





import numpy as np
from PIL import Image






def     lowerCamelCase__			(__lowerCamelCase,       __lowerCamelCase,       __lowerCamelCase	):
     _SCREAMING_SNAKE_CASE       :	Optional[Any]						    =							np.array(__lowerCamelCase	)
     if arr.shape[0] != arr.shape[1]:
          raise ValueError("The input array is not a square matrix"	)
     _SCREAMING_SNAKE_CASE       :	Any						    =							0
     _SCREAMING_SNAKE_CASE       :	Optional[int]						    =							0
     _SCREAMING_SNAKE_CASE       :	Dict						    =							0
     _SCREAMING_SNAKE_CASE       :	str						    =							0

     # compute the shape of the output matrix
     _SCREAMING_SNAKE_CASE       :	str						    =							(arr.shape[0] - size) // stride + 1
     # initialize the output matrix with zeros of shape maxpool_shape
     _SCREAMING_SNAKE_CASE       :	Optional[int]						    =							np.zeros((maxpool_shape, maxpool_shape)	)

     while i < arr.shape[0]:
          if i + size > arr.shape[0]:
               # if the end of the matrix is reached, break
               break
          while j < arr.shape[1]:
               # if the end of the matrix is reached, break
               if j + size > arr.shape[1]:
                    break
               # compute the maximum of the pooling matrix
               _SCREAMING_SNAKE_CASE       :	Dict						    =							np.max(arr[i : i + size, j : j + size]	)
               # shift the pooling matrix by stride of column pixels
               j += stride
               mat_j += 1

          # shift the pooling matrix by stride of row pixels
          i += stride
          mat_i += 1

          # reset the column index to 0
          _SCREAMING_SNAKE_CASE       :	Optional[Any]						    =							0
          _SCREAMING_SNAKE_CASE       :	Optional[Any]						    =							0

     return updated_arr






def     lowerCamelCase__			(__lowerCamelCase,       __lowerCamelCase,       __lowerCamelCase	):
     _SCREAMING_SNAKE_CASE       :	Optional[Any]						    =							np.array(__lowerCamelCase	)
     if arr.shape[0] != arr.shape[1]:
          raise ValueError("The input array is not a square matrix"	)
     _SCREAMING_SNAKE_CASE       :	Optional[Any]						    =							0
     _SCREAMING_SNAKE_CASE       :	Optional[int]						    =							0
     _SCREAMING_SNAKE_CASE       :	Tuple						    =							0
     _SCREAMING_SNAKE_CASE       :	int						    =							0

     # compute the shape of the output matrix
     _SCREAMING_SNAKE_CASE       :	Tuple						    =							(arr.shape[0] - size) // stride + 1
     # initialize the output matrix with zeros of shape avgpool_shape
     _SCREAMING_SNAKE_CASE       :	List[str]						    =							np.zeros((avgpool_shape, avgpool_shape)	)

     while i < arr.shape[0]:
          # if the end of the matrix is reached, break
          if i + size > arr.shape[0]:
               break
          while j < arr.shape[1]:
               # if the end of the matrix is reached, break
               if j + size > arr.shape[1]:
                    break
               # compute the average of the pooling matrix
               _SCREAMING_SNAKE_CASE       :	Optional[Any]						    =							int(np.average(arr[i : i + size, j : j + size]	)	)
               # shift the pooling matrix by stride of column pixels
               j += stride
               mat_j += 1

          # shift the pooling matrix by stride of row pixels
          i += stride
          mat_i += 1
          # reset the column index to 0
          _SCREAMING_SNAKE_CASE       :	Optional[Any]						    =							0
          _SCREAMING_SNAKE_CASE       :	Optional[int]						    =							0

     return updated_arr


# Main Function
if __name__ == "__main__":
       from doctest import testmod

       testmod(name='avgpooling', verbose=True)

       # Loading the image
       UpperCamelCase__      =Image.open('path_to_image')

       # Converting the image to numpy array and maxpooling, displaying the result
       # Ensure that the image is a square matrix

       Image.fromarray(maxpooling(np.array(image), size=3, stride=2)).show()

       # Converting the image to numpy array and averagepooling, displaying the result
       # Ensure that the image is a square matrix

       Image.fromarray(avgpooling(np.array(image), size=3, stride=2)).show()






import cmath
import math






def     lowerCamelCase__			(__lowerCamelCase,       __lowerCamelCase,       __lowerCamelCase,       __lowerCamelCase	):
     _SCREAMING_SNAKE_CASE       :	Any						    =							math.radians(__lowerCamelCase	)
     _SCREAMING_SNAKE_CASE       :	Tuple						    =							math.radians(__lowerCamelCase	)

     # Convert voltage and current to rectangular form
     _SCREAMING_SNAKE_CASE       :	str						    =							cmath.rect(__lowerCamelCase,       __lowerCamelCase	)
     _SCREAMING_SNAKE_CASE       :	str						    =							cmath.rect(__lowerCamelCase,       __lowerCamelCase	)

     # Calculate apparent power
     return voltage_rect * current_rect


if __name__ == "__main__":
       import doctest

       doctest.testmod()