Start implementing JumpSolver

test/src/problems/test_setcover.jl

@@ -0,0 +1,56 @@
+using PyCall
+
+function test_problems_setcover()
+    test_problems_setcover_generator()
+    test_problems_setcover_model()
+end
+
+function test_problems_setcover_generator()
+    np = pyimport("numpy")
+    scipy_stats = pyimport("scipy.stats")
+    randint = scipy_stats.randint
+    uniform = scipy_stats.uniform
+
+    np.random.seed(42)
+    gen = SetCoverGenerator(
+        n_elements = randint(low = 3, high = 4),
+        n_sets = randint(low = 5, high = 6),
+        costs = uniform(loc = 0.0, scale = 100.0),
+        costs_jitter = uniform(loc = 0.95, scale = 0.10),
+        density = uniform(loc = 0.5, scale = 0),
+        K = uniform(loc = 25, scale = 0),
+        fix_sets = false,
+    )
+    data = gen.generate(2)
+    @test data[1].costs == [136.75, 86.17, 25.71, 27.31, 102.48]
+    @test data[1].incidence_matrix == [
+        1 0 1 0 1
+        1 1 0 0 0
+        1 0 0 1 1
+    ]
+    @test data[2].costs == [63.54, 76.6, 48.09, 74.1, 93.33]
+    @test data[2].incidence_matrix == [
+        1 1 0 1 1
+        0 1 0 1 0
+        0 1 1 0 0
+    ]
+end
+
+function test_problems_setcover_model()
+    data = SetCoverData(
+        costs = [5, 10, 12, 6, 8],
+        incidence_matrix = [
+            1 0 0 1 0
+            1 1 0 0 0
+            0 0 1 1 1
+        ],
+    )
+
+    h5 = H5File(tempname(), "w")
+    model = build_setcover_model(data)
+    model.extract_after_load(h5)
+    model.optimize()
+    model.extract_after_mip(h5)
+    @test h5.get_scalar("mip_obj_value") == 11.0
+    h5.close()
+end