import tables as tab
import numpy as np
import matplotlib.pyplot as plt
import DataProcessor as dp
datafile = tab.openFile('InstrumentedBicycleData.h5')
datatable = datafile.root.data.datatable
for x in datatable.iterrows():
if x['RunID'] == 4:
pass
else:
if x['Maneuver'] != 'System Test':
numSamp = x['NINumSamples']
sampleRate = x['NISampleRate']
time = np.linspace(0., numSamp/sampleRate, num=numSamp)
acceleration = dp.unsize_vector(x['FrameAccelY'], numSamp)
print '--------------------'
print 'Run ID:', x['RunID']
print 'Speed:', x['Speed']
print 'Notes:', x['Notes']
print 'Environment:', x['Environment']
print 'Maneuver:', x['Maneuver']
print 'Total time:', time[-1]
print 'Time of max value:', time[np.argmax(acceleration)]
print 'Max value:', np.max(acceleration)
print '--------------------'
if time[np.argmax(acceleration)] > 5.:
plt.figure(x['RunID'])
plt.plot(time, acceleration)
plt.title(x['Speed'])
import tables as tab
import numpy as np
import DataProcessor as dp
datafile = tab.openFile('InstrumentedBicycleData.h5')
datatable = datafile.root.data.datatable
nanList = []
for x in datatable.iterrows():
cell = x['AccelerationX']
vnSampRate = x['NINumSamples']
vnSig = dp.unsize_vector(cell, vnSampRate)
numNan = np.sum(np.isnan(vnSig))
if numNan > 2:
nanList.append((x['RunID'], numNan))
nanList.sort(key=lambda x: x[1])
for thing in nanList:
print thing
