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
Пример #2
0
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