
"""simple docstring"""





def       __a	(						__lowerCamelCase    ):
   if not isinstance(__lowerCamelCase,						__lowerCamelCase    ):
      raise ValueError("Input series is not valid, valid series - [1, 2/3, 2]"    )
   if len(__lowerCamelCase    ) == 0:
      raise ValueError("Input list must be a non empty list"    )
   if len(__lowerCamelCase    ) == 1 and series[0] != 0:
      return True
   UpperCAmelCase_   :   Any     	=       []
   UpperCAmelCase_   :   Optional[Any]     	=       len(__lowerCamelCase    )
   for i in range(0,						__lowerCamelCase    ):
      if series[i] == 0:
         raise ValueError("Input series cannot have 0 as an element"    )
      rec_series.append(1 / series[i]    )
   UpperCAmelCase_   :   str     	=       rec_series[1] - rec_series[0]
   for index in range(2,						__lowerCamelCase    ):
      if rec_series[index] - rec_series[index - 1] != common_diff:
         return False
   return True







def       __a	(						__lowerCamelCase    ):
   if not isinstance(__lowerCamelCase,						__lowerCamelCase    ):
      raise ValueError("Input series is not valid, valid series - [2, 4, 6]"    )
   if len(__lowerCamelCase    ) == 0:
      raise ValueError("Input list must be a non empty list"    )
   UpperCAmelCase_   :   Dict     	=       0
   for val in series:
      answer += 1 / val
   return len(__lowerCamelCase    ) / answer


if __name__ == "__main__":
    import doctest

    doctest.testmod()




"""simple docstring"""





import cva
import numpy as np







def       __a	(						__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase    ):

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







def       __a	(						__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase    ):
   UpperCAmelCase_   :   Optional[int]     	=       image[x_coordinate][y_coordinate]
   UpperCAmelCase_   :   int     	=       [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_   :   List[Any]     	=       [
       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.
    _a									=				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
    _a									=				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]):
            _a									=				local_binary_value(image, i, j)

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


