"IndexError: too many indices" in numpy python

Question

I know many people asked this question, but I could not get an appropriate answer that can solve my problem.

I have an array X::

    X=
    [1. 2. -10.]

Now I am trying to make a matrix Y reading this X array. My code is::

#   make Y matrix

Y=np.matrix(np.zeros((len(X),2)))
i=0

while i < len(load_value):
    if X[i,1] % 2 != 0:
        Y[i,0] = X[i,0]*2-1
    elif X[i,1] % 2 == 0:
        Y[i,0] = X[i,0] * 2
    Y[i,1] = X[i,2]
    i = i + 1
print('Y=')
print(Y)

Now if I run this, it gives following error::

    Traceback (most recent call last):
      File "C:\Users\User\Desktop\Code.py", line 251, in <module>
        if X[i,1] % 2 != 0:
    IndexError: too many indices

here, my array has only 1 row. If I make array X with 2 or more rows, it does not give me any error. It gives me error only when X array has 1 row. Now, in my case, array X can have any number of rows. It can have 1 row or 5 rows or 100 rows. I want to write a code which can read array X with any number of rows without any error. How can I solve this problem?

Thanks in advance....

It sounds like when you say "1 row", you really mean it doesn't have the "rows" dimension at all. Can you change your code so it does have that dimension? — user2357112
– user2357112, Commented Mar 1, 2014 at 1:34

zhangxaochen · Accepted Answer · 2015-03-13 09:45:41Z

6

I suggest using numpy.matrix instead of ndarray, it keeps a dimension of 2 regardless of how many rows you have:

In [17]: x
Out[17]: 
array([[0, 1, 2],
       [3, 4, 5],
       [6, 7, 8]])

In [18]: m=np.asmatrix(x)

In [19]: m[1]
Out[19]: matrix([[3, 4, 5]])

In [20]: m[1][0, 1]
Out[20]: 4

In [21]: x[1][0, 1]
---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-21-bef99eb03402> in <module>()
----> 1 x[1][0, 1]

IndexError: too many indices

Thx for @askewchan mentioning, if you want to use the numpy array arithmetic, use np.atleast_2d:

In [85]: np.atleast_2d(x[1])[0, 1]
Out[85]: 4

edited Mar 13, 2015 at 9:45

answered Mar 1, 2014 at 2:33

zhangxaochen

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3 Comments

askewchan Over a year ago

Or if you don't want the added behavior of the np.matrix (like * doing matrix multiplication), just use x = np.atleast_2d(x).

zhangxaochen Over a year ago

@askewchan thx! forgot it since I seldom use that... updated ;)

Nafees Over a year ago

ahh.... thank you. I just converted numpy array X to numpy matrix X. Now its working fine.

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