





import numpy as np
def   _A (	SCREAMING_SNAKE_CASE  :     Any , SCREAMING_SNAKE_CASE  :     Union[str, Any] , SCREAMING_SNAKE_CASE  :     List[Any]		):





  """simple docstring"""



  a__			:      Optional[int]            =n_draws * class_counts / class_counts.sum()
  # floored means we don't overshoot n_samples, but probably undershoot
  a__			:      Any            =np.floor(SCREAMING_SNAKE_CASE		)
  # we add samples according to how much "left over" probability
  # they had, until we arrive at n_samples
  a__			:      int            =int(n_draws - floored.sum()		)
  if need_to_add > 0:
    a__			:      Any            =continuous - floored
    a__			:      Any            =np.sort(np.unique(SCREAMING_SNAKE_CASE		)		)[::-1]
    # add according to remainder, but break ties
    # randomly to avoid biases
    for value in values:
      (a__							)			:      Dict            =np.where(remainder == value		)
      # if we need_to_add less than what's in inds
      # we draw randomly from them.
      # if we need to add more, we add them all and
      # go to the next value
      a__			:      str            =min(len(SCREAMING_SNAKE_CASE		) , SCREAMING_SNAKE_CASE		)
      a__			:      str            =rng.choice(SCREAMING_SNAKE_CASE , size=SCREAMING_SNAKE_CASE , replace=SCREAMING_SNAKE_CASE		)
      floored[inds] += 1
      need_to_add -= add_now
      if need_to_add == 0:
        break
  return floored.astype(np.intaa		)

def   _A (	SCREAMING_SNAKE_CASE  :     Optional[int] , SCREAMING_SNAKE_CASE  :     Tuple , SCREAMING_SNAKE_CASE  :     List[Any] , SCREAMING_SNAKE_CASE  :     Optional[Any] , SCREAMING_SNAKE_CASE  :     List[str]=10		):





  """simple docstring"""



  a__			:      List[Any]            =np.unique(SCREAMING_SNAKE_CASE , return_inverse=SCREAMING_SNAKE_CASE		)
  a__			:      str            =classes.shape[0]
  a__			:      Any            =np.bincount(SCREAMING_SNAKE_CASE		)
  if np.min(SCREAMING_SNAKE_CASE		) < 2:
    raise ValueError("Minimum class count error"		)
  if n_train < n_classes:
    raise ValueError(
        "The train_size = %d should be greater or " "equal to the number of classes = %d" % (n_train, n_classes)		)
  if n_test < n_classes:
    raise ValueError(
        "The test_size = %d should be greater or " "equal to the number of classes = %d" % (n_test, n_classes)		)
  a__			:      List[str]            =np.split(np.argsort(SCREAMING_SNAKE_CASE , kind="mergesort"		) , np.cumsum(SCREAMING_SNAKE_CASE		)[:-1]		)
  for _ in range(SCREAMING_SNAKE_CASE		):
    a__			:      Any            =approximate_mode(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)
    a__			:      Optional[int]            =class_counts - n_i
    a__			:      Optional[int]            =approximate_mode(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)

    a__			:      Tuple            =[]
    a__			:      Optional[Any]            =[]

    for i in range(SCREAMING_SNAKE_CASE		):
      a__			:      List[str]            =rng.permutation(class_counts[i]		)
      a__			:      int            =class_indices[i].take(SCREAMING_SNAKE_CASE , mode="clip"		)
      train.extend(perm_indices_class_i[: n_i[i]]		)
      test.extend(perm_indices_class_i[n_i[i] : n_i[i] + t_i[i]]		)
    a__			:      Dict            =rng.permutation(SCREAMING_SNAKE_CASE		)
    a__			:      Tuple            =rng.permutation(SCREAMING_SNAKE_CASE		)

    yield train, test













from __future__ import annotations
def   _A (	SCREAMING_SNAKE_CASE  :     str , SCREAMING_SNAKE_CASE  :     dict[str, str]		):





  """simple docstring"""



  a__      ,							a__      ,							a__			:      Optional[int]            ="", "", ""
  a__			:      str            =[]

  for character in message_part:
    tmp.append(character_to_number[character]		)

  for each in tmp:
    one += each[0]
    two += each[1]
    three += each[2]

  return one + two + three
def   _A (	SCREAMING_SNAKE_CASE  :     str , SCREAMING_SNAKE_CASE  :     dict[str, str]		):





  """simple docstring"""



  a__      ,							a__			:      Any            ="", ""
  a__			:      Optional[int]            =[]

  for character in message_part:
    this_part += character_to_number[character]

  for digit in this_part:
    tmp += digit
    if len(SCREAMING_SNAKE_CASE		) == len(SCREAMING_SNAKE_CASE		):
      result.append(SCREAMING_SNAKE_CASE		)
      a__			:      str            =""

  return result[0], result[1], result[2]
def   _A (	SCREAMING_SNAKE_CASE  :     str , SCREAMING_SNAKE_CASE  :     str		):





  """simple docstring"""



  a__			:      Optional[Any]            =alphabet.replace(" " , ""		).upper()
  a__			:      List[str]            =message.replace(" " , ""		).upper()

  # Check length and characters
  if len(SCREAMING_SNAKE_CASE		) != 27:
    raise KeyError("Length of alphabet has to be 27."		)
  for each in message:
    if each not in alphabet:
      raise ValueError("Each message character has to be included in alphabet!"		)

    # Generate dictionares
  a__			:      Any            =(
      "111",
      "112",
      "113",
      "121",
      "122",
      "123",
      "131",
      "132",
      "133",
      "211",
      "212",
      "213",
      "221",
      "222",
      "223",
      "231",
      "232",
      "233",
      "311",
      "312",
      "313",
      "321",
      "322",
      "323",
      "331",
      "332",
      "333",
  )
  a__			:      Tuple            ={}
  a__			:      List[str]            ={}
  for letter, number in zip(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		):
    a__			:      Dict            =number
    a__			:      Union[str, Any]            =letter

  return message, alphabet, character_to_number, number_to_character
def   _A (	SCREAMING_SNAKE_CASE  :     str , SCREAMING_SNAKE_CASE  :     str = "ABCDEFGHIJKLMNOPQRSTUVWXYZ." , SCREAMING_SNAKE_CASE  :     int = 5		):





  """simple docstring"""



  a__      ,							a__      ,							a__      ,							a__			:      Union[str, Any]            =__prepare(
      SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)
  a__      ,							a__			:      Union[str, Any]            ="", ""

  for i in range(0 , len(SCREAMING_SNAKE_CASE		) + 1 , SCREAMING_SNAKE_CASE		):
    encrypted_numeric += __encrypt_part(
        message[i : i + period] , SCREAMING_SNAKE_CASE		)

  for i in range(0 , len(SCREAMING_SNAKE_CASE		) , 3		):
    encrypted += number_to_character[encrypted_numeric[i : i + 3]]

  return encrypted
def   _A (	SCREAMING_SNAKE_CASE  :     str , SCREAMING_SNAKE_CASE  :     str = "ABCDEFGHIJKLMNOPQRSTUVWXYZ." , SCREAMING_SNAKE_CASE  :     int = 5		):





  """simple docstring"""



  a__      ,							a__      ,							a__      ,							a__			:      Dict            =__prepare(
      SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)
  a__			:      Optional[Any]            =[]
  a__			:      Any            =""

  for i in range(0 , len(SCREAMING_SNAKE_CASE		) + 1 , SCREAMING_SNAKE_CASE		):
    a__      ,							a__      ,							a__			:      Union[str, Any]            =__decrypt_part(message[i : i + period] , SCREAMING_SNAKE_CASE		)

    for j in range(0 , len(SCREAMING_SNAKE_CASE		)		):
      decrypted_numeric.append(a[j] + b[j] + c[j]		)

  for each in decrypted_numeric:
    decrypted += number_to_character[each]

  return decrypted


if __name__ == "__main__":
     UpperCAmelCase			:			List[str]	  = """DEFEND THE EAST WALL OF THE CASTLE."""
     UpperCAmelCase			:			Optional[Any]	  = encrypt_message(msg, """EPSDUCVWYM.ZLKXNBTFGORIJHAQ""")
     UpperCAmelCase			:			Optional[int]	  = decrypt_message(encrypted, """EPSDUCVWYM.ZLKXNBTFGORIJHAQ""")
     print(F"""Encrypted: {encrypted}\nDecrypted: {decrypted}""")






