'''simple docstring'''

import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey







class     _lowercase					:


 '''simple docstring'''






 def __init__(				self       :     Optional[Any]				,	SCREAMING_SNAKE_CASE__       :     Any				,	SCREAMING_SNAKE_CASE__       :     int							)  ->   Any:
  __lowerCAmelCase    							=						0
  # max greyscale value for #FFFFFF
  __lowerCAmelCase    							=						int(self.get_greyscale(2_55				,	2_55				,	2_55							)							)

  if not self.min_threshold < threshold < self.max_threshold:
   __lowerCAmelCase    							=						f"""Factor value should be from 0 to {self.max_threshold}"""
   raise ValueError(SCREAMING_SNAKE_CASE__							)

  __lowerCAmelCase    							=						input_img
  __lowerCAmelCase    							=						threshold
  __lowerCAmelCase							,	__lowerCAmelCase    							=						self.input_img.shape[1], self.input_img.shape[0]

  # error table size (+4 columns and +1 row) greater than input image because of
  # lack of if statements
  __lowerCAmelCase    							=						[
      [0 for _ in range(self.height + 4							)] for __ in range(self.width + 1							)
  ]
  __lowerCAmelCase    							=						np.ones((self.width, self.height, 3)				,	np.uinta							) * 2_55
 @classmethod
 def a (				cls       :     Optional[int]				,	SCREAMING_SNAKE_CASE__       :     int				,	SCREAMING_SNAKE_CASE__       :     int				,	SCREAMING_SNAKE_CASE__       :     int							)  ->   float:
  return 0.1_1_4 * blue + 0.5_8_7 * green + 0.2_1_2_6 * red





 def a (				self       :     List[Any]							)  ->   None:
  for y in range(self.height							):
   for x in range(self.width							):
    __lowerCAmelCase    							=						int(self.get_greyscale(*self.input_img[y][x]							)							)
    if self.threshold > greyscale + self.error_table[y][x]:
     __lowerCAmelCase    							=						(0, 0, 0)
     __lowerCAmelCase    							=						greyscale + self.error_table[x][y]
    else:
     __lowerCAmelCase    							=						(2_55, 2_55, 2_55)
     __lowerCAmelCase    							=						greyscale + self.error_table[x][y] - 2_55
    self.error_table[y][x + 1] += int(8 / 32 * current_error							)
    self.error_table[y][x + 2] += int(4 / 32 * current_error							)
    self.error_table[y + 1][x] += int(8 / 32 * current_error							)
    self.error_table[y + 1][x + 1] += int(4 / 32 * current_error							)
    self.error_table[y + 1][x + 2] += int(2 / 32 * current_error							)
    self.error_table[y + 1][x - 1] += int(4 / 32 * current_error							)
    self.error_table[y + 1][x - 2] += int(2 / 32 * current_error							)


if __name__ == "__main__":
 # create Burke's instances with original images in greyscale
 _A      :				Optional[Any] 				=    [
     Burkes(imread('''image_data/lena.jpg''', 1), threshold)
     for threshold in (1, 126, 130, 140)
 ]

 for burkes in burkes_instances:
  burkes.process()

 for burkes in burkes_instances:
  imshow(
      f'Original image with dithering threshold: {burkes.threshold}',
      burkes.output_img,
  )

 waitKey(0)
 destroyAllWindows()







'''simple docstring'''

import functools
from math import sqrt
from time import time







def 					UpperCamelCase_						( snake_case_	:	Dict						,		*snake_case_	:	Union[str, Any]						,		**snake_case_	:	List[str]				) ->					List[str]:






 '''simple docstring'''

 __lowerCAmelCase    							=						time()
 __lowerCAmelCase    							=						func(*snake_case_						,		**snake_case_				)
 __lowerCAmelCase    							=						time()
 if int(end - start				) > 0:
  print(f"""{func.__name__} runtime: {(end - start):0.4f} s"""				)
 else:
  print(f"""{func.__name__} runtime: {(end - start) * 10_00:0.4f} ms"""				)
 return output







def 					UpperCamelCase_						( snake_case_	:	int				) ->					list[int]:






 '''simple docstring'''

 if n < 0:
  raise Exception("""n is negative"""				)
 if n == 0:
  return [0]
 __lowerCAmelCase    							=						[0, 1]
 for _ in range(n - 1				):
  fib.append(fib[-1] + fib[-2]				)
 return fib







def 					UpperCamelCase_						( snake_case_	:	int				) ->					list[int]:






 '''simple docstring'''

 def fib_recursive_term(snake_case_	:	int				) -> int:
  if i < 0:
   raise Exception("""n is negative"""				)
  if i < 2:
   return i
  return fib_recursive_term(i - 1				) + fib_recursive_term(i - 2				)

 if n < 0:
  raise Exception("""n is negative"""				)
 return [fib_recursive_term(snake_case_				) for i in range(n + 1				)]







def 					UpperCamelCase_						( snake_case_	:	int				) ->					list[int]:






 '''simple docstring'''

 @functools.cache
 def fib_recursive_term(snake_case_	:	int				) -> int:
  if i < 0:
   raise Exception("""n is negative"""				)
  if i < 2:
   return i
  return fib_recursive_term(i - 1				) + fib_recursive_term(i - 2				)

 if n < 0:
  raise Exception("""n is negative"""				)
 return [fib_recursive_term(snake_case_				) for i in range(n + 1				)]







def 					UpperCamelCase_						( snake_case_	:	int				) ->					list[int]:






 '''simple docstring'''

 if n < 0:
  raise Exception("""n is negative"""				)
 # Cache must be outside recursuive function
 # other it will reset every time it calls itself.
 __lowerCAmelCase    							=						{0: 0, 1: 1, 2: 1}  # Prefilled cache

 def rec_fn_memoized(snake_case_	:	int				) -> int:
  if num in cache:
   return cache[num]

  __lowerCAmelCase    							=						rec_fn_memoized(num - 1				) + rec_fn_memoized(num - 2				)
  __lowerCAmelCase    							=						value
  return value

 return [rec_fn_memoized(snake_case_				) for i in range(n + 1				)]







def 					UpperCamelCase_						( snake_case_	:	int				) ->					list[int]:






 '''simple docstring'''

 if n < 0:
  raise Exception("""n is negative"""				)
 if n >= 14_75:
  raise Exception("""n is too large"""				)
 __lowerCAmelCase    							=						sqrt(5				)
 __lowerCAmelCase    							=						(1 + sqrt_a) / 2
 return [round(phi**i / sqrt_a				) for i in range(n + 1				)]


if __name__ == "__main__":
 _A      :				Optional[Any] 				=    30
 time_func(fib_iterative, num)
 time_func(fib_recursive, num)  # Around 3s runtime
 time_func(fib_recursive_cached, num)  # Around 0ms runtime
 time_func(fib_memoization, num)
 time_func(fib_binet, num)






