MIPLearn v0.3

tests/problems/test_binpack.py

@@ -0,0 +1,58 @@
+#  MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
+#  Copyright (C) 2020-2022, UChicago Argonne, LLC. All rights reserved.
+#  Released under the modified BSD license. See COPYING.md for more details.
+
+import numpy as np
+from scipy.stats import uniform, randint
+
+from miplearn.problems.binpack import build_binpack_model, BinPackData, BinPackGenerator
+
+
+def test_binpack_generator() -> None:
+    np.random.seed(42)
+    gen = BinPackGenerator(
+        n=randint(low=10, high=11),
+        sizes=uniform(loc=0, scale=10),
+        capacity=uniform(loc=100, scale=0),
+        sizes_jitter=uniform(loc=0.9, scale=0.2),
+        capacity_jitter=uniform(loc=0.9, scale=0.2),
+        fix_items=True,
+    )
+    data = gen.generate(2)
+    assert data[0].sizes.tolist() == [
+        3.39,
+        10.4,
+        7.81,
+        5.64,
+        1.46,
+        1.46,
+        0.56,
+        8.7,
+        5.93,
+        6.79,
+    ]
+    assert data[0].capacity == 102.24
+    assert data[1].sizes.tolist() == [
+        3.48,
+        9.11,
+        7.12,
+        5.93,
+        1.65,
+        1.47,
+        0.58,
+        8.82,
+        5.47,
+        7.23,
+    ]
+    assert data[1].capacity == 93.41
+
+
+def test_binpack() -> None:
+    model = build_binpack_model(
+        BinPackData(
+            sizes=np.array([4, 8, 1, 4, 2, 1]),
+            capacity=10,
+        )
+    )
+    model.optimize()
+    assert model.inner.objVal == 2.0