Add _gurobipy suffix to all build_model functions

tests/components/cuts/test_mem.py

@@ -62,7 +62,7 @@ def test_usage_stab(
     stab_pyo_h5: List[str],
     default_extractor: FeaturesExtractor,
 ) -> None:
-    for (h5, build_model) in [
+    for h5, build_model in [
         (stab_pyo_h5, build_stab_model_pyomo),
         (stab_gp_h5, build_stab_model_gurobipy),
     ]:

tests/components/lazy/test_mem.py

@@ -56,7 +56,7 @@ def test_usage_tsp(
     tsp_pyo_h5: List[str],
     default_extractor: FeaturesExtractor,
 ) -> None:
-    for (h5, build_model) in [
+    for h5, build_model in [
         (tsp_pyo_h5, build_tsp_model_pyomo),
         (tsp_gp_h5, build_tsp_model_gurobipy),
     ]:

tests/problems/test_binpack.py

@@ -5,7 +5,11 @@
 import numpy as np
 from scipy.stats import uniform, randint
 
-from miplearn.problems.binpack import build_binpack_model, BinPackData, BinPackGenerator
+from miplearn.problems.binpack import (
+    build_binpack_model_gurobipy,
+    BinPackData,
+    BinPackGenerator,
+)
 
 
 def test_binpack_generator() -> None:
@@ -48,7 +52,7 @@ def test_binpack_generator() -> None:
 
 
 def test_binpack() -> None:
-    model = build_binpack_model(
+    model = build_binpack_model_gurobipy(
         BinPackData(
             sizes=np.array([4, 8, 1, 4, 2, 1]),
             capacity=10,

tests/problems/test_multiknapsack.py

@@ -8,7 +8,7 @@ from scipy.stats import uniform, randint
 from miplearn.problems.multiknapsack import (
     MultiKnapsackGenerator,
     MultiKnapsackData,
-    build_multiknapsack_model,
+    build_multiknapsack_model_gurobipy,
 )
 
 
@@ -56,6 +56,6 @@ def test_knapsack_model() -> None:
             ]
         ),
     )
-    model = build_multiknapsack_model(data)
+    model = build_multiknapsack_model_gurobipy(data)
     model.optimize()
     assert model.inner.objVal == -460.0

tests/problems/test_pmedian.py

@@ -5,7 +5,7 @@
 import numpy as np
 from scipy.stats import uniform, randint
 
-from miplearn.problems.pmedian import PMedianGenerator, build_pmedian_model
+from miplearn.problems.pmedian import PMedianGenerator, build_pmedian_model_gurobipy
 
 
 def test_pmedian() -> None:
@@ -46,7 +46,7 @@ def test_pmedian() -> None:
         [31.95, 17.05, 67.62, 58.88, 0.0],
     ]
 
-    model = build_pmedian_model(data[0])
+    model = build_pmedian_model_gurobipy(data[0])
     assert model.inner.numVars == 30
     assert model.inner.numConstrs == 11
     model.optimize()

tests/problems/test_setpack.py

@@ -6,7 +6,7 @@ import numpy as np
 
 from miplearn.problems.setpack import (
     SetPackData,
-    build_setpack_model,
+    build_setpack_model_gurobipy,
 )
 
 
@@ -21,6 +21,6 @@ def test_setpack() -> None:
             ],
         ),
     )
-    model = build_setpack_model(data)
+    model = build_setpack_model_gurobipy(data)
     model.optimize()
     assert model.inner.objval == -22.0

tests/problems/test_uc.py

@@ -7,7 +7,7 @@ from scipy.stats import uniform, randint
 
 from miplearn.problems.uc import (
     UnitCommitmentData,
-    build_uc_model,
+    build_uc_model_gurobipy,
     UnitCommitmentGenerator,
 )
 
@@ -60,12 +60,12 @@ def test_uc() -> None:
         cost_prod=np.array([1.0, 1.25, 1.5]),
         cost_fixed=np.array([10, 12, 9]),
     )
-    model = build_uc_model(data)
+    model = build_uc_model_gurobipy(data)
     model.optimize()
     assert model.inner.objVal == 154.5
 
 
 if __name__ == "__main__":
     data = UnitCommitmentGenerator().generate(1)[0]
-    model = build_uc_model(data)
+    model = build_uc_model_gurobipy(data)
     model.optimize()

tests/problems/test_vertexcover.py

@@ -7,7 +7,7 @@ import numpy as np
 
 from miplearn.problems.vertexcover import (
     MinWeightVertexCoverData,
-    build_vertexcover_model,
+    build_vertexcover_model_gurobipy,
 )
 
 
@@ -16,6 +16,6 @@ def test_stab() -> None:
         graph=nx.cycle_graph(5),
         weights=np.array([1.0, 1.0, 1.0, 1.0, 1.0]),
     )
-    model = build_vertexcover_model(data)
+    model = build_vertexcover_model_gurobipy(data)
     model.optimize()
     assert model.inner.objVal == 3.0