Small changes to basemethods and tests

setup.py

@@ -29,7 +29,7 @@
         "Operating System :: OS Independent",
         "Development Status :: 2 - Pre-Alpha",
     ],
-    python_requires=">=3.8",
+    python_requires=">=3.7",
     include_package_data=True,
     install_requires=required,
     extras_require=extra_required,

tsp_solvers/methods/ga.py

@@ -11,7 +11,7 @@
 
 # Import from internal modules
 from tsp_solvers.initializers import NearestNeighbor, RandomInitializer
-from tsp_solvers.methods.base import BaseMethod
+from tsp_solvers.methods.base import BaseSolver
 
 
 class Individual:
@@ -80,7 +80,7 @@ def __str__(self):
         return str(self.genes)
 
 
-class GeneticAlgorithm(BaseMethod):
+class GeneticAlgorithm(BaseSolver):
     def __init__(
         self,
         graph,

tsp_solvers/methods/lp.py

@@ -3,10 +3,10 @@
 
 from pulp import *
 
-from tsp_solvers.methods.base import BaseMethod
+from tsp_solvers.methods.base import BaseSolver
 
 
-class LinearIntegerProgram(BaseMethod):
+class LinearIntegerProgram(BaseSolver):
     def __init__(self, graph, max_time, plot=False):
         super().__init__()
         self.graph = graph

tsp_solvers/methods/lp_dantzig.py

@@ -12,10 +12,10 @@
     PULP_CBC_CMD,
 )
 from pytups import SuperDict
-from tsp_solvers.methods.base import BaseMethod
+from tsp_solvers.methods.base import BaseSolver
 
 
-class LinearIntegerDantzig(BaseMethod):
+class LinearIntegerDantzig(BaseSolver):
     def __init__(self, graph, max_time, plot=False):
         super().__init__()
         self.graph = graph

tsp_solvers/methods/three_opt.py

@@ -2,10 +2,10 @@
 from datetime import datetime
 
 from tsp_solvers.initializers import NearestNeighbor, RandomInitializer
-from tsp_solvers.methods.base import BaseMethod
+from tsp_solvers.methods.base import BaseSolver
 
 
-class ThreeOpt(BaseMethod):
+class ThreeOpt(BaseSolver):
     def __init__(self, graph, max_time, init="random", plot=False):
         super().__init__()
         self.graph = graph

tsp_solvers/methods/three_opt_annealing.py

@@ -3,10 +3,10 @@
 from random import random
 
 from tsp_solvers.initializers import NearestNeighbor, RandomInitializer
-from tsp_solvers.methods.base import BaseMethod
+from tsp_solvers.methods.base import BaseSolver
 
 
-class SimulatedAnnealingThreeOpt(BaseMethod):
+class SimulatedAnnealingThreeOpt(BaseSolver):
     def __init__(self, graph, max_time, init="random", plot=False):
         super().__init__()
         self.graph = graph

tsp_solvers/methods/two_opt.py

@@ -9,10 +9,10 @@
 
 # Import from internal modules
 from tsp_solvers.initializers import NearestNeighbor, RandomInitializer
-from tsp_solvers.methods.base import BaseMethod
+from tsp_solvers.methods.base import BaseSolver
 
 
-class TwoOpt(BaseMethod):
+class TwoOpt(BaseSolver):
     def __init__(self, graph, max_time, init="random", plot=False):
         super().__init__()
         self.graph = graph

tsp_solvers/methods/two_opt_annealing.py

@@ -10,10 +10,10 @@
 
 # Import from internal modules
 from tsp_solvers.initializers import NearestNeighbor, RandomInitializer
-from tsp_solvers.methods.base import BaseMethod
+from tsp_solvers.methods.base import BaseSolver
 
 
-class SimulatedAnnealingTwoOpt(BaseMethod):
+class SimulatedAnnealingTwoOpt(BaseSolver):
     def __init__(self, graph, max_time, init="random", plot=False):
         super().__init__()
         self.graph = graph

tsp_solvers/tests/const.py

@@ -1,6 +1,15 @@
 """
 This file contains the solution of each method 
 """
+import os
+
+# Method to get the files
+path_to_tests_dir = os.path.dirname(os.path.abspath(__file__))
+
+
+def get_test_file(relative_path):
+    return os.path.join(path_to_tests_dir, relative_path)
+
 
 # For the 10 vertex problem
 GA_V10_COST = 54.557082002939914

tsp_solvers/tests/test_ga.py

@@ -5,6 +5,7 @@
     GA_V10_GENES,
     GA_V100_COST,
     GA_V100_GENES,
+    get_test_file,
 )
 from tsp_solvers import Graph
 from tsp_solvers import GeneticAlgorithm
@@ -24,14 +25,14 @@ def tearDown(self):
         pass
 
     def test_ga_10(self):
-        self.g.create_graph_from_json("./tsp_solvers/tests/data/10v.json")
+        self.g.create_graph_from_json(get_test_file("./data/10v.json"))
         ga = GeneticAlgorithm(self.g, 200, 100, 0.1, 120, "nearest")
         ga.run()
         self.assertListEqual(ga.best_genes, GA_V10_GENES)
         self.assertEqual(ga.best_cost, GA_V10_COST)
 
     def test_ga_100(self):
-        self.g.create_graph_from_json("./tsp_solvers/tests/data/100v.json")
+        self.g.create_graph_from_json(get_test_file("./data/100v.json"))
         ga = GeneticAlgorithm(self.g, 200, 100, 0.1, 120, "nearest")
         ga.run()
         self.assertListEqual(ga.best_genes, GA_V100_GENES)