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])