Introduction
Animations help us see how data or pictures change step by step. This makes it easier to understand patterns or movements over time.
Jump into concepts and practice - no test required
Animations help us see how data or pictures change step by step. This makes it easier to understand patterns or movements over time.
import matplotlib.animation as animation ani = animation.FuncAnimation(fig, update_function, frames=number_of_frames, interval=milliseconds)
fig is the plot figure where animation happens.
update_function changes the plot for each frame.
ani = animation.FuncAnimation(fig, update, frames=100, interval=50)
ani = animation.FuncAnimation(fig, update, frames=range(50), interval=100)
This program shows a sine wave that moves sideways. Each frame shifts the wave a little, creating a smooth animation.
import matplotlib.pyplot as plt import matplotlib.animation as animation import numpy as np fig, ax = plt.subplots() x = np.linspace(0, 2 * np.pi, 200) line, = ax.plot(x, np.sin(x)) # Function to update the y-data of the line for each frame def update(frame): line.set_ydata(np.sin(x + frame / 10)) return line, ani = animation.FuncAnimation(fig, update, frames=100, interval=50) plt.show()
Animations show change by updating the plot many times quickly.
Each frame shows a new state, so our eyes see movement or change.
Animations help us see how things change step by step.
They update plots many times to create smooth motion.
This makes understanding data over time easier and clearer.
matplotlib show change over time?matplotlib?matplotlib.animation.import matplotlib.animation as animation.import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig, ax = plt.subplots()
line, = ax.plot([], [])
def update(frame):
x = list(range(frame))
y = [i**2 for i in x]
line.set_data(x, y)
return line,
ani = animation.FuncAnimation(fig, update, frames=5, blit=True)
print(len(ani.frame_seq))frames=5.ani.frame_seq generates frames from 0 to 4, total 5 frames.import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig, ax = plt.subplots()
line, = ax.plot([], [])
def update(frame):
x = range(frame)
y = [i*2 for i in x]
line.set_data(x, y)
ani = animation.FuncAnimation(fig, update, frames=10, blit=True)
plt.show()blit=True, the update function must return the modified artists as a tuple.