#!/usr/bin/env python
import cPickle
import numpy as np
import matplotlib.pyplot as plt
import canonical_system_id as csi
from dtk import bicycle, control
allRiders = ['Charlie', 'Jason', 'Luke']
# create the comparison models
canon = csi.load_benchmark_canon(allRiders)
H = csi.lateral_force_contribution(allRiders)
with open('idMatrices.p') as f:
idMatrices = cPickle.load(f)
def plot(canon, H, riders, environments, idMats):
filename = ''
for rider in riders:
filename += '-' + rider
for env in environments:
filename += '-' + env.replace(' ', '')
filename = 'canonical-id-plots/' + filename[1:]
print filename
v0 = 0.
vf = 10.
num = 100
mM, mC1, mK0, mK2, mH = csi.mean_canon(riders, canon, H)
#!/usr/bin/env python
import cPickle
import canonical_system_id as csi
riders = ['Charlie', 'Jason', 'Luke']
environments = ['Horse Treadmill', 'Pavillion Floor']
maneuvers = ['Balance',
'Track Straight Line',
'Balance With Disturbance',
'Track Straight Line With Disturbance']
runs = csi.select_runs(riders, maneuvers, environments)
# This gives the proportion of the lateral force which should be added to the
# steer torque and roll torque equations in the canonical equations.
H = csi.lateral_force_contribution(riders)
# try to load in all of the runs for the given run numbers.
trials, errors = csi.load_trials(runs, H)
rollParams = ['Mpd', 'C1pd', 'K0pd']
steerParams = ['Mdd', 'C1dp', 'C1dd',
'K0dd', 'K2dd', 'HdF']
canon = csi.load_benchmark_canon(riders)
idMatrices = {}
covarMatrices = {}
print('Computing the estimate for all runs.')
runs = list(set(runs).difference(errors))
means = csi.mean_canon(riders, canon, H)
