动画是描述现象的工具，相比于静态图，我们人类经常执迷于动画和交互图表。在探求时间序列数据时，诸如股价趋势、气候变化、季节等, 动画更有洞感。今天让我们尝试绘制以下三种动图
matplotlib中拥有一个FuncAnimation函数，该函数可以帮助实现动画。如果想将运行的结果存储为gif、mp4，你可能需要在电脑上配置好ffmpeg或imagemagick(请自行百度谷歌)。
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.animation import FuncAnimation
plt.style.use('seaborn-pastel')
#定制画布
fig = plt.figure()
ax = plt.axes(xlim=(0, 4), ylim=(-2, 2))
#折线图对象line
line, = ax.plot([], [], lw=3)
#初始化
def init():
line.set_data([], [])
return line,
#生成每一帧所用的函数
def animate(i):
x = np.linspace(0, 4, 1000)
y = np.sin(2 * np.pi * (x - 0.01 * i))
line.set_data(x, y)
return line,
#帧数frame=200，帧间隔interval=20
#blit不知何意，直接用吧
anim = FuncAnimation(fig, animate, init_func=init,
frames=200, interval=20, blit=True)
anim.save('sine_wave.gif', writer='imagemagick')
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
plt.style.use('dark_background')
fig = plt.figure()
ax = plt.axes(xlim=(-50, 50), ylim=(-50, 50))
line, = ax.plot([], [], lw=2)
# initialization function
def init():
# creating an empty plot/frame
line.set_data([], [])
return line,
# lists to store x and y axis points
xdata, ydata = [], []
# animation function
def animate(i):
# t is a parameter
t = 0.1*i
# x, y values to be plotted
x = t*np.sin(t)
y = t*np.cos(t)
# appending new points to x, y axes points list
xdata.append(x)
ydata.append(y)
line.set_data(xdata, ydata)
return line,
# setting a title for the plot
plt.title('Creating a growing coil with matplotlib!')
# hiding the axis details
plt.axis('off')
# call the animator
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=300, interval=20, blit=True)
# save the animation as mp4 video file
anim.save('coil.gif',writer='imagemagick')
当原始数据发生更改时，之前绘制的图就会发生变化， 参考自 sentdex(一位youtube上的up主)
#importing libraries
import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig = plt.figure()
#creating a subplot
ax1 = fig.add_subplot(1,1,1)
def animate(i):
data = open('stock.txt','r').read()
lines = data.split('\n')
xs = []
ys = []
for line in lines:
x, y = line.split(',') # Delimiter is comma
xs.append(float(x))
ys.append(float(y))
ax1.clear()
ax1.plot(xs, ys)
plt.xlabel('Date')
plt.ylabel('Price')
plt.title('Live graph with matplotlib')
ani = animation.FuncAnimation(fig, animate, interval=1000)
plt.show()
上面的这个股票可视化代码我们会在命令行中运行，当stocks.txt中的数据发生更改的时候，图片也会发生变动。
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