Merge pull request #353 from freemansw1/add_matrix_testing

Add matrix CI Tests on multiple Python versions and OS versions

.github/workflows/matrix_ci.yml

@@ -0,0 +1,53 @@
+name: Matrix Testing CI
+# this is similar to the pyart CI action
+on: [push, pull_request]
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+# This job installs dependencies and runs tests across a matrix of python and OS versions.
+#Add if: github.repository == 'tobac-project/tobac' to limit runs to tobac repo
+
+jobs:
+  build:
+    name: ${{ matrix.os }}-${{ matrix.python-version }}
+    runs-on: ${{ matrix.os }}-latest
+    if: github.repository == 'tobac-project/tobac'
+    defaults:
+      run:
+        shell: bash -l {0}
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.8", "3.9", "3.10", "3.11"]
+        os: [macos, ubuntu, windows]
+
+    steps:
+      - uses: actions/checkout@v2
+
+      # Install micromamba and dependencies
+      - name: Setup Conda Environment
+        uses: mamba-org/setup-micromamba@v1
+        with:
+          environment-file: environment-ci.yml
+          activate-environment: pyart-dev
+          cache-downloads: true
+          channels: conda-forge
+          channel-priority: strict
+          python-version: ${{ matrix.python-version }}
+
+      - name: Fetch all history for all tags and branches
+        run: |
+           git fetch --prune --unshallow
+
+      - name: Install tobac
+        shell: bash -l {0}
+        run: |
+          python -m pip install -e . --no-deps --force-reinstall
+
+      - name: Run Tests
+        id: run_tests
+        shell: bash -l {0}
+        run: |
+          python -m pytest -v 

dev_requirements.txt

@@ -12,4 +12,4 @@ trackpy
 pre-commit
 black
 pytest
-
+typing_extensions

environment-ci.yml

@@ -0,0 +1,16 @@
+name: pyart-dev
+channels:
+  - conda-forge
+dependencies:
+  - numpy
+  - scipy
+  - scikit-image
+  - scikit-learn
+  - pandas
+  - matplotlib
+  - iris
+  - xarray
+  - cartopy
+  - trackpy
+  - pytest
+  - typing_extensions

example_requirements.txt

@@ -14,4 +14,5 @@ notebook
 pytables
 s3fs
 arm_pyart
-h5netcdf
+h5netcdf
+typing_extensions

tobac/testing.py

@@ -62,7 +62,7 @@ def make_simple_sample_data_2D(data_type="iris"):
             ) * np.exp(-np.power(yy - y_i, 2.0) / (2 * np.power(10e3, 2.0)))
 
     t_start = datetime.datetime(1970, 1, 1, 0, 0)
-    t_points = (t - t_start).astype("timedelta64[ms]").astype(int) / 1000
+    t_points = (t - t_start).astype("timedelta64[ms]").astype(int) // 1000
     t_coord = DimCoord(
         t_points,
         standard_name="time",
@@ -176,7 +176,7 @@ def make_sample_data_2D_3blobs(data_type="iris"):
                 -np.power(xx - x_i, 2.0) / (2 * np.power(10e3, 2.0))
             ) * np.exp(-np.power(yy - y_i, 2.0) / (2 * np.power(10e3, 2.0)))
     t_start = datetime.datetime(1970, 1, 1, 0, 0)
-    t_points = (t - t_start).astype("timedelta64[ms]").astype(int) / 1000
+    t_points = (t - t_start).astype("timedelta64[ms]").astype(int) // 1000
     t_coord = DimCoord(
         t_points,
         standard_name="time",
@@ -286,7 +286,7 @@ def make_sample_data_2D_3blobs_inv(data_type="iris"):
             ) * np.exp(-np.power(yy - y_i, 2.0) / (2 * np.power(10e3, 2.0)))
 
     t_start = datetime.datetime(1970, 1, 1, 0, 0)
-    t_points = (t - t_start).astype("timedelta64[ms]").astype(int) / 1000
+    t_points = (t - t_start).astype("timedelta64[ms]").astype(int) // 1000
 
     t_coord = DimCoord(
         t_points,
@@ -432,7 +432,7 @@ def make_sample_data_3D_3blobs(data_type="iris", invert_xy=False):
             )
 
     t_start = datetime.datetime(1970, 1, 1, 0, 0)
-    t_points = (t - t_start).astype("timedelta64[ms]").astype(int) / 1000
+    t_points = (t - t_start).astype("timedelta64[ms]").astype(int) // 1000
     t_coord = DimCoord(
         t_points,
         standard_name="time",

tobac/utils/general.py

@@ -623,10 +623,16 @@ def combine_feature_dataframes(
     if old_feature_column_name is not None:
         combined_df[old_feature_column_name] = combined_df["feature"]
     # count_per_time = combined_feats.groupby('time')['index'].count()
-    combined_df["frame"] = combined_df["time"].rank(method="dense").astype(int) - 1
+    original_frame_dtype = combined_df["frame"].dtype
+    combined_df["frame"] = (
+        combined_df["time"].rank(method="dense").astype(original_frame_dtype) - 1
+    )
     combined_sorted = combined_df.sort_values(sort_features_by, ignore_index=True)
     if renumber_features:
-        combined_sorted["feature"] = np.arange(1, len(combined_sorted) + 1)
+        original_feature_dtype = combined_df["feature"].dtype
+        combined_sorted["feature"] = np.arange(
+            1, len(combined_sorted) + 1, dtype=original_feature_dtype
+        )
     combined_sorted = combined_sorted.reset_index(drop=True)
     return combined_sorted