getAccEff.py 文件源码

def filter(self):
        path = os.getcwd()+'/trialGraspEventDetection_dataFiles'
        self.Fgr = np.sum(self.values[:, 9:15], axis=1)  # SAI
        self.Fgl = np.sum(self.values[:, 0:7], axis=1)  # SAI

        # can use this to plot in matlab graspeventdetection_plot.m
        np.savetxt(path+'/SAI_Fgr.txt', self.Fgr)
        # can use this to plot in matlab
        np.savetxt(path+'/SAI_Fgl.txt', self.Fgl)

        # 0.55*pi rad/samples
        b1, a1 = signal.butter(1, 0.55, 'high', analog=False)
        self.f_acc_x = signal.lfilter(b1, a1, self.acc_x, axis=-1, zi=None)
        self.f_acc_y = signal.lfilter(b1, a1, self.acc_y, axis=-1, zi=None)
        self.f_acc_z = signal.lfilter(b1, a1, self.acc_z, axis=-1, zi=None)
        # self.f_eff = signal.lfilter(b1, a1, self.eff, axis=-1, zi=None)
        # type(eff)
        self.FAII = np.sqrt(np.square(self.f_acc_x) +
                            np.square(self.f_acc_y) +
                            np.square(self.f_acc_z))
        # can use this to plot in matlab
        np.savetxt(path+'/FAII.txt', self.FAII)

        # subtract base values from the values array
        self.values1 = self.values - self.values.min(axis=0)
        # pass the filter for each sensor
        self.fvalues1 = np.zeros(self.values1.shape)
        # 0.48*pi rad/samples
        b, a = signal.butter(1, 0.48, 'high', analog=False)
        for i in range(16):
            self.fvalues1[:, i] = signal.lfilter(b, a, self.values1[:, i],
                                                 axis=-1, zi=None)
        self.FAI = np.sum(self.fvalues1, axis=1)
        # can use this to plot in matlab
        np.savetxt(path+'/FAI.txt', self.FAI)