label=6)
a.addDataFiles(fileSourceName="igor2.txt",
fileSourcePath="../",
startTime=600,
stopTime=6000,
label=6)
a.readDataSet(equalLength=False, checkData=False)
useDump = False
if useDump:
a.loadDumpNormParam(dumpName="dataOnly")
clf = a.loadDumpClassifier("dataOnly")
a.testClassifier(classifier=clf)
a.setFileSink(fileSinkName="chris", fileSinkPath="../")
a.startLiveClassification()
else:
a.initFeatNormalization(dumpName="dataOnly")
from sklearn import svm
clf = svm.SVC(kernel='rbf')
a.trainClassifier(classifier=clf)
a.dumpClassifier(dumpName="dataOnly")
a.testClassifier()
windowedData, windowLabels = a.windowSplitSourceDataTT()
index = np.linspace(0, len(windowedData) - 1, len(windowedData), dtype=int)
random.shuffle(index)
trainingData = []
from abraxasThree.classifierClass import AbraxasClassifier
a = AbraxasClassifier(numIrSensors=1,
numFrSensors=0,
windowWidth=1500,
windowShift=10,
numFreqs=0,
numCoeffs=0,
enaStatFeats=False,
featNormMethod='stand',
trainFraction=2 / 3,
waveletLvl1=False,
randomSortTT=False,
classSortTT=True)
a.setFileSink(fileSinkName="test.txt", fileSinkPath="../")
a.setWindowFunction(functionName='rect', alpha=0)
a.setupSerialInterface(port="/dev/ttyACM0", baudRate=57600)
a.startReceiveData()
a.startPlotStreamData(sensorNr=[5, 7, 8, 10])