IndexError: index 10 is out of bounds for axis 0 with size 10

Question

我在数字上为 x 网格和 x 向量以及时间网格设置了一个网格，但是我再次为 x（位置）设置了一个数组，它应该只在 0 和20 和 t（时间）将从 0 到 1000，因此为了求解热方程。但是每次我想要，例如，我将步数设置为 10，我都会得到一个错误：

"Traceback (most recent call last):
File "/home/universe/Desktop/Python/Heat_1.py", line 33, in <module>
x[i] = a + i*h
IndexError: index 10 is out of bounds for axis 0 with size 10"

这是我的代码：

from math import sin,pi
import numpy
import numpy as np

#Constant variables
N = int(input("Number of intervals in x (<=20):"))
M = int(input("Number of time steps (<=1000):" ))

#Some initialised varibles
a = 0.0
b = 1.0
t_min = 0.0
t_max = 0.5

# Array Variables
x = np.linspace(a,b, M)
t = np.linspace(t_min, t_max, M) 


#Some scalar variables
n = []                         # the number of x-steps
i, s = [], []                  # The position and time

# Get the number of x-steps to use
for n in range(0,N):
    if n > 0 or n <= N:
         continue

# Get the number of time steps to use
for m in range(0,M):
    if m > 0 or n <= M:
         continue

# Set up x-grid  and x-vector
h =(b-a)/n
for i in range(0,N+1):
    x[i] = a + i*h

# Set up time-grid
k = (t_max - t_min)/m
for s in range(0, M+1):
    t[s] = t_min + k*s

print(x,t)

Answer 1

您尝试索引超出范围：

for s in range(0, M+1):
    t[s] = t_min + k*s

更改为：

for s in range(M):
    t[s] = t_min + k*s

而且有效。

您创建 t，长度为 M：

t = np.linspace(t_min, t_max, M)

因此您只能访问 t 中的 M 个元素。

Python 总是从零开始索引。因此：

for s in range(M):

将执行 M 循环，同时：

for s in range(0, M+1):

将进行 M+1 循环。

IndexError: index 10 is out of bounds for axis 0 with size 10

IndexError: index 10 is out of bounds for axis 0 with size 10

arrays

python-2.7

python-3.x

numpy

differential-equations