

import argparse
from collections import defaultdict
def 						_snake_case(    SCREAMING_SNAKE_CASE__			:	Any    ,			SCREAMING_SNAKE_CASE__			:	Union[str, Any]    ,			SCREAMING_SNAKE_CASE__			:	Tuple    ,			SCREAMING_SNAKE_CASE__			:	Optional[int]    ,			SCREAMING_SNAKE_CASE__			:	Union[str, Any]      )							->      Tuple:





    '''simple docstring'''






    A__          =   f'{file}_{class_name}_{test_name}'
    done_test[_id] += 1

    with open(SCREAMING_SNAKE_CASE__    ,			'r'      ) as f:
        A__          =   f.readlines()

    A__          =   f'class {class_name}('
    A__          =   f'{4 * " "}def {test_name}('
    A__          =   f'{8 * " "}{correct_line.split()[0]}'
    A__          =   f'{16 * " "}{correct_line.split()[0]}'
    A__          =   False
    A__          =   False
    A__          =   False
    A__          =   False
    A__          =   0
    A__          =   0

    A__          =   []
    for line in lines:
        if line.startswith(SCREAMING_SNAKE_CASE__      ):
            A__          =   True
        elif in_class and line.startswith(SCREAMING_SNAKE_CASE__      ):
            A__          =   True
        elif in_class and in_func and (line.startswith(SCREAMING_SNAKE_CASE__      ) or line.startswith(SCREAMING_SNAKE_CASE__      )):
            A__          =   len(line.split(correct_line.split()[0]      )[0]      )
            count += 1

            if count == done_test[_id]:
                A__          =   True

        if in_class and in_func and in_line:
            if ")" not in line:
                continue
            else:
                A__          =   True

        if in_class and in_func and in_line and insert_line:
            new_lines.append(f'{spaces * " "}{correct_line}'      )
            A__          =   A__          =   A__          =   A__          =   False
        else:
            new_lines.append(SCREAMING_SNAKE_CASE__      )

    with open(SCREAMING_SNAKE_CASE__    ,			'w'      ) as f:
        for line in new_lines:
            f.write(SCREAMING_SNAKE_CASE__      )
def 						_snake_case(    SCREAMING_SNAKE_CASE__			:	Union[str, Any]    ,			SCREAMING_SNAKE_CASE__			:	List[Any]=None      )							->      Tuple:





    '''simple docstring'''






    if fail is not None:
        with open(SCREAMING_SNAKE_CASE__    ,			'r'      ) as f:
            A__          =   {l.strip() for l in f.readlines()}
    else:
        A__          =   None

    with open(SCREAMING_SNAKE_CASE__    ,			'r'      ) as f:
        A__          =   f.readlines()

    A__          =   defaultdict(SCREAMING_SNAKE_CASE__      )
    for line in correct_lines:
        A__      ,						A__      ,						A__      ,						A__          =   line.split(';'      )
        if test_failures is None or "::".join([file, class_name, test_name]      ) in test_failures:
            overwrite_file(SCREAMING_SNAKE_CASE__    ,			SCREAMING_SNAKE_CASE__    ,			SCREAMING_SNAKE_CASE__    ,			SCREAMING_SNAKE_CASE__    ,			SCREAMING_SNAKE_CASE__      )


if __name__ == "__main__":
     lowercase_       		=  argparse.ArgumentParser()
     parser.add_argument("--correct_filename", help="filename of tests with expected result")
     parser.add_argument("--fail_filename", help="filename of test failures", type=str, default=None)
     lowercase_       		=  parser.parse_args()

     main(args.correct_filename, args.fail_filename)


import doctest
from collections import deque

import numpy as np







class __snake_case				:




   def __init__(    self			:				Dict      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      [2, 1, 2, -1]
     SCREAMING_SNAKE_CASE__										=      [1, 2, 3, 4]




   def 	__a						(    self			:				int      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      len(self.first_signal      )
     SCREAMING_SNAKE_CASE__										=      len(self.second_signal      )

     SCREAMING_SNAKE_CASE__										=      max(_lowercase       ,	_lowercase      )

     # create a zero matrix of max_length x max_length
     SCREAMING_SNAKE_CASE__										=      [[0] * max_length for i in range(_lowercase      )]

     # fills the smaller signal with zeros to make both signals of same length
     if length_first_signal < length_second_signal:
       self.first_signal += [0] * (max_length - length_first_signal)
     elif length_first_signal > length_second_signal:
       self.second_signal += [0] * (max_length - length_second_signal)
     for i in range(_lowercase      ):
       SCREAMING_SNAKE_CASE__										=      deque(self.second_signal      )
       rotated_signal.rotate(_lowercase      )
       for j, item in enumerate(_lowercase      ):
         matrix[i][j] += item

        # multiply the matrix with the first signal
     SCREAMING_SNAKE_CASE__										=      np.matmul(np.transpose(_lowercase      )       ,	np.transpose(self.first_signal      )      )

     # rounding-off to two decimal places
     return [round(_lowercase       ,	2      ) for i in final_signal]


if __name__ == "__main__":
   doctest.testmod()
