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 3794 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 3809 of file processor.h.

03810                 {
03811                         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.";
03812                 }

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 3799 of file processor.h.

References NAME.

03800                 {
03801                         return NAME;
03802                 }

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 3814 of file processor.h.

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

03815                 {
03816                         TypeDict d;
03817                         d.put("value1", EMObject::FLOAT, "sig multiplier");
03818                         d.put("value2", EMObject::FLOAT, "x of center");
03819                         d.put("value3", EMObject::FLOAT, "y of center");
03820                         return d;
03821                 }

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

Definition at line 3804 of file processor.h.

03805                 {
03806                         return new BeamstopProcessor();
03807                 }

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 3075 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().

03076 {
03077         if (!image) {
03078                 LOGWARN("NULL Image");
03079                 return;
03080         }
03081         if (image->get_zsize() > 1) {
03082                 LOGERR("BeamstopProcessor doesn't support 3D model");
03083                 throw ImageDimensionException("3D model not supported");
03084         }
03085 
03086         float value1 = params["value1"];
03087         float value2 = params["value2"];
03088         float value3 = params["value3"];
03089 
03090         float thr = fabs(value1);
03091         float *data = image->get_data();
03092         int cenx = (int) value2;
03093         int ceny = (int) value3;
03094 
03095         int nx = image->get_xsize();
03096         int ny = image->get_ysize();
03097 
03098         if (cenx <= 0) {
03099                 cenx = nx / 2;
03100         }
03101 
03102         if (ceny <= 0) {
03103                 ceny = ny / 2;
03104         }
03105 
03106         int mxr = (int) floor(sqrt(2.0f) * nx / 2);
03107 
03108         float *mean_values = new float[mxr];
03109         float *sigma_values = new float[mxr];
03110         double sum = 0;
03111         int count = 0;
03112         double square_sum = 0;
03113 
03114         for (int i = 0; i < mxr; i++) {
03115                 sum = 0;
03116                 count = 0;
03117                 square_sum = 0;
03118                 int nitems = 6 * i + 2;
03119 
03120                 for (int j = 0; j < nitems; j++) {
03121                         float ang = j * 2 * M_PI / nitems;
03122                         int x0 = (int) floor(cos(ang) * i + cenx);
03123                         int y0 = (int) floor(sin(ang) * i + ceny);
03124 
03125                         if (x0 < 0 || y0 < 0 || x0 >= nx || y0 >= ny) {
03126                                 continue;
03127                         }
03128 
03129                         float f = data[x0 + y0 * nx];
03130                         sum += f;
03131                         square_sum += f * f;
03132                         count++;
03133                 }
03134 
03135                 mean_values[i] = (float)sum / count;
03136                 sigma_values[i] = (float) sqrt(square_sum / count - mean_values[i] * mean_values[i]);
03137         }
03138 
03139 
03140         for (int k = 0; k < 5; k++) {
03141                 for (int i = 0; i < mxr; i++) {
03142                         sum = 0;
03143                         count = 0;
03144                         square_sum = 0;
03145                         int nitems = 6 * i + 2;
03146                         double thr1 = mean_values[i] - sigma_values[i] * thr;
03147                         double thr2 = mean_values[i] + sigma_values[i];
03148 
03149                         for (int j = 0; j < nitems; j++) {
03150                                 float ang = j * 2 * M_PI / nitems;
03151                                 int x0 = (int) floor(cos(ang) * i + cenx);
03152                                 int y0 = (int) floor(sin(ang) * i + ceny);
03153 
03154                                 if (x0 < 0 || y0 < 0 || x0 >= nx || y0 >= ny ||
03155                                         data[x0 + y0 * nx] < thr1 || data[x0 + y0 * nx] > thr2) {
03156                                         continue;
03157                                 }
03158 
03159                                 sum += data[x0 + y0 * nx];
03160                                 square_sum += data[x0 + y0 * nx] * data[x0 + y0 * nx];
03161                                 count++;
03162                         }
03163 
03164                         mean_values[i] = (float) sum / count;
03165                         sigma_values[i] = (float) sqrt(square_sum / count - mean_values[i] * mean_values[i]);
03166                 }
03167         }
03168 
03169         for (int i = 0; i < nx; i++) {
03170                 for (int j = 0; j < ny; j++) {
03171 
03172 #ifdef  _WIN32
03173                         int r = Util::round(_hypot((float) i - cenx, (float) j - ceny));
03174 #else
03175                         int r = Util::round(hypot((float) i - cenx, (float) j - ceny));
03176 #endif  //_WIN32
03177 
03178                         if (value1 < 0) {
03179                                 if (data[i + j * nx] < (mean_values[r] - sigma_values[r] * thr)) {
03180                                         data[i + j * nx] = 0;
03181                                 }
03182                                 else {
03183                                         data[i + j * nx] -= mean_values[r];
03184                                 }
03185                                 continue;
03186                         }
03187                         if (data[i + j * nx] > (mean_values[r] - sigma_values[r] * thr)) {
03188                                 continue;
03189                         }
03190                         data[i + j * nx] = mean_values[r];
03191                 }
03192         }
03193 
03194         if( mean_values )
03195         {
03196                 delete[]mean_values;
03197                 mean_values = 0;
03198         }
03199 
03200         if( sigma_values )
03201         {
03202                 delete[]sigma_values;
03203                 sigma_values = 0;
03204         }
03205 
03206         image->update();
03207 }


Member Data Documentation

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

Definition at line 3823 of file processor.h.

Referenced by get_name().


The documentation for this class was generated from the following files:
Generated on Tue Jul 12 13:49:10 2011 for EMAN2 by  doxygen 1.4.7