Fix formatting issues and remove code format checks from cron ci

Author: ejolly

.github/workflows/cron_tests.yml

@@ -0,0 +1,138 @@
+name: (Auto) Tests and Coverage
+
+on:
+  # Run tests every week on sundays
+  schedule:
+    - cron: "0 0 * * 0"
+
+jobs:
+  # Job (1): Run testing in parallel against multiples OSs and Python versions
+  test:
+    if: "!contains(github.event.head_commit.message, 'skip ci')"
+    name: Test
+    runs-on: ${{ matrix.os }}
+    # Determines whether the entire workflow should pass/fail based on parallel jobs
+    continue-on-error: ${{ matrix.ok-fail }}
+    defaults:
+      # This ensures each step gets properly configured bash shell for conda commands to work
+      run:
+        shell: bash -l {0}
+    strategy:
+      fail-fast: false
+      matrix:
+        # OSs to test
+        os: [ubuntu-latest, macos-latest, windows-latest]
+        # Python versions to test
+        python-version: [3.7, 3.8]
+        # By default everything should pass for the workflow to pass
+        ok-fail: [false]
+    #         include:
+    # Rather than include 3.9 in the python versions, do it here so we can ignore failures on mac and windows with 3.9 (they have install issues)
+    #           - os: ubuntu-latest
+    #             python-version: 3.9
+    #             ok-fail: false
+    #           - os: macos-latest
+    #             python-version: 3.9
+    #             ok-fail: true
+    #           - os: windows-latest
+    #             python-version: 3.9
+    #             ok-fail: true
+    steps:
+      # Step up miniconda
+      - name: Download and setup Miniconda
+        uses: conda-incubator/setup-miniconda@v2
+        with:
+          miniconda-version: "latest"
+          python-version: ${{ matrix.python-version }}
+
+      # Check out latest code on github
+      - name: Checkout Code
+        uses: actions/checkout@v2
+
+      # Install common sci-py packages via conda as well as testing packages and requirements
+      # TODO: unpin pandas version when deepdish adds support for 1.2: https://github.com/uchicago-cs/deepdish/issues/45
+      - name: Install Dependencies
+        run: |
+          conda activate test
+          conda env list
+          conda install -y pip pandas">=1.1.0,<1.2" numpy scipy matplotlib seaborn scikit-learn
+          conda install -y -c conda-forge pytest pytest-xdist pytest-sugar coveralls black
+          pip install . -r requirements.txt
+          pip install . -r optional-dependencies.txt
+
+      # Actually run the tests with coverage
+      - name: Run Tests
+        run: |
+          conda activate test
+          conda env list
+          coverage run --source=nltools -m pytest -rs -n auto
+
+      # Send coverage to coveralls.io but waiting on parallelization to finish
+      # Not using the official github action in the marketplace to upload because it requires a .lcov file, which pytest doesn't generate. It's just easier to use the coveralls python library which does the same thing, but works with pytest.
+      - name: Upload Coverage
+        # The coveralls python package has some 422 server issues with uploads from github-actions so try both service providers, for more see:
+        # https://github.com/TheKevJames/coveralls-python/issues/252
+        run: coveralls --service=github || coveralls --service=github-actions
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          COVERALLS_FLAG_NAME: $${{ matrix}}
+          COVERALLS_PARALLEL: true
+
+  # Job (2): Send a finish notification to coveralls.io to integrate coverage across parallel tests
+  coveralls:
+    if: "!contains(github.event.head_commit.message, 'skip ci')"
+    name: Coveralls.io Upload
+    needs: test
+    runs-on: ubuntu-latest
+    container: python:3-slim
+    continue-on-error: true
+    steps:
+      - name: Finished
+        run: |
+          pip3 install --upgrade coveralls
+          coveralls --service=github --finish || coveralls --service=github-actions --finish
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+  # Job (3): Build docs, but don't deploy. This is effectively another layer of testing because of our sphinx-gallery auto-examples
+  docs:
+    if: "!contains(github.event.head_commit.message, 'skip ci')"
+    name: Build docs and auto-examples
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Code
+        uses: actions/checkout@v2
+
+      - name: Setup Python
+        uses: actions/setup-python@v2
+        with:
+          python-version: "3.8"
+
+      - name: Upgrade pip
+        run: |
+          # install pip=>20.1 to use "pip cache dir"
+          python3 -m pip install --upgrade pip
+
+      - name: Setup pip-cache
+        id: pip-cache
+        run: echo "::set-output name=dir::$(pip cache dir)"
+
+      - name: Cache deps
+        uses: actions/cache@v2
+        with:
+          path: ${{ steps.pip-cache.outputs.dir }}
+          key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements.txt') }}
+          restore-keys: |
+            ${{ runner.os }}-pip-
+
+      - name: Install deps
+        run: |
+          python3 -m pip install . -r requirements.txt
+          python3 -m pip install . -r requirements-dev.txt
+          python3 -m pip install . -r optional-dependencies.txt
+
+      - name: Build docs
+        run: |
+          cd docs
+          make clean
+          make html

.github/workflows/tests_and_coverage.yml

@@ -10,9 +10,6 @@ on:
     branches:
       - main
       - master
-  # Run tests every week on sundays
-  schedule:
-    - cron: "0 0 * * 0"
 
 jobs:
   # Job (1): Run testing in parallel against multiples OSs and Python versions

nltools/analysis.py

@@ -311,7 +311,7 @@ def plot(self, plot_method="gaussian", balanced_acc=False, **kwargs):
         return fig
 
     def summary(self):
-        """ Display a formatted summary of ROC analysis. """
+        """Display a formatted summary of ROC analysis."""
 
         print("------------------------")
         print(".:ROC Analysis Summary:.")

nltools/data/adjacency.py

@@ -338,7 +338,7 @@ def _test_is_single_matrix(data):
         return len(data.shape) == 1
 
     def _import_single_data(self, data, matrix_type=None):
-        """ Helper function to import single data matrix."""
+        """Helper function to import single data matrix."""
 
         if isinstance(data, str) or isinstance(data, Path):
             if os.path.isfile(data):
@@ -595,11 +595,11 @@ def median(self, axis=0):
                 return np.nanmedian(self.data, axis=axis)
 
     def shape(self):
-        """ Calculate shape of data. """
+        """Calculate shape of data."""
         return self.data.shape
 
     def square_shape(self):
-        """ Calculate shape of squareform data. """
+        """Calculate shape of squareform data."""
         if self.matrix_type == "empty":
             return np.array([])
         else:
@@ -609,7 +609,7 @@ def square_shape(self):
                 return self[0].squareform().shape
 
     def copy(self):
-        """ Create a copy of Adjacency object."""
+        """Create a copy of Adjacency object."""
         return deepcopy(self)
 
     def append(self, data):
@@ -788,7 +788,7 @@ def r_to_z(self):
         return out
 
     def z_to_r(self):
-        """ Convert z score back into r value for each element of data object"""
+        """Convert z score back into r value for each element of data object"""
 
         out = self.copy()
         out.data = fisher_z_to_r(out.data)

nltools/data/brain_data.py

@@ -384,7 +384,7 @@ def __iter__(self):
             yield self[x]
 
     def shape(self):
-        """ Get images by voxels shape. """
+        """Get images by voxels shape."""
 
         return self.data.shape
 
@@ -463,7 +463,7 @@ def std(self, axis=0):
         return out
 
     def sum(self):
-        """ Sum over voxels."""
+        """Sum over voxels."""
 
         out = deepcopy(self)
         if len(self.shape()) > 1:
@@ -475,7 +475,7 @@ def sum(self):
         return out
 
     def to_nifti(self):
-        """ Convert Brain_Data Instance into Nifti Object """
+        """Convert Brain_Data Instance into Nifti Object"""
 
         return self.nifti_masker.inverse_transform(self.data)
 
@@ -872,7 +872,7 @@ def append(self, data, **kwargs):
         return out
 
     def empty(self, data=True, Y=True, X=True):
-        """ Initalize Brain_Data.data as empty """
+        """Initalize Brain_Data.data as empty"""
 
         tmp = deepcopy(self)
         if data:
@@ -884,7 +884,7 @@ def empty(self, data=True, Y=True, X=True):
         return tmp
 
     def isempty(self):
-        """ Check if Brain_Data.data is empty """
+        """Check if Brain_Data.data is empty"""
 
         if isinstance(self.data, np.ndarray):
             boolean = False if self.data.size else True
@@ -1651,7 +1651,7 @@ def detrend(self, method="linear"):
         return out
 
     def copy(self):
-        """ Create a copy of a Brain_Data instance.  """
+        """Create a copy of a Brain_Data instance."""
         return deepcopy(self)
 
     def upload_neurovault(
@@ -1751,7 +1751,7 @@ def r_to_z(self):
         return out
 
     def z_to_r(self):
-        """ Convert z score back into r value for each element of data object"""
+        """Convert z score back into r value for each element of data object"""
 
         out = self.copy()
         out.data = fisher_z_to_r(out.data)
@@ -1791,7 +1791,7 @@ def filter(self, sampling_freq=None, high_pass=None, low_pass=None, **kwargs):
         return out
 
     def dtype(self):
-        """ Get data type of Brain_Data.data."""
+        """Get data type of Brain_Data.data."""
         return self.data.dtype
 
     def astype(self, dtype):

nltools/datasets.py

@@ -33,7 +33,7 @@
 
 
 def download_nifti(url, data_dir=None):
-    """ Download a image to a nifti file."""
+    """Download a image to a nifti file."""
     local_filename = url.split("/")[-1]
     if data_dir is not None:
         if not os.path.isdir(data_dir):

nltools/prefs.py

@@ -21,7 +21,7 @@
 
 
 def resolve_mni_path(MNI_Template):
-    """ Helper function to resolve MNI path based on MNI_Template prefs setting."""
+    """Helper function to resolve MNI path based on MNI_Template prefs setting."""
 
     res = MNI_Template["resolution"]
     m = MNI_Template["mask_type"]

nltools/stats.py

@@ -454,14 +454,14 @@ def upsample(
 
 
 def fisher_r_to_z(r):
-    """ Use Fisher transformation to convert correlation to z score """
+    """Use Fisher transformation to convert correlation to z score"""
 
     # return .5*np.log((1 + r)/(1 - r))
     return np.arctanh(r)
 
 
 def fisher_z_to_r(z):
-    """ Use Fisher transformation to convert correlation to z score """
+    """Use Fisher transformation to convert correlation to z score"""
     return np.tanh(z)
 
 

nltools/utils.py

@@ -54,7 +54,7 @@ def _df_meta_to_arr(df):
 
 
 def get_resource_path():
-    """ Get path to nltools resource directory. """
+    """Get path to nltools resource directory."""
     return join(dirname(__file__), "resources") + pathsep
 
 
@@ -231,7 +231,7 @@ def load_class(import_string):
 
 
 def isiterable(obj):
-    """ Returns True if the object is one of allowable iterable types. """
+    """Returns True if the object is one of allowable iterable types."""
     return isinstance(obj, (list, tuple, GeneratorType))