
from __future__ import annotations

from decimal import Decimal

from numpy import array



def 	UpperCamelCase   (							lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						Decimal

					# Check if the provided matrix has 2 rows and 2 columns
					# since this implementation only works for 2x2 matrices
					if len(lowerCAmelCase__		) == 2 and len(matrix[0]		) == 2 and len(matrix[1]		) == 2:
										# Calculate the determinant of the matrix
										lowercase						     =						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
										lowercase						     =						[[0.0, 0.0], [0.0, 0.0]]
										lowercase     ,						lowercase						     =						matrix[1][1], matrix[0][0]
										lowercase     ,						lowercase						     =						-matrix[1][0], -matrix[0][1]

										# Calculate the inverse of the matrix
										return [
										    [(float(d(lowerCAmelCase__		)		) / determinant) or 0.0 for n in row] for row in swapped_matrix
										]
					elif (
					    len(lowerCAmelCase__		) == 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
										lowercase						     =						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
										lowercase						     =						[
										    [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		)],
										]
										lowercase						     =						(d(matrix[1][1]		) * d(matrix[2][2]		)) - (
										    d(matrix[1][2]		) * d(matrix[2][1]		)
										)
										lowercase						     =						-(
										    (d(matrix[1][0]		) * d(matrix[2][2]		)) - (d(matrix[1][2]		) * d(matrix[2][0]		))
										)
										lowercase						     =						(d(matrix[1][0]		) * d(matrix[2][1]		)) - (
										    d(matrix[1][1]		) * d(matrix[2][0]		)
										)
										lowercase						     =						-(
										    (d(matrix[0][1]		) * d(matrix[2][2]		)) - (d(matrix[0][2]		) * d(matrix[2][1]		))
										)
										lowercase						     =						(d(matrix[0][0]		) * d(matrix[2][2]		)) - (
										    d(matrix[0][2]		) * d(matrix[2][0]		)
										)
										lowercase						     =						-(
										    (d(matrix[0][0]		) * d(matrix[2][1]		)) - (d(matrix[0][1]		) * d(matrix[2][0]		))
										)
										lowercase						     =						(d(matrix[0][1]		) * d(matrix[1][2]		)) - (
										    d(matrix[0][2]		) * d(matrix[1][1]		)
										)
										lowercase						     =						-(
										    (d(matrix[0][0]		) * d(matrix[1][2]		)) - (d(matrix[0][2]		) * d(matrix[1][0]		))
										)
										lowercase						     =						(d(matrix[0][0]		) * d(matrix[1][1]		)) - (
										    d(matrix[0][1]		) * d(matrix[1][0]		)
										)

										# Transpose the cofactor matrix (Adjoint matrix)
										lowercase						     =						array(lowerCAmelCase__		)
										for i in range(3		):
															for j in range(3		):
																				lowercase						     =						cofactor_matrix[j][i]

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

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






from statistics import mean

import numpy as np



def 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						0
					# Number of processes finished
					lowercase						     =						0
					# Displays the finished process.
					# If it is 0, the performance is completed if it is 1, before the performance.
					lowercase						     =						[0] * no_of_process
					# List to include calculation results
					lowercase						     =						[0] * no_of_process

					# Sort by arrival time.
					lowercase						     =						[burst_time[i] for i in np.argsort(lowerCAmelCase__		)]
					lowercase						     =						[process_name[i] for i in np.argsort(lowerCAmelCase__		)]
					arrival_time.sort()

					while no_of_process > finished_process_count:
										lowercase						     =						0
										while finished_process[i] == 1:
															i += 1
										if current_time < arrival_time[i]:
															lowercase						     =						arrival_time[i]

										lowercase						     =						0
										# Index showing the location of the process being performed
										lowercase						     =						0
										# Saves the current response ratio.
										lowercase						     =						0
										for i in range(0			,      lowerCAmelCase__		):
															if finished_process[i] == 0 and arrival_time[i] <= current_time:
																				lowercase						     =						(burst_time[i] + (current_time - arrival_time[i])) / burst_time[
																				    i
																				]
															if response_ratio < temp:
																				lowercase						     =						temp
																				lowercase						     =						i

        # Calculate the turn around time
										lowercase						     =						current_time + burst_time[loc] - arrival_time[loc]
										current_time += burst_time[loc]
										# Indicates that the process has been performed.
										lowercase						     =						1
										# Increase finished_process_count by 1
										finished_process_count += 1

					return turn_around_time



def 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						[0] * no_of_process
					for i in range(0			,      lowerCAmelCase__		):
										lowercase						     =						turn_around_time[i] - burst_time[i]
					return waiting_time


if __name__ == "__main__":
							lowercase__		:Dict			  =   5
							lowercase__		:str			  =   ["A", "B", "C", "D", "E"]
							lowercase__		:Optional[int]			  =   [1, 2, 3, 4, 5]
							lowercase__		:List[Any]			  =   [1, 2, 3, 4, 5]

							lowercase__		:List[str]			  =   calculate_turn_around_time(
							    process_name, arrival_time, burst_time, no_of_process
							)
							lowercase__		:List[Any]			  =   calculate_waiting_time(
							    process_name, turn_around_time, burst_time, no_of_process
							)

							print("Process name \tArrival time \tBurst time \tTurn around time \tWaiting time")
							for i in range(0, no_of_process):
														print(
														    F'{process_name[i]}\t\t{arrival_time[i]}\t\t{burst_time[i]}\t\t'
														    F'{turn_around_time[i]}\t\t\t{waiting_time[i]}'
														)

							print(F'average waiting time : {mean(waiting_time):.5f}')
							print(F'average turn around time : {mean(turn_around_time):.5f}')




