
"""simple docstring"""





import numpy as np

_a									=				[
    ['a', 'b', 'c', 'd', 'e'],
    ['f', 'g', 'h', 'i', 'k'],
    ['l', 'm', 'n', 'o', 'p'],
    ['q', 'r', 's', 't', 'u'],
    ['v', 'w', 'x', 'y', 'z'],
]


class A_      :




  '''simple docstring'''







  def __init__(						self    ):

     """simple docstring"""
     UpperCAmelCase_   :   int     	=       np.array(lowercase_    )







  def 			UpperCamelCase__   (						self							,  lowercase_    ):

     """simple docstring"""
     UpperCAmelCase_	,  UpperCAmelCase_   :   int     	=       np.where(letter == self.SQUARE    )
     UpperCAmelCase_   :   Optional[Any]     	=       np.concatenate([indexa + 1, indexa + 1]    )
     return indexes







  def 			UpperCamelCase__   (						self							,  lowercase_							,  lowercase_    ):

     """simple docstring"""
     return self.SQUARE[indexa - 1, indexa - 1]







  def 			UpperCamelCase__   (						self							,  lowercase_    ):

     """simple docstring"""
     UpperCAmelCase_   :   Union[str, Any]     	=       message.lower()
     UpperCAmelCase_   :   int     	=       message.replace("j"							,  "i"    )

     UpperCAmelCase_   :   Union[str, Any]     	=       ""
     for letter_index in range(len(lowercase_    )    ):
        if message[letter_index] != " ":
           UpperCAmelCase_   :   List[Any]     	=       self.letter_to_numbers(message[letter_index]    )
           UpperCAmelCase_   :   Dict     	=       encoded_message + str(numbers[0]    ) + str(numbers[1]    )
        elif message[letter_index] == " ":
           UpperCAmelCase_   :   int     	=       encoded_message + " "

     return encoded_message







  def 			UpperCamelCase__   (						self							,  lowercase_    ):

     """simple docstring"""
     UpperCAmelCase_   :   Any     	=       message.replace(" "							,  "  "    )
     UpperCAmelCase_   :   List[Any]     	=       ""
     for numbers_index in range(int(len(lowercase_    ) / 2    )    ):
        if message[numbers_index * 2] != " ":
           UpperCAmelCase_   :   List[Any]     	=       message[numbers_index * 2]
           UpperCAmelCase_   :   Dict     	=       message[numbers_index * 2 + 1]

           UpperCAmelCase_   :   Tuple     	=       self.numbers_to_letter(int(lowercase_    )							,  int(lowercase_    )    )
           UpperCAmelCase_   :   List[Any]     	=       decoded_message + letter
        elif message[numbers_index * 2] == " ":
           UpperCAmelCase_   :   Optional[Any]     	=       decoded_message + " "

     return decoded_message









import numpy as np






def 				_lowerCAmelCase			(	_a :       Optional[int]       , _a :       str      )						->      Union[str, Any]:
     lowerCAmelCase_       :							int			 =		np.array(_a      )
     lowerCAmelCase_       :							str			 =		np.array(_a      )

     lowerCAmelCase_       :							Optional[Any]			 =		abs(predict - actual      )
     lowerCAmelCase_       :							Dict			 =		difference.mean()

     return score






def 				_lowerCAmelCase			(	_a :       Union[str, Any]       , _a :       int      )						->      Tuple:
     lowerCAmelCase_       :							int			 =		np.array(_a      )
     lowerCAmelCase_       :							int			 =		np.array(_a      )

     lowerCAmelCase_       :							Union[str, Any]			 =		predict - actual
     lowerCAmelCase_       :							Tuple			 =		np.square(_a      )

     lowerCAmelCase_       :							Tuple			 =		square_diff.mean()
     return score






def 				_lowerCAmelCase			(	_a :       Optional[Any]       , _a :       Tuple      )						->      Optional[int]:
     lowerCAmelCase_       :							Optional[Any]			 =		np.array(_a      )
     lowerCAmelCase_       :							Optional[Any]			 =		np.array(_a      )

     lowerCAmelCase_       :							int			 =		predict - actual
     lowerCAmelCase_       :							Any			 =		np.square(_a      )
     lowerCAmelCase_       :							Union[str, Any]			 =		square_diff.mean()
     lowerCAmelCase_       :							Optional[Any]			 =		np.sqrt(_a      )
     return score






def 				_lowerCAmelCase			(	_a :       Optional[Any]       , _a :       Optional[Any]      )						->      List[Any]:
     lowerCAmelCase_       :							Dict			 =		np.array(_a      )
     lowerCAmelCase_       :							List[Any]			 =		np.array(_a      )

     lowerCAmelCase_       :							str			 =		np.log(predict + 1      )
     lowerCAmelCase_       :							Any			 =		np.log(actual + 1      )

     lowerCAmelCase_       :							List[str]			 =		log_predict - log_actual
     lowerCAmelCase_       :							Dict			 =		np.square(_a      )
     lowerCAmelCase_       :							Optional[Any]			 =		square_diff.mean()

     lowerCAmelCase_       :							int			 =		np.sqrt(_a      )

     return score






def 				_lowerCAmelCase			(	_a :       str       , _a :       List[Any]      )						->      int:
     lowerCAmelCase_       :							Any			 =		np.array(_a      )
     lowerCAmelCase_       :							Optional[int]			 =		np.array(_a      )

     lowerCAmelCase_       :							Optional[int]			 =		predict - actual
     lowerCAmelCase_       :							str			 =		np.sum(_a      ) / len(_a      )
     lowerCAmelCase_       :							List[str]			 =		np.sum(_a      ) / len(_a      )
     # print(numerator, denumerator)
     lowerCAmelCase_       :							int			 =		float(_a      ) / denumerator * 1_00

     return score







def 				_lowerCAmelCase			(	_a :       Any       , _a :       Union[str, Any]      )						->      str:
     return np.mean(np.array(_a      ) == np.array(_a      )      )
