def test_basu_to_moore_input():
basu = bicycle.basu_table_one_input()
lam = pi / 10.
rr = 0.3
mooreInput = bicycle.basu_to_moore_input(basu, rr, lam)
for k, v in mooreInput.items():
print k, ':', v
# reminder: u1--yaw rate, u2--roll rate, u3--pitch rate, u4--steer rate, u5--rear wheel ang. vel., u6--front wheel ang. vel.
# kane.kindiffeq(kinematical)
(fr, frstar) = kane.kanes_equations(forceList, bodyList)
kdd = kane.kindiffdict()
bp = bi.benchmark_parameters()
mp = bi.benchmark_to_moore(bp)
rr = bp["rR"]
lam = bp["lam"]
basu_input = bi.basu_table_one_input()
mo_in = bi.basu_to_moore_input(basu_input, rr, lam)
# not include the l1, l2, mc and ic because of the rider
# which will be added into instrumented bicycle later.
para_dict = {
l1: mp["l1"],
l2: mp["l2"],
l3: mp["l3"],
l4: mp["l4"],
mc: mp["mc"],
md: mp["md"],
me: mp["me"],
mf: mp["mf"],
rR: mp["rr"],
rF: mp["rf"],
g: mp["g"],
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)
# set the parameters
whip.parameters = moorePar
whip.constants() # make sure the constants are recalculated with the new parameters
# load the input values specified in table one of Basu-Mandal2007
basuInput = bicycle.basu_table_one_input()
# convert the values to my coordinates and speeds
mooreInput = bicycle.basu_to_moore_input(basuInput, benchmarkPar['rR'],
benchmarkPar['lam'])
# store them in a state array
x = np.array([mooreInput[x] for x in whip.stateNames])
# calculate the derivatives of the state using my model and compare it to
# BasuMandal2007
xd = whip.f(x, 0.)
y = whip.outputs(x)
# convert the outputs from my model to the Basu-Mandal coordinates
mooreOutput = {k : v for k, v in zip(whip.outputNames, y)}
mooreOutputBasu = bicycle.moore_to_basu(mooreOutput, benchmarkPar['rR'], benchmarkPar['lam'])
basuOutput = bicycle.basu_table_one_output()
# make an rst list table
fr, frstar = kane.kanes_equations(forces, bodies)
# Validation of non-linear equations
print('Loading numerical input parameters.')
from dtk import bicycle
bp = bicycle.benchmark_parameters()
mp = bicycle.benchmark_to_moore(bp)
# load the input values specified in table one of Basu-Mandal2007
basu_input = bicycle.basu_table_one_input()
# convert the values to my coordinates and speeds
moore_input = bicycle.basu_to_moore_input(basu_input, bp['rR'], bp['lam'])
constant_substitutions = {}
for k, v in mp.items():
try:
exec('constant_substitutions[{}] = v'.format(k))
except NameError:
pass
dynamic_substitutions = {}
for k, v in moore_input.items():
try:
exec('dynamic_substitutions[{}] = v'.format(k))
except NameError:
pass
substitutions = {T4: 0.0, T6: 0.0, T7: 0.0}
fr, frstar = kane.kanes_equations(forces, bodies)
# Validation of non-linear equations
print('Loading numerical input parameters.')
from dtk import bicycle
bp = bicycle.benchmark_parameters()
mp = bicycle.benchmark_to_moore(bp)
# load the input values specified in table one of Basu-Mandal2007
basu_input = bicycle.basu_table_one_input()
# convert the values to my coordinates and speeds
moore_input = bicycle.basu_to_moore_input(basu_input, bp['rR'],
bp['lam'])
constant_substitutions = {}
for k, v in mp.items():
try:
exec('constant_substitutions[{}] = v'.format(k))
except NameError:
pass
dynamic_substitutions = {}
for k, v in moore_input.items():
try:
exec('dynamic_substitutions[{}] = v'.format(k))
except NameError:
pass
substitutions = {T4: 0.0, T6: 0.0, T7: 0.0}
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)
# set the parameters
whip.parameters = moorePar
whip.constants(
) # make sure the constants are recalculated with the new parameters
# load the input values specified in table one of Basu-Mandal2007
basuInput = bicycle.basu_table_one_input()
# convert the values to my coordinates and speeds
mooreInput = bicycle.basu_to_moore_input(basuInput, benchmarkPar['rR'],
benchmarkPar['lam'])
# store them in a state array
x = np.array([mooreInput[x] for x in whip.stateNames])
# calculate the derivatives of the state using my model and compare it to
# BasuMandal2007
xd = whip.f(x, 0.)
y = whip.outputs(x)
# convert the outputs from my model to the Basu-Mandal coordinates
mooreOutput = {k: v for k, v in zip(whip.outputNames, y)}
mooreOutputBasu = bicycle.moore_to_basu(mooreOutput, benchmarkPar['rR'],
benchmarkPar['lam'])
basuOutput = bicycle.basu_table_one_output()