[英]How can I modify my graph so it displays the proper information for the axes?
I have written a program to solve the Heat Equation ( u_t = k * u_xx
) numerically by method of Finite Differences. 我编写了一个程序,通过有限差分法来数值求解热方程( u_t = k * u_xx
)。
For my problem, u
is function of x
and t
, where 0 < x < L
and t > 0
. 对于我的问题, u
是x
和t
函数,其中0 < x < L
和t > 0
。 I have specified L = 1
(the length of the rod) and the terminal time T = 10
seconds for my problem, so I would like for the graph to be displayed on the domain (x,t) \\in {(0,1) x (0, 10)}
. 我为我的问题指定了L = 1
(杆的长度),并且终止时间T = 10
秒,所以我希望图形显示在域(x,t) \\in {(0,1) x (0, 10)}
。 However, my axes just don't make sense. 但是,我的轴根本没有意义。 It is plotting the x-axis from values of 0 - 40
and the t-axis is showing -0.25 - 0.00
. 它从0 - 40
值绘制x轴,而t轴显示-0.25 - 0.00
。
How can I edit my code so that when I plot u
which depends on x, t
the graph will display for values of x
ranging from 0 - 1
and t
ranging from 0 - 10
seconds?? 如何编辑代码,以便在绘制取决于x, t
u
,图形将显示x
值,范围为0 - 1
, t
范围为0 - 10
秒?
Thanks in advance for any and all help. 在此先感谢您提供的所有帮助。 it is very greatly appreciated. 非常感谢。 Here is the code I am working with: 这是我正在使用的代码:
## 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
# 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] )
# for graph
print u, x, t
plt.plot(u)
plt.title('Finite Difference Approx. to Heat Equation')
plt.xlabel('x-axis')
plt.ylabel('time (seconds)')
plt.axis()
plt.show()
It appears that whatever displays for the x-axis reflects the number of step sizes in space that I take ( N = 40
) for my code. 似乎x轴上的任何显示都反映了我为代码占用的空间步长数( N = 40
)。 I thought np.arange(x_init, x_end, dx)
would return evenly spaced values within the interval (x_init, x_end)
with step size dx
? 我以为np.arange(x_init, x_end, dx)
将以步长dx
返回间隔(x_init, x_end)
内的均匀间隔值? So what am I doing wrong? 那我在做什么错? Thanks again. 再次感谢。
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