基于python的数学建模---二维插值的三维图

import numpy as np

from mpl_toolkits.mplot3d import Axes3D

import matplotlib as mpl

from scipy import interpolate

import matplotlib.cm as cm

import matplotlib.pyplot as plt

def func(x, y):

    return (x + y) * np.exp(-5.0 * (x ** 2 + y ** 2))

x = np.linspace(-1, 1, 20)

y = np.linspace(-1, 1, 20)

x, y = np.meshgrid(x, y)

fvals = func(x, y)

fig = plt.figure(figsize=(9, 6))

ax = plt.subplot(1, 2, 1, projection='3d')

        #三维网面图                  #跨行      跨列

surf = ax.plot_surface(x, y, fvals, rstride=2, cstride=2, cmap=cm.coolwarm, linewidth=0.5, antialiased=True)

ax.set_xlabel('x')

ax.set_ylabel('y')

ax.set_zlabel('f(x, y)')  # 标签

plt.colorbar(surf, shrink=0.5, aspect=5)  # 标注

#插值　　　　　　　　　　　　　　　　kind：插值方式，有三种可选，分别是'linear'（线性插值）、'cubic'（三次样条插值）、'quintic'（五次样条插值）

newfunc = interpolate.interp2d(x, y, fvals, kind='cubic')  # newfunc为一个函数

xnew = np.linspace(-1, 1, 100)  # x

ynew = np.linspace(-1, 1, 100)  # y

fnew = newfunc(xnew, ynew)

xnew, ynew = np.meshgrid(xnew, ynew)

ax2 = plt.subplot(1, 2, 2, projection='3d')

surf2 = ax2.plot_surface(xnew, ynew, fnew, rstride=2, cstride=2, cmap=cm.coolwarm, linewidth=0.5, antialiased=True)

ax2.set_xlabel('xnew')

ax2.set_ylabel('ynew')

ax2.set_zlabel('fnew(x, y)')

plt.colorbar(surf2, shrink=0.5, aspect=5)

plt.show()

基于python的数学建模---二维插值的三维图的相关教程结束。