





"""simple docstring"""




import math
import sys

import cva
import numpy as np






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:np.ndarray   ,   SCREAMING_SNAKE_CASE		:float   )      ->   np.ndarray:
 # For applying gaussian function for each element in matrix.
 __lowerCAmelCase					:	Optional[int]      =       math.sqrt(SCREAMING_SNAKE_CASE   )
 __lowerCAmelCase					:	List[str]      =       1 / (sigma * math.sqrt(2 * math.pi   ))
 return cons * np.exp(-((img / sigma) ** 2) * 0.5   )






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:np.ndarray   ,   SCREAMING_SNAKE_CASE		:int   ,   SCREAMING_SNAKE_CASE		:int   ,   SCREAMING_SNAKE_CASE		:int   )      ->   np.ndarray:
 __lowerCAmelCase					:	Tuple      =       kernel_size // 2
 return img[x - half : x + half + 1, y - half : y + half + 1]






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:int   ,   SCREAMING_SNAKE_CASE		:float   )      ->   np.ndarray:
 # Creates a gaussian kernel of given dimension.
 __lowerCAmelCase					:	int      =       np.zeros((kernel_size, kernel_size)   )
 for i in range(0   ,   SCREAMING_SNAKE_CASE   ):
  for j in range(0   ,   SCREAMING_SNAKE_CASE   ):
   __lowerCAmelCase					:	List[Any]      =       math.sqrt(
       abs(i - kernel_size // 2   ) ** 2 + abs(j - kernel_size // 2   ) ** 2   )
 return vec_gaussian(SCREAMING_SNAKE_CASE   ,   SCREAMING_SNAKE_CASE   )






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:np.ndarray   ,   SCREAMING_SNAKE_CASE		:float   ,   SCREAMING_SNAKE_CASE		:float   ,   SCREAMING_SNAKE_CASE		:int   ,   )      ->   np.ndarray:
 __lowerCAmelCase					:	Optional[int]      =       np.zeros(img.shape   )
 __lowerCAmelCase					:	List[str]      =       get_gauss_kernel(SCREAMING_SNAKE_CASE   ,   SCREAMING_SNAKE_CASE   )
 __lowerCAmelCase					:	Optional[Any]      =       img.shape
 for i in range(kernel_size // 2   ,   size_x - kernel_size // 2   ):
  for j in range(kernel_size // 2   ,   size_y - kernel_size // 2   ):
   __lowerCAmelCase					:	Union[str, Any]      =       get_slice(SCREAMING_SNAKE_CASE   ,   SCREAMING_SNAKE_CASE   ,   SCREAMING_SNAKE_CASE   ,   SCREAMING_SNAKE_CASE   )
   __lowerCAmelCase					:	Union[str, Any]      =       img_s - img_s[kernel_size // 2, kernel_size // 2]
   __lowerCAmelCase					:	Tuple      =       vec_gaussian(SCREAMING_SNAKE_CASE   ,   SCREAMING_SNAKE_CASE   )
   __lowerCAmelCase					:	Optional[Any]      =       np.multiply(SCREAMING_SNAKE_CASE   ,   SCREAMING_SNAKE_CASE   )
   __lowerCAmelCase					:	int      =       np.multiply(SCREAMING_SNAKE_CASE   ,   SCREAMING_SNAKE_CASE   )
   __lowerCAmelCase					:	List[str]      =       np.sum(SCREAMING_SNAKE_CASE   ) / np.sum(SCREAMING_SNAKE_CASE   )
   __lowerCAmelCase					:	str      =       val
 return imga






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:list   )      ->   tuple:
 __lowerCAmelCase					:	Optional[int]      =       args[1] if args[1:] else """../image_data/lena.jpg"""
 __lowerCAmelCase					:	List[Any]      =       float(args[2]   ) if args[2:] else 1.0
 __lowerCAmelCase					:	str      =       float(args[3]   ) if args[3:] else 1.0
 if args[4:]:
  __lowerCAmelCase					:	Union[str, Any]      =       int(args[4]   )
  __lowerCAmelCase					:	Tuple      =       kernel_size + abs(kernel_size % 2 - 1   )
 else:
  __lowerCAmelCase					:	Optional[Any]      =       5
 return filename, spatial_variance, intensity_variance, kernel_size


if __name__ == "__main__":
      _UpperCAmelCase       ,     _UpperCAmelCase       ,     _UpperCAmelCase       ,     _UpperCAmelCase             =							parse_args(sys.argv)
      _UpperCAmelCase             =							cva.imread(filename, 0)
      cva.imshow('input image', img)

      _UpperCAmelCase             =							img / 255
      _UpperCAmelCase             =							out.astype('float32')
      _UpperCAmelCase             =							bilateral_filter(out, spatial_variance, intensity_variance, kernel_size)
      _UpperCAmelCase             =							out * 255
      _UpperCAmelCase             =							np.uinta(out)
      cva.imshow('output image', out)
      cva.waitKey(0)
      cva.destroyAllWindows()






def 	_SCREAMING_SNAKE_CASE		(      )      ->   list[list[int]]:
 return [list(range(1_000 - i   ,   -1_000 - i   ,   -1   )   ) for i in range(1_000   )]


_UpperCAmelCase             =							generate_large_matrix()
_UpperCAmelCase             =							(
    [[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
    [[3, 2], [1, 0]],
    [[7, 7, 6]],
    [[7, 7, 6], [-1, -2, -3]],
    grid,
)






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:list[list[int]]   )      ->   None:
 assert all(row == sorted(SCREAMING_SNAKE_CASE   ,   reverse=SCREAMING_SNAKE_CASE   ) for row in grid   )
 assert all(list(SCREAMING_SNAKE_CASE   ) == sorted(SCREAMING_SNAKE_CASE   ,   reverse=SCREAMING_SNAKE_CASE   ) for col in zip(*SCREAMING_SNAKE_CASE   )   )






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:list[int]   )      ->   int:
 __lowerCAmelCase					:	Optional[int]      =       0
 __lowerCAmelCase					:	Tuple      =       len(SCREAMING_SNAKE_CASE   ) - 1

 # Edge cases such as no values or all numbers are negative.
 if not array or array[0] < 0:
  return 0

 while right + 1 > left:
  __lowerCAmelCase					:	Any      =       (left + right) // 2
  __lowerCAmelCase					:	Optional[int]      =       array[mid]

  # Num must be negative and the index must be greater than or equal to 0.
  if num < 0 and array[mid - 1] >= 0:
   return mid

  if num >= 0:
   __lowerCAmelCase					:	Dict      =       mid + 1
  else:
   __lowerCAmelCase					:	str      =       mid - 1
    # No negative numbers so return the last index of the array + 1 which is the length.
 return len(SCREAMING_SNAKE_CASE   )






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:list[list[int]]   )      ->   int:
 __lowerCAmelCase					:	Any      =       0
 __lowerCAmelCase					:	Union[str, Any]      =       len(grid[0]   )

 for i in range(len(SCREAMING_SNAKE_CASE   )   ):
  __lowerCAmelCase					:	str      =       find_negative_index(grid[i][:bound]   )
  total += bound
 return (len(SCREAMING_SNAKE_CASE   ) * len(grid[0]   )) - total






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:list[list[int]]   )      ->   int:
 return len([number for row in grid for number in row if number < 0]   )






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:list[list[int]]   )      ->   int:
 __lowerCAmelCase					:	List[str]      =       0
 for row in grid:
  for i, number in enumerate(SCREAMING_SNAKE_CASE   ):
   if number < 0:
    total += len(SCREAMING_SNAKE_CASE   ) - i
    break
 return total






def 	_SCREAMING_SNAKE_CASE		(      )      ->   None:
 from timeit import timeit

 print("""Running benchmarks"""   )
 __lowerCAmelCase					:	Tuple      =       (
     """from __main__ import count_negatives_binary_search, """
     """count_negatives_brute_force, count_negatives_brute_force_with_break, grid"""
 )
 for func in (
     "count_negatives_binary_search",  # took 0.7727 seconds
     "count_negatives_brute_force_with_break",  # took 4.6505 seconds
     "count_negatives_brute_force",  # took 12.8160 seconds
 ):
  __lowerCAmelCase					:	Optional[int]      =       timeit(F'''{func}(grid=grid)'''   ,   setup=SCREAMING_SNAKE_CASE   ,   number=500   )
  print(F'''{func}() took {time:0.4f} seconds'''   )


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      benchmark()