Numpy: Select all rows and columns from an array

Question

I was hoping I would solve this before I finished the post, but here it goes:

I have an array array1 with a shape (4808L, 5135L) and I am trying to select a rectangular subset of the array. Specifically, I am trying to select the all values in rows 4460:4807 and all the values in columns 2718:2967.

To start I create a mask of the same shape as array1 like:

mask = np.zeros(array1.shape[:2], dtype = "uint8")
mask[array1== 399] = 255

Then I am trying to find the index of the points where mask = 255:

true_points = np.argwhere(mask)
top_left = true_points.min(axis=0)
# take the largest points and use them as the bottom right of your crop
bottom_right = true_points.max(axis=0)
cmask = mask[top_left[0]:bottom_right[0]+1, top_left[1]:bottom_right[1]+1]

Where: top_left = array([4460, 2718], dtype=int64) bottom_right = array([4807, 2967], dtype=int64)

cmask looks correct. Then using top_left and bottom_right I am trying to subset array1 using:

crop_array = array1[top_left[0]:bottom_right[0]+1, top_left[1]:bottom_right[1]+1]

This results in a crop_array have the same shape of cmask, but the values are populated incorrectly. Since cmask[0][0] = 0 I would expect crop_array[0][0] to be equal to zero as well.

How do I poulate crop_array with the values from array1 while retaining the structure of the cmask?

Thanks in advance.

Don't quite get you. Why would you have 4460 on one hand and want 4417 on the other hand? — akuiper
– akuiper, Commented Jan 29, 2017 at 1:14
@Psidom They both come from a mask. 4460 is the minimum column index where I find my desired value. 4417 is the column associated with the minimum row index where i find my desired value. — dubbbdan
– dubbbdan, Commented Jan 29, 2017 at 1:21

Arex · Accepted Answer · 2017-01-29 01:47:55Z

2

If I understood your question correctly, you're looking for the .copy() method. An example matching your indices and variables:

import numpy as np

array1 = np.random.rand(4808,5135)
crop_array = array1[4417:,2718:2967].copy()

assert np.all(np.equal(array1[4417:,2718:2967], crop_array)) == True, (
    'Equality Failed'
)

answered Jan 29, 2017 at 1:47

Arex

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1 Comment

dubbbdan Over a year ago

Thanks for the answer. My problems were something else, but your solution addressed my orignal post

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