sympy.log: lambda x: core.log(x),
sympy.sin: lambda x: core.sin(x),
sympy.asin: lambda x: core.asin(x),
sympy.sinh: lambda x: core.sinh(x),
sympy.asinh: lambda x: core.asinh(x),
sympy.cos: lambda x: core.cos(x),
sympy.acos: lambda x: core.acos(x),
sympy.cosh: lambda x: core.cosh(x),
sympy.acosh: lambda x: core.acosh(x),
sympy.tan: lambda x: core.tan(x),
sympy.atan: lambda x: core.atan(x),
sympy.tanh: lambda x: core.tanh(x),
sympy.atanh: lambda x: core.atanh(x),
sympy.ceiling: lambda x: core.ceil(x),
sympy.floor: lambda x: core.floor(x),
sympy.sqrt: lambda x: core.sqrt(x),
sympy.Derivative: _nondifferentiable,
sympy.Tuple: lambda *x: x,
}
_pyomo_operator_map = {
EXPR.SumExpression: sympy.Add,
EXPR.ProductExpression: sympy.Mul,
EXPR.NPV_ProductExpression: sympy.Mul,
EXPR.MonomialTermExpression: sympy.Mul,
}
_functionMap = {
'exp': sympy.exp,
'log': sympy.log,
'log10': lambda x: sympy.log(x) / sympy.log(10),
def criticalityCheck(self, x, y, z, rom_params, worstcase=False, M=[0.0]):
model = self.model
self.setVarValue(x=x, y=y, z=z)
self.setBound(x, y, z, 1e10)
self.deactiveExtraConObj()
self.activateRomCons(x, rom_params)
optGJH = SolverFactory('contrib.gjh')
optGJH.solve(model, tee=False, symbolic_solver_labels=True)
g, J, varlist, conlist = model._gjh_info
l = ConcreteModel()
l.v = Var(varlist, domain=Reals)
for i in varlist:
#dummy = model.find_component(i)
l.v[i] = 0.0
l.v[i].setlb(-1.0)
l.v[i].setub(1.0)
if worstcase:
if M.all() == 0.0:
print(
'WARNING: worstcase criticality was requested but Jacobian error bound is zero'
)
l.t = Var(range(0, self.ly), domain=Reals)
for i in range(0, self.ly):
l.t[i].setlb(-M[i])
l.t[i].setub(M[i])
def linConMaker(l, i):
# i should be range(len(conlist) - 1)
# because last element of conlist is the objective
con_i = model.find_component(conlist[i])
isEquality = con_i.equality
isROM = False
if conlist[i][:7] == '.' + self.TRF.name + '.rom':
isROM = True
romIndex = int(filter(str.isdigit, conlist[i]))
# This is very inefficient
# Fix this later if these problems get big
# This is the ith row of J times v
Jv = sum(x[2] * l.v[varlist[x[1]]] for x in J if x[0] == i)
if isEquality:
if worstcase and isROM:
return Jv + l.t[romIndex] == 0
else:
return Jv == 0
else:
lo = con_i.lower
up = con_i.upper
if lo is not None:
level = lo.value - con_i.lslack()
if up is not None:
return (lo.value <= level + Jv <= up.value)
else:
return (lo.value <= level + Jv)
elif up is not None:
level = up.value - con_i.uslack()
return (level + Jv <= up.value)
else:
raise Exception(
"This constraint seems to be neither equality or inequality: "
+ conlist(i))
l.lincons = Constraint(range(len(conlist) - 1), rule=linConMaker)
l.obj = Objective(expr=sum(x[1] * l.v[varlist[x[0]]] for x in g))
# Calculate gradient norm for scaling purposes
gfnorm = sqrt(sum(x[1]**2 for x in g))
opt = SolverFactory(self.config.solver)
opt.options.update(self.config.solver_options)
#opt.options['halt_on_ampl_error'] = 'yes'
#opt.options['max_iter'] = 5000
results = opt.solve(l,
keepfiles=self.keepfiles,
tee=self.stream_solver)
if ((results.solver.status == SolverStatus.ok)
and (results.solver.termination_condition
== TerminationCondition.optimal)):
l.solutions.load_from(results)
if gfnorm > 1:
return True, abs(l.obj()) / gfnorm
else:
return True, abs(l.obj())
else:
print("Waring: Crticality check fails with solver Status: " +
str(results.solver.status))
print("And Termination Conditions: " +
str(results.solver.termination_condition))
return False, infinity
def criticalityCheck(self, x, y, z, rom_params, worstcase=False, M=[0.0]):
model = self.model
self.setVarValue(x=x,y=y,z=z)
self.setBound(x, y, z, 1e10)
self.deactiveExtraConObj()
self.activateRomCons(x, rom_params)
optGJH = SolverFactory('contrib.gjh')
optGJH.solve(model, tee=False, symbolic_solver_labels=True)
g, J, varlist, conlist = model._gjh_info
l = ConcreteModel()
l.v = Var(varlist, domain=Reals)
for i in varlist:
#dummy = model.find_component(i)
l.v[i] = 0.0
l.v[i].setlb(-1.0)
l.v[i].setub(1.0)
if worstcase:
if M.all() == 0.0:
print('WARNING: worstcase criticality was requested but Jacobian error bound is zero')
l.t = Var(range(0, self.ly), domain=Reals)
for i in range(0, self.ly):
l.t[i].setlb(-M[i])
l.t[i].setub(M[i])
def linConMaker(l, i):
# i should be range(len(conlist) - 1)
# because last element of conlist is the objective
con_i = model.find_component(conlist[i])
isEquality = con_i.equality
isROM = False
if conlist[i][:7] == '.' + self.TRF.name + '.rom':
isROM = True
romIndex = int(filter(str.isdigit, conlist[i]))
# This is very inefficient
# Fix this later if these problems get big
# This is the ith row of J times v
Jv = sum(x[2] * l.v[varlist[x[1]]] for x in J if x[0] == i)
if isEquality:
if worstcase and isROM:
return Jv + l.t[romIndex] == 0
else:
return Jv == 0
else:
lo = con_i.lower
up = con_i.upper
if lo is not None:
level = lo.value - con_i.lslack()
if up is not None:
return (lo.value <= level + Jv <= up.value)
else:
return (lo.value <= level + Jv)
elif up is not None:
level = up.value - con_i.uslack()
return (level + Jv <= up.value)
else:
raise Exception(
"This constraint seems to be neither equality or inequality: " + conlist(i))
l.lincons = Constraint(range(len(conlist)-1), rule=linConMaker)
l.obj = Objective(expr=sum(x[1] * l.v[varlist[x[0]]] for x in g))
# Calculate gradient norm for scaling purposes
gfnorm = sqrt(sum(x[1]**2 for x in g))
opt = SolverFactory(self.config.solver)
opt.options.update(self.config.solver_options)
#opt.options['halt_on_ampl_error'] = 'yes'
#opt.options['max_iter'] = 5000
results = opt.solve(
l, keepfiles=self.keepfiles, tee=self.stream_solver)
if ((results.solver.status == SolverStatus.ok)
and (results.solver.termination_condition == TerminationCondition.optimal)):
l.solutions.load_from(results)
if gfnorm > 1:
return True, abs(l.obj())/gfnorm
else:
return True, abs(l.obj())
else:
print("Waring: Crticality check fails with solver Status: " + str(results.solver.status))
print("And Termination Conditions: " + str(results.solver.termination_condition))
return False, infinity