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EMAN::TomoTiltEdgeMaskProcessor Class Reference

A processor designed specifically for tomographic tilt series data. More...

#include <processor.h>

Inheritance diagram for EMAN::TomoTiltEdgeMaskProcessor:

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Collaboration diagram for EMAN::TomoTiltEdgeMaskProcessor:

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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 TypeDict get_param_types () const
 Get processor parameter information in a dictionary.
virtual string get_desc () const
 Get the descrition of this specific processor.

Static Public Member Functions

ProcessorNEW ()

Static Public Attributes

const string NAME = "tomo.tiltedgemask"

Detailed Description

A processor designed specifically for tomographic tilt series data.

This processors masks out 'mass' in tilted images that is not present in the zero-tilt (0 degrees) image. It does this based on the tilt angle. The tilt angle can be extracted from the image metadata (stored as the euler_alt attribute), or it may be specified explicitly (specifying the angle is the default behavior). The masked out regions at both sides of the image are set to 0 by default, but can also be set to the mean of the nearest non-masked data edge (in the y direction), or similarly the mean of both non-masked data edges on either side of the image. A gaussian fall-off is optional (but off by default).

Author:
David Woolford <woolford@bcm.edu>
Date:
01/10/2008
Parameters:
biedgemean Mutually exclusive of edgemean. Experimental. Causes the pixels in the masked out areas to take the average value of both the left and right edge pixel strips
edgemean Mutually exclusive of biedgemean. Masked pixels values assume the mean edge pixel value, independently, for both sides of the image
angle The angle that the image is, with respect to the zero tilt image
angle_fim Read fim as 'from image metadata' - this causes the altitude angle stored in by the image object (i.e. as extracted from the header, as currently stored in memory) to be used as the angle. This overrides the angle argument
gauss_falloff Causes the edge masking to have a smooth Gaussian fall-off - this parameter specifies how many pixels the fall-off will proceed over. Default is 0
gauss_sigma The sigma of the Gaussian function used to smooth the edge fall-off (functional form is exp(-(pixel distance)^2/sigma^2)

Definition at line 6649 of file processor.h.


Member Function Documentation

virtual string EMAN::TomoTiltEdgeMaskProcessor::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 6676 of file processor.h.

06677                 {
06678                         return "Masks the part of the image which is not present in the 0-tilt image. Masked areas can be 0 or set to the edgemean (of the nearest or both edges). Masked areas can also have a Gaussian fall-off to make the appearance smooth.";
06679                 }

virtual string EMAN::TomoTiltEdgeMaskProcessor::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 6654 of file processor.h.

06655                 {
06656                         return NAME;
06657                 }

virtual TypeDict EMAN::TomoTiltEdgeMaskProcessor::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 6664 of file processor.h.

References EMAN::TypeDict::put().

06665                 {
06666                         TypeDict d;
06667                         d.put("biedgemean", EMObject::BOOL, "Mutually  exclusive of edgemean. Experimental. Causes the pixels in the masked out areas to take the average value of both the left and right edge pixel strips");
06668                         d.put("edgemean", EMObject::BOOL, "Mutually  exclusive of biedgemean. Masked pixels values assume the mean edge pixel value, independently, for both sides of the image.");
06669                         d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image");
06670                         d.put("gauss_falloff",EMObject::INT, "Causes the edge masking to have a smooth Gaussian fall-off - this parameter specifies how many pixels the fall-off will proceed over. Default is 0.");
06671                         d.put("gauss_sigma",EMObject::FLOAT,"The sigma of the Gaussian function used to smooth the edge fall-off (functional form is exp(-(pixel distance)^2/sigma^2)");
06672                         d.put("angle_fim",EMObject::BOOL,"Read fim as 'from image metadata' - this causes the altitude angle stored in by the image object (i.e. as extracted from the header, as currently stored in memory) to be used as the angle. This overrides the angle argument");
06673                         return d;
06674                 }

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

Definition at line 6659 of file processor.h.

06660                 {
06661                         return new TomoTiltEdgeMaskProcessor();
06662                 }

void TomoTiltEdgeMaskProcessor::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 9309 of file processor.cpp.

References EMAN::EMData::get_attr(), EMAN::Transform::get_params(), EMAN::EMData::get_value_at(), EMAN::EMData::get_xsize(), EMAN::EMData::get_ysize(), InvalidParameterException, nx, ny, EMAN::EMData::process_inplace(), EMAN::Dict::set_default(), EMAN::EMData::set_value_at(), t, and EMAN::EMData::update().

09310 {
09311         bool biedgemean = params.set_default("biedgemean", false);
09312         bool edgemean = params.set_default("edgemean", false);
09313         // You can only do one of these - so if someone specifies them both the code complains loudly
09314         if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive");
09315 
09316         bool fim = params.set_default("angle_fim", false);
09317         float alt;
09318         if ( fim ) {
09319                 Transform* t = (Transform*)image->get_attr("xform.projection");
09320                 Dict d = t->get_params("eman");
09321                 alt = (float) d["alt"];
09322                 if(t) {delete t; t=0;}
09323         }
09324         else alt = params.set_default("angle", 0.0f);
09325 
09326 
09327         float cosine = cos(alt*M_PI/180.0f);
09328 
09329         // Zero the edges
09330         int nx = image->get_xsize();
09331         int ny = image->get_ysize();
09332         int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0);
09333 
09334         float x1_edge_mean = 0.0;
09335         float x2_edge_mean = 0.0;
09336 
09337         if ( biedgemean )
09338         {
09339                 float edge_mean = 0.0;
09340 
09341                 // Accrue the pixel densities on the side strips
09342                 for ( int i = 0; i < ny; ++i ) {
09343                         edge_mean += image->get_value_at(x_clip, i );
09344                         edge_mean += image->get_value_at(nx - x_clip-1, i );
09345                 }
09346                 // Now make it so the mean is stored
09347                 edge_mean /= 2*ny;
09348 
09349                 // Now shift pixel values accordingly
09350                 for ( int i = 0; i < ny; ++i ) {
09351                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09352                                 image->set_value_at(j,i,edge_mean);
09353                         }
09354                         for ( int j = 0; j < x_clip; ++j) {
09355                                 image->set_value_at(j,i,edge_mean);
09356                         }
09357                 }
09358                 x1_edge_mean = edge_mean;
09359                 x2_edge_mean = edge_mean;
09360         }
09361         else if (edgemean)
09362         {
09363                 for ( int i = 0; i < ny; ++i ) {
09364                         x1_edge_mean += image->get_value_at(x_clip, i );
09365                         x2_edge_mean += image->get_value_at(nx - x_clip-1, i );
09366                 }
09367                 x1_edge_mean /= ny;
09368                 x2_edge_mean /= ny;
09369 
09370                 for ( int i = 0; i < ny; ++i ) {
09371                         for ( int j = 0; j < x_clip; ++j) {
09372                                 image->set_value_at(j,i,x1_edge_mean);
09373                         }
09374                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09375                                 image->set_value_at(j,i,x2_edge_mean);
09376                         }
09377                 }
09378         }
09379         else
09380         {
09381                 // The edges are just zeroed -
09382                 Dict zero_dict;
09383                 zero_dict["x0"] = x_clip;
09384                 zero_dict["x1"] = x_clip;
09385                 zero_dict["y0"] = 0;
09386                 zero_dict["y1"] = 0;
09387                 image->process_inplace( "mask.zeroedge2d", zero_dict );
09388         }
09389 
09390         int gauss_rad = params.set_default("gauss_falloff", 0);
09391         if ( gauss_rad != 0)
09392         {
09393                 // If the gaussian falloff distance is greater than x_clip, it will technically
09394                 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen.
09395                 // Therefore, there is potential here for (benevolent) unexpected behavior.
09396                 if ( gauss_rad > x_clip ) gauss_rad = x_clip;
09397 
09398                 float gauss_sigma = params.set_default("gauss_sigma", 3.0f);
09399                 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma");
09400                 float sigma = (float) gauss_rad/gauss_sigma;
09401 
09402                 GaussianFunctoid gf(sigma);
09403 
09404                 for ( int i = 0; i < ny; ++i ) {
09405 
09406                         float left_value = image->get_value_at(x_clip, i );
09407                         float scale1 = left_value-x1_edge_mean;
09408 
09409                         float right_value = image->get_value_at(nx - x_clip - 1, i );
09410                         float scale2 = right_value-x2_edge_mean;
09411 
09412                         for ( int j = 1; j < gauss_rad; ++j )
09413                         {
09414                                 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean );
09415                                 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean);
09416                         }
09417                 }
09418         }
09419 
09420         image->update();
09421 }


Member Data Documentation

const string TomoTiltEdgeMaskProcessor::NAME = "tomo.tiltedgemask" [static]
 

Definition at line 217 of file processor.cpp.


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