GurobiModel: Capture static_var_obj_coeffs_quad

miplearn/problems/maxcut.py

@@ -80,6 +80,7 @@ class MaxCutGenerator:
     def _generate_graph(self) -> Graph:
         return nx.generators.random_graphs.binomial_graph(self.n.rvs(), self.p.rvs())
 
+
 def build_maxcut_model_gurobipy(
     data: Union[str, MaxCutData],
     params: Optional[dict[str, Any]] = None,
@@ -97,13 +98,16 @@ def build_maxcut_model_gurobipy(
     x = model.addVars(nodes, vtype=gp.GRB.BINARY, name="x")
 
     # Add the objective function
-    model.setObjective(quicksum(
-        - data.weights[i] * x[e[0]] * (1 - x[e[1]]) for (i, e) in enumerate(edges)
-    ))
+    model.setObjective(
+        quicksum(
+            -data.weights[i] * x[e[0]] * (1 - x[e[1]]) for (i, e) in enumerate(edges)
+        )
+    )
 
     model.update()
     return GurobiModel(model)
 
+
 def _maxcut_read(data: Union[str, MaxCutData]) -> MaxCutData:
     if isinstance(data, str):
         data = read_pkl_gz(data)

miplearn/solvers/gurobi.py

@@ -264,6 +264,13 @@ class GurobiModel(AbstractModel):
             h5.put_array(
                 h5_field, np.array(self.inner.getAttr(gp_field, gp_vars), dtype=float)
             )
+        obj = self.inner.getObjective()
+        if isinstance(obj, gp.QuadExpr):
+            nvars = len(self.inner.getVars())
+            obj_q = np.zeros((nvars, nvars))
+            for i in range(obj.size()):
+                obj_q[obj.getVar1(i).index, obj.getVar2(i).index] = obj.getCoeff(i)
+            h5.put_array("static_var_obj_coeffs_quad", obj_q)
 
     def _extract_after_load_constrs(self, h5: H5File) -> None:
         gp_constrs = self.inner.getConstrs()