replace np.float with float (#162)

* replace np.float with float

* Merge minimamba changes into this PR

* Fix np.float occurences in datasets.py

* Update test_utils.py

.github/workflows/ci.yaml

@@ -24,32 +24,24 @@ jobs:
  python-version: ["3.9", "3.10"]
  steps:
  - uses: actions/checkout@v3
- - name: Cache conda
- uses: actions/cache@v3
- env:
- # Increase this value to reset cache if ci/environment.yml has not changed
- CACHE_NUMBER: 0
+ - name: Create conda environment
+ uses: mamba-org/provision-with-micromamba@main
  with:
- path: ~/conda_pkgs_dir
- key: ${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-${{ hashFiles('ci/environment.yml') }}
- - uses: conda-incubator/setup-miniconda@v2
- with:
- mamba-version: "*"
- channels: conda-forge, defaults
- activate-environment: test_env_xarrayutils # Defined in ci/environment*.yml
- auto-update-conda: false
- python-version: ${{ matrix.python-version }}
+ cache-downloads: true
+ cache-env: true
+ micromamba-version: 'latest'
  environment-file: ci/environment.yml
- use-only-tar-bz2: true # IMPORTANT: This needs to be set for caching to work properly!
- - name: Set up conda environment
+ extra-specs: |
+ python=${{ matrix.python-version }}
+ - name: Install xarrayutils
  run: |
- python -m pip install -e .
+ python -m pip install -e . --no-deps
  conda list
  - name: Run Tests
  run: |
  pytest -n auto --cov=./ --cov-report=xml
  - name: Upload code coverage to Codecov
- uses: codecov/[email protected].1
+ uses: codecov/[email protected].3
  with:
  file: ./coverage.xml
  flags: unittests
@@ -63,25 +55,31 @@ jobs:
  run:
  shell: bash -l {0}
  steps:
- - uses: actions/checkout@v3
- - name: Cache conda
- uses: actions/cache@v3
- env:
- # Increase this value to reset cache if ci/environment-upstream-dev.yml has not changed
- CACHE_NUMBER: 0
- with:
- path: ~/conda_pkgs_dir
- key: ${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-${{ hashFiles('ci/environment-upstream-dev.yml') }}
- - uses: conda-incubator/setup-miniconda@v2
- with:
- activate-environment: test_env_xarrayutils # Defined in ci/environment-upstream-dev.yml
- auto-update-conda: false
- environment-file: ci/environment-upstream-dev.yml
- use-only-tar-bz2: true # IMPORTANT: This needs to be set for caching to work properly!
- - name: Set up conda environment
- run: |
- python -m pip install -e .
- conda list
- - name: Run Tests
- run: |
- pytest -n auto
+ - uses: actions/checkout@v3
+ - name: Create conda environment
+ uses: mamba-org/provision-with-micromamba@main
+ with:
+ cache-downloads: true
+ cache-env: true
+ micromamba-version: 'latest'
+ environment-file: ci/environment-upstream-dev.yml
+ extra-specs: |
+ python=3.10
+ - name: Install xarrayutils
+ run: |
+ python -m pip install -e . --no-deps
+ conda list
+ - name: Run Tests
+ run: |
+ pytest -n auto --cov=./ --cov-report=xml
+ - name: Upload code coverage to Codecov
+ uses: codecov/[email protected]
+ with:
+ file: ./coverage.xml
+ flags: unittests
+ env_vars: OS,PYTHON
+ name: codecov-umbrella
+ fail_ci_if_error: false
+ - name: Run Tests
+ run: |
+ pytest -n auto

xarrayutils/test/datasets.py

@@ -13,10 +13,10 @@
  [2, 2, 2, 4, 4, 4, 6, 6],
  [2, 2, 2, 4, 4, 4, 6, 6],
  ],
- dtype=np.float,
+ dtype=float,
 )
 
-ones_2d = np.ones([6, 8], dtype=np.float)
+ones_2d = np.ones([6, 8], dtype=float)
 
 ones_2d_nan = ones_2d.copy()
 ones_2d_nan[2, 2] = np.nan

xarrayutils/test/test_utils.py

@@ -176,11 +176,8 @@ def _linregress_ufunc(a: np.ndarray, b: np.ndarray, nanmask: bool = False):
  ({"x": -1, "y": 1}, "x"),
  ],
 )
-# @pytest.mark.parametrize("variant", range(3))
 @pytest.mark.parametrize("variant", [0])
-# @pytest.mark.parametrize("dtype", [None, np.float])
 @pytest.mark.parametrize("dtype", [None])
-# @pytest.mark.parametrize("nans", [False, True])
 @pytest.mark.parametrize("nans", [True, "all"])
 @pytest.mark.parametrize(
  "ni, parameter", enumerate(["slope", "intercept", "r_value", "p_value", "std_err"])
@@ -599,7 +596,7 @@ def test_aggregate_input_da(dataarray_2d_example):
 
 
 def test_aggregate_w_nanmean(dataarray_2d_ones, dataarray_2d_ones_nan):
- expected_result = np.array([[1, 1], [1, 1]], dtype=np.float)
+ expected_result = np.array([[1, 1], [1, 1]], dtype=float)
  blocks = [("i", 3), ("j", 3)]
 
  data = dataarray_2d_ones_nan

xarrayutils/utils.py

@@ -109,7 +109,7 @@ def linear_trend(obj, dim):
  trend is in units/yr.
  """
  x = xr.DataArray(
- np.arange(len(obj[dim])).astype(np.float), dims=dim, coords={dim: obj[dim]}
+ np.arange(len(obj[dim])).astype(float), dims=dim, coords={dim: obj[dim]}
  )
  trend = xr_linregress(x, obj, dim=dim)
  return trend