def test_XML(self):
self.message("JModelica XML parsing")
ocp = SymbolicOCP()
ocp.parseFMI('data/cstr.xml')
self.assertEqual(ocp.t0, 0)
self.assertEqual(ocp.tf, 150)
#self.assertFalse(ocp.t0_free)
#self.assertFalse(ocp.tf_free)
self.assertTrue(ocp.lterm.size() == 0)
self.assertTrue(ocp.mterm.size() == 1)
m = ocp.mterm
self.assertTrue(isinstance(m, SXMatrix))
self.assertTrue(isinstance(ocp.t, SXMatrix))
self.assertEquals(str(m), 'cost.atTime(150)')
print dir(ocp)
self.assertEquals(ocp.ode.size(), 3)
self.assertEquals(len(ocp.x), 3) # there are three states
c = ocp.variable("cstr.c")
T = ocp.variable("cstr.T")
cost = ocp.variable("cost")
self.assertTrue(isinstance(c, Variable))
self.assertEquals(c.getName(), "cstr.c")
self.assertEquals(T.getName(), "cstr.T")
self.assertEquals(cost.getName(), "cost")
self.assertEquals(c.getNominal(), 1000)
#print c.atTime(0)
c = c.var()
T = T.var()
cost = cost.var()
u = ocp.variable("u").var()
self.assertEquals(ocp.path.size(), 3)
#self.assertEquals(len(ocp.cfcn_lb),3)
#self.assertEquals(len(ocp.cfcn_ub),3)
#self.assertTrue(ocp.cfcn[0].isEqual(T))
#self.assertTrue(ocp.cfcn[1].isEqual(u))
#self.assertTrue(ocp.cfcn[2].isEqual(u))
#self.assertTrue(ocp.cfcn_lb[0].isMinusInf())
#self.assertEquals(ocp.cfcn_lb[1].getValue(),230)
#self.assertTrue(ocp.cfcn_lb[2].isMinusInf())
#self.assertEquals(ocp.cfcn_ub[0].getValue(),350)
#self.assertTrue(ocp.cfcn_ub[1].isInf())
#self.assertEquals(ocp.cfcn_ub[2].getValue(),370)
print ocp.initial
print c, T, cost
#print c.atTime(0)
f = SXFunction([vertcat([c, T, cost])], [ocp.initial])
f.init()
return
f.evaluate()
self.checkarray(f.output(),
matrix([-956.271065, -250.051971, 0]).T, "initeq")
mystates = []
def test_XML(self):
self.message("JModelica XML parsing")
ocp = SymbolicOCP()
ocp.parseFMI('data/cstr.xml')
self.assertEqual(ocp.t0,0)
self.assertEqual(ocp.tf,150)
#self.assertFalse(ocp.t0_free)
#self.assertFalse(ocp.tf_free)
self.assertTrue(ocp.lterm.size()==0)
self.assertTrue(ocp.mterm.size()==1)
m = ocp.mterm
self.assertTrue(isinstance(m,SXMatrix))
self.assertTrue(isinstance(ocp.t,SXMatrix))
self.assertEquals(str(m),'cost.atTime(150)')
print dir(ocp)
self.assertEquals(ocp.ode.size(),3)
self.assertEquals(len(ocp.x),3) # there are three states
c = ocp.variable("cstr.c")
T = ocp.variable("cstr.T")
cost = ocp.variable("cost")
self.assertTrue(isinstance(c,Variable))
self.assertEquals(c.getName(),"cstr.c")
self.assertEquals(T.getName(),"cstr.T")
self.assertEquals(cost.getName(),"cost")
self.assertEquals(c.getNominal(),1000)
#print c.atTime(0)
c = c.var()
T = T.var()
cost = cost.var()
u = ocp.variable("u").var()
self.assertEquals(ocp.path.size(),3)
#self.assertEquals(len(ocp.cfcn_lb),3)
#self.assertEquals(len(ocp.cfcn_ub),3)
#self.assertTrue(ocp.cfcn[0].isEqual(T))
#self.assertTrue(ocp.cfcn[1].isEqual(u))
#self.assertTrue(ocp.cfcn[2].isEqual(u))
#self.assertTrue(ocp.cfcn_lb[0].isMinusInf())
#self.assertEquals(ocp.cfcn_lb[1].getValue(),230)
#self.assertTrue(ocp.cfcn_lb[2].isMinusInf())
#self.assertEquals(ocp.cfcn_ub[0].getValue(),350)
#self.assertTrue(ocp.cfcn_ub[1].isInf())
#self.assertEquals(ocp.cfcn_ub[2].getValue(),370)
print ocp.initial
print c,T,cost
#print c.atTime(0)
f=SXFunction([vertcat([c,T,cost])],[ocp.initial])
f.init()
return
f.evaluate()
self.checkarray(f.output(),matrix([-956.271065,-250.051971,0]).T,"initeq")
mystates = []
def _load_xml_to_casadi(self, xml, verbose):
# Create a symbolic OCP
self.ocp = casadi.SymbolicOCP()
options = {}
options["verbose"] = verbose
options["sort_equations"] = False
options["eliminate_dependent"] = False
self.ocp.parseFMI(xml, options)
if self._casadi_blt:
self.ocp.makeExplicit()
self.ocp.eliminateAlgebraic()
if len(self.ocp.z) > 0 or self.ocp.ode.empty():
raise RuntimeError("Unable to reformulate as ODE.")
casadi.updateDependent(self.ocp)
# Store list of non-free parameters
self._parameters = ([pi for pi in self.ocp.pi] +
[pd for pd in self.ocp.pd])
# Check the absence of multiple Mayer and Lagrange terms
if self.ocp.lterm.numel() > 1:
raise NotImplementedError("Multiple Lagrange terms are not " +
"supported.")
if self.ocp.mterm.numel() > 1:
raise NotImplementedError("Multiple Mayer terms are not " +
"supported.")
# Identify variables
variables = {}
variables['x'] = self.ocp.x
variables['u'] = self.ocp.u
variables['w'] = self.ocp.z
variables['p_opt'] = self.ocp.pf
names = {}
for vt in variables:
names[vt] = [(var.getValueReference(), var.getName()) for
var in variables[vt]]
# Make sure the variables appear in value reference order
var_vectors = {}
for var_type in names:
var_dict = dict((repr(v), v) for v in variables[var_type])
name_dict = dict((x[0], x[1]) for x in names[var_type])
if var_type == 'p_opt':
free_times = 0
if self.xmldoc.get_opt_finaltime_free():
free_times += 1
if self.xmldoc.get_opt_starttime_free():
free_times += 1
var_vectors[var_type] = casadi.VariableVector(len(var_dict) -
free_times)
else:
var_vectors[var_type] = casadi.VariableVector(len(var_dict))
i = 0
for vr in sorted(name_dict):
if (self.xmldoc.get_opt_finaltime_free() or
self.xmldoc.get_opt_starttime_free()):
if (name_dict[vr] == "finalTime" or
name_dict[vr] == "startTime"):
continue
var_vectors[var_type][i] = var_dict[name_dict[vr]]
i = i + 1
self._var_vectors = var_vectors
# Create symbolic variables
self.dx = casadi.vertcat(casadi.der(var_vectors['x']))
self.x = casadi.vertcat(casadi.var(var_vectors['x']))
self.u = casadi.vertcat(casadi.var(var_vectors['u']))
self.w = casadi.vertcat(casadi.var(var_vectors['w']))
self.t = self.ocp.t
self.p = casadi.vertcat(casadi.var(var_vectors['p_opt']))
sym_vars = {'dx': self.dx,
'x': self.x,
'u': self.u,
'w': self.w,
'p_opt': self.p}
# Create maps from value reference to CasADi variable index and type
vr_map = {}
get_vr = self.xmldoc.get_value_reference
for vt in sym_vars.keys():
i = 0
for v in sym_vars[vt]:
var_name = str(v)
if vt == "dx":
var_name = convert_casadi_der_name(var_name)
vr_map[get_vr(var_name)] = (i, vt)
i = i + 1
self.vr_map = vr_map
# Read integer parameter values separately (circumvent SymbolicOCP bug)
integer_vars = self.xmldoc.get_all_integer_variables()
if len(integer_vars) > 0:
[int_vr, int_names] = \
zip(*[(var.get_value_reference(), var.get_name()) for
var in integer_vars])
for (vr, start) in self.xmldoc.get_variable_start_attributes():
try:
index = int_vr.index(vr)
except ValueError:
pass
else:
var = self.ocp.variable(int_names[index])
# Assume that independent parameters have start values
if start is not None:
var.setStart(start)
casadi.updateDependent(self.ocp) # Handle dependent parameters
# Count variables
self.n_x = self.x.numel()
self.n_u = self.u.numel()
self.n_w = self.w.numel()
self.n_p = self.p.numel()
# Create scaling factors
sf = {}
sf['dx'] = N.ones(self.n_x)
sf['x'] = N.ones(self.n_x)
sf['u'] = N.ones(self.n_u)
sf['w'] = N.ones(self.n_w)
sf['p_opt'] = N.ones(self.n_p)
self.sf = sf
self._update_sf()
