update napari examples (#357)

examples/napari_combine_qt.py

@@ -0,0 +1,42 @@
+"""
+Napari provides a few conveniences with magicgui, and one of the
+most commonly used is the layer combo box that gets created when
+a parameter is annotated as napari.layers.Layer.
+
+The layer box will stay in sync with the viewer model, adding and
+removing layers as needed.
+
+This example shows how to use just that widget in the context
+of a larger custom QWidget.
+"""
+import napari
+from qtpy.QtWidgets import QVBoxLayout, QWidget
+
+from magicgui.widgets import create_widget
+
+
+class CustomWidget(QWidget):
+    def __init__(self) -> None:
+        super().__init__()
+        self.setLayout(QVBoxLayout())
+        # change annotation to napari.layers.Image (e.g) to restrict to just Images
+        self._layer_combo = create_widget(annotation=napari.layers.Layer)
+        # magicgui widgets hold the Qt widget at `widget.native`
+        self.layout().addWidget(self._layer_combo.native)
+
+
+viewer = napari.Viewer()
+viewer.add_points()
+viewer.add_points()
+
+my_widget = CustomWidget()
+viewer.window.add_dock_widget(my_widget)
+
+# when my_widget is a magicgui.Widget, it will detect that it has been added
+# to a viewer, and automatically update the choices.  Otherwise, you need to
+# trigger this yourself:
+my_widget._layer_combo.reset_choices()
+viewer.layers.events.inserted.connect(my_widget._layer_combo.reset_choices)
+viewer.layers.events.removed.connect(my_widget._layer_combo.reset_choices)
+
+napari.run()

examples/napari_image_arithmetic.py

@@ -1,8 +1,8 @@
 """Basic example of using magicgui to create an Image Arithmetic GUI in napari."""
 from enum import Enum
 
+import napari
 import numpy
-from napari import Viewer, gui_qt
 from napari.layers import Image
 from napari.types import ImageData
 
@@ -23,28 +23,25 @@ class Operation(Enum):
     divide = numpy.divide
 
 
-with gui_qt():
-    # create a viewer and add a couple image layers
-    viewer = Viewer()
-    viewer.add_image(numpy.random.rand(20, 20), name="Layer 1")
-    viewer.add_image(numpy.random.rand(20, 20), name="Layer 2")
+# create a viewer and add a couple image layers
+viewer = napari.Viewer()
+viewer.add_image(numpy.random.rand(20, 20), name="Layer 1")
+viewer.add_image(numpy.random.rand(20, 20), name="Layer 2")
 
-    # use the magic decorator!  This takes a function, and generates a widget instance
-    # using the function signature. Note that we aren't returning a napari Image layer,
-    # but instead a numpy array which we want napari to interperate as Image data.
-    @magicgui(call_button="execute")
-    def image_arithmetic(
-        layerA: Image, operation: Operation, layerB: Image
-    ) -> ImageData:
-        """Add, subtracts, multiplies, or divides to image layers with equal shape."""
-        return operation.value(layerA.data, layerB.data)
 
-    # add our new magicgui widget to the viewer
-    viewer.window.add_dock_widget(image_arithmetic)
+# for details on why the `-> ImageData` return annotation works:
+# https://napari.org/guides/stable/magicgui.html#return-annotations
+@magicgui(call_button="execute", layout="horizontal")
+def image_arithmetic(layerA: Image, operation: Operation, layerB: Image) -> ImageData:
+    """Add, subtracts, multiplies, or divides to image layers with equal shape."""
+    return operation.value(layerA.data, layerB.data)
 
-    # keep the dropdown menus in the gui in sync with the layer model
-    viewer.layers.events.inserted.connect(image_arithmetic.reset_choices)
-    viewer.layers.events.removed.connect(image_arithmetic.reset_choices)
 
-    # note: the function may still be called directly as usual!
-    # new_image = image_arithmetic(img_a, Operation.add, img_b)
+# add our new magicgui widget to the viewer
+viewer.window.add_dock_widget(image_arithmetic, area="bottom")
+
+
+# note: the function may still be called directly as usual!
+# new_image = image_arithmetic(img_a, Operation.add, img_b)
+
+napari.run()

examples/napari_param_sweep.py

@@ -13,32 +13,31 @@
 
 from magicgui import magicgui
 
-with napari.gui_qt():
-    # create a viewer and add some images
-    viewer = napari.Viewer()
-    viewer.add_image(skimage.data.astronaut().mean(-1), name="astronaut")
-    viewer.add_image(skimage.data.grass().astype("float"), name="grass")
-
-    # turn the gaussian blur function into a magicgui
-    # - `auto_call` tells magicgui to call the function whenever a parameter changes
-    # - we use `widget_type` to override the default "float" widget on sigma
-    # - we provide some Qt-specific parameters
-    # - we contstrain the possible choices for `mode`
-    # Note that we aren't returning a napari Image layer, but instead a numpy array
-    # which we want napari to interperate as Image data.
-    @magicgui(
-        auto_call=True,
-        sigma={"widget_type": "FloatSlider", "max": 6},
-        mode={"choices": ["reflect", "constant", "nearest", "mirror", "wrap"]},
-    )
-    def gaussian_blur(layer: Image, sigma: float = 1.0, mode="nearest") -> ImageData:
-        """Apply a gaussian blur to ``layer``."""
-        if layer:
-            return skimage.filters.gaussian(layer.data, sigma=sigma, mode=mode)
-
-    # Add it to the napari viewer
-    # NOTE: using `.native` will not be necessary after
-    # https://github.com/napari/napari/pull/1994
-    viewer.window.add_dock_widget(gaussian_blur.native)
-    # update the layer dropdown menu when the layer list changes
-    viewer.layers.events.changed.connect(gaussian_blur.reset_choices)
+# create a viewer and add some images
+viewer = napari.Viewer()
+viewer.add_image(skimage.data.astronaut().mean(-1), name="astronaut")
+viewer.add_image(skimage.data.grass().astype("float"), name="grass")
+
+
+# turn the gaussian blur function into a magicgui
+# for details on why the `-> ImageData` return annotation works:
+# https://napari.org/guides/stable/magicgui.html#return-annotations
+@magicgui(
+    # tells magicgui to call the function whenever a parameter changes
+    auto_call=True,
+    # `widget_type` to override the default (spinbox) "float" widget
+    sigma={"widget_type": "FloatSlider", "max": 6},
+    # contstrain the possible choices for `mode`
+    mode={"choices": ["reflect", "constant", "nearest", "mirror", "wrap"]},
+    layout="horizontal",
+)
+def gaussian_blur(layer: Image, sigma: float = 1.0, mode="nearest") -> ImageData:
+    """Apply a gaussian blur to ``layer``."""
+    if layer:
+        return skimage.filters.gaussian(layer.data, sigma=sigma, mode=mode)
+
+
+# Add it to the napari viewer
+viewer.window.add_dock_widget(gaussian_blur, area="bottom")
+
+napari.run()