






'''simple docstring'''




from __future__ import annotations

def 					__lowercase						(			__lowercase   ,  __lowercase = None   ,  __lowercase = None   ,  __lowercase = False   ,  )       ->						tuple[int, float, str]:

      '''simple docstring'''


      _A			     =	cipher_alphabet or [chr(__lowercase       ) for i in range(97   ,  123       )]

      # If the argument is None or the user provided an empty dictionary
      if not frequencies_dict:
            # Frequencies of letters in the english language (how much they show up)
            _A			     =	{
                "a": 0.08497,
                "b": 0.01492,
                "c": 0.02202,
                "d": 0.04253,
                "e": 0.11162,
                "f": 0.02228,
                "g": 0.02015,
                "h": 0.06094,
                "i": 0.07546,
                "j": 0.00153,
                "k": 0.01292,
                "l": 0.04025,
                "m": 0.02406,
                "n": 0.06749,
                "o": 0.07507,
                "p": 0.01929,
                "q": 0.00095,
                "r": 0.07587,
                "s": 0.06327,
                "t": 0.09356,
                "u": 0.02758,
                "v": 0.00978,
                "w": 0.02560,
                "x": 0.00150,
                "y": 0.01994,
                "z": 0.00077,
            }
      else:
            # Custom frequencies dictionary
            _A			     =	frequencies_dict

      if not case_sensitive:
            _A			     =	ciphertext.lower()

      # Chi squared statistic values
      _A			     =	{}

      # cycle through all of the shifts
      for shift in range(len(__lowercase       )       ):
            _A			     =	""

            # decrypt the message with the shift
            for letter in ciphertext:
                  try:
                        # Try to index the letter in the alphabet
                        _A			     =	(alphabet_letters.index(letter.lower()       ) - shift) % len(
                            __lowercase       )
                        decrypted_with_shift += (
                            alphabet_letters[new_key].upper()
                            if case_sensitive and letter.isupper()
                            else alphabet_letters[new_key]
                        )
                  except ValueError:
                        # Append the character if it isn't in the alphabet
                        decrypted_with_shift += letter

            _A			     =	0.0

            # Loop through each letter in the decoded message with the shift
            for letter in decrypted_with_shift:
                  if case_sensitive:
                        _A			     =	letter.lower()
                        if letter in frequencies:
                              # Get the amount of times the letter occurs in the message
                              _A			     =	decrypted_with_shift.lower().count(__lowercase       )

                              # Get the excepcted amount of times the letter should appear based
                              # on letter frequencies
                              _A			     =	frequencies[letter] * occurrences

                              # Complete the chi squared statistic formula
                              _A			     =	((occurrences - expected) ** 2) / expected

                              # Add the margin of error to the total chi squared statistic
                              chi_squared_statistic += chi_letter_value
                  else:
                        if letter.lower() in frequencies:
                              # Get the amount of times the letter occurs in the message
                              _A			     =	decrypted_with_shift.count(__lowercase       )

                              # Get the excepcted amount of times the letter should appear based
                              # on letter frequencies
                              _A			     =	frequencies[letter] * occurrences

                              # Complete the chi squared statistic formula
                              _A			     =	((occurrences - expected) ** 2) / expected

                              # Add the margin of error to the total chi squared statistic
                              chi_squared_statistic += chi_letter_value

        # Add the data to the chi_squared_statistic_values dictionary
            _A			     =	(
                chi_squared_statistic,
                decrypted_with_shift,
            )

      # Get the most likely cipher by finding the cipher with the smallest chi squared
      # statistic
      def chi_squared_statistic_values_sorting_key(__lowercase       ) -> tuple[float, str]:
            return chi_squared_statistic_values[key]

      _A			     =	min(
          __lowercase   ,  key=__lowercase   ,  )

      # Get all the data from the most likely cipher (key, decoded message)
      (
          (
          _A
      )     ,	(
          _A
      )     ,	
      )			     =	chi_squared_statistic_values[most_likely_cipher]

      # Return the data on the most likely shift
      return (
          most_likely_cipher,
          most_likely_cipher_chi_squared_value,
          decoded_most_likely_cipher,
      )








import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Audio, Features, Value
from .base import TaskTemplate



@dataclass(frozen=UpperCAmelCase_	)
class   __lowercase				( UpperCAmelCase_	):




			"""simple docstring"""







			_UpperCAmelCase   :							str										=     field(default='''automatic-speech-recognition'''		,       metadata={'''include_in_asdict_even_if_is_default''': True}	)
			_UpperCAmelCase   :							ClassVar[Features]										=     Features({'''audio''': Audio()}	)
			_UpperCAmelCase   :							ClassVar[Features]										=     Features({'''transcription''': Value('''string'''	)}	)
			_UpperCAmelCase   :							str										=     "audio"
			_UpperCAmelCase   :							str										=     "transcription"



			def        _SCREAMING_SNAKE_CASE			( self  :     Optional[Any]   ,						lowerCAmelCase__  :     int):
									if self.audio_column not in features:
															raise ValueError(F"Column {self.audio_column} is not present in features.")
									if not isinstance(features[self.audio_column]   ,						lowerCAmelCase__):
															raise ValueError(F"Column {self.audio_column} is not an Audio type.")
									SCREAMING_SNAKE_CASE_: Tuple  		=       copy.deepcopy(self)
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       self.input_schema.copy()
									SCREAMING_SNAKE_CASE_: Dict  		=       features[self.audio_column]
									SCREAMING_SNAKE_CASE_: int  		=       input_schema
									return task_template




			@property
			def        _SCREAMING_SNAKE_CASE			( self  :     int):
									return {self.audio_column: "audio", self.transcription_column: "transcription"}






