def __init__(self, parent, name=None, offset=None):
"""
Construct point trajectory.
@param parent: Parent L{Joint} in the body model hierarchy.
@param name: Name of the point.
@param offset: Offset of the point in the parent joint
co-ordinate frame.
"""
Point.__init__(self, parent, name, offset)
OffsetTrajectory.__init__(self, parent, offset)
def __init__(self, parent, name=None, offset=None):
"""
Construct point trajectory.
@param parent: Parent L{Joint} in the body model hierarchy.
@param name: Name of the point.
@param offset: Offset of the point in the parent joint
co-ordinate frame.
"""
Point.__init__(self, parent, name, offset)
OffsetTrajectory.__init__(self, parent, offset)
def __init__(self, parent, name=None, offset=None):
"""
Initialise sampled joint.
@param parent: Parent L{Joint} in the body model hierarchy.
@param name: Name of the joint.
@param offset: Offset of the joint in the parent joint
co-ordinate frame.
"""
Joint.__init__(self, parent, name, offset)
OffsetTrajectory.__init__(self, parent, offset)
SampledRotationTrajectory.__init__(self)
def __init__(self, parent, name=None, offset=None):
"""
Initialise sampled joint.
@param parent: Parent L{Joint} in the body model hierarchy.
@param name: Name of the joint.
@param offset: Offset of the joint in the parent joint
co-ordinate frame.
"""
Joint.__init__(self, parent, name, offset)
OffsetTrajectory.__init__(self, parent, offset)
SampledRotationTrajectory.__init__(self)
def __init__(self, parent, sampled, **kwargs):
"""
Initialise splined joint.
@param sampled: the L{SampledJoint} from which to generate splined
trajectories
@param parent: the parent joint in the body model hierarchy
"""
Joint.__init__(self, parent, sampled.name, sampled.positionOffset)
OffsetTrajectory.__init__(self, parent, sampled.positionOffset)
SplinedRotationTrajectory.__init__(self, sampled, **kwargs)
self.children = [
(SplinedJoint(self, child, **kwargs) if child.isJoint
else PointTrajectory(self, child.name, child.positionOffset))
for child in sampled.children]
def setupIMU(id, joint):
offset = randomPosition((-0.1, 0.1))
platform = IdealIMU()
calibration = calibrator.calibrate(platform)
platform.simulation = sim
platform.trajectory = OffsetTrajectory(joint, offset)
filter = DistLinAccelCF(samplingPeriod,
platform.trajectory.rotation(simModel.startTime),
k, joint, offset)
def updateChildren():
for child in filter.children:
childID = joints.index(child)
childAccel = filter.childAcceleration(child.positionOffset, samplingPeriod)
if childAccel is not None:
auxPacket = AuxPacket(id, childID,
[('linearAcceleration', childAccel)])
mac.queueAuxPacket(auxPacket)
def handlePacket(packet):
filter.handleLinearAcceleration(packet['linearAcceleration'], samplingPeriod)
updateChildren()
def handleSample(behaviour):
rotation = filter.rotation.latestValue
packet = DataPacket(id, [('rotation', rotation)])
mac.queuePacket(packet)
if not filter.joint.hasParent:
updateChildren()
behaviour = BasicIMUBehaviour(platform, samplingPeriod, calibration,
filter, handleSample, initialTime=sim.time)
mac = InterSlaveMAC(platform.radio, behaviour.timerMux, schedule,
id, handlePacket)
def _trajectoryChange(self):
parentTrajectory = self.platform.trajectory
if parentTrajectory is None:
self.trajectory = None
else:
self.trajectory = OffsetTrajectory(parentTrajectory,
self._positionOffset, self._rotationOffset)
def __init__(self, parent, sampled, **kwargs):
"""
Initialise splined joint.
@param sampled: the L{SampledJoint} from which to generate splined
trajectories
@param parent: the parent joint in the body model hierarchy
"""
Joint.__init__(self, parent, sampled.name, sampled.positionOffset)
OffsetTrajectory.__init__(self, parent, sampled.positionOffset)
SplinedRotationTrajectory.__init__(self, sampled, **kwargs)
self.children = [
(SplinedJoint(self, child, **kwargs) if child.isJoint else
PointTrajectory(self, child.name, child.positionOffset))
for child in sampled.children
]
def testOffsetTrajectories():
for i in range(10):
T = RandomTrajectory()
t = T.positionKeyFrames.timestamps
dt = t[1] - t[0]
p = T.position(t)
r = T.rotation(t)
offset = randomPosition()
rotationOffset = randomRotation()
oT = OffsetTrajectory(T, offset, rotationOffset)
offsetPositions = p + r.rotateVector(offset)
offsetRotations = r * rotationOffset
yield checkTrajectory, oT, TimeSeries(t, offsetPositions), TimeSeries(
t, offsetRotations)
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