动画 2D plot（2D 布朗运动）在 Python 中不起作用

Question

我正在尝试 plot Python 中的 2D 布朗运动，但我的 plot 绘制网格但不为线设置动画。

尝试执行此 plot 如下，

!apt install ffmpeg

import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import matplotlib.animation as animation


np.random.seed(5)


# Set up formatting for the movie files
Writer = animation.writers['ffmpeg']
writer = Writer(fps=15, metadata=dict(artist='Me'), bitrate=1800)


def generateRandomLines(dt, N):
    dX = np.sqrt(dt) * np.random.randn(1, N)
    X = np.cumsum(dX, axis=1)

    dY = np.sqrt(dt) * np.random.randn(1, N)
    Y = np.cumsum(dY, axis=1)

    lineData = np.vstack((X, Y))

    return lineData


# Returns Line2D objects
def updateLines(num, dataLines, lines):
    for u, v in zip(lines, dataLines):
        u.set_data(v[0:2, :num])

    return lines

N = 501 # Number of points
T = 1.0
dt = T/(N-1)


fig, ax = plt.subplots()

data = [generateRandomLines(dt, N)]

ax = plt.axes(xlim=(-2.0, 2.0), ylim=(-2.0, 2.0))

ax.set_xlabel('X(t)')
ax.set_ylabel('Y(t)')
ax.set_title('2D Discretized Brownian Paths')

## Create a list of line2D objects
lines = [ax.plot(dat[0, 0:1], dat[1, 0:1])[0] for dat in data]


## Create the animation object
anim = animation.FuncAnimation(fig, updateLines, N+1, fargs=(data, lines), interval=30, repeat=True, blit=False)

plt.tight_layout()
plt.show()

## Uncomment to save the animation
#anim.save('brownian2d_1path.mp4', writer=writer)

但是，程序正在打印，而不是执行 plot，

如何为这个 plot 设置动画？ 我是 python 的新手，所以如果这是一个简单的问题，我提前道歉。

我在http://people.bu.edu/andasari/courses/stochasticmodeling/lecture5/stochasticlecture5.html上找到了这个问题，有一个关于这段代码是如何产生的演练。

Answer 1

感谢@JohanC 的帮助，让它工作起来。

#!apt install ffmpeg
#!brew install imagemagick

import numpy as np
import matplotlib
import matplotlib.pyplot as plt

from matplotlib import animation, rc
from IPython.display import HTML, Image # For GIF

rc('animation', html='html5')
np.random.seed(5)


# Set up formatting for the movie files
Writer = animation.writers['ffmpeg']
writer = Writer(fps=15, metadata=dict(artist='Me'), bitrate=1800)


def generateRandomLines(dt, N):
    dX = np.sqrt(dt) * np.random.randn(1, N)
    X = np.cumsum(dX, axis=1)

    dY = np.sqrt(dt) * np.random.randn(1, N)
    Y = np.cumsum(dY, axis=1)

    lineData = np.vstack((X, Y))

    return lineData


# Returns Line2D objects
def updateLines(num, dataLines, lines):
    for u, v in zip(lines, dataLines):
        u.set_data(v[0:2, :num])

    return lines

N = 501 # Number of points
T = 1.0
dt = T/(N-1)


fig, ax = plt.subplots()

data = [generateRandomLines(dt, N)]

ax = plt.axes(xlim=(-2.0, 2.0), ylim=(-2.0, 2.0))

ax.set_xlabel('X(t)')
ax.set_ylabel('Y(t)')
ax.set_title('2D Discretized Brownian Paths')

## Create a list of line2D objects
lines = [ax.plot(dat[0, 0:1], dat[1, 0:1])[0] for dat in data]


## Create the animation object
anim = animation.FuncAnimation(fig, updateLines, N+1, fargs=(data, lines), 
interval=30, repeat=True, blit=False)

plt.tight_layout()
plt.show()

# Save as GIF
anim.save('animationBrownianMotion2d.gif', writer='pillow', fps=60)

Image(url='animationBrownianMotion2d.gif')
## Uncomment to save the animation
#anim.save('brownian2d_1path.mp4', writer=writer)