def getRabeData(sensors, length, shift=256):
from abraxas4.abraxasFrame import AbraxasFrame
b = AbraxasFrame(numIrSensors=10, numFrSensors=2, windowWidth=length, windowShift=shift, numFreqs=0, numCoeffs=0,
enaStatFeats=False, featNormMethod='none', trainFraction=2/3, waveletLvl1=False,
randomSortTT=False, classSortTT=True)
b.setWindowFunction(functionName='rect', alpha=0.25)
# b.plotWindowFunction()
b.selectSensorSubset(selectedSensors=[False, False, False], sensorType='bno')
b.selectSensorSubset(selectedSensors=[], sensorType='fr')
b.selectSensorSubset(selectedSensors=sensors, sensorType='ir')
#b.selectSensorSubset(selectedSensors=[2], sensorType='ir')
b.addDataFiles(fileSourceName="igor2.txt", fileSourcePath="../", startTime=600, stopTime=6000, label=0)
b.addDataFiles(fileSourceName="ankita_pos2_lrRl.txt", fileSourcePath="../", startTime=150, stopTime=2500, label=1)
b.addDataFiles(fileSourceName="markus.txt", fileSourcePath="../", startTime=500, stopTime=3300, label=2)
dataSet = b.readDataSet(checkData=False, equalLength=True)
# dataSet := Array with shape dataSet[i][j, k], where i refers to the i-th file loaded, k indicates the sensor and
# j is the "time"-index.
wData, wLabels = b.windowSplitSourceDataTT(inputData=dataSet, inputLabels=np.array([0, 1, 2]))
wLabels = np.array(wLabels)
print("Number of windows, Igor: ", str(np.size(wLabels[wLabels == 0])))
print("Number of windows, Ankita: ", str(np.size(wLabels[wLabels == 1])))
print("Number of windows, Markus: ", str(np.size(wLabels[wLabels == 2])))
igor = []
ankita = []
markus = []
#for i in range(len(wLabels)):
# wData[i] = wData[i]*(1+0*np.random.random([250, 1]))
for i in range(len(wLabels)):
if wLabels[i]==0:
igor.append(wData[i]*1)
if wLabels[i]==1:
ankita.append(wData[i]*1)
if wLabels[i]==2:
markus.append(wData[i]*1)
return igor, ankita, markus
from abraxas4.abraxasFrame import AbraxasFrame
b = AbraxasFrame(numIrSensors=10,
numFrSensors=2,
windowWidth=250,
windowShift=50,
numFreqs=0,
numCoeffs=0,
enaStatFeats=False,
featNormMethod='none',
trainFraction=2 / 3,
waveletLvl1=False,
randomSortTT=False,
classSortTT=True)
b.setWindowFunction(functionName='rect', alpha=0.25)
# b.plotWindowFunction()
b.selectSensorSubset(selectedSensors=[False, False, False], sensorType='bno')
b.selectSensorSubset(selectedSensors=[], sensorType='fr')
b.selectSensorSubset(selectedSensors=[0, 1, 2, 3, 5, 7, 9], sensorType='ir')
b.addDataFiles(fileSourceName="igor2.txt",
fileSourcePath="../",
startTime=600,
stopTime=6000,
label=0)
b.addDataFiles(fileSourceName="ankita_pos2_lrRl.txt",
fileSourcePath="../",
startTime=150,
dtAbra = AbraxasFrame(numIrSensors=10,
numFrSensors=2,
windowWidth=100,
windowShift=25,
numFreqs=1,
numCoeffs=0,
enaStatFeats=True,
featNormMethod='stand',
trainFraction=2 / 3,
waveletLvl1=False,
randomSortTT=False,
classSortTT=True,
corrPeaks=0,
enaRawFeats=False)
dtAbra.setWindowFunction(functionName='tukey', alpha=0.1)
dtAbra.selectSensorSubset(selectedSensors=[False, True, True],
sensorType='bno')
dtAbra.addDataFiles(fileSourceName="igor.txt",
fileSourcePath="../",
startTime=3550,
stopTime=3800,
label=0,
className="not walking")
dtAbra.addDataFiles(fileSourceName="igor2.txt",
fileSourcePath="../",
startTime=300,
stopTime=500,
label=0)
from abraxasOne.gaussFilter import gaussFilter
b = AbraxasFrame(numIrSensors=10,
numFrSensors=2,
windowWidth=250,
windowShift=50,
numFreqs=0,
numCoeffs=0,
enaStatFeats=False,
featNormMethod='none',
trainFraction=2 / 3,
waveletLvl1=False,
randomSortTT=False,
classSortTT=True)
b.setWindowFunction(functionName='kaiser', alpha=0.25)
# b.plotWindowFunction()
b.selectSensorSubset(selectedSensors=[False, False, False], sensorType='bno')
b.selectSensorSubset(selectedSensors=[], sensorType='fr')
# b.selectSensorSubset(selectedSensors=[0], sensorType='ir')
b.addDataFiles(fileSourceName="igor2.txt",
fileSourcePath="../",
startTime=600,
stopTime=6000,
label=0)
b.addDataFiles(fileSourceName="ankita_pos2_lrRl.txt",
fileSourcePath="../",
startTime=150,
numFrSensors=2,
windowWidth=100,
windowShift=10,
numFreqs=1,
numCoeffs=3,
enaStatFeats=True,
featNormMethod='stand',
trainFraction=2 / 3,
waveletLvl1=False,
randomSortTT=False,
classSortTT=True,
corrPeaks=0,
enaRawFeats=False,
statStages=3)
oc.setWindowFunction(functionName='tukey', alpha=0.1)
oc.selectSensorSubset(selectedSensors=[False, True, True], sensorType='bno')
# oc.selectSensorSubset(selectedSensors=[], sensorType='fr')
# oc.selectSensorSubset(selectedSensors=[0], sensorType='ir')
oc.addDataFiles(fileSourceName="chrisOut2.txt",
fileSourcePath="../",
startTime=1500,
stopTime=5000,
label=0)
oc.addDataFiles(fileSourceName="chrisOut2.txt",
fileSourcePath="../",
startTime=8000,
stopTime=13000,
label=0)
import numpy as np
import random
import xgboost
from sklearn.model_selection import StratifiedKFold
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import train_test_split
#abra = AbraxasFrame(numIrSensors=10, numFrSensors=2, windowWidth=100, windowShift=10, numCoeffs=5, numFreqs=1,
# enaStatFeats=True, wavelet='haar', waveletLvl1=False, featNormMethod='stand', trainFraction=0.66,
# classSortTT=True, randomSortTT=False, lineThresholdAfterNorm=10, enaRawFeats=False, corrPeaks=2)
abra = AbraxasFrame(numIrSensors=10, numFrSensors=2, windowWidth=100, windowShift=10, numFreqs=1, numCoeffs=5,
enaStatFeats=True, featNormMethod='stand', trainFraction=2/3, waveletLvl1=False,
randomSortTT=False, classSortTT=True, corrPeaks=1, enaRawFeats=False)
abra.setWindowFunction(functionName='tukey', alpha=0.3)
abra.selectSensorSubset(selectedSensors=[False, False, False], sensorType='bno')
abra.addDataFiles(fileSourceName="igor.txt", fileSourcePath="../", startTime=3550, stopTime=3800, label=0,
className="not walking")
abra.addDataFiles(fileSourceName="igor2.txt", fileSourcePath="../", startTime=300, stopTime=500, label=0)
abra.addDataFiles(fileSourceName="ankita.txt", fileSourcePath="../", startTime=0, stopTime=150, label=0)
abra.addDataFiles(fileSourceName="markusSchnell.txt", fileSourcePath="../", startTime=4100, stopTime=4300, label=0)
abra.addDataFiles(fileSourceName="stefan.txt", fileSourcePath="../", startTime=7600, stopTime=8600, label=0)
abra.addDataFiles(fileSourceName="stefan.txt", fileSourcePath="../", startTime=0, stopTime=300, label=0)
abra.addDataFiles(fileSourceName="ben.txt", fileSourcePath="../", startTime=0, stopTime=1000, label=0)
abra.addDataFiles(fileSourceName="ben.txt", fileSourcePath="../", startTime=7100, stopTime=8000, label=0)
abra.addDataFiles(fileSourceName="chris1.txt", fileSourcePath="../", startTime=5200, stopTime=6000, label=0)
abra.addDataFiles(fileSourceName="novcc.txt", fileSourcePath="../", startTime=0, stopTime=10000, label=0)
abra.addDataFiles(fileSourceName="nowalk.txt", fileSourcePath="../", startTime=0, stopTime=10000, label=0)
abra.addDataFiles(fileSourceName="nowalk2.txt", fileSourcePath="../", startTime=0, stopTime=10000, label=0)