This page was generated from examples/tidbits/play-buttons.ipynb. Interactive online version: (Warning: The interactions will be much laggier on Binder than on your computer.) .

Attaching play buttons to sliders¶

Note

The labels will not update as that requires a Python kernel.

If you are working in Jupyter then you can add an ipywidgets.Play widget to the sliders for any of the interactive_* functions.

In this tutorial all the functions are scatter but this will work for plot, hist, imshow, etc…

Specifying Which Sliders Get Play buttons¶

[1]:

%matplotlib ipympl
import matplotlib.pyplot as plt
import numpy as np

import mpl_interactions.ipyplot as iplt

# turn off interactive mode so that broken
# plots don't render in the docs
plt.ioff()


Boolean: All get a button¶

[2]:

N = 50
x = np.random.rand(N)

def f_y(x, tau, beta):
return np.sin(x * tau) ** 2 + np.random.randn(N) * 0.01 * beta

fig, ax = plt.subplots()
controls = iplt.scatter(x, f_y, tau=(1, 2 * np.pi, 100), beta=(0, 2), play_buttons=True)


String:¶

You make a play button for all sliders on either the left or the right using a string argument.

[3]:

fig, ax = plt.subplots()
controls = iplt.scatter(
x, f_y, tau=(1, 2 * np.pi, 100), beta=(0, 2), play_buttons="left"
)

[4]:

fig, ax = plt.subplots()
controls = iplt.scatter(
x, f_y, tau=(1, 2 * np.pi, 100), beta=(0, 2), play_buttons="right"
)


List: Choose by name¶

[5]:

fig, ax = plt.subplots()
controls = iplt.scatter(
x, f_y, tau=(1, 2 * np.pi, 100), beta=(0, 2), play_buttons=["tau"]
)


defaultdict: Specify by name and choose default¶

If you have many parameters and you want the most, but not all, of them to have a Play button then you should use a defaultdict

[6]:

from collections import defaultdict

def f(x, **kwargs):
return x

play_buttons = defaultdict(lambda: True)
play_buttons["tau"] = False
fig, ax = plt.subplots()
controls = iplt.scatter(
x,
f,
tau=(1, 2 * np.pi, 100),
beta=(0, 2),
zeta=(0, 1),
psi=(0, 1),
play_buttons=play_buttons,
)

[ ]:


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