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I have a numpy array let's say that has a shape (10,10) for example. Now i want to apply np.exp() to this array, but just to some specific elements that satisfy a condition. For example i want to apply np.exp to all the elements that are not 0 or 1. Is there a way to do that without using for loop that iterate on each element of the array?

Marco
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  • Yes. Numpy has both [advanced indexing](https://docs.scipy.org/doc/numpy-1.13.0/reference/arrays.indexing.html) and the [where](https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.where.html) function for more complex queries. – armatita Nov 07 '17 at 15:55
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1 Answers1

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This is achievable with basic numpy operations. Here is a way to do that :

A = np.random.randint(0,5,size=(10,10)).astype(float)  # data
goods = (A!=0) & (A!=1)  # 10 x 10 boolean array
A[goods] = np.exp(A[goods])  # boolean indexing
B. M.
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