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 6643 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 6670 of file processor.h.

06671                 {
06672                         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.";
06673                 }

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 6648 of file processor.h.

References NAME.

06649                 {
06650                         return NAME;
06651                 }

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 6658 of file processor.h.

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

06659                 {
06660                         TypeDict d;
06661                         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");
06662                         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.");
06663                         d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image");
06664                         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.");
06665                         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)");
06666                         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");
06667                         return d;
06668                 }

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

Definition at line 6653 of file processor.h.

06654                 {
06655                         return new TomoTiltEdgeMaskProcessor();
06656                 }

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 9215 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().

09216 {
09217         bool biedgemean = params.set_default("biedgemean", false);
09218         bool edgemean = params.set_default("edgemean", false);
09219         // You can only do one of these - so if someone specifies them both the code complains loudly
09220         if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive");
09221 
09222         bool fim = params.set_default("angle_fim", false);
09223         float alt;
09224         if ( fim ) {
09225                 Transform* t = (Transform*)image->get_attr("xform.projection");
09226                 Dict d = t->get_params("eman");
09227                 alt = (float) d["alt"];
09228                 if(t) {delete t; t=0;}
09229         }
09230         else alt = params.set_default("angle", 0.0f);
09231 
09232 
09233         float cosine = cos(alt*M_PI/180.0f);
09234 
09235         // Zero the edges
09236         int nx = image->get_xsize();
09237         int ny = image->get_ysize();
09238         int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0);
09239 
09240         float x1_edge_mean = 0.0;
09241         float x2_edge_mean = 0.0;
09242 
09243         if ( biedgemean )
09244         {
09245                 float edge_mean = 0.0;
09246 
09247                 // Accrue the pixel densities on the side strips
09248                 for ( int i = 0; i < ny; ++i ) {
09249                         edge_mean += image->get_value_at(x_clip, i );
09250                         edge_mean += image->get_value_at(nx - x_clip-1, i );
09251                 }
09252                 // Now make it so the mean is stored
09253                 edge_mean /= 2*ny;
09254 
09255                 // Now shift pixel values accordingly
09256                 for ( int i = 0; i < ny; ++i ) {
09257                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09258                                 image->set_value_at(j,i,edge_mean);
09259                         }
09260                         for ( int j = 0; j < x_clip; ++j) {
09261                                 image->set_value_at(j,i,edge_mean);
09262                         }
09263                 }
09264                 x1_edge_mean = edge_mean;
09265                 x2_edge_mean = edge_mean;
09266         }
09267         else if (edgemean)
09268         {
09269                 for ( int i = 0; i < ny; ++i ) {
09270                         x1_edge_mean += image->get_value_at(x_clip, i );
09271                         x2_edge_mean += image->get_value_at(nx - x_clip-1, i );
09272                 }
09273                 x1_edge_mean /= ny;
09274                 x2_edge_mean /= ny;
09275 
09276                 for ( int i = 0; i < ny; ++i ) {
09277                         for ( int j = 0; j < x_clip; ++j) {
09278                                 image->set_value_at(j,i,x1_edge_mean);
09279                         }
09280                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09281                                 image->set_value_at(j,i,x2_edge_mean);
09282                         }
09283                 }
09284         }
09285         else
09286         {
09287                 // The edges are just zeroed -
09288                 Dict zero_dict;
09289                 zero_dict["x0"] = x_clip;
09290                 zero_dict["x1"] = x_clip;
09291                 zero_dict["y0"] = 0;
09292                 zero_dict["y1"] = 0;
09293                 image->process_inplace( "mask.zeroedge2d", zero_dict );
09294         }
09295 
09296         int gauss_rad = params.set_default("gauss_falloff", 0);
09297         if ( gauss_rad != 0)
09298         {
09299                 // If the gaussian falloff distance is greater than x_clip, it will technically
09300                 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen.
09301                 // Therefore, there is potential here for (benevolent) unexpected behavior.
09302                 if ( gauss_rad > x_clip ) gauss_rad = x_clip;
09303 
09304                 float gauss_sigma = params.set_default("gauss_sigma", 3.0f);
09305                 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma");
09306                 float sigma = (float) gauss_rad/gauss_sigma;
09307 
09308                 GaussianFunctoid gf(sigma);
09309 
09310                 for ( int i = 0; i < ny; ++i ) {
09311 
09312                         float left_value = image->get_value_at(x_clip, i );
09313                         float scale1 = left_value-x1_edge_mean;
09314 
09315                         float right_value = image->get_value_at(nx - x_clip - 1, i );
09316                         float scale2 = right_value-x2_edge_mean;
09317 
09318                         for ( int j = 1; j < gauss_rad; ++j )
09319                         {
09320                                 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean );
09321                                 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean);
09322                         }
09323                 }
09324         }
09325 
09326         image->update();
09327 }


Member Data Documentation

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

Definition at line 6675 of file processor.h.

Referenced by get_name().


The documentation for this class was generated from the following files:
Generated on Tue May 25 17:17:40 2010 for EMAN2 by  doxygen 1.4.7