From 2f62fe8d368dffe97c0460010f39ce1bce4e480a Mon Sep 17 00:00:00 2001 From: atmorling Date: Thu, 25 Apr 2024 10:23:44 +0200 Subject: [PATCH 1/7] Fix #128 (#130) --- ecoscope/io/earthranger.py | 89 +++++++++++++++++++-------- notebooks/01. IO/EarthRanger_IO.ipynb | 14 +++-- tests/test_base.py | 10 +-- tests/test_earthranger_io.py | 11 +++- 4 files changed, 87 insertions(+), 37 deletions(-) diff --git a/ecoscope/io/earthranger.py b/ecoscope/io/earthranger.py index b01b2e17..c1d21abb 100644 --- a/ecoscope/io/earthranger.py +++ b/ecoscope/io/earthranger.py @@ -2,7 +2,9 @@ import pytz import json import typing +import math +import numpy as np import geopandas as gpd import pandas as pd import requests @@ -122,13 +124,14 @@ def get_subjects( self, include_inactive=None, bbox=None, - subject_group=None, + subject_group_id=None, name=None, updated_since=None, tracks=None, id=None, updated_until=None, - group_name=None, + subject_group_name=None, + max_ids_per_request=50, **addl_kwargs, ): """ @@ -137,13 +140,15 @@ def get_subjects( include_inactive: Include inactive subjects in list. bbox: Include subjects having track data within this bounding box defined by a 4-tuple of coordinates marking west, south, east, north. - subject_group: Indicate a subject group for which Subjects should be listed. + subject_group_id: Indicate a subject group id for which Subjects should be listed. + This is translated to the subject_group parameter in the ER backend name : Find subjects with the given name updated_since: Return Subject that have been updated since the given timestamp. tracks: Indicate whether to render each subject's recent tracks. id: A comma-delimited list of Subject IDs. updated_until - group_name + subject_group_name: A subject group name for which Subjects should be listed. + This is translated to the group_name parameter in the ER backend Returns ------- subjects : pd.DataFrame @@ -153,13 +158,13 @@ def get_subjects( addl_kwargs, include_inactive=include_inactive, bbox=bbox, - subject_group=subject_group, + subject_group=subject_group_id, name=name, updated_since=updated_since, tracks=tracks, id=id, updated_until=updated_until, - group_name=group_name, + group_name=subject_group_name, ) assert params.get("subject_group") is None or params.get("group_name") is None @@ -178,11 +183,32 @@ def get_subjects( except IndexError: raise KeyError("`group_name` not found") - df = pd.DataFrame( - self.get_objects_multithreaded( - object="subjects/", threads=self.tcp_limit, page_size=self.sub_page_size, **params + if params.get("id") is not None: + params["id"] = params.get("id").split(",") + + def partial_subjects(subjects): + params["id"] = ",".join(subjects) + return pd.DataFrame( + self.get_objects_multithreaded( + object="subjects/", threads=self.tcp_limit, page_size=self.sub_page_size, **params + ) + ) + + df = pd.concat( + [ + partial_subjects(s) + for s in np.array_split(params["id"], math.ceil(len(params["id"]) / max_ids_per_request)) + ], + ignore_index=True, ) - ) + + else: + df = pd.DataFrame( + self.get_objects_multithreaded( + object="subjects/", threads=self.tcp_limit, page_size=self.sub_page_size, **params + ) + ) + assert not df.empty df["hex"] = df["additional"].str["rgb"].map(to_hex) if "additional" in df else "#ff0000" @@ -350,8 +376,8 @@ def get_subject_observations( Get observations for each listed subject and create a `Relocations` object. Parameters ---------- - subject_ids : str or list[str] - List of subject UUIDs + subject_ids : str or list[str] or pd.DataFrame + List of subject UUIDs, or a DataFrame of subjects include_source_details : bool, optional Whether to merge source info into dataframe include_subject_details : bool, optional @@ -369,6 +395,10 @@ def get_subject_observations( if isinstance(subject_ids, str): subject_ids = [subject_ids] + elif isinstance(subject_ids, pd.DataFrame): + subject_ids = subject_ids.id.tolist() + elif not isinstance(subject_ids, list): + raise ValueError(f"subject_ids must be either a str or list[str] or pd.DataFrame, not {type(subject_ids)}") observations = self._get_observations(subject_ids=subject_ids, **kwargs) @@ -382,11 +412,18 @@ def get_subject_observations( right_on="source__id", ) if include_subject_details: - observations = observations.merge( - self.get_subjects(id=",".join(subject_ids), include_inactive=True).add_prefix("subject__"), - left_on="subject_id", - right_on="subject__id", - ) + if isinstance(subject_ids, pd.DataFrame): + observations = observations.merge( + subject_ids.add_prefix("subject__"), + left_on="subject_id", + right_on="subject__id", + ) + else: + observations = observations.merge( + self.get_subjects(id=",".join(subject_ids), include_inactive=True).add_prefix("subject__"), + left_on="subject_id", + right_on="subject__id", + ) if include_subjectsource_details: observations = observations.merge( @@ -456,13 +493,15 @@ def get_subjectsource_observations( else: return observations - def get_subjectgroup_observations(self, subject_group=None, group_name=None, include_inactive=True, **kwargs): + def get_subjectgroup_observations( + self, subject_group_id=None, subject_group_name=None, include_inactive=True, **kwargs + ): """ Parameters ---------- - subject_group : str + subject_group_id : str UUID of subject group to filter by - group_name : str + subject_group_name : str Common name of subject group to filter by include_inactive : bool, optional Whether to get observations for Subjects marked inactive by EarthRanger @@ -475,14 +514,14 @@ def get_subjectgroup_observations(self, subject_group=None, group_name=None, inc Observations in `Relocations` format """ - assert (subject_group is None) != (group_name is None) + assert (subject_group_id is None) != (subject_group_name is None) - if subject_group: - subject_ids = self.get_subjects(subject_group=subject_group, include_inactive=include_inactive).id.tolist() + if subject_group_id: + subjects = self.get_subjects(subject_group=subject_group_id, include_inactive=include_inactive) else: - subject_ids = self.get_subjects(group_name=group_name, include_inactive=include_inactive).id.tolist() + subjects = self.get_subjects(group_name=subject_group_name, include_inactive=include_inactive) - return self.get_subject_observations(subject_ids, **kwargs) + return self.get_subject_observations(subjects, **kwargs) def get_event_types(self, include_inactive=False, **addl_kwargs): params = self._clean_kwargs(addl_kwargs, include_inactive=include_inactive) diff --git a/notebooks/01. IO/EarthRanger_IO.ipynb b/notebooks/01. IO/EarthRanger_IO.ipynb index 207868ca..9af4c13d 100644 --- a/notebooks/01. IO/EarthRanger_IO.ipynb +++ b/notebooks/01. IO/EarthRanger_IO.ipynb @@ -423,7 +423,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### By `SubjectGroup` `group_name`" + "### By `SubjectGroup` `subject_group_name`" ] }, { @@ -432,7 +432,7 @@ "metadata": {}, "outputs": [], "source": [ - "er_io.get_subjects(group_name=\"Elephants\")" + "er_io.get_subjects(subject_group_name=\"Elephants\")" ] }, { @@ -459,7 +459,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### By `SubjectGroup` `group_name`:" + "### By `SubjectGroup` `subject_group_name`:" ] }, { @@ -479,7 +479,7 @@ "outputs": [], "source": [ "relocs = er_io.get_subjectgroup_observations(\n", - " group_name=\"Elephants\",\n", + " subject_group_name=\"Elephants\",\n", " filter=0,\n", " since=since,\n", " until=until,\n", @@ -704,7 +704,9 @@ "metadata": {}, "outputs": [], "source": [ - "elephants = er_io.get_subjectgroup_observations(group_name=\"Elephants\", since=pd.Timestamp(\"2022-01-01\").isoformat())\n", + "elephants = er_io.get_subjectgroup_observations(\n", + " subject_group_name=\"Elephants\", since=pd.Timestamp(\"2022-01-01\").isoformat()\n", + ")\n", "\n", "if not elephants.empty:\n", " for i, value in elephants.iterrows():\n", @@ -834,7 +836,7 @@ "outputs": [], "source": [ "relocs = er_io.get_subjectgroup_observations(\n", - " group_name=\"Elephants\",\n", + " subject_group_name=\"Elephants\",\n", " filter=0,\n", " since=since,\n", " until=until,\n", diff --git a/tests/test_base.py b/tests/test_base.py index ec225ab7..48e9e27c 100644 --- a/tests/test_base.py +++ b/tests/test_base.py @@ -11,7 +11,7 @@ @pytest.mark.skipif(not pytest.earthranger, reason="No connection to EarthRanger") def test_trajectory_is_not_empty(er_io): # test there is actually data in trajectory - relocations = er_io.get_subjectgroup_observations(group_name=er_io.GROUP_NAME) + relocations = er_io.get_subjectgroup_observations(subject_group_name=er_io.GROUP_NAME) trajectory = ecoscope.base.Trajectory.from_relocations(relocations) assert not trajectory.empty @@ -19,7 +19,7 @@ def test_trajectory_is_not_empty(er_io): @pytest.mark.skipif(not pytest.earthranger, reason="No connection to EarthRanger") def test_redundant_columns_in_trajectory(er_io): # test there is no redundant column in trajectory - relocations = er_io.get_subjectgroup_observations(group_name=er_io.GROUP_NAME) + relocations = er_io.get_subjectgroup_observations(subject_group_name=er_io.GROUP_NAME) trajectory = ecoscope.base.Trajectory.from_relocations(relocations) assert "extra__fixtime" not in trajectory assert "extra___fixtime" not in trajectory @@ -28,7 +28,7 @@ def test_redundant_columns_in_trajectory(er_io): @pytest.mark.skipif(not pytest.earthranger, reason="No connection to EarthRanger") def test_relocs_speedfilter(er_io): - relocations = er_io.get_subjectgroup_observations(group_name=er_io.GROUP_NAME) + relocations = er_io.get_subjectgroup_observations(subject_group_name=er_io.GROUP_NAME) relocs_speed_filter = ecoscope.base.RelocsSpeedFilter(max_speed_kmhr=8) relocs_after_filter = relocations.apply_reloc_filter(relocs_speed_filter) relocs_after_filter.remove_filtered(inplace=True) @@ -37,7 +37,7 @@ def test_relocs_speedfilter(er_io): @pytest.mark.skipif(not pytest.earthranger, reason="No connection to EarthRanger") def test_relocs_distancefilter(er_io): - relocations = er_io.get_subjectgroup_observations(group_name=er_io.GROUP_NAME) + relocations = er_io.get_subjectgroup_observations(subject_group_name=er_io.GROUP_NAME) relocs_speed_filter = ecoscope.base.RelocsDistFilter(min_dist_km=1.0, max_dist_km=6.0) relocs_after_filter = relocations.apply_reloc_filter(relocs_speed_filter) relocs_after_filter.remove_filtered(inplace=True) @@ -46,7 +46,7 @@ def test_relocs_distancefilter(er_io): @pytest.mark.skipif(not pytest.earthranger, reason="No connection to EarthRanger") def test_relocations_from_gdf_preserve_fields(er_io): - relocations = er_io.get_subjectgroup_observations(group_name=er_io.GROUP_NAME) + relocations = er_io.get_subjectgroup_observations(subject_group_name=er_io.GROUP_NAME) gpd.testing.assert_geodataframe_equal(relocations, ecoscope.base.Relocations.from_gdf(relocations)) diff --git a/tests/test_earthranger_io.py b/tests/test_earthranger_io.py index 6f87e2dd..e98a65ef 100644 --- a/tests/test_earthranger_io.py +++ b/tests/test_earthranger_io.py @@ -66,7 +66,7 @@ def test_get_subjectsource_no_observations(er_io): def test_get_subjectgroup_observations(er_io): - relocations = er_io.get_subjectgroup_observations(group_name=er_io.GROUP_NAME) + relocations = er_io.get_subjectgroup_observations(subject_group_name=er_io.GROUP_NAME) assert "groupby_col" in relocations @@ -190,6 +190,7 @@ def test_patch_event(er_io): pd.testing.assert_frame_equal(result, updated_event) +@pytest.mark.skip(reason="Known issue: https://github.com/wildlife-dynamics/ecoscope/issues/109") def test_get_patrol_observations(er_io): patrols = er_io.get_patrols() observations = er_io.get_patrol_observations( @@ -216,3 +217,11 @@ def test_get_spatial_features_group(er_io): spatial_features_group_id="15698426-7e0f-41df-9bc3-495d87e2e097" ) assert not spatial_features.empty + + +def test_get_subjects_chunking(er_io): + subject_ids = ",".join(er_io.SUBJECT_IDS) + single_request_result = er_io.get_subjects(id=subject_ids) + chunked_request_result = er_io.get_subjects(id=subject_ids, max_ids_per_request=1) + + pd.testing.assert_frame_equal(single_request_result, chunked_request_result) From b3b9d1543eee5357ef9b2df8a4135d47d40f39d4 Mon Sep 17 00:00:00 2001 From: atmorling Date: Tue, 30 Apr 2024 15:10:43 +0200 Subject: [PATCH 2/7] fix get_subjects params in get_subjectgroup_observations (#137) --- ecoscope/io/earthranger.py | 4 ++-- tests/test_earthranger_io.py | 1 + 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/ecoscope/io/earthranger.py b/ecoscope/io/earthranger.py index c1d21abb..1a4e66ac 100644 --- a/ecoscope/io/earthranger.py +++ b/ecoscope/io/earthranger.py @@ -517,9 +517,9 @@ def get_subjectgroup_observations( assert (subject_group_id is None) != (subject_group_name is None) if subject_group_id: - subjects = self.get_subjects(subject_group=subject_group_id, include_inactive=include_inactive) + subjects = self.get_subjects(subject_group_id=subject_group_id, include_inactive=include_inactive) else: - subjects = self.get_subjects(group_name=subject_group_name, include_inactive=include_inactive) + subjects = self.get_subjects(subject_group_name=subject_group_name, include_inactive=include_inactive) return self.get_subject_observations(subjects, **kwargs) diff --git a/tests/test_earthranger_io.py b/tests/test_earthranger_io.py index e98a65ef..f6af1f2c 100644 --- a/tests/test_earthranger_io.py +++ b/tests/test_earthranger_io.py @@ -68,6 +68,7 @@ def test_get_subjectsource_no_observations(er_io): def test_get_subjectgroup_observations(er_io): relocations = er_io.get_subjectgroup_observations(subject_group_name=er_io.GROUP_NAME) assert "groupby_col" in relocations + assert len(relocations["extra__subject_id"].unique()) == 2 def test_get_events(er_events_io): From 2fa1e1a1225e0e1518b66e4b7cf32fdafdd781e9 Mon Sep 17 00:00:00 2001 From: Eric Gitonga Date: Thu, 9 May 2024 12:56:01 +0300 Subject: [PATCH 3/7] fix bug in get_events that chokes on subsecond values in timestamp (#147) --- ecoscope/io/earthranger.py | 4 +++- ecoscope/version.py | 2 +- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/ecoscope/io/earthranger.py b/ecoscope/io/earthranger.py index 1a4e66ac..129fdc7c 100644 --- a/ecoscope/io/earthranger.py +++ b/ecoscope/io/earthranger.py @@ -8,6 +8,7 @@ import geopandas as gpd import pandas as pd import requests +from dateutil import parser from erclient.client import ERClient, ERClientException, ERClientNotFound from tqdm.auto import tqdm @@ -632,7 +633,8 @@ def get_events( ) assert not df.empty - df["time"] = pd.to_datetime(df["time"]) + + df["time"] = df["time"].apply(lambda x: pd.to_datetime(parser.parse(x))) gdf = gpd.GeoDataFrame(df) if gdf.loc[0, "location"] is not None: diff --git a/ecoscope/version.py b/ecoscope/version.py index 14d9d2f5..3c1e9cbd 100644 --- a/ecoscope/version.py +++ b/ecoscope/version.py @@ -1 +1 @@ -__version__ = "1.7.0" +__version__ = "1.7.1" From d02a3f3ce0c1b1524b98ef7ff5940adbe9c6ac8c Mon Sep 17 00:00:00 2001 From: Eric Gitonga Date: Tue, 14 May 2024 16:36:48 +0300 Subject: [PATCH 4/7] remove skip on test_get_patrol_observations() (#156) --- ecoscope/version.py | 2 +- tests/test_earthranger_io.py | 1 - 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/ecoscope/version.py b/ecoscope/version.py index 3c1e9cbd..1db13ec2 100644 --- a/ecoscope/version.py +++ b/ecoscope/version.py @@ -1 +1 @@ -__version__ = "1.7.1" +__version__ = "1.7.2" diff --git a/tests/test_earthranger_io.py b/tests/test_earthranger_io.py index f6af1f2c..d5712a6e 100644 --- a/tests/test_earthranger_io.py +++ b/tests/test_earthranger_io.py @@ -191,7 +191,6 @@ def test_patch_event(er_io): pd.testing.assert_frame_equal(result, updated_event) -@pytest.mark.skip(reason="Known issue: https://github.com/wildlife-dynamics/ecoscope/issues/109") def test_get_patrol_observations(er_io): patrols = er_io.get_patrols() observations = er_io.get_patrol_observations( From 733d3c4bc73b5132c2e63b41a8089a10557f8a50 Mon Sep 17 00:00:00 2001 From: atmorling Date: Wed, 15 May 2024 14:52:01 +0200 Subject: [PATCH 5/7] rework of std_ndvi_vals (#138) --- ecoscope/analysis/seasons.py | 15 +++++++++------ .../Seasonal Calculation.ipynb | 9 +++++---- tests/test_seasons.py | 11 +++++++++-- 3 files changed, 23 insertions(+), 12 deletions(-) diff --git a/ecoscope/analysis/seasons.py b/ecoscope/analysis/seasons.py index d6c3a87e..73f87ab0 100644 --- a/ecoscope/analysis/seasons.py +++ b/ecoscope/analysis/seasons.py @@ -19,11 +19,11 @@ def _min_max_scaler(x): return x_std -def std_ndvi_vals(aoi=None, img_coll=None, band=None, img_scale=1, start=None, end=None): +def std_ndvi_vals(aoi=None, img_coll=None, nir_band=None, red_band=None, img_scale=1, start=None, end=None): coll = ( ee.ImageCollection(img_coll) - .select(band) + .select([nir_band, red_band]) .filterDate(start, end) .map(lambda x: x.multiply(ee.Image(img_scale)).set("system:time_start", x.get("system:time_start"))) ) @@ -33,11 +33,14 @@ def std_ndvi_vals(aoi=None, img_coll=None, band=None, img_scale=1, start=None, e else: geo = None + img_dates = pandas.to_datetime(coll.aggregate_array("system:time_start").getInfo(), unit="ms", utc=True) + + coll = coll.map(lambda x: x.normalizedDifference([nir_band, red_band])) ndvi_vals = coll.toBands().reduceRegion("mean", geo, bestEffort=True).values().getInfo() df = pandas.DataFrame( { - "img_date": pandas.to_datetime(coll.aggregate_array("system:time_start").getInfo(), unit="ms", utc=True), + "img_date": img_dates, "NDVI": ndvi_vals, } ).dropna(axis=0) @@ -110,13 +113,13 @@ def seasonal_windows(ndvi_vals, cuts, season_labels): def add_seasonal_index( - df, index_name, start_date, end_date, aoi_geom_filter=None, seasons=2, season_labels=["dry", "wet"] + df, index_name, start_date, end_date, time_col, aoi_geom_filter=None, seasons=2, season_labels=["dry", "wet"] ): aoi_ = None try: aoi_ = aoi_geom_filter.dissolve().iloc[0]["geometry"] - except: + except AttributeError: aoi_ = aoi_geom_filter if len(season_labels) != seasons: @@ -124,7 +127,7 @@ def add_seasonal_index( f"Parameter value 'seasons' ({seasons}) must match the number of 'season_labels' elements ({season_labels})" ) # extract the standardized NDVI ndvi_vals within the AOI - ndvi_vals = std_ndvi_vals(aoi_, start=since_filter.isoformat(), end=until_filter.isoformat()) + ndvi_vals = std_ndvi_vals(aoi_, start=start_date.isoformat(), end=end_date.isoformat()) # calculate the seasonal transition point cuts = val_cuts(ndvi_vals, seasons) diff --git a/notebooks/05. Environmental Analyses/Seasonal Calculation.ipynb b/notebooks/05. Environmental Analyses/Seasonal Calculation.ipynb index 349585bc..a021513a 100644 --- a/notebooks/05. Environmental Analyses/Seasonal Calculation.ipynb +++ b/notebooks/05. Environmental Analyses/Seasonal Calculation.ipynb @@ -155,15 +155,16 @@ "metadata": {}, "outputs": [], "source": [ - "img_coll = \"MODIS/061/MOD13A1\"\n", + "img_coll = \"MODIS/061/MCD43A4\"\n", "band = \"NDVI\"\n", - "img_scale = 0.0001\n", - "since_filter = \"2010-01-01\"\n", + "img_scale = 1\n", + "since_filter = \"2020-01-01\"\n", "until_filter = \"2022-06-18\"\n", "\n", "ndvi_vals = seasons.std_ndvi_vals(\n", " img_coll=img_coll,\n", - " band=band,\n", + " nir_band=\"Nadir_Reflectance_Band2\",\n", + " red_band=\"Nadir_Reflectance_Band1\",\n", " img_scale=img_scale,\n", " aoi=aoi,\n", " start=since_filter,\n", diff --git a/tests/test_seasons.py b/tests/test_seasons.py index f2a547d9..a39c4051 100644 --- a/tests/test_seasons.py +++ b/tests/test_seasons.py @@ -10,14 +10,21 @@ ) -@pytest.mark.skip(reason="this has been failing since May 2022; will be fixed in a follow-up pull") +@pytest.mark.skipif(not pytest.earthengine, reason="No connection to EarthEngine.") def test_seasons(): gdf = gpd.read_file("tests/sample_data/vector/AOI_sites.gpkg").to_crs(4326) aoi = gdf.geometry.iat[0] # Extract the standardized NDVI ndvi_vals within the AOI - ndvi_vals = ecoscope.analysis.seasons.std_ndvi_vals(aoi, start="2010-01-01", end="2021-01-01") + ndvi_vals = ecoscope.analysis.seasons.std_ndvi_vals( + aoi, + img_coll="MODIS/061/MCD43A4", + nir_band="Nadir_Reflectance_Band2", + red_band="Nadir_Reflectance_Band1", + start="2010-01-01", + end="2021-01-01", + ) # Calculate the seasonal transition point cuts = ecoscope.analysis.seasons.val_cuts(ndvi_vals, 2) From 29f6fdacf104b78e24dd6ba735ab91e755151c01 Mon Sep 17 00:00:00 2001 From: atmorling Date: Thu, 16 May 2024 09:41:07 +0200 Subject: [PATCH 6/7] 127/tests (#131) --- .github/workflows/main.yml | 2 +- .gitignore | 5 +- ecoscope/analysis/ecograph.py | 48 ++---- ecoscope/analysis/proximity.py | 2 +- ecoscope/base/base.py | 23 ++- ecoscope/base/utils.py | 5 +- ecoscope/io/raster.py | 8 +- .../Relocations_and_Trajectories.ipynb | 8 +- .../Elliptical Time Density (ETD).ipynb | 6 +- notebooks/04. EcoMap & EcoPlot/EcoMap.ipynb | 44 +++--- tests/conftest.py | 6 +- tests/reference_data/salif_btwn_max.feather | Bin 0 -> 267602 bytes tests/reference_data/salif_ci_min.feather | Bin 0 -> 224346 bytes .../reference_data/salif_degree_mean.feather | Bin 0 -> 153442 bytes .../salif_degree_mean_std.feather | Bin 0 -> 153538 bytes .../salif_dotprod.feather | Bin 204722 -> 206066 bytes tests/reference_data/salif_sl_median.feather | Bin 0 -> 278162 bytes .../salif_speed.feather | Bin 205066 -> 206410 bytes .../{movbank_data.csv => movebank_data.csv} | 0 ...ank_data.feather => movebank_data.feather} | Bin tests/test_base.py | 40 ++--- tests/test_ecograph.py | 138 +++++++----------- tests/test_eetools.py | 20 +-- tests/test_immobility.py | 6 +- tests/test_io_utils.py | 3 +- tests/test_output/salif_btwn_max.feather | Bin 266218 -> 0 bytes tests/test_output/salif_ci_min.feather | Bin 222922 -> 0 bytes tests/test_output/salif_degree_mean.feather | Bin 151714 -> 0 bytes .../test_output/salif_degree_mean_std.feather | Bin 151810 -> 0 bytes tests/test_output/salif_sl_median.feather | Bin 276810 -> 0 bytes tests/test_speed.py | 4 +- tests/test_ud.py | 19 +-- tests/test_utils.py | 7 +- 33 files changed, 182 insertions(+), 212 deletions(-) create mode 100644 tests/reference_data/salif_btwn_max.feather create mode 100644 tests/reference_data/salif_ci_min.feather create mode 100644 tests/reference_data/salif_degree_mean.feather create mode 100644 tests/reference_data/salif_degree_mean_std.feather rename tests/{test_output => reference_data}/salif_dotprod.feather (96%) create mode 100644 tests/reference_data/salif_sl_median.feather rename tests/{test_output => reference_data}/salif_speed.feather (96%) rename tests/sample_data/vector/{movbank_data.csv => movebank_data.csv} (100%) rename tests/sample_data/vector/{movbank_data.feather => movebank_data.feather} (100%) delete mode 100644 tests/test_output/salif_btwn_max.feather delete mode 100644 tests/test_output/salif_ci_min.feather delete mode 100644 tests/test_output/salif_degree_mean.feather delete mode 100644 tests/test_output/salif_degree_mean_std.feather delete mode 100644 tests/test_output/salif_sl_median.feather diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml index e329e650..1150635a 100644 --- a/.github/workflows/main.yml +++ b/.github/workflows/main.yml @@ -18,7 +18,7 @@ jobs: - uses: actions/checkout@v2 - name: Setup Micromamba - uses: mamba-org/provision-with-micromamba@main + uses: mamba-org/setup-micromamba@v1 with: environment-file: ${{ matrix.env }} diff --git a/.gitignore b/.gitignore index ac3caf00..b8e78189 100644 --- a/.gitignore +++ b/.gitignore @@ -124,6 +124,9 @@ venv.bak/ #Jetbrains .idea/ +#vscode +.vscode/ + # mypy .mypy_cache/ .dmypy.json @@ -162,4 +165,4 @@ tests/test_output/new.html tests/test_output/movbank_data.csv tests/test_output/movbank_data.csv.zip tests/test_output/download_data.csv -tests/test_output/config.json \ No newline at end of file +tests/test_output/config.json diff --git a/ecoscope/analysis/ecograph.py b/ecoscope/analysis/ecograph.py index 1deef492..976c2d2f 100644 --- a/ecoscope/analysis/ecograph.py +++ b/ecoscope/analysis/ecograph.py @@ -75,10 +75,10 @@ def __init__(self, trajectory, resolution=15, radius=2, cutoff=None, tortuosity_ def compute(df): subject_name = df.name print(f"Computing EcoGraph for subject {subject_name}") - G = self._get_ecograph(self, df, subject_name, radius, cutoff, tortuosity_length) + G = self._get_ecograph(df, subject_name, radius, cutoff, tortuosity_length) self.graphs[subject_name] = G - self.trajectory.groupby("groupby_col").progress_apply(compute) + self.trajectory.groupby("groupby_col")[self.trajectory.columns].progress_apply(compute) def to_csv(self, output_path): """ @@ -122,13 +122,13 @@ def to_geotiff(self, feature, output_path, individual="all", interpolation=None, if feature in self.features: if individual == "all": - feature_ndarray = self._get_feature_mosaic(self, feature, interpolation) + feature_ndarray = self._get_feature_mosaic(feature, interpolation) elif individual in self.graphs.keys(): - feature_ndarray = self._get_feature_map(self, feature, individual, interpolation) + feature_ndarray = self._get_feature_map(feature, individual, interpolation) else: - raise IndividualNameError("This individual is not in the dataset") + raise ValueError("This individual is not in the dataset") else: - raise FeatureNameError("This feature was not computed by EcoGraph") + raise ValueError("This feature was not computed by EcoGraph") if isinstance(transform, sklearn.base.TransformerMixin): nan_mask = ~np.isnan(feature_ndarray) @@ -151,7 +151,6 @@ def to_geotiff(self, feature, output_path, individual="all", interpolation=None, **raster_profile, ) - @staticmethod def _get_ecograph(self, trajectory_gdf, individual_name, radius, cutoff, tortuosity_length): G = nx.Graph() geom = trajectory_gdf["geometry"] @@ -174,7 +173,7 @@ def _get_ecograph(self, trajectory_gdf, individual_name, radius, cutoff, tortuos trajectory_gdf.iloc[i + (tortuosity_length - 1)]["segment_end"] ) - pd.to_datetime(t) time_delta = time_diff.total_seconds() / 3600.0 - tortuosity_1, tortuosity_2 = self._get_tortuosities(self, lines, time_delta) + tortuosity_1, tortuosity_2 = self._get_tortuosities(lines, time_delta) attributes = { "dot_product": self._get_dot_product(p1, p2, p3, p4), @@ -202,7 +201,7 @@ def _get_ecograph(self, trajectory_gdf, individual_name, radius, cutoff, tortuos else: G.nodes[node][key] = np.nan - self._compute_network_metrics(self, G, radius, cutoff) + self._compute_network_metrics(G, radius, cutoff) return G @staticmethod @@ -244,7 +243,6 @@ def _get_dot_product(x, y, z, w): else: return np.nan - @staticmethod def _get_tortuosities(self, lines, time_delta): point1, point2 = lines[0][0], lines[len(lines) - 1][1] beeline_dist = np.sqrt((point2[0] - point1[0]) ** 2 + (point2[1] - point1[1]) ** 2) @@ -270,18 +268,16 @@ def _get_tortuosities(self, lines, time_delta): else: return np.nan, np.nan - @staticmethod def _compute_network_metrics(self, G, radius, cutoff): self._compute_degree(G) self._compute_betweenness(G, cutoff) - self._compute_collective_influence(self, G, radius) + self._compute_collective_influence(G, radius) @staticmethod def _compute_degree(G): for node in G.nodes(): G.nodes[node]["degree"] = G.degree[node] - @staticmethod def _compute_collective_influence(self, G, radius): for node in G.nodes(): G.nodes[node]["collective_influence"] = self._get_collective_influence(G, node, radius) @@ -303,11 +299,10 @@ def _compute_betweenness(G, cutoff): node = v["_nx_name"] G.nodes[node]["betweenness"] = btw_idx[v.index] - @staticmethod def _get_feature_mosaic(self, feature, interpolation=None): features = [] for individual in self.graphs.keys(): - features.append(self._get_feature_map(self, feature, individual, interpolation)) + features.append(self._get_feature_map(feature, individual, interpolation)) mosaic = np.full((self.n_cols, self.n_rows), np.nan) for i in range(self.n_cols): for j in range(self.n_rows): @@ -322,23 +317,20 @@ def _get_feature_mosaic(self, feature, interpolation=None): mosaic[i][j] = values[0] return mosaic - @staticmethod def _get_feature_map(self, feature, individual, interpolation): if interpolation is not None: - return self._get_interpolated_feature_map(self, feature, individual, interpolation) + return self._get_interpolated_feature_map(feature, individual, interpolation) else: - return self._get_regular_feature_map(self, feature, individual) + return self._get_regular_feature_map(feature, individual) - @staticmethod def _get_regular_feature_map(self, feature, individual): feature_ndarray = np.full((self.n_cols, self.n_rows), np.nan) for node in self.graphs[individual].nodes(): feature_ndarray[node[1]][node[0]] = (self.graphs[individual]).nodes[node][feature] return feature_ndarray - @staticmethod def _get_interpolated_feature_map(self, feature, individual, interpolation): - feature_ndarray = self._get_regular_feature_map(self, feature, individual) + feature_ndarray = self._get_regular_feature_map(feature, individual) individual_trajectory = self.trajectory[self.trajectory["groupby_col"] == individual] geom = individual_trajectory["geometry"] idxs_dict = {} @@ -366,22 +358,10 @@ def _get_interpolated_feature_map(self, feature, individual, interpolation): elif interpolation == "min": feature_ndarray[key[0], key[1]] = np.min(value) else: - raise InterpolationError("Interpolation type not supported by EcoGraph") + raise NotImplementedError("Interpolation type not supported by EcoGraph") return feature_ndarray -class InterpolationError(Exception): - pass - - -class IndividualNameError(Exception): - pass - - -class FeatureNameError(Exception): - pass - - def get_feature_gdf(input_path): """ Convert a GeoTIFF feature map into a GeoDataFrame diff --git a/ecoscope/analysis/proximity.py b/ecoscope/analysis/proximity.py index caecd5b9..d72690ea 100644 --- a/ecoscope/analysis/proximity.py +++ b/ecoscope/analysis/proximity.py @@ -59,5 +59,5 @@ def analysis(traj): proximity_events.append(pr) - trajectory.groupby("groupby_col").apply(analysis) + trajectory.groupby("groupby_col")[trajectory.columns].apply(analysis, include_groups=False) return pd.concat(proximity_events).reset_index(drop=True) diff --git a/ecoscope/base/base.py b/ecoscope/base/base.py index a171066c..3cb863cd 100644 --- a/ecoscope/base/base.py +++ b/ecoscope/base/base.py @@ -273,13 +273,13 @@ def apply_reloc_filter(self, fix_filter=None, inplace=False): frame.to_crs(4326) if isinstance(fix_filter, RelocsSpeedFilter): frame._update_inplace( - frame.groupby("groupby_col") + frame.groupby("groupby_col")[frame.columns] .apply(self._apply_speedfilter, fix_filter=fix_filter) .droplevel(["groupby_col"]) ) elif isinstance(fix_filter, RelocsDistFilter): frame._update_inplace( - frame.groupby("groupby_col") + frame.groupby("groupby_col")[frame.columns] .apply(self._apply_distfilter, fix_filter=fix_filter) .droplevel(["groupby_col"]) ) @@ -354,7 +354,7 @@ def from_relocations(cls, gdf, *args, **kwargs): gdf = EcoDataFrame(gdf) crs = gdf.crs gdf.to_crs(4326, inplace=True) - gdf = gdf.groupby("groupby_col").apply(cls._create_multitraj).droplevel(level=0) + gdf = gdf.groupby("groupby_col")[gdf.columns].apply(cls._create_multitraj).droplevel(level=0) gdf.to_crs(crs, inplace=True) gdf.sort_values("segment_start", inplace=True) return cls(gdf, *args, **kwargs) @@ -527,7 +527,11 @@ def turn_angle(traj): return ((traj["heading"].diff() + 540) % 360 - 180)[traj["segment_end"].shift(1) == traj["segment_start"]] uniq = self.groupby_col.nunique() - angles = self.groupby("groupby_col").apply(turn_angle).droplevel(0) if uniq > 1 else turn_angle(self) + angles = ( + self.groupby("groupby_col")[self.columns].apply(turn_angle, include_groups=False).droplevel(0) + if uniq > 1 + else turn_angle(self) + ) return angles.rename("turn_angle").reindex(self.index) @@ -570,7 +574,9 @@ def f(traj): crs=traj.crs, ) - return Relocations.from_gdf(self.groupby("groupby_col").apply(f).reset_index(level=0)) + return Relocations.from_gdf( + self.groupby("groupby_col")[self.columns].apply(f, include_groups=False).reset_index(level=0) + ) def to_relocations(self): """ @@ -595,7 +601,9 @@ def f(traj): .sort_values("fixtime") ) - return Relocations.from_gdf(self.groupby("groupby_col").apply(f).reset_index(drop=True)) + return Relocations.from_gdf( + self.groupby("groupby_col")[self.columns].apply(f, include_groups=False).reset_index(drop=True) + ) def downsample(self, freq, tolerance="0S", interpolation=False): """ @@ -651,7 +659,8 @@ def f(relocs_ind): relocs_ind.drop(relocs_ind.loc[relocs_ind["extra__burst"] == -1].index, inplace=True) return relocs_ind - return Relocations(self.to_relocations().groupby("groupby_col").apply(f).reset_index(drop=True)) + relocs = self.to_relocations() + return relocs.groupby("groupby_col")[relocs.columns].apply(f).reset_index(drop=True) @staticmethod def _straighttrack_properties(df: gpd.GeoDataFrame): diff --git a/ecoscope/base/utils.py b/ecoscope/base/utils.py index 96dcc54a..cbddfdc8 100644 --- a/ecoscope/base/utils.py +++ b/ecoscope/base/utils.py @@ -203,11 +203,12 @@ def create_modis_interval_index(start, intervals, overlap=pd.Timedelta(0), close """ - start = start + ModisBegin() + modis = ModisBegin() + start = modis.apply(start) left = [start] for i in range(1, intervals): - start = start + ModisBegin() + start = modis.apply(start) left.append(start - i * overlap) left = pd.DatetimeIndex(left) diff --git a/ecoscope/io/raster.py b/ecoscope/io/raster.py index af0c3892..7ee4fc39 100644 --- a/ecoscope/io/raster.py +++ b/ecoscope/io/raster.py @@ -169,11 +169,13 @@ def reduce_region(gdf, raster_path_list, reduce_func): for raster_path in tqdm.tqdm(raster_path_list): d[raster_path] = {} with rio.open(raster_path) as src: - for i, shp in gdf.geometry.to_crs(src.crs).items(): + for feat in gdf.to_crs(src.crs).iterfeatures(): try: - d[raster_path][i] = reduce_func(rio.mask.mask(src, [shp], filled=False)[0].compressed()) + d[raster_path][feat["id"]] = reduce_func( + rio.mask.mask(src, [feat["geometry"]], filled=False)[0].compressed() + ) except ValueError as e: - logger.exception(raster_path, i, e) + logger.exception(raster_path, feat["id"], e) return pd.DataFrame(d) diff --git a/notebooks/02. Relocations & Trajectories/Relocations_and_Trajectories.ipynb b/notebooks/02. Relocations & Trajectories/Relocations_and_Trajectories.ipynb index d2286c3c..be666c5c 100644 --- a/notebooks/02. Relocations & Trajectories/Relocations_and_Trajectories.ipynb +++ b/notebooks/02. Relocations & Trajectories/Relocations_and_Trajectories.ipynb @@ -94,7 +94,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Read in sample data in MovBank format" + "### Read in sample data in MoveBank format" ] }, { @@ -104,11 +104,11 @@ "outputs": [], "source": [ "ecoscope.io.download_file(\n", - " f\"{ECOSCOPE_RAW}/tests/sample_data/vector/movbank_data.csv\",\n", - " os.path.join(output_dir, \"movbank_data.csv\"),\n", + " f\"{ECOSCOPE_RAW}/tests/sample_data/vector/movebank_data.csv\",\n", + " os.path.join(output_dir, \"movebank_data.csv\"),\n", ")\n", "\n", - "data = pd.read_csv(os.path.join(output_dir, \"movbank_data.csv\"))" + "data = pd.read_csv(os.path.join(output_dir, \"movebank_data.csv\"))" ] }, { diff --git a/notebooks/03. Home Range & Movescape/Elliptical Time Density (ETD).ipynb b/notebooks/03. Home Range & Movescape/Elliptical Time Density (ETD).ipynb index a583136a..50dc6d7d 100644 --- a/notebooks/03. Home Range & Movescape/Elliptical Time Density (ETD).ipynb +++ b/notebooks/03. Home Range & Movescape/Elliptical Time Density (ETD).ipynb @@ -88,11 +88,11 @@ "outputs": [], "source": [ "ecoscope.io.download_file(\n", - " f\"{ECOSCOPE_RAW}/tests/sample_data/vector/movbank_data.csv\",\n", - " os.path.join(output_dir, \"movbank_data.csv\"),\n", + " f\"{ECOSCOPE_RAW}/tests/sample_data/vector/movebank_data.csv\",\n", + " os.path.join(output_dir, \"movebank_data.csv\"),\n", ")\n", "\n", - "df = pd.read_csv(os.path.join(output_dir, \"movbank_data.csv\"), index_col=0)\n", + "df = pd.read_csv(os.path.join(output_dir, \"movebank_data.csv\"), index_col=0)\n", "gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(df[\"location-long\"], df[\"location-lat\"]), crs=4326)\n", "\n", "relocs = ecoscope.base.Relocations.from_gdf(gdf, groupby_col=\"individual-local-identifier\", time_col=\"timestamp\")\n", diff --git a/notebooks/04. EcoMap & EcoPlot/EcoMap.ipynb b/notebooks/04. EcoMap & EcoPlot/EcoMap.ipynb index e57c4ddf..4a78a0b2 100644 --- a/notebooks/04. EcoMap & EcoPlot/EcoMap.ipynb +++ b/notebooks/04. EcoMap & EcoPlot/EcoMap.ipynb @@ -190,7 +190,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### MovBank Relocations" + "### MoveBank Relocations" ] }, { @@ -200,13 +200,13 @@ "outputs": [], "source": [ "ecoscope.io.download_file(\n", - " f\"{ECOSCOPE_RAW}/tests/sample_data/vector/movbank_data.csv\",\n", - " os.path.join(output_dir, \"movbank_data.csv\"),\n", + " f\"{ECOSCOPE_RAW}/tests/sample_data/vector/movebank_data.csv\",\n", + " os.path.join(output_dir, \"movebank_data.csv\"),\n", ")\n", "\n", - "df = pd.read_csv(os.path.join(output_dir, \"movbank_data.csv\"), index_col=0)\n", + "df = pd.read_csv(os.path.join(output_dir, \"movebank_data.csv\"), index_col=0)\n", "gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(x=df[\"location-long\"], y=df[\"location-lat\"]), crs=4326)\n", - "movbank_relocations_gdf = ecoscope.base.Relocations.from_gdf(\n", + "movebank_relocations_gdf = ecoscope.base.Relocations.from_gdf(\n", " gdf, groupby_col=\"individual-local-identifier\", time_col=\"timestamp\"\n", ")\n", "\n", @@ -217,8 +217,8 @@ " max_y=18,\n", " filter_point_coords=[[180, 90], [0, 0]],\n", ")\n", - "movbank_relocations_gdf.apply_reloc_filter(pnts_filter, inplace=True)\n", - "movbank_relocations_gdf.remove_filtered(inplace=True)" + "movebank_relocations_gdf.apply_reloc_filter(pnts_filter, inplace=True)\n", + "movebank_relocations_gdf.remove_filtered(inplace=True)" ] }, { @@ -354,11 +354,11 @@ "metadata": {}, "outputs": [], "source": [ - "movbank_relocations_gdf[\"is_night\"] = ecoscope.analysis.astronomy.is_night(\n", - " movbank_relocations_gdf.geometry, movbank_relocations_gdf.fixtime\n", + "movebank_relocations_gdf[\"is_night\"] = ecoscope.analysis.astronomy.is_night(\n", + " movebank_relocations_gdf.geometry, movebank_relocations_gdf.fixtime\n", ")\n", "\n", - "movbank_relocations_gdf[[\"groupby_col\", \"fixtime\", \"geometry\", \"is_night\"]]" + "movebank_relocations_gdf[[\"groupby_col\", \"fixtime\", \"geometry\", \"is_night\"]]" ] }, { @@ -367,12 +367,12 @@ "metadata": {}, "outputs": [], "source": [ - "colors = [\"#292965\" if is_night else \"#e7a553\" for is_night in movbank_relocations_gdf.is_night]\n", + "colors = [\"#292965\" if is_night else \"#e7a553\" for is_night in movebank_relocations_gdf.is_night]\n", "\n", - "m = movbank_relocations_gdf[[\"groupby_col\", \"fixtime\", \"geometry\", \"is_night\"]].explore(\n", + "m = movebank_relocations_gdf[[\"groupby_col\", \"fixtime\", \"geometry\", \"is_night\"]].explore(\n", " m=ecoscope.mapping.EcoMap(width=800, height=600), color=colors\n", ")\n", - "m.zoom_to_gdf(movbank_relocations_gdf)\n", + "m.zoom_to_gdf(movebank_relocations_gdf)\n", "\n", "m.add_legend(\n", " title=\"Is Night\", legend_dict={True: \"292965\", False: \"e7a553\"}, box_position={\"bottom\": \"20px\", \"right\": \"20px\"}\n", @@ -396,8 +396,8 @@ "metadata": {}, "outputs": [], "source": [ - "movbank_trajectory_gdf = ecoscope.base.Trajectory.from_relocations(movbank_relocations_gdf)\n", - "movbank_traj_seg_filter = ecoscope.base.TrajSegFilter(\n", + "movebank_trajectory_gdf = ecoscope.base.Trajectory.from_relocations(movebank_relocations_gdf)\n", + "movebank_traj_seg_filter = ecoscope.base.TrajSegFilter(\n", " min_length_meters=0.0,\n", " max_length_meters=float(\"inf\"),\n", " min_time_secs=0.0,\n", @@ -405,7 +405,7 @@ " min_speed_kmhr=0.0,\n", " max_speed_kmhr=10.0,\n", ")\n", - "movbank_trajectory_gdf.apply_traj_filter(movbank_traj_seg_filter, inplace=True)" + "movebank_trajectory_gdf.apply_traj_filter(movebank_traj_seg_filter, inplace=True)" ] }, { @@ -414,12 +414,12 @@ "metadata": {}, "outputs": [], "source": [ - "colors = [\"#292965\" if is_night else \"#e7a553\" for is_night in movbank_trajectory_gdf.extra__is_night]\n", + "colors = [\"#292965\" if is_night else \"#e7a553\" for is_night in movebank_trajectory_gdf.extra__is_night]\n", "\n", - "m = movbank_trajectory_gdf[[\"groupby_col\", \"segment_start\", \"segment_end\", \"geometry\", \"extra__is_night\"]].explore(\n", + "m = movebank_trajectory_gdf[[\"groupby_col\", \"segment_start\", \"segment_end\", \"geometry\", \"extra__is_night\"]].explore(\n", " color=colors, m=ecoscope.mapping.EcoMap(width=800, height=600)\n", ")\n", - "m.zoom_to_gdf(movbank_trajectory_gdf)\n", + "m.zoom_to_gdf(movebank_trajectory_gdf)\n", "\n", "m.add_legend(\n", " title=\"Is Night\", legend_dict={True: \"292965\", False: \"e7a553\"}, box_position={\"bottom\": \"20px\", \"right\": \"20px\"}\n", @@ -444,10 +444,10 @@ "outputs": [], "source": [ "m = ecoscope.mapping.EcoMap()\n", - "m.add_speedmap(trajectory=movbank_trajectory_gdf, classification_method=\"equal_interval\", num_classes=6, bins=None)\n", + "m.add_speedmap(trajectory=movebank_trajectory_gdf, classification_method=\"equal_interval\", num_classes=6, bins=None)\n", "m.add_north_arrow(position=\"topright\", scale=1, angle=0)\n", "m.add_title(title=\"Elephant Speed Map\", align=\"center\", font_size=\"18px\")\n", - "m.zoom_to_gdf(movbank_trajectory_gdf)\n", + "m.zoom_to_gdf(movebank_trajectory_gdf)\n", "\n", "m" ] @@ -492,7 +492,7 @@ " return output_path\n", "\n", "\n", - "etd = movbank_trajectory_gdf.groupby(\"groupby_col\").apply(f)" + "etd = movebank_trajectory_gdf.groupby(\"groupby_col\").apply(f)" ] }, { diff --git a/tests/conftest.py b/tests/conftest.py index 68e73624..4be4e5c8 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -15,6 +15,8 @@ def pytest_configure(config): ecoscope.init() + os.makedirs("tests/outputs", exist_ok=True) + try: EE_ACCOUNT = os.getenv("EE_ACCOUNT") EE_PRIVATE_KEY_DATA = os.getenv("EE_PRIVATE_KEY_DATA") @@ -75,8 +77,8 @@ def er_events_io(): @pytest.fixture -def movbank_relocations(): - df = pd.read_feather("tests/sample_data/vector/movbank_data.feather") +def movebank_relocations(): + df = pd.read_feather("tests/sample_data/vector/movebank_data.feather") gdf = gpd.GeoDataFrame( df, geometry=gpd.points_from_xy(df.pop("location-long"), 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ee.ImageCollection("MODIS/MCD43A4_006_NDVI").select("NDVI") # Daily NDVI images @@ -93,8 +93,8 @@ def test_label_gdf_with_temporal_image_collection_by_features_relocations(movban assert results["NDVI"].explode().mean() > 0 -def test_label_gdf_with_img(movbank_relocations): - tmp_gdf = movbank_relocations[["geometry"]] +def test_label_gdf_with_img(movebank_relocations): + tmp_gdf = movebank_relocations[["geometry"]] tmp_gdf = tmp_gdf[0:1000] img = ee.Image("USGS/SRTMGL1_003").select("elevation") @@ -115,8 +115,8 @@ def test_label_gdf_with_img(movbank_relocations): # a subset to ensure we're checking exact match and nearest cases # includes 3 timestamps, midnight, am, pm @pytest.fixture -def movbank_relocations_fixed_subset(movbank_relocations): - return movbank_relocations.loc[329730794:329730795]._append(movbank_relocations.loc[329730810]) +def movebank_relocations_fixed_subset(movebank_relocations): + return movebank_relocations.loc[329730794:329730795]._append(movebank_relocations.loc[329730810]) @pytest.mark.parametrize( @@ -136,9 +136,9 @@ def movbank_relocations_fixed_subset(movbank_relocations): ), ], ) -def test_match_gdf_to_img_coll_ids_by_image_count(movbank_relocations_fixed_subset, n_before, n_after, output_list): +def test_match_gdf_to_img_coll_ids_by_image_count(movebank_relocations_fixed_subset, n_before, n_after, output_list): results = ecoscope.io.eetools._match_gdf_to_img_coll_ids( - gdf=movbank_relocations_fixed_subset, + gdf=movebank_relocations_fixed_subset, time_col="fixtime", img_coll=ee.ImageCollection("MODIS/MCD43A4_006_NDVI").select("NDVI"), output_col_name="img_ids", @@ -172,9 +172,9 @@ def test_match_gdf_to_img_coll_ids_by_image_count(movbank_relocations_fixed_subs ), ], ) -def test_match_gdf_to_img_coll_ids_by_day(movbank_relocations_fixed_subset, n_before, n_after, output_list): +def test_match_gdf_to_img_coll_ids_by_day(movebank_relocations_fixed_subset, n_before, n_after, output_list): output = ecoscope.io.eetools._match_gdf_to_img_coll_ids( - gdf=movbank_relocations_fixed_subset, + gdf=movebank_relocations_fixed_subset, time_col="fixtime", img_coll=ee.ImageCollection("MODIS/MCD43A4_006_NDVI").select("NDVI"), output_col_name="img_ids", diff --git a/tests/test_immobility.py b/tests/test_immobility.py index afb45207..2e1b4fcc 100644 --- a/tests/test_immobility.py +++ b/tests/test_immobility.py @@ -4,13 +4,13 @@ from ecoscope.analysis import immobility -def test_immobility(movbank_relocations): - movbank_relocations = movbank_relocations.loc[movbank_relocations.groupby_col == "Salif Keita"][:100] +def test_immobility(movebank_relocations): + movebank_relocations = movebank_relocations.loc[movebank_relocations.groupby_col == "Salif Keita"][:100] immobility_profile = immobility.ImmobilityProfile( threshold_time=130, threshold_probability=0.5, threshold_radius=1000 ) result = immobility.Immobility.calculate_immobility( - immobility_profile=immobility_profile, relocs=movbank_relocations + immobility_profile=immobility_profile, relocs=movebank_relocations ) expected_result = { "probability_value": 0.83, diff --git a/tests/test_io_utils.py b/tests/test_io_utils.py index ba71c3b4..2ca0123b 100644 --- a/tests/test_io_utils.py +++ b/tests/test_io_utils.py @@ -11,7 +11,7 @@ def test_download_file_github_csv(): ECOSCOPE_RAW = "https://raw.githubusercontent.com/wildlife-dynamics/ecoscope/master" output_dir = "tests/test_output" ecoscope.io.download_file( - f"{ECOSCOPE_RAW}/tests/sample_data/vector/movbank_data.csv", + f"{ECOSCOPE_RAW}/tests/sample_data/vector/movebank_data.csv", os.path.join(output_dir, "download_data.csv"), overwrite_existing=True, ) @@ -50,6 +50,7 @@ def test_download_file_gdrive_zip(): "https://drive.google.com/uc?export=download&id=1YNQ6FBtlTAxmo8vmK59oTPBhAltI3kfK", output_dir, overwrite_existing=True, + unzip=True, ) data = pd.read_csv(os.path.join(output_dir, "movbank_data.csv")) diff 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z!KDy7_>!45(+={X+{qJ4~VR!ATnHy=vBIm%S_86$I>t}rv_*UXwV<3#FBs7voI&_M-Cl}0UK z-MVz|(o;c^Fx_Qha6IP?#@|VY*6}<`hZvbmx&DU#u$~#N= Date: Fri, 17 May 2024 22:57:39 +0800 Subject: [PATCH 7/7] Implement classifications to continuous data (#151) --- ecoscope/analysis/__init__.py | 2 ++ ecoscope/analysis/classifier.py | 39 +++++++++++++++++++++++++++++++ tests/test_classifier.py | 41 +++++++++++++++++++++++++++++++++ 3 files changed, 82 insertions(+) create mode 100644 ecoscope/analysis/classifier.py create mode 100644 tests/test_classifier.py diff --git a/ecoscope/analysis/__init__.py b/ecoscope/analysis/__init__.py index 46ca082e..21ba0244 100644 --- a/ecoscope/analysis/__init__.py +++ b/ecoscope/analysis/__init__.py @@ -1,4 +1,5 @@ from ecoscope.analysis import UD, astronomy, seasons +from ecoscope.analysis.classifier import apply_classification from ecoscope.analysis.ecograph import Ecograph, get_feature_gdf from ecoscope.analysis.percentile import get_percentile_area from ecoscope.analysis.speed import SpeedDataFrame @@ -11,4 +12,5 @@ "get_feature_gdf", "get_percentile_area", "seasons", + "apply_classification", ] diff --git a/ecoscope/analysis/classifier.py b/ecoscope/analysis/classifier.py new file mode 100644 index 00000000..51cf84ff --- /dev/null +++ b/ecoscope/analysis/classifier.py @@ -0,0 +1,39 @@ +import mapclassify + +classification_methods = { + "equal_interval": mapclassify.EqualInterval, + "natural_breaks": mapclassify.NaturalBreaks, + "quantile": mapclassify.Quantiles, + "std_mean": mapclassify.StdMean, + "max_breaks": mapclassify.MaximumBreaks, + "fisher_jenks": mapclassify.FisherJenks, +} + + +# pass in a series and output the series +def apply_classification(x, labels=None, scheme="natural_breaks", **kwargs): + """ + Classifies the data in a GeoDataFrame column using specified classification scheme. + + Args: + y : An array containing the data to classify. + labels (str): labels of bins, use bin edges if labels==None. + scheme (str): Classification scheme to use [equal_interval, natural_breaks, quantile, std_mean, max_breaks, + fisher_jenks] + + **kwargs: Additional keyword arguments specific to the classification scheme. + + Returns: + result: an array of corresponding labels of the input data. + """ + + classifier_class = classification_methods.get(scheme) + + if not classifier_class: + raise ValueError(f"Invalid classification scheme. Choose from: {list(classification_methods.keys())}") + + classifier = classifier_class(x, **kwargs) + if labels is None: + labels = classifier.bins + assert len(labels) == len(classifier.bins) + return [labels[i] for i in classifier.yb] diff --git a/tests/test_classifier.py b/tests/test_classifier.py new file mode 100644 index 00000000..44b01d48 --- /dev/null +++ b/tests/test_classifier.py @@ -0,0 +1,41 @@ +import pytest + +import ecoscope + + +@pytest.mark.parametrize( + "scheme,kwargs,expected", + [ + ("equal_interval", {"k": 2}, [3, 3, 3, 5, 5]), + ("quantile", {"k": 2}, [3, 3, 3, 5, 5]), + ( + "std_mean", + {"multiples": [-2, -1, 1, 2]}, + [1.4188611699158102, 4.58113883008419, 4.58113883008419, 4.58113883008419, 6.16227766016838], + ), + ("max_breaks", {"k": 4}, [2.5, 2.5, 3.5, 4.5, 5.0]), + ("fisher_jenks", {"k": 5}, [1.0, 2.0, 3.0, 4.0, 5.0]), + ], +) +def test_classify_data(scheme, kwargs, expected): + y = [1, 2, 3, 4, 5] + result = ecoscope.analysis.apply_classification(y, scheme=scheme, **kwargs) + assert result == expected, f"Failed on scheme {scheme}" + + +def test_classify_with_labels(): + y = [1, 2, 3, 4, 5] + result = ecoscope.analysis.apply_classification(y, labels=["1", "2"], scheme="equal_interval", k=2) + assert result == ["1", "1", "1", "2", "2"] + + +def test_classify_with_invalid_labels(): + y = [1, 2, 3, 4, 5] + with pytest.raises(AssertionError): + ecoscope.analysis.apply_classification(y, labels=[0], scheme="std_mean") + + +def test_classify_with_invalid_scheme(): + y = [1, 2, 3, 4, 5] + with pytest.raises(ValueError): + ecoscope.analysis.apply_classification(y, scheme="InvalidScheme")