def run_demo(with_plots=True):
"""
An example on how to simulate a model using the DAE simulator. The result
can be compared with that of sim_rlc.py which has solved the same problem
using dymola. Also writes information to a file.
"""
curr_dir = os.path.dirname(os.path.abspath(__file__));
model_name = 'RLC_Circuit'
mofile = curr_dir+'/files/RLC_Circuit.mo'
jmu_name = compile_jmu(model_name, mofile)
model = JMUModel(jmu_name)
init_res = model.initialize()
(E_dae,A_dae,B_dae,F_dae,g_dae,state_names,input_names,algebraic_names, \
dx0,x0,u0,w0,t0) = linearize_dae(init_res.model)
(A_ode,B_ode,g_ode,H_ode,M_ode,q_ode) = linear_dae_to_ode(
E_dae,A_dae,B_dae,F_dae,g_dae)
res1 = model.simulate()
jmu_name = compile_jmu("RLC_Circuit_Linearized",mofile)
lin_model = JMUModel(jmu_name)
res2 = lin_model.simulate()
c_v_1 = res1['capacitor.v']
i_p_i_1 = res1['inductor.p.i']
i_p1_i_1 = res1['inductor1.p.i']
t_1 = res1['time']
c_v_2 = res2['x[1]']
i_p_i_2 = res2['x[2]']
i_p1_i_2 = res2['x[3]']
t_2 = res2['time']
assert N.abs(res1.final('capacitor.v') - res2.final('x[1]')) < 1e-3
if with_plots:
p.figure(1)
p.hold(True)
p.subplot(311)
p.plot(t_1,c_v_1)
p.plot(t_2,c_v_2,'g')
p.ylabel('c.v')
p.legend(('original model','linearized ODE'))
p.grid()
p.subplot(312)
p.plot(t_1,i_p_i_1)
p.plot(t_2,i_p_i_2,'g')
p.ylabel('i.p.i')
p.grid()
p.subplot(313)
p.plot(t_1,i_p1_i_1)
p.plot(t_2,i_p1_i_2,'g')
p.ylabel('i.p1.i')
p.grid()
p.show()
def run_demo(with_plots=True):
"""
An example on how to simulate a model using the DAE simulator. The result
can be compared with that of sim_rlc.py which has solved the same problem
using dymola. Also writes information to a file.
"""
curr_dir = os.path.dirname(os.path.abspath(__file__))
model_name = "RLC_Circuit"
mofile = curr_dir + "/files/RLC_Circuit.mo"
jmu_name = compile_jmu(model_name, mofile)
model = JMUModel(jmu_name)
init_res = model.initialize()
(E_dae, A_dae, B_dae, F_dae, g_dae, state_names, input_names, algebraic_names, dx0, x0, u0, w0, t0) = linearize_dae(
init_res.model
)
(A_ode, B_ode, g_ode, H_ode, M_ode, q_ode) = linear_dae_to_ode(E_dae, A_dae, B_dae, F_dae, g_dae)
res1 = model.simulate()
jmu_name = compile_jmu("RLC_Circuit_Linearized", mofile)
lin_model = JMUModel(jmu_name)
res2 = lin_model.simulate()
c_v_1 = res1["capacitor.v"]
i_p_i_1 = res1["inductor.p.i"]
i_p1_i_1 = res1["inductor1.p.i"]
t_1 = res1["time"]
c_v_2 = res2["x[1]"]
i_p_i_2 = res2["x[2]"]
i_p1_i_2 = res2["x[3]"]
t_2 = res2["time"]
assert N.abs(res1.final("capacitor.v") - res2.final("x[1]")) < 1e-3
if with_plots:
p.figure(1)
p.hold(True)
p.subplot(311)
p.plot(t_1, c_v_1)
p.plot(t_2, c_v_2, "g")
p.ylabel("c.v")
p.legend(("original model", "linearized ODE"))
p.grid()
p.subplot(312)
p.plot(t_1, i_p_i_1)
p.plot(t_2, i_p_i_2, "g")
p.ylabel("i.p.i")
p.grid()
p.subplot(313)
p.plot(t_1, i_p1_i_1)
p.plot(t_2, i_p1_i_2, "g")
p.ylabel("i.p1.i")
p.grid()
p.show()
def getLinearDaeFromJmu(self):
"""
Takes a ModelicaObject, and returns a dictionary containing the output
"""
if(self.linJmu):
return self.linJmu
else:
init_res=self.jmu.initialize()
(E_dae,A_dae,B_dae,F_dae,g_dae,state_names,input_names,algebraic_names, dx0,x0,u0,w0,t0) = linearize_dae(init_res.model);
toReturn={"E":E_dae,"A":A_dae,"B":B_dae,"F":F_dae,"g":g_dae,"State_names":state_names,"input_names":input_names,"algebraic_names":algebraic_names,"dx0":dx0,"x0":x0,"u0":u0,"w0":w0,"t0":t0}
self.linJmu=toReturn;
return self.linJmu
