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!
答案 0 :(得分:2)
打印变量x
,t
和u
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x
和t
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
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:
因为matplotlib的文档似乎不是很透彻,而且在示例中缺乏