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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 6727 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 6754 of file processor.h.

06755                 {
06756                         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.";
06757                 }

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 6732 of file processor.h.

06733                 {
06734                         return NAME;
06735                 }

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 6742 of file processor.h.

References EMAN::TypeDict::put().

06743                 {
06744                         TypeDict d;
06745                         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");
06746                         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.");
06747                         d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image");
06748                         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.");
06749                         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)");
06750                         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");
06751                         return d;
06752                 }

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

Definition at line 6737 of file processor.h.

06738                 {
06739                         return new TomoTiltEdgeMaskProcessor();
06740                 }

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 9482 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().

09483 {
09484         bool biedgemean = params.set_default("biedgemean", false);
09485         bool edgemean = params.set_default("edgemean", false);
09486         // You can only do one of these - so if someone specifies them both the code complains loudly
09487         if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive");
09488 
09489         bool fim = params.set_default("angle_fim", false);
09490         float alt;
09491         if ( fim ) {
09492                 Transform* t = (Transform*)image->get_attr("xform.projection");
09493                 Dict d = t->get_params("eman");
09494                 alt = (float) d["alt"];
09495                 if(t) {delete t; t=0;}
09496         }
09497         else alt = params.set_default("angle", 0.0f);
09498 
09499 
09500         float cosine = cos(alt*M_PI/180.0f);
09501 
09502         // Zero the edges
09503         int nx = image->get_xsize();
09504         int ny = image->get_ysize();
09505         int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0);
09506 
09507         float x1_edge_mean = 0.0;
09508         float x2_edge_mean = 0.0;
09509 
09510         if ( biedgemean )
09511         {
09512                 float edge_mean = 0.0;
09513 
09514                 // Accrue the pixel densities on the side strips
09515                 for ( int i = 0; i < ny; ++i ) {
09516                         edge_mean += image->get_value_at(x_clip, i );
09517                         edge_mean += image->get_value_at(nx - x_clip-1, i );
09518                 }
09519                 // Now make it so the mean is stored
09520                 edge_mean /= 2*ny;
09521 
09522                 // Now shift pixel values accordingly
09523                 for ( int i = 0; i < ny; ++i ) {
09524                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09525                                 image->set_value_at(j,i,edge_mean);
09526                         }
09527                         for ( int j = 0; j < x_clip; ++j) {
09528                                 image->set_value_at(j,i,edge_mean);
09529                         }
09530                 }
09531                 x1_edge_mean = edge_mean;
09532                 x2_edge_mean = edge_mean;
09533         }
09534         else if (edgemean)
09535         {
09536                 for ( int i = 0; i < ny; ++i ) {
09537                         x1_edge_mean += image->get_value_at(x_clip, i );
09538                         x2_edge_mean += image->get_value_at(nx - x_clip-1, i );
09539                 }
09540                 x1_edge_mean /= ny;
09541                 x2_edge_mean /= ny;
09542 
09543                 for ( int i = 0; i < ny; ++i ) {
09544                         for ( int j = 0; j < x_clip; ++j) {
09545                                 image->set_value_at(j,i,x1_edge_mean);
09546                         }
09547                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09548                                 image->set_value_at(j,i,x2_edge_mean);
09549                         }
09550                 }
09551         }
09552         else
09553         {
09554                 // The edges are just zeroed -
09555                 Dict zero_dict;
09556                 zero_dict["x0"] = x_clip;
09557                 zero_dict["x1"] = x_clip;
09558                 zero_dict["y0"] = 0;
09559                 zero_dict["y1"] = 0;
09560                 image->process_inplace( "mask.zeroedge2d", zero_dict );
09561         }
09562 
09563         int gauss_rad = params.set_default("gauss_falloff", 0);
09564         if ( gauss_rad != 0)
09565         {
09566                 // If the gaussian falloff distance is greater than x_clip, it will technically
09567                 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen.
09568                 // Therefore, there is potential here for (benevolent) unexpected behavior.
09569                 if ( gauss_rad > x_clip ) gauss_rad = x_clip;
09570 
09571                 float gauss_sigma = params.set_default("gauss_sigma", 3.0f);
09572                 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma");
09573                 float sigma = (float) gauss_rad/gauss_sigma;
09574 
09575                 GaussianFunctoid gf(sigma);
09576 
09577                 for ( int i = 0; i < ny; ++i ) {
09578 
09579                         float left_value = image->get_value_at(x_clip, i );
09580                         float scale1 = left_value-x1_edge_mean;
09581 
09582                         float right_value = image->get_value_at(nx - x_clip - 1, i );
09583                         float scale2 = right_value-x2_edge_mean;
09584 
09585                         for ( int j = 1; j < gauss_rad; ++j )
09586                         {
09587                                 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean );
09588                                 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean);
09589                         }
09590                 }
09591         }
09592 
09593         image->update();
09594 }


Member Data Documentation

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

Definition at line 212 of file processor.cpp.


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