How to make a checkerboard in numpy?

Question

I\'m using numpy to initialize a pixel array to a gray checkerboard (the classic representation for \"no pixels\", or transparent). It seems like there ought to be a whizzy

Answer 1

import numpy as np

a=np.array(([1,0]*4+[0,1]*4)*4).reshape((8,8))
print(a)


[[1 0 1 0 1 0 1 0]
 [0 1 0 1 0 1 0 1]
 [1 0 1 0 1 0 1 0]
 [0 1 0 1 0 1 0 1]
 [1 0 1 0 1 0 1 0]
 [0 1 0 1 0 1 0 1]
 [1 0 1 0 1 0 1 0]
 [0 1 0 1 0 1 0 1]]

Answer 2

I recently want the same function and i modified doug's answer a little bit as follows:

def gen_checkerboard(grid_num, grid_size):
    row_even = grid_num/2 * [0,1]
    row_odd = grid_num/2 * [1,0]
    checkerboard = numpy.row_stack(grid_num/2*(row_even, row_odd))
    return checkerboard.repeat(grid_size, axis = 0).repeat(grid_size, axis = 1)

Answer 3

def checkerboard(shape):
    return np.indices(shape).sum(axis=0) % 2

Most compact, probably the fastest, and also the only solution posted that generalizes to n-dimensions.

Answer 4

import numpy as np
x = np.ones((3,3))
print("Checkerboard pattern:")
x = np.zeros((8,8),dtype=int)
# (odd_rows, even_columns)
x[1::2,::2] = 1
# (even_rows, odd_columns)
x[::2,1::2] = 1
print(x)

Answer 5

Very very late, but I needed a solution that allows for a non-unit checker size on an arbitrarily sized checkerboard. Here's a simple and fast solution:

import numpy as np

def checkerboard(shape, dw):
    """Create checkerboard pattern, each square having width ``dw``.

    Returns a numpy boolean array.
    """
    # Create individual block
    block = np.zeros((dw * 2, dw * 2), dtype=bool)
    block[dw:, :dw] = 1
    block[:dw, dw:] = 1

    # Tile until we exceed the size of the mask, then trim
    repeat = (np.array(shape) + dw * 2) // np.array(block.shape)
    trim = tuple(slice(None, s) for s in shape)
    checkers = np.tile(block, repeat)[trim]

    assert checkers.shape == shape
    return checkers

To convert the checkerboard squares to colors, you could do:

checkers = checkerboard(shape, dw)
img = np.empty_like(checkers, dtype=np.uint8)
img[checkers] = 0xAA
img[~checkers] = 0x99

Answer 6

Here is the solution using tile function in numpy.

import numpy as np

x = np.array([[0, 1], [1, 0]])
check = np.tile(x, (n//2, n//2))
# Print the created matrix
print(check)

1. for input 2, the Output is

     [[0 1]
     [1 0]]

2. for input 4, the Output is

     [[0 1 0 1] 
     [1 0 1 0]
     [0 1 0 1]
     [1 0 1 0]]