




'''simple docstring'''




from __future__ import annotations

from decimal import Decimal

from numpy import array

def 	__UpperCAmelCase       ( __magic_name__						)->    list[list[float]]:



			"""simple docstring"""



			snake_case_				:					Dict   =       Decimal

			# Check if the provided matrix has 2 rows and 2 columns
			# since this implementation only works for 2x2 matrices
			if len(lowercase_						) == 2 and len(matrix[0]						) == 2 and len(matrix[1]						) == 2:
						# Calculate the determinant of the matrix
						snake_case_				:					Optional[int]   =       float(
						    d(matrix[0][0]						) * d(matrix[1][1]						) - d(matrix[1][0]						) * d(matrix[0][1]						)						)
						if determinant == 0:
									raise ValueError("This matrix has no inverse."						)

						# Creates a copy of the matrix with swapped positions of the elements
						snake_case_				:					List[Any]   =       [[0.0, 0.0], [0.0, 0.0]]
						snake_case_				:					int   =       matrix[1][1], matrix[0][0]
						snake_case_				:					List[str]   =       -matrix[1][0], -matrix[0][1]

						# Calculate the inverse of the matrix
						return [
						    [(float(d(lowercase_						)						) / determinant) or 0.0 for n in row] for row in swapped_matrix
						]
			elif (
			    len(lowercase_						) == 3
			    and len(matrix[0]						) == 3
			    and len(matrix[1]						) == 3
			    and len(matrix[2]						) == 3
			):
						# Calculate the determinant of the matrix using Sarrus rule
						snake_case_				:					Optional[int]   =       float(
						    (
						        (d(matrix[0][0]						) * d(matrix[1][1]						) * d(matrix[2][2]						))
						        + (d(matrix[0][1]						) * d(matrix[1][2]						) * d(matrix[2][0]						))
						        + (d(matrix[0][2]						) * d(matrix[1][0]						) * d(matrix[2][1]						))
						    )
						    - (
						        (d(matrix[0][2]						) * d(matrix[1][1]						) * d(matrix[2][0]						))
						        + (d(matrix[0][1]						) * d(matrix[1][0]						) * d(matrix[2][2]						))
						        + (d(matrix[0][0]						) * d(matrix[1][2]						) * d(matrix[2][1]						))
						    )						)
						if determinant == 0:
									raise ValueError("This matrix has no inverse."						)

						# Creating cofactor matrix
						snake_case_				:					Optional[Any]   =       [
						    [d(0.0						), d(0.0						), d(0.0						)],
						    [d(0.0						), d(0.0						), d(0.0						)],
						    [d(0.0						), d(0.0						), d(0.0						)],
						]
						snake_case_				:					Optional[Any]   =       (d(matrix[1][1]						) * d(matrix[2][2]						)) - (
						    d(matrix[1][2]						) * d(matrix[2][1]						)
						)
						snake_case_				:					Optional[int]   =       -(
						    (d(matrix[1][0]						) * d(matrix[2][2]						)) - (d(matrix[1][2]						) * d(matrix[2][0]						))
						)
						snake_case_				:					str   =       (d(matrix[1][0]						) * d(matrix[2][1]						)) - (
						    d(matrix[1][1]						) * d(matrix[2][0]						)
						)
						snake_case_				:					int   =       -(
						    (d(matrix[0][1]						) * d(matrix[2][2]						)) - (d(matrix[0][2]						) * d(matrix[2][1]						))
						)
						snake_case_				:					Optional[int]   =       (d(matrix[0][0]						) * d(matrix[2][2]						)) - (
						    d(matrix[0][2]						) * d(matrix[2][0]						)
						)
						snake_case_				:					List[str]   =       -(
						    (d(matrix[0][0]						) * d(matrix[2][1]						)) - (d(matrix[0][1]						) * d(matrix[2][0]						))
						)
						snake_case_				:					Any   =       (d(matrix[0][1]						) * d(matrix[1][2]						)) - (
						    d(matrix[0][2]						) * d(matrix[1][1]						)
						)
						snake_case_				:					Union[str, Any]   =       -(
						    (d(matrix[0][0]						) * d(matrix[1][2]						)) - (d(matrix[0][2]						) * d(matrix[1][0]						))
						)
						snake_case_				:					List[str]   =       (d(matrix[0][0]						) * d(matrix[1][1]						)) - (
						    d(matrix[0][1]						) * d(matrix[1][0]						)
						)

						# Transpose the cofactor matrix (Adjoint matrix)
						snake_case_				:					str   =       array(lowercase_						)
						for i in range(3						):
									for j in range(3						):
												snake_case_				:					List[str]   =       cofactor_matrix[j][i]

        # Inverse of the matrix using the formula (1/determinant) * adjoint matrix
						snake_case_				:					List[str]   =       array(lowercase_						)
						for i in range(3						):
									for j in range(3						):
												inverse_matrix[i][j] /= d(lowercase_						)

        # Calculate the inverse of the matrix
						return [[float(d(lowercase_						)						) or 0.0 for n in row] for row in inverse_matrix]
			raise ValueError("Please provide a matrix of size 2x2 or 3x3."						)












'''simple docstring'''




from unittest import TestCase

from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters

def 	__UpperCAmelCase       ( )->    int:



			"""simple docstring"""



			snake_case_				:					Any   =       {
			    "repo_name": ["test_repo1", "test_repo2", "test_repo3"],
			    "path": ["test_1.py", "test_2.py", "unit_test.py"],
			    "content": ["a " * 20, "a " * 30, "b " * 7],
			}
			snake_case_				:					int   =       Dataset.from_dict(__magic_name__						)
			return dataset







class    A_	(a_							):
							"""simple docstring"""




							def 							_A	(		self			:List[str]				)				->  str:


										'''simple docstring'''




										snake_case_				:					Union[str, Any]   =       get_dataset()
										snake_case_				:					Optional[int]   =       make_duplicate_clusters(lowerCAmelCase__       ,							0.8_5				)
										self.assertEqual(len(duplicate_clusters[0]				)       ,							2				)






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


										'''simple docstring'''




										snake_case_				:					Optional[int]   =       get_dataset()
										snake_case_,	snake_case_				:					List[Any]   =       deduplicate_dataset(lowerCAmelCase__				)
										self.assertEqual(len(lowerCAmelCase__				)       ,							2				)
										print(lowerCAmelCase__				)
										self.assertEqual(duplicate_clusters[0][0]["copies"]       ,							2				)
										self.assertEqual(duplicate_clusters[0][0]["is_extreme"]       ,							lowerCAmelCase__				)




