

"""simple docstring"""


from __future__ import annotations

import numpy as np
from numpy import floataa
from numpy.typing import NDArray




def  _lowercase					(    __lowerCAmelCase  ,					__lowerCAmelCase  ,					__lowerCAmelCase  ,					__lowerCAmelCase  ,					)       ->				list[float]:
      SCREAMING_SNAKE_CASE__		,		SCREAMING_SNAKE_CASE__   :      List[str]      		=	coefficient_matrix.shape
      SCREAMING_SNAKE_CASE__		,		SCREAMING_SNAKE_CASE__   :      List[str]      		=	constant_matrix.shape

      if rowsa != colsa:
            SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	F'''Coefficient matrix dimensions must be nxn but received {rowsa}x{colsa}'''
            raise ValueError(__lowerCAmelCase							)

      if colsa != 1:
            SCREAMING_SNAKE_CASE__   :      int      		=	F'''Constant matrix must be nx1 but received {rowsa}x{colsa}'''
            raise ValueError(__lowerCAmelCase							)

      if rowsa != rowsa:
            SCREAMING_SNAKE_CASE__   :      Any      		=	(
                """Coefficient and constant matrices dimensions must be nxn and nx1 but """
                F'''received {rowsa}x{colsa} and {rowsa}x{colsa}'''
            )
            raise ValueError(__lowerCAmelCase							)

      if len(__lowerCAmelCase							) != rowsa:
            SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	(
                """Number of initial values must be equal to number of rows in coefficient """
                F'''matrix but received {len(__lowerCAmelCase							)} and {rowsa}'''
            )
            raise ValueError(__lowerCAmelCase							)

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

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

      SCREAMING_SNAKE_CASE__		,		SCREAMING_SNAKE_CASE__   :      Any      		=	table.shape

      strictly_diagonally_dominant(__lowerCAmelCase							)

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

      return [float(__lowerCAmelCase							) for i in new_val]




def  _lowercase					(    __lowerCAmelCase							)       ->				bool:
      SCREAMING_SNAKE_CASE__		,		SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	table.shape

      SCREAMING_SNAKE_CASE__   :      List[Any]      		=	True

      for i in range(0  ,					__lowerCAmelCase							):
            SCREAMING_SNAKE_CASE__   :      Dict      		=	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 re
from pathlib import Path
from unittest import TestCase

import pytest

@pytest.mark.integration
class      __a							(UpperCamelCase_):






     '''simple docstring'''

     def 					_a			(						self	,    _a  )  ->      Union[str, Any]:


           """simple docstring"""


           with open(_a	,    encoding="""utf-8"""  ) as input_file:
                 SCREAMING_SNAKE_CASE__   :      str      		=	re.compile(r"""(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)"""  )
                 SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	input_file.read()
                 SCREAMING_SNAKE_CASE__   :      str      		=	regexp.search(_a  )

           return match

     def 					_a			(						self	,    _a  )  ->      Optional[Any]:


           """simple docstring"""


           with open(_a	,    encoding="""utf-8"""  ) as input_file:
                 SCREAMING_SNAKE_CASE__   :      Tuple      		=	re.compile(r"""#[^\r\n]*print\(|\"[^\r\n]*print\(|\"\"\".*?print\(.*?\"\"\"|(print\()"""	,    re.DOTALL  )
                 SCREAMING_SNAKE_CASE__   :      List[Any]      		=	input_file.read()
                 # use `re.finditer` to handle the case where the ignored groups would be matched first by `re.search`
                 SCREAMING_SNAKE_CASE__   :      Dict      		=	regexp.finditer(_a  )

           SCREAMING_SNAKE_CASE__   :      int      		=	[match for match in matches if match is not None and match.group(1  ) is not None]
           return matches[0] if matches else None

     def 					_a			(						self  )  ->      str:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	Path("""./datasets"""  )
           SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	list(dataset_paths.absolute().glob("""**/*.py"""  )  )

           for dataset in dataset_files:
                 if self._no_encoding_on_file_open(str(_a  )  ):
                       raise AssertionError(f'''open(...) must use utf-8 encoding in {dataset}'''  )





     def 					_a			(						self  )  ->      Dict:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	Path("""./datasets"""  )
           SCREAMING_SNAKE_CASE__   :      List[str]      		=	list(dataset_paths.absolute().glob("""**/*.py"""  )  )

           for dataset in dataset_files:
                 if self._no_print_statements(str(_a  )  ):
                       raise AssertionError(f'''print statement found in {dataset}. Use datasets.logger/logging instead.'''  )




