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

static ProcessorNEW ()

Static Public Attributes

static const string NAME = "tomo.tiltedgemask"

Classes

class  GaussianFunctoid

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 6725 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 6752 of file processor.h.

06753                 {
06754                         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.";
06755                 }

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 6730 of file processor.h.

References NAME.

06731                 {
06732                         return NAME;
06733                 }

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 6740 of file processor.h.

References EMAN::EMObject::BOOL, EMAN::EMObject::FLOAT, EMAN::EMObject::INT, and EMAN::TypeDict::put().

06741                 {
06742                         TypeDict d;
06743                         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");
06744                         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.");
06745                         d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image");
06746                         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.");
06747                         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)");
06748                         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");
06749                         return d;
06750                 }

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

Definition at line 6735 of file processor.h.

06736                 {
06737                         return new TomoTiltEdgeMaskProcessor();
06738                 }

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 9467 of file processor.cpp.

References EMAN::EMData::get_attr(), EMAN::EMData::get_value_at(), EMAN::EMData::get_xsize(), EMAN::EMData::get_ysize(), InvalidParameterException, EMAN::Processor::params, EMAN::EMData::process_inplace(), EMAN::Dict::set_default(), EMAN::EMData::set_value_at(), t, and EMAN::EMData::update().

09468 {
09469         bool biedgemean = params.set_default("biedgemean", false);
09470         bool edgemean = params.set_default("edgemean", false);
09471         // You can only do one of these - so if someone specifies them both the code complains loudly
09472         if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive");
09473 
09474         bool fim = params.set_default("angle_fim", false);
09475         float alt;
09476         if ( fim ) {
09477                 Transform* t = (Transform*)image->get_attr("xform.projection");
09478                 Dict d = t->get_params("eman");
09479                 alt = (float) d["alt"];
09480                 if(t) {delete t; t=0;}
09481         }
09482         else alt = params.set_default("angle", 0.0f);
09483 
09484 
09485         float cosine = cos(alt*M_PI/180.0f);
09486 
09487         // Zero the edges
09488         int nx = image->get_xsize();
09489         int ny = image->get_ysize();
09490         int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0);
09491 
09492         float x1_edge_mean = 0.0;
09493         float x2_edge_mean = 0.0;
09494 
09495         if ( biedgemean )
09496         {
09497                 float edge_mean = 0.0;
09498 
09499                 // Accrue the pixel densities on the side strips
09500                 for ( int i = 0; i < ny; ++i ) {
09501                         edge_mean += image->get_value_at(x_clip, i );
09502                         edge_mean += image->get_value_at(nx - x_clip-1, i );
09503                 }
09504                 // Now make it so the mean is stored
09505                 edge_mean /= 2*ny;
09506 
09507                 // Now shift pixel values accordingly
09508                 for ( int i = 0; i < ny; ++i ) {
09509                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09510                                 image->set_value_at(j,i,edge_mean);
09511                         }
09512                         for ( int j = 0; j < x_clip; ++j) {
09513                                 image->set_value_at(j,i,edge_mean);
09514                         }
09515                 }
09516                 x1_edge_mean = edge_mean;
09517                 x2_edge_mean = edge_mean;
09518         }
09519         else if (edgemean)
09520         {
09521                 for ( int i = 0; i < ny; ++i ) {
09522                         x1_edge_mean += image->get_value_at(x_clip, i );
09523                         x2_edge_mean += image->get_value_at(nx - x_clip-1, i );
09524                 }
09525                 x1_edge_mean /= ny;
09526                 x2_edge_mean /= ny;
09527 
09528                 for ( int i = 0; i < ny; ++i ) {
09529                         for ( int j = 0; j < x_clip; ++j) {
09530                                 image->set_value_at(j,i,x1_edge_mean);
09531                         }
09532                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09533                                 image->set_value_at(j,i,x2_edge_mean);
09534                         }
09535                 }
09536         }
09537         else
09538         {
09539                 // The edges are just zeroed -
09540                 Dict zero_dict;
09541                 zero_dict["x0"] = x_clip;
09542                 zero_dict["x1"] = x_clip;
09543                 zero_dict["y0"] = 0;
09544                 zero_dict["y1"] = 0;
09545                 image->process_inplace( "mask.zeroedge2d", zero_dict );
09546         }
09547 
09548         int gauss_rad = params.set_default("gauss_falloff", 0);
09549         if ( gauss_rad != 0)
09550         {
09551                 // If the gaussian falloff distance is greater than x_clip, it will technically
09552                 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen.
09553                 // Therefore, there is potential here for (benevolent) unexpected behavior.
09554                 if ( gauss_rad > x_clip ) gauss_rad = x_clip;
09555 
09556                 float gauss_sigma = params.set_default("gauss_sigma", 3.0f);
09557                 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma");
09558                 float sigma = (float) gauss_rad/gauss_sigma;
09559 
09560                 GaussianFunctoid gf(sigma);
09561 
09562                 for ( int i = 0; i < ny; ++i ) {
09563 
09564                         float left_value = image->get_value_at(x_clip, i );
09565                         float scale1 = left_value-x1_edge_mean;
09566 
09567                         float right_value = image->get_value_at(nx - x_clip - 1, i );
09568                         float scale2 = right_value-x2_edge_mean;
09569 
09570                         for ( int j = 1; j < gauss_rad; ++j )
09571                         {
09572                                 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean );
09573                                 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean);
09574                         }
09575                 }
09576         }
09577 
09578         image->update();
09579 }


Member Data Documentation

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

Definition at line 6757 of file processor.h.

Referenced by get_name().


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