fastplotlib · almarklein · Mar 31, 2025 · Mar 31, 2025 · Mar 31, 2025 · Mar 31, 2025
@@ -0,0 +1,38 @@
+name: lint
+
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - main
+    types:
+      - opened
+      - reopened
+      - synchronize
+      - ready_for_review
+
+jobs:
+  lint:
+    name: Test Linting
+    timeout-minutes: 5
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+    steps:
+    - uses: actions/checkout@v4
+    - name: Set up Python
+      uses: actions/setup-python@v5
+      with:
+        python-version: '3.12'
+    - name: Install dependencies
+      run: |
+          python -m pip install --upgrade pip
+          pip install ruff
+    - name: Ruff lint
+      run: |
+          ruff check --output-format=github .
+    - name: Ruff format
+      run: |
+          ruff format --check .
@@ -44,7 +44,7 @@
     "sphinx.ext.viewcode",
     "sphinx_copybutton",
     "sphinx_design",
-    "sphinx_gallery.gen_gallery"
+    "sphinx_gallery.gen_gallery",
 ]
 
 sphinx_gallery_conf = {
@@ -70,9 +70,9 @@
             "../../examples/qt",
         ]
     ),
-    "ignore_pattern": r'__init__\.py',
+    "ignore_pattern": r"__init__\.py",
     "nested_sections": False,
-    "thumbnail_size": (250, 250)
+    "thumbnail_size": (250, 250),
 }
 
 extra_conf = find_examples_for_gallery(EXAMPLES_DIR)
@@ -100,8 +100,8 @@
     "check_switcher": True,
     "switcher": {
         "json_url": "http://www.fastplotlib.org/_static/switcher.json",
-        "version_match": release
-    }
+        "version_match": release,
+    },
 }
 
 html_static_path = ["_static"]

@@ -42,15 +42,10 @@
         "fastplotlib\n"
         "***********\n\n"
         ".. currentmodule:: fastplotlib\n\n"
-
         ".. autofunction:: fastplotlib.pause_events\n\n"
-
         ".. autofunction:: fastplotlib.enumerate_adapters\n\n"
-
         ".. autofunction:: fastplotlib.select_adapter\n\n"
-
         ".. autofunction:: fastplotlib.print_wgpu_report\n\n"
-
         "fastplotlib.loop\n"
         "------------------\n"
         "See the rendercanvas docs: https://rendercanvas.readthedocs.io/stable/api.html#rendercanvas.BaseLoop "
@@ -60,7 +55,6 @@
     f.write(
         "fastplotlib.utils\n"
         "*****************\n\n"
-
         "..currentmodule:: fastplotlib.utils\n"
         "..automodule:: fastplotlib.utils.functions\n"
         "    : members:\n"
@@ -106,8 +100,8 @@

    underline = "=" * len(name)

    methods_str = "\n    ".join([""] + methods)
    properties_str = "\n    ".join([""] + properties)

    out = (
        f"{underline}\n"
@@ -161,15 +155,9 @@
 ):
     page_name_underline = "*" * len(page_name)
     with open(source_path, "w") as f:
-        f.write(
-            f".. _api.{page_name}:\n"
-            f"\n"
-            f"{page_name}\n"
-            f"{page_name_underline}\n"
-            f"\n"
-        )
+        f.write(f".. _api.{page_name}:\n\n{page_name}\n{page_name_underline}\n\n")
 
-        for cls, module in zip(classes, modules):
+        for cls, module in zip(classes, modules, strict=False):
             to_write = generate_class(cls, module)
             f.write(to_write)
 
@@ -199,15 +187,15 @@
     # layouts classes index file
     with open(LAYOUTS_DIR.joinpath("index.rst"), "w") as f:
         f.write(
-            f"Layouts\n"
-            f"********\n"
-            f"\n"
-            f".. toctree::\n"
-            f"    :maxdepth: 1\n"
-            f"\n"
-            f"    imgui_figure\n"
-            f"    figure\n"
-            f"    subplot\n"
+            "Layouts\n"
+            "********\n"
+            "\n"
+            ".. toctree::\n"
+            "    :maxdepth: 1\n"
+            "\n"
+            "    imgui_figure\n"
+            "    figure\n"
+            "    subplot\n"
         )
 
     # the rest of this is a mess and can be refactored later
@@ -216,7 +204,7 @@

    graphic_class_names = [g.__name__ for g in graphic_classes]

    graphic_class_names_str = "\n    ".join([""] + graphic_class_names)

    # graphic classes index file
    with open(GRAPHICS_DIR.joinpath("index.rst"), "w") as f:
@@ -242,7 +230,7 @@

    feature_class_names = [f.__name__ for f in feature_classes]

    feature_class_names_str = "\n    ".join([""] + feature_class_names)

    with open(GRAPHIC_FEATURES_DIR.joinpath("index.rst"), "w") as f:
        f.write(
@@ -267,7 +255,7 @@

    selector_class_names = [s.__name__ for s in selector_classes]

    selector_class_names_str = "\n    ".join([""] + selector_class_names)

    with open(SELECTORS_DIR.joinpath("index.rst"), "w") as f:
        f.write(
@@ -292,7 +280,7 @@

    widget_class_names = [w.__name__ for w in widget_classes]

    widget_class_names_str = "\n    ".join([""] + widget_class_names)

    with open(WIDGETS_DIR.joinpath("index.rst"), "w") as f:
        f.write(
@@ -317,7 +305,7 @@

    ui_class_names = [cls.__name__ for cls in ui_classes]

    ui_class_names_str = "\n    ".join([""] + ui_class_names)

    with open(UI_DIR.joinpath("index.rst"), "w") as f:
        f.write(
@@ -362,5 +350,6 @@
             "    utils\n"
         )
 
+
 if __name__ == "__main__":
     main()
@@ -12,16 +12,12 @@
 import numpy as np
 
 
-figure = fpl.Figure(
-    shape=(2, 3),
-    size=(700, 560),
-    names=list(map(str, range(6)))
-)
+figure = fpl.Figure(shape=(2, 3), size=(700, 560), names=list(map(str, range(6))))
 
 np.random.seed(0)
 a = np.random.rand(6, 10, 10)
 
-for data, subplot in zip(a, figure):
+for data, subplot in zip(a, figure, strict=False):
     subplot.add_image(data)
     subplot.docks["left"].size = 20
     subplot.docks["right"].size = 30

@@ -17,7 +17,7 @@
 figure = fpl.Figure(
     shape=(2, 2),
     names=[["image-overlay", "circles"], ["line-stack", "scatter"]],
-    size=(700, 560)
+    size=(700, 560),
 )
 
 img = iio.imread("imageio:coffee.png")
@@ -36,6 +36,7 @@
 # add overlay to image
 figure["image-overlay"].add_image(data=overlay)
 
+
 # generate some circles
 def make_circle(center, radius: float, n_points: int = 75) -> np.ndarray:
     theta = np.linspace(0, 2 * np.pi, n_points)
@@ -54,12 +55,7 @@ def make_circle(center, radius: float, n_points: int = 75) -> np.ndarray:
     circles.append(make_circle(center, 5, n_points=75))
 
 # things like class labels, cluster labels, etc.
-cmap_transform = [
-    0, 1, 1, 2,
-    0, 0, 1, 1,
-    2, 2, 8, 3,
-    1, 9, 1, 5
-]
+cmap_transform = [0, 1, 1, 2, 0, 0, 1, 1, 2, 2, 8, 3, 1, 9, 1, 5]
 
 # add an image to overlay the circles on
 img2 = iio.imread("imageio:coins.png")[10::5, 5::5]
@@ -73,7 +69,7 @@ def make_circle(center, radius: float, n_points: int = 75) -> np.ndarray:
     cmap_transform=cmap_transform,
     thickness=3,
     alpha=0.5,
-    name="circles-graphic"
+    name="circles-graphic",
 )
 
 # move the circles graphic so that it is centered over the image
@@ -115,4 +111,3 @@ def make_circle(center, radius: float, n_points: int = 75) -> np.ndarray:
 if __name__ == "__main__":
     print(__doc__)
     fpl.loop.run()
-
@@ -41,14 +41,18 @@ def update(self):
         something_changed = False
 
         # slider for gaussian filter sigma value
-        changed, value = imgui.slider_float(label="sigma", v=self.sigma, v_min=0.0, v_max=20.0)
+        changed, value = imgui.slider_float(
+            label="sigma", v=self.sigma, v_min=0.0, v_max=20.0
+        )
         if changed:
             self.sigma = value
             something_changed = True
 
         # int entries for gaussian filter order
         for axis in ["x", "y"]:
-            changed, value = imgui.input_int(f"order {axis}", v=getattr(self, f"order_{axis}"))
+            changed, value = imgui.input_int(
+                f"order {axis}", v=getattr(self, f"order_{axis}")
+            )
             if changed:
                 if value < 0:
                     value = 0
@@ -63,11 +67,15 @@ def update(self):
         # do not call imgui.end_frame(), this is handled by Figure
 
     def process_image(self):
-        processed = gaussian_filter(a, sigma=self.sigma, order=(self.order_y, self.order_x))
+        processed = gaussian_filter(
+            a, sigma=self.sigma, order=(self.order_y, self.order_x)
+        )
         iw.set_data(processed)
 
 
-gui = ImageProcessingWindow(iw.figure, size=200, location="right", title="Gaussian Filter")
+gui = ImageProcessingWindow(
+    iw.figure, size=200, location="right", title="Gaussian Filter"
+)
 
 
 iw.figure.add_gui(gui)

@@ -29,10 +29,14 @@
 figure = fpl.Figure(size=(700, 560))
 
 # make some scatter points at every 10th point
-figure[0, 0].add_scatter(data[::10], colors="cyan", sizes=15, name="sine-scatter", uniform_color=True)
+figure[0, 0].add_scatter(
+    data[::10], colors="cyan", sizes=15, name="sine-scatter", uniform_color=True
+)
 
 # place a line above the scatter
-figure[0, 0].add_line(data, thickness=3, colors="r", name="sine-wave", uniform_color=True)
+figure[0, 0].add_line(
+    data, thickness=3, colors="r", name="sine-wave", uniform_color=True
+)
 
 
 class ImguiExample(EdgeWindow):
@@ -60,27 +64,35 @@ def update(self):
         # get current line color alpha value
         alpha = self._line.colors[-1]
         # make float slider
-        changed_alpha, new_alpha = imgui.slider_float("alpha", v=alpha, v_min=0.0, v_max=1.0)
+        changed_alpha, new_alpha = imgui.slider_float(
+            "alpha", v=alpha, v_min=0.0, v_max=1.0
+        )
 
         # if RGB or alpha changed
         if changed_color | changed_alpha:
             # set new color along with alpha
             self._line.colors = [*rgb, new_alpha]
 
         # example of a slider, you can also use input_float
-        changed, amplitude = imgui.slider_float("amplitude", v=self._amplitude, v_max=10, v_min=0.1)
+        changed, amplitude = imgui.slider_float(
+            "amplitude", v=self._amplitude, v_max=10, v_min=0.1
+        )
         if changed:
             # set y values
             self._amplitude = amplitude
             self._set_data()
 
         # slider for thickness
-        changed, thickness = imgui.slider_float("thickness", v=self._line.thickness, v_max=50.0, v_min=2.0)
+        changed, thickness = imgui.slider_float(
+            "thickness", v=self._line.thickness, v_max=50.0, v_min=2.0
+        )
         if changed:
             self._line.thickness = thickness
 
         # slider for gaussian noise
-        changed, sigma = imgui.slider_float("noise-sigma", v=self._sigma, v_max=1.0, v_min=0.0)
+        changed, sigma = imgui.slider_float(
+            "noise-sigma", v=self._sigma, v_max=1.0, v_min=0.0
+        )
         if changed:
             self._sigma = sigma
             self._set_data()
@@ -99,7 +111,9 @@ def update(self):
             self._set_data()
 
     def _set_data(self):
-        self._line.data[:, 1] = (np.sin(xs) * self._amplitude) + np.random.normal(scale=self._sigma, size=100)
+        self._line.data[:, 1] = (np.sin(xs) * self._amplitude) + np.random.normal(
+            scale=self._sigma, size=100
+        )
 
 
 # make GUI instance

@@ -14,10 +14,7 @@
 
 figure = fpl.Figure(size=(700, 560))
 
-data = np.array(
-    [[0, 1, 2],
-     [3, 4, 5]]
-)
+data = np.array([[0, 1, 2], [3, 4, 5]])
 image_graphic = figure[0, 0].add_image(data)
 
 figure.show()

@@ -18,7 +18,7 @@
 
 iw = fpl.ImageWidget(
     data=[img1, img2, img3, img4],
-    rgb=[False, True, True, True], # mix of grayscale and RGB images
+    rgb=[False, True, True, True],  # mix of grayscale and RGB images
     names=["cameraman", "astronaut", "chelsea", "Almar's cat"],
     # ImageWidget will sync controllers by default
     # by setting `controller_ids=None` we can have independent controllers for each subplot

@@ -29,7 +29,7 @@
     [random_data, cockatoo_sub],
     rgb=[False, True],
     figure_shape=(2, 1),  # 2 rows, 1 column
-    figure_kwargs={"size": (700, 940)}
+    figure_kwargs={"size": (700, 940)},
 )
 
 iw.show()

@@ -24,19 +24,13 @@
 
 # cmap_transform from an array, so the colors on the sine line will be based on the sine y-values
 sine_graphic = figure[0, 0].add_line(
-    data=sine,
-    thickness=10,
-    cmap="plasma",
-    cmap_transform=sine[:, 1]
+    data=sine, thickness=10, cmap="plasma", cmap_transform=sine[:, 1]
 )
 
 # qualitative colormaps, useful for cluster labels or other types of categorical labels
 labels = [0] * 25 + [5] * 10 + [1] * 35 + [2] * 30
 cosine_graphic = figure[0, 0].add_line(
-    data=cosine,
-    thickness=10,
-    cmap="tab10",
-    cmap_transform=labels
+    data=cosine, thickness=10, cmap="tab10", cmap_transform=labels
 )
 
 figure.show()