def testOrient3Model():
env = Environment()
calibrator = ScaleAndOffsetCalibrator(env, 1000, 1 / 100, 10)
for i in range(3):
imu = Orient3IMU()
cal = calibrator.calibrate(imu)
sim = Simulation(environment=env)
traj = RandomTrajectory()
imu.simulation = sim
imu.trajectory = traj
sim.time = imu.trajectory.startTime
BasicIMUBehaviour(imu, 1 / 256, calibration=cal, initialTime=sim.time)
sim.run(traj.endTime)
t = imu.accelerometer.calibratedMeasurements.timestamps
r = traj.rotation(t)
a = r.rotateFrame(
traj.acceleration(t) - env.gravitationalField(traj.position(t), t))
m = r.rotateFrame(env.magneticField(traj.position(t), t))
w = r.rotateFrame(traj.rotationalVelocity(t))
g = env.gravitationalField.nominalMagnitude
a_within_5g = abs(a) < 5 * g
for i in range(3):
yield assert_array_almost_equal, \
np.array([a[i ,a_within_5g[i]]]), \
np.array([imu.accelerometer.calibratedMeasurements(t)
[i, a_within_5g[i]]]), -2
yield assert_array_almost_equal, m, \
imu.magnetometer.calibratedMeasurements(t), 0
yield assert_array_almost_equal, w, \
imu.gyroscope.calibratedMeasurements(t), 0
def testOrient3Model():
env = Environment()
calibrator = ScaleAndOffsetCalibrator(env, 1000, 1/100, 10)
for i in range(3):
imu = Orient3IMU()
cal = calibrator.calibrate(imu)
sim = Simulation(environment=env)
traj = RandomTrajectory()
imu.simulation = sim
imu.trajectory = traj
sim.time = imu.trajectory.startTime
BasicIMUBehaviour(imu, 1/256, calibration=cal, initialTime=sim.time)
sim.run(traj.endTime)
t = imu.accelerometer.calibratedMeasurements.timestamps
r = traj.rotation(t)
a = r.rotateFrame(traj.acceleration(t) -
env.gravitationalField(traj.position(t), t))
m = r.rotateFrame(env.magneticField(traj.position(t), t))
w = r.rotateFrame(traj.rotationalVelocity(t))
g = env.gravitationalField.nominalMagnitude
a_within_5g = abs(a) < 5*g
for i in range(3):
yield assert_array_almost_equal, \
np.array([a[i ,a_within_5g[i]]]), \
np.array([imu.accelerometer.calibratedMeasurements(t)
[i, a_within_5g[i]]]), -2
yield assert_array_almost_equal, m, \
imu.magnetometer.calibratedMeasurements(t), 0
yield assert_array_almost_equal, w, \
imu.gyroscope.calibratedMeasurements(t), 0
def testBERRadioEnvironment():
env = Environment(radioEnvironment=BERRadioEnvironment(1e-4, seed=0))
sim = Simulation(environment=env)
tx = TestPlatform(sim)
rx = TestPlatform(sim)
packet = TestPacket()
for _ in range(1000):
tx.sendPacket(packet)
assert len(tx.packetsReceived) == 0
assert 0 < len(rx.packetsReceived) < 1000
def __init__(self,
seed=None,
environment=None,
engine=SimPy.Simulation.Simulation):
"""
Initialise simulation.
@param seed: Seed value for L{np.random.RandomState}.
@param environment: L{Environment} to simulate in.
@param engine: L{SimPy.Simulation} subclass to drive simulation.
"""
self.environment = Environment(
) if environment is None else environment
self.engine = engine()
self.engine.initialize()
self.rng = np.random.RandomState(seed)
def testAgainstReality():
dir = path.dirname(__file__)
filebase = path.join(dir, "swing")
refbase = path.join(dir, "stand")
magbases = [path.join(dir, f) for f in ['magsweep1', 'magsweep2']]
maglookup = {'Upper Leg IMU': '66', 'Orient 8': '8', 'Orient 43': '43'}
magSamples = 2000
refTime = 1.0
posStdDev = 0.0005
rotStdDev = 0.004
ref3D = SplinedMarkerCapture(loadQualisysTSVFile(refbase + "_3D.tsv"),
positionStdDev=posStdDev)
ref6D = SplinedMarkerCapture(loadQualisysTSVFile(refbase + "_6D.tsv"),
rotationStdDev=rotStdDev)
capture3D = SplinedMarkerCapture(loadQualisysTSVFile(filebase + "_3D.tsv"),
positionStdDev=posStdDev)
captureSD = SensorDataCapture.load(filebase + ".sdc")
hip, thigh, knee, shin, ankle = \
['Hip', 'Thigh', 'Knee Hinge', 'Shin', 'Ankle']
jointNames = ['Upper Leg', 'Lower Leg', 'Foot']
jointAbbrevs = ['femur', 'tibia', 'foot']
orientIDs = ['66', '43', '8']
jointMarkerNames = [hip, knee, ankle]
refMarkerNames = [[thigh, knee], [shin, ankle], []]
imuMarkerNames = \
[[j + ' IMU - ' + str(i) for i in range(1,4)] for j in jointNames]
jointMarkerSets = lambda c: [
list(map(c.marker, jointMarkerNames)),
[list(map(c.marker, r)) for r in refMarkerNames],
[list(map(c.marker, i)) for i in imuMarkerNames]
]
imuMarkerSets = lambda c: [[
c.marker(i[0]) for i in imuMarkerNames
], [list(map(c.marker, i[1:])) for i in imuMarkerNames]]
jointRefTrajectories = [
MultiMarkerTrajectory(j, r + i, refTime=refTime)
for j, r, i in zip(*(jointMarkerSets(ref3D)))
]
jointTrajectories = [
MultiMarkerTrajectory(j, r + i, refVectors=m.refVectors) \
for j, r, i, m in \
zip(*(jointMarkerSets(capture3D) + [jointRefTrajectories]))]
imuRefTrajectories = [
MultiMarkerTrajectory(p, r, refTime=refTime)
for p, r in zip(*(imuMarkerSets(ref3D)))
]
imuVecTrajectories = [
MultiMarkerTrajectory(p, r, refVectors=m.refVectors)
for p, r, m in zip(*(imuMarkerSets(capture3D) + [imuRefTrajectories]))
]
imuRefMarkers = [ref6D.marker(j + ' IMU') for j in jointNames]
imuOffsets = [
i.position(refTime) - j.position(refTime)
for i, j in zip(imuRefTrajectories, jointRefTrajectories)
]
imuRotations = [
t.rotation(refTime).conjugate * m.rotation(refTime)
for t, m in zip(imuRefTrajectories, imuRefMarkers)
]
imuTrajectories = [
OffsetTrajectory(v, o, r)
for v, o, r in zip(imuVecTrajectories, imuOffsets, imuRotations)
]
imuData = [captureSD.device(i) for i in orientIDs]
joints = []
for i in range(len(jointNames)):
name = jointNames[i]
traj = jointTrajectories[i]
if i == 0:
model = SampledBodyModel(name)
model.positionKeyFrames = traj.posMarker.positionKeyFrames
joint = model
else:
parent = joints[-1]
refTraj = jointRefTrajectories[i]
parentRefTraj = jointRefTrajectories[i - 1]
pos = refTraj.position(refTime)
parentPos = parentRefTraj.position(refTime)
joint = SampledJoint(joints[-1], name, offset=(pos - parentPos))
joint.rotationKeyFrames = traj.rotationKeyFrames
joints.append(joint)
model = SplinedBodyModel(model)
joints = model.joints
imuJointTrajectories = [
OffsetTrajectory(j, o, r)
for j, o, r in zip(joints, imuOffsets, imuRotations)
]
positionSets = []
valueSets = []
for magbase in magbases:
orient = SensorDataCapture.load(magbase + '.sdc')
optical = loadQualisysTSVFile(magbase + '_6D.tsv')
for marker in optical.markers:
device = orient.device(maglookup[marker.id])
magData = device.sensorData('magnetometer').values
positionSets.append(marker.positionKeyFrames.values)
valueSets.append(
marker.rotationKeyFrames.values.rotateVector(magData))
positions = np.hstack(positionSets)
values = np.hstack(valueSets)
valid = ~np.any(np.isnan(positions), axis=0) & ~np.any(np.isnan(values),
axis=0)
dev = values - np.median(values[:, valid], axis=1).reshape((3, 1))
step = np.shape(values[:, valid])[1] // magSamples
posSamples = positions[:, valid][:, ::step]
valSamples = values[:, valid][:, ::step]
environment = Environment()
environment.magneticField = \
NaturalNeighbourInterpolatedField(posSamples, valSamples)
sim = Simulation(environment=environment)
sim.time = model.startTime
distortIMUs = []
dt = 1 / capture3D.sampled.frameRate
for traj in imuJointTrajectories:
platform = IdealIMU(sim, traj)
distortIMUs.append(BasicIMUBehaviour(platform, dt))
sim.run(model.endTime)
for imu in range(3):
for sensorName in ['accelerometer', 'magnetometer', 'gyroscope']:
sim = getattr(distortIMUs[imu].imu, sensorName).rawMeasurements
true = imuData[imu].sensorData(sensorName)(sim.timestamps +
model.startTime)
yield assert_vectors_correlated, sim.values, true, 0.8
def testAgainstReality():
dir = path.dirname(__file__)
filebase = path.join(dir, "swing")
refbase = path.join(dir, "stand")
magbases = [path.join(dir, f) for f in ['magsweep1', 'magsweep2']]
maglookup = {
'Upper Leg IMU' : '66',
'Orient 8' : '8',
'Orient 43': '43'}
magSamples = 2000
refTime = 1.0
posStdDev = 0.0005
rotStdDev = 0.004
ref3D = SplinedMarkerCapture(
loadQualisysTSVFile(refbase + "_3D.tsv"), positionStdDev=posStdDev)
ref6D = SplinedMarkerCapture(
loadQualisysTSVFile(refbase + "_6D.tsv"), rotationStdDev=rotStdDev)
capture3D = SplinedMarkerCapture(
loadQualisysTSVFile(filebase + "_3D.tsv"), positionStdDev=posStdDev)
captureSD = SensorDataCapture.load(filebase + ".sdc")
hip, thigh, knee, shin, ankle = \
['Hip', 'Thigh', 'Knee Hinge', 'Shin', 'Ankle']
jointNames = ['Upper Leg', 'Lower Leg', 'Foot']
jointAbbrevs = ['femur', 'tibia', 'foot']
orientIDs = ['66', '43', '8']
jointMarkerNames = [hip, knee, ankle]
refMarkerNames = [[thigh, knee], [shin, ankle], []]
imuMarkerNames = \
[[j + ' IMU - ' + str(i) for i in range(1,4)] for j in jointNames]
jointMarkerSets = lambda c: [
map(c.marker, jointMarkerNames),
[map(c.marker, r) for r in refMarkerNames],
[map(c.marker, i) for i in imuMarkerNames]]
imuMarkerSets = lambda c: [
[c.marker(i[0]) for i in imuMarkerNames],
[map(c.marker,i[1:]) for i in imuMarkerNames]]
jointRefTrajectories = [MultiMarkerTrajectory(j, r + i, refTime=refTime)
for j, r, i in zip(*(jointMarkerSets(ref3D)))]
jointTrajectories = [
MultiMarkerTrajectory(j, r + i, refVectors=m.refVectors) \
for j, r, i, m in \
zip(*(jointMarkerSets(capture3D) + [jointRefTrajectories]))]
imuRefTrajectories = [MultiMarkerTrajectory(p, r, refTime=refTime)
for p, r in zip(*(imuMarkerSets(ref3D)))]
imuVecTrajectories = [MultiMarkerTrajectory(p, r, refVectors=m.refVectors)
for p, r, m in zip(*(imuMarkerSets(capture3D) + [imuRefTrajectories]))]
imuRefMarkers = [ref6D.marker(j + ' IMU') for j in jointNames]
imuOffsets = [i.position(refTime) - j.position(refTime)
for i, j in zip(imuRefTrajectories, jointRefTrajectories)]
imuRotations = [t.rotation(refTime).conjugate * m.rotation(refTime)
for t, m in zip(imuRefTrajectories, imuRefMarkers)]
imuTrajectories = [OffsetTrajectory(v, o, r)
for v, o, r in zip(imuVecTrajectories, imuOffsets, imuRotations)]
imuData = [captureSD.device(i) for i in orientIDs]
joints = []
for i in range(len(jointNames)):
name = jointNames[i]
traj = jointTrajectories[i]
if i == 0:
model = SampledBodyModel(name)
model.positionKeyFrames = traj.posMarker.positionKeyFrames
joint = model
else:
parent = joints[-1]
refTraj = jointRefTrajectories[i]
parentRefTraj = jointRefTrajectories[i - 1]
pos = refTraj.position(refTime)
parentPos = parentRefTraj.position(refTime)
joint = SampledJoint(joints[-1],name, offset=(pos - parentPos))
joint.rotationKeyFrames = traj.rotationKeyFrames
joints.append(joint)
model = SplinedBodyModel(model)
joints = model.joints
imuJointTrajectories = [OffsetTrajectory(j, o, r)
for j, o, r in zip(joints, imuOffsets, imuRotations)]
positionSets = []
valueSets = []
for magbase in magbases:
orient = SensorDataCapture.load(magbase + '.sdc')
optical = loadQualisysTSVFile(magbase + '_6D.tsv')
for marker in optical.markers:
device = orient.device(maglookup[marker.id])
magData = device.sensorData('magnetometer').values
positionSets.append(marker.positionKeyFrames.values)
valueSets.append(
marker.rotationKeyFrames.values.rotateVector(magData))
positions = np.hstack(positionSets)
values = np.hstack(valueSets)
valid = ~np.any(np.isnan(positions),axis=0) & ~np.any(np.isnan(values),axis=0)
dev = values - np.median(values[:,valid],axis=1).reshape((3,1))
step = np.shape(values[:,valid])[1] / magSamples
posSamples = positions[:,valid][:,::step]
valSamples = values[:,valid][:,::step]
environment = Environment()
environment.magneticField = \
NaturalNeighbourInterpolatedField(posSamples, valSamples)
sim = Simulation(environment=environment)
sim.time = model.startTime
distortIMUs = []
dt = 1/capture3D.sampled.frameRate
for traj in imuJointTrajectories:
platform = IdealIMU(sim, traj)
distortIMUs.append(BasicIMUBehaviour(platform, dt))
sim.run(model.endTime)
for imu in range(3):
for sensorName in ['accelerometer', 'magnetometer', 'gyroscope']:
sim = getattr(distortIMUs[imu].imu,sensorName).rawMeasurements
true = imuData[imu].sensorData(sensorName)(sim.timestamps + model.startTime)
yield assert_vectors_correlated, sim.values, true, 0.8