Merge pull request #492 from SpikeInterface/incr_version

SE dependencies and new release

.github/workflows/python-package.yml

@@ -0,0 +1,31 @@
+name: Python Package using Conda
+
+on: [push]
+
+jobs:
+  build-and-test:
+    name: Test on (${{ matrix.os }})
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: ["ubuntu-latest", "macos-latest", "windows-latest"]
+    steps:
+      - uses: actions/checkout@v2
+      - uses: s-weigand/setup-conda@v1
+        with:
+          python-version: 3.8
+      - name: Which python
+        run: |
+          conda --version
+          which python
+      - name: Install dependencies
+        run: |
+          pip install https://github.com/SpikeInterface/spikeextractors/archive/master.zip
+          pip install https://github.com/SpikeInterface/spikemetrics/archive/master.zip
+          pip install https://github.com/SpikeInterface/spikefeatures/archive/master.zip
+          pip install -e .
+          pip install pytest
+      - name: Test with pytest and build coverage report
+        run: |
+          pytest

.github/workflows/python-publish.yml

@@ -0,0 +1,41 @@
+# This workflow will upload a Python Package using Twine when a release is created
+# For more information see: https://help.github.com/en/actions/language-and-framework-guides/using-python-with-github-actions#publishing-to-package-registries
+
+name: Test and Upload Python Package
+
+on:
+  push:
+    tags:
+       - '*'
+
+jobs:
+  deploy:
+
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python 3.8
+        uses: actions/setup-python@v2
+        with:
+          python-version: 3.8
+      - name: Add conda to system path
+        run: |
+          # $CONDA is an environment variable pointing to the root of the miniconda directory
+          echo $CONDA/bin >> $GITHUB_PATH
+      - name: Install dependencies
+        run: |
+          pip install numpy>=1.20
+          pip install pandas>=1.2
+          pip install -e .
+          pip install pytest
+      - name: Test with pytest and build coverage report
+        run: |
+          pytest
+      - name: Publish on PyPI
+        env:
+          TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
+          TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
+        run: |
+          python setup.py sdist bdist_wheel
+          twine upload dist/*

setup.py

@@ -20,7 +20,7 @@
     package_data={},
     install_requires=[
         'numpy',
-        'spikeextractors>=0.9.4',
+        'spikeextractors>=0.9.7',
         'spikemetrics>=0.2.4',
         'spikefeatures',
         'scikit-learn',

spiketoolkit/preprocessing/mask.py

@@ -13,7 +13,7 @@ def __init__(self, recording, bool_mask):
         self._mask = bool_mask
         assert len(bool_mask) == recording.get_num_frames(), "'bool_mask' should be a boolean array with length of " \
                                                              "number of frames"
-        assert np.array(bool_mask).dtype in (bool, np.bool), "'bool_mask' should be a boolean array"
+        assert np.array(bool_mask).dtype == bool, "'bool_mask' should be a boolean array"
         self.is_dumpable = False
         BasePreprocessorRecordingExtractor.__init__(self, recording)
         self._kwargs = {'recording': recording.make_serialized_dict(), 'bool_mask': bool_mask}

spiketoolkit/preprocessing/transform.py

@@ -28,7 +28,7 @@ def get_traces(self, channel_ids=None, start_frame=None, end_frame=None, return_
 
         traces = self._recording.get_traces(channel_ids=channel_ids, start_frame=start_frame, end_frame=end_frame,
                                             return_scaled=return_scaled)
-        if isinstance(self._scalar, (int, float, np.integer, np.float)):
+        if isinstance(self._scalar, (int, float, np.integer)):
             traces = traces*self._scalar
         else:
             if len(self._scalar) == len(channel_ids):
@@ -37,7 +37,7 @@ def get_traces(self, channel_ids=None, start_frame=None, end_frame=None, return_
                 channel_idxs = np.array([self._recording.get_channel_ids().index(ch) for ch in channel_ids])
                 scalar = np.array(self._scalar)[channel_idxs]
             traces = traces * scalar[:, np.newaxis]
-        if isinstance(self._offset, (int, float, np.integer, np.float)):
+        if isinstance(self._offset, (int, float, np.integer)):
             traces = traces + self._offset
         else:
             if len(self._offset) == len(channel_ids):

spiketoolkit/version.py

@@ -1 +1 @@
-version = '0.7.5'
+version = '0.7.6'