# -- (2) Time discretisation --
t = TimeDiscretisation(t0,h)
# -- (3) one step non smooth problem
osnspb = LCP()
s = TimeStepping(impactingBar, t,OSI,osnspb)
k =0
N = int((T-t0)/h)
dataPlot = np.zeros((N+1, 5))
q = bar.q()
v = bar.velocity()
p = bar.p(1)
lambda_ = inter.lambda_(1)
# time loop
while s.hasNextEvent():
s.computeOneStep()
dataPlot[k, 0] = s.nextTime()
print('time=', dataPlot[k, 0])
dataPlot[k, 1] = q[0]
dataPlot[k, 2] = v[0]
dataPlot[k, 3] = p[0]/h
dataPlot[k, 4] = lambda_[0]
k += 1
s.nextStep()
# the number of time steps N = (T - t0) / h # Get the values to be plotted # ->saved in a matrix dataPlot dataPlot = empty((N+1, 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
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)
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)
# -- (2) Time discretisation --
t = TimeDiscretisation(t0, h)
# -- (3) one step non smooth problem
osnspb = LCP()
s = TimeStepping(impactingBar, t, OSI, osnspb)
k = 0
N = int((T - t0) / h)
dataPlot = np.zeros((N + 1, 5))
q = body.q()
v = body.velocity()
p = body.p(1)
#lambda_ = inter.lambda_(1)
# time loop
while s.hasNextEvent():
s.computeOneStep()
dataPlot[k, 0] = s.nextTime()
print('time=', dataPlot[k, 0])
print('q=', q)
dataPlot[k, 1] = q[n_dof - 1]
dataPlot[k, 2] = v[n_dof - 1]
dataPlot[k, 3] = p[n_dof - 1] / h
#dataPlot[k, 4] = lambda_[0]
k += 1
s.nextStep()
