fastplotlib · clewis7 · Mar 15, 2025 · Feb 27, 2025 · Feb 27, 2025 · Feb 28, 2025
@@ -23,24 +23,25 @@ Properties
     Figure.cameras
     Figure.canvas
     Figure.controllers
-    Figure.mode
+    Figure.layout
     Figure.names
     Figure.renderer
     Figure.shape
-    Figure.spacing
 
 Methods
 ~~~~~~~
 .. autosummary::
     :toctree: Figure_api
 
     Figure.add_animations
+    Figure.add_subplot
     Figure.clear
     Figure.close
     Figure.export
     Figure.export_numpy
     Figure.get_pygfx_render_area
     Figure.open_popup
     Figure.remove_animation
+    Figure.remove_subplot
     Figure.show
 
@@ -25,11 +25,10 @@ Properties
     ImguiFigure.controllers
     ImguiFigure.guis
     ImguiFigure.imgui_renderer
-    ImguiFigure.mode
+    ImguiFigure.layout
     ImguiFigure.names
     ImguiFigure.renderer
     ImguiFigure.shape
-    ImguiFigure.spacing
 
 Methods
 ~~~~~~~
@@ -38,6 +37,7 @@ Methods
 
     ImguiFigure.add_animations
     ImguiFigure.add_gui
+    ImguiFigure.add_subplot
     ImguiFigure.clear
     ImguiFigure.close
     ImguiFigure.export
@@ -46,5 +46,6 @@ Methods
     ImguiFigure.open_popup
     ImguiFigure.register_popup
     ImguiFigure.remove_animation
+    ImguiFigure.remove_subplot
     ImguiFigure.show
 
@@ -26,6 +26,7 @@ Properties
     Subplot.canvas
     Subplot.controller
     Subplot.docks
+    Subplot.frame
     Subplot.graphics
     Subplot.legends
     Subplot.name
@@ -34,6 +35,7 @@ Properties
     Subplot.renderer
     Subplot.scene
     Subplot.selectors
+    Subplot.title
     Subplot.toolbar
     Subplot.viewport
 
@@ -53,13 +55,11 @@ Methods
     Subplot.auto_scale
     Subplot.center_graphic
     Subplot.center_scene
-    Subplot.center_title
     Subplot.clear
     Subplot.delete_graphic
     Subplot.get_figure
     Subplot.insert_graphic
     Subplot.map_screen_to_world
     Subplot.remove_animation
     Subplot.remove_graphic
-    Subplot.set_title
 
@@ -59,6 +59,7 @@
             "../../examples/heatmap",
             "../../examples/image_widget",
             "../../examples/gridplot",
+            "../../examples/window_layouts",
             "../../examples/line",
             "../../examples/line_collection",
             "../../examples/scatter",

@@ -29,7 +29,7 @@
     [random_data, cockatoo_sub],
     rgb=[False, True],
     figure_shape=(2, 1),  # 2 rows, 1 column
-    figure_kwargs={"size": (700, 560)}
+    figure_kwargs={"size": (700, 940)}
 )
 
 iw.show()

@@ -3,6 +3,9 @@
 ===================================
 
 Example showing how you can perform K-Means clustering on the MNIST dataset.
+
+Use WASD keys on your keyboard to fly through the data in PCA space.
+Use the mouse pointer to select points.
 """
 
 # test_example = false
@@ -29,17 +32,17 @@
 # iterate through each subplot
 for i, subplot in enumerate(fig_data):
     # reshape each image to (8, 8)
-    subplot.add_image(data[i].reshape(8,8), cmap="gray", interpolation="linear")
+    subplot.add_image(data[i].reshape(8, 8), cmap="gray", interpolation="linear")
    <
1004E
span class='blob-code-inner blob-code-marker ' data-code-marker=" ">    # add the label as a title
-    subplot.set_title(f"Label: {labels[i]}")
+    subplot.title = f"Label: {labels[i]}"
     # turn off the axes and toolbar
     subplot.axes.visible = False
-    subplot.toolbar  = False
+    subplot.toolbar = False
 
 fig_data.show()
 
 # project the data from 64 dimensions down to the number of unique digits
-n_digits = len(np.unique(labels)) # 10
+n_digits = len(np.unique(labels))  # 10
 
 reduced_data = PCA(n_components=n_digits).fit_transform(data) # (1797, 10)
 
@@ -53,17 +56,17 @@
 
 # plot the kmeans result and corresponding original image
 figure = fpl.Figure(
-    shape=(1,2),
-    size=(700, 400),
+    shape=(1, 2),
+    size=(700, 560),
     cameras=["3d", "2d"],
-    controller_types=[["fly", "panzoom"]]
+    controller_types=["fly", "panzoom"]
 )
 
-# set the axes to False
-figure[0, 0].axes.visible = False
+# set the axes to False in the image subplot
 figure[0, 1].axes.visible = False
 
-figure[0, 0].set_title(f"K-means clustering of PCA-reduced data")
+figure[0, 0].title = "k-means clustering of PCA-reduced data"
+figure[0, 1].title = "handwritten digit"
 
 # plot the centroids
 figure[0, 0].add_scatter(
@@ -94,6 +97,7 @@
 digit_scatter.colors[ix] = "magenta"
 digit_scatter.sizes[ix] = 10
 
+
 # define event handler to update the selected data point
 @digit_scatter.add_event_handler("pointer_enter")
 def update(ev):
@@ -110,8 +114,10 @@ def update(ev):
     # update digit fig
     figure[0, 1]["digit"].data = data[ix].reshape(8, 8)
 
+
 figure.show()
 
+
 # NOTE: `if __name__ == "__main__"` is NOT how to use fastplotlib interactively
 # please see our docs for using fastplotlib interactively in ipython and jupyter
 if __name__ == "__main__":

@@ -102,7 +102,7 @@ def plot_test(name, fig: fpl.Figure):
         # hacky but it works for now
         fig.imgui_renderer.render()
 
-    fig._set_viewport_rects()
+    fig._fpl_reset_layout()
     # render each subplot
     for subplot in fig:
         subplot.viewport.render(subplot.scene, subplot.camera)