EMAN::BeamstopProcessor Class Reference

Try to eliminate beamstop in electron diffraction patterns. More...

#include <processor.h>

Inheritance diagram for EMAN::BeamstopProcessor:

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Collaboration diagram for EMAN::BeamstopProcessor:

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List of all members.

Public Member Functions

void process_inplace (EMData *image)
 To process an image in-place.
string get_name () const
 Get the processor's name.
string get_desc () const
 Get the descrition of this specific processor.
TypeDict get_param_types () const
 Get processor parameter information in a dictionary.

Static Public Member Functions

static ProcessorNEW ()

Static Public Attributes

static const string NAME = "mask.beamstop"

Detailed Description

Try to eliminate beamstop in electron diffraction patterns.

If value1<0 also does radial subtract.

Parameters:
value1 sig multiplier
value2 x of center
value3 y of center

Definition at line 3756 of file processor.h.


Member Function Documentation

string EMAN::BeamstopProcessor::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 3771 of file processor.h.

03772                 {
03773                         return "Try to eliminate beamstop in electron diffraction patterns. value1=sig multiplier; value2,value3 are x,y of center, if value1<0 also does radial subtract.";
03774                 }

string EMAN::BeamstopProcessor::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 3761 of file processor.h.

References NAME.

03762                 {
03763                         return NAME;
03764                 }

TypeDict EMAN::BeamstopProcessor::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 3776 of file processor.h.

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

03777                 {
03778                         TypeDict d;
03779                         d.put("value1", EMObject::FLOAT, "sig multiplier");
03780                         d.put("value2", EMObject::FLOAT, "x of center");
03781                         d.put("value3", EMObject::FLOAT, "y of center");
03782                         return d;
03783                 }

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

Definition at line 3766 of file processor.h.

03767                 {
03768                         return new BeamstopProcessor();
03769                 }

void BeamstopProcessor::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 3047 of file processor.cpp.

References EMAN::EMData::get_data(), EMAN::EMData::get_xsize(), EMAN::EMData::get_ysize(), EMAN::EMData::get_zsize(), ImageDimensionException, LOGERR, LOGWARN, EMAN::Processor::params, EMAN::Util::round(), sqrt(), and EMAN::EMData::update().

03048 {
03049         if (!image) {
03050                 LOGWARN("NULL Image");
03051                 return;
03052         }
03053         if (image->get_zsize() > 1) {
03054                 LOGERR("BeamstopProcessor doesn't support 3D model");
03055                 throw ImageDimensionException("3D model not supported");
03056         }
03057 
03058         float value1 = params["value1"];
03059         float value2 = params["value2"];
03060         float value3 = params["value3"];
03061 
03062         float thr = fabs(value1);
03063         float *data = image->get_data();
03064         int cenx = (int) value2;
03065         int ceny = (int) value3;
03066 
03067         int nx = image->get_xsize();
03068         int ny = image->get_ysize();
03069 
03070         if (cenx <= 0) {
03071                 cenx = nx / 2;
03072         }
03073 
03074         if (ceny <= 0) {
03075                 ceny = ny / 2;
03076         }
03077 
03078         int mxr = (int) floor(sqrt(2.0f) * nx / 2);
03079 
03080         float *mean_values = new float[mxr];
03081         float *sigma_values = new float[mxr];
03082         double sum = 0;
03083         int count = 0;
03084         double square_sum = 0;
03085 
03086         for (int i = 0; i < mxr; i++) {
03087                 sum = 0;
03088                 count = 0;
03089                 square_sum = 0;
03090                 int nitems = 6 * i + 2;
03091 
03092                 for (int j = 0; j < nitems; j++) {
03093                         float ang = j * 2 * M_PI / nitems;
03094                         int x0 = (int) floor(cos(ang) * i + cenx);
03095                         int y0 = (int) floor(sin(ang) * i + ceny);
03096 
03097                         if (x0 < 0 || y0 < 0 || x0 >= nx || y0 >= ny) {
03098                                 continue;
03099                         }
03100 
03101                         float f = data[x0 + y0 * nx];
03102                         sum += f;
03103                         square_sum += f * f;
03104                         count++;
03105                 }
03106 
03107                 mean_values[i] = (float)sum / count;
03108                 sigma_values[i] = (float) sqrt(square_sum / count - mean_values[i] * mean_values[i]);
03109         }
03110 
03111 
03112         for (int k = 0; k < 5; k++) {
03113                 for (int i = 0; i < mxr; i++) {
03114                         sum = 0;
03115                         count = 0;
03116                         square_sum = 0;
03117                         int nitems = 6 * i + 2;
03118                         double thr1 = mean_values[i] - sigma_values[i] * thr;
03119                         double thr2 = mean_values[i] + sigma_values[i];
03120 
03121                         for (int j = 0; j < nitems; j++) {
03122                                 float ang = j * 2 * M_PI / nitems;
03123                                 int x0 = (int) floor(cos(ang) * i + cenx);
03124                                 int y0 = (int) floor(sin(ang) * i + ceny);
03125 
03126                                 if (x0 < 0 || y0 < 0 || x0 >= nx || y0 >= ny ||
03127                                         data[x0 + y0 * nx] < thr1 || data[x0 + y0 * nx] > thr2) {
03128                                         continue;
03129                                 }
03130 
03131                                 sum += data[x0 + y0 * nx];
03132                                 square_sum += data[x0 + y0 * nx] * data[x0 + y0 * nx];
03133                                 count++;
03134                         }
03135 
03136                         mean_values[i] = (float) sum / count;
03137                         sigma_values[i] = (float) sqrt(square_sum / count - mean_values[i] * mean_values[i]);
03138                 }
03139         }
03140 
03141         for (int i = 0; i < nx; i++) {
03142                 for (int j = 0; j < ny; j++) {
03143 
03144 #ifdef  _WIN32
03145                         int r = Util::round(_hypot((float) i - cenx, (float) j - ceny));
03146 #else
03147                         int r = Util::round(hypot((float) i - cenx, (float) j - ceny));
03148 #endif  //_WIN32
03149 
03150                         if (value1 < 0) {
03151                                 if (data[i + j * nx] < (mean_values[r] - sigma_values[r] * thr)) {
03152                                         data[i + j * nx] = 0;
03153                                 }
03154                                 else {
03155                                         data[i + j * nx] -= mean_values[r];
03156                                 }
03157                                 continue;
03158                         }
03159                         if (data[i + j * nx] > (mean_values[r] - sigma_values[r] * thr)) {
03160                                 continue;
03161                         }
03162                         data[i + j * nx] = mean_values[r];
03163                 }
03164         }
03165 
03166         if( mean_values )
03167         {
03168                 delete[]mean_values;
03169                 mean_values = 0;
03170         }
03171 
03172         if( sigma_values )
03173         {
03174                 delete[]sigma_values;
03175                 sigma_values = 0;
03176         }
03177 
03178         image->update();
03179 }


Member Data Documentation

const string BeamstopProcessor::NAME = "mask.beamstop" [static]

Definition at line 3785 of file processor.h.

Referenced by get_name().


The documentation for this class was generated from the following files:
Generated on Mon May 2 13:30:30 2011 for EMAN2 by  doxygen 1.4.7