Template for unit tests

.github/workflows/main.yml

@@ -14,7 +14,7 @@ on:
 jobs:
   black:
     name: Code Style Compliance
-    runs-on: ubuntu-22.04
+    runs-on: ubuntu-latest
     defaults:
       run:
         shell: bash -l {0}
@@ -35,39 +35,57 @@ jobs:
           tox -e black
 
   testing:
-    name: Smoke Test with Python${{ matrix.python-version }} (${{ matrix.tox-build }})
+    name: Smoke Test with Python${{ matrix.python-version }}
     needs: black
-    runs-on: ubuntu-22.04
+    runs-on: ubuntu-latest
     strategy:
       fail-fast: false
       matrix:
         include:
           - python-version: "3.9"
-            tox-build: "py39"
+#            tox-build: "py39"
           - python-version: "3.10"
-            tox-build: "py310"
+#            tox-build: "py310"
     defaults:
       run:
         shell: bash -l {0}
     steps:
       - uses: actions/checkout@v3
       - name: Setup Conda (Micromamba) with Python ${{ matrix.python-version }}
-        uses: mamba-org/provision-with-micromamba@main
+        uses: mamba-org/setup-micromamba@v1
         with:
           cache-downloads: true
           environment-file: environment.yml
-          extra-specs: |
+          create-args: >-
+            coveralls
             mamba
             python=${{ matrix.python-version }}
             pytest
             pytest-cov
             xdoctest
-      - name: Conda and mamba versions
+      - name: Conda and Mamba versions
         run: |
           mamba --version
+          echo "micromamba $(micromamba --version)"
+      - name: Install xscen
+        run: |
+          pip install --editable .
+      - name: Check versions
+        run: |
+          conda list
+          pip check
       - name: Test with pytest
         run: |
           pytest --cov xscen
+      - name: Report coverage
+        run: |
+          coveralls
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          COVERALLS_FLAG_NAME: run-Python${{ matrix.python-version }}
+          COVERALLS_PARALLEL: true
+          COVERALLS_SERVICE_NAME: github
+
 #      - name: Install tox-current-env
 #        run: |
 #          pip install tox tox-conda tox-current-env
@@ -77,3 +95,17 @@ jobs:
 #        env:
 #          CONDA_EXE: mamba
 #          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+  finish:
+    needs:
+      - testing
+    runs-on: ubuntu-latest
+    container: python:3-slim
+    steps:
+      - name: Coveralls Finished
+        run: |
+          pip install --upgrade coveralls
+          coveralls --finish
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          COVERALLS_SERVICE_NAME: github

HISTORY.rst

@@ -4,15 +4,15 @@ History
 
 v0.7.0 (unreleased)
 -------------------
-Contributors to this version: Gabriel Rondeau-Genesse (:user:`RondeauG`).
+Contributors to this version: Pascal Bourgault (:user:`aulemahal`), Gabriel Rondeau-Genesse (:user:`RondeauG`), Trevor James Smith (:user:`Zeitsperre`).
 
 Announcements
 ^^^^^^^^^^^^^
 * Dropped support for Python 3.8. (:pull:`199`).
 
 New features and enhancements
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-* N/A
+* `xscen` now tracks code coverage using `coveralls <https://coveralls.io/>`_. (:pull:`187`).
 
 Breaking changes
 ^^^^^^^^^^^^^^^^
@@ -21,11 +21,14 @@ Breaking changes
 Bug fixes
 ^^^^^^^^^
 * Fix bug in ``unstack_dates`` with seasonal climatological mean. (:issue:`202`, :pull:`202`).
+* Added NotImplemented errors when trying to call `climatological_mean` and `compute_deltas` with daily data. (:pull:`187`).
 
 Internal changes
 ^^^^^^^^^^^^^^^^
 * Removed the pin on xarray's version. (:issue:`175`, :pull:`199`).
 * Updated ReadTheDocs configuration to prevent ``--eager`` installation of xscen (:pull:`209`).
+* Implemented a template to be used for unit tests. (:pull:`187`).
+* Updated GitHub Actions to remove deprecation warnings. (:pull:`187`).
 
 v0.6.0 (2023-05-04)
 -------------------

README.rst

@@ -2,7 +2,7 @@
 xscen |logo|
 ============
 
-|pypi| |status| |build| |docs| |black| |pre-commit| |versions|
+|pypi| |status| |build| |coverage| |docs| |black| |pre-commit| |versions|
 
 A climate change scenario-building analysis framework, built with Intake-esm catalogs and xarray-based packages such as xclim and xESMF.
 
@@ -32,11 +32,16 @@ This package was created with Cookiecutter_ and the `Ouranosinc/cookiecutter-pyp
 
 .. |logo| image:: https://raw.githubusercontent.com/Ouranosinc/xscen/main/docs/_static/_images/xscen-logo-small.png
         :target: https://github.com/Ouranosinc/xscen
+        :alt: xscen Logo
 
 .. |build| image:: https://github.com/Ouranosinc/xscen/actions/workflows/main.yml/badge.svg
         :target: https://github.com/Ouranosinc/xscen/actions/workflows/main.yml
         :alt: Build Status
 
+.. |coverage| image:: https://coveralls.io/repos/github/Ouranosinc/xscen/badge.svg
+        :target: https://coveralls.io/github/Ouranosinc/xscen
+        :alt: Code Coverage
+
 .. |pypi| image:: https://img.shields.io/pypi/v/xscen.svg
         :target: https://pypi.python.org/pypi/xscen
         :alt: Python Package Index Build

environment-dev.yml

@@ -26,14 +26,15 @@ dependencies:
   - rechunker
   - shapely
   - xarray
-  - xclim >=0.37
+  - xclim >=0.43.0
   - xesmf >=0.7
   - zarr
   # Opt
   - nc-time-axis >=1.3.1
   - pyarrow >=1.0.0  # For lighter in-memory catalogs
   # Dev
   - bumpversion
+  - coveralls
   - ipykernel
   - ipython
   - jupyter_client

environment.yml

@@ -25,7 +25,7 @@ dependencies:
   - rechunker
   - shapely
   - xarray
-  - xclim >=0.37
+  - xclim >=0.43.0
   - xesmf >=0.7
   - zarr
   # Opt

tests/test_aggregate.py

@@ -0,0 +1,140 @@
+import numpy as np
+import pytest
+import xarray as xr
+from xclim.testing.helpers import test_timeseries as timeseries
+
+import xscen as xs
+
+
+class TestClimatologicalMean:
+    def test_daily(self):
+        ds = timeseries(
+            np.tile(np.arange(1, 13), 3),
+            variable="tas",
+            start="2001-01-01",
+            freq="D",
+            as_dataset=True,
+        )
+        with pytest.raises(NotImplementedError):
+            xs.climatological_mean(ds)
+
+    @pytest.mark.parametrize("xrfreq", ["MS", "AS-JAN"])
+    def test_all_default(self, xrfreq):
+        o = 12 if xrfreq == "MS" else 1
+
+        ds = timeseries(
+            np.tile(np.arange(1, o + 1), 30),
+            variable="tas",
+            start="2001-01-01",
+            freq=xrfreq,
+            as_dataset=True,
+        )
+        out = xs.climatological_mean(ds)
+
+        # Test output values
+        np.testing.assert_array_equal(out.tas, np.arange(1, o + 1))
+        assert len(out.time) == (o * len(np.unique(out.horizon.values)))
+        np.testing.assert_array_equal(out.time[0], ds.time[0])
+        assert (out.horizon == "2001-2030").all()
+        # Test metadata
+        assert (
+            out.tas.attrs["description"]
+            == f"30-year mean of {ds.tas.attrs['description']}"
+        )
+        assert (
+            "30-year rolling average (non-centered) with a minimum of 30 years of data"
+            in out.tas.attrs["history"]
+        )
+        assert out.attrs["cat:processing_level"] == "climatology"
+
+    @pytest.mark.parametrize("xrfreq", ["MS", "AS-JAN"])
+    def test_options(self, xrfreq):
+        o = 12 if xrfreq == "MS" else 1
+
+        ds = timeseries(
+            np.tile(np.arange(1, o + 1), 30),
+            variable="tas",
+            start="2001-01-01",
+            freq=xrfreq,
+            as_dataset=True,
+        )
+        out = xs.climatological_mean(ds, window=15, interval=5, to_level="for_testing")
+
+        # Test output values
+        np.testing.assert_array_equal(
+            out.tas,
+            np.tile(np.arange(1, o + 1), len(np.unique(out.horizon.values))),
+        )
+        assert len(out.time) == (o * len(np.unique(out.horizon.values)))
+        np.testing.assert_array_equal(out.time[0], ds.time[0])
+        assert {"2001-2015", "2006-2020", "2011-2025", "2016-2030"}.issubset(
+            out.horizon.values
+        )
+        # Test metadata
+        assert (
+            out.tas.attrs["description"]
+            == f"15-year mean of {ds.tas.attrs['description']}"
+        )
+        assert (
+            "15-year rolling average (non-centered) with a minimum of 15 years of data"
+            in out.tas.attrs["history"]
+        )
+        assert out.attrs["cat:processing_level"] == "for_testing"
+
+    def test_minperiods(self):
+        ds = timeseries(
+            np.tile(np.arange(1, 5), 30),
+            variable="tas",
+            start="2001-03-01",
+            freq="QS-DEC",
+            as_dataset=True,
+        )
+        ds = ds.where(ds["time"].dt.strftime("%Y-%m-%d") != "2030-12-01")
+
+        out = xs.climatological_mean(ds, window=30)
+        assert all(np.isreal(out.tas))
+        assert len(out.time) == 4
+        np.testing.assert_array_equal(out.tas, np.arange(1, 5))
+
+        out = xs.climatological_mean(ds, window=30, min_periods=30)
+        assert np.sum(np.isnan(out.tas)) == 1
+
+        with pytest.raises(ValueError):
+            xs.climatological_mean(ds, window=5, min_periods=6)
+
+    def test_periods(self):
+        ds1 = timeseries(
+            np.tile(np.arange(1, 2), 10),
+            variable="tas",
+            start="2001-01-01",
+            freq="AS-JAN",
+            as_dataset=True,
+        )
+        ds2 = timeseries(
+            np.tile(np.arange(1, 2), 10),
+            variable="tas",
+            start="2021-01-01",
+            freq="AS-JAN",
+            as_dataset=True,
+        )
+
+        ds = xr.concat([ds1, ds2], dim="time")
+        with pytest.raises(ValueError):
+            xs.climatological_mean(ds)
+
+        out = xs.climatological_mean(ds, periods=[["2001", "2010"], ["2021", "2030"]])
+        assert len(out.time) == 2
+        assert {"2001-2010", "2021-2030"}.issubset(out.horizon.values)
+
+    @pytest.mark.parametrize("cal", ["proleptic_gregorian", "noleap", "360_day"])
+    def test_calendars(self, cal):
+        ds = timeseries(
+            np.tile(np.arange(1, 2), 30),
+            variable="tas",
+            start="2001-01-01",
+            freq="AS-JAN",
+            as_dataset=True,
+        )
+
+        out = xs.climatological_mean(ds.convert_calendar(cal, align_on="date"))
+        assert out.time.dt.calendar == cal

xscen/aggregate.py

@@ -73,6 +73,11 @@ def climatological_mean(
         Returns a Dataset of the climatological mean
 
     """
+    if xr.infer_freq(ds.time) == "D":
+        raise NotImplementedError(
+            "xs.climatological_mean does not currently support daily data."
+        )
+
     # there is one less occurrence when a period crosses years
     freq_across_year = [
         f"{f}-{mon}"
@@ -100,9 +105,17 @@ def climatological_mean(
 
     window = window or int(periods[0][1]) - int(periods[0][0]) + 1
 
-    if ds.attrs.get("cat:xrfreq") in freq_across_year and min_periods is None:
+    if (
+        any(
+            x in freq_across_year
+            for x in [ds.attrs.get("cat:xrfreq"), xr.infer_freq(ds.time)]
+        )
+        and min_periods is None
+    ):
         min_periods = window - 1
     min_periods = min_periods or window
+    if min_periods > window:
+        raise ValueError("'min_periods' should be smaller or equal to 'window'")
 
     for period in periods:
         # Rolling average
@@ -174,7 +187,6 @@ def climatological_mean(
             else new_history
         )
         ds_rolling[vv].attrs["history"] = history
-
     if to_level is not None:
         ds_rolling.attrs["cat:processing_level"] = to_level
 
@@ -234,6 +246,11 @@ def compute_deltas(
         )
 
     if "time" in ds:
+        if xr.infer_freq(ds.time) == "D":
+            raise NotImplementedError(
+                "xs.climatological_mean does not currently support daily data."
+            )
+
         # Remove references to 'year' in REF
         ind = pd.MultiIndex.from_arrays(
             [ref.time.dt.month.values, ref.time.dt.day.values], names=["month", "day"]