def doublependulummodifiedTS_withnoise(finaltime=600.0,dt=0.025):
from DoublePendulumModified import solvePendulum
timeseries = solvePendulum([1.0,2.0,3.0,2.0],finaltime,dt)
for j in range(timeseries.shape[1]):
s = np.std(timeseries[:,j])
timeseries[:,j] += -0.01*s + 0.02*s*np.random.random(timeseries[:,j].shape)
eqns = 'Double pendulum with noise'
names = ['x','y','z','w']
return eqns,names,timeseries
def doublependulumTS(finaltime=600.0,dt=0.025):
from DoublePendulum import solvePendulum
timeseries = solvePendulum([1.0,2.0,3.0,2.0],finaltime,dt)
eqns = 'Double pendulum'
names = ['x','y','z','w']
return eqns,names,timeseries
def doublependulummodifiedTS_changedbeta(finaltime=600.0,dt=0.025):
from DoublePendulumModified import solvePendulum
timeseries = solvePendulum([1.0,2.0,3.0,2.0],finaltime,dt,beta=1.2)
eqns = 'Double pendulum modified'
names = ['x','y','z','w']
return eqns,names,timeseries
import StateSpaceReconstructionPlots as SSRPlots
# from LorenzEqns import solveLorenz
# timeseries = solveLorenz([1.0,0.5,0.5],80.0)
# l,avg1,avg2,std1,std2 = causalityWrapper(timeseries[:4001,0],timeseries[:4001,1],2,8,range(20,2000,200),25,causalitytester=testCausality)
# from differenceEqns import solve2Species
# timeseries = solve2Species([0.4,0.2],8.0)
# l,avg1,avg2,std1,std2 = causalityWrapper(timeseries[:,0],timeseries[:,1],2,8,range(20,320,40),25,causalitytester=testCausality)
# print(np.array(l))
# print(np.array([avg1,avg2]))
# avgarr = np.zeros((len(avg1),2))
# avgarr[:,0] = avg1
# avgarr[:,1] = avg2
# SSRPlots.plots(np.array(l),avgarr,hold=0,show=1,stylestr=['b-','r-'],leglabels=['x from My','y from Mx'], legloc=0,xstr='length of time interval',ystr='mean corr coeff')
from DoublePendulum import solvePendulum
timeseries = solvePendulum([1.0, 2.0, 3.0, 2.0], 300.0)
names = ['x', 'y', 'z']
styles = ['b-', 'r-', 'g-', 'k-']
hold = 0
show = 0
for k in range(3):
l, avg1, avg2, std1, std2 = causalityWrapper(
timeseries[200:, k],
timeseries[200:, -1],
4,
8,
range(500, 3000, 500),
25,
causalitytester=testCausality)
print(np.array(l))
print(np.array([avg1, avg2]))