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.setSimulation(aTS) DiodeBridge.initialize() k = 0 h = aTS.timeStep() print("Timestep : ", h) # Number of time steps N = int((T - t0) / h) print("Number of steps : ", N) # Get the values to be plotted # ->saved in a matrix dataPlot from numpy import zeros dataPlot = zeros([N, 10])
td = TimeDiscretisation(t0, h) s = TimeStepping(td) myIntegrator = EulerMoreauOSI(theta) s.insertIntegrator(myIntegrator) #TODO python <- SICONOS_RELAY_LEMKE # access dparam osnspb = Relay() s.insertNonSmoothProblem(osnspb) s.setComputeResiduY(True) s.setComputeResiduR(True) filippov.setSimulation(s) filippov.initialize() # matrix to save data dataPlot = empty((N+1,5)) control = empty((N+1,)) dataPlot[0, 0] = t0 dataPlot[0, 1:3] = process.x() dataPlot[0, 3] = myProcessInteraction.lambda_(0)[0] dataPlot[0, 4] = myProcessInteraction.lambda_(0)[1] # time loop k = 1 while(s.hasNextEvent()): s.newtonSolve(1e-14, 30) dataPlot[k, 0] = s.nextTime() dataPlot[k, 1] = process.x()[0]
td = TimeDiscretisation(t0, h) s = TimeStepping(td) myIntegrator = EulerMoreauOSI(theta) s.insertIntegrator(myIntegrator) #TODO python <- SICONOS_RELAY_LEMKE # access dparam osnspb = Relay() s.insertNonSmoothProblem(osnspb) s.setComputeResiduY(True) s.setComputeResiduR(True) filippov.setSimulation(s) filippov.initialize() # matrix to save data dataPlot = empty((N+1,5)) dataPlot[0, 0] = t0 dataPlot[0, 1:3] = process.x() dataPlot[0, 3] = myProcessInteraction.lambda_(0)[0] dataPlot[0, 4] = myProcessInteraction.lambda_(0)[1] # time loop k = 1 while(s.hasNextEvent()): s.newtonSolve(1e-12, 40) dataPlot[k, 0] = s.nextTime() dataPlot[k, 1] = process.x()[0] dataPlot[k, 2] = process.x()[1]
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.setSimulation(aTS) DiodeBridge.initialize() 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 from numpy import zeros dataPlot = zeros([N, 8])
# (3) one step non smooth problem osnspb = LCP() # (4) Simulation setup with (1) (2) (3) s = TimeStepping(t, OSI, osnspb) # end of model definition # # computation # # simulation initialization bouncingBall.setSimulation(s) bouncingBall.initialize() # 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()
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.setDisplayNewtonConvergence(True) s.setNewtonTolerance(1e-10) #s.setNewtonMaxIteration(1) s.insertIntegrator(OSI) s.insertNonSmoothProblem(osnspb) model.setSimulation(s) # end of model definition # # computation # # simulation initialization model.initialize() # Get the values to be plotted # ->saved in a matrix dataPlot dataPlot = np.empty((N + 1, 26)) # # numpy pointers on dense Siconos vectors #
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
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 CircuitRLCD.setSimulation(aTS) CircuitRLCD.initialize() 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 from numpy import zeros dataPlot = zeros([N+1, 6])
aTiDisc = TimeDiscretisation(t0,h_step) # (3) Non smooth problem aRelay = Relay() # (4) Simulation setup with (1) (2) (3) aTS = TimeStepping(aTiDisc,aOSI,aRelay) # end of model definition # # computation # # simulation initialization RelayOscillator.setSimulation(aTS) RelayOscillator.initialize() 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 from numpy import empty dataPlot = empty([N+1,8])
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 DiodeBridgeCapFilter.setSimulation(aTS) DiodeBridgeCapFilter.initialize() 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 from numpy import zeros dataPlot = zeros([N-1, 10])
def test_smc1(): from siconos.kernel import FirstOrderLinearDS, Model, TimeDiscretisation, \ TimeStepping, ZeroOrderHoldOSI, TD_EVENT from siconos.control.simulation import ControlManager from siconos.control.sensor import LinearSensor from siconos.control.controller import LinearSMCOT2 from numpy import eye, empty, zeros import numpy as np from math import ceil, sin # Derive our own version of FirstOrderLinearDS class MyFOLDS(FirstOrderLinearDS): def computeb(self, time): t = sin(50 * time) # XXX fix this ! u = [t, -t] self.setbPtr(u) # variable declaration ndof = 2 # Number of degrees of freedom of your system t0 = 0.0 # start time T = 1 # end time h = 1.0e-4 # time step for simulation hControl = 1.0e-2 # time step for control Xinit = 1.0 # initial position N = int(ceil((T - t0) / h + 10)) # number of time steps outputSize = 4 # number of variable to store at each time step # Matrix declaration A = zeros((ndof, ndof)) x0 = [Xinit, -Xinit] Brel = np.array([[0], [1]]) sensorC = eye(ndof) sensorD = zeros((ndof, ndof)) Csurface = [[0, 1.0]] # Simple check if h > hControl: print("hControl must be bigger than h") exit(1) # Declaration of the Dynamical System processDS = MyFOLDS(x0, A) # XXX b is not automatically created ... # processDS.setb([0, 0]) # Model process = Model(t0, T) process.nonSmoothDynamicalSystem().insertDynamicalSystem(processDS) # time discretization processTD = TimeDiscretisation(t0, h) tSensor = TimeDiscretisation(t0, hControl) tActuator = TimeDiscretisation(t0, hControl) # Creation of the Simulation processSimulation = TimeStepping(processTD, 0) processSimulation.setName("plant simulation") processSimulation.setNonSmoothDynamicalSystemPtr( process.nonSmoothDynamicalSystem()) # Declaration of the integrator processIntegrator = ZeroOrderHoldOSI() processSimulation.prepareIntegratorForDS(processIntegrator, processDS, process, t0) # Actuator, Sensor & ControlManager control = ControlManager(processSimulation) sens = LinearSensor(processDS, sensorC, sensorD) control.addSensorPtr(sens, tSensor) act = LinearSMCOT2(sens) act.setCsurface(Csurface) act.setB(Brel) control.addActuatorPtr(act, tActuator) # Initialization. process.setSimulation(processSimulation) process.initialize() control.initialize(process) # This is not working right now # eventsManager = s.eventsManager() # Matrix for data storage dataPlot = empty((3 * (N + 1), outputSize)) dataPlot[0, 0] = t0 dataPlot[0, 1] = processDS.x()[0] dataPlot[0, 2] = processDS.x()[1] dataPlot[0, 3] = act.u()[0] # Main loop k = 1 while processSimulation.hasNextEvent(): if processSimulation.eventsManager().nextEvent().getType() == TD_EVENT: processSimulation.computeOneStep() dataPlot[k, 0] = processSimulation.nextTime() dataPlot[k, 1] = processDS.x()[0] dataPlot[k, 2] = processDS.x()[1] dataPlot[k, 3] = act.u()[0] k += 1 processSimulation.nextStep() # print processSimulation.nextTime() # Resize matrix dataPlot.resize(k, outputSize)
aTiDisc = TimeDiscretisation(t0, h_step) # (3) Non smooth problem aRelay = Relay() # (4) Simulation setup with (1) (2) (3) aTS = TimeStepping(aTiDisc, aOSI, aRelay) # end of model definition # # computation # # simulation initialization RelayOscillator.setSimulation(aTS) RelayOscillator.initialize() k = 0 h = aTS.timeStep() print("Timestep : ", h) # Number of time steps N = (int)((T - t0) / h) print("Number of steps : ", N) # Get the values to be plotted # ->saved in a matrix dataPlot from numpy import empty dataPlot = empty([N + 1, 8])
broadphase.collisionConfiguration().setConvexConvexMultipointIterations() broadphase.collisionConfiguration().setPlaneConvexMultipointIterations() # The ground is a static object # we give it a group contactor id : 0 broadphase.addStaticObject(ground, 0) # (6) Simulation setup with (1) (2) (3) (4) (5) simulation = BulletTimeStepping(timedisc) #simulation.setNewtonOptions(1) simulation.insertIntegrator(osi) simulation.insertNonSmoothProblem(osnspb) # simulation initialization bouncingBox.setSimulation(simulation) bouncingBox.initialize() # Get the values to be plotted # ->saved in a matrix dataPlot N = (T - t0) / h dataPlot = zeros((N+1, 4)) # # numpy pointers on dense Siconos vectors # q = body.q() v = body.velocity() #
# The ground is a static object # we give it a group contactor id : 0 scs = SiconosContactorSet() scs.append(SiconosContactor(ground)) broadphase.insertStaticContactorSet(scs, groundOffset) # (6) Simulation setup with (1) (2) (3) (4) (5) simulation = TimeStepping(timedisc) simulation.insertInteractionManager(broadphase) simulation.insertIntegrator(osi) simulation.insertNonSmoothProblem(osnspb) # simulation initialization bouncingBox.setSimulation(simulation) bouncingBox.initialize() # Get the values to be plotted # ->saved in a matrix dataPlot N = int((T - t0) / h) dataPlot = zeros((N + 1, 4)) # # numpy pointers on dense Siconos vectors # q = body.q() v = body.velocity() #
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 DiodeBridgeCapFilter.setSimulation(aTS) DiodeBridgeCapFilter.initialize() k = 0 h = aTS.timeStep() print("Timestep : ", h) # Number of time steps N = int((T - t0) / h) print("Number of steps : ", N) # Get the values to be plotted # ->saved in a matrix dataPlot from numpy import zeros dataPlot = zeros([N - 1, 10])
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)
# (3) one step non smooth problem osnspb = LCP() # (4) Simulation setup with (1) (2) (3) s = TimeStepping(t, OSI, osnspb) # end of model definition # # computation # # simulation initialization bouncingBall.setSimulation(s) bouncingBall.initialize() # the number of time steps N = int((T - t0) / h) # Get the values to be plotted # ->saved in a matrix dataPlot dataPlot = zeros((N+1, 5)) # # numpy pointers on dense Siconos vectors # q = ball.q()