def _main():
fileName = 'Subject005Trial08.txt'
forcePlateNames = ['FP1']
footMarkerNames = ['RHEE', 'RMT5']
forceData = Question1.parsePointFile(fileName, forcePlateNames, suffix='ForX')
momentData = Question1.parsePointFile(fileName, forcePlateNames, suffix='MomX')
copData = Question1.parsePointFile(fileName, forcePlateNames, suffix='CopX')
markerData = Question1.parsePointFile(fileName, footMarkerNames)
xCoords = np.zeros(400)
zCoords = np.zeros_like(xCoords)
yTorques = np.zeros_like(xCoords)
for i, frame in enumerate(range(600,1000)):
xCoords[i], zCoords[i], yTorques[i] = calcualteCop(forceData['FP1'][frame], momentData['FP1'][frame])
# print xCoord, copData['FP1'][i,0], zCoord, copData['FP1'][i,2], yTorque
plt.style.use('/home/will/Projects/MCLS_CSU/MCLS_Res/GeneralTools/Visualization/matplotlibStyleSheets/MCLSPoster')
fig, ax = plt.subplots(nrows=3)
xVals = np.arange(600, 1000)*0.01
ax[0].plot(xVals, xCoords, color='g', linewidth=2)
ax[1].plot(xVals, zCoords, color='r', linewidth=2)
ax[2].plot(xVals, yTorques, color='b', linewidth=2)
ax[0].set_ylabel(r'$COP_x$')
ax[1].set_ylabel(r'$COP_z$')
ax[2].set_ylabel(r'$T_y$')
ax[2].set_xlabel('Time (s)')
for i in range(3):
ax[i].grid()
ax[i].set_ylim(0,1)
ax[2].set_ylim(-4,4)
fig2, ax2 = plt.subplots(nrows=1)
copx = ax2.plot(xVals, xCoords, color='g', linewidth=2)
rhee = ax2.plot(xVals, markerData['RHEE'][600:1000,0], color='c', linewidth=2.5)
rmt = ax2.plot(xVals, markerData['RMT5'][600:1000,0], color='m', linewidth=2.5)
ax2.set_xlabel('Time (s)')
ax2.set_ylabel(r'$COP_x, Marker_x$')
ax2.set_ylim(0,1)
ax2.grid()
fig2.legend([copx[0], rhee[0], rmt[0]], (r'$COP_x$', 'RHEE', 'RMT5'),
loc='upper center', ncol=3, borderpad=0.4, numpoints=2, columnspacing=0.5)
plt.show()
def _main():
# Define the file that contains the data, the desired range of frames, and the marker names that will be used.
fileName = 'Subject005Trial08.txt'
frames = range(600, 1000)
desiredPointNames3 = ['RGTRO', 'RHEE', 'RMT5']
desiredPointNames5 = ['RGTRO', 'RLEK', 'RLM', 'RHEE', 'RMT5']
# Parse the marker data, and define the number of frames and number of markers
marker3Data = Question1.parsePointFile(fileName, desiredPointNames3)
marker5Data = Question1.parsePointFile(fileName, desiredPointNames5)
frameNumber = len(frames)
# Define the leg model
femurLength = 0.46 # m
shankLength = 0.41 # m
footLength = 0.20 # m
femurAxis = np.array([0.0, -1])
shankAxis = np.array([0.0, -1])
footAxis = np.array([1, 0.0])
femurBody = BodySegment(femurLength, femurAxis)
shankBody = BodySegment(shankLength, shankAxis)
footBody = BodySegment(footLength, footAxis)
bodySegments = [femurBody, shankBody, footBody]
initialGuess = np.array([0.38, 0.84, 40.0, -60.0, 0.0])#np.zeros(5)
marker3Results = run3MarkerForwardKinematics(marker3Data, bodySegments, frameNumber, frames, initialGuess)
marker5Results = run5MarkerForwardKinematics(marker5Data, bodySegments, frameNumber, frames, initialGuess)
print 'Tx = ', min(marker3Results[:,0]), max(marker3Results[:,0])
print 'Ty = ', min(marker3Results[:,1]), max(marker3Results[:,1])
print 'hip = ', min(marker3Results[:,2]), max(marker3Results[:,2])
print 'knee = ', min(marker3Results[:,3]), max(marker3Results[:,3])
print 'foot = ', min(marker3Results[:,4]), max(marker3Results[:,4])
plotGeneralizedCoordinates([marker3Results, marker5Results])
return
