CODEWITHSUNDEEP
pythonboundsout
Shaun
Shaun

Reputation: 531

index 4 is out of bounds for axis 1 with size 4 Code with Double Sum

Hi I have the following function which produces an out of bounds error:

import numpy as np
import pylab as plt
import scipy
import math
import sympy as sy


T = sy.Symbol('T')
rho = sy.Symbol('rho')


g_T   = [1,T,T**2,T*sy.log(T),T**2*sy.log(T)]
g_rho  = [1,rho,rho**2,rho*sy.log(rho),rho**2*sy.log(rho)]

g_T_np = np.asarray(g_T)
g_rho_np = np.asarray(g_rho)


c = np.loadtxt("c_test.txt")


def F(T,rho):
    ret = 0
    for n in xrange(1,5):
        for m in xrange(1,6):
            inner= c[n,m]*g_T_np*g_rho_np
        ret += inner
    return ret

print F(T,rho)

where the .txt file is like this:

-0.529586   -0.000208559    -3.36563E-09    2.29441E-05 
2.22722E-06 -0.00014526 -2.48888E-09    1.89488E-05 
-6.26662E-05    0.000421028 6.17407E-09 -5.14488E-05    
0.09977346  -0.000622051    -8.56485E-09    7.49956E-05 
-0.01437627 -9.86754E-05    -1.59808E-09    1.22574E-05

The full error displayed is:

Traceback (most recent call last):File "EOS_test.py", line 38, in <module> print F(T,rho) File "EOS_test.py", line 31, in F inner=c[n,m]*g_T_np*g_rho_np IndexError: index 4 is out of bounds for axis 1 with size 4

How can I solve this error?

Upvotes: 4

Views: 94401

Answers (2)

Scott Mermelstein
Scott Mermelstein

Reputation: 15397

Your problem is in setting your xranges.

Python lists (and np arrays) are 0 indexed, so you don't want the indices [1,2,3,4,5] and [1,2,3,4,5,6], but instead want [0,1,2,3,4] and [0,1,2,3,4,5] [0,1,2,3] and [0,1,2,3,4].

Setting up your for loops like this would solve your problem:

for n in xrange(0,4):
    for m in xrange(0,5):

Or, you can take advantage of xrange's default starting point, and simply list one parameter:

for n in xrange(4):
    for m in xrange(5):

Also, for a "more pythonic" solution, instead of having nested for loops, look up how to iterate over an ndarray. The docs give this example:

it = np.nditer(c, flags=['f_index'])
while not it.finished:
    inner= c[it[0]]*g_T_np*g_rho_np
    ret += inner
    it.iternext()

This avoids the whole issue of needing to know the size of the array you're importing, and is therefore much more robust.

Edit: As pdowling mentioned in his answer, the range numbers should be 4 and 5. I had left 5 and 6 in my aswer, and have now changed that.

Upvotes: 0

pdowling
pdowling

Reputation: 500

Numpy uses 0-based indexing. From the looks of it you are indexing the array from 1 (2nd position) to 4 (5th position), which is of course out of bounds for the array you are working with. The same is true for the second axis.

Secondly, you've mixed up your axes:

  • The first axis (0) is the index of the selected row (0 to 5)
  • the second axis indexes the column, i.e. the value inside a row (indexed 0 to 4)

This should work:

def F(T,rho):
    ret = 0
    for n in range(5):
        for m in range(4):
            inner= c[n,m]*g_T_np*g_rho_np
        ret += inner
    return ret

Upvotes: 5

Related Questions