在python中使用matplotlib创建3D曲面图

时间:2016-07-12 21:20:09

标签: python matplotlib plot mplot3d

我正在尝试绘制3D表面,但我遇到了一些麻烦,因为matplotlib的文档看起来并不是非常彻底,并且在示例中缺乏。无论如何,我编写的程序是通过有限差分方法以数值方式求解热方程。这是我的代码:

    ## This program is to implement a Finite Difference method approximation
## to solve the Heat Equation, u_t = k * u_xx,
## in 1D w/out sources & on a finite interval 0 < x < L. The PDE
## is subject to B.C: u(0,t) = u(L,t) = 0,
## and the I.C: u(x,0) = f(x).
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D

# Parameters    
L = 1 # length of the rod
T = 10 # terminal time
N = 40 # spatial values
M = 1600 # time values/hops; (M ~ N^2)
s = 0.25 # s := k * ( (dt) / (dx)^2 )

# uniform mesh
x_init = 0
x_end = L
dx = float(x_end - x_init) / N

x = np.arange(x_init, x_end, dx)
x[0] = x_init

# time discretization
t_init = 0
t_end = T
dt = float(t_end - t_init) / M

t = np.arange(t_init, t_end, dt)
t[0] = t_init

# time-vector
for m in xrange(0, M):
    t[m] = m * dt

# spatial-vector
for j in xrange(0, N):
    x[j] = j * dx

# definition of the solution u(x,t) to u_t = k * u_xx
u = np.zeros((N, M+1)) # array to store values of the solution

# Finite Difference Scheme:

u[:,0] = x * (x - 1) #initial condition

for m in xrange(0, M):
    for j in xrange(1, N-1):
        if j == 1:
            u[j-1,m] = 0 # Boundary condition
        elif j == N-1:
            u[j+1,m] = 0 # Boundary Condition
        else:
            u[j,m+1] = u[j,m] + s * ( u[j+1,m] - 
            2 * u[j,m] + u[j-1,m] )

这是我为编写3D表面图而编写的内容:

    # for 3D graph
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
surf = ax.plot_surface(x, t, u, rstride=1, cstride=1, cmap=cm.coolwarm, linewidth=0, antialiased=False)
fig.colorbar(surf, shrink=0.5, aspect=5)
plt.show()

当我运行代码绘制图形时,我收到此错误:&#34; ValueError:形状不匹配:两个或多个数组在轴1上具有不兼容的尺寸。&#34;

请,任何和所有帮助都非常有用。我认为错误出现是因为我将u定义为Nx(M+1)矩阵,但是必须使原始程序运行。我不确定如何纠正这一点,因此图表正确绘制。谢谢!

2 个答案:

答案 0 :(得分:2)

打印变量xtu的形状会很有帮助:

x.shape == (40,)
t.shape == (1600,)
u.shape == (40, 1601)

所以这里有两个问题。 第一个是xt是1维的,即使它们需要是2维的。 第二个是u在第二维中有一个元素而不是t。 您可以通过运行

来解决这两个问题
t, x = np.meshgrid(t, x)
u = u[:,:-1]

在创建3d图之前。

答案 1 :(得分:1)

使用此代码(查看评论):

-Djavax.net.debug=ssl

结果:

enter image description here

  

因为matplotlib的文档似乎不是很透彻,而且在示例中缺乏

http://matplotlib.org/examples/mplot3d/index.html