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I'm trying to animate a scatter plot but with a variable number of points at each iteration of my animation.

Animating a scatter plot has been addressed before (e.g., here and here). However, the number of points is always assumed to be fixed. For example, if Axes3D is used, then axes3d.scatter._offsets3d won't work if the number of points are different in each iteration of FuncAnimation.

How can I animate a scatter plot when each animation iteration contains a different number of points?

starball
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Discombobulous
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1 Answers1

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If your goal is to create an animated plot that contains a variable number of points on each frame of the animation, the following code might do the trick:

# == Import Required Libraries =================================================
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from IPython.display import HTML


# ATTENTION: Uncomment this line, if you're running on a Jupyter Notebook
# %matplotlib notebook


def next_frame(total_frame_count: int = 10):
    """
    Generate random 2D frames of varying dimensions.

    This function serves as a generator that yields 2D numpy arrays with random
    values. The dimensions of these arrays range between 5 and 50, inclusive.
    The generator will continue yielding arrays until the total_frame_count
    reaches zero.

    Parameters
    ----------
    total_frame_count : int, optional
        The number of frames to be generated. The default value is 10.

    Yields
    ------
    array_like
        2D numpy array with random values. The dimensions of the array range
        between 5 and 50, inclusive. In other words, the number points
        each frame of the animation will have varies between 5 and 50.

    Examples
    --------
    Use this function in a for-loop to generate and process frames:

    >>> frame_generator = next_frame(3)
    >>> for frame in frame_generator:
    >>>     print(frame.shape)
    (30, 2)
    (12, 2)
    (48, 2)

    Notes
    -----
    This function can be used to generate frames for an animation iteratively.
    """
    while total_frame_count > 0:
        yield np.random.rand(np.random.randint(5, 50), 2)
        total_frame_count -= 1


def update(frame):
    """
    Update a scatter plot with new data.

    This function clears the current scatter plot in the 'ax' Axes object,
    sets the plot limits, and then creates a new scatter plot based on the
    provided 2D frame. The 'ax' Axes object must be pre-defined.

    Parameters
    ----------
    frame : array_like
        A 2D array where each row represents a point in the scatter plot.
        The first column represents the x-values, and the second column
        represents the y-values.

    Returns
    -------
    scat : PathCollection
        A collection of paths that make up the scatter plot.

    Raises
    ------
    NameError
        If 'ax' isn't defined in the scope where this function is called.

    Examples
    --------
    This function can be used in animation generation:

    >>> import matplotlib.pyplot as plt
    >>> import matplotlib.animation as animation
    >>> fig, ax = plt.subplots()
    >>> ani = animation.FuncAnimation(fig, update, frames=next_frame(3))
    >>> plt.show()
    """

    # Clear the last scatter plot
    ax.clear()

    # Set the limits of your plot again
    # NOTE: You might want to dynamically set these limits based on the new frame
    #       values that you're plotting.
    ax.set_xlim(0, 1)
    ax.set_ylim(0, 1)

    # Plot the new scatter plot
    scat = ax.scatter(frame[:, 0], frame[:, 1])

    return scat


# == Create the Animation ======================================================
# Create a figure and an Axes object
fig, ax = plt.subplots()

# Set the initial limits of your plot
ax.set_xlim(0, 1)
ax.set_ylim(0, 1)

# Create the animation object
ani = FuncAnimation(fig, update, frames=next_frame, blit=True)

# Convert the animation to HTML5 video
video = ani.to_html5_video()

# Display the video
HTML(video)

Note that the axis limits can also be modified on each frame.

Ingwersen_erik
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