🤝 Merge 'source' into cpac-py

.circleci/config.yml

@@ -15,7 +15,7 @@ jobs:
             apt-get update && apt-get -y install git rsync python-dev graphviz libgraphviz-dev pkg-config python3-sphinx
             pip install --user -r https://raw.githubusercontent.com/FCP-INDI/C-PAC/develop/requirements.txt
             pip install --user git+https://github.com/FCP-INDI/C-PAC.git sphinx m2r numpydoc PyGithub sphinxcontrib-programoutput
-            git clone https://github.com/FCP-INDI/C-PAC.git
+            git clone https://github.com/FCP-INDI/C-PAC.git /build/C-PAC
             python -m venv ~/simple
             source ~/simple/bin/activate
             pip install cpac

docs/user/_sources/_static/params/group_config.csv

@@ -2,7 +2,7 @@ participant_list,A list of subjects to be included in the model. This should be
 pheno_file,A csv file containing EV information for each subject.,"A path (e.g., ‘/data/my_analysis/ev.csv’)."
 participant_id_label,Name of the subjects column in your EV file.,A string.
 ev_selections,"Specify which EVs from your phenotype are categorical or numerical. Of those which are numerical, specify which are to be demeaned.","A dictionary with two keys, ‘demean’ and ‘categorical’. Each of these keys has a list as its value, with the names of the EVs that are categorical and which are to be demeaned. For example: {‘demean’: [‘age’], ‘categorical’: [‘sex’, ‘diagnosis’]}"
-design_formula,"Specify the formula to describe your model design. Essentially, including EVs in this formula inserts them into the model. The most basic format to include each EV you select would be ‘EV + EV + EV + ..’, etc. You can also select to include MeanFD, Measure_Mean, and Custom_ROI_Mean here. See the GUI instructions for more details.","A formula (e.g., ‘sex + diagnosis + age + MeanFD_Jenkinson’)."
+design_formula,"Specify the formula to describe your model design. Essentially, including EVs in this formula inserts them into the model. The most basic format to include each EV you select would be ‘EV + EV + EV + ..’, etc. You can also select to include MeanFD, Measure_Mean, and Custom_ROI_Mean here.","A formula (e.g., ‘sex + diagnosis + age + MeanFD_Jenkinson’)."
 mean_mask,Choose whether to use a group mask or individual-specific mask when calculating the output means to be used as a regressor. This only takes effect if you include the ‘Measure_Mean’ regressor in your Design Matrix Formula.,A string within a list- can be [‘Group Mask’] or [‘Individual Mask’].
 custom_roi_mask,Full path to a NIFTI file containing one or more ROI masks. The means of the masked regions will then be computed for each subject’s output and will be included in the model as regressors (one for each ROI in the mask file) if you include ‘Custom_ROI_Mean’ in the Design Matrix Formula.,"A path (e.g., ‘/data/my_analysis/ROI.nii.gz’) or None."
 derivative_list,"Choose the derivatives to run the group model on. These must be written out as a list, and must be one of the options listed below this table.","A list (e.g., [‘alff_to_standard_smooth_zstd’, ‘sca_roi_files_to_standard_smooth_fisher_zstd’] )."
@@ -13,7 +13,7 @@ z_threshold,Only voxels with a Z-score higher than this value will be considered
 p_threshold,Significance threshold (P-value) to use when doing cluster correction for multiple comparisons.,"A list containing a decimal value as a string (e.g., [‘0.05’])."
 sessions_list,For repeated measures only. This is a list of session names that you wish to include in a single model to run repeated measures or within-subject analysis.  Repeated measures will run automatically if this is non-empty.,"A list containing a session names as strings (e.g., [‘session_1’,'session_2'])."
 series_list,For repeated measures only. This is a list of series/scan names that you wish to include in a single model to run repeated measures or within-subject analysis.  Repeated measures will run automatically if this is non-empty.,"A list containing a scan names as strings (e.g., [‘scan_1’,'scan_2'])."
-contrasts,The contrasts to be run as part of the group analysis. See the GUI instructions for more details.,"A list of contrast descriptions (e.g., [‘C(diagnosis)[T.ADHD] - C(diagnosis)[T.Typical] = 0’, 'age = 0'])."
+contrasts,The contrasts to be run as part of the group analysis.,"A list of contrast descriptions (e.g., [‘C(diagnosis)[T.ADHD] - C(diagnosis)[T.Typical] = 0’, 'age = 0'])."
 f_tests,"An optional list of f-test strings containing contrasts. If you do not wish to run f-tests, leave this blank.","A list of strings containing all the contrasts to be included in the f-test separated by commas (e.g., [‘C(diagnosis)[T.ADHD] - C(diagnosis)[T.Typical] = 0, age = 0’])."
 custom_contrasts,An optional path to a CSV file which specifies the contrasts you wish to run in group analysis. See ‘Custom Contrasts’ section below.,"A path (e.g., ‘/data/my_analysis/custom_contrasts.csv’)."
 model_name,A name for the new model.,A string.

docs/user/_sources/appendix.txt

@@ -142,7 +142,6 @@ Please ensure that you are using Python 3.6 and above. Though many computers com
 * `Nipype <http://nipype.readthedocs.io/en/latest/>`__ - version 1.1.2
 * `NetworkX <http://networkx.lanl.gov/>`__ - version 1.11
 * `Jinja2 <http://jinja.pocoo.org/docs/intro/#installation>`__ - version 2.7.2
-* `wxPython 3 <https://wxpython.org/>`__ - version 3.0.0 (if using the GUI)
 
 These specific versions can be installed via pip:
 

docs/user/_sources/docker.txt

@@ -73,3 +73,20 @@ Finally, to run the Docker container with a specific data configuration file (in
 
 Note: we are still providing ``/bids_dataset`` to the ``bids_dir`` input parameter. However, we have mapped this to any directory on your machine, as C-PAC will not look for data in this directory when you provide a data configuration YAML with the ``--data_config_file`` flag. In addition, if the dataset in your data configuration file is not in BIDS format, just make sure to add the ``--skip_bids_validator`` flag at the end of your command to bypass the BIDS validation process.
 
+The full list of parameters and options that can be passed to the Docker container are shown below:
+
+.. include:: /run/help.txt
+
+Note that any of the optional arguments above will over-ride any pipeline settings in the default pipeline or in the pipeline configuration file you provide via the ``--pipeline_file`` parameter.
+
+**Further usage notes:**
+
+* You can run only anatomical preprocessing easily, without modifying your data or pipeline configuration files, by providing the ``--anat_only`` flag.
+
+* As stated, the default behavior is to read data that is organized in the BIDS format. This includes data that is in Amazon AWS S3 by using the format ``s3://<bucket_name>/<bids_dir>`` for the ``bids_dir`` command line argument. Outputs can be written to S3 using the same format for the ``output_dir``. Credentials for accessing these buckets can be specified on the command line (using ``--aws_input_creds`` or ``--aws_output_creds``).
+
+* When the app is run, a data configuration file is written to the working directory. This file can be passed into subsequent runs, which avoids the overhead of re-parsing the BIDS input directory on each run (i.e. for cluster or cloud runs). These files can be generated without executing the C-PAC pipeline using the test_run command line argument.
+
+* The ``participant_label`` and ``participant_ndx`` arguments allow the user to specify which of the many datasets should be processed, which is useful when parallelizing the run of multiple participants.
+
+

docs/user/_sources/futuredocs/basc.txt

@@ -5,7 +5,7 @@ Introduction & Background
 ^^^^^^^^^^^^^^^^^^^^^^^^^
 Bootstrap Analysis of Stable Clusters (BASC) is a statistical framework that quantifies the stability of Resting State Networks (RSNs) by comparing the results of cluster analysis across replications (Bellec et al. 2010) As it is often impossible or impractical to repeat data collection for an experiment multiple times, BASC utilizes bootstrapping to generate a large number of samples from the existing data. BASC can be used to characterize stable RSNs at both the individual and group levels. 
 
-**Important Note: BASC is currently not fully implemented in C-PAC.  This page is a reference for how to use it in future releases.  An interface is available in the C-PAC GUI, but it is not functional.**
+**Important Note: BASC is currently not fully implemented in C-PAC.  This page is a reference for how to use it in future releases.**
 
 Computation and Analysis Considerations
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^