


from abc import ABC, abstractmethod
from argparse import ArgumentParser







class     __lowercase    (				SCREAMING_SNAKE_CASE_   ):



		"""simple docstring"""

		@staticmethod
		@abstractmethod
		def  __A					(      A     )   ->      Optional[Any]:







					'''simple docstring'''







					raise NotImplementedError()







		@abstractmethod
		def  __A					(      self     )   ->      int:







					'''simple docstring'''







					raise NotImplementedError()






'''simple docstring'''





from __future__ import annotations

import math
from collections import Counter
from string import ascii_lowercase
def    _SCREAMING_SNAKE_CASE  (       UpperCamelCase			):



    """simple docstring"""





    lowerCAmelCase__      ,   lowerCAmelCase__ :  List[str]							      =					analyze_text(UpperCamelCase			)
    lowerCAmelCase__ :  Optional[int]							      =					list(""" """ + ascii_lowercase			)
    # what is our total sum of probabilities.
    lowerCAmelCase__ :  List[Any]							      =					sum(single_char_strings.values()			)

    # one length string
    lowerCAmelCase__ :  Optional[int]							      =					0
    # for each alpha we go in our dict and if it is in it we calculate entropy
    for ch in my_alphas:
        if ch in single_char_strings:
            lowerCAmelCase__ :  List[Any]							      =					single_char_strings[ch]
            lowerCAmelCase__ :  List[Any]							      =					my_str / all_sum
            my_fir_sum += prob * math.loga(UpperCamelCase			)  # entropy formula.

    # print entropy
    print(f"""{round(-1 * my_fir_sum			):.1f}"""			)

    # two len string
    lowerCAmelCase__ :  Dict							      =					sum(two_char_strings.values()			)
    lowerCAmelCase__ :  int							      =					0
    # for each alpha (two in size) calculate entropy.
    for cha in my_alphas:
        for cha in my_alphas:
            lowerCAmelCase__ :  Union[str, Any]							      =					cha + cha
            if sequence in two_char_strings:
                lowerCAmelCase__ :  Dict							      =					two_char_strings[sequence]
                lowerCAmelCase__ :  Tuple							      =					int(UpperCamelCase			) / all_sum
                my_sec_sum += prob * math.loga(UpperCamelCase			)

    # print second entropy
    print(f"""{round(-1 * my_sec_sum			):.1f}"""			)

    # print the difference between them
    print(f"""{round((-1 * my_sec_sum) - (-1 * my_fir_sum)			):.1f}"""			)
def    _SCREAMING_SNAKE_CASE  (       UpperCamelCase			):



    """simple docstring"""





    lowerCAmelCase__ :  Optional[Any]							      =					Counter()  # type: ignore
    lowerCAmelCase__ :  Tuple							      =					Counter()  # type: ignore
    single_char_strings[text[-1]] += 1

    # first case when we have space at start.
    two_char_strings[" " + text[0]] += 1
    for i in range(0							,    len(UpperCamelCase			) - 1			):
        single_char_strings[text[i]] += 1
        two_char_strings[text[i : i + 2]] += 1
    return single_char_strings, two_char_strings
def    _SCREAMING_SNAKE_CASE  (       ):



    """simple docstring"""





    import doctest

    doctest.testmod()
    # text = (
    #     "Had repulsive dashwoods suspicion sincerity but advantage now him. Remark "
    #     "easily garret nor nay. Civil those mrs enjoy shy fat merry. You greatest "
    #     "jointure saw horrible. He private he on be imagine suppose. Fertile "
    #     "beloved evident through no service elderly is. Blind there if every no so "
    #     "at. Own neglected you preferred way sincerity delivered his attempted. To "
    #     "of message cottage windows do besides against uncivil.  Delightful "
    #     "unreserved impossible few estimating men favourable see entreaties. She "
    #     "propriety immediate was improving. He or entrance humoured likewise "
    #     "moderate. Much nor game son say feel. Fat make met can must form into "
    #     "gate. Me we offending prevailed discovery. "
    # )

    # calculate_prob(text)


if __name__ == "__main__":
 main()


