Reformat; remove unused imports

docs/guide/features.ipynb

@@ -166,7 +166,7 @@
     "\n",
     "    # Extract and print constraint features\n",
     "    x3 = ext.get_constr_features(h5)\n",
-    "    print(\"constraint features\", x3.shape, \"\\n\", x3)\n"
+    "    print(\"constraint features\", x3.shape, \"\\n\", x3)"
    ]
   },
   {

docs/guide/primal.ipynb

@@ -120,7 +120,7 @@
     "    extractor=H5FieldsExtractor(instance_fields=[\"static_var_obj_coeffs\"]),\n",
     "    constructor=MergeTopSolutions(k=3, thresholds=[0.25, 0.75]),\n",
     "    action=EnforceProximity(3),\n",
-    ")\n"
+    ")"
    ]
   },
   {
@@ -175,7 +175,7 @@
     "    ),\n",
     "    extractor=AlvLouWeh2017Extractor(),\n",
     "    action=SetWarmStart(),\n",
-    ")\n"
+    ")"
    ]
   },
   {
@@ -230,7 +230,7 @@
     "        instance_fields=[\"static_var_obj_coeffs\"],\n",
     "    ),\n",
     "    action=SetWarmStart(),\n",
-    ")\n"
+    ")"
    ]
   },
   {
@@ -263,7 +263,7 @@
     "# Configures an expert primal component, which reads a pre-computed\n",
     "# optimal solution from the HDF5 file and provides it to the solver\n",
     "# as warm start.\n",
-    "comp = ExpertPrimalComponent(action=SetWarmStart())\n"
+    "comp = ExpertPrimalComponent(action=SetWarmStart())"
    ]
   }
  ],

docs/guide/problems.ipynb

@@ -194,7 +194,7 @@
     "\n",
     "# Optimize first instance\n",
     "model = build_binpack_model(data[0])\n",
-    "model.optimize()\n"
+    "model.optimize()"
    ]
   },
   {
@@ -397,7 +397,7 @@
     "\n",
     "# Build model and optimize\n",
     "model = build_multiknapsack_model(data[0])\n",
-    "model.optimize()\n"
+    "model.optimize()"
    ]
   },
   {
@@ -577,7 +577,7 @@
     "\n",
     "# Build and optimize model\n",
     "model = build_pmedian_model(data[0])\n",
-    "model.optimize()\n"
+    "model.optimize()"
    ]
   },
   {
@@ -726,7 +726,7 @@
     "\n",
     "# Build and optimize model\n",
     "model = build_setcover_model_gurobipy(data[0])\n",
-    "model.optimize()\n"
+    "model.optimize()"
    ]
   },
   {
@@ -862,7 +862,7 @@
     "\n",
     "# Build and optimize model\n",
     "model = build_setpack_model(data[0])\n",
-    "model.optimize()\n"
+    "model.optimize()"
    ]
   },
   {
@@ -999,7 +999,7 @@
     "\n",
     "# Load and optimize the first instance\n",
     "model = build_stab_model(data[0])\n",
-    "model.optimize()\n"
+    "model.optimize()"
    ]
   },
   {
@@ -1174,7 +1174,7 @@
     "\n",
     "# Load and optimize the first instance\n",
     "model = build_tsp_model(data[0])\n",
-    "model.optimize()\n"
+    "model.optimize()"
    ]
   },
   {
@@ -1412,7 +1412,7 @@
     "\n",
     "# Load and optimize the first instance\n",
     "model = build_uc_model(data[0])\n",
-    "model.optimize()\n"
+    "model.optimize()"
    ]
   },
   {
@@ -1553,7 +1553,7 @@
     "\n",
     "# Load and optimize the first instance\n",
     "model = build_vertexcover_model(data[0])\n",
-    "model.optimize()\n"
+    "model.optimize()"
    ]
   },
   {

tests/components/cuts/test_mem.py

@@ -2,30 +2,16 @@
 #  Copyright (C) 2020-2023, UChicago Argonne, LLC. All rights reserved.
 #  Released under the modified BSD license. See COPYING.md for more details.
 
-from typing import Any, List, Hashable, Dict
+from typing import Any, List, Dict
 from unittest.mock import Mock
 
-import gurobipy as gp
-import networkx as nx
-from gurobipy import GRB, quicksum
 from sklearn.dummy import DummyClassifier
 from sklearn.neighbors import KNeighborsClassifier
 
 from miplearn.components.cuts.mem import MemorizingCutsComponent
 from miplearn.extractors.abstract import FeaturesExtractor
 from miplearn.problems.stab import build_stab_model
-from miplearn.solvers.gurobi import GurobiModel
 from miplearn.solvers.learning import LearningSolver
-import numpy as np
-
-
-# def test_usage() -> None:
-#     model = _build_cut_model()
-#     solver = LearningSolver(components=[])
-#     solver.optimize(model)
-#     assert model.cuts_ is not None
-#     assert len(model.cuts_) > 0
-#     assert False
 
 
 def test_mem_component(