



from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros






def      __lowercase       (			a__							,       a__       )    ->			Union[str, Any]:
							__SCREAMING_SNAKE_CASE									= k_size // 2
							__SCREAMING_SNAKE_CASE							,	__SCREAMING_SNAKE_CASE									= mgrid[0 - center : k_size - center, 0 - center : k_size - center]
							__SCREAMING_SNAKE_CASE									= 1 / (2 * pi * sigma) * exp(-(square(a__       ) + square(a__       )) / (2 * square(a__       ))       )
							return g






def      __lowercase       (			a__							,       a__							,       a__       )    ->			List[str]:
							__SCREAMING_SNAKE_CASE							,	__SCREAMING_SNAKE_CASE									= image.shape[0], image.shape[1]
							# dst image height and width
							__SCREAMING_SNAKE_CASE									= height - k_size + 1
							__SCREAMING_SNAKE_CASE									= width - k_size + 1

							# im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
							__SCREAMING_SNAKE_CASE									= zeros((dst_height * dst_width, k_size * k_size)       )
							__SCREAMING_SNAKE_CASE									= 0
							for i, j in product(range(a__       )							,       range(a__       )       ):
														__SCREAMING_SNAKE_CASE									= ravel(image[i : i + k_size, j : j + k_size]       )
														__SCREAMING_SNAKE_CASE									= window
														row += 1

							#  turn the kernel into shape(k*k, 1)
							__SCREAMING_SNAKE_CASE									= gen_gaussian_kernel(a__							,       a__       )
							__SCREAMING_SNAKE_CASE									= ravel(a__       )

							# reshape and get the dst image
							__SCREAMING_SNAKE_CASE									= dot(a__							,       a__       ).reshape(a__							,       a__       ).astype(a__       )

							return dst


if __name__ == "__main__":
			# read original image
			lowerCAmelCase__		:					Tuple							=imread(r'''../image_data/lena.jpg''')
			# turn image in gray scale value
			lowerCAmelCase__		:					Dict							=cvtColor(img, COLOR_BGR2GRAY)

			# get values with two different mask size
			lowerCAmelCase__		:					List[Any]							=gaussian_filter(gray, 3, sigma=1)
			lowerCAmelCase__		:					int							=gaussian_filter(gray, 5, sigma=0.8)

			# show result images
			imshow('''gaussian filter with 3x3 mask''', gaussianaxa)
			imshow('''gaussian filter with 5x5 mask''', gaussianaxa)
			waitKey()











import pytest

from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested

from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows






def      __lowercase       (			a__       )    ->			List[Any]:  # picklable for multiprocessing
							return i + 1






@require_dill_gt_0_3_2
@require_joblibspark
@require_not_windows
def      __lowercase       (			)    ->			Any:
							with parallel_backend('spark'       ):
														assert ParallelBackendConfig.backend_name == "spark"

							__SCREAMING_SNAKE_CASE									= [1, 2, 3]
							with pytest.raises(a__       ):
														with parallel_backend('unsupported backend'       ):
																					map_nested(a__							,       a__							,       num_proc=2       )

							with pytest.raises(a__       ):
														with parallel_backend('unsupported backend'       ):
																					map_nested(a__							,       a__							,       num_proc=-1       )






@require_dill_gt_0_3_2
@require_joblibspark
@require_not_windows
@pytest.mark.parametrize('num_proc'							,       [2, -1]       )
def      __lowercase       (			a__       )    ->			Union[str, Any]:
							__SCREAMING_SNAKE_CASE									= [1, 2]
							__SCREAMING_SNAKE_CASE									= {'a': 1, 'b': 2}
							__SCREAMING_SNAKE_CASE									= {'a': [1, 2], 'b': [3, 4]}
							__SCREAMING_SNAKE_CASE									= {'a': {'1': 1}, 'b': 2}
							__SCREAMING_SNAKE_CASE									= {'a': 1, 'b': 2, 'c': 3, 'd': 4}
							__SCREAMING_SNAKE_CASE									= [2, 3]
							__SCREAMING_SNAKE_CASE									= {'a': 2, 'b': 3}
							__SCREAMING_SNAKE_CASE									= {'a': [2, 3], 'b': [4, 5]}
							__SCREAMING_SNAKE_CASE									= {'a': {'1': 2}, 'b': 3}
							__SCREAMING_SNAKE_CASE									= {'a': 2, 'b': 3, 'c': 4, 'd': 5}

							with parallel_backend('spark'       ):
														assert map_nested(a__							,       a__							,       num_proc=a__       ) == expected_map_nested_sa
														assert map_nested(a__							,       a__							,       num_proc=a__       ) == expected_map_nested_sa
														assert map_nested(a__							,       a__							,       num_proc=a__       ) == expected_map_nested_sa
														assert map_nested(a__							,       a__							,       num_proc=a__       ) == expected_map_nested_sa
														assert map_nested(a__							,       a__							,       num_proc=a__       ) == expected_map_nested_sa






