pieern.py 文件源码

def trainClassifier(self):
        if self.trainCap is None:
            raise Exception('No data available for training.')

        dialog = wx.ProgressDialog('Training Classifier',
                    'Featurizing', maximum=self.nFold+1,
                    style=wx.PD_ELAPSED_TIME | wx.PD_SMOOTH)

        segmented = self.trainCap.segment(start=0.0, end=self.trialSecs)
        segs = [segmented.select(matchFunc=lambda mark: self.markToStim(mark) == choice)
                for choice in self.choices]

        assert segs[0].getNSeg() == self.nTrainTrial

        ##print 'nSegs:'
        ##for sg in segs:
        ##    print sg.getNSeg(), sg.data.shape

        freqs, trainData = self.powerize(segs)

        self.plotPanel.plotFeatures(trainData, freqs, self.choices,
                                    self.trainCap.getChanNames())

        ##print trainData[0].mean(axis=0)
        ##print trainData[0].mean(axis=0).shape
        ##print trainData[1].mean(axis=0)
        ##print trainData[1].mean(axis=0).shape

        if self.classifierKind == 'lda':
            self.trainLDA(trainData, dialog)
        elif self.classifierKind == 'nn':
            self.trainNN(trainData, dialog)
        else:
            raise Exception('Invalid classifier kind: %s.' % str(self.classifierKind))

        self.plotPanel.showPieMenu()