コード例 #1
0
ファイル: FreqDomainSimple.py プロジェクト: jessab/ML
                                 if col in posCols()]
    generatedFeatures['features'] = [f for f in generatedFeatures['features']
                                     if f in posFeatures().keys()]

    return generatedFeatures


def getSimpleFreqDomainFeatures(data, requiredFeatures=None):
    requiredFeatures = checkRequiredFeatures(requiredFeatures)

    data = toFreq(data[requiredFeatures['cols']])

    features = dict()

    for f in requiredFeatures['features']:
        features.update(posFeatures()[f](data, f))

    return features

if __name__ == '__main__':
    import dataTransform.accproc as ac
    import dataTransform.Preprocessing as pp
    for i in range(9):
        nb = int(i + 1)
        if nb == 4:
            data = ac.readGCDCFormat("..\data\Runs\Tina\enkel\DATA-00" +
                                     `nb` + ".csv")
            data = ac.preprocessGCDC(data)
            filtered = pp.filterRun3(data)
            print(getSimpleFreqDomainFeatures(data, None))
コード例 #2
0
ファイル: DataLoader.py プロジェクト: jessab/ML
 def getRunningPart(data, hip):
     try:
         return pp.filterRun3(data, hip)
     except:
         return None
コード例 #3
0
ファイル: PeakSimple.py プロジェクト: jessab/ML

def getSimplePeakFeatures(data, requiredFeatures=None):
    generatedFeatures = {'cols': posPeaks(), 'features': posFeatures().keys()}
    if requiredFeatures is None:
        requiredFeatures = generatedFeatures
    generatedFeatures.update(requiredFeatures)

    peaks = toPeaks(data, generatedFeatures['cols'])

    features = dict()

    for f in generatedFeatures['features']:
        features.update(applyFun(peaks, posFeatures()[f], f))

    return features


if __name__ == '__main__':
    import dataTransform.accproc as ac
    import dataTransform.Preprocessing as pp
    for i in range(9):
        nb = int(i + 1)
        if nb == 4:
            data = ac.readGCDCFormat("..\..\Runs\Tina\enkel\DATA-00"
                                     + `nb` + ".csv")
            data = ac.preprocessGCDC(data)
            filtered = pp.filterRun3(data, False)

            print(getSimplePeakFeatures(data))