problems: Allow correlated arguments in random problem generators

tests/problems/test_multiknapsack.py

@@ -32,6 +32,21 @@ def test_knapsack_generator() -> None:
     ]
 
 
+def test_knapsack_generator_callable() -> None:
+    np.random.seed(42)
+    gen = MultiKnapsackGenerator(
+        n=randint(low=10, high=11),
+        m=lambda n: n // 3,
+        w=randint(low=0, high=1000),
+        K=randint(low=500, high=501),
+        u=uniform(loc=0.0, scale=1.0),
+        alpha=uniform(loc=0.25, scale=0.0),
+    )
+    data = gen.generate(1)[0]
+    assert data.weights.shape[1] == 10
+    assert data.weights.shape[0] == 3
+
+
 def test_knapsack_model() -> None:
     data = MultiKnapsackData(
         prices=np.array([344.0, 527.0, 658.0, 519.0, 460.0]),

tests/problems/test_pmedian.py

@@ -36,3 +36,18 @@ def test_pmedian() -> None:
     assert model.inner.numConstrs == 11
     model.optimize()
     assert round(model.inner.objVal) == 107
+
+
+def test_pmedian_generator_callable() -> None:
+    np.random.seed(42)
+    gen = PMedianGenerator(
+        x=uniform(loc=0.0, scale=100.0),
+        y=uniform(loc=0.0, scale=100.0),
+        n=randint(low=10, high=11),
+        p=lambda n: n // 5,
+        demands=uniform(loc=0, scale=20),
+        capacities=uniform(loc=0, scale=100),
+    )
+    data = gen.generate(1)
+    assert data[0].p == 2
+    assert len(data[0].demands) == 10

tests/problems/test_setcover.py

@@ -35,6 +35,22 @@ def test_set_cover_generator() -> None:
     ]
 
 
+def test_set_cover_generator_callable() -> None:
+    np.random.seed(42)
+    gen = SetCoverGenerator(
+        n_elements=randint(low=4, high=5),
+        n_sets=lambda n: n * 2,
+        costs=uniform(loc=10.0, scale=0.0),
+        density=uniform(loc=0.5, scale=0),
+        K=uniform(loc=0, scale=0),
+    )
+    data = gen.generate(1)
+    n_elements, n_sets = data[0].incidence_matrix.shape
+    assert n_elements == 4
+    assert n_sets == 8
+    assert len(data[0].costs) == 8
+
+
 def test_set_cover() -> None:
     data = SetCoverData(
         costs=np.array([5, 10, 12, 6, 8]),

tests/problems/test_setpack.py

@@ -3,9 +3,11 @@
 #  Released under the modified BSD license. See COPYING.md for more details.
 
 import numpy as np
+from scipy.stats import randint, uniform
 
 from miplearn.problems.setpack import (
     SetPackData,
+    SetPackGenerator,
     build_setpack_model_gurobipy,
 )
 
@@ -24,3 +26,19 @@ def test_setpack() -> None:
     model = build_setpack_model_gurobipy(data)
     model.optimize()
     assert model.inner.objval == -22.0
+
+
+def test_set_pack_generator_callable() -> None:
+    np.random.seed(42)
+    gen = SetPackGenerator(
+        n_elements=randint(low=4, high=5),
+        n_sets=lambda n: n * 2,
+        costs=uniform(loc=10.0, scale=0.0),
+        density=uniform(loc=0.5, scale=0),
+        K=uniform(loc=0, scale=0),
+    )
+    data = gen.generate(1)
+    n_elements, n_sets = data[0].incidence_matrix.shape
+    assert n_elements == 4
+    assert n_sets == 8
+    assert len(data[0].costs) == 8