使用matplotlib动画的子图

时间:2015-04-23 18:56:01

标签: python matplotlib

我有这个代码。我想添加一个子图来绘制余弦函数。 (我不想创建一个类)。第二个图也应该动态更新

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

def data_gen():
    t = data_gen.t
    cnt = 0
    while cnt < 1000:
        cnt+=1
        t += 0.05
        yield t, np.sin(2*np.pi*t) * np.exp(-t/10.)
data_gen.t = 0

fig, ax = plt.subplots()
line, = ax.plot([], [], lw=2)
ax.set_ylim(-1.1, 1.1)
ax.set_xlim(0, 5)
ax.grid()
xdata, ydata = [], []
def run(data):
    # update the data
    t,y = data
    xdata.append(t)
    ydata.append(y)
    xmin, xmax = ax.get_xlim()

    if t >= xmax:
        ax.set_xlim(xmin, 2*xmax)
        ax.figure.canvas.draw()
    line.set_data(xdata, ydata)

    return line,

ani = animation.FuncAnimation(fig, run, data_gen, blit=True, interval=10,
    repeat=False)
plt.show()

1 个答案:

答案 0 :(得分:17)

基本上,您可以使用与示例中的结构非常相似的结构。您只需要创建一个附加轴(子图)和第二个线对象:

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

def data_gen():
    t = data_gen.t
    cnt = 0
    while cnt < 1000:
        cnt+=1
        t += 0.05
        y1 = np.sin(2*np.pi*t) * np.exp(-t/10.)
        y2 = np.cos(2*np.pi*t) * np.exp(-t/10.)
        # adapted the data generator to yield both sin and cos
        yield t, y1, y2

data_gen.t = 0

# create a figure with two subplots
fig, (ax1, ax2) = plt.subplots(2,1)

# intialize two line objects (one in each axes)
line1, = ax1.plot([], [], lw=2)
line2, = ax2.plot([], [], lw=2, color='r')
line = [line1, line2]

# the same axes initalizations as before (just now we do it for both of them)
for ax in [ax1, ax2]:
    ax.set_ylim(-1.1, 1.1)
    ax.set_xlim(0, 5)
    ax.grid()

# initialize the data arrays 
xdata, y1data, y2data = [], [], []
def run(data):
    # update the data
    t, y1, y2 = data
    xdata.append(t)
    y1data.append(y1)
    y2data.append(y2)

    # axis limits checking. Same as before, just for both axes
    for ax in [ax1, ax2]:
        xmin, xmax = ax.get_xlim()
        if t >= xmax:
            ax.set_xlim(xmin, 2*xmax)
            ax.figure.canvas.draw()

    # update the data of both line objects
    line[0].set_data(xdata, y1data)
    line[1].set_data(xdata, y2data)

    return line

ani = animation.FuncAnimation(fig, run, data_gen, blit=True, interval=10,
    repeat=False)
plt.show()