pose2sim/Pose2Sim/MarkerAugmenter/utilsDataman.py

283 lines
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Python
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2024-01-09 19:15:12 +08:00
"""Manages the movement and use of data files."""
import os
import warnings
from scipy.spatial.transform import Rotation as R
import numpy as np
from numpy.lib.recfunctions import append_fields
class TRCFile(object):
"""A plain-text file format for storing motion capture marker trajectories.
TRC stands for Track Row Column.
The metadata for the file is stored in attributes of this object.
See
http://simtk-confluence.stanford.edu:8080/display/OpenSim/Marker+(.trc)+Files
for more information.
"""
def __init__(self, fpath=None, **kwargs):
#path=None,
#data_rate=None,
#camera_rate=None,
#num_frames=None,
#num_markers=None,
#units=None,
#orig_data_rate=None,
#orig_data_start_frame=None,
#orig_num_frames=None,
#marker_names=None,
#time=None,
#):
"""
Parameters
----------
fpath : str
Valid file path to a TRC (.trc) file.
"""
self.marker_names = []
if fpath != None:
self.read_from_file(fpath)
else:
for k, v in kwargs.items():
setattr(self, k, v)
def read_from_file(self, fpath):
# Read the header lines / metadata.
# ---------------------------------
# Split by any whitespace.
# TODO may cause issues with paths that have spaces in them.
f = open(fpath)
# These are lists of each entry on the first few lines.
first_line = f.readline().split()
# Skip the 2nd line.
f.readline()
third_line = f.readline().split()
fourth_line = f.readline().split()
f.close()
# First line.
if len(first_line) > 3:
self.path = first_line[3]
else:
self.path = ''
# Third line.
self.data_rate = float(third_line[0])
self.camera_rate = float(third_line[1])
self.num_frames = int(third_line[2])
self.num_markers = int(third_line[3])
self.units = third_line[4]
self.orig_data_rate = float(third_line[5])
self.orig_data_start_frame = int(third_line[6])
self.orig_num_frames = int(third_line[7])
# Marker names.
# The first and second column names are 'Frame#' and 'Time'.
self.marker_names = fourth_line[2:]
len_marker_names = len(self.marker_names)
if len_marker_names != self.num_markers:
warnings.warn('Header entry NumMarkers, %i, does not '
'match actual number of markers, %i. Changing '
'NumMarkers to match actual number.' % (
self.num_markers, len_marker_names))
self.num_markers = len_marker_names
# Load the actual data.
# ---------------------
col_names = ['frame_num', 'time']
# This naming convention comes from OpenSim's Inverse Kinematics tool,
# when it writes model marker locations.
for mark in self.marker_names:
col_names += [mark + '_tx', mark + '_ty', mark + '_tz']
dtype = {'names': col_names,
'formats': ['int'] + ['float64'] * (3 * self.num_markers + 1)}
usecols = [i for i in range(3 * self.num_markers + 1 + 1)]
self.data = np.loadtxt(fpath, delimiter='\t', skiprows=5, dtype=dtype,
usecols=usecols)
self.time = self.data['time']
# Check the number of rows.
n_rows = self.time.shape[0]
if n_rows != self.num_frames:
warnings.warn('%s: Header entry NumFrames, %i, does not '
'match actual number of frames, %i, Changing '
'NumFrames to match actual number.' % (fpath,
self.num_frames, n_rows))
self.num_frames = n_rows
def __getitem__(self, key):
"""See `marker()`.
"""
return self.marker(key)
def units(self):
return self.units
def time(self):
this_dat = np.empty((self.num_frames, 1))
this_dat[:, 0] = self.time
return this_dat
def marker(self, name):
"""The trajectory of marker `name`, given as a `self.num_frames` x 3
array. The order of the columns is x, y, z.
"""
this_dat = np.empty((self.num_frames, 3))
this_dat[:, 0] = self.data[name + '_tx']
this_dat[:, 1] = self.data[name + '_ty']
this_dat[:, 2] = self.data[name + '_tz']
return this_dat
def add_marker(self, name, x, y, z):
"""Add a marker, with name `name` to the TRCFile.
Parameters
----------
name : str
Name of the marker; e.g., 'R.Hip'.
x, y, z: array_like
Coordinates of the marker trajectory. All 3 must have the same
length.
"""
if (len(x) != self.num_frames or len(y) != self.num_frames or len(z) !=
self.num_frames):
raise Exception('Length of data (%i, %i, %i) is not '
'NumFrames (%i).', len(x), len(y), len(z), self.num_frames)
self.marker_names += [name]
self.num_markers += 1
if not hasattr(self, 'data'):
self.data = np.array(x, dtype=[('%s_tx' % name, 'float64')])
self.data = append_fields(self.data,
['%s_t%s' % (name, s) for s in 'yz'],
[y, z], usemask=False)
else:
self.data = append_fields(self.data,
['%s_t%s' % (name, s) for s in 'xyz'],
[x, y, z], usemask=False)
def marker_at(self, name, time):
x = np.interp(time, self.time, self.data[name + '_tx'])
y = np.interp(time, self.time, self.data[name + '_ty'])
z = np.interp(time, self.time, self.data[name + '_tz'])
return [x, y, z]
def marker_exists(self, name):
"""
Returns
-------
exists : bool
Is the marker in the TRCFile?
"""
return name in self.marker_names
def write(self, fpath):
"""Write this TRCFile object to a TRC file.
Parameters
----------
fpath : str
Valid file path to which this TRCFile is saved.
"""
f = open(fpath, 'w')
# Line 1.
f.write('PathFileType 4\t(X/Y/Z) %s\n' % os.path.split(fpath)[0])
# Line 2.
f.write('DataRate\tCameraRate\tNumFrames\tNumMarkers\t'
'Units\tOrigDataRate\tOrigDataStartFrame\tOrigNumFrames\n')
# Line 3.
f.write('%.1f\t%.1f\t%i\t%i\t%s\t%.1f\t%i\t%i\n' % (
self.data_rate, self.camera_rate, self.num_frames,
self.num_markers, self.units, self.orig_data_rate,
self.orig_data_start_frame, self.orig_num_frames))
# Line 4.
f.write('Frame#\tTime\t')
for imark in range(self.num_markers):
f.write('%s\t\t\t' % self.marker_names[imark])
f.write('\n')
# Line 5.
f.write('\t\t')
for imark in np.arange(self.num_markers) + 1:
f.write('X%i\tY%s\tZ%s\t' % (imark, imark, imark))
f.write('\n')
# Line 6.
f.write('\n')
# Data.
for iframe in range(self.num_frames):
f.write('%i' % (iframe + 1))
f.write('\t%.7f' % self.time[iframe])
for mark in self.marker_names:
idxs = [mark + '_tx', mark + '_ty', mark + '_tz']
f.write('\t%.7f\t%.7f\t%.7f' % tuple(
self.data[coln][iframe] for coln in idxs))
f.write('\n')
f.close()
def add_noise(self, noise_width):
""" add random noise to each component of the marker trajectory
The noise mean will be zero, with the noise_width being the
standard deviation.
noise_width : int
"""
for imarker in range(self.num_markers):
components = ['_tx', '_ty', '_tz']
for iComponent in range(3):
# generate noise
noise = np.random.normal(0, noise_width, self.num_frames)
# add noise to each component of marker data.
self.data[self.marker_names[imarker] + components[iComponent]] += noise
def rotate(self, axis, value):
""" rotate the data.
axis : rotation axis
value : angle in degree
"""
for imarker in range(self.num_markers):
temp = np.zeros((self.num_frames, 3))
temp[:,0] = self.data[self.marker_names[imarker] + '_tx']
temp[:,1] = self.data[self.marker_names[imarker] + '_ty']
temp[:,2] = self.data[self.marker_names[imarker] + '_tz']
r = R.from_euler(axis, value, degrees=True)
temp_rot = r.apply(temp)
self.data[self.marker_names[imarker] + '_tx'] = temp_rot[:,0]
self.data[self.marker_names[imarker] + '_ty'] = temp_rot[:,1]
self.data[self.marker_names[imarker] + '_tz'] = temp_rot[:,2]
def offset(self, axis, value):
""" offset the data.
axis : rotation axis
value : offset in m
"""
for imarker in range(self.num_markers):
if axis.lower() == 'x':
self.data[self.marker_names[imarker] + '_tx'] += value
elif axis.lower() == 'y':
self.data[self.marker_names[imarker] + '_ty'] += value
elif axis.lower() == 'z':
self.data[self.marker_names[imarker] + '_tz'] += value
else:
raise ValueError("Axis not recognized")