






from __future__ import annotations

import math
from collections import Counter
from string import ascii_lowercase


def 				__lowerCamelCase     (							__lowerCAmelCase							:					str							)     ->  None:
   __UpperCamelCase	,     __UpperCamelCase	:			Dict					=					analyze_text(__lowerCAmelCase							)
   __UpperCamelCase	:			Tuple					=					list(""" """ + ascii_lowercase							)
   # what is our total sum of probabilities.
   __UpperCamelCase	:			Tuple					=					sum(single_char_strings.values()							)

   # one length string
   __UpperCamelCase	:			Tuple					=					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:
         __UpperCamelCase	:			Dict					=					single_char_strings[ch]
         __UpperCamelCase	:			Optional[int]					=					my_str / all_sum
         my_fir_sum += prob * math.loga(__lowerCAmelCase							)  # entropy formula.

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

   # two len string
   __UpperCamelCase	:			int					=					sum(two_char_strings.values()							)
   __UpperCamelCase	:			Optional[int]					=					0
   # for each alpha (two in size) calculate entropy.
   for cha in my_alphas:
      for cha in my_alphas:
         __UpperCamelCase	:			Dict					=					cha + cha
         if sequence in two_char_strings:
            __UpperCamelCase	:			int					=					two_char_strings[sequence]
            __UpperCamelCase	:			int					=					int(__lowerCAmelCase							) / all_sum
            my_sec_sum += prob * math.loga(__lowerCAmelCase							)

    # 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 				__lowerCamelCase     (							__lowerCAmelCase							:					str							)     ->  tuple[dict, dict]:
   __UpperCamelCase	:			Tuple					=					Counter()  # type: ignore
   __UpperCamelCase	:			str					=					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(__lowerCAmelCase							) - 1							):
      single_char_strings[text[i]] += 1
      two_char_strings[text[i : i + 2]] += 1
   return single_char_strings, two_char_strings


def 				__lowerCamelCase     (							)     ->  Optional[int]:
   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()











import os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


UpperCamelCase    							=      namedtuple(
    '_TestCommandArgs',
    [
        'dataset',
        'name',
        'cache_dir',
        'data_dir',
        'all_configs',
        'save_infos',
        'ignore_verifications',
        'force_redownload',
        'clear_cache',
    ],
    defaults=[None, None, None, False, False, False, False, False],
)


def 				__lowerCamelCase     (							__lowerCAmelCase							:					List[Any]					,							__lowerCAmelCase							:					Any							)     ->  Optional[int]:
   return (abs(source - target							) / target) < 0.01



@pytest.mark.integration
def 				__lowerCamelCase     (							__lowerCAmelCase							:					str							)     ->  Union[str, Any]:
   __UpperCamelCase	:			Dict					=					_TestCommandArgs(dataset=__lowerCAmelCase					,							all_configs=__lowerCAmelCase					,							save_infos=__lowerCAmelCase							)
   __UpperCamelCase	:			List[Any]					=					TestCommand(*__lowerCAmelCase							)
   test_command.run()
   __UpperCamelCase	:			Any					=					os.path.join(__lowerCAmelCase					,							"""README.md"""							)
   assert os.path.exists(__lowerCAmelCase							)
   __UpperCamelCase	:			Optional[int]					=					DatasetInfosDict.from_directory(__lowerCAmelCase							)
   __UpperCamelCase	:			List[Any]					=					DatasetInfosDict(
       {
           """default""": DatasetInfo(
               features=Features(
                   {
                       """tokens""": Sequence(Value("""string"""							)							),
                       """ner_tags""": Sequence(
                           ClassLabel(names=["""O""", """B-PER""", """I-PER""", """B-ORG""", """I-ORG""", """B-LOC""", """I-LOC"""]							)							),
                       """langs""": Sequence(Value("""string"""							)							),
                       """spans""": Sequence(Value("""string"""							)							),
                   }							)					,							splits=[
                   {
                       """name""": """train""",
                       """num_bytes""": 2351563,
                       """num_examples""": 10000,
                   },
                   {
                       """name""": """validation""",
                       """num_bytes""": 238418,
                       """num_examples""": 1000,
                   },
               ]					,							download_size=3940680					,							dataset_size=2589981					,							)
       }							)
   assert dataset_infos.keys() == expected_dataset_infos.keys()
   for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
      __UpperCamelCase	,     __UpperCamelCase	:			Union[str, Any]					=					getattr(dataset_infos["""default"""]					,							__lowerCAmelCase							), getattr(expected_dataset_infos["""default"""]					,							__lowerCAmelCase							)
      if key == "num_bytes":
         assert is_apercent_close(__lowerCAmelCase					,							__lowerCAmelCase							)
      elif key == "splits":
         assert list(__lowerCAmelCase							) == list(__lowerCAmelCase							)
         for split in result:
            assert result[split].name == expected[split].name
            assert result[split].num_examples == expected[split].num_examples
            assert is_apercent_close(result[split].num_bytes					,							expected[split].num_bytes							)
      else:
         result == expected



