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Use np.ndarray for var_types, basis_status

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This commit is contained in:
Alinson S. Xavier
2021-08-08 07:36:57 -05:00
parent 7d55d6f34c
commit 45667ac2e4
6 changed files with 31 additions and 23 deletions
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31
miplearn/solvers/gurobi.py
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@@ -79,7 +79,7 @@ class GurobiSolver(InternalSolver):
self._gp_constrs: List["gurobipy.Constr"] = []
self._var_names: np.ndarray = np.empty(0)
self._constr_names: List[str] = []
self._var_types: List[str] = []
self._var_types: np.ndarray = np.empty(0)
self._var_lbs: np.ndarray = np.empty(0)
self._var_ubs: np.ndarray = np.empty(0)
self._var_obj_coeffs: np.ndarray = np.empty(0)
@@ -322,8 +322,9 @@ class GurobiSolver(InternalSolver):
else:
raise Exception(f"unknown vbasis: {basis_status}")
basis_status: Optional[np.ndarray] = None
upper_bounds, lower_bounds, types, values = None, None, None, None
obj_coeffs, reduced_costs, basis_status = None, None, None
obj_coeffs, reduced_costs = None, None
sa_obj_up, sa_ub_up, sa_lb_up = None, None, None
sa_obj_down, sa_ub_down, sa_lb_down = None, None, None
@@ -335,11 +336,12 @@ class GurobiSolver(InternalSolver):
if self._has_lp_solution:
reduced_costs = np.array(model.getAttr("rc", self._gp_vars), dtype=float)
basis_status = list(
map(
_parse_gurobi_vbasis,
model.getAttr("vbasis", self._gp_vars),
)
basis_status = np.array(
[
_parse_gurobi_vbasis(b)
for b in model.getAttr("vbasis", self._gp_vars)
],
dtype="S",
)
if with_sa:
@@ -513,7 +515,7 @@ class GurobiSolver(InternalSolver):
self._apply_params(streams)
assert self.model is not None
for (i, var) in enumerate(self._gp_vars):
if self._var_types[i] == "B":
if self._var_types[i] == b"B":
var.vtype = self.gp.GRB.CONTINUOUS
var.lb = 0.0
var.ub = 1.0
@@ -521,7 +523,7 @@ class GurobiSolver(InternalSolver):
self.model.optimize()
self._dirty = False
for (i, var) in enumerate(self._gp_vars):
if self._var_types[i] == "B":
if self._var_types[i] == b"B":
var.vtype = self.gp.GRB.BINARY
log = streams[0].getvalue()
self._has_lp_solution = self.model.solCount > 0
@@ -590,7 +592,10 @@ class GurobiSolver(InternalSolver):
self.model.getAttr("varName", gp_vars),
dtype="S",
)
var_types: List[str] = self.model.getAttr("vtype", gp_vars)
var_types: np.ndarray = np.array(
self.model.getAttr("vtype", gp_vars),
dtype="S",
)
var_ubs: np.ndarray = np.array(
self.model.getAttr("ub", gp_vars),
dtype=float,
@@ -611,7 +616,7 @@ class GurobiSolver(InternalSolver):
f"Duplicated variable name detected: {var_names[i]}. "
f"Unique variable names are currently required."
)
if var_types[i] == "I":
if var_types[i] == b"I":
assert var_ubs[i] == 1.0, (
"Only binary and continuous variables are currently supported. "
f"Integer variable {var_names[i]} has upper bound {var_ubs[i]}."
@@ -620,8 +625,8 @@ class GurobiSolver(InternalSolver):
"Only binary and continuous variables are currently supported. "
f"Integer variable {var_names[i]} has lower bound {var_ubs[i]}."
)
var_types[i] = "B"
assert var_types[i] in ["B", "C"], (
var_types[i] = b"B"
assert var_types[i] in [b"B", b"C"], (
"Only binary and continuous variables are currently supported. "
f"Variable {var_names[i]} has type {var_types[i]}."
)