RangeImage.py 文件源码

def populateMissingData(self,approach="Smooth",ilog=None):
        '''
        This function is used to interpolate missing data in the image.
        '''
        if approach == 'Smooth':
            # first run a median filter over the array, then smooth the result.
            #xmin,xmax,ymin,ymax,zmin,zmax = self.getRange()
            mask = np.array(self.flags,dtype=np.bool)

            z = self.getZImage().asMatrix2D()
            median = nd.median_filter(z,size=(15,15))

            mask = mask.flatten()
            z = z.flatten()
            median = median.flatten()

            z[ mask==False ] = median[ mask==False ]

            if ilog != None:
                ilog.log(pv.Image(median.reshape(self.width,self.height)),label="Median")
                ilog.log(pv.Image(z.reshape(self.width,self.height)),label="ZMedian")

            mask = mask.flatten()
            z = z.flatten()
            median = median.flatten()

            for i in range(5):
                tmp = z.copy()
                smooth = nd.gaussian_filter(z.reshape(self.width,self.height),2.0).flatten()
                z[ mask==False ] = smooth[ mask==False ]
                print "Iteration:",i,(z-tmp).max(),(z-tmp).min()
                ilog.log(pv.Image(z.reshape(self.width,self.height)),label="ZSmooth%02d"%i)
                ilog.log(pv.Image((z-tmp).reshape(self.width,self.height)),label="ZSmooth%02d"%i)


        if approach == 'RBF':
            mask = np.array(self.flags,dtype=np.bool)
            mask = mask.flatten()

            x = np.arange(self.width).reshape(self.width,1)
            x = x*np.ones((1,self.height))
            x = x.flatten()

            y = np.arange(self.height).reshape(1,self.height)
            y = y*np.ones((self.width,1))
            y = y.flatten()

            z = self.z.copy()
            z = z.flatten()

            print "Coords:"
            print len(mask)
            print len(x[mask])
            print len(y[mask])
            print len(z[mask])

            # this produces an error.  Probably has too much data
            it.Rbf(x[mask],y[mask],z[mask])
            pass