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lab 2 ready

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This commit is contained in:
Dario Mantegazza 2020-11-01 19:24:26 +01:00
parent 6947aaacb1
commit 4598f90ed7
4 changed files with 906 additions and 121 deletions
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153
Lectures/Student_lecture 1.ipynb
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File diff suppressed because one or more lines are too long

841
Lectures/Student_lecture 2.ipynb
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File diff suppressed because one or more lines are too long

31
src/TSP_solver.py
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@ -52,10 +52,17 @@ class TSPSolver:
print(f"### solving with {self.algorithms} ####") print(f"### solving with {self.algorithms} ####")
start_time = t() start_time = t()
self.solution = self.available_solvers[self.algorithms[0]](self.problem_instance) self.solution = self.available_solvers[self.algorithms[0]](self.problem_instance)
assert self.check_if_solution_is_valid(), "Error the solution is not valid" if self.check_if_solution_is_valid():
print(f"Error the solution of {self.algorithm_name} for problem {self.problem_instance.name} is not valid")
if return_value:
return False
for i in range(1, len(self.algorithms)): for i in range(1, len(self.algorithms)):
self.solution = self.available_improvers[self.algorithms[i]](self.solution, self.problem_instance) improver = self.algorithms[i]
assert self.check_if_solution_is_valid(), "Error the solution is not valid" self.solution = self.available_improvers[improver](self.solution, self.problem_instance)
if self.check_if_solution_is_valid():
print(f"Error the solution of {self.algorithm_name} with {improver} for problem {self.problem_instance.name} is not valid")
if return_value:
return False
end_time = t() end_time = t()
self.duration = np.around(end_time - start_time, 3) self.duration = np.around(end_time - start_time, 3)
@ -75,17 +82,17 @@ class TSPSolver:
plt.show() plt.show()
def check_if_solution_is_valid(self): def check_if_solution_is_valid(self):
# rights_values = np.sum(
# [self.check_validation(i, solution[:-1]) for i in np.arange(self.problem_instance.nPoints)])
rights_values = np.sum( rights_values = np.sum(
[1 if np.sum(self.solution[:-1] == i) == 1 else 0 for i in np.arange(self.problem_instance.nPoints)]) [self.check_validation(i, self.solution[:-1]) for i in np.arange(self.problem_instance.nPoints)])
return rights_values == self.problem_instance.nPoints # rights_values = np.sum(
# [1 if np.sum(self.solution[:-1] == i) == 1 else 0 for i in np.arange(self.problem_instance.nPoints)])
# return rights_values == self.problem_instance.nPoints
# def check_validation(self, node, solution): def check_validation(self, node, solution):
# if np.sum(solution == node) == 1: if np.sum(solution == node) == 1:
# return 1 return 1
# else: else:
# return 0 return 0
def evaluate_solution(self, return_value=False): def evaluate_solution(self, return_value=False):
total_length = 0 total_length = 0

2
src/utils.py
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@ -12,7 +12,7 @@ def compute_length(solution, dist_matrix):
def distance_euc(point_i, point_j): def distance_euc(point_i, point_j):
rounding=0 rounding = 0
x_i, y_i = point_i[0], point_i[1] x_i, y_i = point_i[0], point_i[1]
x_j, y_j = point_j[0], point_j[1] x_j, y_j = point_j[0], point_j[1]
distance = np.sqrt((x_i - x_j) ** 2 + (y_i - y_j) ** 2) distance = np.sqrt((x_i - x_j) ** 2 + (y_i - y_j) ** 2)