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 6680 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 6707 of file processor.h.

06708                 {
06709                         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.";
06710                 }

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 6685 of file processor.h.

References NAME.

06686                 {
06687                         return NAME;
06688                 }

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 6695 of file processor.h.

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

06696                 {
06697                         TypeDict d;
06698                         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");
06699                         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.");
06700                         d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image");
06701                         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.");
06702                         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)");
06703                         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");
06704                         return d;
06705                 }

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

Definition at line 6690 of file processor.h.

06691                 {
06692                         return new TomoTiltEdgeMaskProcessor();
06693                 }

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 9395 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().

09396 {
09397         bool biedgemean = params.set_default("biedgemean", false);
09398         bool edgemean = params.set_default("edgemean", false);
09399         // You can only do one of these - so if someone specifies them both the code complains loudly
09400         if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive");
09401 
09402         bool fim = params.set_default("angle_fim", false);
09403         float alt;
09404         if ( fim ) {
09405                 Transform* t = (Transform*)image->get_attr("xform.projection");
09406                 Dict d = t->get_params("eman");
09407                 alt = (float) d["alt"];
09408                 if(t) {delete t; t=0;}
09409         }
09410         else alt = params.set_default("angle", 0.0f);
09411 
09412 
09413         float cosine = cos(alt*M_PI/180.0f);
09414 
09415         // Zero the edges
09416         int nx = image->get_xsize();
09417         int ny = image->get_ysize();
09418         int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0);
09419 
09420         float x1_edge_mean = 0.0;
09421         float x2_edge_mean = 0.0;
09422 
09423         if ( biedgemean )
09424         {
09425                 float edge_mean = 0.0;
09426 
09427                 // Accrue the pixel densities on the side strips
09428                 for ( int i = 0; i < ny; ++i ) {
09429                         edge_mean += image->get_value_at(x_clip, i );
09430                         edge_mean += image->get_value_at(nx - x_clip-1, i );
09431                 }
09432                 // Now make it so the mean is stored
09433                 edge_mean /= 2*ny;
09434 
09435                 // Now shift pixel values accordingly
09436                 for ( int i = 0; i < ny; ++i ) {
09437                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09438                                 image->set_value_at(j,i,edge_mean);
09439                         }
09440                         for ( int j = 0; j < x_clip; ++j) {
09441                                 image->set_value_at(j,i,edge_mean);
09442                         }
09443                 }
09444                 x1_edge_mean = edge_mean;
09445                 x2_edge_mean = edge_mean;
09446         }
09447         else if (edgemean)
09448         {
09449                 for ( int i = 0; i < ny; ++i ) {
09450                         x1_edge_mean += image->get_value_at(x_clip, i );
09451                         x2_edge_mean += image->get_value_at(nx - x_clip-1, i );
09452                 }
09453                 x1_edge_mean /= ny;
09454                 x2_edge_mean /= ny;
09455 
09456                 for ( int i = 0; i < ny; ++i ) {
09457                         for ( int j = 0; j < x_clip; ++j) {
09458                                 image->set_value_at(j,i,x1_edge_mean);
09459                         }
09460                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09461                                 image->set_value_at(j,i,x2_edge_mean);
09462                         }
09463                 }
09464         }
09465         else
09466         {
09467                 // The edges are just zeroed -
09468                 Dict zero_dict;
09469                 zero_dict["x0"] = x_clip;
09470                 zero_dict["x1"] = x_clip;
09471                 zero_dict["y0"] = 0;
09472                 zero_dict["y1"] = 0;
09473                 image->process_inplace( "mask.zeroedge2d", zero_dict );
09474         }
09475 
09476         int gauss_rad = params.set_default("gauss_falloff", 0);
09477         if ( gauss_rad != 0)
09478         {
09479                 // If the gaussian falloff distance is greater than x_clip, it will technically
09480                 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen.
09481                 // Therefore, there is potential here for (benevolent) unexpected behavior.
09482                 if ( gauss_rad > x_clip ) gauss_rad = x_clip;
09483 
09484                 float gauss_sigma = params.set_default("gauss_sigma", 3.0f);
09485                 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma");
09486                 float sigma = (float) gauss_rad/gauss_sigma;
09487 
09488                 GaussianFunctoid gf(sigma);
09489 
09490                 for ( int i = 0; i < ny; ++i ) {
09491 
09492                         float left_value = image->get_value_at(x_clip, i );
09493                         float scale1 = left_value-x1_edge_mean;
09494 
09495                         float right_value = image->get_value_at(nx - x_clip - 1, i );
09496                         float scale2 = right_value-x2_edge_mean;
09497 
09498                         for ( int j = 1; j < gauss_rad; ++j )
09499                         {
09500                                 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean );
09501                                 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean);
09502                         }
09503                 }
09504         }
09505 
09506         image->update();
09507 }


Member Data Documentation

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

Definition at line 6712 of file processor.h.

Referenced by get_name().


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