def test_getMatrix():
assert (K.getMatrix([[1,2,3]]) == np.array([[1,2,3]])).all()
m = K.SimpleMatrix(1,3)
m.setValue(0,0,1)
m.setValue(0,1,2)
m.setValue(0,2,3)
assert (K.getMatrix(m) == np.array([[1,2,3]])).all()
assert (K.getMatrix(m) != np.array([[1,0,3]])).any()
def test_getMatrix():
assert (K.getMatrix([[1,2,3]]) == np.array([[1,2,3]])).all()
m = K.SimpleMatrix(1,3)
m.setValue(0,0,1)
m.setValue(0,1,2)
m.setValue(0,2,3)
assert (K.getMatrix(m) == np.array([[1,2,3]])).all()
assert (K.getMatrix(m) != np.array([[1,0,3]])).any()
m1 = K.SimpleMatrix(((1,2,3), (4,5,6)))
m2 = K.SimpleMatrix(np.array([[1,2,3],[4,5,6]]))
assert (K.getMatrix(m1) == K.getMatrix(K.SimpleMatrix(m2))).all()
def test_getMatrix():
assert (sk.getMatrix([[1, 2, 3]]) == np.array([[1, 2, 3]])).all()
m = sk.SimpleMatrix(1, 3)
m.setValue(0, 0, 1)
m.setValue(0, 1, 2)
m.setValue(0, 2, 3)
assert (sk.getMatrix(m) == np.array([[1, 2, 3]])).all()
assert (sk.getMatrix(m) != np.array([[1, 0, 3]])).any()
m1 = sk.SimpleMatrix(((1, 2, 3), (4, 5, 6)))
m2 = sk.SimpleMatrix(np.array([[1, 2, 3], [4, 5, 6]]))
assert (sk.getMatrix(m1) == sk.getMatrix(sk.SimpleMatrix(m2))).all()
def compute_dt_matrices(A, B, h, TV=False):
# variable declaration
t0 = 0.0 # start time
T = 1 # end time
n, m = B.shape
# Matrix declaration
x0 = np.random.random(n)
Csurface = np.random.random((m, n))
# Declaration of the Dynamical System
if TV:
process_ds = SK.FirstOrderLinearDS(x0, A)
else:
process_ds = SK.FirstOrderLinearTIDS(x0, A)
# Model
process = SK.Model(t0, T)
process.nonSmoothDynamicalSystem().insertDynamicalSystem(process_ds)
# time discretisation
process_time_discretisation = SK.TimeDiscretisation(t0, h)
# Creation of the Simulation
process_simu = SK.TimeStepping(process_time_discretisation, 0)
process_simu.setName("plant simulation")
# Declaration of the integrator
process_integrator = SK.ZeroOrderHoldOSI()
process_integrator.insertDynamicalSystem(process_ds)
process_simu.insertIntegrator(process_integrator)
rel = SK.FirstOrderLinearTIR(Csurface, B)
nslaw = SK.RelayNSL(m)
inter = SK.Interaction(m, nslaw, rel)
#process.nonSmoothDynamicalSystem().insertInteraction(inter, True)
process.nonSmoothDynamicalSystem().link(inter, process_ds)
process.nonSmoothDynamicalSystem().setControlProperty(inter, True)
# Initialization
process.initialize(process_simu)
# Main loop
process_simu.computeOneStep()
Ad = SK.getMatrix(process_integrator.Ad(process_ds)).copy()
Bd = SK.getMatrix(process_integrator.Bd(process_ds)).copy()
return (Ad, Bd)
def test_xml1():
''' the BouncingBall '''
bouncingBall = buildModelXML(os.path.join(working_dir, 'data/BBallTS.xml'))
# --- Get the simulation ---
s = bouncingBall.simulation()
dsN = SK.dynamicalSystems(
bouncingBall.nonSmoothDynamicalSystem().topology().dSG(0))[0].number()
ball = bouncingBall.nonSmoothDynamicalSystem().dynamicalSystem(dsN)
N = 2000 # Number of time steps
# saved in a matrix dataPlot
outputSize = 4
dataPlot = np.zeros((N + 1, outputSize))
q = ball.q()
v = ball.velocity()
p = ball.p(1)
dataPlot[0, 0] = bouncingBall.t0()
dataPlot[0, 1] = q[0]
dataPlot[0, 2] = v[0]
dataPlot[0, 3] = p[0]
print("====> Start computation ...")
# --- Time loop ---
k = 1
while s.hasNextEvent():
s.computeOneStep()
# --- Get values to be plotted ---
dataPlot[k, 0] = s.nextTime()
dataPlot[k, 1] = q[0]
dataPlot[k, 2] = v[0]
dataPlot[k, 3] = p[0]
s.nextStep()
k += 1
print("End of computation - Number of iterations done: {:}".format(k))
print("====> Output file writing ...")
dataPlot.resize(k, outputSize)
np.savetxt("BBallTS.dat", dataPlot)
# Comparison with a reference file
dataPlotRef = SK.getMatrix(
SK.SimpleMatrix(os.path.join(working_dir, 'data/BBallTSXML.ref')))
if np.linalg.norm(dataPlot - dataPlotRef, ord=np.inf) > 1e-12:
print(dataPlot - dataPlotRef)
print("ERROR: The result is rather different from the reference file.")
def test_xml1():
''' the BouncingBall '''
bouncingBall = buildModelXML(os.path.join(working_dir, 'data/BBallTS.xml'))
# --- Get the simulation ---
s = bouncingBall.simulation()
dsN = SK.dynamicalSystems(bouncingBall.nonSmoothDynamicalSystem().topology().dSG(0))[0].number()
ball = bouncingBall.nonSmoothDynamicalSystem().dynamicalSystem(dsN)
N = 2000 # Number of time steps
# saved in a matrix dataPlot
outputSize = 4
dataPlot = np.zeros((N + 1, outputSize))
q = ball.q()
v = ball.velocity()
p = ball.p(1)
dataPlot[0, 0] = bouncingBall.t0()
dataPlot[0, 1] = q[0]
dataPlot[0, 2] = v[0]
dataPlot[0, 3] = p[0]
print("====> Start computation ...")
# --- Time loop ---
k = 1
while s.hasNextEvent():
s.computeOneStep()
# --- Get values to be plotted ---
dataPlot[k, 0] = s.nextTime()
dataPlot[k, 1] = q[0]
dataPlot[k, 2] = v[0]
dataPlot[k, 3] = p[0]
s.nextStep()
k += 1
print("End of computation - Number of iterations done: {:}".format(k))
print("====> Output file writing ...")
dataPlot.resize(k, outputSize)
np.savetxt("BBallTS.dat", dataPlot)
# Comparison with a reference file
dataPlotRef = SK.getMatrix(SK.SimpleMatrix(os.path.join(working_dir, 'data/BBallTSXML.ref')))
if np.linalg.norm(dataPlot - dataPlotRef, ord=np.inf) > 1e-12:
print(dataPlot - dataPlotRef)
print("ERROR: The result is rather different from the reference file.")
# diode R1 current
dataPlot[k, 3] = y[0]
# diode R1 voltage
dataPlot[k, 4] = - lambda_[0]
# diode F2 voltage
dataPlot[k, 5] = - lambda_[1]
# diode F1 current
dataPlot[k, 6] = lambda_[2]
k += 1
aTS.nextStep()
# comparison with reference file
from siconos.kernel import SimpleMatrix, getMatrix
from numpy.linalg import norm
ref = getMatrix(SimpleMatrix("DiodeBridge.ref"))
error = norm(dataPlot[:,0:6] - ref[:,0:6])
print("error = " , error)
#assert (error < 1e-09)
withRef = True
if (withPlot):
#
# plots
#
subplot(411)
title('inductor voltage')
plot(dataPlot[0:k - 1, 0], dataPlot[0:k - 1, 1])
if (withRef):
plot(ref[0:k - 1, 0], ref[0:k - 1, 1])
def test_bouncing_ball1():
"""Run a complete simulation (Bouncing ball example)
LagrangianLinearTIDS, no plugins.
"""
t0 = 0. # start time
tend = 10. # end time
h = 0.005 # time step
r = 0.1 # ball radius
g = 9.81 # gravity
m = 1 # ball mass
e = 0.9 # restitution coeficient
theta = 0.5 # theta scheme
#
# dynamical system
#
x = np.zeros(3, dtype=np.float64)
x[0] = 1.
v = np.zeros_like(x)
# mass matrix
mass = np.eye(3, dtype=np.float64)
mass[2, 2] = 3. / 5 * r * r
# the dynamical system
ball = sk.LagrangianLinearTIDS(x, v, mass)
# set external forces
weight = np.zeros_like(x)
weight[0] = -m * g
ball.setFExtPtr(weight)
#
# Interactions
#
# ball-floor
H = np.zeros((1, 3), dtype=np.float64)
H[0, 0] = 1.
nslaw = sk.NewtonImpactNSL(e)
relation = sk.LagrangianLinearTIR(H)
inter = sk.Interaction(nslaw, relation)
#
# NSDS
#
bouncing_ball = sk.NonSmoothDynamicalSystem(t0, tend)
# add the dynamical system to the non smooth dynamical system
bouncing_ball.insertDynamicalSystem(ball)
# link the interaction and the dynamical system
bouncing_ball.link(inter, ball)
#
# Simulation
#
# (1) OneStepIntegrators
OSI = sk.MoreauJeanOSI(theta)
# (2) Time discretisation --
t = sk.TimeDiscretisation(t0, h)
# (3) one step non smooth problem
osnspb = sk.LCP()
# (4) Simulation setup with (1) (2) (3)
s = sk.TimeStepping(bouncing_ball,t, OSI, osnspb)
# end of model definition
#
# computation
#
#
# save and load data from xml and .dat
#
try:
from siconos.io import save
save(bouncing_ball, "bouncingBall.xml")
save(bouncing_ball, "bouncingBall.bin")
except:
print("Warning : could not import save from siconos.io")
# the number of time steps
nb_time_steps = int((tend - t0) / h + 1)
# Get the values to be plotted
# ->saved in a matrix dataPlot
data = np.empty((nb_time_steps, 5))
#
# numpy pointers on dense Siconos vectors
#
q = ball.q()
v = ball.velocity()
p = ball.p(1)
lambda_ = inter.lambda_(1)
#
# initial data
#
data[0, 0] = t0
data[0, 1] = q[0]
data[0, 2] = v[0]
data[0, 3] = p[0]
data[0, 4] = lambda_[0]
k = 1
# time loop
while(s.hasNextEvent()):
s.computeOneStep()
data[k, 0] = s.nextTime()
data[k, 1] = q[0]
data[k, 2] = v[0]
data[k, 3] = p[0]
data[k, 4] = lambda_[0]
k += 1
#print(s.nextTime())
s.nextStep()
#
# comparison with the reference file
#
ref = sk.getMatrix(sk.SimpleMatrix(
os.path.join(working_dir, "data/result.ref")))
assert (np.linalg.norm(data - ref) < 1e-12)
# inductor voltage
dataPlot[k, 1] = x[0]
# inductor current
dataPlot[k, 2] = x[1]
# diode voltage
dataPlot[k, 3] = - y[0]
# diode current
dataPlot[k, 4] = lambda_[0]
k += 1
aTS.nextStep()
# comparison with reference file
from siconos.kernel import SimpleMatrix, getMatrix
from numpy.linalg import norm
ref = getMatrix(SimpleMatrix("CircuitRLCD.ref"))
assert (norm(dataPlot - ref) < 1e-10)
if (withPlot):
#
# plots
#
subplot(411)
title('inductor voltage')
plot(dataPlot[0:k - 1, 0], dataPlot[0:k - 1, 1])
grid()
subplot(412)
title('inductor current')
plot(dataPlot[0:k - 1, 0], dataPlot[0:k - 1, 2])
grid()
# inductor voltage
dataPlot[k, 1] = x[0]
# inductor current
dataPlot[k, 2] = x[1]
# diode voltage
dataPlot[k, 3] = -y[0]
# diode current
dataPlot[k, 4] = lambda_[0]
k += 1
aTS.nextStep()
# comparison with reference file
from siconos.kernel import SimpleMatrix, getMatrix
from numpy.linalg import norm
ref = getMatrix(SimpleMatrix("CircuitRLCD.ref"))
assert (norm(dataPlot - ref) < 1e-10)
if (withPlot):
#
# plots
#
subplot(411)
title('inductor voltage')
plot(dataPlot[0:k - 1, 0], dataPlot[0:k - 1, 1])
grid()
subplot(412)
title('inductor current')
plot(dataPlot[0:k - 1, 0], dataPlot[0:k - 1, 2])
grid()
def test_diodebridge1():
from siconos.kernel import FirstOrderLinearDS, FirstOrderLinearTIR, \
ComplementarityConditionNSL, Interaction,\
Model, EulerMoreauOSI, TimeDiscretisation, LCP, \
TimeStepping
from numpy import empty
from siconos.kernel import SimpleMatrix, getMatrix
from numpy.linalg import norm
t0 = 0.0
T = 5.0e-3 # Total simulation time
h_step = 1.0e-6 # Time step
Lvalue = 1e-2 # inductance
Cvalue = 1e-6 # capacitance
Rvalue = 1e3 # resistance
Vinit = 10.0 # initial voltage
Modeltitle = "DiodeBridge"
#
# dynamical system
#
init_state = [Vinit, 0]
A = [[0, -1.0/Cvalue],
[1.0/Lvalue, 0 ]]
LSDiodeBridge=FirstOrderLinearDS(init_state, A)
#
# Interactions
#
C = [[0., 0.],
[0, 0.],
[-1., 0.],
[1., 0.]]
D = [[1./Rvalue, 1./Rvalue, -1., 0.],
[1./Rvalue, 1./Rvalue, 0., -1.],
[1., 0., 0., 0.],
[0., 1., 0., 0.]]
B = [[0., 0., -1./Cvalue, 1./Cvalue],
[0., 0., 0., 0. ]]
LTIRDiodeBridge=FirstOrderLinearTIR(C, B)
LTIRDiodeBridge.setDPtr(D)
LTIRDiodeBridge.display()
nslaw=ComplementarityConditionNSL(4)
InterDiodeBridge=Interaction(4, nslaw, LTIRDiodeBridge, 1)
#
# Model
#
DiodeBridge=Model(t0, T, Modeltitle)
# add the dynamical system in the non smooth dynamical system
DiodeBridge.nonSmoothDynamicalSystem().insertDynamicalSystem(LSDiodeBridge)
# link the interaction and the dynamical system
DiodeBridge.nonSmoothDynamicalSystem().link(InterDiodeBridge, LSDiodeBridge)
#
# Simulation
#
# (1) OneStepIntegrators
theta = 0.5
aOSI = EulerMoreauOSI(LSDiodeBridge, theta)
# (2) Time discretisation
aTiDisc = TimeDiscretisation(t0, h_step)
# (3) Non smooth problem
aLCP = LCP()
# (4) Simulation setup with (1) (2) (3)
aTS = TimeStepping(aTiDisc, aOSI, aLCP)
# end of model definition
#
# computation
#
# simulation initialization
DiodeBridge.initialize(aTS)
k = 0
h = aTS.timeStep()
print("Timestep : ", h)
# Number of time steps
N = (T-t0)/h
print("Number of steps : ", N)
# Get the values to be plotted
# ->saved in a matrix dataPlot
dataPlot = empty([N, 8])
x = LSDiodeBridge.x()
print("Initial state : ", x)
y = InterDiodeBridge.y(0)
print("First y : ", y)
lambda_ = InterDiodeBridge.lambda_(0)
# For the initial time step:
# time
dataPlot[k, 0] = t0
# inductor voltage
dataPlot[k, 1] = x[0]
# inductor current
dataPlot[k, 2] = x[1]
# diode R1 current
dataPlot[k, 3] = y[0]
# diode R1 voltage
dataPlot[k, 4] = - lambda_[0]
# diode F2 voltage
dataPlot[k, 5] = - lambda_[1]
# diode F1 current
dataPlot[k, 6] = lambda_[2]
# resistor current
dataPlot[k, 7] = y[0] + lambda_[2]
k += 1
while (k < N):
aTS.computeOneStep()
#aLCP.display()
dataPlot[k, 0] = aTS.nextTime()
# inductor voltage
dataPlot[k, 1] = x[0]
# inductor current
dataPlot[k, 2] = x[1]
# diode R1 current
dataPlot[k, 3] = y[0]
# diode R1 voltage
dataPlot[k, 4] = - lambda_[0]
# diode F2 voltage
dataPlot[k, 5] = - lambda_[1]
# diode F1 current
dataPlot[k, 6] = lambda_[2]
# resistor current
dataPlot[k, 7] = y[0] + lambda_[2]
k += 1
aTS.nextStep()
#
# comparison with the reference file
#
ref = getMatrix(SimpleMatrix(os.path.join(working_dir,"data/diode_bridge.ref")))
print(norm(dataPlot - ref))
assert (norm(dataPlot - ref) < 1e-12)
return ref, dataPlot
# diode R1 current
dataPlot[k, 3] = y[0]
# diode R1 voltage
dataPlot[k, 4] = -lambda_[0]
# diode F2 voltage
dataPlot[k, 5] = -lambda_[1]
# diode F1 current
dataPlot[k, 6] = lambda_[2]
k += 1
aTS.nextStep()
# comparison with reference file
from siconos.kernel import SimpleMatrix, getMatrix
from numpy.linalg import norm
ref = getMatrix(SimpleMatrix("DiodeBridge.ref"))
error = norm(dataPlot[:, 0:6] - ref[:, 0:6])
print("error = ", error)
#assert (error < 1e-09)
withRef = True
if (withPlot):
#
# plots
#
subplot(411)
title('inductor voltage')
plot(dataPlot[0:k - 1, 0], dataPlot[0:k - 1, 1])
if (withRef):
plot(ref[0:k - 1, 0], ref[0:k - 1, 1])
def test_diode_bridge():
"""Build diode bridge model"""
# dynamical system
bridge_ds = FirstOrderLinearDS(init_state, A)
# interaction
diode_bridge_relation = FirstOrderLinearTIR(C, B)
diode_bridge_relation.setDPtr(D)
nslaw = ComplementarityConditionNSL(4)
bridge_interaction = Interaction(4, nslaw, diode_bridge_relation, 1)
# Model
diode_bridge = Model(t0, total_time, model_title)
# add the dynamical system in the non smooth dynamical system
diode_bridge.nonSmoothDynamicalSystem().insertDynamicalSystem(bridge_ds)
# link the interaction and the dynamical system
diode_bridge.nonSmoothDynamicalSystem().link(bridge_interaction, bridge_ds)
# Simulation
# (1) OneStepIntegrators
theta = 0.5
integrator = EulerMoreauOSI(theta)
# (2) Time discretisation
time_discretisation = TimeDiscretisation(t0, time_step)
# (3) Non smooth problem
non_smooth_problem = LCP()
# (4) Simulation setup with (1) (2) (3)
bridge_simulation = TimeStepping(time_discretisation,
integrator, non_smooth_problem)
# simulation initialization
diode_bridge.setSimulation(bridge_simulation)
diode_bridge.initialize()
k = 0
h = bridge_simulation.timeStep()
# Number of time steps
N = (total_time - t0) / h
# Get the values to be plotted
# ->saved in a matrix dataPlot
data_plot = empty([N, 8])
x = bridge_ds.x()
print("Initial state : ", x)
y = bridge_interaction.y(0)
print("First y : ", y)
lambda_ = bridge_interaction.lambda_(0)
# For the initial time step:
# time
data_plot[k, 0] = t0
# inductor voltage
data_plot[k, 1] = x[0]
# inductor current
data_plot[k, 2] = x[1]
# diode R1 current
data_plot[k, 3] = y[0]
# diode R1 voltage
data_plot[k, 4] = - lambda_[0]
# diode F2 voltage
data_plot[k, 5] = - lambda_[1]
# diode F1 current
data_plot[k, 6] = lambda_[2]
# resistor current
data_plot[k, 7] = y[0] + lambda_[2]
k += 1
while k < N:
bridge_simulation.computeOneStep()
#non_smooth_problem.display()
data_plot[k, 0] = bridge_simulation.nextTime()
# inductor voltage
data_plot[k, 1] = x[0]
# inductor current
data_plot[k, 2] = x[1]
# diode R1 current
data_plot[k, 3] = y[0]
# diode R1 voltage
data_plot[k, 4] = - lambda_[0]
# diode F2 voltage
data_plot[k, 5] = - lambda_[1]
# diode F1 current
data_plot[k, 6] = lambda_[2]
# resistor current
data_plot[k, 7] = y[0] + lambda_[2]
k += 1
bridge_simulation.nextStep()
#
# comparison with the reference file
#
ref = getMatrix(SimpleMatrix(os.path.join(working_dir,
"data/diode_bridge.ref")))
assert norm(data_plot - ref) < 1e-12
return ref, data_plot
def test_bouncing_ball1():
from siconos.kernel import LagrangianLinearTIDS, NewtonImpactNSL, \
LagrangianLinearTIR, Interaction, Model, MoreauJeanOSI, TimeDiscretisation, LCP, TimeStepping
from numpy import array, eye, empty
t0 = 0 # start time
T = 10 # end time
h = 0.005 # time step
r = 0.1 # ball radius
g = 9.81 # gravity
m = 1 # ball mass
e = 0.9 # restitution coeficient
theta = 0.5 # theta scheme
#
# dynamical system
#
x = array([1, 0, 0]) # initial position
v = array([0, 0, 0]) # initial velocity
mass = eye(3) # mass matrix
mass[2, 2] = 3./5 * r * r
# the dynamical system
ball = LagrangianLinearTIDS(x, v, mass)
# set external forces
weight = array([-m * g, 0, 0])
ball.setFExtPtr(weight)
#
# Interactions
#
# ball-floor
H = array([[1, 0, 0]])
nslaw = NewtonImpactNSL(e)
relation = LagrangianLinearTIR(H)
inter = Interaction(1, nslaw, relation)
#
# Model
#
bouncingBall = Model(t0, T)
# add the dynamical system to the non smooth dynamical system
bouncingBall.nonSmoothDynamicalSystem().insertDynamicalSystem(ball)
# link the interaction and the dynamical system
bouncingBall.nonSmoothDynamicalSystem().link(inter, ball)
#
# Simulation
#
# (1) OneStepIntegrators
OSI = MoreauJeanOSI(theta)
OSI.insertDynamicalSystem(ball)
# (2) Time discretisation --
t = TimeDiscretisation(t0, h)
# (3) one step non smooth problem
osnspb = LCP()
# (4) Simulation setup with (1) (2) (3)
s = TimeStepping(t)
s.insertIntegrator(OSI)
s.insertNonSmoothProblem(osnspb)
# end of model definition
#
# computation
#
# simulation initialization
bouncingBall.initialize(s)
#
# save and load data from xml and .dat
#
try:
from siconos.io import save
save(bouncingBall, "bouncingBall.xml")
save(bouncingBall, "bouncingBall.bin")
except:
print("Warning : could not import save from siconos.io")
# the number of time steps
N = (T-t0)/h+1
# Get the values to be plotted
# ->saved in a matrix dataPlot
dataPlot = empty((N, 5))
#
# numpy pointers on dense Siconos vectors
#
q = ball.q()
v = ball.velocity()
p = ball.p(1)
lambda_ = inter.lambda_(1)
#
# initial data
#
dataPlot[0, 0] = t0
dataPlot[0, 1] = q[0]
dataPlot[0, 2] = v[0]
dataPlot[0, 3] = p[0]
dataPlot[0, 4] = lambda_[0]
k = 1
# time loop
while(s.hasNextEvent()):
s.computeOneStep()
dataPlot[k, 0] = s.nextTime()
dataPlot[k, 1] = q[0]
dataPlot[k, 2] = v[0]
dataPlot[k, 3] = p[0]
dataPlot[k, 4] = lambda_[0]
k += 1
#print(s.nextTime())
s.nextStep()
#
# comparison with the reference file
#
from siconos.kernel import SimpleMatrix, getMatrix
from numpy.linalg import norm
ref = getMatrix(SimpleMatrix(os.path.join(working_dir, "data/result.ref")))
assert (norm(dataPlot - ref) < 1e-12)
sim.initialize()
# Run simulation
sim.run()
# Get data
dataPlot = sim.data()
# Save to disk
savetxt('SMCExampleImplicitOT2-noCplugin-sage-py.dat', dataPlot)
# Plot interesting data
subplot(411)
title('x1')
plot(dataPlot[:, 0], dataPlot[:, 1])
grid()
subplot(412)
title('x2')
plot(dataPlot[:, 0], dataPlot[:, 2])
grid()
subplot(413)
title('u')
plot(dataPlot[:, 0], dataPlot[:, 3])
savefig('ismcOT2_x_u.png')
# compare with the reference
ref = getMatrix(SimpleMatrix("SMCExampleImplicitOT2-py.ref"))
print("%19e" % norm(dataPlot - ref))
if (norm(dataPlot - ref) > 1e-12):
print(dataPlot - ref)
print("Warning. The result is rather different from the reference file.")
def test_xml5():
''' Bouncing Ball ED '''
# --- buildModelXML loading from xml file ---
bouncingBall = buildModelXML(os.path.join(working_dir, 'data/BBallED.xml'))
# --- Get and initialize the simulation ---
s = bouncingBall.simulation()
dsN = SK.dynamicalSystems(bouncingBall.nonSmoothDynamicalSystem().topology().dSG(0))[0].number()
ball = bouncingBall.nonSmoothDynamicalSystem().dynamicalSystem(dsN)
# --- Get the values to be plotted ---
# . saved in a matrix dataPlot
N = 12368 # Number of saved points: depends on the number of events ...
outputSize = 5
dataPlot = np.zeros((N + 1, outputSize))
q = ball.q()
v = ball.velocity()
p = ball.p(1)
f = ball.p(2)
dataPlot[0, 0] = bouncingBall.t0()
dataPlot[0, 1] = q[0]
dataPlot[0, 2] = v[0]
dataPlot[0, 3] = p[0]
dataPlot[0, 4] = f[0]
print("====> Start computation ... ")
# --- Time loop ---
eventsManager = s.eventsManager()
numberOfEvent = 0
k = 0
nonSmooth = False
while s.hasNextEvent():
k += 1
s.advanceToEvent()
if eventsManager.nextEvent().getType() == 2:
nonSmooth = True
s.processEvents()
# If the treated event is non smooth, the pre-impact state has been solved in memory vectors during process.
if nonSmooth:
dataPlot[k, 0] = s.startingTime()
dataPlot[k, 1] = ball.qMemory().getSiconosVector(1)[0]
dataPlot[k, 2] = ball.velocityMemory().getSiconosVector(1)[0]
k += 1
nonSmooth = False
dataPlot[k, 0] = s.startingTime()
dataPlot[k, 1] = q[0]
dataPlot[k, 2] = v[0]
dataPlot[k, 3] = p[0]
dataPlot[k, 4] = f[0]
numberOfEvent += 1
# --- Output files ---
dataPlot.resize(k, outputSize)
np.savetxt("BBallED.dat", dataPlot)
# Comparison with a reference file
dataPlotRef = SK.getMatrix(SK.SimpleMatrix(os.path.join(working_dir, 'data/BouncingBallEDXml.ref')))
if np.linalg.norm(dataPlot - dataPlotRef, ord=np.inf) > 1e-11:
print("Warning. The results is rather different from the reference file.")
print(np.linalg.norm(dataPlot - dataPlotRef, ord=np.inf))
exit(1)
index1 = sk.interactions(simulation.indexSet(1))
if (len(index1) == 4):
dataPlot[k, 3] = norm(index1[0].lambda_(1)) + \
norm(index1[1].lambda_(1)) + norm(index1[2].lambda_(1)) + \
norm(index1[3].lambda_(1))
k += 1
simulation.nextStep()
#
# comparison with the reference file
#
from siconos.kernel import SimpleMatrix, getMatrix
from numpy.linalg import norm
ref = getMatrix(SimpleMatrix("result_dynamic.ref"))
print("norm(dataPlot - ref) = {0}".format(norm(dataPlot - ref)))
if (norm(dataPlot - ref) > 1e-11):
print("Warning. The result is rather different from the reference file.")
#
# plots
#
from matplotlib.pyplot import subplot, title, plot, grid, show
subplot(511)
title('position')
plot(dataPlot[0:k, 0], dataPlot[0:k, 1])
def test_diode_bridge():
"""Build diode bridge model"""
# dynamical system
bridge_ds = FirstOrderLinearDS(init_state, A)
# interaction
diode_bridge_relation = FirstOrderLinearTIR(C, B)
diode_bridge_relation.setDPtr(D)
nslaw = ComplementarityConditionNSL(4)
bridge_interaction = Interaction(4, nslaw, diode_bridge_relation, 1)
# Model
diode_bridge = Model(t0, total_time, model_title)
# add the dynamical system in the non smooth dynamical system
diode_bridge.nonSmoothDynamicalSystem().insertDynamicalSystem(bridge_ds)
# link the interaction and the dynamical system
diode_bridge.nonSmoothDynamicalSystem().link(bridge_interaction, bridge_ds)
# Simulation
# (1) OneStepIntegrators
theta = 0.5
integrator = EulerMoreauOSI(theta)
integrator.insertDynamicalSystem(bridge_ds)
# (2) Time discretisation
time_discretisation = TimeDiscretisation(t0, time_step)
# (3) Non smooth problem
non_smooth_problem = LCP()
# (4) Simulation setup with (1) (2) (3)
bridge_simulation = TimeStepping(time_discretisation, integrator,
non_smooth_problem)
# simulation initialization
diode_bridge.initialize(bridge_simulation)
k = 0
h = bridge_simulation.timeStep()
# Number of time steps
N = (total_time - t0) / h
# Get the values to be plotted
# ->saved in a matrix dataPlot
data_plot = empty([N, 8])
x = bridge_ds.x()
print("Initial state : ", x)
y = bridge_interaction.y(0)
print("First y : ", y)
lambda_ = bridge_interaction.lambda_(0)
# For the initial time step:
# time
data_plot[k, 0] = t0
# inductor voltage
data_plot[k, 1] = x[0]
# inductor current
data_plot[k, 2] = x[1]
# diode R1 current
data_plot[k, 3] = y[0]
# diode R1 voltage
data_plot[k, 4] = -lambda_[0]
# diode F2 voltage
data_plot[k, 5] = -lambda_[1]
# diode F1 current
data_plot[k, 6] = lambda_[2]
# resistor current
data_plot[k, 7] = y[0] + lambda_[2]
k += 1
while k < N:
bridge_simulation.computeOneStep()
#non_smooth_problem.display()
data_plot[k, 0] = bridge_simulation.nextTime()
# inductor voltage
data_plot[k, 1] = x[0]
# inductor current
data_plot[k, 2] = x[1]
# diode R1 current
data_plot[k, 3] = y[0]
# diode R1 voltage
data_plot[k, 4] = -lambda_[0]
# diode F2 voltage
data_plot[k, 5] = -lambda_[1]
# diode F1 current
data_plot[k, 6] = lambda_[2]
# resistor current
data_plot[k, 7] = y[0] + lambda_[2]
k += 1
bridge_simulation.nextStep()
#
# comparison with the reference file
#
ref = getMatrix(
SimpleMatrix(os.path.join(working_dir, "data/diode_bridge.ref")))
assert norm(data_plot - ref) < 1e-12
return ref, data_plot
dataPlot[k, 0] = aTS.nextTime()
# inductor voltage
dataPlot[k, 1] = x[0]
# inductor current
dataPlot[k, 2] = x[1]
# diode voltage
dataPlot[k, 3] = -y[0]
# diode current
dataPlot[k, 4] = lambda_[0]
dataPlot[k, 5] = 0.
k += 1
aTS.nextStep()
# comparison with reference file
ref = sk.getMatrix(sk.SimpleMatrix("CircuitRLCD.ref"))
#assert (np.linalg.norm(dataPlot - ref) < 1e-10)
if (withPlot):
#
# plots
#
subplot(411)
title('inductor voltage')
plot(dataPlot[0:k - 1, 0], dataPlot[0:k - 1, 1])
grid()
subplot(412)
title('inductor current')
plot(dataPlot[0:k - 1, 0], dataPlot[0:k - 1, 2])
grid()
while s.hasNextEvent():
s.computeOneStep()
dataPlot[k, 0] = s.nextTime()
dataPlot[k, 1] = q[0]
dataPlot[k, 2] = v[0]
dataPlot[k, 3] = p[0]
dataPlot[k, 4] = lambda_[0]
k += 1
s.nextStep()
#
# comparison with the reference file
#
ref = getMatrix(SimpleMatrix("BouncingBallTS.ref"))
if (norm(dataPlot - ref) > 1e-12):
print("Warning. The result is rather different from the reference file.")
print(norm(dataPlot - ref))
#
# plots
#
havedisplay = "DISPLAY" in os.environ
if not havedisplay:
matplotlib.use('Agg')
plt.subplot(411)
plt.title('position')
plt.plot(dataPlot[:, 0], dataPlot[:, 1])
def test_serialization4():
from siconos.kernel import LagrangianLinearTIDS, NewtonImpactNSL, \
LagrangianLinearTIR, Interaction, Model, MoreauJeanOSI, TimeDiscretisation, LCP, TimeStepping
from numpy import array, eye, empty
t0 = 0 # start time
T = 10 # end time
h = 0.005 # time step
r = 0.1 # ball radius
g = 9.81 # gravity
m = 1 # ball mass
e = 0.9 # restitution coeficient
theta = 0.5 # theta scheme
#
# dynamical system
#
x = array([1, 0, 0]) # initial position
v = array([0, 0, 0]) # initial velocity
mass = eye(3) # mass matrix
mass[2, 2] = 3./5 * r * r
# the dynamical system
ball = LagrangianLinearTIDS(x, v, mass)
# set external forces
weight = array([-m * g, 0, 0])
ball.setFExtPtr(weight)
#
# Interactions
#
# ball-floor
H = array([[1, 0, 0]])
nslaw = NewtonImpactNSL(e)
relation = LagrangianLinearTIR(H)
inter = Interaction(1, nslaw, relation)
#
# Model
#
first_bouncingBall = Model(t0, T)
# add the dynamical system to the non smooth dynamical system
first_bouncingBall.nonSmoothDynamicalSystem().insertDynamicalSystem(ball)
# link the interaction and the dynamical system
first_bouncingBall.nonSmoothDynamicalSystem().link(inter, ball)
#
# Simulation
#
# (1) OneStepIntegrators
OSI = MoreauJeanOSI(theta)
# (2) Time discretisation --
t = TimeDiscretisation(t0, h)
# (3) one step non smooth problem
osnspb = LCP()
# (4) Simulation setup with (1) (2) (3)
s = TimeStepping(t)
s.insertIntegrator(OSI)
s.insertNonSmoothProblem(osnspb)
# end of model definition
#
# computation
#
# simulation initialization
first_bouncingBall.setSimulation(s)
first_bouncingBall.initialize()
#
# save and load data from xml and .dat
#
from siconos.io.io_base import save, load
save(first_bouncingBall, "bouncingBall.xml")
bouncingBall = load("bouncingBall.xml")
# the number of time steps
N = (T-t0)/h+1
# Get the values to be plotted
# ->saved in a matrix dataPlot
dataPlot = empty((N, 5))
#
# numpy pointers on dense Siconos vectors
#
q = ball.q()
v = ball.velocity()
p = ball.p(1)
lambda_ = inter.lambda_(1)
#
# initial data
#
dataPlot[0, 0] = t0
dataPlot[0, 1] = q[0]
dataPlot[0, 2] = v[0]
dataPlot[0, 3] = p[0]
dataPlot[0, 4] = lambda_[0]
k = 1
# time loop
while(s.hasNextEvent()):
s.computeOneStep()
dataPlot[k, 0] = s.nextTime()
dataPlot[k, 1] = q[0]
dataPlot[k, 2] = v[0]
dataPlot[k, 3] = p[0]
dataPlot[k, 4] = lambda_[0]
k += 1
print(s.nextTime())
s.nextStep()
#
# comparison with the reference file
#
from siconos.kernel import SimpleMatrix, getMatrix
from numpy.linalg import norm
ref = getMatrix(SimpleMatrix(os.path.join(working_dir,
"data/result.ref")))
assert (norm(dataPlot - ref) < 1e-12)
subplot(411)
title('x1')
plot(dataPlot[:, 0], dataPlot[:, 1])
grid()
subplot(412)
title('x2')
plot(dataPlot[:, 0], dataPlot[:, 2])
grid()
subplot(413)
title('u')
plot(dataPlot[:, 0], dataPlot[:, 3])
grid()
savefig('ismcOT2_x_u')
subplot(211)
p1 = plot(dataPlot[:, 0], dataPlot[:, 2])
plt.ylabel('$\sigma$')
plt.xlabel('t')
grid()
subplot(212)
p2 = plot(dataPlot[:, 0], dataPlot[:, 3])
plt.ylabel('u')
plt.xlabel('t')
savefig('ismcOT2_sigma_u')
# TODO
# compare with the reference
ref = getMatrix(SimpleMatrix("SMCExampleImplicitOT2-py.ref"))
if (norm(dataPlot - ref) > 1e-12):
print("Warning. The result is rather different from the reference file.")
dataPlot[k, 10] = q[3]
dataPlot[k, 11] = q[4]
dataPlot[k, 12] = q[5]
dataPlot[k, 13] = q[6]
dataPlot[k, 14] = v[1]
dataPlot[k, 15] = v[2]
k = k + 1
s.nextStep()
savetxt("result-py.dat", dataPlot)
#
# comparison with the reference file
#
from siconos.kernel import SimpleMatrix, getMatrix
ref = getMatrix(SimpleMatrix("resultNETS.ref"))
err = linalg.norm(dataPlot - ref)
print("error w.r.t reference file =", err)
if (err > 1e-12):
print("Warning. The result is rather different from the reference file.")
#
# plots
#
from matplotlib.pyplot import subplot, title, plot, grid, show
subplot(411)
title('position')
plot(dataPlot[:, 0], dataPlot[:, 1])
index1 = sk.interactions(simulation.indexSet(1))
if (len(index1) == 4):
dataPlot[k, 3] = norm(index1[0].lambda_(1)) + \
norm(index1[1].lambda_(1)) + norm(index1[2].lambda_(1)) + \
norm(index1[3].lambda_(1))
k += 1
simulation.nextStep()
#
# comparison with the reference file
#
from siconos.kernel import SimpleMatrix, getMatrix
from numpy.linalg import norm
ref = getMatrix(SimpleMatrix("result_dynamic.ref"))
print("norm(dataPlot - ref) = {0}".format(norm(dataPlot - ref)))
if (norm(dataPlot - ref) > 1e-11):
print("Warning. The result is rather different from the reference file.")
#
# plots
#
if do_plot:
subplot(511)
title('position')
plot(dataPlot[0:k, 0], dataPlot[0:k, 1])
y = ylim()
plot(ref[0:k, 0], ref[0:k, 1])
# diode R1 current
dataPlot[k, 3] = lambda_[0]
# diode R1 voltage
dataPlot[k, 4] = -y[0]
# diode F2 voltage
dataPlot[k, 5] = -lambda_[1]
# diode F1 current
dataPlot[k, 6] = lambda_[2]
k += 1
aTS.nextStep()
# comparison with reference file
from siconos.kernel import SimpleMatrix, getMatrix
from numpy.linalg import norm
ref = getMatrix(SimpleMatrix("DiodeBridgeCapFilter.ref"))
error = norm(dataPlot[:, 0:4] - ref[:, 0:4])
print("error = ", error)
assert (error < 1e-09)
withRef = False
if (withPlot):
#
# plots
#
subplot(411)
title('inductor voltage')
plot(dataPlot[0:k - 1, 0], dataPlot[0:k - 1, 1])
if (withRef):
plot(ref[0:k - 1, 0], ref[0:k - 1, 1])
def test_bouncing_ball1():
"""Run a complete simulation (Bouncing ball example)
LagrangianLinearTIDS, no plugins.
"""
t0 = 0. # start time
tend = 10. # end time
h = 0.005 # time step
r = 0.1 # ball radius
g = 9.81 # gravity
m = 1 # ball mass
e = 0.9 # restitution coeficient
theta = 0.5 # theta scheme
#
# dynamical system
#
x = np.zeros(3, dtype=np.float64)
x[0] = 1.
v = np.zeros_like(x)
# mass matrix
mass = np.eye(3, dtype=np.float64)
mass[2, 2] = 3. / 5 * r * r
# the dynamical system
ball = sk.LagrangianLinearTIDS(x, v, mass)
# set external forces
weight = np.zeros_like(x)
weight[0] = -m * g
ball.setFExtPtr(weight)
#
# Interactions
#
# ball-floor
H = np.zeros((1, 3), dtype=np.float64)
H[0, 0] = 1.
nslaw = sk.NewtonImpactNSL(e)
relation = sk.LagrangianLinearTIR(H)
inter = sk.Interaction(nslaw, relation)
#
# NSDS
#
bouncing_ball = sk.NonSmoothDynamicalSystem(t0, tend)
# add the dynamical system to the non smooth dynamical system
bouncing_ball.insertDynamicalSystem(ball)
# link the interaction and the dynamical system
bouncing_ball.link(inter, ball)
#
# Simulation
#
# (1) OneStepIntegrators
OSI = sk.MoreauJeanOSI(theta)
# (2) Time discretisation --
t = sk.TimeDiscretisation(t0, h)
# (3) one step non smooth problem
osnspb = sk.LCP()
# (4) Simulation setup with (1) (2) (3)
s = sk.TimeStepping(bouncing_ball,t, OSI, osnspb)
# end of model definition
#
# computation
#
#
# save and load data from xml and .dat
#
try:
from siconos.io import save
save(bouncing_ball, "bouncingBall.xml")
save(bouncing_ball, "bouncingBall.bin")
except:
print("Warning : could not import save from siconos.io")
# the number of time steps
nb_time_steps = int((tend - t0) / h + 1)
# Get the values to be plotted
# ->saved in a matrix dataPlot
data = np.empty((nb_time_steps, 5))
#
# numpy pointers on dense Siconos vectors
#
q = ball.q()
v = ball.velocity()
p = ball.p(1)
lambda_ = inter.lambda_(1)
#
# initial data
#
data[0, 0] = t0
data[0, 1] = q[0]
data[0, 2] = v[0]
data[0, 3] = p[0]
data[0, 4] = lambda_[0]
k = 1
# time loop
while(s.hasNextEvent()):
s.computeOneStep()
data[k, 0] = s.nextTime()
data[k, 1] = q[0]
data[k, 2] = v[0]
data[k, 3] = p[0]
data[k, 4] = lambda_[0]
k += 1
#print(s.nextTime())
s.nextStep()
#
# comparison with the reference file
#
ref = sk.getMatrix(sk.SimpleMatrix(
os.path.join(working_dir, "data/result.ref")))
assert (np.linalg.norm(data - ref) < 1e-12)
# diode R1 current
dataPlot[k, 3] = lambda_[0]
# diode R1 voltage
dataPlot[k, 4] = - y[0]
# diode F2 voltage
dataPlot[k, 5] = - lambda_[1]
# diode F1 current
dataPlot[k, 6] = lambda_[2]
k += 1
aTS.nextStep()
# comparison with reference file
from siconos.kernel import SimpleMatrix, getMatrix
from numpy.linalg import norm
ref = getMatrix(SimpleMatrix("DiodeBridgeCapFilter.ref"))
error = norm(dataPlot[:,0:6] - ref[:,0:6])
print "error = " , error
#assert (error < 1e-09)
withRef = False
if (withPlot):
#
# plots
#
subplot(411)
title('inductor voltage')
plot(dataPlot[0:k - 1, 0], dataPlot[0:k - 1, 1])
if (withRef):
plot(ref[0:k - 1, 0], ref[0:k - 1, 1])
dataPlot[k, 0] = s.nextTime()
dataPlot[k, 1] = q[0]
dataPlot[k, 2] = v[0]
dataPlot[k, 3] = p[0]
dataPlot[k, 4] = lambda_[0]
k += 1
s.nextStep()
#
# comparison with the reference file
#
from siconos.kernel import SimpleMatrix, getMatrix
from numpy.linalg import norm
ref = getMatrix(SimpleMatrix("result.ref"))
if (norm(dataPlot - ref) > 1e-12):
print("Warning. The result is rather different from the reference file.")
#
# plots
#
import matplotlib,os
havedisplay = "DISPLAY" in os.environ
if not havedisplay:
matplotlib.use('Agg')
import matplotlib.pyplot as plt
plt.subplot(411)
dataPlot[k, 10] = q[3]
dataPlot[k, 11] = q[4]
dataPlot[k, 12] = q[5]
dataPlot[k, 13] = q[6]
dataPlot[k, 14] = v[1]
dataPlot[k, 15] = v[2]
k = k + 1
s.nextStep()
savetxt("result-py.dat", dataPlot)
#
# comparison with the reference file
#
from siconos.kernel import SimpleMatrix, getMatrix
ref = getMatrix(SimpleMatrix("resultNETS.ref"))
err = linalg.norm(dataPlot - ref)
print("error w.r.t reference file =", err)
if (err > 1e-12):
print("Warning. The result is rather different from the reference file.")
#
# plots
#
from matplotlib.pyplot import subplot, title, plot, grid, show
subplot(411)
title('position')
plot(dataPlot[:, 0], dataPlot[:, 1])
grid()
