#!/usr/bin/env python3
# -*- coding: utf-8 -*-
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"""file containing the solver for the optimization of the integer program
"""
from itertools import permutations
from typing import Callable
import numpy as np
[docs]
def find_parameter_sets(
parameter: list,
validation_func: Callable,
) -> list[list]:
"""find_parameter_sets executes a modified backtracking algorithms to find all
validated parameter sets
:param parameter: an initial parameter set
:param validation_func: a function to validate the current parameter_set
:return: a list of all validated parameter sets
"""
def next_branch(parameter: list, level: int) -> list:
"""the next_branch function increases the parameter in the level and
sets all others to 1, which can be interpreted as switching to the next upper
branch in the backtracking algorithm
:param parameter: a list with parameter
:param level: each parameter with its index represent a level in a search tree
:returns: new set of parameter
"""
parameter[level] += 1
for i in range(level):
parameter[i] = 1
return parameter
# condition to stop the backtracking algorithm
# max_level is max_index in uml diagram
max_level = len(parameter) - 1
# condition the move to the next upper branch in the search tree
max_value = np.inf
level = 0
parameter_list = []
while True:
max_para = max(parameter)
# if false move to next upper branch
if max_para <= max_value:
# test all validation function
if validation_func(parameter):
parameter_list.append(parameter.copy())
max_value = max(parameter) - 1
level += 1
parameter = next_branch(parameter, level)
level = 0
else:
parameter[level] += 1
else:
level = parameter.index(max_para) + 1
if level > max_level:
break
parameter = next_branch(parameter, level)
level = 0
solution = []
# add to found solution all permutations
for para in parameter_list:
# the set cast speeds up the whole permutation process
solution.extend(list(set(permutations(para))))
return solution