Remove most usages of put_{vector,vector_list}; deprecate get_set

tests/components/test_objective.py

@@ -13,6 +13,7 @@ from miplearn.components.objective import ObjectiveValueComponent
 from miplearn.features.sample import Sample, MemorySample
 from miplearn.solvers.learning import LearningSolver
 from miplearn.solvers.pyomo.gurobi import GurobiPyomoSolver
+from miplearn.solvers.tests import assert_equals
 
 
 @pytest.fixture
@@ -21,7 +22,7 @@ def sample() -> Sample:
         {
             "mip_lower_bound": 1.0,
             "mip_upper_bound": 2.0,
-            "lp_instance_features": [1.0, 2.0, 3.0],
+            "lp_instance_features": np.array([1.0, 2.0, 3.0]),
         },
     )
     return sample
@@ -29,18 +30,18 @@ def sample() -> Sample:
 
 def test_sample_xy(sample: Sample) -> None:
     x_expected = {
-        "Lower bound": [[1.0, 2.0, 3.0]],
-        "Upper bound": [[1.0, 2.0, 3.0]],
+        "Lower bound": np.array([[1.0, 2.0, 3.0]]),
+        "Upper bound": np.array([[1.0, 2.0, 3.0]]),
     }
     y_expected = {
-        "Lower bound": [[1.0]],
-        "Upper bound": [[2.0]],
+        "Lower bound": np.array([[1.0]]),
+        "Upper bound": np.array([[2.0]]),
     }
     xy = ObjectiveValueComponent().sample_xy(None, sample)
     assert xy is not None
     x_actual, y_actual = xy
-    assert x_actual == x_expected
-    assert y_actual == y_expected
+    assert_equals(x_actual, x_expected)
+    assert_equals(y_actual, y_expected)
 
 
 def test_fit_xy() -> None:

tests/components/test_static_lazy.py

@@ -36,13 +36,15 @@ def sample() -> Sample:
             "static_constr_names": np.array(["c1", "c2", "c3", "c4", "c5"], dtype="S"),
             "static_instance_features": [5.0],
             "mip_constr_lazy_enforced": {b"c1", b"c2", b"c4"},
-            "lp_constr_features": [
-                [1.0, 1.0],
-                [1.0, 2.0],
-                [1.0, 3.0],
-                [1.0, 4.0, 0.0],
-                None,
-            ],
+            "lp_constr_features": np.array(
+                [
+                    [1.0, 1.0, 0.0],
+                    [1.0, 2.0, 0.0],
+                    [1.0, 3.0, 0.0],
+                    [1.0, 4.0, 0.0],
+                    [0.0, 0.0, 0.0],
+                ]
+            ),
             "static_constr_lazy_count": 4,
         },
     )
@@ -216,7 +218,7 @@ def test_fit_xy() -> None:
 
 def test_sample_xy(sample: Sample) -> None:
     x_expected = {
-        b"type-a": [[5.0, 1.0, 1.0], [5.0, 1.0, 2.0], [5.0, 1.0, 3.0]],
+        b"type-a": [[5.0, 1.0, 1.0, 0.0], [5.0, 1.0, 2.0, 0.0], [5.0, 1.0, 3.0, 0.0]],
         b"type-b": [[5.0, 1.0, 4.0, 0.0]],
     }
     y_expected = {

tests/features/test_extractor.py

@@ -61,7 +61,7 @@ def test_knapsack() -> None:
         np.array(["default", "default", "default", "default", ""], dtype="S"),
     )
     assert_equals(
-        sample.get_vector_list("static_var_features"),
+        sample.get_array("static_var_features"),
         np.array(
             [
                 [23.0, 505.0, 1.0, 0.32899, 0.0, 505.0, 1.0],
@@ -155,7 +155,7 @@ def test_knapsack() -> None:
         np.array([1.0, 0.923077, 1.0, 0.0, 67.0]),
     )
     assert_equals(
-        sample.get_vector_list("lp_var_features"),
+        sample.get_array("lp_var_features"),
         np.array(
             [
                 [

tests/instance/test_file.py

@@ -18,7 +18,7 @@ def test_usage() -> None:
     filename = tempfile.mktemp()
     FileInstance.save(original, filename)
     sample = Hdf5Sample(filename, check_data=True)
-    assert len(sample.get_bytes("pickled")) > 0
+    assert len(sample.get_array("pickled")) > 0
 
     # Solve instance from disk
     solver = LearningSolver(solver=GurobiSolver())