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 6683 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 6710 of file processor.h.

06711                 {
06712                         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.";
06713                 }

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 6688 of file processor.h.

References NAME.

06689                 {
06690                         return NAME;
06691                 }

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 6698 of file processor.h.

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

06699                 {
06700                         TypeDict d;
06701                         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");
06702                         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.");
06703                         d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image");
06704                         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.");
06705                         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)");
06706                         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");
06707                         return d;
06708                 }

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

Definition at line 6693 of file processor.h.

06694                 {
06695                         return new TomoTiltEdgeMaskProcessor();
06696                 }

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 9322 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().

09323 {
09324         bool biedgemean = params.set_default("biedgemean", false);
09325         bool edgemean = params.set_default("edgemean", false);
09326         // You can only do one of these - so if someone specifies them both the code complains loudly
09327         if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive");
09328 
09329         bool fim = params.set_default("angle_fim", false);
09330         float alt;
09331         if ( fim ) {
09332                 Transform* t = (Transform*)image->get_attr("xform.projection");
09333                 Dict d = t->get_params("eman");
09334                 alt = (float) d["alt"];
09335                 if(t) {delete t; t=0;}
09336         }
09337         else alt = params.set_default("angle", 0.0f);
09338 
09339 
09340         float cosine = cos(alt*M_PI/180.0f);
09341 
09342         // Zero the edges
09343         int nx = image->get_xsize();
09344         int ny = image->get_ysize();
09345         int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0);
09346 
09347         float x1_edge_mean = 0.0;
09348         float x2_edge_mean = 0.0;
09349 
09350         if ( biedgemean )
09351         {
09352                 float edge_mean = 0.0;
09353 
09354                 // Accrue the pixel densities on the side strips
09355                 for ( int i = 0; i < ny; ++i ) {
09356                         edge_mean += image->get_value_at(x_clip, i );
09357                         edge_mean += image->get_value_at(nx - x_clip-1, i );
09358                 }
09359                 // Now make it so the mean is stored
09360                 edge_mean /= 2*ny;
09361 
09362                 // Now shift pixel values accordingly
09363                 for ( int i = 0; i < ny; ++i ) {
09364                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09365                                 image->set_value_at(j,i,edge_mean);
09366                         }
09367                         for ( int j = 0; j < x_clip; ++j) {
09368                                 image->set_value_at(j,i,edge_mean);
09369                         }
09370                 }
09371                 x1_edge_mean = edge_mean;
09372                 x2_edge_mean = edge_mean;
09373         }
09374         else if (edgemean)
09375         {
09376                 for ( int i = 0; i < ny; ++i ) {
09377                         x1_edge_mean += image->get_value_at(x_clip, i );
09378                         x2_edge_mean += image->get_value_at(nx - x_clip-1, i );
09379                 }
09380                 x1_edge_mean /= ny;
09381                 x2_edge_mean /= ny;
09382 
09383                 for ( int i = 0; i < ny; ++i ) {
09384                         for ( int j = 0; j < x_clip; ++j) {
09385                                 image->set_value_at(j,i,x1_edge_mean);
09386                         }
09387                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09388                                 image->set_value_at(j,i,x2_edge_mean);
09389                         }
09390                 }
09391         }
09392         else
09393         {
09394                 // The edges are just zeroed -
09395                 Dict zero_dict;
09396                 zero_dict["x0"] = x_clip;
09397                 zero_dict["x1"] = x_clip;
09398                 zero_dict["y0"] = 0;
09399                 zero_dict["y1"] = 0;
09400                 image->process_inplace( "mask.zeroedge2d", zero_dict );
09401         }
09402 
09403         int gauss_rad = params.set_default("gauss_falloff", 0);
09404         if ( gauss_rad != 0)
09405         {
09406                 // If the gaussian falloff distance is greater than x_clip, it will technically
09407                 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen.
09408                 // Therefore, there is potential here for (benevolent) unexpected behavior.
09409                 if ( gauss_rad > x_clip ) gauss_rad = x_clip;
09410 
09411                 float gauss_sigma = params.set_default("gauss_sigma", 3.0f);
09412                 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma");
09413                 float sigma = (float) gauss_rad/gauss_sigma;
09414 
09415                 GaussianFunctoid gf(sigma);
09416 
09417                 for ( int i = 0; i < ny; ++i ) {
09418 
09419                         float left_value = image->get_value_at(x_clip, i );
09420                         float scale1 = left_value-x1_edge_mean;
09421 
09422                         float right_value = image->get_value_at(nx - x_clip - 1, i );
09423                         float scale2 = right_value-x2_edge_mean;
09424 
09425                         for ( int j = 1; j < gauss_rad; ++j )
09426                         {
09427                                 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean );
09428                                 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean);
09429                         }
09430                 }
09431         }
09432 
09433         image->update();
09434 }


Member Data Documentation

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

Definition at line 6715 of file processor.h.

Referenced by get_name().


The documentation for this class was generated from the following files:
Generated on Mon Jul 19 12:44:14 2010 for EMAN2 by  doxygen 1.4.7