


from __future__ import annotations

import random




class A  :
      UpperCamelCase__							:  Union[str, Any]				=6






      def __init__( self						:					Dict			) ->						List[Any]:
             """simple docstring"""




             _lowerCamelCase	:		Optional[int]          =list(range(1      ,       Dice.NUM_SIDES + 1			)			)






      def 	lowerCamelCase	( self						:					Tuple			) ->						Optional[Any]:
             """simple docstring"""




             return random.choice(self.sides			)




def      a_				(   SCREAMING_SNAKE_CASE__ :				int		,      SCREAMING_SNAKE_CASE__ :				int = 2					):
       '''simple docstring'''





       _lowerCamelCase	:		Tuple          =[Dice() for i in range(snake_case__					)]
       _lowerCamelCase	:		List[str]          =[0] * (len(snake_case__					) * Dice.NUM_SIDES + 1)
       for _ in range(snake_case__					):
              count_of_sum[sum(dice.roll() for dice in dices					)] += 1
       _lowerCamelCase	:		Any          =[round((count * 100) / num_throws		,      2					) for count in count_of_sum]
       return probability[num_dice:]  # remove probability of sums that never appear


if __name__ == "__main__":
 import doctest

 doctest.testmod()






import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey

from digital_image_processing.filters.convolve import img_convolve




def      a_				(   SCREAMING_SNAKE_CASE__ :				Optional[Any]					):
       '''simple docstring'''





       _lowerCamelCase	:		List[str]          =np.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]]					)
       _lowerCamelCase	:		Dict          =np.array([[1, 2, 1], [0, 0, 0], [-1, -2, -1]]					)

       _lowerCamelCase	:		Optional[Any]          =np.abs(img_convolve(SCREAMING_SNAKE_CASE__		,      SCREAMING_SNAKE_CASE__					)					)
       _lowerCamelCase	:		Optional[int]          =np.abs(img_convolve(SCREAMING_SNAKE_CASE__		,      SCREAMING_SNAKE_CASE__					)					)
       # modify the pix within [0, 255]
       _lowerCamelCase	:		Optional[int]          =dst_x * 255 / np.max(SCREAMING_SNAKE_CASE__					)
       _lowerCamelCase	:		Any          =dst_y * 255 / np.max(SCREAMING_SNAKE_CASE__					)

       _lowerCamelCase	:		Tuple          =np.sqrt((np.square(SCREAMING_SNAKE_CASE__					)) + (np.square(SCREAMING_SNAKE_CASE__					))					)
       _lowerCamelCase	:		int          =dst_xy * 255 / np.max(SCREAMING_SNAKE_CASE__					)
       _lowerCamelCase	:		int          =dst_xy.astype(np.uinta					)

       _lowerCamelCase	:		Optional[int]          =np.arctana(SCREAMING_SNAKE_CASE__		,      SCREAMING_SNAKE_CASE__					)
       return dst, theta


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

 lowerCamelCase ,    lowerCamelCase						 =	sobel_filter(gray)

 # show result images
 imshow('sobel filter', sobel_grad)
 imshow('sobel theta', sobel_theta)
 waitKey(0)


