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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 6470 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 6497 of file processor.h.

06498                 {
06499                         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.";
06500                 }

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 6475 of file processor.h.

06476                 {
06477                         return NAME;
06478                 }

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 6485 of file processor.h.

References EMAN::TypeDict::put().

06486                 {
06487                         TypeDict d;
06488                         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");
06489                         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.");
06490                         d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image");
06491                         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.");
06492                         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)");
06493                         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");
06494                         return d;
06495                 }

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

Definition at line 6480 of file processor.h.

06481                 {
06482                         return new TomoTiltEdgeMaskProcessor();
06483                 }

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 9230 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().

09231 {
09232         bool biedgemean = params.set_default("biedgemean", false);
09233         bool edgemean = params.set_default("edgemean", false);
09234         // You can only do one of these - so if someone specifies them both the code complains loudly
09235         if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive");
09236 
09237         bool fim = params.set_default("angle_fim", false);
09238         float alt;
09239         if ( fim ) {
09240                 Transform* t = (Transform*)image->get_attr("xform.projection");
09241                 Dict d = t->get_params("eman");
09242                 alt = (float) d["alt"];
09243                 if(t) {delete t; t=0;}
09244         }
09245         else alt = params.set_default("angle", 0.0f);
09246 
09247 
09248         float cosine = cos(alt*M_PI/180.0f);
09249 
09250         // Zero the edges
09251         int nx = image->get_xsize();
09252         int ny = image->get_ysize();
09253         int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0);
09254 
09255         float x1_edge_mean = 0.0;
09256         float x2_edge_mean = 0.0;
09257 
09258         if ( biedgemean )
09259         {
09260                 float edge_mean = 0.0;
09261 
09262                 // Accrue the pixel densities on the side strips
09263                 for ( int i = 0; i < ny; ++i ) {
09264                         edge_mean += image->get_value_at(x_clip, i );
09265                         edge_mean += image->get_value_at(nx - x_clip-1, i );
09266                 }
09267                 // Now make it so the mean is stored
09268                 edge_mean /= 2*ny;
09269 
09270                 // Now shift pixel values accordingly
09271                 for ( int i = 0; i < ny; ++i ) {
09272                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09273                                 image->set_value_at(j,i,edge_mean);
09274                         }
09275                         for ( int j = 0; j < x_clip; ++j) {
09276                                 image->set_value_at(j,i,edge_mean);
09277                         }
09278                 }
09279                 x1_edge_mean = edge_mean;
09280                 x2_edge_mean = edge_mean;
09281         }
09282         else if (edgemean)
09283         {
09284                 for ( int i = 0; i < ny; ++i ) {
09285                         x1_edge_mean += image->get_value_at(x_clip, i );
09286                         x2_edge_mean += image->get_value_at(nx - x_clip-1, i );
09287                 }
09288                 x1_edge_mean /= ny;
09289                 x2_edge_mean /= ny;
09290 
09291                 for ( int i = 0; i < ny; ++i ) {
09292                         for ( int j = 0; j < x_clip; ++j) {
09293                                 image->set_value_at(j,i,x1_edge_mean);
09294                         }
09295                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09296                                 image->set_value_at(j,i,x2_edge_mean);
09297                         }
09298                 }
09299         }
09300         else
09301         {
09302                 // The edges are just zeroed -
09303                 Dict zero_dict;
09304                 zero_dict["x0"] = x_clip;
09305                 zero_dict["x1"] = x_clip;
09306                 zero_dict["y0"] = 0;
09307                 zero_dict["y1"] = 0;
09308                 image->process_inplace( "mask.zeroedge2d", zero_dict );
09309         }
09310 
09311         int gauss_rad = params.set_default("gauss_falloff", 0);
09312         if ( gauss_rad != 0)
09313         {
09314                 // If the gaussian falloff distance is greater than x_clip, it will technically
09315                 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen.
09316                 // Therefore, there is potential here for (benevolent) unexpected behavior.
09317                 if ( gauss_rad > x_clip ) gauss_rad = x_clip;
09318 
09319                 float gauss_sigma = params.set_default("gauss_sigma", 3.0f);
09320                 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma");
09321                 float sigma = (float) gauss_rad/gauss_sigma;
09322 
09323                 GaussianFunctoid gf(sigma);
09324 
09325                 for ( int i = 0; i < ny; ++i ) {
09326 
09327                         float left_value = image->get_value_at(x_clip, i );
09328                         float scale1 = left_value-x1_edge_mean;
09329 
09330                         float right_value = image->get_value_at(nx - x_clip - 1, i );
09331                         float scale2 = right_value-x2_edge_mean;
09332 
09333                         for ( int j = 1; j < gauss_rad; ++j )
09334                         {
09335                                 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean );
09336                                 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean);
09337                         }
09338                 }
09339         }
09340 
09341         image->update();
09342 }


Member Data Documentation

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

Definition at line 207 of file processor.cpp.


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