.22855697 0.22855697 0.22855697 0.22855697 0.22855697 0.22855697
-#> [5287] 0.22855697 0.22855697 0.22855697 0.22855697 0.22855697 0.22855697
-#> [5293] 0.22855697 0.22855697 0.22855697 0.22855697 0.22855697 0.22855697
-#> [5299] 0.22855697 0.22855697 0.22855697 0.22855697 0.22855697 0.22855697
-#> [5305] 0.22855697 0.22855697 0.22855697 0.22855697 0.22855697 0.22855697
-#> [5311] 0.72122081 0.72122081 0.72122081 0.72122081 0.72122081 0.72122081
-#> [5317] 0.72122081 0.72122081 0.72122081 0.72122081 0.72122081 0.72122081
-#> [5323] 0.72122081 0.72122081 0.72122081 0.72122081 0.72122081 0.72122081
-#> [5329] 0.72122081 0.72122081 0.72122081 0.72122081 0.72122081 0.72122081
-#> [5335] 0.72122081 0.72122081 0.72122081 0.72122081 0.72122081 0.72122081
-#> [5341] -0.45801807 -0.45801807 -0.45801807 -0.45801807 -0.45801807 -0.45801807
-#> [5347] -0.45801807 -0.45801807 -0.45801807 -0.45801807 -0.45801807 -0.45801807
-#> [5353] -0.45801807 -0.45801807 -0.45801807 -0.45801807 -0.45801807 -0.45801807
-#> [5359] -0.45801807 -0.45801807 -0.45801807 -0.45801807 -0.45801807 -0.45801807
-#> [5365] -0.45801807 -0.45801807 -0.45801807 -0.45801807 -0.45801807 -0.45801807
-#> [5371] 0.60613026 0.60613026 0.60613026 0.60613026 0.60613026 0.60613026
-#> [5377] 0.60613026 0.60613026 0.60613026 0.60613026 0.60613026 0.60613026
-#> [5383] 0.60613026 0.60613026 0.60613026 0.60613026 0.60613026 0.60613026
-#> [5389] 0.60613026 0.60613026 0.60613026 0.60613026 0.60613026 0.60613026
-#> [5395] 0.60613026 0.60613026 0.60613026 0.60613026 0.60613026 0.60613026
-#> [5401] -1.02040059 -1.02040059 -1.02040059 -1.02040059 -1.02040059 -1.02040059
-#> [5407] -1.02040059 -1.02040059 -1.02040059 -1.02040059 -1.02040059 -1.02040059
-#> [5413] -1.02040059 -1.02040059 -1.02040059 -1.02040059 -1.02040059 -1.02040059
-#> [5419] -1.02040059 -1.02040059 -1.02040059 -1.02040059 -1.02040059 -1.02040059
-#> [5425] -1.02040059 -1.02040059 -1.02040059 -1.02040059 -1.02040059 -1.02040059
-#> [5431] 0.05576477 0.05576477 0.05576477 0.05576477 0.05576477 0.05576477
-#> [5437] 0.05576477 0.05576477 0.05576477 0.05576477 0.05576477 0.05576477
-#> [5443] 0.05576477 0.05576477 0.05576477 0.05576477 0.05576477 0.05576477
-#> [5449] 0.05576477 0.05576477 0.05576477 0.05576477 0.05576477 0.05576477
-#> [5455] 0.05576477 0.05576477 0.05576477 0.05576477 0.05576477 0.05576477
-#> [5461] -0.95167954 -0.95167954 -0.95167954 -0.95167954 -0.95167954 -0.95167954
-#> [5467] -0.95167954 -0.95167954 -0.95167954 -0.95167954 -0.95167954 -0.95167954
-#> [5473] -0.95167954 -0.95167954 -0.95167954 -0.95167954 -0.95167954 -0.95167954
-#> [5479] -0.95167954 -0.95167954 -0.95167954 -0.95167954 -0.95167954 -0.95167954
-#> [5485] -0.95167954 -0.95167954 -0.95167954 -0.95167954 -0.95167954 -0.95167954
-#> [5491] 0.05455325 0.05455325 0.05455325 0.05455325 0.05455325 0.05455325
-#> [5497] 0.05455325 0.05455325 0.05455325 0.05455325 0.05455325 0.05455325
-#> [5503] 0.05455325 0.05455325 0.05455325 0.05455325 0.05455325 0.05455325
-#> [5509] 0.05455325 0.05455325 0.05455325 0.05455325 0.05455325 0.05455325
-#> [5515] 0.05455325 0.05455325 0.05455325 0.05455325 0.05455325 0.05455325
-#> [5521] -0.61298775 -0.61298775 -0.61298775 -0.61298775 -0.61298775 -0.61298775
-#> [5527] -0.61298775 -0.61298775 -0.61298775 -0.61298775 -0.61298775 -0.61298775
-#> [5533] -0.61298775 -0.61298775 -0.61298775 -0.61298775 -0.61298775 -0.61298775
-#> [5539] -0.61298775 -0.61298775 -0.61298775 -0.61298775 -0.61298775 -0.61298775
-#> [5545] -0.61298775 -0.61298775 -0.61298775 -0.61298775 -0.61298775 -0.61298775
-#> [5551] -0.97592669 -0.97592669 -0.97592669 -0.97592669 -0.97592669 -0.97592669
-#> [5557] -0.97592669 -0.97592669 -0.97592669 -0.97592669 -0.97592669 -0.97592669
-#> [5563] -0.97592669 -0.97592669 -0.97592669 -0.97592669 -0.97592669 -0.97592669
-#> [5569] -0.97592669 -0.97592669 -0.97592669 -0.97592669 -0.97592669 -0.97592669
-#> [5575] -0.97592669 -0.97592669 -0.97592669 -0.97592669 -0.97592669 -0.97592669
-#> [5581] 1.77910267 1.77910267 1.77910267 1.77910267 1.77910267 1.77910267
-#> [5587] 1.77910267 1.77910267 1.77910267 1.77910267 1.77910267 1.77910267
-#> [5593] 1.77910267 1.77910267 1.77910267 1.77910267 1.77910267 1.77910267
-#> [5599] 1.77910267 1.77910267 1.77910267 1.77910267 1.77910267 1.77910267
-#> [5605] 1.77910267 1.77910267 1.77910267 1.77910267 1.77910267 1.77910267
-#> [5611] -0.58240167 -0.58240167 -0.58240167 -0.58240167 -0.58240167 -0.58240167
-#> [5617] -0.58240167 -0.58240167 -0.58240167 -0.58240167 -0.58240167 -0.58240167
-#> [5623] -0.58240167 -0.58240167 -0.58240167 -0.58240167 -0.58240167 -0.58240167
-#> [5629] -0.58240167 -0.58240167 -0.58240167 -0.58240167 -0.58240167 -0.58240167
-#> [5635] -0.58240167 -0.58240167 -0.58240167 -0.58240167 -0.58240167 -0.58240167
-#> [5641] -0.33433805 -0.33433805 -0.33433805 -0.33433805 -0.33433805 -0.33433805
-#> [5647] -0.33433805 -0.33433805 -0.33433805 -0.33433805 -0.33433805 -0.33433805
-#> [5653] -0.33433805 -0.33433805 -0.33433805 -0.33433805 -0.33433805 -0.33433805
-#> [5659] -0.33433805 -0.33433805 -0.33433805 -0.33433805 -0.33433805 -0.33433805
-#> [5665] -0.33433805 -0.33433805 -0.33433805 -0.33433805 -0.33433805 -0.33433805
-#> [5671] -1.02362359 -1.02362359 -1.02362359 -1.02362359 -1.02362359 -1.02362359
-#> [5677] -1.02362359 -1.02362359 -1.02362359 -1.02362359 -1.02362359 -1.02362359
-#> [5683] -1.02362359 -1.02362359 -1.02362359 -1.02362359 -1.02362359 -1.02362359
-#> [5689] -1.02362359 -1.02362359 -1.02362359 -1.02362359 -1.02362359 -1.02362359
-#> [5695] -1.02362359 -1.02362359 -1.02362359 -1.02362359 -1.02362359 -1.02362359
-#> [5701] -1.74837228 -1.74837228 -1.74837228 -1.74837228 -1.74837228 -1.74837228
-#> [5707] -1.74837228 -1.74837228 -1.74837228 -1.74837228 -1.74837228 -1.74837228
-#> [5713] -1.74837228 -1.74837228 -1.74837228 -1.74837228 -1.74837228 -1.74837228
-#> [5719] -1.74837228 -1.74837228 -1.74837228 -1.74837228 -1.74837228 -1.74837228
-#> [5725] -1.74837228 -1.74837228 -1.74837228 -1.74837228 -1.74837228 -1.74837228
-#> [5731] 1.01724925 1.01724925 1.01724925 1.01724925 1.01724925 1.01724925
-#> [5737] 1.01724925 1.01724925 1.01724925 1.01724925 1.01724925 1.01724925
-#> [5743] 1.01724925 1.01724925 1.01724925 1.01724925 1.01724925 1.01724925
-#> [5749] 1.01724925 1.01724925 1.01724925 1.01724925 1.01724925 1.01724925
-#> [5755] 1.01724925 1.01724925 1.01724925 1.01724925 1.01724925 1.01724925
-#> [5761] 1.04062315 1.04062315 1.04062315 1.04062315 1.04062315 1.04062315
-#> [5767] 1.04062315 1.04062315 1.04062315 1.04062315 1.04062315 1.04062315
-#> [5773] 1.04062315 1.04062315 1.04062315 1.04062315 1.04062315 1.04062315
-#> [5779] 1.04062315 1.04062315 1.04062315 1.04062315 1.04062315 1.04062315
-#> [5785] 1.04062315 1.04062315 1.04062315 1.04062315 1.04062315 1.04062315
-#> [5791] 0.80062236 0.80062236 0.80062236 0.80062236 0.80062236 0.80062236
-#> [5797] 0.80062236 0.80062236 0.80062236 0.80062236 0.80062236 0.80062236
-#> [5803] 0.80062236 0.80062236 0.80062236 0.80062236 0.80062236 0.80062236
-#> [5809] 0.80062236 0.80062236 0.80062236 0.80062236 0.80062236 0.80062236
-#> [5815] 0.80062236 0.80062236 0.80062236 0.80062236 0.80062236 0.80062236
-#> [5821] -0.27396237 -0.27396237 -0.27396237 -0.27396237 -0.27396237 -0.27396237
-#> [5827] -0.27396237 -0.27396237 -0.27396237 -0.27396237 -0.27396237 -0.27396237
-#> [5833] -0.27396237 -0.27396237 -0.27396237 -0.27396237 -0.27396237 -0.27396237
-#> [5839] -0.27396237 -0.27396237 -0.27396237 -0.27396237 -0.27396237 -0.27396237
-#> [5845] -0.27396237 -0.27396237 -0.27396237 -0.27396237 -0.27396237 -0.27396237
-#> [5851] 0.16122635 0.16122635 0.16122635 0.16122635 0.16122635 0.16122635
-#> [5857] 0.16122635 0.16122635 0.16122635 0.16122635 0.16122635 0.16122635
-#> [5863] 0.16122635 0.16122635 0.16122635 0.16122635 0.16122635 0.16122635
-#> [5869] 0.16122635 0.16122635 0.16122635 0.16122635 0.16122635 0.16122635
-#> [5875] 0.16122635 0.16122635 0.16122635 0.16122635 0.16122635 0.16122635
-#> [5881] -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924
-#> [5887] -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924
-#> [5893] -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924
-#> [5899] -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924
-#> [5905] -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924 -0.91597924
-#> [5911] -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637
-#> [5917] -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637
-#> [5923] -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637
-#> [5929] -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637
-#> [5935] -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637 -0.45364637
-#> [5941] -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344
-#> [5947] -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344
-#> [5953] -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344
-#> [5959] -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344
-#> [5965] -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344 -1.43684344
-#> [5971] -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462
-#> [5977] -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462
-#> [5983] -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462
-#> [5989] -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462
-#> [5995] -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462 -1.56842462
-#>
-#>
-
rbind a matrix or dataframe to itself n times
-stack_matrix(m, n)
a matrix or dataframe
number of times to rbind
matrix or dataframe
-R/fitted_flocker.R
- summarise_fun.Rd
summarize matrix of linear predictors to its mean and CI
-summarise_fun(x, CI)
linpreds
fractional bounds of credible interval between 0 and 1 inclusive
summary
-flocker_data_output_types valid for use with threading
-threading_types()
character vector of data output types
-Extract lik_type from object of class flocker_fit
-type_flocker_fit(x)
flocker_fit object
string giving model type
-Check validity of params passed to `flock`
-validate_flock_params(
- f_occ,
- f_det,
- flocker_data,
- multiseason,
- f_col,
- f_ex,
- multi_init,
- f_auto,
- augmented,
- threads
-)
occupancy formula
detection formula
flocker_data object
multiseason flag
colonization formula
extinction formula
multi_init flag
autologistic formula
augmented flag
threads number
silent if parameters are valid
-R/utils.R
- validate_param_combos_augmented.Rd
Check validity of params passed to `flock` if `type` is `augmented`
-validate_param_combos_augmented(
- f_occ,
- f_det,
- flocker_data,
- multiseason,
- f_col,
- f_ex,
- multi_init,
- f_auto,
- augmented,
- threads
-)
occupancy formula
detection formula
flocker_data object
multiseason flag
colonization formula
extinction formula
multi_init flag
autologistic formula
augmented flag
threads number
silent if parameters are valid
-R/utils.R
- validate_param_combos_multi.Rd
Check validity of params passed to `flock` if `type` is `multi`
-validate_param_combos_multi(
- f_occ,
- f_det,
- flocker_data,
- multiseason,
- f_col,
- f_ex,
- multi_init,
- f_auto,
- augmented,
- threads
-)
occupancy formula
detection formula
flocker_data object
multiseason flag
colonization formula
extinction formula
multi_init flag
autologistic formula
augmented flag
threads number
silent if parameters are valid
-R/utils.R
- validate_param_combos_single.Rd
Check validity of params passed to `flock` if `type` is `single`
-validate_param_combos_single(
- f_occ,
- f_det,
- flocker_data,
- multiseason,
- f_col,
- f_ex,
- multi_init,
- f_auto,
- augmented
-)
occupancy formula
detection formula
flocker_data object
multiseason flag
colonization formula
extinction formula
multi_init flag
autologistic formula
augmented flag
silent if parameters are valid
-R/utils.R
- validate_param_combos_single_C.Rd
Check validity of params passed to `flock` if `type` is `single_C`
-validate_param_combos_single_C(
- f_occ,
- f_det,
- flocker_data,
- multiseason,
- f_col,
- f_ex,
- multi_init,
- f_auto,
- augmented
-)
occupancy formula
detection formula
flocker_data object
multiseason flag
colonization formula
extinction formula
multi_init flag
autologistic formula
augmented flag
silent if parameters are valid
-R/utils.R
- validate_param_combos_single_generic.Rd
Check validity of some params passed to flock if `type` is `single` or `single_C`
-validate_param_combos_single_generic(
- f_occ,
- f_det,
- flocker_data,
- multiseason,
- f_col,
- f_ex,
- multi_init,
- f_auto,
- augmented
-)
occupancy formula
detection formula
flocker_data object
multiseason flag
colonization formula
extinction formula
multi_init flag
autologistic formula
augmented flag
silent if parameters are valid
-R/utils.R
- validate_params_individually.Rd
Check individual validity of params passed to `flock`
-validate_params_individually(
- f_occ,
- f_det,
- flocker_data,
- multiseason,
- f_col,
- f_ex,
- multi_init,
- f_auto,
- augmented,
- threads
-)
occupancy formula
detection formula
flocker_data object
multiseason flag
colonization formula
extinction formula
multi_init flag
autologistic formula
augmented flag
threads number
silent if parameters are valid
-R/utils.R
- validate_unit_formula_variables.Rd
Check that no event covariates are used in unit formulas
-validate_unit_formula_variables(f_occ, f_col, f_ex, f_auto, flocker_data)
occupancy formula
colonization formula
extinction formula
autologistic formula
flocker_data object
silent if parameters are valid
-params
-## $n_sims
-## [1] 1000
-##
-## $n_sites
-## [1] 200
-library(flocker)
-library(brms)
-## Loading required package: Rcpp
-## Loading 'brms' package (version 2.20.0). Useful instructions
-## can be found by typing help('brms'). A more detailed introduction
-## to the package is available through vignette('brms_overview').
-##
-## Attaching package: 'brms'
-## The following object is masked from 'package:stats':
-##
-## ar
-library(SBC)
-set.seed(3)
-This document performs simulation-based calibration for the models
-available in R package flocker
. Here, our goal is to
-validate flocker
’s data formatting, decoding, and
-likelihood implementations, and not brms
’s construction of
-the linear predictors.
The encoding of the data for a flocker
model tends to be
-more complex in the presence of missing observations, and so we include
-missingness in the data simulation wherever possible (some visits
-missing in all models, some time-steps missing in multiseason
-models).
In all models, we include one unit covariate that affects detection -and occupancy, colonization, extinction and/or autologistic terms as -applicable, and one event covariate that affects detection only (for all -models except the rep-constant).
-# make the stancode
-model_name <- paste0(tempdir(), "/sbc_rep_constant_model.stan")
-fd <- simulate_flocker_data(
- n_pt = params$n_sites, n_sp = 1,
- params = list(
- coefs = data.frame(
- det_intercept = rnorm(1),
- det_slope_unit = rnorm(1),
- occ_intercept = rnorm(1),
- occ_slope_unit = rnorm(1)
- )
- ),
- seed = NULL,
- rep_constant = TRUE,
- ragged_rep = TRUE
-)
-flocker_data = make_flocker_data(fd$obs, fd$unit_covs, quiet = TRUE)
-
-scode <- flocker_stancode(
- f_occ = ~ 0 + Intercept + uc1,
- f_det = ~ 0 + Intercept + uc1,
- flocker_data = flocker_data,
- prior =
- brms::set_prior("std_normal()") +
- brms::set_prior("std_normal()", dpar = "occ"),
- backend = "cmdstanr"
- )
-
-writeLines(scode, model_name)
-
-rep_constant_generator <- function(N){
- fd <- simulate_flocker_data(
- n_pt = N, n_sp = 1,
- params = list(
- coefs = data.frame(
- det_intercept = rnorm(1),
- det_slope_unit = rnorm(1),
- occ_intercept = rnorm(1),
- occ_slope_unit = rnorm(1)
- )
- ),
- seed = NULL,
- rep_constant = TRUE,
- ragged_rep = TRUE
- )
-
- flocker_data = make_flocker_data(fd$obs, fd$unit_covs, quiet = TRUE)
-
- # format for return
- list(
- variables = list(
- `b[1]` = fd$params$coefs$det_intercept,
- `b[2]` = fd$params$coefs$det_slope_unit,
- `b_occ[1]` = fd$params$coefs$occ_intercept,
- `b_occ[2]` = fd$params$coefs$occ_slope_unit
- ),
- generated = flocker_standata(
- f_occ = ~ 0 + Intercept + uc1,
- f_det = ~ 0 + Intercept + uc1,
- flocker_data = flocker_data
- )
- )
-}
-
-rep_constant_gen <- SBC_generator_function(
- rep_constant_generator,
- N = params$n_sites
- )
-rep_constant_dataset <- suppressMessages(
- generate_datasets(rep_constant_gen, params$n_sims)
-)
-
-rep_constant_backend <-
- SBC_backend_cmdstan_sample(
- cmdstanr::cmdstan_model(
- paste0(tempdir(), "/sbc_rep_constant_model.stan")
- )
- )
-
-rep_constant_results <- compute_SBC(rep_constant_dataset, rep_constant_backend)
-
-plot_ecdf(rep_constant_results)
-
-plot_rank_hist(rep_constant_results)
-
-plot_ecdf_diff(rep_constant_results)
-
-# make the stancode
-model_name <- paste0(tempdir(), "/sbc_rep_varying_model.stan")
-fd <- simulate_flocker_data(
- n_pt = params$n_sites, n_sp = 1,
- params = list(
- coefs = data.frame(
- det_intercept = rnorm(1),
- det_slope_unit = rnorm(1),
- det_slope_visit = rnorm(1),
- occ_intercept = rnorm(1),
- occ_slope_unit = rnorm(1)
- )
- ),
- seed = NULL,
- rep_constant = FALSE,
- ragged_rep = TRUE
-)
-flocker_data = make_flocker_data(fd$obs, fd$unit_covs, fd$event_covs, quiet = TRUE)
-
-scode <- flocker_stancode(
- f_occ = ~ 0 + Intercept + uc1,
- f_det = ~ 0 + Intercept + uc1 + ec1,
- flocker_data = flocker_data,
- prior =
- brms::set_prior("std_normal()") +
- brms::set_prior("std_normal()", dpar = "occ"),
- backend = "cmdstanr"
- )
-writeLines(scode, model_name)
-
-rep_varying_generator <- function(N){
- fd <- simulate_flocker_data(
- n_pt = N, n_sp = 1,
- params = list(
- coefs = data.frame(
- det_intercept = rnorm(1),
- det_slope_unit = rnorm(1),
- det_slope_visit = rnorm(1),
- occ_intercept = rnorm(1),
- occ_slope_unit = rnorm(1)
- )
- ),
- seed = NULL,
- rep_constant = FALSE,
- ragged_rep = TRUE
- )
-
- flocker_data = make_flocker_data(fd$obs, fd$unit_covs, fd$event_covs, quiet = TRUE)
-
- # format for return
- list(
- variables = list(
- `b[1]` = fd$params$coefs$det_intercept,
- `b[2]` = fd$params$coefs$det_slope_unit,
- `b[3]` = fd$params$coefs$det_slope_visit,
- `b_occ[1]` = fd$params$coefs$occ_intercept,
- `b_occ[2]` = fd$params$coefs$occ_slope_unit
- ),
- generated = flocker_standata(
- f_occ = ~ 0 + Intercept + uc1,
- f_det = ~ 0 + Intercept + uc1 + ec1,
- flocker_data = flocker_data
- )
- )
-}
-
-rep_varying_gen <- SBC_generator_function(
- rep_varying_generator,
- N = params$n_sites
- )
-rep_varying_dataset <- suppressMessages(
- generate_datasets(rep_varying_gen, params$n_sims)
-)
-
-rep_varying_backend <-
- SBC_backend_cmdstan_sample(
- cmdstanr::cmdstan_model(
- paste0(tempdir(), "/sbc_rep_varying_model.stan")
- )
- )
-
-rep_varying_results <- compute_SBC(rep_varying_dataset, rep_varying_backend)
-
-plot_ecdf(rep_varying_results)
-
-plot_rank_hist(rep_varying_results)
-
-plot_ecdf_diff(rep_varying_results)
-
-flocker
fits multi-season models that parameterize the
-dynamics using colonization/extinction or autologistic specifications,
-and that parameterize the initial occupancy state using explicit and
-equilibrium parameterizations, for a total of four classes of
-multi-season model. We validate each class.
# make the stancode
-model_name <- paste0(tempdir(), "/sbc_colex_ex_model.stan")
-fd <- simulate_flocker_data(
- n_pt = params$n_sites, n_sp = 1, n_season = 4,
- params = list(
- coefs = data.frame(
- det_intercept = rnorm(1),
- det_slope_unit = rnorm(1),
- det_slope_visit = rnorm(1),
- occ_intercept = rnorm(1),
- occ_slope_unit = rnorm(1),
- col_intercept = rnorm(1),
- col_slope_unit = rnorm(1),
- ex_intercept = rnorm(1),
- ex_slope_unit = rnorm(1)
- )
- ),
- seed = NULL,
- rep_constant = FALSE,
- multiseason = "colex",
- multi_init = "explicit",
- ragged_rep = TRUE
-)
-flocker_data = make_flocker_data(
- fd$obs, fd$unit_covs, fd$event_covs,
- type = "multi", quiet = TRUE)
-
-scode <- flocker_stancode(
- f_occ = ~ 0 + Intercept + uc1,
- f_col = ~ 0 + Intercept + uc1,
- f_ex = ~ 0 + Intercept + uc1,
- f_det = ~ 0 + Intercept + uc1 + ec1,
- flocker_data = flocker_data,
- prior =
- brms::set_prior("std_normal()") +
- brms::set_prior("std_normal()", dpar = "occ") +
- brms::set_prior("std_normal()", dpar = "colo") +
- brms::set_prior("std_normal()", dpar = "ex"),
- multiseason = "colex",
- multi_init = "explicit",
- backend = "cmdstanr"
- )
-writeLines(scode, model_name)
-
-colex_ex_generator <- function(N){
- fd <- simulate_flocker_data(
- n_pt = params$n_sites, n_sp = 1, n_season = 4,
- params = list(
- det_intercept = rnorm(1),
- det_slope_unit = rnorm(1),
- det_slope_visit = rnorm(1),
- occ_intercept = rnorm(1),
- occ_slope_unit = rnorm(1),
- colo_intercept = rnorm(1),
- colo_slope_unit = rnorm(1),
- ex_intercept = rnorm(1),
- ex_slope_unit = rnorm(1)
- ),
- seed = NULL,
- rep_constant = FALSE,
- multiseason = "colex",
- multi_init = "explicit",
- ragged_rep = TRUE
- )
-
- flocker_data = make_flocker_data(
- fd$obs, fd$unit_covs, fd$event_covs,
- type = "multi", quiet = TRUE)
-
- # format for return
- list(
- variables = list(
- `b[1]` = fd$params$coefs$det_intercept,
- `b[2]` = fd$params$coefs$det_slope_unit,
- `b[3]` = fd$params$coefs$det_slope_visit,
- `b_occ[1]` = fd$params$coefs$occ_intercept,
- `b_occ[2]` = fd$params$coefs$occ_slope_unit,
- `b_colo[1]` = fd$params$coefs$col_intercept,
- `b_colo[2]` = fd$params$coefs$col_slope_unit,
- `b_ex[1]` = fd$params$coefs$ex_intercept,
- `b_ex[2]` = fd$params$coefs$ex_slope_unit
- ),
- generated = flocker_standata(
- f_occ = ~ 0 + Intercept + uc1,
- f_col = ~ 0 + Intercept + uc1,
- f_ex = ~ 0 + Intercept + uc1,
- f_det = ~ 0 + Intercept + uc1 + ec1,
- flocker_data = flocker_data,
- multiseason = "colex",
- multi_init = "explicit"
- )
- )
-}
-
-colex_ex_gen <- SBC_generator_function(
- colex_ex_generator,
- N = params$n_sites
- )
-colex_ex_dataset <- suppressMessages(
- generate_datasets(colex_ex_gen, params$n_sims)
-)
-
-colex_ex_backend <-
- SBC_backend_cmdstan_sample(
- cmdstanr::cmdstan_model(
- paste0(tempdir(), "/sbc_colex_ex_model.stan")
- )
- )
-
-colex_ex_results <- compute_SBC(colex_ex_dataset, colex_ex_backend)
-
-plot_ecdf(colex_ex_results)
-
-plot_rank_hist(colex_ex_results)
-
-plot_ecdf_diff(colex_ex_results)
-
-# make the stancode
-model_name <- paste0(tempdir(), "/sbc_colex_eq_model.stan")
-fd <- simulate_flocker_data(
- n_pt = params$n_sites, n_sp = 1, n_season = 4,
- params = list(
- det_intercept = rnorm(1),
- det_slope_unit = rnorm(1),
- det_slope_visit = rnorm(1),
- colo_intercept = rnorm(1),
- colo_slope_unit = rnorm(1),
- ex_intercept = rnorm(1),
- ex_slope_unit = rnorm(1)
- ),
- seed = NULL,
- rep_constant = FALSE,
- multiseason = "colex",
- multi_init = "equilibrium",
- ragged_rep = TRUE
-)
-flocker_data = make_flocker_data(
- fd$obs, fd$unit_covs, fd$event_covs,
- type = "multi", quiet = TRUE)
-
-scode <- flocker_stancode(
- f_col = ~ 0 + Intercept + uc1,
- f_ex = ~ 0 + Intercept + uc1,
- f_det = ~ 0 + Intercept + uc1 + ec1,
- flocker_data = flocker_data,
- prior =
- brms::set_prior("std_normal()") +
- brms::set_prior("std_normal()", dpar = "colo") +
- brms::set_prior("std_normal()", dpar = "ex"),
- multiseason = "colex",
- multi_init = "equilibrium",
- backend = "cmdstanr"
- )
-writeLines(scode, model_name)
-
-colex_eq_generator <- function(N){
- fd <- simulate_flocker_data(
- n_pt = params$n_sites, n_sp = 1, n_season = 4,
- params = list(
- det_intercept = rnorm(1),
- det_slope_unit = rnorm(1),
- det_slope_visit = rnorm(1),
- col_intercept = rnorm(1),
- col_slope_unit = rnorm(1),
- ex_intercept = rnorm(1),
- ex_slope_unit = rnorm(1)
- ),
- seed = NULL,
- rep_constant = FALSE,
- multiseason = "colex",
- multi_init = "equilibrium",
- ragged_rep = TRUE
- )
-
- flocker_data = make_flocker_data(
- fd$obs, fd$unit_covs, fd$event_covs,
- type = "multi", quiet = TRUE)
-
- # format for return
- list(
- variables = list(
- `b[1]` = fd$params$coefs$det_intercept,
- `b[2]` = fd$params$coefs$det_slope_unit,
- `b[3]` = fd$params$coefs$det_slope_visit,
- `b_colo[1]` = fd$params$coefs$col_intercept,
- `b_colo[2]` = fd$params$coefs$col_slope_unit,
- `b_ex[1]` = fd$params$coefs$ex_intercept,
- `b_ex[2]` = fd$params$coefs$ex_slope_unit
- ),
- generated = flocker_standata(
- f_col = ~ 0 + Intercept + uc1,
- f_ex = ~ 0 + Intercept + uc1,
- f_det = ~ 0 + Intercept + uc1 + ec1,
- flocker_data = flocker_data,
- multiseason = "colex",
- multi_init = "equilibrium"
- )
- )
-}
-
-colex_eq_gen <- SBC_generator_function(
- colex_eq_generator,
- N = params$n_sites
- )
-colex_eq_dataset <- suppressMessages(
- generate_datasets(colex_eq_gen, params$n_sims)
-)
-
-colex_eq_backend <-
- SBC_backend_cmdstan_sample(
- cmdstanr::cmdstan_model(
- paste0(tempdir(), "/sbc_colex_eq_model.stan")
- )
- )
-
-colex_eq_results <- compute_SBC(colex_eq_dataset, colex_eq_backend)
-## - 865 (86%) fits had some steps rejected. Maximum number of rejections was 4.
-## Not all diagnostics are OK.
-## You can learn more by inspecting $default_diagnostics, $backend_diagnostics
-## and/or investigating $outputs/$messages/$warnings for detailed output from the backend.
-plot_ecdf(colex_eq_results)
-
-plot_rank_hist(colex_eq_results)
-
-plot_ecdf_diff(colex_eq_results)
-
-# make the stancode
-model_name <- paste0(tempdir(), "/sbc_auto_ex_model.stan")
-fd <- simulate_flocker_data(
- n_pt = params$n_sites, n_sp = 1, n_season = 4,
- params = list(
- det_intercept = rnorm(1),
- det_slope_unit = rnorm(1),
- det_slope_visit = rnorm(1),
- occ_intercept = rnorm(1),
- occ_slope_unit = rnorm(1),
- col_intercept = rnorm(1),
- col_slope_unit = rnorm(1),
- auto_intercept = rnorm(1),
- auto_slope_unit = rnorm(1)
- ),
- seed = NULL,
- rep_constant = FALSE,
- multiseason = "autologistic",
- multi_init = "explicit",
- ragged_rep = TRUE
-)
-flocker_data = make_flocker_data(
- fd$obs, fd$unit_covs, fd$event_covs,
- type = "multi", quiet = TRUE)
-
-scode <- flocker_stancode(
- f_occ = ~ 0 + Intercept + uc1,
- f_col = ~ 0 + Intercept + uc1,
- f_auto = ~ 0 + Intercept + uc1,
- f_det = ~ 0 + Intercept + uc1 + ec1,
- flocker_data = flocker_data,
- prior =
- brms::set_prior("std_normal()") +
- brms::set_prior("std_normal()", dpar = "occ") +
- brms::set_prior("std_normal()", dpar = "colo") +
- brms::set_prior("std_normal()", dpar = "autologistic"),
- multiseason = "autologistic",
- multi_init = "explicit",
- backend = "cmdstanr"
- )
-writeLines(scode, model_name)
-
-auto_ex_generator <- function(N){
- fd <- simulate_flocker_data(
- n_pt = params$n_sites, n_sp = 1, n_season = 4,
- params = list(
- det_intercept = rnorm(1),
- det_slope_unit = rnorm(1),
- det_slope_visit = rnorm(1),
- occ_intercept = rnorm(1),
- occ_slope_unit = rnorm(1),
- colo_intercept = rnorm(1),
- colo_slope_unit = rnorm(1),
- auto_intercept = rnorm(1),
- auto_slope_unit = rnorm(1)
- ),
- seed = NULL,
- rep_constant = FALSE,
- multiseason = "autologistic",
- multi_init = "explicit",
- ragged_rep = TRUE
- )
-
- flocker_data = make_flocker_data(
- fd$obs, fd$unit_covs, fd$event_covs,
- type = "multi", quiet = TRUE)
-
- # format for return
- list(
- variables = list(
- `b[1]` = fd$params$coefs$det_intercept,
- `b[2]` = fd$params$coefs$det_slope_unit,
- `b[3]` = fd$params$coefs$det_slope_visit,
- `b_occ[1]` = fd$params$coefs$occ_intercept,
- `b_occ[2]` = fd$params$coefs$occ_slope_unit,
- `b_colo[1]` = fd$params$coefs$col_intercept,
- `b_colo[2]` = fd$params$coefs$col_slope_unit,
- `b_autologistic[1]` = fd$params$coefs$auto_intercept,
- `b_autologistic[2]` = fd$params$coefs$auto_slope_unit
- ),
- generated = flocker_standata(
- f_occ = ~ 0 + Intercept + uc1,
- f_col = ~ 0 + Intercept + uc1,
- f_auto = ~ 0 + Intercept + uc1,
- f_det = ~ 0 + Intercept + uc1 + ec1,
- flocker_data = flocker_data,
- multiseason = "autologistic",
- multi_init = "explicit"
- )
- )
-}
-
-auto_ex_gen <- SBC_generator_function(
- auto_ex_generator,
- N = params$n_sites
- )
-auto_ex_dataset <- suppressMessages(
- generate_datasets(auto_ex_gen, params$n_sims)
-)
-
-auto_ex_backend <-
- SBC_backend_cmdstan_sample(
- cmdstanr::cmdstan_model(
- paste0(tempdir(), "/sbc_auto_ex_model.stan")
- )
- )
-
-auto_ex_results <- compute_SBC(auto_ex_dataset, auto_ex_backend)
-
-plot_ecdf(auto_ex_results)
-
-plot_rank_hist(auto_ex_results)
-
-plot_ecdf_diff(auto_ex_results)
-
-# make the stancode
-model_name <- paste0(tempdir(), "/sbc_auto_eq_model.stan")
-fd <- simulate_flocker_data(
- n_pt = params$n_sites, n_sp = 1, n_season = 4,
- params = list(
- det_intercept = rnorm(1),
- det_slope_unit = rnorm(1),
- det_slope_visit = rnorm(1),
- auto_intercept = rnorm(1),
- auto_slope_unit = rnorm(1)
- ),
- seed = NULL,
- rep_constant = FALSE,
- multiseason = "autologistic",
- multi_init = "equilibrium",
- ragged_rep = TRUE
-)
-flocker_data = make_flocker_data(
- fd$obs, fd$unit_covs, fd$event_covs,
- type = "multi", quiet = TRUE)
-
-scode <- flocker_stancode(
- f_col = ~ 0 + Intercept + uc1,
- f_auto = ~ 0 + Intercept + uc1,
- f_det = ~ 0 + Intercept + uc1 + ec1,
- flocker_data = flocker_data,
- prior =
- brms::set_prior("std_normal()") +
- brms::set_prior("std_normal()", dpar = "colo") +
- brms::set_prior("std_normal()", dpar = "autologistic"),
- multiseason = "autologistic",
- multi_init = "equilibrium",
- backend = "cmdstanr"
- )
-writeLines(scode, model_name)
-
-auto_eq_generator <- function(N){
- fd <- simulate_flocker_data(
- n_pt = params$n_sites, n_sp = 1, n_season = 4,
- params = list(
- det_intercept = rnorm(1),
- det_slope_unit = rnorm(1),
- det_slope_visit = rnorm(1),
- col_intercept = rnorm(1),
- col_slope_unit = rnorm(1),
- auto_intercept = rnorm(1),
- auto_slope_unit = rnorm(1)
- ),
- seed = NULL,
- rep_constant = FALSE,
- multiseason = "autologistic",
- multi_init = "equilibrium",
- ragged_rep = TRUE
- )
-
- flocker_data = make_flocker_data(
- fd$obs, fd$unit_covs, fd$event_covs,
- type = "multi", quiet = TRUE)
-
- # format for return
- list(
- variables = list(
- `b[1]` = fd$params$coefs$det_intercept,
- `b[2]` = fd$params$coefs$det_slope_unit,
- `b[3]` = fd$params$coefs$det_slope_visit,
- `b_colo[1]` = fd$params$coefs$col_intercept,
- `b_colo[2]` = fd$params$coefs$col_slope_unit,
- `b_autologistic[1]` = fd$params$coefs$auto_intercept,
- `b_autologistic[2]` = fd$params$coefs$auto_slope_unit
- ),
- generated = flocker_standata(
- f_col = ~ 0 + Intercept + uc1,
- f_auto = ~ 0 + Intercept + uc1,
- f_det = ~ 0 + Intercept + uc1 + ec1,
- flocker_data = flocker_data,
- multiseason = "autologistic",
- multi_init = "equilibrium"
- )
- )
-}
-
-auto_eq_gen <- SBC_generator_function(
- auto_eq_generator,
- N = params$n_sites
- )
-auto_eq_dataset <- suppressMessages(
- generate_datasets(auto_eq_gen, params$n_sims)
-)
-
-auto_eq_backend <-
- SBC_backend_cmdstan_sample(
- cmdstanr::cmdstan_model(
- paste0(tempdir(), "/sbc_auto_eq_model.stan")
- )
- )
-
-auto_eq_results <- compute_SBC(auto_eq_dataset, auto_eq_backend)
-## - 319 (32%) fits had some steps rejected. Maximum number of rejections was 4.
-## Not all diagnostics are OK.
-## You can learn more by inspecting $default_diagnostics, $backend_diagnostics
-## and/or investigating $outputs/$messages/$warnings for detailed output from the backend.
-plot_ecdf(auto_eq_results)
-
-plot_rank_hist(auto_eq_results)
-
-plot_ecdf_diff(auto_eq_results)
-
-params
-## $n_sims
-## [1] 200
-##
-## $n_sites
-## [1] 50
-##
-## $n_pseudospecies
-## [1] 50
-library(flocker)
-library(brms)
-## Loading required package: Rcpp
-## Loading 'brms' package (version 2.20.0). Useful instructions
-## can be found by typing help('brms'). A more detailed introduction
-## to the package is available through vignette('brms_overview').
-##
-## Attaching package: 'brms'
-## The following object is masked from 'package:stats':
-##
-## ar
-library(SBC)
-set.seed(2)
-# make the stancode
-model_name <- paste0(tempdir(), "/sbc_augmented_model.stan")
-
-omega <- boot::inv.logit(rnorm(1, 0, .1))
-available <- rbinom(1, params$n_pseudospecies, omega)
-unavailable <- params$n_pseudospecies - available
-coef_means <- rnorm(5) # normal prior on random effect means
-sigma <- abs(rnorm(5)) # half-normal prior on all random effect sds
-Sigma <- diag(5) * sigma
-
-fd <- simulate_flocker_data(
- n_pt = params$n_sites, n_sp = available,
- params = list(
- coef_means = coef_means,
- Sigma = Sigma,
- coefs = data.frame(
- det_intercept = rnorm(available, coef_means[1], sigma[1]),
- det_slope_unit = rnorm(available, coef_means[2], sigma[2]),
- det_slope_visit = rnorm(available, coef_means[3], sigma[3]),
- occ_intercept = rnorm(available, coef_means[4], sigma[4]),
- occ_slope_unit = rnorm(available, coef_means[5], sigma[5])
- )
- ),
- seed = NULL,
- rep_constant = FALSE,
- ragged_rep = TRUE
-)
-
-obs_aug <- fd$obs[seq_len(params$n_sites), ]
-
-for(i in 2:available){
- obs_aug <- abind::abind(
- obs_aug,
- fd$obs[((i - 1) * params$n_sites) + seq_len(params$n_sites), ],
- along = 3
- )
-}
-
-event_covs_aug <- list(ec1 = fd$event_covs$ec1[seq_len(params$n_sites), ])
-unit_covs_aug <- data.frame(uc1 = fd$unit_covs[seq_len(params$n_sites), "uc1"])
-
-flocker_data = make_flocker_data(
- obs_aug, unit_covs_aug, event_covs_aug,
- type = "augmented", n_aug = unavailable,
- quiet = TRUE)
-
-scode <- flocker_stancode(
- f_occ = ~ 0 + Intercept + uc1 + (1 + uc1 || ff_species),
- f_det = ~ 0 + Intercept + uc1 + ec1 + (1 + uc1 + ec1 || ff_species),
- flocker_data = flocker_data,
- prior =
- brms::set_prior("std_normal()") +
- brms::set_prior("std_normal()", class = "sd") +
- brms::set_prior("std_normal()", dpar = "occ") +
- brms::set_prior("std_normal()", class = "sd", dpar = "occ") +
- brms::set_prior("normal(0, 0.1)", class = "Intercept", dpar = "Omega"),
- backend = "cmdstanr",
- augmented = TRUE
- )
-writeLines(scode, model_name)
-
-aug_generator <- function(N){
- omega <- boot::inv.logit(rnorm(1, 0, .1))
- available <- rbinom(1, params$n_pseudospecies, omega)
- unavailable <- params$n_pseudospecies - available
- coef_means <- rnorm(5) # normal prior on random effect means
- sigma <- abs(rnorm(5)) # half-normal prior on all random effect sds
- Sigma <- diag(5) * sigma
-
- fd <- simulate_flocker_data(
- n_pt = params$n_sites, n_sp = available,
- params = list(
- coef_means = coef_means,
- Sigma = Sigma,
- coefs = data.frame(
- det_intercept = rnorm(available, coef_means[1], sigma[1]),
- det_slope_unit = rnorm(available, coef_means[2], sigma[2]),
- det_slope_visit = rnorm(available, coef_means[3], sigma[3]),
- occ_intercept = rnorm(available, coef_means[4], sigma[4]),
- occ_slope_unit = rnorm(available, coef_means[5], sigma[5])
- )
- ),
- seed = NULL,
- rep_constant = FALSE,
- ragged_rep = TRUE
- )
-
- obs_aug <- fd$obs[seq_len(params$n_sites), ]
-
- for(i in 2:available){
- obs_aug <- abind::abind(
- obs_aug,
- fd$obs[((i - 1) * params$n_sites) + seq_len(params$n_sites), ],
- along = 3
- )
- }
-
- event_covs_aug <- list(ec1 = fd$event_covs$ec1[seq_len(params$n_sites), ])
- unit_covs_aug <- data.frame(uc1 = fd$unit_covs[seq_len(params$n_sites), "uc1"])
-
- flocker_data = make_flocker_data(
- obs_aug, unit_covs_aug, event_covs_aug,
- type = "augmented", n_aug = unavailable,
- quiet = TRUE)
- # format for return
- list(
- variables = list(
- `b[1]` = fd$params$coef_means[1],
- `b[2]` = fd$params$coef_means[2],
- `b[3]` = fd$params$coef_means[3],
- `b_occ[1]` = fd$params$coef_means[4],
- `b_occ[2]` = fd$params$coef_means[5],
- `Intercept_Omega` = boot::logit(omega)
- ),
- generated = flocker_standata(
- f_occ = ~ 0 + Intercept + uc1 + (1 + uc1 || ff_species),
- f_det = ~ 0 + Intercept + uc1 + ec1 + (1 + uc1 + ec1 || ff_species),
- flocker_data = flocker_data,
- augmented = TRUE
- )
- )
-}
-
-aug_gen <- SBC_generator_function(
- aug_generator,
- N = params$n_sites
- )
-aug_dataset <- suppressMessages(
- generate_datasets(aug_gen, params$n_sims)
-)
-
-aug_backend <-
- SBC_backend_cmdstan_sample(
- cmdstanr::cmdstan_model(
- paste0(tempdir(), "/sbc_augmented_model.stan")
- )
- )
-
-aug_results <- compute_SBC(aug_dataset, aug_backend)
-## - 8 (4%) fits had at least one Rhat > 1.01. Largest Rhat was 1.019.
-## - 3 (2%) fits had divergent transitions. Maximum number of divergences was 1.
-## - 5 (2%) fits had some steps rejected. Maximum number of rejections was 1.
-## Not all diagnostics are OK.
-## You can learn more by inspecting $default_diagnostics, $backend_diagnostics
-## and/or investigating $outputs/$messages/$warnings for detailed output from the backend.
-plot_ecdf(aug_results)
-
-plot_rank_hist(aug_results)
-
-plot_ecdf_diff(aug_results)
-
-