def loadViconCSVFile(filename):
"""
Load 3DOF marker data from a Vicon CSV file.
@param filename: Name of the CSV file to load.
@return: A L{MarkerCapture} object.
"""
# Open file to read header.
datafile = open(filename, 'r')
# Function to get comma-separated values from a line.
values = lambda line: line.rstrip('\r\n').split(',')
# Get column names.
colnames = values(datafile.readline())
# Get marker names.
markernames = [n.split(':')[-2] for n in colnames[2::3]]
# Get data.
data = np.array([[float(v or np.nan) for v in values(line)]
for line in datafile.readlines()]).T
frameTimes = data[1]
positions = data[2:].reshape((len(markernames),3,-1)) / 1000
capture = MarkerCapture()
capture.frameTimes = frameTimes
capture.frameCount = len(frameTimes)
capture.framePeriod = np.min(np.diff(frameTimes))
capture.frameRate = 1 / capture.framePeriod
for i, name in enumerate(markernames):
marker = Marker3DOF(capture, name)
for time, position in zip(capture.frameTimes, positions[i].T):
marker.positionKeyFrames.add(time, position.reshape(3,1))
return capture
def loadQualisysTSVFile(filename):
"""
Load 3DOF or 6DOF marker data from a Qualisys Track Manager TSV file.
@param filename: Name of TSV file to load.
@return: A L{MarkerCapture} instance.
"""
# Open file to read header.
datafile = open(filename, 'r')
# Count of header lines in file.
headerLines = 0
capture = MarkerCapture()
markerIndices = dict()
while True:
# Read and count each file header line.
line = datafile.readline().strip('\r\n')
headerLines = headerLines + 1
# Key and values are tab-separated.
items = line.split('\t')
key = items[0]
values = items[1:]
# Handle relevant fields.
if key == 'FREQUENCY':
# Frame rate.
capture.frameRate = int(values[0])
capture.framePeriod = 1/capture.frameRate
elif key == 'DATA_INCLUDED':
# 3D or 6D data.
type = values[0]
if (type == '3D'):
# 3D data fields are implicitly XYZ co-ordinates.
fieldNames = ['X', 'Y', 'Z']
elif key == 'BODY_NAMES' or key == 'MARKER_NAMES':
# List of markers or 6DOF body names.
for i in range(len(values)):
name = values[i]
if type == '6D':
markerClass = Marker6DOF
else:
markerClass = Marker3DOF
markerIndices[markerClass(capture, name)] = i
if (type == '6D'):
# Field names are on a line after the body names, each
# beginning with a space.
fieldNames = [x.strip(' ') for x in
datafile.readline().strip('\r\n').split('\t')]
headerLines = headerLines + 1
# The above keys are always on the last line in the header.
datafile.close()
break
# Load values from file, skipping header.
data = np.loadtxt(filename, skiprows = headerLines)
capture.frameCount = len(data)
capture.frameTimes = np.arange(0, capture.frameCount / capture.frameRate,
capture.framePeriod)
# Find index in data array for a given marker and marker field name.
def index(marker, name):
offset = markerIndices[marker] * len(fieldNames)
return offset + fieldNames.index(name)
# Return data for a given marker and marker field names.
def fields(marker, names):
indices = [index(marker, name) for name in names]
return data[:,indices[0]:indices[-1]+1]
# Iterate through markers to fill in their data.
for marker in capture.markers:
# Get position data.
positions = fields(marker, ['X', 'Y', 'Z']) / 1000
if type == '6D':
# Get rotation matrices.
matrix_coeffs = fields(marker, ['Rot[%d]' % i for i in range(9)])
# Mark invalid data (residual = -1) with NaNs.
invalid = fields(marker, ['Residual'])[:,0] == -1.0
matrix_coeffs[invalid] = np.nan
positions[invalid] = np.nan
# Convert to quaternions and unflip.
quats = QuaternionArray(np.empty((capture.frameCount,4)))
for i in range(len(quats)):
q = Quaternion()
q.setFromMatrix(matrix_coeffs[i].reshape((3,3)).T)
quats[i] = q
rotations = quats.unflipped()
# Add rotation data to marker.
for time, rotation in zip(capture.frameTimes, rotations):
marker.rotationKeyFrames.add(time, rotation)
# Add position data to marker.
for time, position in zip(capture.frameTimes, positions):
marker.positionKeyFrames.add(time, position.reshape(3,1))
return capture
def loadQualisysTSVFile(filename):
"""
Load 3DOF or 6DOF marker data from a Qualisys Track Manager TSV file.
@param filename: Name of TSV file to load.
@return: A L{MarkerCapture} instance.
"""
# Open file to read header.
datafile = open(filename, 'r')
# Count of header lines in file.
headerLines = 0
capture = MarkerCapture()
markerIndices = dict()
while True:
# Read and count each file header line.
line = datafile.readline().strip('\r\n')
headerLines = headerLines + 1
# Key and values are tab-separated.
items = line.split('\t')
key = items[0]
values = items[1:]
# Handle relevant fields.
if key == 'FREQUENCY':
# Frame rate.
capture.frameRate = int(values[0])
capture.framePeriod = 1 / capture.frameRate
elif key == 'DATA_INCLUDED':
# 3D or 6D data.
type = values[0]
if (type == '3D'):
# 3D data fields are implicitly XYZ co-ordinates.
fieldNames = ['X', 'Y', 'Z']
elif key == 'BODY_NAMES' or key == 'MARKER_NAMES':
# List of markers or 6DOF body names.
for i in range(len(values)):
name = values[i]
if type == '6D':
markerClass = Marker6DOF
else:
markerClass = Marker3DOF
markerIndices[markerClass(capture, name)] = i
if (type == '6D'):
# Field names are on a line after the body names, each
# beginning with a space.
fieldNames = [
x.strip(' ')
for x in datafile.readline().strip('\r\n').split('\t')
]
headerLines = headerLines + 1
# The above keys are always on the last line in the header.
datafile.close()
break
# Load values from file, skipping header.
data = np.loadtxt(filename, skiprows=headerLines)
capture.frameCount = len(data)
capture.frameTimes = np.arange(0, capture.frameCount / capture.frameRate,
capture.framePeriod)
# Find index in data array for a given marker and marker field name.
def index(marker, name):
offset = markerIndices[marker] * len(fieldNames)
return offset + fieldNames.index(name)
# Return data for a given marker and marker field names.
def fields(marker, names):
indices = [index(marker, name) for name in names]
return data[:, indices[0]:indices[-1] + 1]
# Iterate through markers to fill in their data.
for marker in capture.markers:
# Get position data.
positions = fields(marker, ['X', 'Y', 'Z']) / 1000
if type == '6D':
# Get rotation matrices.
matrix_coeffs = fields(marker, ['Rot[%d]' % i for i in range(9)])
# Mark invalid data (residual = -1) with NaNs.
invalid = fields(marker, ['Residual'])[:, 0] == -1.0
matrix_coeffs[invalid] = np.nan
positions[invalid] = np.nan
# Convert to quaternions and unflip.
quats = QuaternionArray(np.empty((capture.frameCount, 4)))
for i in range(len(quats)):
q = Quaternion()
q.setFromMatrix(matrix_coeffs[i].reshape((3, 3)).T)
quats[i] = q
rotations = quats.unflipped()
# Add rotation data to marker.
for time, rotation in zip(capture.frameTimes, rotations):
marker.rotationKeyFrames.add(time, rotation)
# Add position data to marker.
for time, position in zip(capture.frameTimes, positions):
marker.positionKeyFrames.add(time, position.reshape(3, 1))
return capture