refactor: update GitHub actions workflows

.github/workflows/CI.yml

@@ -4,6 +4,8 @@ name:  CI
 
 on:
   push:
+    branches:
+      - all
     tags:
       - "v*"
   workflow_dispatch:
@@ -71,7 +73,7 @@ jobs:
     # this will run when you have tagged a commit, starting with "v*"
     # and requires that you have put your twine API key in your
     # github secrets
-    needs: [test]
+    needs: [check]
     runs-on: ubuntu-latest
     if: contains(github.ref, 'tags')
     steps:

.github/workflows/test_matrix_and_deploy.yml

@@ -36,15 +36,9 @@ jobs:
           git clone --depth 1 https://github.com/pyvista/gl-ci-helpers.git
           powershell gl-ci-helpers/appveyor/install_opengl.ps1
 
-      - name: Install dependencies
+      - name: "Install napari-locan and dependencies"
         run: |
           python -m pip install --upgrade pip
-          python -m pip install setuptools tox tox-gh-actions
-
-      # this runs the platform-specific tests declared in tox.ini
-      - name: Test with tox
-        uses: aganders3/headless-gui@v1
-        with:
-          run: python -m tox
-        env:
-          PLATFORM: ${{ matrix.platform }}
+          python -m pip install .[test]
+      - name: "Run tests"
+        run:  pytest

src/napari_locan/_sample_data.py

@@ -21,7 +21,7 @@ def make_image_tubulin() -> list[LayerData]:
     Generate a sample image from `locan.datasets.load_tubulin`.
     """
     locdata = lc.datasets.load_tubulin()
-    data, bins, labels = lc.histogram(locdata, bin_size=10)
+    data, bins, labels = lc.histogram(locdata, bin_size=10, bin_range="zero")
     data = lc.adjust_contrast(data, rescale=lc.Trafo.EQUALIZE_0P3)
     napari.utils.notifications.show_info("message")
     return [(data, {"name": "tubulin", "colormap": "gray"}, "image")]
@@ -32,7 +32,7 @@ def make_image_npc() -> list[LayerData]:
     Generate a sample image from `locan.datasets.load_npc`.
     """
     locdata = lc.datasets.load_npc()
-    data, bins, labels = lc.histogram(locdata, bin_size=10)
+    data, bins, labels = lc.histogram(locdata, bin_size=10, bin_range="zero")
     data = lc.adjust_contrast(data, rescale=lc.Trafo.EQUALIZE_0P3)
     return [(data, {"name": "npc", "colormap": "gray"}, "image")]