def plotDSAgainst(nr):
plt.close('all')
nadja = createDataSetFromFile('nadja_'+str(nr)+'_fullSet.npz')
line = createDataSetFromFile('line_'+str(nr)+'_fullSet.npz')
stephan = createDataSetFromFile('stephan_'+str(nr)+'_fullSet.npz')
nike = createDataSetFromFile('nike_'+str(nr)+'_fullSet.npz')
julian = createDataSetFromFile('julian_'+str(nr)+'_fullSet.npz')
nadja.plot(2,False)
line.plot(2,False) #falsch
stephan.plot(2,False)
nike.plot(2,False)
julian.plot(2,False) #falsch
def plotDSAgainst(nr):
plt.close('all')
nadja = createDataSetFromFile('nadja_' + str(nr) + '_fullSet.npz')
line = createDataSetFromFile('line_' + str(nr) + '_fullSet.npz')
stephan = createDataSetFromFile('stephan_' + str(nr) + '_fullSet.npz')
nike = createDataSetFromFile('nike_' + str(nr) + '_fullSet.npz')
julian = createDataSetFromFile('julian_' + str(nr) + '_fullSet.npz')
nadja.plot(2, False)
line.plot(2, False) #falsch
stephan.plot(2, False)
nike.plot(2, False)
julian.plot(2, False) #falsch
def analyseDataSet(dataSetName):
ds = createDataSetFromFile(dataSetName)
signals = ds.getAllSignals()
lengths = map(len,signals)
power = map(normPower,signals)
rot = map(normRot,signals)
fused = map(normFused,signals)
power_means = map(np.mean,power)
rot_means = map(np.mean,rot)
fused_means = map(np.mean,fused)
print np.var(lengths)
print np.var(power_means)
print np.var(rot_means)
print np.var(fused_means)
return [np.var(lengths), np.var(power_means),np.var(rot_means),np.var(fused_means)]
def analyseDataSet(dataSetName):
ds = createDataSetFromFile(dataSetName)
signals = ds.getAllSignals()
lengths = map(len, signals)
power = map(normPower, signals)
rot = map(normRot, signals)
fused = map(normFused, signals)
power_means = map(np.mean, power)
rot_means = map(np.mean, rot)
fused_means = map(np.mean, fused)
print np.var(lengths)
print np.var(power_means)
print np.var(rot_means)
print np.var(fused_means)
return [
np.var(lengths),
np.var(power_means),
np.var(rot_means),
np.var(fused_means)
]
def analyseBias():
dsNames = getAllDataSetNames()
dataSets = []
for dsName in dsNames:
dataSets.append(createDataSetFromFile(dsName))
meanDrifts = []
for gesture in range(0,10):
signals = []
for dataSet in dataSets:
signals.extend( dataSet.getAllSignals(gesture, 2))
signalSums = np.zeros((len(signals),9))
for i, signal in enumerate(signals):
signalSums[i,:] = np.sum(signal[:,0:9],0)
meanDrifts.append( np.mean(signalSums,0))
plt.figure()
for meanDrift in meanDrifts:
plt.plot(meanDrift)
pass
def analyseBias():
dsNames = getAllDataSetNames()
dataSets = []
for dsName in dsNames:
dataSets.append(createDataSetFromFile(dsName))
meanDrifts = []
for gesture in range(0, 10):
signals = []
for dataSet in dataSets:
signals.extend(dataSet.getAllSignals(gesture, 2))
signalSums = np.zeros((len(signals), 9))
for i, signal in enumerate(signals):
signalSums[i, :] = np.sum(signal[:, 0:9], 0)
meanDrifts.append(np.mean(signalSums, 0))
plt.figure()
for meanDrift in meanDrifts:
plt.plot(meanDrift)
pass
def plotGesturesVs():
pass
#if __name__ == '__main__':
ds1 = createDataSetFromFile('nadja_7_fullSet.npz')
ds1signals = ds1.getAllSignals(7,2)
ds2 = createDataSetFromFile('julian_7_fullSet.npz')
ds2signals = ds2.getAllSignals(7,2)
ds3 = createDataSetFromFile('julian_2_fullSet.npz')
ds4 = createDataSetFromFile('julian_3_fullSet.npz')
plt.switch_backend('Qt4Agg')
axes, subs = plt.subplots(3, 1, True)
print zip(map(len,ds1signals),map(len,ds2signals))
for i in range(0,3):
label=['Gest. 1 X','Gest. 1 Y','Gest. 1 Z']
cmap = mpl.cm.Reds_r
subs[0].plot(ds1signals[1][:,i] ,label=label[i] ,color=cmap(i / 3.0))
for i in range(0,3):
label=['Gest. 2 X','Gest. 2 Y','Gest. 2 Z']
cmap = mpl.cm.Blues
subs[0].plot(ds2signals[8][:,i] ,label=label[i] ,color=cmap((i+0.5) / 3.0))
subs[0].set_title('Fused')
for i in range(3,6):
label=['Gest. 1 X','Gest. 1 Y','Gest. 1 Z']
cmap = mpl.cm.Reds_r
subs[1].plot(ds1signals[1][:,i] ,label=label[i-3] ,color=cmap((i-3) / 3.0))
for i in range(3,6):
label=['Gest. 2 X','Gest. 2 Y','Gest. 2 Z']
cmap = mpl.cm.Blues
subs[1].plot(ds2signals[8][:,i] ,label=label[i-3] ,color=cmap((i+1-3) / 3.0))
subs[1].set_title('Rotation')
for i in range(6,9):
label=['Gest. 1 X','Gest. 1 Y','Gest. 1 Z']
cmap = mpl.cm.Reds_r
subs[2].plot(ds1signals[1][:,i] ,label=label[i-6] ,color=cmap((i-6) / 3.0))
for i in range(6,9):
label=['Gest. 2 X','Gest. 2 Y','Gest. 2 Z']
cmap = mpl.cm.Blues
subs[2].plot(ds2signals[8][:,i] ,label=label[i-6] ,color=cmap((i+1-6) / 3.0))
subs[2].set_title('Acceleration')
subs[0].legend()
subs[1].legend()
subs[2].legend()
for name in ['stephan','julian','nadja','line','nike']:
ds1 = createDataSetFromFile(name+'_0_fullSet.npz')
ds2 = createDataSetFromFile(name+'_1_fullSet.npz')
ds3 = createDataSetFromFile(name+'_2_fullSet.npz')
ds4 = createDataSetFromFile(name+'_3_fullSet.npz')
plot3dFused([ds1, ds2,ds3,ds4],'Gyroscope trajectories for snap gestures')
for j, signal in enumerate(createDataSetFromFile('nike_3_fullSet.npz').getAllSignals()):
fig,axes = plt.subplots(2, 1, True)
fused1 = signal[:,0:3]
fusedInt1 = np.zeros(fused1.shape)
fusedInt2 = np.zeros(fused1.shape)
for i in range(1,fused1.shape[0]):
fusedInt1[i] = np.sum(fused1[:i],0)
fusedInt2[i] = fusedInt2[i-1]*0.95+fused1[i]
axes[0].plot(fusedInt1)
axes[1].plot(fusedInt2)
plt.title(str(j))
totalTotalGestureRotation = []
totalTotalGestureAvgRotation = []
totalTotalGesturePerformer = []
lengthVariances = []
for gestureNr in range(0,10):
totalSignalLengths = []
totalSignalPowers = []
totalSignalAvgPowers = []
totalSignalRotation = []
totalSignalAvgRotation = []
totalFileNames = []
totalGesturePerformer = []
for iFile in inputFiles:
ds =createDataSetFromFile(iFile+'_'+str(gestureNr)+'_fullSet.npz')
dataSets.append(ds)
signals = ds.getAllSignals(gestureNr, 2)
nSignals = len(signals)
if nSignals > 0:
signalLengths = np.zeros((nSignals,1))
signalPower = np.zeros((nSignals,1))
signalRotation = np.zeros((nSignals,1))
signalAvgPower = np.zeros((nSignals,1))
signalAvgRotation = np.zeros((nSignals,1))
for i in range(0,nSignals):
signal = signals[i]
#signal lenght
rows, cols = signal.shape
def createGroundTruthCreation():
ds = createDataSetFromFile('julian_0_fullSet.npz')
def plotGesturesVs():
pass
#if __name__ == '__main__':
ds1 = createDataSetFromFile('nadja_7_fullSet.npz')
ds1signals = ds1.getAllSignals(7, 2)
ds2 = createDataSetFromFile('julian_7_fullSet.npz')
ds2signals = ds2.getAllSignals(7, 2)
ds3 = createDataSetFromFile('julian_2_fullSet.npz')
ds4 = createDataSetFromFile('julian_3_fullSet.npz')
plt.switch_backend('Qt4Agg')
axes, subs = plt.subplots(3, 1, True)
print zip(map(len, ds1signals), map(len, ds2signals))
for i in range(0, 3):
label = ['Gest. 1 X', 'Gest. 1 Y', 'Gest. 1 Z']
cmap = mpl.cm.Reds_r
subs[0].plot(ds1signals[1][:, i], label=label[i], color=cmap(i / 3.0))
for i in range(0, 3):
label = ['Gest. 2 X', 'Gest. 2 Y', 'Gest. 2 Z']
cmap = mpl.cm.Blues
subs[0].plot(ds2signals[8][:, i],
label=label[i],
color=cmap((i + 0.5) / 3.0))
subs[0].set_title('Fused')
for i in range(3, 6):
label = ['Gest. 1 X', 'Gest. 1 Y', 'Gest. 1 Z']
cmap = mpl.cm.Reds_r
subs[1].plot(ds1signals[1][:, i],
label=label[i - 3],
color=cmap((i - 3) / 3.0))
for i in range(3, 6):
label = ['Gest. 2 X', 'Gest. 2 Y', 'Gest. 2 Z']
cmap = mpl.cm.Blues
subs[1].plot(ds2signals[8][:, i],
label=label[i - 3],
color=cmap((i + 1 - 3) / 3.0))
subs[1].set_title('Rotation')
for i in range(6, 9):
label = ['Gest. 1 X', 'Gest. 1 Y', 'Gest. 1 Z']
cmap = mpl.cm.Reds_r
subs[2].plot(ds1signals[1][:, i],
label=label[i - 6],
color=cmap((i - 6) / 3.0))
for i in range(6, 9):
label = ['Gest. 2 X', 'Gest. 2 Y', 'Gest. 2 Z']
cmap = mpl.cm.Blues
subs[2].plot(ds2signals[8][:, i],
label=label[i - 6],
color=cmap((i + 1 - 6) / 3.0))
subs[2].set_title('Acceleration')
subs[0].legend()
subs[1].legend()
subs[2].legend()
for name in ['stephan', 'julian', 'nadja', 'line', 'nike']:
ds1 = createDataSetFromFile(name + '_0_fullSet.npz')
ds2 = createDataSetFromFile(name + '_1_fullSet.npz')
ds3 = createDataSetFromFile(name + '_2_fullSet.npz')
ds4 = createDataSetFromFile(name + '_3_fullSet.npz')
plot3dFused([ds1, ds2, ds3, ds4],
'Gyroscope trajectories for snap gestures')
for j, signal in enumerate(
createDataSetFromFile('nike_3_fullSet.npz').getAllSignals()):
fig, axes = plt.subplots(2, 1, True)
fused1 = signal[:, 0:3]
fusedInt1 = np.zeros(fused1.shape)
fusedInt2 = np.zeros(fused1.shape)
for i in range(1, fused1.shape[0]):
fusedInt1[i] = np.sum(fused1[:i], 0)
fusedInt2[i] = fusedInt2[i - 1] * 0.95 + fused1[i]
axes[0].plot(fusedInt1)
axes[1].plot(fusedInt2)
plt.title(str(j))
totalTotalGestureRotation = []
totalTotalGestureAvgRotation = []
totalTotalGesturePerformer = []
lengthVariances = []
for gestureNr in range(0, 10):
totalSignalLengths = []
totalSignalPowers = []
totalSignalAvgPowers = []
totalSignalRotation = []
totalSignalAvgRotation = []
totalFileNames = []
totalGesturePerformer = []
for iFile in inputFiles:
ds = createDataSetFromFile(iFile + '_' + str(gestureNr) +
'_fullSet.npz')
dataSets.append(ds)
signals = ds.getAllSignals(gestureNr, 2)
nSignals = len(signals)
if nSignals > 0:
signalLengths = np.zeros((nSignals, 1))
signalPower = np.zeros((nSignals, 1))
signalRotation = np.zeros((nSignals, 1))
signalAvgPower = np.zeros((nSignals, 1))
signalAvgRotation = np.zeros((nSignals, 1))
for i in range(0, nSignals):
signal = signals[i]
#signal lenght
rows, cols = signal.shape