animator

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animator#

class braintools.visualize.animator(data, fig, ax, num_steps=False, interval=40, cmap='plasma')#

Generate an animation by looping through the first dimension of a sample of image-like data. Time must be the first dimension of data.

Example:

import numpy as np
import matplotlib.pyplot as plt
from IPython.display import HTML
from braintools.visualize import animator

#  A single sample across 100 time steps of 28x28 frames
spike_data_sample = np.random.rand(100, 28, 28)

fig, ax = plt.subplots()
anim = animator(spike_data_sample, fig, ax)
HTML(anim.to_html5_video())

#  Save as a gif
anim.save("spike_mnist.gif", writer="pillow")
Parameters:

  • data (array-like) – Data array of shape (num_steps, height, width). Accepts NumPy, JAX, or brainunit arrays (converted internally).

  • fig (matplotlib.figure.Figure) – Top level container for all plot elements.

  • ax (matplotlib.axes.Axes) – Axes that set the coordinate system, e.g. fig, ax = plt.subplots(facecolor='w', figsize=(12, 7)).

  • num_steps (int, optional) – Number of time steps to plot. When falsy (the default False or 0), every entry along the first dimension of data is used.

  • interval (int, optional) – Delay between frames in milliseconds, defaults to 40.

  • cmap (str, optional) – Color map, defaults to "plasma".

Returns:

anim – Animation to be displayed (e.g. via anim.to_html5_video()) or saved with anim.save(...).

Return type:

matplotlib.animation.ArtistAnimation

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