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EMAN::TestImageGaussian Class Reference

Replace a source image as a Gaussian Blob. More...

#include <processor.h>

Inheritance diagram for EMAN::TestImageGaussian:

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Collaboration diagram for EMAN::TestImageGaussian:

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List of all members.

Public Member Functions

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

Static Public Member Functions

ProcessorNEW ()

Static Public Attributes

const string NAME = "testimage.gaussian"

Detailed Description

Replace a source image as a Gaussian Blob.

Parameters:
sigma sigma value for this Gaussian blob
axis specify a major axis for asymmetric features
c distance between focus and the center of an ellipse

Definition at line 5997 of file processor.h.


Member Function Documentation

virtual string EMAN::TestImageGaussian::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 6007 of file processor.h.

06008                 {
06009                         return "Replace a source image as a Gaussian Blob";
06010                 }

virtual string EMAN::TestImageGaussian::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 6002 of file processor.h.

06003                 {
06004                         return NAME;
06005                 }

virtual TypeDict EMAN::TestImageGaussian::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 6017 of file processor.h.

References EMAN::TypeDict::put().

06018                 {
06019                         TypeDict d;
06020                         d.put("sigma", EMObject::FLOAT, "sigma value for this Gaussian blob");
06021                         d.put("axis", EMObject::STRING, "specify a major axis for asymmetric features");
06022                         d.put("c", EMObject::FLOAT, "distance between focus and the center of an ellipse");
06023                         return d;
06024                 }

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

Definition at line 6012 of file processor.h.

06013                 {
06014                         return new TestImageGaussian();
06015                 }

void TestImageGaussian::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 6992 of file processor.cpp.

References EMAN::EMData::get_data(), InvalidValueException, nx, ny, EMAN::TestImageProcessor::preprocess(), sqrt(), and EMAN::EMData::update().

06993 {
06994         preprocess(image);
06995 
06996         float sigma = params["sigma"];
06997         string axis = (const char*)params["axis"];
06998         float c = params["c"];
06999 
07000         float *dat = image->get_data();
07001         float r; //this is the distance of pixel from the image center(nx/2, ny/2, nz/2)
07002         float x2, y2, z2; //this is the coordinates of this pixel from image center
07003         for (int k = 0; k < nz; ++k) {
07004                 for (int j = 0; j < ny; ++j) {
07005                         for (int i = 0; i < nx; ++i, ++dat) {
07006                                 x2 = (float)( i - nx/2 );
07007                                 y2 = (float)( j - ny/2 );
07008                                 z2 = (float)( k - nz/2 );
07009 
07010                                 if(axis==""){
07011                                         r = (float)sqrt(x2*x2+y2*y2+z2*z2);
07012                                 }
07013                                 else if(axis == "x"){
07014                                         float lc = -c;
07015                                         float rc = c;
07016                                         r = ( (float)sqrt((x2-lc)*(x2-lc)+y2*y2+z2*z2) +
07017                                                   (float)sqrt((x2-rc)*(x2-rc)+y2*y2+z2*z2) ) /2.0f - c;
07018                                 }
07019                                 else if(axis == "y"){
07020                                         float lc = -c;
07021                                         float rc = c;
07022                                         r = ( (float)sqrt(x2*x2+(y2-lc)*(y2-lc)+z2*z2) +
07023                                                   (float)sqrt(x2*x2+(y2-rc)*(y2-rc)+z2*z2) ) /2.0f - c;
07024                                 }
07025                                 else if(axis == "z"){
07026                                         if( nz == 1 ){
07027                                                 throw InvalidValueException(0, "This is a 2D image, no asymmetric feature for z axis");
07028                                         }
07029                                         float lc = -c;
07030                                         float rc = c;
07031                                         r = ( (float)sqrt(x2*x2+y2*y2+(z2-lc)*(z2-lc)) +
07032                                                   (float)sqrt(x2*x2+y2*y2+(z2-rc)*(z2-rc)) ) /2.0f - c;
07033                                 }
07034                                 else{
07035                                         throw InvalidValueException(0, "please specify a valid axis for asymmetric features");
07036                                 }
07037                                 //the amplitude of the pixel is proportional to the distance of this pixel from the center
07038                                 *dat = (float)gsl_ran_gaussian_pdf((double)r,(double)sigma);
07039                         }
07040                 }
07041         }
07042 
07043         image->update();
07044 }


Member Data Documentation

const string TestImageGaussian::NAME = "testimage.gaussian" [static]
 

Definition at line 196 of file processor.cpp.


The documentation for this class was generated from the following files:
Generated on Thu Mar 10 23:00:58 2011 for EMAN2 by  doxygen 1.3.9.1