use least square method to normalize More...

#include <processor.h>

Inheritance diagram for EMAN::NormalizeToLeastSquareProcessor:

Collaboration diagram for EMAN::NormalizeToLeastSquareProcessor:

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Public Member Functions
void	process_inplace (EMData *image)
	To process an image in-place. More...

string	get_name () const
	Get the processor's name. More...

TypeDict	get_param_types () const
	Get processor parameter information in a dictionary. More...

string	get_desc () const
	Get the descrition of this specific processor. More...

Public Member Functions inherited from EMAN::Processor
virtual	~Processor ()

virtual EMData *	process (const EMData *const image)
	To proccess an image out-of-place. More...

virtual void	process_list_inplace (vector< EMData * > &images)
	To process multiple images using the same algorithm. More...

virtual Dict	get_params () const
	Get the processor parameters in a key/value dictionary. More...

virtual void	set_params (const Dict &new_params)
	Set the processor parameters using a key/value dictionary. More...

Static Public Member Functions
static Processor *	NEW ()

Static Public Member Functions inherited from EMAN::Processor
static string	get_group_desc ()
	Get the description of this group of processors. More...

static void	EMFourierFilterInPlace (EMData *fimage, Dict params)
	Compute a Fourier-filter processed image in place. More...

static EMData *	EMFourierFilter (EMData *fimage, Dict params)
	Compute a Fourier-processor processed image without altering the original image. More...

Static Public Attributes
static const string	NAME = "normalize.toimage"

Additional Inherited Members
Public Types inherited from EMAN::Processor
enum	fourier_filter_types { TOP_HAT_LOW_PASS , TOP_HAT_HIGH_PASS , TOP_HAT_BAND_PASS , TOP_HOMOMORPHIC , GAUSS_LOW_PASS , GAUSS_HIGH_PASS , GAUSS_BAND_PASS , GAUSS_INVERSE , GAUSS_HOMOMORPHIC , BUTTERWORTH_LOW_PASS , BUTTERWORTH_HIGH_PASS , BUTTERWORTH_HOMOMORPHIC , KAISER_I0 , KAISER_SINH , KAISER_I0_INVERSE , KAISER_SINH_INVERSE , SHIFT , TANH_LOW_PASS , TANH_HIGH_PASS , TANH_HOMOMORPHIC , TANH_BAND_PASS , RADIAL_TABLE , CTF_ }
	Fourier filter Processor type enum. More...

Protected Attributes inherited from EMAN::Processor
Dict	params

Detailed Description

use least square method to normalize

Parameters

to	reference image normalize to
low_threshold	only take into account the reference image's pixel value between high and low threshold (zero is ignored)
high_threshold	only take into account the reference image's pixel value between high and low threshold (zero is ignored)

Definition at line 6262 of file processor.h.

Member Function Documentation

◆ get_desc()

string EMAN::NormalizeToLeastSquareProcessor::get_desc ( ) const

inlinevirtual

Get the descrition of this specific processor.

This function must be overwritten by a subclass.

Returns: The description of this processor.

Implements EMAN::Processor.

Definition at line 6290 of file processor.h.

                {
                        return "This will use a pixel vs pixel least squares fit to normalize one image to optimally match a second image, with various options for excluding some pixels. norm_mult and norm_add will be set in the header of the result.";
                }

◆ get_name()

string EMAN::NormalizeToLeastSquareProcessor::get_name ( ) const

inlinevirtual

Get the processor's name.

Each processor is identified by a unique name.

Returns: The processor's name.

Implements EMAN::Processor.

Definition at line 6267 of file processor.h.

                {
                        return NAME;
                }

References NAME.

◆ get_param_types()

TypeDict EMAN::NormalizeToLeastSquareProcessor::get_param_types ( ) const

inlinevirtual

Get processor parameter information in a dictionary.

Each parameter has one record in the dictionary. Each record contains its name, data-type, and description.

Returns: A dictionary containing the parameter info.

Reimplemented from EMAN::Processor.

Definition at line 6277 of file processor.h.

                {
                        TypeDict d;
                        d.put("to", EMObject::EMDATA, "reference image normalize to");
                        d.put("fourieramp", EMObject::INT, "If set, performs normalization using Fourier amplitudes instead of real-space image. Default = False.");
                        d.put("ignore_zero", EMObject::BOOL, "If set, ignores any pixels which are exactly zero in either image. Defaut = True.");
                        d.put("ignore_lowsig", EMObject::FLOAT, "If >0, then any pixels closer to the mean than val*sigma in either image excluded");
                        d.put("low_threshold", EMObject::FLOAT, "only take into account the reference image's pixel value between high and low threshold (zero is always ignored)");
                        d.put("high_threshold", EMObject::FLOAT, "only take into account the reference image's pixel value between high and low threshold (zero is always ignored)");
                        d.put("debug", EMObject::BOOL, "This is a debugging flag which will cause various diagnostic files to be written.");
                        return d;
                }

References EMAN::EMObject::BOOL, EMAN::EMObject::EMDATA, EMAN::EMObject::FLOAT, EMAN::EMObject::INT, and EMAN::TypeDict::put().

◆ NEW()

static Processor * EMAN::NormalizeToLeastSquareProcessor::NEW ( )

inlinestatic

Definition at line 6272 of file processor.h.

                {
                        return new NormalizeToLeastSquareProcessor();
                }

◆ process_inplace()

void NormalizeToLeastSquareProcessor::process_inplace ( EMData * image )

virtual

To process an image in-place.

For those processors which can only be processed out-of-place, override this function to just print out some error message to remind user call the out-of-place version.

Parameters

image The image to be processed.

Implements EMAN::Processor.

Definition at line 5203 of file processor.cpp.

{
        if (!image) {
                LOGWARN("NULL Image");
                return;
        }
 
        EMData *to = params["to"];
 
        bool ignore_zero = params.set_default("ignore_zero",true);
        bool fourieramp = params.set_default("fourieramp",false);
        bool debug = params.set_default("debug",false);
        float ignore_lowsig = params.set_default("ignore_lowsig",-1.0);
        float low_threshold = params.set_default("low_threshold",-FLT_MAX);
        float high_threshold = params.set_default("high_threshold",FLT_MAX);
 
        int nx = image->get_xsize();
        int ny = image->get_ysize();
        int nz = image->get_zsize();
        size_t size = (size_t)nx * ny * nz;
        size_t size2 = 0;
        
        EMData *fim = NULL;
        EMData *fto = NULL;
        float *dimage;          // unthresholded image data
        float *dto;
        int step=1;                     // used in Fourier mode
        
        float meani=(float)image->get_attr("mean");
        float meant=(float)to->get_attr("mean");
        float sigi=(float)image->get_attr("sigma")*ignore_lowsig;
        float sigt=(float)to->get_attr("sigma")*ignore_lowsig;
        
        if (fourieramp) {
                fim=image->do_fft();
                fto=to->do_fft();
                fim->ri2ap();
                fto->ri2ap();
                dimage=fim->get_data();
                dto=fto->get_data();
                step=2;
                size2=(size_t)(nx+2) * ny * nz;
                
                // sigma for thresholding
                meani=meant=0;                                          // Fourier amplitude >=0, so we reference everything to this point
                sigi=sigt=0;
                for (size_t i=0; i<size2; i+=2) { sigi+=pow(dimage[i],2.0f); sigt+=pow(dto[i],2.0f); }
                sigi=ignore_lowsig*sqrt(sigi/(size2/2));
                sigt=ignore_lowsig*sqrt(sigt/(size2/2));
        } 
        else {
                dimage = image->get_data();
                dto = to->get_data();
                size2=size;
        }
        
 
        // rewrote this to just use GSL and get rid of David's old code.
        // The two passes are just to make sure we don't eat too much RAM if we do 3D
        if (ignore_lowsig<0) ignore_lowsig=0;
 
        size_t count=0;
        for (size_t i = 0; i < size2; i+=step) {
                if (dto[i] >= low_threshold && dto[i] <= high_threshold
                        && (dto[i]>=meant+sigt || dto[i]<=meant-sigt)
                        && (dimage[i]>=meani+sigi || dimage[i]<=meani-sigi)
                        && (!ignore_zero ||(dto[i] != 0.0f && dimage[i] != 0.0f))) {
                        count++;
                }
        }
 
 
        double *x=(double *)malloc(count*sizeof(double));
        double *y=(double *)malloc(count*sizeof(double));
        count=0;
        for (size_t i = 0; i < size2; i+=step) {
                if (dto[i] >= low_threshold && dto[i] <= high_threshold
                        && (dto[i]>=meant+sigt || dto[i]<=meant-sigt)
                        && (dimage[i]>=meani+sigi || dimage[i]<=meani-sigi)
                        && (!ignore_zero ||(dto[i] != 0.0f && dimage[i] != 0.0f))) {
                        x[count]=dimage[i];
                        y[count]=dto[i];
                        count++;
                }
        }
        double c0,c1;
        double cov00,cov01,cov11,sumsq;
        gsl_fit_linear (x, 1, y, 1, count, &c0, &c1, &cov00, &cov01, &cov11, &sumsq);
 
        if (debug) {
                FILE*out=fopen("debug.txt","w");
                for (size_t i = 0; i < count; i++) {
                        fprintf(out,"%lf\t%lf\n",x[i],y[i]);
                }
                fclose(out);
                printf("add %lf\tmul %lf\t%lf\t%lf\t%lf\t%lf\n",c0,c1,cov00,cov01,cov11,sumsq);
        }
 
        free(x);
        free(y);
        if (fim!=NULL) delete fim;
        if (fto!=NULL) delete fto;
 
        if (fourieramp) c0=0;   // c0 makes no sense in this context. Really just a measure of noise
        dimage = image->get_data();
        for (size_t i = 0; i < size; ++i) dimage[i]=dimage[i]*c1+c0;
        image->update();
        image->set_attr("norm_mult",c1);
        image->set_attr("norm_add",c0);
}

References LOGWARN, EMAN::Processor::params, EMAN::Dict::set_default(), sqrt(), x, and y.

Member Data Documentation

◆ NAME

const string NormalizeToLeastSquareProcessor::NAME = "normalize.toimage"

static

Definition at line 6295 of file processor.h.

Referenced by get_name().

The documentation for this class was generated from the following files:

Public Member Functions

Static Public Member Functions

Static Public Attributes

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ get_desc()

◆ get_name()

◆ get_param_types()

◆ NEW()

◆ process_inplace()

Member Data Documentation

◆ NAME