Matplotlib数据关系型图表（2）

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(0)
x = 4 + np.random.normal(0, 2, 24)
y = 4 + np.random.normal(0, 2, len(x))
sizes = np.random.uniform(15, 80, len(x))*10
colors = np.random.uniform(15, 80, len(x))

fig = plt.figure(figsize = (8, 8))
#默认绘图，利用默认的颜色 
ax1 = fig.add_subplot(221)
ax1.scatter(x, y, s = sizes, alpha = .3)
#设置颜色数组，利用默认的颜色条带
ax2 = fig.add_subplot(222)
ax2.scatter(x, y, s = sizes, c = colors, alpha = .6)
#设置颜色数组，指定颜色条带，添加颜色指示图例
ax3 = fig.add_subplot(212)
cf = ax3.scatter(x, y, s = sizes, c = y, cmap = 'jet', alpha = .6)
cbar = fig.colorbar(cf, ax = ax3, extend = 'both', orientation='horizontal') 
cbar.set_label("Value")

plt.show()

fig = plt.figure(figsize = (10, 10))
#2维散点图
ax1 = fig.add_subplot(221)
ax1.scatter(x, y, s = sizes, c = colors, cmap = 'jet', alpha = .6)
#设置三维散点图，指定z值为sizes数组
ax2 = fig.add_subplot(222, projection = '3d')
ax2.scatter(x, y, sizes, c = colors, cmap = 'jet', alpha = .6)
#指定z值和大小为sizes数组
ax3 = fig.add_subplot(223, projection = '3d')
ax3.scatter(x, y, sizes, s = sizes, c = colors, cmap = 'jet', alpha = .6)
#旋转三维图，azim表示绕着Z轴旋转，elev表示绕着Y轴旋转 
ax4 = fig.add_subplot(224, projection = '3d')
ax4.scatter(x, y, sizes, s = sizes, c = colors, cmap = 'jet', alpha = .6)
ax4.view_init(azim = 40, elev = 20)

plt.show()

#构建子图，3行2列，在列上共享x轴，行上共享y轴 
fig, ax = plt.subplots(3, 2, sharex = 'col', sharey = 'row', figsize = (10, 15))
#构造数据 
N = 100
x = np.linspace(-2, 2, N)
y = np.linspace(-2, 2, N)
X, Y = np.meshgrid(x, y) ##关键语法，生成格网化的X,Y 
def Z(a, b): #Z值生成规则
    return (1 - b ** 5 + a ** 5) * np.exp(-a ** 2 - b ** 2)
    
#生成10条等高线，颜色为黑色     
ax1 = ax[0, 0]
ax1.contour(X, Y, Z(X, Y), 10, colors='k')

#生成10条等高线，并添加等高线的数值，保留2位小数 
ax2 = ax[0, 1]
labels = ax2.contour(X, Y, Z(X, Y), 10, colors='k')
ax2.clabel(labels, inline=True, colors=['k', 'r', 'g', 'b'], fmt='%.2f')

#为每条等高线设置颜色，一共10条等高线，按照k,r,g,b分别设色，并设置线形
ax3 = ax[1, 0]
colors = ['k', 'r', 'g', 'b']
labels = ax3.contour(X, Y, Z(X, Y), 10, colors = colors, linestyles = '--')
ax3.clabel(labels, inline = True, colors = colors, fmt = '%.2f')

#为等高线设置颜色映射，映射名称为jet
ax4 = ax[1, 1]
labels = ax4.contour(X, Y, Z(X, Y), 10, cmap = 'jet')
ax4.clabel(labels, inline = True, colors = 'k', fmt = '%.2f')

#传入levels数组，手动设置等高线条数和数值
ax5 = ax[2, 0]
labels = ax5.contour(X, Y, Z(X, Y), levels = [-0.6, -0.3, 0.0, 0.4, 0.8], cmap = 'jet')
ax5.clabel(labels, inline = True, colors = 'k', fmt = '%.2f')

#等高线填充颜色，就将contour改为contourf即可
ax6 = ax[2, 1]
ax6.contourf(X, Y, Z(X, Y), levels = 10, cmap = 'jet')
labels = ax6.contour(X, Y, Z(X, Y), levels = 10, cmap = 'jet')
ax6.clabel(labels, inline = True, colors = 'k', fmt = '%.2f')
#调整子图水平、垂直间距
plt.subplots_adjust(wspace = 0.05, hspace = 0.05)
plt.show()

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt

fig = plt.figure(figsize = (7, 7))
ax2 = Axes3D(fig) #生成axes3D对象
#绘制曲面图
cf = ax2.plot_surface(X, Y, Z(X, Y), cmap = 'jet', alpha = .8)
#绘制等高线图，offset表示z值所处位置
labels = ax2.contour(X, Y, Z(X, Y), levels = 10, cmap = 'jet', offset = -0.6, linestyles = '--')
ax2.clabel(labels, inline = True, colors = 'k', fmt = '%.2f')
#绘制色条 
cbar = fig.colorbar(cf, ax = ax2, orientation='horizontal', pad = -0.01) 
cbar.set_label("Value")

plt.show()