def new_constraint_status_var(self, ct):
# INTERNAL
model = self._model
binary_vartype = model.binary_vartype
status_var_fmt = self.status_var_fmt
if model.ignore_names or status_var_fmt is None:
varname = None
else:
# use name if any else use truncated ct string representation
base_varname = self.status_var_fmt.format(
ct.name or str_holo(ct, maxlen=20))
# if name is already taken, use unique index at end to disambiguate
varname = model._get_non_ambiguous_varname(base_varname)
svar = Var(model,
binary_vartype,
lb=0,
ub=1,
_safe_lb=True,
_safe_ub=True,
name=varname)
svar.notify_origin(ct) # generated
idx = self._engine.create_one_variable(binary_vartype, 0, 1, varname)
model._register_one_var(svar, idx, varname)
return svar
def new_multitype_var_list(self,
size,
vartypes,
lbs=None,
ubs=None,
names=None,
key_format=None):
if not size:
return []
mdl = self._model
assert size == len(vartypes)
assert size == len(lbs)
assert size == len(ubs)
assert size == len(names)
allvars = [
Var(mdl,
vartypes[k],
names[k] if names[k] else None,
lbs[k],
ubs[k],
_safe_lb=True,
_safe_ub=True) for k in fast_range(size)
]
indices = self._engine.create_multitype_variables(
size, vartypes, lbs, ubs, names)
mdl._register_block_vars(allvars, indices, names)
return allvars
def new_safe_var(self, vartype, lb=None, ub=None, varname=None):
# INTERNAL
self_model = self._model
used_varname = None if self_model.ignore_names else varname
rlb = vartype._lb if lb is None else lb
rub = vartype._ub if ub is None else ub
var = Var(self_model, vartype, used_varname, rlb, rub, _safe_lb=True, _safe_ub=True)
idx = self._engine.create_one_variable(vartype, rlb, rub, varname)
self_model._register_one_var(var, idx, used_varname)
return var
def new_var(self, vartype, lb=None, ub=None, varname=None):
self_model = self._model
self._checker.check_var_domain(lb, ub, varname)
logger = self_model.logger
rlb = vartype.resolve_lb(lb, logger)
rub = vartype.resolve_ub(ub, logger)
used_varname = None if self_model.ignore_names else varname
var = Var(self_model, vartype, used_varname, rlb, rub, _safe_lb=True, _safe_ub=True)
idx = self._engine.create_one_variable(vartype, rlb, rub, varname)
self_model._register_one_var(var, idx, varname)
return var
def new_var_list(self,
var_container,
key_seq,
vartype,
lb=None,
ub=None,
name=str,
dimension=1,
key_format=None):
number_of_vars = len(key_seq)
if 0 == number_of_vars:
return []
# compute defaults once
default_lb = vartype.default_lb
default_ub = vartype.default_ub
xlbs = self._expand_bounds(key_seq,
lb,
default_lb,
number_of_vars,
true_if_lb=True)
xubs = self._expand_bounds(key_seq,
ub,
default_ub,
number_of_vars,
true_if_lb=False)
# at this point both list are either [] or have size numberOfVars
all_names = self._expand_names(key_seq, name, dimension, key_format)
safe_lbs = not xlbs
safe_ubs = not xubs
if xlbs and xubs:
self._checker.check_vars_domain(xlbs, xubs, all_names)
mdl = self._model
allvars = [
Var(mdl,
vartype,
all_names[k] if all_names else None,
xlbs[k] if xlbs else default_lb,
xubs[k] if xubs else default_ub,
container=var_container,
_safe_lb=safe_lbs,
_safe_ub=safe_ubs) for k in fast_range(number_of_vars)
]
# query the engine for a list of indices.
indices = self._engine.create_variables(len(key_seq), vartype, xlbs,
xubs, all_names)
mdl._register_block_vars(allvars, indices, all_names)
return allvars
def get_noise(variable: Var) -> float:
stdev = 1 + (4000 if 'x0,' in variable.get_name() else 1000) / (
(epoch_num + 1) * self.envt.NUM_AGENTS)
return abs(gauss(0, stdev)) if is_training else 0
