/
bounded.py
105 lines (90 loc) · 3.86 KB
/
bounded.py
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"Implements Bounded"
from collections import defaultdict
import numpy as np
from .. import Variable
from .set import ConstraintSet
from ..small_scripts import appendsolwarning
def varkey_bounds(varkeys, lower, upper):
"""Returns constraints list bounding all varkeys.
Arguments
---------
varkeys : iterable
list of varkeys to create bounds for
lower : float
lower bound for all varkeys
upper : float
upper bound for all varkeys
"""
constraints = []
for varkey in varkeys:
variable = Variable(**varkey.descr)
if variable.units: # non-dimensionalize the variable monomial
variable.units = variable.hmap.units = None
constraint = []
if lower:
constraint.append(lower <= variable)
if upper:
constraint.append(variable <= upper)
constraints.append(constraint)
return constraints
class Bounded(ConstraintSet):
"""Bounds contained variables, generally ensuring dual feasibility.
Arguments
---------
constraints : iterable
constraints whose varkeys will be bounded
verbosity : int (default 1)
how detailed of a warning to print on solve
0: nothing
1: print warnings
eps : float (default 1e-30)
default lower bound is eps, upper bound is 1/eps
lower : float (default None)
lower bound for all varkeys, replaces eps
upper : float (default None)
upper bound for all varkeys, replaces 1/eps
"""
sens_threshold = 1e-7
logtol_threshold = 3
def __init__(self, constraints, *, eps=1e-30, lower=None, upper=None):
if not isinstance(constraints, ConstraintSet):
constraints = ConstraintSet(constraints)
self.lowerbound = lower or eps
self.upperbound = upper or 1/eps
constrained_varkeys = constraints.constrained_varkeys()
self.bound_varkeys = frozenset(vk for vk in constrained_varkeys
if vk not in constraints.substitutions)
bounding_constraints = varkey_bounds(self.bound_varkeys,
self.lowerbound, self.upperbound)
super().__init__({"original constraints": constraints,
"variable bounds": bounding_constraints})
def process_result(self, result):
"Add boundedness to the model's solution"
ConstraintSet.process_result(self, result)
if "boundedness" not in result:
result["boundedness"] = {}
result["boundedness"].update(self.check_boundaries(result))
def check_boundaries(self, result):
"Creates (and potentially prints) a dictionary of unbounded variables."
out = defaultdict(set)
for i, varkey in enumerate(self.bound_varkeys):
value = result["variables"][varkey]
c_senss = [result["sensitivities"]["constraints"].get(c, 0)
for c in self["variable bounds"][i]]
if self.lowerbound:
bound = "lower bound of %.2g" % self.lowerbound
if c_senss[0] >= self.sens_threshold:
out["sensitive to " + bound].add(varkey)
if np.log(value/self.lowerbound) <= self.logtol_threshold:
out["value near " + bound].add(varkey)
if self.upperbound:
bound = "upper bound of %.2g" % self.upperbound
if c_senss[-1] >= self.sens_threshold:
out["sensitive to " + bound].add(varkey)
if np.log(self.upperbound/value) <= self.logtol_threshold:
out["value near " + bound].add(varkey)
for bound, vks in out.items():
msg = "% 34s: %s" % (bound, ", ".join([str(v) for v in vks]))
appendsolwarning(msg, out, result,
"Arbitrarily Bounded Variables")
return out