学习python总会被一些炫酷的python库所惊讶，Python库已经成为Python语言的一大亮点，众多的Python库不仅为我们的学习提供乐趣，也提高了我们开发的效率。今天接着为大家介绍一个炫酷无比的Python库-animatplot，animatplot是一个基于Matplotlib的Python动图库，通过这个库可以画出花哨的动态图形。
效果预览
安装
animatplot库可以直接通过pip命令安装，其使用需要依赖matplotlib第三方库。安装命令：
pip install animatplot
功能模块
Animation：将Block和Timeline组合起来，创建图形
Animation(blocks[, timeline, fig])
2、Block：表示需要被画的数据块
Block([ax, t_axis])
Line(x, y[, ax, t_axis])
Quiver(X, Y, U, V[, ax, t_axis])
Pcolormesh(*args[, ax, t_axis])
Imshow(images[, ax, t_axis])
Nuke(func, length[, fargs, ax, axis])
3、Timeline：控制画图的时间逻辑模块
Timeline(t[, units, fps, log])
资源地址
项目链接：
https://github.com/t-makaro/animatplot
文档：
https://animatplot.readthedocs.io/en/latest
使用示例
（由于动态图尺寸较大，无法上传，所以使用静态图并附上动态图地址）
一、Nuke
import numpy as np
import matplotlib.pyplot as plt
import animatplot as amp
#first construct our data
E0 = np.array([1, 2])
E0 = E0 / np.linalg.norm(E0)
phi = np.array([0, np.pi/7])
f = 3
t = np.linspace(0,2*np.pi,100)
ES = E0[:, np.newaxis]*np.exp(1j*(t+phi[:, np.newaxis]))
#animate the data
fig, ax = plt.subplots()
def animate(i):
ax.set_title('Polarization')
ax.set_aspect('equal')
ax.set(xlim=(-1.2, 1.2), ylim=(-1.2, 1.2))
E = E0*np.exp(1j*(f*t[i]+phi))
xx = np.array([0,E[0].real,0])
yy = np.array([0,0,0])
uu = np.array([E[0].real,0,E[0].real])
vv = np.array([0,E[1].real,E[1].real])
plax = ax.plot(ES[0].real, ES.real[1])
qax = ax.quiver(xx,yy,uu,vv,[0,55,200], scale_units='xy', scale=1.)
animate(0) # initialise the plot with the animate function
timeline = amp.Timeline(t, units='ns', fps=10)
block = amp.blocks.Nuke(animate, length=len(timeline), ax=ax)
anim = amp.Animation([block], timeline)
anim.controls()
anim.save_gif('nuke')
plt.show()
效果
动态图地址：
https://animatplot.readthedocs.io/en/latest/gallery/Nuke..html
二、Imshow
import numpy as np
import matplotlib.pyplot as plt
import animatplot as amp
#first construct our data
# Define LxL matrix
L = 55
# Initialize as random spin
M = 2*(np.random.rand(L,L)>.5)-1
J = 1
b = 2.5
nPer = 100
images = [M]
for i in range(100):
M = M.copy()
for dm in range(nPer):
jj = int(np.random.rand()*L - 1)
kk = int(np.random.rand()*L - 1)
dE = 2*J*(M[jj+1,kk] + M[jj-1,kk] + M[jj,kk+1] + M[jj,kk-1])*M[jj,kk]
if dE <= 0:
M[jj,kk]*=-1
else:
if(np.random.rand()<np.exp(-b*dE)):
M[jj,kk]*=-1
images.append(M)
M[:,-1] = M[:,0]
M[-1,:] = M[0,:]
#animate the data
block = amp.blocks.Imshow(images)
anim = amp.Animation([block])
anim.controls()
anim.save_gif('ising')
plt.show()
效果
动态图地址：
https://animatplot.readthedocs.io/en/latest/gallery/imshow..html
三、Parametric
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import PillowWriter
import animatplot as aplt
def psi(t):
x = t
y = np.sin(t)
return x, y
t = np.linspace(0, 2*np.pi, 25)
x, y = psi(t)
X, Y = aplt.util.parametric_line(x, y)
timeline = aplt.Timeline(t, 's', 24)
ax = plt.axes(xlim=[0, 7], ylim=[-1.1, 1.1])
block1 = aplt.blocks.Line(X, Y, ax)
# or equivalently
# block1 = aplt.blocks.ParametricLine(x, y, ax)
anim = aplt.Animation([block1], timeline)
# Your standard matplotlib stuff
plt.title('Parametric Line')
plt.xlabel('x')
plt.ylabel(r'y')
# Create Interactive Elements
anim.toggle()
anim.timeline_slider()
anim.save('parametric.gif', writer=PillowWriter(fps=5))
plt.show()
效果
动态图地址：
https://animatplot.readthedocs.io/en/latest/gallery/parametric..html
更多示例参看项目文档，对机器学习感兴趣的同学欢迎大家转发&转载本公众号文章，让更多学习机器学习的伙伴加入公众号《python练手项目实战》，在实战中成长。
