



from __future__ import annotations

import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def 						UpperCamelCase      (  snake_case__			:       Dict			,	snake_case__			:       Optional[Any]			,	snake_case__			:       Tuple			,	snake_case__			:       int			,	)      ->	list[float]:
   UpperCamelCase       :    List[Any]		      =      coefficient_matrix.shape
   UpperCamelCase       :    Dict		      =      constant_matrix.shape

   if rowsa != colsa:
      UpperCamelCase       :    Optional[Any]		      =      F"""Coefficient matrix dimensions must be nxn but received {rowsa}x{colsa}"""
      raise ValueError(__SCREAMING_SNAKE_CASE      )

   if colsa != 1:
      UpperCamelCase       :    str		      =      F"""Constant matrix must be nx1 but received {rowsa}x{colsa}"""
      raise ValueError(__SCREAMING_SNAKE_CASE      )

   if rowsa != rowsa:
      UpperCamelCase       :    Optional[int]		      =      (
          'Coefficient and constant matrices dimensions must be nxn and nx1 but '
          F"""received {rowsa}x{colsa} and {rowsa}x{colsa}"""
      )
      raise ValueError(__SCREAMING_SNAKE_CASE      )

   if len(__SCREAMING_SNAKE_CASE      ) != rowsa:
      UpperCamelCase       :    Any		      =      (
          'Number of initial values must be equal to number of rows in coefficient '
          F"""matrix but received {len(__SCREAMING_SNAKE_CASE      )} and {rowsa}"""
      )
      raise ValueError(__SCREAMING_SNAKE_CASE      )

   if iterations <= 0:
      raise ValueError('Iterations must be at least 1'      )

   UpperCamelCase       :    NDArray[floataa]		      =      np.concatenate(
       (coefficient_matrix, constant_matrix)			,	axis=1      )

   UpperCamelCase       :    Union[str, Any]		      =      table.shape

   strictly_diagonally_dominant(__SCREAMING_SNAKE_CASE      )

   # Iterates the whole matrix for given number of times
   for _ in range(__SCREAMING_SNAKE_CASE      ):
      UpperCamelCase       :    List[Any]		      =      []
      for row in range(__SCREAMING_SNAKE_CASE      ):
         UpperCamelCase       :    Optional[int]		      =      0
         for col in range(__SCREAMING_SNAKE_CASE      ):
            if col == row:
               UpperCamelCase       :    Tuple		      =      table[row][col]
            elif col == cols - 1:
               UpperCamelCase       :    Union[str, Any]		      =      table[row][col]
            else:
               temp += (-1) * table[row][col] * init_val[col]
         UpperCamelCase       :    List[str]		      =      (temp + val) / denom
         new_val.append(__SCREAMING_SNAKE_CASE      )
      UpperCamelCase       :    str		      =      new_val

   return [float(__SCREAMING_SNAKE_CASE      ) for i in new_val]
def 						UpperCamelCase      (  snake_case__			:       Dict      )      ->	bool:
   UpperCamelCase       :    Any		      =      table.shape

   UpperCamelCase       :    int		      =      True

   for i in range(0			,	__SCREAMING_SNAKE_CASE      ):
      UpperCamelCase       :    str		      =      0
      for j in range(0			,	cols - 1      ):
         if i == j:
            continue
         else:
            total += table[i][j]

      if table[i][i] <= total:
         raise ValueError('Coefficient matrix is not strictly diagonally dominant'      )

   return is_diagonally_dominant


# Test Cases
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))
