Animating bubble plots

Let's look at how to animate a bubble plot. This is useful when you want to visualize data that's transient and dynamic.

How to do it…

  1. Create a new Python file, and import the following packages:
    import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
  2. Let's define a tracker function that will dynamically update the bubble plot:
    def tracker(cur_num):
    # Get the current index 
    cur_index = cur_num % num_points
  3. Define the color:
        # Set the color of the datapoints 
    datapoints['color'][:, 3] = 1.0
  4. Update the size of the circles:
        # Update the size of the circles 
    datapoints['size'] += datapoints['growth']
  5. Update the position of the oldest datapoint in the set:
        # Update the position of the oldest datapoint 
    datapoints['position'][cur_index] = np.random.uniform(0, 1, 2)
    datapoints['size'][cur_index] = 7
    datapoints['color'][cur_index] = (0, 0, 0, 1)
    datapoints['growth'][cur_index] = np.random.uniform(40, 150)
  6. Update the parameters of the scatterplot:
        # Update the parameters of the scatter plot 
    scatter_plot.set_edgecolors(datapoints['color'])
    scatter_plot.set_sizes(datapoints['size'])
    scatter_plot.set_offsets(datapoints['position'])
  7. Define the main function and create an empty figure:
    if __name__=='__main__':
    # Create a figure 
    fig = plt.figure(figsize=(9, 7), facecolor=(0,0.9,0.9))
    ax = fig.add_axes([0, 0, 1, 1], frameon=False)
    ax.set_xlim(0, 1), ax.set_xticks([])
    ax.set_ylim(0, 1), ax.set_yticks([])
  8. Define the number of points that will be on the plot at any given point of time:
        # Create and initialize the datapoints in random positions 
    # and with random growth rates.
    num_points = 20
  9. Define the datapoints using random values:
        datapoints = np.zeros(num_points, dtype=[('position', float, 2),
            ('size', float, 1), ('growth', float, 1), ('color', float, 4)])
    datapoints['position'] = np.random.uniform(0, 1, (num_points, 2))
    datapoints['growth'] = np.random.uniform(40, 150, num_points)
  10. Create the scatterplot that will be updated every frame:
        # Construct the scatter plot that will be updated every frame
    scatter_plot = ax.scatter(datapoints['position'][:, 0], datapoints['position'][:, 1],
                      s=datapoints['size'], lw=0.7, edgecolors=datapoints['color'],
                      facecolors='none')
  11. Start the animation using the tracker function:
        # Start the animation using the 'tracker' function 
    animation = FuncAnimation(fig, tracker, interval=10)

    plt.show()
  12. The full code is in the dynamic_bubble_plot.py file that's already provided to you. If you run this code, you will see the following figure:
    How to do it…
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