
from __future__ import annotations

import pandas as pd






def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)		->		list[int]:
					'''simple docstring'''


					SCREAMING_SNAKE_CASE__													= [0] * no_of_processes
					SCREAMING_SNAKE_CASE__													= [0] * no_of_processes
					# Copy the burst time into remaining_time[]
					for i in range(UpperCamelCase_		):
										SCREAMING_SNAKE_CASE__													= burst_time[i]

					SCREAMING_SNAKE_CASE__													= 0
					SCREAMING_SNAKE_CASE__													= 0
					SCREAMING_SNAKE_CASE__													= 999999999
					SCREAMING_SNAKE_CASE__													= 0
					SCREAMING_SNAKE_CASE__													= False

					# Process until all processes are completed
					while complete != no_of_processes:
										for j in range(UpperCamelCase_		):
															if arrival_time[j] <= increment_time and remaining_time[j] > 0:
																				if remaining_time[j] < minm:
																									SCREAMING_SNAKE_CASE__													= remaining_time[j]
																									SCREAMING_SNAKE_CASE__													= j
																									SCREAMING_SNAKE_CASE__													= True

										if not check:
															increment_time += 1
															continue
										remaining_time[short] -= 1

										SCREAMING_SNAKE_CASE__													= remaining_time[short]
										if minm == 0:
															SCREAMING_SNAKE_CASE__													= 999999999

										if remaining_time[short] == 0:
															complete += 1
															SCREAMING_SNAKE_CASE__													= False

															# Find finish time of current process
															SCREAMING_SNAKE_CASE__													= increment_time + 1

															# Calculate waiting time
															SCREAMING_SNAKE_CASE__													= finish_time - arrival_time[short]
															SCREAMING_SNAKE_CASE__													= finar - burst_time[short]

															if waiting_time[short] < 0:
																				SCREAMING_SNAKE_CASE__													= 0

        # Increment time
										increment_time += 1
					return waiting_time






def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)		->		list[int]:
					'''simple docstring'''


					SCREAMING_SNAKE_CASE__													= [0] * no_of_processes
					for i in range(UpperCamelCase_		):
										SCREAMING_SNAKE_CASE__													= burst_time[i] + waiting_time[i]
					return turn_around_time






def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)		->		None:
					'''simple docstring'''


					SCREAMING_SNAKE_CASE__													= 0
					SCREAMING_SNAKE_CASE__													= 0
					for i in range(UpperCamelCase_		):
										SCREAMING_SNAKE_CASE__													= total_waiting_time + waiting_time[i]
										SCREAMING_SNAKE_CASE__													= total_turn_around_time + turn_around_time[i]
					print(F'Average waiting time = {total_waiting_time / no_of_processes:.5f}'		)
					print('Average turn around time ='	,	total_turn_around_time / no_of_processes		)


if __name__ == "__main__":
				print("""Enter how many process you want to analyze""")
				__snake_case								=  int(input())
				__snake_case								=  [0] * no_of_processes
				__snake_case								=  [0] * no_of_processes
				__snake_case								=  list(range(1, no_of_processes + 1))

				for i in range(no_of_processes):
								print("""Enter the arrival time and burst time for process:--""" + str(i + 1))
								__snake_case	,__snake_case								=  map(int, input().split())

				__snake_case								=  calculate_waitingtime(arrival_time, burst_time, no_of_processes)

				__snake_case								=  burst_time
				__snake_case								=  no_of_processes
				__snake_case								=  waiting_time
				__snake_case								=  calculate_turnaroundtime(bt, n, wt)

				calculate_average_times(waiting_time, turn_around_time, no_of_processes)

				__snake_case								=  pd.DataFrame(
				    list(zip(processes, burst_time, arrival_time, waiting_time, turn_around_time)),
				    columns=[
				        """Process""",
				        """BurstTime""",
				        """ArrivalTime""",
				        """WaitingTime""",
				        """TurnAroundTime""",
				    ],
				)

				# Printing the dataFrame
				pd.set_option("""display.max_rows""", fcfs.shape[0] + 1)
				print(fcfs)







def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)		->		int:
					'''simple docstring'''


					def update_area_of_max_square(UpperCamelCase_	,	UpperCamelCase_		) -> int:
										# BASE CASE
										if row >= rows or col >= cols:
															return 0

										SCREAMING_SNAKE_CASE__													= update_area_of_max_square(UpperCamelCase_	,	col + 1		)
										SCREAMING_SNAKE_CASE__													= update_area_of_max_square(row + 1	,	col + 1		)
										SCREAMING_SNAKE_CASE__													= update_area_of_max_square(row + 1	,	UpperCamelCase_		)

										if mat[row][col]:
															SCREAMING_SNAKE_CASE__													= 1 + min([right, diagonal, down]		)
															SCREAMING_SNAKE_CASE__													= max(largest_square_area[0]	,	UpperCamelCase_		)
															return sub_problem_sol
										else:
															return 0

					SCREAMING_SNAKE_CASE__													= [0]
					update_area_of_max_square(0	,	0		)
					return largest_square_area[0]






def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)		->		int:
					'''simple docstring'''


					def update_area_of_max_square_using_dp_array(
					    UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		) -> int:
										if row >= rows or col >= cols:
															return 0
										if dp_array[row][col] != -1:
															return dp_array[row][col]

										SCREAMING_SNAKE_CASE__													= update_area_of_max_square_using_dp_array(UpperCamelCase_	,	col + 1	,	UpperCamelCase_		)
										SCREAMING_SNAKE_CASE__													= update_area_of_max_square_using_dp_array(row + 1	,	col + 1	,	UpperCamelCase_		)
										SCREAMING_SNAKE_CASE__													= update_area_of_max_square_using_dp_array(row + 1	,	UpperCamelCase_	,	UpperCamelCase_		)

										if mat[row][col]:
															SCREAMING_SNAKE_CASE__													= 1 + min([right, diagonal, down]		)
															SCREAMING_SNAKE_CASE__													= max(largest_square_area[0]	,	UpperCamelCase_		)
															SCREAMING_SNAKE_CASE__													= sub_problem_sol
															return sub_problem_sol
										else:
															return 0

					SCREAMING_SNAKE_CASE__													= [0]
					SCREAMING_SNAKE_CASE__													= [[-1] * cols for _ in range(UpperCamelCase_		)]
					update_area_of_max_square_using_dp_array(0	,	0	,	UpperCamelCase_		)

					return largest_square_area[0]






def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)		->		int:
					'''simple docstring'''


					SCREAMING_SNAKE_CASE__													= [[0] * (cols + 1) for _ in range(rows + 1		)]
					SCREAMING_SNAKE_CASE__													= 0
					for row in range(rows - 1	,	-1	,	-1		):
										for col in range(cols - 1	,	-1	,	-1		):
															SCREAMING_SNAKE_CASE__													= dp_array[row][col + 1]
															SCREAMING_SNAKE_CASE__													= dp_array[row + 1][col + 1]
															SCREAMING_SNAKE_CASE__													= dp_array[row + 1][col]

															if mat[row][col] == 1:
																				SCREAMING_SNAKE_CASE__													= 1 + min(UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)
																				SCREAMING_SNAKE_CASE__													= max(dp_array[row][col]	,	UpperCamelCase_		)
															else:
																				SCREAMING_SNAKE_CASE__													= 0

					return largest_square_area






def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)		->		int:
					'''simple docstring'''


					SCREAMING_SNAKE_CASE__													= [0] * (cols + 1)
					SCREAMING_SNAKE_CASE__													= [0] * (cols + 1)
					SCREAMING_SNAKE_CASE__													= 0
					for row in range(rows - 1	,	-1	,	-1		):
										for col in range(cols - 1	,	-1	,	-1		):
															SCREAMING_SNAKE_CASE__													= current_row[col + 1]
															SCREAMING_SNAKE_CASE__													= next_row[col + 1]
															SCREAMING_SNAKE_CASE__													= next_row[col]

															if mat[row][col] == 1:
																				SCREAMING_SNAKE_CASE__													= 1 + min(UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)
																				SCREAMING_SNAKE_CASE__													= max(current_row[col]	,	UpperCamelCase_		)
															else:
																				SCREAMING_SNAKE_CASE__													= 0
										SCREAMING_SNAKE_CASE__													= current_row

					return largest_square_area


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				print(largest_square_area_in_matrix_bottom_up(2, 2, [[1, 1], [1, 1]]))





