ENH: add demo of binding widgets to sliders

Author: tacaswell

data_prototype/containers.py

@@ -165,15 +165,19 @@ def _split(input_dict):
         self._xyfuncs = _split(xyfuncs) if xyfuncs is not None else {}
         self._cache: MutableMapping[Union[str, int], Any] = LFUCache(64)
 
+    def _query_hash(self, coord_transform, size):
+        # TODO find a better way to compute the hash key, this is not sentative to
+        # scale changes, only limit changes
+        data_bounds = tuple(coord_transform.transform([[0, 0], [1, 1]]).flatten())
+        hash_key = hash((data_bounds, size))
+        return hash_key
+
     def query(
         self,
         coord_transform: _MatplotlibTransform,
         size: Tuple[int, int],
     ) -> Tuple[Dict[str, Any], Union[str, int]]:
-        # TODO find a better way to compute the hash key, this is not sentative to
-        # scale changes, only limit changes
-        data_bounds = tuple(coord_transform.transform([[0, 0], [1, 1]]).flatten())
-        hash_key = hash((data_bounds, size))
+        hash_key = self._query_hash(coord_transform, size)
         if hash_key in self._cache:
             return self._cache[hash_key], hash_key
 

examples/widgets.py

@@ -0,0 +1,136 @@
+"""
+======
+Slider
+======
+
+In this example, sliders are used to control the frequency and amplitude of
+a sine wave.
+
+See :doc:`/gallery/widgets/slider_snap_demo` for an example of having
+the ``Slider`` snap to discrete values.
+
+See :doc:`/gallery/widgets/range_slider` for an example of using
+a ``RangeSlider`` to define a range of values.
+"""
+import inspect
+
+import numpy as np
+import matplotlib.pyplot as plt
+from matplotlib.widgets import Slider, Button
+
+from data_prototype.wrappers import LineWrapper
+from data_prototype.containers import FuncContainer
+
+
+class SliderContainer(FuncContainer):
+    def __init__(self, xfuncs, /, **sliders):
+        self._sliders = sliders
+        for slider in sliders.values():
+            slider.on_changed(
+                lambda x, sld=slider: sld.ax.figure.canvas.draw_idle(),
+            )
+
+        def get_needed_keys(f, offset=1):
+            return tuple(inspect.signature(f).parameters)[offset:]
+
+        super().__init__(
+            {
+                k: (
+                    s,
+                    # this line binds the correct sliders to the functions
+                    # and makes lambdas that match the API FuncContainer needs
+                    lambda x, keys=get_needed_keys(f), f=f: f(x, *(sliders[k].val for k in keys)),
+                )
+                for k, (s, f) in xfuncs.items()
+            },
+        )
+
+    def _query_hash(self, coord_transform, size):
+        key = super()._query_hash(coord_transform, size)
+        # inject the slider values into the hashing logic
+        return hash((key, tuple(s.val for s in self._sliders.values())))
+
+
+# Define initial parameters
+init_amplitude = 5
+init_frequency = 3
+
+# Create the figure and the line that we will manipulate
+fig, ax = plt.subplots()
+ax.set_xlim(0, 1)
+ax.set_ylim(-7, 7)
+
+ax.set_xlabel("Time [s]")
+
+# adjust the main plot to make room for the sliders
+fig.subplots_adjust(left=0.25, bottom=0.25, right=0.75)
+
+# Make a horizontal slider to control the frequency.
+axfreq = fig.add_axes([0.25, 0.1, 0.65, 0.03])
+freq_slider = Slider(
+    ax=axfreq,
+    label="Frequency [Hz]",
+    valmin=0.1,
+    valmax=30,
+    valinit=init_frequency,
+)
+
+# Make a vertically oriented slider to control the amplitude
+axamp = fig.add_axes([0.1, 0.25, 0.0225, 0.63])
+amp_slider = Slider(
+    ax=axamp,
+    label="Amplitude",
+    valmin=0,
+    valmax=10,
+    valinit=init_amplitude,
+    orientation="vertical",
+)
+
+# Make a vertically oriented slider to control the phase
+axphase = fig.add_axes([0.85, 0.25, 0.0225, 0.63])
+phase_slider = Slider(
+    ax=axphase,
+    label="Phase [rad]",
+    valmin=-2 * np.pi,
+    valmax=2 * np.pi,
+    valinit=0,
+    orientation="vertical",
+)
+
+# pick a cyclic color map
+cmap = plt.get_cmap("twilight")
+
+# set up the data container
+fc = SliderContainer(
+    {
+        # the x data does not need the sliders values
+        "x": (("N",), lambda t: t),
+        "y": (
+            ("N",),
+            # the y data needs all three sliders
+            lambda t, amplitude, frequency, phase: amplitude * np.sin(2 * np.pi * frequency * t + phase),
+        ),
+        # the color data has to take the x (because reasons), but just
+        # needs the phase
+        "color": ((1,), lambda t, phase: phase),
+    },
+    # bind the sliders to the data container
+    amplitude=amp_slider,
+    frequency=freq_slider,
+    phase=phase_slider,
+)
+lw = LineWrapper(
+    fc,
+    # color map phase (scaled to 2pi and wrapped to [0, 1])
+    {"color": lambda color: cmap((color / (2 * np.pi)) % 1)},
+    lw=5,
+)
+ax.add_artist(lw)
+
+
+# Create a `matplotlib.widgets.Button` to reset the sliders to initial values.
+resetax = fig.add_axes([0.8, 0.025, 0.1, 0.04])
+button = Button(resetax, "Reset", hovercolor="0.975")
+button.on_clicked(lambda event: [sld.reset() for sld in (freq_slider, amp_slider, phase_slider)])
+
+plt.show()