CODEWITHSUNDEEP
pythonnumpynumpy-slicing
Mathieu Châteauvert
Mathieu Châteauvert

Reputation: 479

Ways to filter specific value of array in numpy

I haven't use numpy to his full potential yet. I have this pretty huge 3d array (700000 x 32 x 32). All of the values are int between 1 and 4. I want to be able to filter the array so that the I get a same shape array, but only with 1 for values of 4 and 0 for everything else.

For example, 

[[4, 2, 2, 3],      [[1, 0, 0, 0],
 [1, 4, 4, 2],       [0, 1, 1, 0],
 [2, 4, 1, 3],   ->  [0, 1, 0, 0],
 [2, 3, 2, 4]]       [0, 0, 0, 1]]

It works with np.where(array==4). I get a huge 3d array that I can reshape, but would there more numpy way to do it ? Thanks.

Upvotes: 1

Views: 328

Answers (3)

IMB
IMB

Reputation: 529

You can also get it with np.where without having to reshape it with the next expression:

arr = np.array([[4, 2, 2, 3],      
                [1, 4, 4, 2],       
                [2, 4, 1, 3],  
                [2, 3, 2, 4]])

np.where(arr == 4, 1, 0)

Output:

array([[1, 0, 0, 0],
       [0, 1, 1, 0],
       [0, 1, 0, 0],
       [0, 0, 0, 1]])

Upvotes: 1

Mehul Gupta
Mehul Gupta

Reputation: 1939

import numpy as np
matrix = np.zeros((5,5))
matrix[0]=[1,-2,3,4,-5]
matrix[2]=[0,1,4,0,4]
matrix=np.array([[1 if value==4 else 0 for value in row ] for row in matrix])

enter image description here

The above snippet uses nested list comprehension & than converts list back to np array

Upvotes: 0

AMH
AMH

Reputation: 528

arr = np.array([[4, 2, 2, 3],      
                [1, 4, 4, 2],       
                [2, 4, 1, 3],  
                [2, 3, 2, 4]])

In[58]: (arr==4).astype(int)

Out[58]: array([[1, 0, 0, 0],
                [0, 1, 1, 0],
                [0, 1, 0, 0],
                [0, 0, 0, 1]])

Upvotes: 2

Related Questions