Python绘制动画示例

照猫画虎，首先看看Python matpotlib官网http://matplotlib.org/examples/index.html上的示例都完成了什么功能，毕竟自己研究API太费时

1、

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animationdef data_gen(t=0):cnt = 0while cnt < 1000:cnt += 1t += 0.1yield t, np.sin(2*np.pi*t) * np.exp(-t/10.)def init():ax.set_ylim(-1.1, 1.1)ax.set_xlim(0, 10)del xdata[:]del ydata[:]line.set_data(xdata, ydata)return line,fig, ax = plt.subplots()
line, = ax.plot([], [], lw=2)
ax.grid()
xdata, ydata = [], []def run(data):# update the datat, y = dataxdata.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=False, interval=10,repeat=False, init_func=init)
plt.show()

2、

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animationfig = plt.figure()def f(x, y):return np.sin(x) + np.cos(y)x = np.linspace(0, 2 * np.pi, 120)
y = np.linspace(0, 2 * np.pi, 100).reshape(-1, 1)im = plt.imshow(f(x, y), animated=True)def updatefig(*args):global x, yx += np.pi / 15.y += np.pi / 20.im.set_array(f(x, y))return im,ani = animation.FuncAnimation(fig, updatefig, interval=50, blit=True)
plt.show()

3、

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animationdef update_line(num, data, line):line.set_data(data[..., :num])return line,fig1 = plt.figure()data = np.random.rand(2, 25)
l, = plt.plot([], [], 'r-')
plt.xlim(0, 1)
plt.ylim(0, 1)
plt.xlabel('x')
plt.title('test')
line_ani = animation.FuncAnimation(fig1, update_line, 25, fargs=(data, l),interval=50, blit=True)# To save the animation, use the command: line_ani.save('lines.mp4')fig2 = plt.figure()x = np.arange(-9, 10)
y = np.arange(-9, 10).reshape(-1, 1)
base = np.hypot(x, y)
ims = []
for add in np.arange(15):ims.append((plt.pcolor(x, y, base + add, norm=plt.Normalize(0, 30)),))im_ani = animation.ArtistAnimation(fig2, ims, interval=50, repeat_delay=3000,blit=True)
# To save this second animation with some metadata, use the following command:
# im_ani.save('im.mp4', metadata={'artist':'Guido'})plt.show()

4、

import numpy as npimport matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.path as path
import matplotlib.animation as animationfig, ax = plt.subplots()# histogram our data with numpy
data = np.random.randn(1000)
n, bins = np.histogram(data, 100)# get the corners of the rectangles for the histogram
left = np.array(bins[:-1])
right = np.array(bins[1:])
bottom = np.zeros(len(left))
top = bottom + n
nrects = len(left)# here comes the tricky part -- we have to set up the vertex and path
# codes arrays using moveto, lineto and closepoly# for each rect: 1 for the MOVETO, 3 for the LINETO, 1 for the
# CLOSEPOLY; the vert for the closepoly is ignored but we still need
# it to keep the codes aligned with the vertices
nverts = nrects*(1 + 3 + 1)
verts = np.zeros((nverts, 2))
codes = np.ones(nverts, int) * path.Path.LINETO
codes[0::5] = path.Path.MOVETO
codes[4::5] = path.Path.CLOSEPOLY
verts[0::5, 0] = left
verts[0::5, 1] = bottom
verts[1::5, 0] = left
verts[1::5, 1] = top
verts[2::5, 0] = right
verts[2::5, 1] = top
verts[3::5, 0] = right
verts[3::5, 1] = bottombarpath = path.Path(verts, codes)
patch = patches.PathPatch(barpath, facecolor='green', edgecolor='yellow', alpha=0.5)
ax.add_patch(patch)ax.set_xlim(left[0], right[-1])
ax.set_ylim(bottom.min(), top.max())def animate(i):# simulate new data coming indata = np.random.randn(1000)n, bins = np.histogram(data, 100)top = bottom + nverts[1::5, 1] = topverts[2::5, 1] = topreturn [patch, ]ani = animation.FuncAnimation(fig, animate, 100, repeat=False, blit=True)
plt.show()

5、将动画保存视频文件，先安装 sudo apt -get install ffmpeg

import numpy as np
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import matplotlib.animation as animationdef update_line(num, data, line):line.set_data(data[..., :num])return line,# Set up formatting for the movie files
Writer = animation.writers['ffmpeg']
writer = Writer(fps=15, metadata=dict(artist='Me'), bitrate=1800)fig1 = plt.figure()data = np.random.rand(2, 25)
l, = plt.plot([], [], 'r-')
plt.xlim(0, 1)
plt.ylim(0, 1)
plt.xlabel('x')
plt.title('test')
line_ani = animation.FuncAnimation(fig1, update_line, 25, fargs=(data, l),interval=50, blit=True)
FFwriter = animation.FFMpegWriter()
line_ani.save('basic_animation.mp4', writer = FFwriter, fps=30, extra_args=['-vcodec', 'libx264'])
#line_ani.save('lines.mp4', writer=writer)fig2 = plt.figure()x = np.arange(-9, 10)
y = np.arange(-9, 10).reshape(-1, 1)
base = np.hypot(x, y)
ims = []
for add in np.arange(15):ims.append((plt.pcolor(x, y, base + add, norm=plt.Normalize(0, 30)),))im_ani = animation.ArtistAnimation(fig2, ims, interval=50, repeat_delay=3000,blit=True)
#im_ani.save('im.mp4', writer=writer)

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