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 6611 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 6638 of file processor.h.

06639                 {
06640                         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.";
06641                 }

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 6616 of file processor.h.

References NAME.

06617                 {
06618                         return NAME;
06619                 }

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 6626 of file processor.h.

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

06627                 {
06628                         TypeDict d;
06629                         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");
06630                         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.");
06631                         d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image");
06632                         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.");
06633                         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)");
06634                         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");
06635                         return d;
06636                 }

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

Definition at line 6621 of file processor.h.

06622                 {
06623                         return new TomoTiltEdgeMaskProcessor();
06624                 }

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 9277 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().

09278 {
09279         bool biedgemean = params.set_default("biedgemean", false);
09280         bool edgemean = params.set_default("edgemean", false);
09281         // You can only do one of these - so if someone specifies them both the code complains loudly
09282         if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive");
09283 
09284         bool fim = params.set_default("angle_fim", false);
09285         float alt;
09286         if ( fim ) {
09287                 Transform* t = (Transform*)image->get_attr("xform.projection");
09288                 Dict d = t->get_params("eman");
09289                 alt = (float) d["alt"];
09290                 if(t) {delete t; t=0;}
09291         }
09292         else alt = params.set_default("angle", 0.0f);
09293 
09294 
09295         float cosine = cos(alt*M_PI/180.0f);
09296 
09297         // Zero the edges
09298         int nx = image->get_xsize();
09299         int ny = image->get_ysize();
09300         int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0);
09301 
09302         float x1_edge_mean = 0.0;
09303         float x2_edge_mean = 0.0;
09304 
09305         if ( biedgemean )
09306         {
09307                 float edge_mean = 0.0;
09308 
09309                 // Accrue the pixel densities on the side strips
09310                 for ( int i = 0; i < ny; ++i ) {
09311                         edge_mean += image->get_value_at(x_clip, i );
09312                         edge_mean += image->get_value_at(nx - x_clip-1, i );
09313                 }
09314                 // Now make it so the mean is stored
09315                 edge_mean /= 2*ny;
09316 
09317                 // Now shift pixel values accordingly
09318                 for ( int i = 0; i < ny; ++i ) {
09319                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09320                                 image->set_value_at(j,i,edge_mean);
09321                         }
09322                         for ( int j = 0; j < x_clip; ++j) {
09323                                 image->set_value_at(j,i,edge_mean);
09324                         }
09325                 }
09326                 x1_edge_mean = edge_mean;
09327                 x2_edge_mean = edge_mean;
09328         }
09329         else if (edgemean)
09330         {
09331                 for ( int i = 0; i < ny; ++i ) {
09332                         x1_edge_mean += image->get_value_at(x_clip, i );
09333                         x2_edge_mean += image->get_value_at(nx - x_clip-1, i );
09334                 }
09335                 x1_edge_mean /= ny;
09336                 x2_edge_mean /= ny;
09337 
09338                 for ( int i = 0; i < ny; ++i ) {
09339                         for ( int j = 0; j < x_clip; ++j) {
09340                                 image->set_value_at(j,i,x1_edge_mean);
09341                         }
09342                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09343                                 image->set_value_at(j,i,x2_edge_mean);
09344                         }
09345                 }
09346         }
09347         else
09348         {
09349                 // The edges are just zeroed -
09350                 Dict zero_dict;
09351                 zero_dict["x0"] = x_clip;
09352                 zero_dict["x1"] = x_clip;
09353                 zero_dict["y0"] = 0;
09354                 zero_dict["y1"] = 0;
09355                 image->process_inplace( "mask.zeroedge2d", zero_dict );
09356         }
09357 
09358         int gauss_rad = params.set_default("gauss_falloff", 0);
09359         if ( gauss_rad != 0)
09360         {
09361                 // If the gaussian falloff distance is greater than x_clip, it will technically
09362                 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen.
09363                 // Therefore, there is potential here for (benevolent) unexpected behavior.
09364                 if ( gauss_rad > x_clip ) gauss_rad = x_clip;
09365 
09366                 float gauss_sigma = params.set_default("gauss_sigma", 3.0f);
09367                 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma");
09368                 float sigma = (float) gauss_rad/gauss_sigma;
09369 
09370                 GaussianFunctoid gf(sigma);
09371 
09372                 for ( int i = 0; i < ny; ++i ) {
09373 
09374                         float left_value = image->get_value_at(x_clip, i );
09375                         float scale1 = left_value-x1_edge_mean;
09376 
09377                         float right_value = image->get_value_at(nx - x_clip - 1, i );
09378                         float scale2 = right_value-x2_edge_mean;
09379 
09380                         for ( int j = 1; j < gauss_rad; ++j )
09381                         {
09382                                 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean );
09383                                 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean);
09384                         }
09385                 }
09386         }
09387 
09388         image->update();
09389 }


Member Data Documentation

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

Definition at line 6643 of file processor.h.

Referenced by get_name().


The documentation for this class was generated from the following files:
Generated on Mon May 2 13:31:11 2011 for EMAN2 by  doxygen 1.4.7