Is there a function to add a buffer of (NaN) values around a NumPy ndarray?-CodePudding

I am working with a thematic raster of land use classes. The goal is to split the raster into smaller tiles of a given size. For example, I have a raster of 1490 pixels and I want to split it into tiles of 250x250 pixels. To get tiles of equal size, I would want to increase the width of the raster to 1500 pixels to fit in exactly 6 tiles. To do so, I need to increase the size of the raster by 10 pixels.

I am currently opening the raster with the rasterio library, which returns a NumPy ndarray. Is there a function to add a buffer around this array? The goal would be something like this:

import numpy as np

a = np.array([
    [1,4,5],
    [4,5,5],
    [1,2,2]
])

a_with_buffer = a.buffer(a, 1) # 2nd argument refers to the buffer size

Then a_with_buffer would look as following:

[0,0,0,0,0]
[0,1,4,5,0],
[0,4,5,5,0],
[0,1,2,2,0],
[0,0,0,0,0]

CodePudding user response：

You can use np.pad:

>>> np.pad(a, 1)
array([[0, 0, 0, 0, 0],
       [0, 1, 4, 5, 0],
       [0, 4, 5, 5, 0],
       [0, 1, 2, 2, 0],
       [0, 0, 0, 0, 0]])

CodePudding user response：

you can create np.zeros then insert a in the index what you want like below.

Try this:

>>> a = np.array([[1,4,5],[4,5,5],[1,2,2]])

>>> b = np.zeros((5,5))

>>> b[1:1 a.shape[0],1:1 a.shape[1]] = a

>>> b
array([[0., 0., 0., 0., 0.],
       [0., 1., 4., 5., 0.],
       [0., 4., 5., 5., 0.],
       [0., 1., 2., 2., 0.],
       [0., 0., 0., 0., 0.]])