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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 704 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 730 of file processor.h.

00731                 {
00732                         return "Segments a volume into pieces separated by distances in the specified range.";
00733                 }

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 707 of file processor.h.

00708                 {
00709                         return NAME;
00710                 }

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 715 of file processor.h.

References EMAN::TypeDict::put().

00716                 {
00717                         TypeDict d ;
00718                         d.put("thr",EMObject::FLOAT,"Optional : Isosurface threshold value. Pixels below this will not be segment centers (default = 0.9)");
00719                         d.put("minsegsep",EMObject::FLOAT,"Required: Minimum segment separation in pixels. Segments too close will trigger a reseed");
00720                         d.put("maxsegsep",EMObject::FLOAT,"Required: Maximum segment separation in pixels. Segments too close will trigger a reseed");
00721                         d.put("verbose",EMObject::INT,"Be verbose while running");
00722                         return d;
00723                 }

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

Definition at line 725 of file processor.h.

00726                 {
00727                         return new DistanceSegmentProcessor();
00728                 }

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 790 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.

00791 {
00792         EMData * result = image->copy();
00793 
00794         float thr = params.set_default("thr",0.9f);
00795         float minsegsep = params.set_default("minsegsep",5.0f);
00796         float maxsegsep = params.set_default("maxsegsep",5.1f);
00797         int verbose = params.set_default("verbose",0);
00798 
00799         vector<Pixel> pixels=image->calc_highest_locations(thr);
00800 
00801         vector<float> centers(3);       // only 1 to start
00802         int nx=image->get_xsize();
00803         int ny=image->get_ysize();
00804         int nz=image->get_zsize();
00805 //      int nxy=nx*ny;
00806 
00807         // seed the process with the highest valued point
00808         centers[0]=(float)pixels[0].x;
00809         centers[1]=(float)pixels[0].y;
00810         centers[2]=(float)pixels[0].z;
00811         pixels.erase(pixels.begin());
00812 
00813         // outer loop. We add one center per iteration
00814         // This is NOT a very efficient algorithm, it assumes points are fairly sparse
00815         while (pixels.size()>0) {
00816                 // iterate over pixels until we find a new center (then stop), delete any 'bad' pixels
00817                 // no iterators because we remove elements
00818 
00819                 for (unsigned int i=0; i<pixels.size(); i++) {
00820 
00821                         Pixel p=pixels[i];
00822                         // iterate over existing centers to see if this pixel should be removed ... technically we only should need to check the last center
00823                         for (unsigned int j=0; j<centers.size(); j+=3) {
00824                                 float d=Util::hypot3(centers[j]-p.x,centers[j+1]-p.y,centers[j+2]-p.z);
00825                                 if (d<minsegsep) {              // conflicts with existing center, erase
00826                                         pixels.erase(pixels.begin()+i);
00827                                         i--;
00828                                         break;
00829                                 }
00830                         }
00831                 }
00832 
00833                 int found=0;
00834                 for (unsigned int i=0; i<pixels.size() && found==0; i++) {
00835                         Pixel p=pixels[i];
00836 
00837                         // iterate again to see if this may be a new valid center. Start at the end so we tend to build chains
00838                         for (unsigned int j=centers.size()-3; j>0; j-=3) {
00839                                 float d=Util::hypot3(centers[j]-p.x,centers[j+1]-p.y,centers[j+2]-p.z);
00840                                 if (d<maxsegsep) {              // we passed minsegsep question already, so we know we're in the 'good' range
00841                                         centers.push_back((float)p.x);
00842                                         centers.push_back((float)p.y);
00843                                         centers.push_back((float)p.z);
00844                                         pixels.erase(pixels.begin()+i); // in the centers list now, don't need it any more
00845                                         found=1;
00846                                         break;
00847                                 }
00848                         }
00849                 }
00850 
00851                 // If we went through the whole list and didn't find one, we need to reseed again
00852                 if (!found && pixels.size()) {
00853                         if (verbose) printf("New chain\n");
00854                         centers.push_back((float)pixels[0].x);
00855                         centers.push_back((float)pixels[0].y);
00856                         centers.push_back((float)pixels[0].z);
00857                         pixels.erase(pixels.begin());
00858                 }
00859 
00860                 if (verbose) printf("%d points found\n",(int)(centers.size()/3));
00861         }
00862 
00863         // after we have our list of centers classify pixels
00864         for (int z=0; z<nz; z++) {
00865                 for (int y=0; y<ny; y++) {
00866                         for (int x=0; x<nz; x++) {
00867                                 if (image->get_value_at(x,y,z)<thr) {
00868                                         result->set_value_at(x,y,z,-1.0);               //below threshold -> -1 (unclassified)
00869                                         continue;
00870                                 }
00871                                 int bcls=-1;                    // best matching class
00872                                 float bdist=(float)(nx+ny+nz);  // distance for best class
00873                                 for (unsigned int c=0; c<centers.size()/3; c++) {
00874                                         float d=Util::hypot3(x-centers[c*3],y-centers[c*3+1],z-centers[c*3+2]);
00875                                         if (d<bdist) { bdist=d; bcls=c; }
00876                                 }
00877                                 result->set_value_at(x,y,z,(float)bcls);                // set the pixel to the class number
00878                         }
00879                 }
00880         }
00881 
00882         result->set_attr("segment_centers",centers);
00883 
00884         return result;
00885 }

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 783 of file processor.cpp.

00784 {
00785         printf("Process inplace not implemented. Please use process.\n");
00786         return;
00787 }


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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