Python LinearWhipple Examples

Example #1

from dtk import bicycle

# local dependencies
try:
    f = open('Whipple.py', 'r')
except IOError:
    from altk import alparse
    alparse.alparse('Whipple', 'Whipple', code='Python')
else:
    f.close()
    del f

from Whipple import LinearWhipple

# create the Whipple model (with my parameters)
whip = LinearWhipple()

# load the benchmark parameters
pathToData = '/media/Data/Documents/School/UC Davis/Bicycle Mechanics/BicycleParameters/data/'
benchmark = bp.Bicycle('Benchmark', pathToData)
benchmarkPar = bp.io.remove_uncertainties(benchmark.parameters['Benchmark'])
# convert to my parameter set
moorePar = bicycle.benchmark_to_moore(benchmarkPar, oldMassCenter=False)
whip.set_parameters(moorePar)

# set the initial conditions to match Meijaard2007
speedNaught = 4.6
u6Naught = -speedNaught / moorePar['rr']
rollRateNaught = 0.5
pitchAngle = bicycle.pitch_from_roll_and_steer(0., 0., moorePar['rf'],
                                               moorePar['rr'], moorePar['d1'],

Example #2

File: crescendo_eigenvectors.py Project: StefenYin/dissertation

from dtk import bicycle

# create the Whipple model (with my parameters)
try:
    f = open('Whipple.py', 'r')
except IOError:
    from altk import alparse
    alparse.alparse('Whipple', 'Whipple', code='Python')
else:
    f.close()
    del f

# local dependencies
from Whipple import LinearWhipple

whip = LinearWhipple()

# load the benchmark parameters
pathToData='/media/Data/Documents/School/UC Davis/Bicycle Mechanics/BicycleParameters/data/'
crescendo = bp.Bicycle('Crescendo', pathToData=pathToData, forceRawCalc=True)
benchmarkPar = bp.io.remove_uncertainties(crescendo.parameters['Benchmark'])
# convert to my parameter set
moorePar = bicycle.benchmark_to_moore(benchmarkPar, oldMassCenter=False)
whip.set_parameters(moorePar)

# linearize about the nominal configuration
equilibrium = np.zeros(len(whip.stateNames))
pitchAngle = bicycle.pitch_from_roll_and_steer(0., 0., moorePar['rf'], moorePar['rr'],
        moorePar['d1'], moorePar['d2'], moorePar['d3'])
equilibrium[whip.stateNames.index('q5')] = pitchAngle
speedNaught = 1.5

Example #3

File: plot_eigenvectors.py Project: goatchurchprime/dissertation

    'xtick.labelsize': 8,
    'ytick.labelsize': 8,
    'text.usetex': True,
    'figure.figsize': fig_size,
    'figure.dpi': 300
}
plt.rcParams.update(params)

# load the benchmark parameters
pathToData = '/media/Data/Documents/School/UC Davis/Bicycle Mechanics/BicycleParameters/data/'
benchmark = bp.Bicycle('Benchmark', pathToData)
benchmarkPar = bp.io.remove_uncertainties(benchmark.parameters['Benchmark'])
# convert to my parameter set
moorePar = bicycle.benchmark_to_moore(benchmarkPar, oldMassCenter=False)

whip = LinearWhipple()
whip.set_parameters(moorePar)

# linearize about the nominal configuration
equilibrium = np.zeros(len(whip.stateNames))
pitchAngle = bicycle.pitch_from_roll_and_steer(0., 0., moorePar['rf'],
                                               moorePar['rr'], moorePar['d1'],
                                               moorePar['d2'], moorePar['d3'])
equilibrium[whip.stateNames.index('q5')] = pitchAngle

# below the weave bifurcation
speedNaught = 0.5
u6Naught = -speedNaught / moorePar['rr']
equilibrium[whip.stateNames.index('u6')] = u6Naught
whip.linear(equilibrium)

Example #4

File: plot_eigenvectors.py Project: StefenYin/dissertation

          'legend.fontsize': 8,
          'xtick.labelsize': 8,
          'ytick.labelsize': 8,
          'text.usetex': True,
          'figure.figsize': fig_size,
          'figure.dpi': 300}
plt.rcParams.update(params)

# load the benchmark parameters
pathToData='/media/Data/Documents/School/UC Davis/Bicycle Mechanics/BicycleParameters/data/'
benchmark = bp.Bicycle('Benchmark', pathToData)
benchmarkPar = bp.io.remove_uncertainties(benchmark.parameters['Benchmark'])
# convert to my parameter set
moorePar = bicycle.benchmark_to_moore(benchmarkPar, oldMassCenter=False)

whip = LinearWhipple()
whip.set_parameters(moorePar)

# linearize about the nominal configuration
equilibrium = np.zeros(len(whip.stateNames))
pitchAngle = bicycle.pitch_from_roll_and_steer(0., 0., moorePar['rf'], moorePar['rr'],
        moorePar['d1'], moorePar['d2'], moorePar['d3'])
equilibrium[whip.stateNames.index('q5')] = pitchAngle

# below the weave bifurcation
speedNaught = 0.5
u6Naught = -speedNaught / moorePar['rr']
equilibrium[whip.stateNames.index('u6')] = u6Naught
whip.linear(equilibrium)

figs = whip.plot_eigenvectors(states=('q4', 'q7'))

Example #5

File: linear_comparison.py Project: StefenYin/dissertation

from dtk import bicycle

# local dependencies
try:
    f = open('Whipple.py', 'r')
except IOError:
    from altk import alparse
    alparse.alparse('Whipple', 'Whipple', code='Python')
else:
    f.close()
    del f

from Whipple import LinearWhipple

# create the Whipple model (with my parameters)
whip = LinearWhipple()

# load the benchmark parameters
pathToData='/media/Data/Documents/School/UC Davis/Bicycle Mechanics/BicycleParameters/data/'
benchmark = bp.Bicycle('Benchmark', pathToData)
benchmarkPar = bp.io.remove_uncertainties(benchmark.parameters['Benchmark'])
# convert to my parameter set
moorePar = bicycle.benchmark_to_moore(benchmarkPar, oldMassCenter=False)
whip.set_parameters(moorePar)

# set the initial conditions to match Meijaard2007
speedNaught = 4.6
u6Naught = -speedNaught / moorePar['rr']
rollRateNaught = 0.5
pitchAngle = bicycle.pitch_from_roll_and_steer(0., 0., moorePar['rf'], moorePar['rr'],
        moorePar['d1'], moorePar['d2'], moorePar['d3'])