code: 
  
  
  
  
  
  
  __A  							=  10_00
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	float		)  ->							float:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         return x * x
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	List[Any]     ,			A_:	float     ,			A_:	float     ,			A_:	int = 4		)  ->							float:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         assert callable(
             A_		), F'''the function(object) passed should be callable your input : {function}'''
         assert isinstance(A_     ,			(float, int)		), F'''a should be float or integer your input : {a}'''
         assert isinstance(function(A_		)     ,			(float, int)		), (
             "the function should return integer or float return type of your function, "
             F'''{type(A_		)}'''
         )
         assert isinstance(A_     ,			(float, int)		), F'''b should be float or integer your input : {b}'''
         assert (
             isinstance(A_     ,			A_		) and precision > 0
         ), F'''precision should be positive integer your input : {precision}'''
  
         # just applying the formula of simpson for approximate integration written in
         # mentioned article in first comment of this file and above this function
  
         __UpperCAmelCase    							=(b - a) / N_STEPS
         __UpperCAmelCase    							=function(A_		) + function(A_		)
  
         for i in range(1     ,			A_		):
                __UpperCAmelCase    							=a + h * i
                result += function(A_		) * (4 if i % 2 else 2)
  
         result *= h / 3
         return round(A_     ,			A_		)
  
  
  if __name__ == "__main__":
     import doctest
  
     doctest.testmod()
  
  
  
  
  
style_context: 
  
  
  
  
  
  
  from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
  from numpy import divide, inta, multiply, ravel, sort, zeros_like
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	int     ,			A_:	Any=3		)  ->							Dict:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         __UpperCAmelCase    							=int(mask / 2		)
         # copy image size
         __UpperCAmelCase    							=zeros_like(A_		)
         for i in range(A_     ,			gray_img.shape[0] - bd		):
                for j in range(A_     ,			gray_img.shape[1] - bd		):
                       # get mask according with mask
                       __UpperCAmelCase    							=ravel(gray_img[i - bd : i + bd + 1, j - bd : j + bd + 1]		)
                       # calculate mask median
                       __UpperCAmelCase    							=sort(A_		)[inta(divide((multiply(A_     ,			A_		))     ,			2		) + 1		)]
                       __UpperCAmelCase    							=median
         return median_img
  
  
  if __name__ == "__main__":
     # read original image
     __A  							=  imread("../image_data/lena.jpg")
     # turn image in gray scale value
     __A  							=  cvtColor(img, COLOR_BGR2GRAY)
  
     # get values with two different mask size
     __A  							=  median_filter(gray, 3)
     __A  							=  median_filter(gray, 5)
  
     # show result images
     imshow("median filter with 3x3 mask", medianaxa)
     imshow("median filter with 5x5 mask", medianaxa)
     waitKey(0)
  
  
  
  
  