




'''simple docstring'''



import cva
import numpy as np







def 			_UpperCamelCase (_lowerCamelCase							:     np.ndarray   ,	_lowerCamelCase							:     int   ,	_lowerCamelCase							:     int   ,	_lowerCamelCase							:     int	)->   int:




     '''simple docstring'''





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







def 			_UpperCamelCase (_lowerCamelCase							:     np.ndarray   ,	_lowerCamelCase							:     int   ,	_lowerCamelCase							:     int	)->   int:




     '''simple docstring'''





     __snake_case    					=  image[x_coordinate][y_coordinate]
     __snake_case    					=  [1, 2, 4, 8, 16, 32, 64, 1_28]

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

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

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


if __name__ == "__main__":
     # Reading the image and converting it to grayscale.
     UpperCAmelCase_       :  str      =		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
     UpperCAmelCase_       :  List[str]      =		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]):
               UpperCAmelCase_       :  Optional[int]      =		local_binary_value(image, i, j)

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





'''simple docstring'''



from datetime import date

import requests

UpperCAmelCase_       :  str      =		'''https://api.carbonintensity.org.uk/intensity'''







def 			_UpperCamelCase ()->   str:




     '''simple docstring'''





     __snake_case    					=  requests.get(_lowerCamelCase	).json()['''data'''][0]
     return last_half_hour["intensity"]["actual"]







def 			_UpperCamelCase (_lowerCamelCase							:     Dict   ,	_lowerCamelCase							:     List[Any]	)->   list:




     '''simple docstring'''





     return requests.get(f'''{BASE_URL}/{start}/{end}'''	).json()["data"]


if __name__ == "__main__":
     for entry in fetch_from_to(start=date(2_0_2_0, 1_0, 1), end=date(2_0_2_0, 1_0, 3)):
          print('''from {from} to {to}: {intensity[actual]}'''.format(**entry))
     print(F"""{fetch_last_half_hour() = }""")






