#include <processor.h>
Inheritance diagram for EMAN::GradientRemoverProcessor:


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. | |
Static Public Member Functions | |
| Processor * | NEW () |
Static Public Attributes | |
| const string | NAME = "math.lineargradientfix" |
Definition at line 3549 of file processor.h.
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Get the descrition of this specific processor. This function must be overwritten by a subclass.
Implements EMAN::Processor. Definition at line 3563 of file processor.h. 03564 {
03565 return "Gradient remover, does a rough plane fit to find linear gradients.";
03566 }
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Get the processor's name. Each processor is identified by a unique name.
Implements EMAN::Processor. Definition at line 3554 of file processor.h. Referenced by process_inplace(). 03555 {
03556 return NAME;
03557 }
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Definition at line 3558 of file processor.h. 03559 {
03560 return new GradientRemoverProcessor();
03561 }
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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.
Implements EMAN::Processor. Definition at line 2597 of file processor.cpp. References b, EMAN::Util::calc_least_square_fit(), data, EMAN::EMData::get_data(), get_name(), EMAN::EMData::get_xsize(), EMAN::EMData::get_ysize(), EMAN::EMData::get_zsize(), ImageDimensionException, LOGERR, LOGWARN, nx, ny, and EMAN::EMData::update(). 02598 {
02599 if (!image) {
02600 LOGWARN("NULL Image");
02601 return;
02602 }
02603
02604 int nz = image->get_zsize();
02605 if (nz > 1) {
02606 LOGERR("%s Processor doesn't support 3D model", get_name().c_str());
02607 throw ImageDimensionException("3D model not supported");
02608 }
02609
02610 int nx = image->get_xsize();
02611 int ny = image->get_ysize();
02612 float *dy = new float[ny];
02613 float m = 0;
02614 float b = 0;
02615 float sum_y = 0;
02616 float *data = image->get_data();
02617
02618 for (int i = 0; i < ny; i++) {
02619 Util::calc_least_square_fit(nx, 0, data + i * nx, &m, &b, false);
02620 dy[i] = b;
02621 sum_y += m;
02622 }
02623
02624 float mean_y = sum_y / ny;
02625 float sum_x = 0;
02626 Util::calc_least_square_fit(ny, 0, dy, &sum_x, &b, false);
02627
02628 for (int j = 0; j < ny; j++) {
02629 for (int i = 0; i < nx; i++) {
02630 data[i + j * nx] -= i * sum_x + j * mean_y + b;
02631 }
02632 }
02633
02634 image->update();
02635 }
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Definition at line 128 of file processor.cpp. |
1.3.9.1