一个例程

# _*_ coding: utf-8 _*_

"""
:FILE:
	       测试Matplotlib的各种功能
:Auther: hazy
:Create: 2023/9/4 14:13
:Blog:   https://hazy-.notion.site/Notes-ED-c2d966a38fb34e8f9dec5811e8c78537?pvs=4
"""

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

# np.random.seed(1231321)
# data = {'a': np.arange(50),
#         'c': np.random.randint(0, 50, 50),
#         'd': np.random.randn(50)}
# data['b'] = data['a'] + 10 * np.random.randn(50)
# data['d'] = np.abs(data['d']) * 100

# fig, ax = plt.subplots(figsize=(5,2.7), layout='constrained')
# ax.scatter('a', 'b', c='c', s='d', data=data)
# ax.set_xlabel('entry a')
# ax.set_ylabel('entry b')
# fig.show()

data1,data2,data3 = np.random.randn(3,50)
fig1, ax = plt.subplots(figsize=(5, 2.7))
x = np.arange(len(data1))
ax.plot(x, np.cumsum(data1),color='blue',linewidth=3,linestyle='--')
l, =ax.plot(x, np.cumsum(data2),color='orange', linewidth=2)
l.set_linestyle('-.')
ax.annotate('local max', xy=(10,8),xytext=(30,8),
            arrowprops=dict(facecolor='black', shrink=0.05))
fig1.show()

"""
Color mapped data
"""
# using numpy to mesh.
# method 1:matrix+matrix
# method 2:row + column, sparse=Ture.
x = np.linspace(-5, 5, 101)
y = np.linspace(-5, 5, 101)
xx, yy = np.meshgrid(x, y)
zz = np.sqrt(xx**2 + yy**2)
xs, ys = np.meshgrid(x, y, sparse=True) # reduced
zs = np.sqrt(xs**2 + ys**2)

h = plt.contourf(x, y, zs)
plt.axis('scaled')
plt.colorbar()
plt.show()

X, Y = np.meshgrid(np.linspace(-3, 3, 128),
                   np.linspace(-3, 3, 128))
Z = (1 - X/2 + X**5 + Y**3) * np.exp(-X**2 - Y**2)
# pcolormesh() 逐点描绘
fig_color, axs = plt.subplots(2, 2, layout='constrained')
pc = axs[0, 0].pcolormesh(X, Y, Z, vmin=-1, vmax=1,
                          cmap='RdBu_r')
fig_color.colorbar(pc, ax=axs[0,0])
axs[0, 0].set_title('pcolormesh()')
# contourf() 分层描绘
co = axs[0, 1].contourf(X, Y, Z,
                        levels=np.linspace(-1.25, 1.25, 11))
fig_color.colorbar(co, ax=axs[0, 1])
axs[0, 1].set_title('contourf()')
# a pseudocolor 伪彩色image
pc = axs[1, 0].imshow(Z**2 *100, cmap='plasma',
                      norm=mpl.colors.LogNorm(vmin=0.01, vmax=100))
fig_color.colorbar(pc, ax=axs[1,0], extend='both')
axs[1, 0].set_title('imshow() with LogNorm()')
# Scatter()
pc = axs[1, 1].scatter(data1, data2, c=data3,
                       cmap='RdBu_r')
fig_color.colorbar(pc, ax=axs[1, 1], extend='both')
axs[1, 1].set_title('scatter()')

"""
Animation with Matplotlib
"""
fig_animation, ax = plt.subplots()
t = np.linspace(0, 3, 40)
g = -9.81
v0 = 12
z = g * t**2 / 2 + v0 * t

v02 = 5
z2 = g * t**2 / 2 + v02 * t

scat = ax.scatter(t[0], z[0], c='b',
                  s=5, label=f'v0 = {v0} m/s') # format
line2 = ax.plot(t[0], z2[0], label=f'v0 = {v02} m/s')[0]
ax.set(xlim=[0, 3], ylim=[-4, 10], xlabel='Time [s]',
       ylabel='Z [m]')
ax.legend()

def update(frame):
    # for each frame, update the data stored on each artist.
    x = t[:frame]
    y = z[:frame]
    # update the scatter plot
    data = np.stack([x, y]).T # column matrix
    scat.set_offsets(data)
    # update the line plot
    line2.set_xdata(t[:frame])
    line2.set_ydata(z2[:frame])
    return (scat, line2)

ani = animation.FuncAnimation(fig=fig_animation,
                              func=update,
                              frames=40,
                              interval=30)

ani.save(filename="/pillow_example.gif", writer='pillow')
plt.show()