

"""simple docstring"""
import cva
import numpy as np




def     __lowerCamelCase  (		UpperCamelCase__				,     UpperCamelCase__				,     UpperCamelCase__				,     UpperCamelCase__      ):


	"""simple docstring"""






	try:
		return int(image[x_coordinate][y_coordinate] >= center      )
	except (IndexError, TypeError):
		return 0




def     __lowerCamelCase  (		UpperCamelCase__				,     UpperCamelCase__				,     UpperCamelCase__      ):


	"""simple docstring"""






	_UpperCAmelCase =						image[x_coordinate][y_coordinate]
	_UpperCAmelCase =						[1, 2, 4, 8, 16, 32, 64, 128]

	# skip get_neighbors_pixel if center is null
	if center is None:
		return 0

	# Starting from the top right, assigning value to pixels clockwise
	_UpperCAmelCase =						[
	    get_neighbors_pixel(UpperCamelCase__				,     x_coordinate - 1				,     y_coordinate + 1				,     UpperCamelCase__      ),
	    get_neighbors_pixel(UpperCamelCase__				,     UpperCamelCase__				,     y_coordinate + 1				,     UpperCamelCase__      ),
	    get_neighbors_pixel(UpperCamelCase__				,     x_coordinate - 1				,     UpperCamelCase__				,     UpperCamelCase__      ),
	    get_neighbors_pixel(UpperCamelCase__				,     x_coordinate + 1				,     y_coordinate + 1				,     UpperCamelCase__      ),
	    get_neighbors_pixel(UpperCamelCase__				,     x_coordinate + 1				,     UpperCamelCase__				,     UpperCamelCase__      ),
	    get_neighbors_pixel(UpperCamelCase__				,     x_coordinate + 1				,     y_coordinate - 1				,     UpperCamelCase__      ),
	    get_neighbors_pixel(UpperCamelCase__				,     UpperCamelCase__				,     y_coordinate - 1				,     UpperCamelCase__      ),
	    get_neighbors_pixel(UpperCamelCase__				,     x_coordinate - 1				,     y_coordinate - 1				,     UpperCamelCase__      ),
	]

	# Converting the binary value to decimal.
	return sum(
	    binary_value * power for binary_value, power in zip(UpperCamelCase__				,     UpperCamelCase__      )      )


if __name__ == "__main__":
			# Reading the image and converting it to grayscale.
			__magic_name__		       =				cva.imread(
			    '''digital_image_processing/image_data/lena.jpg''', cva.IMREAD_GRAYSCALE
			)

			# Create a numpy array as the same height and width of read image
			__magic_name__		       =				np.zeros((image.shape[0], image.shape[1]))

			# Iterating through the image and calculating the
			# local binary pattern value for each pixel.
			for i in range(0, image.shape[0]):
						for j in range(0, image.shape[1]):
									__magic_name__		       =				local_binary_value(image, i, j)

			cva.imshow('''local binary pattern''', lbp_image)
			cva.waitKey(0)
			cva.destroyAllWindows()






"""simple docstring"""
from collections import namedtuple

__magic_name__		       =				namedtuple('''from_to''', '''from_ to''')

__magic_name__		       =				{
    '''atm''': from_to(1, 1),
    '''pascal''': from_to(0.0000098, 10_13_25),
    '''bar''': from_to(0.986923, 1.01325),
    '''kilopascal''': from_to(0.00986923, 101.325),
    '''megapascal''': from_to(9.86923, 0.101325),
    '''psi''': from_to(0.068046, 14.6959),
    '''inHg''': from_to(0.0334211, 29.9213),
    '''torr''': from_to(0.00131579, 7_60),
}




def     __lowerCamelCase  (		UpperCamelCase__				,     UpperCamelCase__				,     UpperCamelCase__      ):


	"""simple docstring"""






	if from_type not in PRESSURE_CONVERSION:
		raise ValueError(
		    f"Invalid 'from_type' value: {from_type!r}  Supported values are:\n"
		    + ", ".join(UpperCamelCase__      )      )
	if to_type not in PRESSURE_CONVERSION:
		raise ValueError(
		    f"Invalid 'to_type' value: {to_type!r}.  Supported values are:\n"
		    + ", ".join(UpperCamelCase__      )      )
	return (
	    value * PRESSURE_CONVERSION[from_type].from_ * PRESSURE_CONVERSION[to_type].to
	)


if __name__ == "__main__":
			import doctest

			doctest.testmod()




