lab 2 WIP

This commit is contained in:
Dario Mantegazza 2020-10-19 17:25:30 +02:00
parent af0a5c7e4e
commit 6947aaacb1
5 changed files with 26 additions and 77 deletions

View file

@ -9,7 +9,7 @@
}
},
"source": [
"## First Tutorial\n",
"## First Lab\n",
"\n",
"What we are going to do today:\n",
"- read TSP data\n",

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@ -1,60 +0,0 @@
{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {
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},
"source": [
"## First Lecture\n",
"What we are going to do today:\n",
"- read TSP data\n",
"- store nodes in data structure\n",
"- plot raw data\n",
"- define distance function\n",
"- create distance matrix\n",
"- generate naive solution \n",
"- check if the solution is valid\n",
"- evaluate solution!"
]
},
{
"cell_type": "markdown",
"source": [
"### Read TSP data\n"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Read TSP data\n"
]
}
],
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"display_name": "Python 3",
"language": "python",
"name": "python3"
},
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"file_extension": ".py",
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"nbformat_minor": 1
}

6
run.py
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@ -1,7 +1,7 @@
import glob
import pandas as pd
from src.io_tsp import ProblemInstance
from src.TSP_solver import SolverTSP, available_improvers, available_solvers
from src.TSP_solver import TSPSolver, available_improvers, available_solvers
import numpy as np
@ -38,7 +38,7 @@ def run(show_plots=False, verbose=False):
for solver_name in solvers_names:
for improve in improvers_names:
solver = SolverTSP(solver_name, prob_instance)
solver = TSPSolver(solver_name, prob_instance)
use_solver_to_compute_solution(solver, improve, index, results, problem_path, verbose, show_plots)
for improve2 in [j for j in improvers_names if j not in [improve]]:
use_solver_to_compute_solution(solver, improve2, index, results, problem_path, verbose, show_plots)
@ -51,7 +51,7 @@ def run(show_plots=False, verbose=False):
solver.pop()
if prob_instance.exist_opt and show_plots:
solver = SolverTSP("optimal", prob_instance)
solver = TSPSolver("optimal", prob_instance)
solver.solved = True
solver.solution = np.concatenate([prob_instance.optimal_tour, [prob_instance.optimal_tour[0]]])
solver.plot_solution()

View file

@ -18,9 +18,15 @@ available_improvers = {"2-opt": loop2opt,
"simulated_annealing": sa}
class SolverTSP:
def __init__(self, algorithm_name, problem_instance):
class TSPSolver:
def __init__(self, algorithm_name, problem_instance, passed_avail_solvers=None, passed_avail_improvers=None):
# assert algorithm_name in available_solvers, f"the {algorithm_name} initializer is not available currently."
if passed_avail_improvers is None:
passed_avail_improvers = available_improvers
if passed_avail_solvers is None:
passed_avail_solvers = available_solvers
self.available_improvers = passed_avail_improvers
self.available_solvers = passed_avail_solvers
self.duration = np.inf
self.found_length = np.inf
self.algorithm_name = algorithm_name
@ -31,7 +37,7 @@ class SolverTSP:
self.solution = None
def bind(self, local_or_meta):
assert local_or_meta in available_improvers, f"the {local_or_meta} method is not available currently."
assert local_or_meta in self.available_improvers, f"the {local_or_meta} method is not available currently."
self.algorithms.append(local_or_meta)
self.name_method += ", improved with " + local_or_meta
@ -45,11 +51,11 @@ class SolverTSP:
if verbose:
print(f"### solving with {self.algorithms} ####")
start_time = t()
self.solution = available_solvers[self.algorithms[0]](self.problem_instance)
assert self.check_if_solution_is_valid(self.solution), "Error the solution is not valid"
self.solution = self.available_solvers[self.algorithms[0]](self.problem_instance)
assert self.check_if_solution_is_valid(), "Error the solution is not valid"
for i in range(1, len(self.algorithms)):
self.solution = available_improvers[self.algorithms[i]](self.solution, self.problem_instance)
assert self.check_if_solution_is_valid(self.solution), "Error the solution is not valid"
self.solution = self.available_improvers[self.algorithms[i]](self.solution, self.problem_instance)
assert self.check_if_solution_is_valid(), "Error the solution is not valid"
end_time = t()
self.duration = np.around(end_time - start_time, 3)
@ -68,11 +74,11 @@ class SolverTSP:
plt.plot(ordered_points[:, 1], ordered_points[:, 2], 'b-')
plt.show()
def check_if_solution_is_valid(self, solution):
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(
[1 if np.sum(solution[:-1] == i) == 1 else 0 for i in np.arange(self.problem_instance.nPoints)])
[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):

View file

@ -10,8 +10,10 @@ class ProblemInstance:
self.exist_opt = False
self.optimal_tour = None
self.dist_matrix = None
# read raw data
file_object = open(name_tsp)
self.file_name = name_tsp
file_object = open(self.file_name)
data = file_object.read()
file_object.close()
self.lines = data.splitlines()
@ -30,9 +32,10 @@ class ProblemInstance:
self.points[i, 2] = line_i[2]
self.create_dist_matrix()
if name_tsp in ["./problems/eil76.tsp", "./problems/kroA100.tsp"]:
if self.file_name in ["./problems/eil76.tsp", "./problems/kroA100.tsp", "../problems/eil76.tsp",
"../problems/kroA100.tsp"]:
self.exist_opt = True
file_object = open(name_tsp.replace(".tsp", ".opt.tour"))
file_object = open(self.file_name.replace(".tsp", ".opt.tour"))
data = file_object.read()
file_object.close()
lines = data.splitlines()
@ -50,7 +53,7 @@ class ProblemInstance:
print('best_sol: ' + str(self.best_sol))
print('exist optimal: ' + str(self.exist_opt))
def plot_data(self,show_numbers=False):
def plot_data(self, show_numbers=False):
plt.figure(figsize=(8, 8))
plt.title(self.name)
plt.scatter(self.points[:, 1], self.points[:, 2])