def test_pca_lin_Phos():
NUM_STEPS = 30
PHOS_LIN_ITER_STEPS = 1 #Number of steps between each recomputation of LinApp Templates.
PHOS_PCA_ITER_STEPS = 1 #Number of steps between each recomputation of PCA Templates.
'PCA Strategy Parameters'
PHOS_PCA_TRAJ_STEPS = 5 #Number of steps our sample trajectories should run.
PHOS_PCA_NUM_TRAJ = 200 #Number of sample trajectories we should use for the PCA routine.
PHOS_LIFE_SPAN = 3
unit_model = Phosphorelay_UnitBox()
unit_mod_reach = ReachSet(unit_model)
#points = [[1,1,1], [1.005, 1,1], [1.01,1.01,1.01], [1.005,1.01,1.01], [1,1.005,1], [1.01,1,1.05]]
#trajs = [Traj(unit_model , point, NUM_STEPS) for point in points]
multi_strat = MultiStrategy(LinStrat(unit_model, iter_steps=PHOS_LIN_ITER_STEPS), \
DelayedPCAStrat(unit_model, traj_steps=PHOS_PCA_TRAJ_STEPS, num_trajs=PHOS_PCA_NUM_TRAJ, life_span=PHOS_LIFE_SPAN))
#PCAStrat(unit_model, traj_steps=PHOS_PCA_TRAJ_STEPS, num_trajs=PHOS_PCA_NUM_TRAJ, iter_steps=PHOS_PCA_ITER_STEPS+PHOS_PCA_DELAY))
#PCAStrat(unit_model, traj_steps=PHOS_PCA_TRAJ_STEPS, num_trajs=PHOS_PCA_NUM_TRAJ, iter_steps=PHOS_PCA_ITER_STEPS+2*PHOS_PCA_DELAY))
mod_lin_flow = unit_mod_reach.computeReachSet(NUM_STEPS,
tempstrat=multi_strat)
# points = [[0,1.97], [0.01, 1.97], [0.01,2], [0,2], [0.005,1.97], [0.005,2], [0,1.97], [0,1.985], [0.01,1.985]]
#trajs = [Traj(unit_model, point, NUM_STEPS) for point in points]
phos_plot = Plot()
phos_plot.add(mod_lin_flow)
'Add trajectories'
for traj in trajs:
phos_plot.add(traj)
phos_plot.plot2DPhase(0, 1, separate=False, plotvertices=True)
def test_pca_VDP():
NUM_STEPS = 3
model = VanDerPol(delta=0.08)
unit_model = VanDerPol_UnitBox(delta=0.08)
VDP_PCA_ITER_STEPS = 1 #Number of steps between each recomputation of PCA Templates.
'PCA Strategy Parameters'
VDP_PCA_TRAJ_STEPS = 5 #Number of steps our sample trajectories should run.
VDP_PCA_NUM_TRAJ = 50 #Number of sample trajectories we should use for the PCA routine.
VDP_PCA_DELAY = 5
pca_dirs = GeneratedPCADirs(model, VDP_PCA_NUM_TRAJ, NUM_STEPS)
pca_strat = MultiStrategy(PCAStrat(unit_model, traj_steps=VDP_PCA_TRAJ_STEPS, num_trajs=VDP_PCA_NUM_TRAJ, iter_steps=VDP_PCA_ITER_STEPS, pca_dirs=pca_dirs), \
PCAStrat(unit_model, traj_steps=VDP_PCA_TRAJ_STEPS, num_trajs=VDP_PCA_NUM_TRAJ, iter_steps=VDP_PCA_ITER_STEPS+VDP_PCA_DELAY, pca_dirs=pca_dirs), \
PCAStrat(unit_model, traj_steps=VDP_PCA_TRAJ_STEPS, num_trajs=VDP_PCA_NUM_TRAJ, iter_steps=VDP_PCA_ITER_STEPS+2*VDP_PCA_DELAY, pca_dirs=pca_dirs))
inputs = [
ExperimentInput(model, label="VDP Sapo"),
ExperimentInput(unit_model, strat=pca_strat, label="VDP Kaa PCA")
]
vdp_pca = PhasePlotExperiment(inputs)
vdp_pca.execute(NUM_STEPS)
vdp_pca.plot_results(0, 1)
Timer.generate_stats()
def test_pca_lin_VDP():
NUM_STEPS = 70
VDP_LIN_ITER_STEPS = 1 #Number of steps between each recomputation of LinApp Templates.
VDP_PCA_ITER_STEPS = 1 #Number of steps between each recomputation of PCA Templates.
'PCA Strategy Parameters'
VDP_PCA_TRAJ_STEPS = 2 #Number of steps our sample trajectories should run.
VDP_PCA_NUM_TRAJ = 200 #Number of sample trajectories we should use for the PCA routine.
VDP_LIN_DELAY = 2
VDP_PCA_DELAY = 5
model = VanDerPol(delta=0.08)
unit_model = VanDerPol_UnitBox(delta=0.08)
lin_strat = MultiStrategy(LinStrat(unit_model, iter_steps=VDP_LIN_ITER_STEPS), \
LinStrat(unit_model, iter_steps=VDP_LIN_ITER_STEPS+VDP_LIN_DELAY), \
PCAStrat(unit_model, traj_steps=VDP_PCA_TRAJ_STEPS, num_trajs=VDP_PCA_NUM_TRAJ, iter_steps=VDP_PCA_ITER_STEPS), \
PCAStrat(unit_model, traj_steps=VDP_PCA_TRAJ_STEPS, num_trajs=VDP_PCA_NUM_TRAJ, iter_steps=VDP_PCA_ITER_STEPS+VDP_PCA_DELAY))
inputs = [
ExperimentInput(model, label="VDP Sapo"),
ExperimentInput(unit_model, strat=lin_strat, label="VDP Kaa")
]
vdp_pca = PhasePlotExperiment(inputs)
vdp_pca.execute(NUM_STEPS)
vdp_pca.plot_results(0, 1)
Timer.generate_stats()
def test_ani_pca_lin_VDP():
NUM_STEPS = 70
VDP_LIN_ITER_STEPS = 1 #Number of steps between each recomputation of LinApp Templates.
VDP_PCA_ITER_STEPS = 1 #Number of steps between each recomputation of PCA Templates.
'PCA Strategy Parameters'
VDP_PCA_TRAJ_STEPS = 2 #Number of steps our sample trajectories should run.
VDP_PCA_NUM_TRAJ = 200 #Number of sample trajectories we should use for the PCA routine.
VDP_LIN_DELAY = 2
VDP_PCA_DELAY = 5
model = VanDerPol(delta=0.08)
unit_model = VanDerPol_UnitBox(delta=0.08)
lin_1 = LinStrat(unit_model, iter_steps=VDP_LIN_ITER_STEPS)
lin_2 = LinStrat(unit_model, iter_steps=VDP_LIN_ITER_STEPS + VDP_LIN_DELAY)
pca_1 = PCAStrat(unit_model,
traj_steps=VDP_PCA_TRAJ_STEPS,
num_trajs=VDP_PCA_NUM_TRAJ,
iter_steps=VDP_PCA_ITER_STEPS)
pca_2 = PCAStrat(unit_model,
traj_steps=VDP_PCA_TRAJ_STEPS,
num_trajs=VDP_PCA_NUM_TRAJ,
iter_steps=VDP_PCA_ITER_STEPS + VDP_PCA_DELAY)
lin_strat = MultiStrategy(lin_1, lin_2, pca_1, pca_2)
inputs = ExperimentInput(unit_model, strat=lin_strat, label="VDP Kaa")
vdp_pca = Animation(inputs)
vdp_pca.execute(NUM_STEPS)
vdp_pca.animate(0, 1, lin_1, lin_2)
#vdp_pca.animate(0,1, lin_2)
#vdp_pca.animate(0,1, pca_2)
Timer.generate_stats()
def test_sir_lin_pca_strat():
NUM_STEPS = 70
SIR_PCA_ITER_STEPS = 1 #Number of steps between each recomputation of PCA Templates.
'PCA Strategy Parameters'
SIR_PCA_TRAJ_STEPS = 1 #Number of steps our sample trajectories should run.
SIR_PCA_NUM_TRAJ = 100 #Number of sample trajectories we should use for the PCA routine.
SIR_LIN_ITER_STEPS = 1
#
SIR_PCA_LIFE_SPAN = 3
sir_pca = SIR_UnitBox(delta=0.5)
sir_plot = Plot()
points = [[0.79,0.19,0], [0.79, 0.2,0], [0.8,0.19,0], [0.8,0.2,0], [0.79,0.195,0], [0.8,0.195,0], [0.795,0.19,0], [0.795,0.2,0]]
trajs = [Traj(sir_pca, point, NUM_STEPS) for point in points]
pca_strat = MultiStrategy(LinStrat(sir_pca, iter_steps=SIR_LIN_ITER_STEPS), \
DelayedPCAStrat(sir_pca, traj_steps=SIR_PCA_TRAJ_STEPS, num_trajs=SIR_PCA_NUM_TRAJ, life_span=SIR_PCA_LIFE_SPAN))
sir_pca_reach = ReachSet(sir_pca)
sir_flow_pca = sir_pca_reach.computeReachSet(NUM_STEPS, tempstrat=pca_strat)
sir_plot.add(sir_flow_pca, "SIR_LinApp&PCA")
'Add trajectories'
for traj in trajs:
sir_plot.add(traj)
# sir_plot.plot2DPhase(0,1,separate=False, plotvertices=True)
sir_plot.plot2DPhase(1,2,separate=False, plotvertices=True)
sir_plot.plot2DPhase(0,2,separate=False, plotvertices=True)
Timer.generate_stats()
def test_ani_pca_VDP():
NUM_STEPS = 70
#model = VanDerPol(delta=0.08)
unit_model = VanDerPol_UnitBox(delta=0.08)
VDP_PCA_ITER_STEPS = 1 #Number of steps between each recomputation of PCA Templates.
'PCA Strategy Parameters'
VDP_PCA_TRAJ_STEPS = 5 #Number of steps our sample trajectories should run.
VDP_PCA_NUM_TRAJ = 100 #Number of sample trajectories we should use for the PCA routine.
VDP_PCA_DELAY = 5
pca_1 = PCAStrat(unit_model,
traj_steps=VDP_PCA_TRAJ_STEPS,
num_trajs=VDP_PCA_NUM_TRAJ,
iter_steps=VDP_PCA_ITER_STEPS)
pca_2 = PCAStrat(unit_model,
traj_steps=VDP_PCA_TRAJ_STEPS,
num_trajs=VDP_PCA_NUM_TRAJ,
iter_steps=VDP_PCA_ITER_STEPS + VDP_PCA_DELAY)
pca_3 = PCAStrat(unit_model,
traj_steps=VDP_PCA_TRAJ_STEPS,
num_trajs=VDP_PCA_NUM_TRAJ,
iter_steps=VDP_PCA_ITER_STEPS + 2 * VDP_PCA_DELAY)
pca_strat = MultiStrategy(pca_1, pca_2, pca_3)
experi_input = ExperimentInput(unit_model,
strat=pca_strat,
label="VDP Kaa PCA")
vdp_pca = Animation(experi_input)
vdp_pca.execute(NUM_STEPS)
vdp_pca.animate(0, 1, pca_1)
vdp_pca.animate(0, 1, pca_2)
vdp_pca.animate(0, 1, pca_3)
Timer.generate_stats()
def test_lin_VDP():
NUM_STEPS = 70
VDP_LIN_ITER_STEPS = 1 #Number of steps between each recomputation of LinApp Templates.
VDP_LIN_DELAY = 1
model = VanDerPol(delta=0.08)
unit_model = VanDerPol_UnitBox(delta=0.08)
lin_strat = MultiStrategy(LinStrat(unit_model, iter_steps=VDP_LIN_ITER_STEPS), \
LinStrat(unit_model, iter_steps=VDP_LIN_ITER_STEPS+VDP_LIN_DELAY), \
LinStrat(unit_model, iter_steps=VDP_LIN_ITER_STEPS+2*VDP_LIN_DELAY))
inputs = [
ExperimentInput(model, label="VDP Sapo"),
ExperimentInput(unit_model, strat=lin_strat, label="VDP Kaa Lin")
]
vdp_pca = PhasePlotExperiment(inputs)
vdp_pca.execute(NUM_STEPS)
vdp_pca.plot_results(0, 1)
Timer.generate_stats()
def test_pca_lin_HarOsc():
NUM_STEPS = 4
model = HarOsc()
#trajs = generate_traj(model, 10, 200)
mod_reach = ReachSet(model)
#mod_flow = mod_reach.computeReachSet()
sir_plot = Plot()dd
SIR_LIN_ITER_STEPS = 1 #Number of steps between each recomputation of PCA Templates.
SIR_PCA_ITER_STEPS = 1 #Number of steps between each recomputation of PCA Templates.
'PCA Strategy Parameters'
SIR_PCA_TRAJ_STEPS = 2 #Number of steps our sample trajectories should run.
SIR_PCA_NUM_TRAJ = 100 #Number of sample trajectories we should use for the PCA routine.
tandem_strat = MultiStrategy(LinStrat(model, iter_steps=SIR_LIN_ITER_STEPS), PCAStrat(model, traj_steps=SIR_PCA_TRAJ_STEPS, num_trajs=SIR_PCA_NUM_TRAJ, iter_steps=SIR_PCA_ITER_STEPS))
mod_pca_flow = mod_reach.computeReachSet(NUM_STEPS, tempstrat=tandem_strat, transmode=BundleMode.AFO)
#trajs = generate_traj(model, 10, 200)
'Generaste the trajectories and add them to the plot.'
sir_plot.add(mod_pca_flow, "HarOsc PCA")
sir_plot.plot2DPhase(0,1, separate=True, plotvertices=True)dd