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 6555 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 6582 of file processor.h.

06583                 {
06584                         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.";
06585                 }

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 6560 of file processor.h.

References NAME.

06561                 {
06562                         return NAME;
06563                 }

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 6570 of file processor.h.

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

06571                 {
06572                         TypeDict d;
06573                         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");
06574                         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.");
06575                         d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image");
06576                         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.");
06577                         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)");
06578                         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");
06579                         return d;
06580                 }

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

Definition at line 6565 of file processor.h.

06566                 {
06567                         return new TomoTiltEdgeMaskProcessor();
06568                 }

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 9280 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().

09281 {
09282         bool biedgemean = params.set_default("biedgemean", false);
09283         bool edgemean = params.set_default("edgemean", false);
09284         // You can only do one of these - so if someone specifies them both the code complains loudly
09285         if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive");
09286 
09287         bool fim = params.set_default("angle_fim", false);
09288         float alt;
09289         if ( fim ) {
09290                 Transform* t = (Transform*)image->get_attr("xform.projection");
09291                 Dict d = t->get_params("eman");
09292                 alt = (float) d["alt"];
09293                 if(t) {delete t; t=0;}
09294         }
09295         else alt = params.set_default("angle", 0.0f);
09296 
09297 
09298         float cosine = cos(alt*M_PI/180.0f);
09299 
09300         // Zero the edges
09301         int nx = image->get_xsize();
09302         int ny = image->get_ysize();
09303         int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0);
09304 
09305         float x1_edge_mean = 0.0;
09306         float x2_edge_mean = 0.0;
09307 
09308         if ( biedgemean )
09309         {
09310                 float edge_mean = 0.0;
09311 
09312                 // Accrue the pixel densities on the side strips
09313                 for ( int i = 0; i < ny; ++i ) {
09314                         edge_mean += image->get_value_at(x_clip, i );
09315                         edge_mean += image->get_value_at(nx - x_clip-1, i );
09316                 }
09317                 // Now make it so the mean is stored
09318                 edge_mean /= 2*ny;
09319 
09320                 // Now shift pixel values accordingly
09321                 for ( int i = 0; i < ny; ++i ) {
09322                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09323                                 image->set_value_at(j,i,edge_mean);
09324                         }
09325                         for ( int j = 0; j < x_clip; ++j) {
09326                                 image->set_value_at(j,i,edge_mean);
09327                         }
09328                 }
09329                 x1_edge_mean = edge_mean;
09330                 x2_edge_mean = edge_mean;
09331         }
09332         else if (edgemean)
09333         {
09334                 for ( int i = 0; i < ny; ++i ) {
09335                         x1_edge_mean += image->get_value_at(x_clip, i );
09336                         x2_edge_mean += image->get_value_at(nx - x_clip-1, i );
09337                 }
09338                 x1_edge_mean /= ny;
09339                 x2_edge_mean /= ny;
09340 
09341                 for ( int i = 0; i < ny; ++i ) {
09342                         for ( int j = 0; j < x_clip; ++j) {
09343                                 image->set_value_at(j,i,x1_edge_mean);
09344                         }
09345                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09346                                 image->set_value_at(j,i,x2_edge_mean);
09347                         }
09348                 }
09349         }
09350         else
09351         {
09352                 // The edges are just zeroed -
09353                 Dict zero_dict;
09354                 zero_dict["x0"] = x_clip;
09355                 zero_dict["x1"] = x_clip;
09356                 zero_dict["y0"] = 0;
09357                 zero_dict["y1"] = 0;
09358                 image->process_inplace( "mask.zeroedge2d", zero_dict );
09359         }
09360 
09361         int gauss_rad = params.set_default("gauss_falloff", 0);
09362         if ( gauss_rad != 0)
09363         {
09364                 // If the gaussian falloff distance is greater than x_clip, it will technically
09365                 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen.
09366                 // Therefore, there is potential here for (benevolent) unexpected behavior.
09367                 if ( gauss_rad > x_clip ) gauss_rad = x_clip;
09368 
09369                 float gauss_sigma = params.set_default("gauss_sigma", 3.0f);
09370                 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma");
09371                 float sigma = (float) gauss_rad/gauss_sigma;
09372 
09373                 GaussianFunctoid gf(sigma);
09374 
09375                 for ( int i = 0; i < ny; ++i ) {
09376 
09377                         float left_value = image->get_value_at(x_clip, i );
09378                         float scale1 = left_value-x1_edge_mean;
09379 
09380                         float right_value = image->get_value_at(nx - x_clip - 1, i );
09381                         float scale2 = right_value-x2_edge_mean;
09382 
09383                         for ( int j = 1; j < gauss_rad; ++j )
09384                         {
09385                                 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean );
09386                                 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean);
09387                         }
09388                 }
09389         }
09390 
09391         image->update();
09392 }


Member Data Documentation

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

Definition at line 6587 of file processor.h.

Referenced by get_name().


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