Temporarily remove unused files; make package work with Cbc

miplearn/tests/test_solver.py

@@ -0,0 +1,16 @@
+# MIPLearn: A Machine-Learning Framework for Mixed-Integer Optimization
+# Copyright (C) 2019-2020 Argonne National Laboratory. All rights reserved.
+# Written by Alinson S. Xavier <axavier@anl.gov>
+
+from miplearn import LearningSolver
+from miplearn.problems.knapsack import KnapsackInstance2
+
+
+def test_solver():
+    instance = KnapsackInstance2(weights=[23., 26., 20., 18.],
+                                 prices=[505., 352., 458., 220.],
+                                 capacity=67.)
+    solver = LearningSolver()
+    solver.solve(instance)
+    solver.fit()
+    solver.solve(instance)

miplearn/tests/test_transformer.py

@@ -2,19 +2,22 @@
 # Copyright (C) 2019-2020 Argonne National Laboratory. All rights reserved.
 # Written by Alinson S. Xavier <axavier@anl.gov>
 
-from miplearn import Instance, LearningSolver
 from miplearn.transformers import PerVariableTransformer
 from miplearn.problems.knapsack import KnapsackInstance, KnapsackInstance2
 import numpy as np
 import pyomo.environ as pe
 
+
 def test_transform():
     transformer = PerVariableTransformer()
     instance = KnapsackInstance(weights=[23., 26., 20., 18.],
                                 prices=[505., 352., 458., 220.],
                                 capacity=67.)
     model = instance.to_model()
-    
+    solver = pe.SolverFactory('cbc')
+    solver.options["threads"] = 1
+    solver.solve(model)
+
     var_split = transformer.split_variables(instance, model)
     var_split_expected = {
         "default": [
@@ -26,7 +29,7 @@ def test_transform():
     }
     assert var_split == var_split_expected
     var_index_pairs = [(model.x, i) for i in range(4)]
-    
+
     x_actual = transformer.transform_instance(instance, var_index_pairs)
     x_expected = np.array([
         [67., 21.75, 23., 505.],
@@ -34,24 +37,29 @@ def test_transform():
         [67., 21.75, 20., 458.],
         [67., 21.75, 18., 220.],
     ])
-    assert x_expected.tolist() == x_actual.tolist()
-    
-    solver = pe.SolverFactory('cplex')
-    solver.options["threads"] = 1
+    assert x_expected.tolist() == np.round(x_actual, decimals=2).tolist()
+
     solver.solve(model)
-    
     y_actual = transformer.transform_solution(var_index_pairs)
-    y_expected = np.array([1., 0., 1., 1.])
+    y_expected = np.array([
+        [0., 1.],
+        [1., 0.],
+        [0., 1.],
+        [0., 1.],
+    ])
     assert y_actual.tolist() == y_expected.tolist()
-    
-    
+
+
 def test_transform_with_categories():
     transformer = PerVariableTransformer()
     instance = KnapsackInstance2(weights=[23., 26., 20., 18.],
                                  prices=[505., 352., 458., 220.],
                                  capacity=67.)
     model = instance.to_model()
-    
+    solver = pe.SolverFactory('cbc')
+    solver.options["threads"] = 1
+    solver.solve(model)
+
     var_split = transformer.split_variables(instance, model)
     var_split_expected = {
         0: [(model.x, 0)],
@@ -63,13 +71,13 @@ def test_transform_with_categories():
 
     var_index_pairs = var_split[0]
     x_actual = transformer.transform_instance(instance, var_index_pairs)
-    x_expected = np.array([[23., 26., 20., 18., 505., 352., 458., 220.]])
-    assert x_expected.tolist() == x_actual.tolist()
+    x_expected = np.array([
+        [23., 26., 20., 18., 505., 352., 458., 220.]
+    ])
+    assert x_expected.tolist() == np.round(x_actual, decimals=2).tolist()
 
-    solver = pe.SolverFactory('cplex')
-    solver.options["threads"] = 1
     solver.solve(model)
-    
+
     y_actual = transformer.transform_solution(var_index_pairs)
-    y_expected = np.array([1.])
-    assert y_actual.tolist() == y_expected.tolist()
+    y_expected = np.array([[0., 1.]])
+    assert y_actual.tolist() == y_expected.tolist()