finding element of numpy array that satisfies condition

Question

One can use numpy's extract function to match an element in an array. The following code matches an element 'a.' exactly in an array. Suppose I want to match all elements containing '.', how would I do that? Note that in this case, there would be two matches. I'd also like to get the row and column number of the matches. The method doesn't have to use extract; any method will do. Thanks.

In [110]: x = np.array([['a.','cd'],['ef','g.']])

In [111]: 'a.' == x
Out[111]: 
array([[ True, False],
       [False, False]], dtype=bool)

In [112]: np.extract('a.' == x, x)
Out[112]: 
array(['a.'], 
      dtype='|S2')

It would be less confusing to write x == 'a.', not that it helps answer you question — Benjamin
– Benjamin, Commented Dec 6, 2011 at 21:31

mac · Accepted Answer · 2011-12-06 22:15:29Z

9

You can use the string operations:

>>> import numpy as np
>>> x = np.array([['a.','cd'],['ef','g.']])
>>> x[np.char.find(x, '.') > -1]
array(['a.', 'g.'], 
      dtype='|S2')

EDIT: As per request in the comments... If you want to find out the indexes of where the target condition is true, use numpy.where:

>>> np.where(np.char.find(x, '.') > -1)
(array([0, 1]), array([0, 1]))

or

>>> zip(*np.where(np.char.find(x, '.') > -1))
[(0, 0), (1, 1)]

edited Dec 6, 2011 at 22:15

answered Dec 6, 2011 at 21:38

mac

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4 Comments

Benjamin Over a year ago

Nice, never knew about char

Faheem Mitha Over a year ago

Thanks. Any way of finding the row and column?

Faheem Mitha Over a year ago

@mac: See comment at the bottom of the main question. I couldn't fit it into SO's notion of a comment.

mac Over a year ago

@FaheemMitha - Sorry, my bad. You should compare with >-1 as 0 is the valid positional index for "found as first character"... (You should probably remove the edited part if it solves, as it will only confuse future visitors...).

jterrace · Accepted Answer · 2011-12-06 21:36:25Z

3

How about this?

>>> import numpy as np
>>> x = np.array([['a.','cd'],['ef','g.']])
>>> selector = np.array(['.' in s for s in x.flat]).reshape(x.shape)
>>> x[selector]
array(['a.', 'g.'], 
      dtype='|S2')

answered Dec 6, 2011 at 21:36

jterrace

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1 Comment

Faheem Mitha Over a year ago

Thanks. Any way of finding the row and column?

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