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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 6091 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 6101 of file processor.h.

06102                 {
06103                         return "Replace a source image as a Gaussian Blob";
06104                 }

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 6096 of file processor.h.

06097                 {
06098                         return NAME;
06099                 }

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 6111 of file processor.h.

References EMAN::TypeDict::put().

06112                 {
06113                         TypeDict d;
06114                         d.put("sigma", EMObject::FLOAT, "sigma value for this Gaussian blob");
06115                         d.put("axis", EMObject::STRING, "specify a major axis for asymmetric features");
06116                         d.put("c", EMObject::FLOAT, "distance between focus and the center of an ellipse");
06117                         return d;
06118                 }

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

Definition at line 6106 of file processor.h.

06107                 {
06108                         return new TestImageGaussian();
06109                 }

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 7022 of file processor.cpp.

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

07023 {
07024         preprocess(image);
07025 
07026         float sigma = params["sigma"];
07027         string axis = (const char*)params["axis"];
07028         float c = params["c"];
07029 
07030         float *dat = image->get_data();
07031         float r; //this is the distance of pixel from the image center(nx/2, ny/2, nz/2)
07032         float x2, y2, z2; //this is the coordinates of this pixel from image center
07033         for (int k = 0; k < nz; ++k) {
07034                 for (int j = 0; j < ny; ++j) {
07035                         for (int i = 0; i < nx; ++i, ++dat) {
07036                                 x2 = (float)( i - nx/2 );
07037                                 y2 = (float)( j - ny/2 );
07038                                 z2 = (float)( k - nz/2 );
07039 
07040                                 if(axis==""){
07041                                         r = (float)sqrt(x2*x2+y2*y2+z2*z2);
07042                                 }
07043                                 else if(axis == "x"){
07044                                         float lc = -c;
07045                                         float rc = c;
07046                                         r = ( (float)sqrt((x2-lc)*(x2-lc)+y2*y2+z2*z2) +
07047                                                   (float)sqrt((x2-rc)*(x2-rc)+y2*y2+z2*z2) ) /2.0f - c;
07048                                 }
07049                                 else if(axis == "y"){
07050                                         float lc = -c;
07051                                         float rc = c;
07052                                         r = ( (float)sqrt(x2*x2+(y2-lc)*(y2-lc)+z2*z2) +
07053                                                   (float)sqrt(x2*x2+(y2-rc)*(y2-rc)+z2*z2) ) /2.0f - c;
07054                                 }
07055                                 else if(axis == "z"){
07056                                         if( nz == 1 ){
07057                                                 throw InvalidValueException(0, "This is a 2D image, no asymmetric feature for z axis");
07058                                         }
07059                                         float lc = -c;
07060                                         float rc = c;
07061                                         r = ( (float)sqrt(x2*x2+y2*y2+(z2-lc)*(z2-lc)) +
07062                                                   (float)sqrt(x2*x2+y2*y2+(z2-rc)*(z2-rc)) ) /2.0f - c;
07063                                 }
07064                                 else{
07065                                         throw InvalidValueException(0, "please specify a valid axis for asymmetric features");
07066                                 }
07067                                 //the amplitude of the pixel is proportional to the distance of this pixel from the center
07068                                 *dat = (float)gsl_ran_gaussian_pdf((double)r,(double)sigma);
07069                         }
07070                 }
07071         }
07072 
07073         image->update();
07074 }


Member Data Documentation

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

Definition at line 203 of file processor.cpp.


The documentation for this class was generated from the following files:
Generated on Tue Jul 12 13:51:29 2011 for EMAN2 by  doxygen 1.3.9.1