average3.py 文件源码

def translate_group(self, signalimg, group, translateaxis):
        n_channels = len(self.locs)
        all_xcorr = np.zeros((1, n_channels))
        all_da = np.zeros((1, n_channels))

        if translateaxis == 'x':
            proplane = 'xy'
        elif translateaxis == 'y':
            proplane = 'xy'
        elif translateaxis == 'z':
            proplane = 'xz'

        plotmode = 0

        for j in range(n_channels):
            if plotmode:
                fig = plt.figure()
                ax1 = fig.add_subplot(1, 3, 1)
                plt.plot(signalimg[j])
                ax2 = fig.add_subplot(1, 3, 2)

            if self.dataset_dialog.checks[j].isChecked():
                index = self.group_index[j][group].nonzero()[1]
                x_rot = self.locs[j].x[index]
                y_rot = self.locs[j].y[index]
                z_rot = self.locs[j].z[index]

                xcorr_max = 0.0
                plane = self.render_planes(x_rot, y_rot, z_rot, proplane, self.pixelsize) #
                if translateaxis == 'x':
                    projection = np.sum(plane, axis=0)
                elif translateaxis == 'y':
                    projection = np.sum(plane, axis=1)
                elif translateaxis == 'z':
                    projection = np.sum(plane, axis=1)

                if plotmode:
                    plt.plot(projection)
                #print('Step X')
                #ax3 = fig.add_subplot(1,3,3)
                #plt.imshow(plane, interpolation='nearest', cmap=plt.cm.ocean)
                corrval = np.max(signal.correlate(signalimg[j],projection))
                shiftval = np.argmax(signal.correlate(signalimg[j], projection))-len(signalimg[j])+1
                all_xcorr[0,j] = corrval
                all_da[0,j] = shiftval/self.oversampling

            if plotmode:
                plt.show()

        #value with biggest cc value form table
        maximumcc = np.argmax(np.sum(all_xcorr,axis = 1))
        dafinal = np.mean(all_da[maximumcc,:])
        for j in range(n_channels):
            index = self.group_index[j][group].nonzero()[1]
            if translateaxis == 'x':
                self.locs[j].x[index] += dafinal
            elif translateaxis == 'y':
                self.locs[j].y[index] += dafinal
            elif translateaxis == 'z':
                self.locs[j].z[index] += dafinal*self.pixelsize