CODEWITHSUNDEEP
pythonpython-2.7python-3.xnumpyscipy
Rudresha Parameshappa
Rudresha Parameshappa

Reputation: 3926

select first occurance of minimum index from numpy array

I am trying to find out the index of the minimum value in each row and I am using below code.

#code
import numpy as np
C = np.array([[1,2,4],[2,2,5],[4,3,3]])
ind = np.where(C == C.min(axis=1).reshape(len(C),1))
ind

#output
(array([0, 1, 1, 2, 2], dtype=int64), array([0, 0, 1, 1, 2], dtype=int64))

but the problem it is returning all indices of minimum values in each row. but I want only the first occurrence of minimum values. like 

(array([0, 1, 2], dtype=int64), array([0, 0, 1], dtype=int64))

Upvotes: 1

Views: 1627

Answers (1)

Divakar
Divakar

Reputation: 221514

If you want to use comparison against the minimum value, we need to use np.min and keep the dimensions with keepdims set as True to give us a boolean array/mask. To select the first occurance, we can use argmax along each row of the mask and thus have our desired output.

Thus, the implementation to get the corresponding column indices would be -

(C==C.min(1, keepdims=True)).argmax(1)

Sample step-by-step run -

In [114]: C   # Input array
Out[114]: 
array([[1, 2, 4],
       [2, 2, 5],
       [4, 3, 3]])

In [115]: C==C.min(1, keepdims=1) # boolean array of min values
Out[115]: 
array([[ True, False, False],
       [ True,  True, False],
       [False,  True,  True]], dtype=bool)

In [116]: (C==C.min(1, keepdims=True)).argmax(1) # argmax to get first occurances
Out[116]: array([0, 0, 1])

The first output of row indices would simply be a range array -

np.arange(C.shape[0])

To achieve the same column indices of first occurance of minimum values, a direct way would be to use np.argmin -

C.argmin(axis=1)

Upvotes: 3

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