Make a numpy array selecting only certain rows and certain columns from another

Question

I have created a very large NumPy array of size 500 x 10000, called first_array, to solve a partial differential equation using the Crank Nicolson method. This method needs to create and use all the data stored in the array, but I only need a small part of it. For example, 50 rows and 50 columns would be enough.

How could I create a smaller array, second_array, from first_array by selecting only those rows and columns that are multiples of a certain number? Is there any built-in NumPy method for this task?

For example, if first_array is

array([[11, 12, 13, 14],
       [21, 22, 23, 24],
       [31, 32, 33, 34],
       [14, 42, 43, 44]])

then I would like second_array to be an array formed with the 1st and 3d rows of first_array and with the 2ns and 4th column of first_array:

array([[12, 14],
       [32, 34],])

can you provide a minimal example of input output?

mozway
– mozway

2022-05-10 11:17:21 +00:00
Commented May 10, 2022 at 11:17 — mozway
– mozway, Commented May 10, 2022 at 11:17

ymmx · Accepted Answer · 2022-05-10 11:19:38Z

1

Something like this

import numpy as np

first_array = np.random.rand(500,1000)
row_factor = 10
row_start = 1
col_factor = 10
col_start = 1
second_array = first_array[row_start:-1:row_factor,col_start:-1:col_factor]
print(second_array.shape)

You can make simple slicing where you skip row_factor or col_factor in both direction

answered May 10, 2022 at 11:19

ymmx

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2 Comments

User1234321 Over a year ago

It works perfectly with 2D arrays! Could it also be applied to 1D arrays? I tried 1D_array[col_start:-1:col_factor], but didn't work.

ymmx Over a year ago

You cannot name a variable starting with a number. but it works

import numpy as np       D1_array = np.random.rand(500)        col_factor = 10       col_start = 1       D2_array = D1_array[col_start:-1:col_factor]

System123 · Accepted Answer · 2022-05-10 11:20:30Z

1

You can do it as such:

import numpy as np
x = np.arange(100).reshape(10,10)
y = x[slice(0,-1,3), slice(0,-1,4)].copy()

Now you have selected every row which is a multiple of 3, and every column which is a multiple of 4. You can adjust the slice start and end points if you want to start at a specific offset.

Note: you need to use .copy() if you want to avoid modifying the original array x. Otherwise slices are just a view to the original array.

answered May 10, 2022 at 11:20

System123

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