




'''simple docstring'''






from __future__ import annotations

import numpy as np






def 		UpperCamelCase__      (		__SCREAMING_SNAKE_CASE		)    ->   tuple[np.ndarray, np.ndarray]:
      snake_case__      ,							snake_case__       :   int	      =    np.shape(__SCREAMING_SNAKE_CASE		)
      if rows != columns:
            snake_case__       :   Union[str, Any]	      =    (
                '\'table\' has to be of square shaped array but got a '
                f"{rows}x{columns} array:\n{table}"
            )
            raise ValueError(__SCREAMING_SNAKE_CASE		)

      snake_case__       :   Tuple	      =    np.zeros((rows, columns)		)
      snake_case__       :   Any	      =    np.zeros((rows, columns)		)
      for i in range(__SCREAMING_SNAKE_CASE		):
            for j in range(__SCREAMING_SNAKE_CASE		):
                  snake_case__       :   str	      =    sum(lower[i][k] * upper[k][j] for k in range(__SCREAMING_SNAKE_CASE		)		)
                  if upper[j][j] == 0:
                        raise ArithmeticError('No LU decomposition exists'		)
                  snake_case__       :   Optional[Any]	      =    (table[i][j] - total) / upper[j][j]
            snake_case__       :   Union[str, Any]	      =    1
            for j in range(__SCREAMING_SNAKE_CASE				,      __SCREAMING_SNAKE_CASE		):
                  snake_case__       :   Optional[Any]	      =    sum(lower[i][k] * upper[k][j] for k in range(__SCREAMING_SNAKE_CASE		)		)
                  snake_case__       :   Dict	      =    table[i][j] - total
      return lower, upper


if __name__ == "__main__":
      import doctest

      doctest.testmod()






'''simple docstring'''






import requests
from bsa import BeautifulSoup






def 		UpperCamelCase__      (		__SCREAMING_SNAKE_CASE				,      __SCREAMING_SNAKE_CASE		)    ->   str:
      snake_case__       :   List[Any]	      =    BeautifulSoup(requests.get(__SCREAMING_SNAKE_CASE				,      params=__SCREAMING_SNAKE_CASE		).content				,      'html.parser'		)
      snake_case__       :   Optional[int]	      =    soup.find('div'				,      attrs={'class': 'gs_ri'}		)
      snake_case__       :   Dict	      =    div.find('div'				,      attrs={'class': 'gs_fl'}		).find_all('a'		)
      return anchors[2].get_text()


if __name__ == "__main__":
      A_			      =		{
          "title": (
              "Precisely geometry controlled microsupercapacitors for ultrahigh areal "
              "capacitance, volumetric capacitance, and energy density"
          ),
          "journal": "Chem. Mater.",
          "volume": 30,
          "pages": "3979-3990",
          "year": 2018,
          "hl": "en",
      }
      print(get_citation("https://scholar.google.com/scholar_lookup", params=params))
