
from __future__ import annotations

import time

import numpy as np

snake_case :		Union[str, Any]							      =  [8, 5, 9, 7]
snake_case :		Dict							      =  [
    [2, 0, 1, 1],
    [0, 1, 2, 1],
    [4, 0, 0, 3],
    [0, 2, 1, 0],
    [1, 0, 3, 0],
]
snake_case :		Optional[Any]							      =  [
    [3, 2, 1, 4],
    [0, 2, 5, 2],
    [5, 1, 0, 5],
    [1, 5, 3, 0],
    [3, 0, 3, 3],
]





class       _snake_case					:







			def __init__(				self						,   _a						,   _a						,   _a						,   ):
				__magic_name__		:		List[str]	   =     claim_vector
				__magic_name__		:		Union[str, Any]	   =     allocated_resources_table
				__magic_name__		:		List[str]	   =     maximum_claim_table







			def 			SCREAMING_SNAKE_CASE    (				self		):
				return [
				    sum(p_item[i] for p_item in self.__allocated_resources_table		)
				    for i in range(len(self.__allocated_resources_table[0]		)		)
				]







			def 			SCREAMING_SNAKE_CASE    (				self		):
				return np.array(self.__claim_vector		) - np.array(
				    self.__processes_resource_summation()		)







			def 			SCREAMING_SNAKE_CASE    (				self		):
				return [
				    list(np.array(self.__maximum_claim_table[i]		) - np.array(_a		)		)
				    for i, allocated_resource in enumerate(self.__allocated_resources_table		)
				]







			def 			SCREAMING_SNAKE_CASE    (				self		):
				return {self.__need().index(_a		): i for i in self.__need()}







			def 			SCREAMING_SNAKE_CASE    (				self						,   **_a		):
				__magic_name__		:		Dict	   =     self.__need()
				__magic_name__		:		int	   =     self.__allocated_resources_table
				__magic_name__		:		str	   =     self.__available_resources()
				__magic_name__		:		Union[str, Any]	   =     self.__need_index_manager()
				for kw, val in kwargs.items():
					if kw and val is True:
						self.__pretty_data()
				print("_" * 50 + "\n"		)
				while need_list:
					__magic_name__		:		Tuple	   =     False
					for each_need in need_list:
						__magic_name__		:		Tuple	   =     True
						for index, need in enumerate(_a		):
							if need > available_resources[index]:
								__magic_name__		:		Any	   =     False
								break
						if execution:
							__magic_name__		:		Optional[int]	   =     True
							# get the original index of the process from ind_ctrl db
							for original_need_index, need_clone in need_index_manager.items():
								if each_need == need_clone:
									__magic_name__		:		Optional[Any]	   =     original_need_index
							print(f'''Process {process_number + 1} is executing.'''		)
							# remove the process run from stack
							need_list.remove(_a		)
							# update available/freed resources stack
							__magic_name__		:		Optional[Any]	   =     np.array(_a		) + np.array(
							    alloc_resources_table[process_number]		)
							print(
							    "Updated available resource stack for processes: "
							    + " ".join([str(_a		) for x in available_resources]		)		)
							break
					if safe:
						print("The process is in a safe state.\n"		)
					else:
						print("System in unsafe state. Aborting...\n"		)
						break







			def 			SCREAMING_SNAKE_CASE    (				self		):
				print(" " * 9 + "Allocated Resource Table"		)
				for item in self.__allocated_resources_table:
					print(
					    f'''P{self.__allocated_resources_table.index(_a		) + 1}'''
					    + " ".join(f'''{it:>8}''' for it in item		)
					    + "\n"		)
				print(" " * 9 + "System Resource Table"		)
				for item in self.__maximum_claim_table:
					print(
					    f'''P{self.__maximum_claim_table.index(_a		) + 1}'''
					    + " ".join(f'''{it:>8}''' for it in item		)
					    + "\n"		)
				print(
				    "Current Usage by Active Processes: "
				    + " ".join(str(_a		) for x in self.__claim_vector		)		)
				print(
				    "Initial Available Resources:       "
				    + " ".join(str(_a		) for x in self.__available_resources()		)		)
				time.sleep(1		)


if __name__ == "__main__":
				import doctest

				doctest.testmod()



def 					__lowerCamelCase	( UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__      ):







							'''simple docstring'''






							global f  # a global dp table for knapsack
							if f[i][j] < 0:
														if j < wt[i - 1]:
																					snake_case_							=    mf_knapsack(i - 1   ,							UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__      )
														else:
																					snake_case_							=    max(
																					    mf_knapsack(i - 1   ,							UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__      )   ,							mf_knapsack(i - 1   ,							UpperCamelCase__   ,							UpperCamelCase__   ,							j - wt[i - 1]      ) + val[i - 1]   ,							)
														snake_case_							=    val
							return f[i][j]





def 					__lowerCamelCase	( UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__      ):







							'''simple docstring'''






							snake_case_							=    [[0] * (w + 1) for _ in range(n + 1      )]

							for i in range(1   ,							n + 1      ):
														for w_ in range(1   ,							w + 1      ):
																					if wt[i - 1] <= w_:
																												snake_case_							=    max(val[i - 1] + dp[i - 1][w_ - wt[i - 1]]   ,							dp[i - 1][w_]      )
																					else:
																												snake_case_							=    dp[i - 1][w_]

							return dp[n][w_], dp





def 					__lowerCamelCase	( UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__      ):







							'''simple docstring'''






							if not (isinstance(UpperCamelCase__   ,							(list, tuple)      ) and isinstance(UpperCamelCase__   ,							(list, tuple)      )):
														raise ValueError(
														    'Both the weights and values vectors must be either lists or tuples'      )

							snake_case_							=    len(UpperCamelCase__      )
							if num_items != len(UpperCamelCase__      ):
														snake_case_							=    (
														    'The number of weights must be the same as the number of values.\n'
														    F'''But got {num_items} weights and {len(UpperCamelCase__      )} values'''
														)
														raise ValueError(UpperCamelCase__      )
							for i in range(UpperCamelCase__      ):
														if not isinstance(wt[i]   ,							UpperCamelCase__      ):
																					snake_case_							=    (
																					    'All weights must be integers but got weight of '
																					    F'''type {type(wt[i]      )} at index {i}'''
																					)
																					raise TypeError(UpperCamelCase__      )

							snake_case_				,    snake_case_							=    knapsack(UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__      )
							snake_case_							=    set()
							_construct_solution(UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__      )

							return optimal_val, example_optional_set





def 					__lowerCamelCase	( UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__      ):







							'''simple docstring'''






							if i > 0 and j > 0:
														if dp[i - 1][j] == dp[i][j]:
																					_construct_solution(UpperCamelCase__   ,							UpperCamelCase__   ,							i - 1   ,							UpperCamelCase__   ,							UpperCamelCase__      )
														else:
																					optimal_set.add(UpperCamelCase__      )
																					_construct_solution(UpperCamelCase__   ,							UpperCamelCase__   ,							i - 1   ,							j - wt[i - 1]   ,							UpperCamelCase__      )


if __name__ == "__main__":
					_UpperCAmelCase		:   Tuple										=       [3, 2, 4, 4]
					_UpperCAmelCase		:   Optional[Any]										=       [4, 3, 2, 3]
					_UpperCAmelCase		:   List[str]										=       4
					_UpperCAmelCase		:   str										=       6
					_UpperCAmelCase		:   Tuple										=       [[0] * (w + 1)] + [[0] + [-1] * (w + 1) for _ in range(n + 1)]
					_UpperCAmelCase				,						_UpperCAmelCase		:   List[Any]										=       knapsack(w, wt, val, n)
					print(optimal_solution)
					print(mf_knapsack(n, wt, val, w))  # switched the n and w

					# testing the dynamic programming problem with example
					# the optimal subset for the above example are items 3 and 4
					_UpperCAmelCase				,						_UpperCAmelCase		:   Any										=       knapsack_with_example_solution(w, wt, val)
					assert optimal_solution == 8
					assert optimal_subset == {3, 4}
					print("""optimal_value = """, optimal_solution)
					print("""An optimal subset corresponding to the optimal value""", optimal_subset)




