def test_vanderpol(b=0.5, solver='RungeKutta4'):
vdp = VanderPolOscillator(b=b)
timestep = 1.0
sim = Simulator(vdp, timestep)
dur = 1000000.0
nsteps = int(dur / timestep)
state = list()
state.append(vdp.initialState)
for t in range(nsteps):
x = sim.next(solverName=solver)
state.append(x)
state = np.array(state)
print 'state.shape=',state.shape
plt.figure()
plt.plot(state[:, 0], 'k-')
return state[:, 0]
def testHHNeuronSimulator(step_size=1e-6, sim_duration=0.030):
tstep = step_size
tsim = sim_duration
nsteps = int(round(tsim / tstep))
print 'nsteps={0}'.format(nsteps)
hh = HHNeuron()
hh.setCurrentWaveform(GenerateStepCurrent(0.050, tsim, 0e-9))
#solvers = ['ForwardEuler', 'BackwardEuler', 'RungeKutta4']
solvers = ['RungeKutta4']
#solvers = ['ForwardEuler']
#print 'hh.initialState={0}'.format(repr(hh.initialState))
plt.figure()
plt.hold(True)
for s in solvers:
sim = Simulator(hh, tstep)
#print 'sim.currentValue={0}'.format(repr(sim.currentValue))
vals = list()
for n in range(nsteps):
#sim.next()
sim.next(s)
#print 'n={0}, value={1}'.format(n, repr(sim.currentValue))
vals.append(sim.currentValue[0])
t = np.arange(0.0, tsim, tstep)
vals = np.array(vals)
print 't.shape=',t.shape
print 'vals.shape=',vals.shape
plt.plot(t, vals)
plt.axis([0, tsim, -0.080, 0.040])
plt.legend(solvers, loc=2)
plt.show()
def test_fitzhugh_nagumo(spacing=0.05, bounds=None, v0=0.0, w0=0.0, dc_current=0.0, solver='RungeKutta4'):
fn = FitzHughNagumo(np.array([v0, w0]), dc_current)
if bounds is None:
bnds = Bounds()
bnds.xmax = 1.0
bnds.xmin = -1.0
bnds.ymax = 1.0
bnds.ymin = -0.5
else:
bnds = Bounds()
bnds.xmin = bounds[0]
bnds.xmax = bounds[1]
bnds.ymin = bounds[2]
bnds.ymax = bounds[3]
pp = PhasePlot(fn, bnds, spacing)
pp.renderPlot()
timestep = 0.01
sim = Simulator(fn, timestep)
dur = 2000.00
nsteps = int(dur / timestep)
state = list()
state.append(fn.initialState)
for t in range(nsteps):
x = sim.next(solverName=solver)
state.append(x)
state = np.array(state)
print 'state.shape=',state.shape
plt.figure()
plt.plot(state[:, 0], 'k-')
return state[:, 0]
def testIZNeuronSimulator():
iz = IZNeuron()
iz.setCurrentWaveform(GenerateStepCurrent(100, 1000, 70))
solvers = ['ForwardEuler', 'BackwardEuler', 'RungeKutta4']
tstep = 1
tsim = 250
nsteps = int(round(tsim / tstep))
print 'nsteps={0}'.format(nsteps)
#print 'iz.initialState={0}'.format(repr(iz.initialState))
#print 'sim.currentValue={0}'.format(repr(sim.currentValue))
plt.figure()
plt.hold(True)
for s in solvers:
sim = Simulator(iz, tstep)
vals = np.zeros( (nsteps, 1) )
vals[0] = sim.currentValue[0]
for n in range(nsteps):
#sim.next()
sim.next(s)
#print 'n={0}, value={1}'.format(n, repr(sim.currentValue))
vals[n] = sim.currentValue[0]
t = np.arange(0, tsim, tstep)
plt.plot(t, vals)
plt.legend(solvers, loc=2)
plt.show()
