Matplotlib で散布図をアニメーション化して時変データを視覚化する方法

<code class="python">scat = plt.scatter(x, y, c=c)

# Update position
scat.set_offsets(new_xy)

# Update size
scat.set_sizes(new_sizes)

# Update color
scat.set_array(new_colors)</code>

<code class="python">import matplotlib.animation as animation

def update(i):
    # Update data
    x, y, c = get_data(i)

    # Update plot
    scat.set_offsets(x, y)
    scat.set_array(c)

    return scat,

ani = animation.FuncAnimation(fig, update, interval=5)
plt.show()</code>

<code class="python">import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation

# Create random data
num_points = 50
xy = (np.random.rand(2, num_points) - 0.5) * 10
c = np.random.rand(num_points)

# Setup figure and axes
fig, ax = plt.subplots()
scat = ax.scatter(xy[0], xy[1], c=c, s=30)

# Define animation update function
def update(i):
    # Update data
    xy += np.random.rand(2, num_points) * 0.02
    c = np.random.rand(num_points)

    # Update plot
    scat.set_offsets(xy)
    scat.set_array(c)

    return scat,

# Create animation
ani = animation.FuncAnimation(fig, update, interval=10)
plt.show()</code>