Merge pull request #157 from tobac-project/dev

Merge `dev` into `main` for v1.3.2

.coveragerc

@@ -0,0 +1,3 @@
+[run]
+source=tobac
+omit = tobac/tests/*

.github/workflows/codecov-CI.yml

@@ -0,0 +1,33 @@
+name: Codecov CI
+
+on: [push, pull_request]
+
+jobs:
+  run:
+    runs-on: ubuntu-latest
+    env:
+      OS: ubuntu-latest
+      PYTHON: '3.9'
+    steps:
+    - uses: actions/checkout@v2
+    # Similar to MetPy install-conda action
+    - name: Set up conda
+      uses: conda-incubator/setup-miniconda@v2
+      with:
+        miniforge-version: latest
+        miniforge-variant: mambaforge
+        channel-priority: strict
+        channels: conda-forge
+        show-channel-urls: true
+        use-only-tar-bz2: true
+
+    - name: Install dependencies and generate report
+      shell: bash -l {0}
+      run: mamba install --quiet --yes --file conda-requirements.txt coverage pytest-cov &&
+           python -m coverage run -m pytest --cov=./ --cov-report=xml
+    - name: Upload Coverage to Codecov
+      uses: codecov/codecov-action@v2
+      with: 
+        fail_ci_if_error: true
+        flags: unittests
+

CHANGELOG.md

@@ -1,5 +1,18 @@
 ### Tobac Changelog
 
+_**Version 1.3.2:**_
+
+**Bug fixes**
+
+- Fixed a bug with Feature Detection that caused it to fail when using `weighted_abs` position [#148](https://github.com/tobac-project/tobac/pull/148)
+- Fixed a bug where adaptive_search within `linking_trackpy` was not working correctly [#140](https://github.com/tobac-project/tobac/pull/140)
+
+**Repository enhancements**
+
+- Added automatic code coverage reports [#124](https://github.com/tobac-project/tobac/pull/124)
+- Added automatic building of readthedocs documentation on pull requests
+
+
 _**Version 1.3.1:**_
 
 **Enhancements**

setup.py

@@ -2,7 +2,7 @@
 
 setup(
     name="tobac",
-    version="1.3.1",
+    version="1.3.2",
     description="Tracking and object-based analysis of clouds",
     url="http://github.com/tobac-project/tobac",
     author=[

tobac/feature_detection.py

@@ -90,7 +90,7 @@ def feature_position(
 
     elif position_threshold == "weighted_abs":
         # get position as centre of identified region, weighted by absolute values if the field:
-        weights = abs(track_data[region_small])
+        weights = abs(track_data_region[region_small])
         if sum(weights) == 0:
             weights = None
         hdim1_index = np.average(hdim1_indices, weights=weights)

tobac/tests/Dockerfile-coverage

@@ -0,0 +1,15 @@
+FROM mambaorg/micromamba
+ARG MAMBA_DOCKERFILE_ACTIVATE=1
+
+RUN micromamba install -y -n base -c conda-forge numpy \
+    scipy scikit-image pandas pytables matplotlib iris \
+    cf-units xarray cartopy trackpy numba pytest pip \
+    pytest-cov coverage
+
+COPY . ./
+
+RUN pip install .
+
+RUN coverage run -m pytest --cov-report=xml &&\
+    mv coverage.xml shared
+

tobac/tests/test_feature_detection.py

@@ -1,4 +1,4 @@
-import tobac.testing
+import tobac.testing as tbtest
 import tobac.feature_detection as feat_detect
 import pytest
 
@@ -8,7 +8,6 @@ def test_feature_detection_multithreshold_timestep():
     Tests ```tobac.feature_detection.feature_detection_multithreshold_timestep
     """
     import numpy as np
-    from tobac import testing
     from tobac import feature_detection
 
     # start by building a simple dataset with a single feature and seeing
@@ -26,15 +25,15 @@ def test_feature_detection_multithreshold_timestep():
     test_min_num = 2
 
     test_data = np.zeros(test_dset_size)
-    test_data = testing.make_feature_blob(
+    test_data = tbtest.make_feature_blob(
         test_data,
         test_hdim_1_pt,
         test_hdim_2_pt,
         h1_size=test_hdim_1_sz,
         h2_size=test_hdim_2_sz,
         amplitude=test_amp,
     )
-    test_data_iris = testing.make_dataset_from_arr(test_data, data_type="iris")
+    test_data_iris = tbtest.make_dataset_from_arr(test_data, data_type="iris")
     fd_output = feature_detection.feature_detection_multithreshold_timestep(
         test_data_iris, 0, threshold=test_threshs, n_min_threshold=test_min_num
     )
@@ -44,3 +43,35 @@ def test_feature_detection_multithreshold_timestep():
     # Make sure that the location of the feature is correct
     assert fd_output.iloc[0]["hdim_1"] == pytest.approx(test_hdim_1_pt)
     assert fd_output.iloc[0]["hdim_2"] == pytest.approx(test_hdim_2_pt)
+
+
+@pytest.mark.parametrize(
+    "position_threshold", [("center"), ("extreme"), ("weighted_diff"), ("weighted_abs")]
+)
+def test_feature_detection_position(position_threshold):
+    """
+    Tests to make sure that all feature detection position_thresholds work.
+    """
+    import numpy as np
+
+    test_dset_size = (50, 50)
+
+    test_data = np.zeros(test_dset_size)
+
+    test_data[0:5, 0:5] = 3
+    test_threshs = [
+        1.5,
+    ]
+    test_min_num = 2
+
+    test_data_iris = tbtest.make_dataset_from_arr(test_data, data_type="iris")
+
+    fd_output = feat_detect.feature_detection_multithreshold_timestep(
+        test_data_iris,
+        0,
+        threshold=test_threshs,
+        n_min_threshold=test_min_num,
+        position_threshold=position_threshold,
+    )
+
+    pass

tobac/tracking.py

@@ -89,7 +89,12 @@ def linking_trackpy(
 
     # If subnetwork size given, set maximum subnet size
     if subnetwork_size is not None:
-        tp.linking.Linker.MAX_SUB_NET_SIZE = subnetwork_size
+        # Choose the right parameter depending on the use of adaptive search
+        if adaptive_step is None and adaptive_stop is None:
+            tp.linking.Linker.MAX_SUB_NET_SIZE = subnetwork_size
+        else:
+            tp.linking.Linker.MAX_SUB_NET_SIZE_ADAPTIVE = subnetwork_size
+
     # deep copy to preserve features field:
     features_linking = deepcopy(features)