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EMAN::DistanceSegmentProcessor Class Reference

Segment a volume about:homeinto subvolumes based on a center separation value. More...

#include <processor.h>

Inheritance diagram for EMAN::DistanceSegmentProcessor:

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Collaboration diagram for EMAN::DistanceSegmentProcessor:

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List of all members.

Public Member Functions

string get_name () const
 Get the processor's name.
virtual EMDataprocess (const EMData *const image)
 To proccess an image out-of-place.
void process_inplace (EMData *image)
 To process an image in-place.
TypeDict get_param_types () const
 Get processor parameter information in a dictionary.
string get_desc () const
 Get the descrition of this specific processor.

Static Public Member Functions

ProcessorNEW ()

Static Public Attributes

const string NAME = "segment.distance"

Detailed Description

Segment a volume about:homeinto subvolumes based on a center separation value.

For linear densities such as skeletons this should fill linear regions with uniformly separated points

Author:
Steve Ludtke
Date:
2010/07/14

Definition at line 679 of file processor.h.


Member Function Documentation

string EMAN::DistanceSegmentProcessor::get_desc  )  const [inline, virtual]
 

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 705 of file processor.h.

00706                 {
00707                         return "Segments a volume into pieces separated by distances in the specified range.";
00708                 }

string EMAN::DistanceSegmentProcessor::get_name  )  const [inline, virtual]
 

Get the processor's name.

Each processor is identified by a unique name.

Returns:
The processor's name.

Implements EMAN::Processor.

Definition at line 682 of file processor.h.

00683                 {
00684                         return NAME;
00685                 }

TypeDict EMAN::DistanceSegmentProcessor::get_param_types  )  const [inline, virtual]
 

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 690 of file processor.h.

References EMAN::TypeDict::put().

00691                 {
00692                         TypeDict d ;
00693                         d.put("thr",EMObject::FLOAT,"Optional : Isosurface threshold value. Pixels below this will not be segment centers (default = 0.9)");
00694                         d.put("minsegsep",EMObject::FLOAT,"Required: Minimum segment separation in pixels. Segments too close will trigger a reseed");
00695                         d.put("maxsegsep",EMObject::FLOAT,"Required: Maximum segment separation in pixels. Segments too close will trigger a reseed");
00696                         d.put("verbose",EMObject::INT,"Be verbose while running");
00697                         return d;
00698                 }

Processor* EMAN::DistanceSegmentProcessor::NEW  )  [inline, static]
 

Definition at line 700 of file processor.h.

00701                 {
00702                         return new DistanceSegmentProcessor();
00703                 }

EMData * DistanceSegmentProcessor::process const EMData *const   image  )  [virtual]
 

To proccess an image out-of-place.

For those processors which can only be processed out-of-place, override this function to give the right behavior.

Parameters:
image The image will be copied, actual process happen on copy of image.
Returns:
the image processing result, may or may not be the same size of the input image

Reimplemented from EMAN::Processor.

Definition at line 784 of file processor.cpp.

References EMAN::EMData::calc_highest_locations(), EMAN::EMData::copy(), EMAN::EMData::get_value_at(), EMAN::EMData::get_xsize(), EMAN::EMData::get_ysize(), EMAN::EMData::get_zsize(), EMAN::Util::hypot3(), nx, ny, EMAN::EMData::set_attr(), EMAN::Dict::set_default(), EMAN::EMData::set_value_at(), x, EMAN::Pixel::x, y, EMAN::Pixel::y, and EMAN::Pixel::z.

00785 {
00786         EMData * result = image->copy();
00787 
00788         float thr = params.set_default("thr",0.9f);
00789         float minsegsep = params.set_default("minsegsep",5.0f);
00790         float maxsegsep = params.set_default("maxsegsep",5.1f);
00791         int verbose = params.set_default("verbose",0);
00792 
00793         vector<Pixel> pixels=image->calc_highest_locations(thr);
00794 
00795         vector<float> centers(3);       // only 1 to start
00796         int nx=image->get_xsize();
00797         int ny=image->get_ysize();
00798         int nz=image->get_zsize();
00799 //      int nxy=nx*ny;
00800 
00801         // seed the process with the highest valued point
00802         centers[0]=(float)pixels[0].x;
00803         centers[1]=(float)pixels[0].y;
00804         centers[2]=(float)pixels[0].z;
00805         pixels.erase(pixels.begin());
00806 
00807         // outer loop. We add one center per iteration
00808         // This is NOT a very efficient algorithm, it assumes points are fairly sparse
00809         while (pixels.size()>0) {
00810                 // iterate over pixels until we find a new center (then stop), delete any 'bad' pixels
00811                 // no iterators because we remove elements
00812 
00813                 for (unsigned int i=0; i<pixels.size(); i++) {
00814 
00815                         Pixel p=pixels[i];
00816                         // iterate over existing centers to see if this pixel should be removed ... technically we only should need to check the last center
00817                         for (unsigned int j=0; j<centers.size(); j+=3) {
00818                                 float d=Util::hypot3(centers[j]-p.x,centers[j+1]-p.y,centers[j+2]-p.z);
00819                                 if (d<minsegsep) {              // conflicts with existing center, erase
00820                                         pixels.erase(pixels.begin()+i);
00821                                         i--;
00822                                         break;
00823                                 }
00824                         }
00825                 }
00826 
00827                 int found=0;
00828                 for (unsigned int i=0; i<pixels.size() && found==0; i++) {
00829                         Pixel p=pixels[i];
00830 
00831                         // iterate again to see if this may be a new valid center. Start at the end so we tend to build chains
00832                         for (unsigned int j=centers.size()-3; j>0; j-=3) {
00833                                 float d=Util::hypot3(centers[j]-p.x,centers[j+1]-p.y,centers[j+2]-p.z);
00834                                 if (d<maxsegsep) {              // we passed minsegsep question already, so we know we're in the 'good' range
00835                                         centers.push_back((float)p.x);
00836                                         centers.push_back((float)p.y);
00837                                         centers.push_back((float)p.z);
00838                                         pixels.erase(pixels.begin()+i); // in the centers list now, don't need it any more
00839                                         found=1;
00840                                         break;
00841                                 }
00842                         }
00843                 }
00844 
00845                 // If we went through the whole list and didn't find one, we need to reseed again
00846                 if (!found && pixels.size()) {
00847                         if (verbose) printf("New chain\n");
00848                         centers.push_back((float)pixels[0].x);
00849                         centers.push_back((float)pixels[0].y);
00850                         centers.push_back((float)pixels[0].z);
00851                         pixels.erase(pixels.begin());
00852                 }
00853 
00854                 if (verbose) printf("%d points found\n",(int)(centers.size()/3));
00855         }
00856 
00857         // after we have our list of centers classify pixels
00858         for (int z=0; z<nz; z++) {
00859                 for (int y=0; y<ny; y++) {
00860                         for (int x=0; x<nz; x++) {
00861                                 if (image->get_value_at(x,y,z)<thr) {
00862                                         result->set_value_at(x,y,z,-1.0);               //below threshold -> -1 (unclassified)
00863                                         continue;
00864                                 }
00865                                 int bcls=-1;                    // best matching class
00866                                 float bdist=(float)(nx+ny+nz);  // distance for best class
00867                                 for (unsigned int c=0; c<centers.size()/3; c++) {
00868                                         float d=Util::hypot3(x-centers[c*3],y-centers[c*3+1],z-centers[c*3+2]);
00869                                         if (d<bdist) { bdist=d; bcls=c; }
00870                                 }
00871                                 result->set_value_at(x,y,z,(float)bcls);                // set the pixel to the class number
00872                         }
00873                 }
00874         }
00875 
00876         result->set_attr("segment_centers",centers);
00877 
00878         return result;
00879 }

void DistanceSegmentProcessor::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 777 of file processor.cpp.

00778 {
00779         printf("Process inplace not implemented. Please use process.\n");
00780         return;
00781 }


Member Data Documentation

const string DistanceSegmentProcessor::NAME = "segment.distance" [static]
 

Definition at line 78 of file processor.cpp.


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