aligner.cpp

Go to the documentation of this file.
00001 
00005 /*
00006  * Author: Steven Ludtke, 04/10/2003 (sludtke@bcm.edu)
00007  * Copyright (c) 2000-2006 Baylor College of Medicine
00008  *
00009  * This software is issued under a joint BSD/GNU license. You may use the
00010  * source code in this file under either license. However, note that the
00011  * complete EMAN2 and SPARX software packages have some GPL dependencies,
00012  * so you are responsible for compliance with the licenses of these packages
00013  * if you opt to use BSD licensing. The warranty disclaimer below holds
00014  * in either instance.
00015  *
00016  * This complete copyright notice must be included in any revised version of the
00017  * source code. Additional authorship citations may be added, but existing
00018  * author citations must be preserved.
00019  *
00020  * This program is free software; you can redistribute it and/or modify
00021  * it under the terms of the GNU General Public License as published by
00022  * the Free Software Foundation; either version 2 of the License, or
00023  * (at your option) any later version.
00024  *
00025  * This program is distributed in the hope that it will be useful,
00026  * but WITHOUT ANY WARRANTY; without even the implied warranty of
00027  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
00028  * GNU General Public License for more details.
00029  *
00030  * You should have received a copy of the GNU General Public License
00031  * along with this program; if not, write to the Free Software
00032  * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
00033  *
00034  * */
00035 #include "emfft.h"
00036 #include "cmp.h"
00037 #include "aligner.h"
00038 #include "averager.h"
00039 #include "emdata.h"
00040 #include "processor.h"
00041 #include "util.h"
00042 #include "symmetry.h"
00043 #include <gsl/gsl_multimin.h>
00044 #include "plugins/aligner_template.h"
00045 
00046 #ifdef EMAN2_USING_CUDA
00047         #include "cuda/cuda_processor.h"
00048         #include "cuda/cuda_cmp.h"
00049 #endif
00050 
00051 #ifdef SPARX_USING_CUDA
00052         #include <sparx/cuda/cuda_ccf.h>
00053 #endif
00054 
00055 #define EMAN2_ALIGNER_DEBUG 0
00056 
00057 using namespace EMAN;
00058 
00059 const string TranslationalAligner::NAME = "translational";
00060 const string RotationalAligner::NAME = "rotational";
00061 const string RotationalAlignerIterative::NAME = "rotational_iterative";
00062 const string RotatePrecenterAligner::NAME = "rotate_precenter";
00063 const string RotateTranslateAligner::NAME = "rotate_translate";
00064 const string RotateTranslateScaleAligner::NAME = "rotate_translate_scale";
00065 const string RotateTranslateAlignerIterative::NAME = "rotate_translate_iterative";
00066 const string RotateTranslateScaleAlignerIterative::NAME = "rotate_trans_scale_iter";
00067 const string RotateTranslateAlignerPawel::NAME = "rotate_translate_resample";
00068 const string RotateTranslateBestAligner::NAME = "rotate_translate_best";
00069 const string RotateFlipAligner::NAME = "rotate_flip";
00070 const string RotateFlipAlignerIterative::NAME = "rotate_flip_iterative";
00071 const string RotateTranslateFlipAligner::NAME = "rotate_translate_flip";
00072 const string RotateTranslateFlipScaleAligner::NAME = "rotate_trans_flip_scale";
00073 const string RotateTranslateFlipAlignerIterative::NAME = "rotate_translate_flip_iterative";
00074 const string RotateTranslateFlipScaleAlignerIterative::NAME = "rotate_trans_flip_scale_iter";
00075 const string RotateTranslateFlipAlignerPawel::NAME = "rotate_translate_flip_resample";
00076 const string RTFExhaustiveAligner::NAME = "rtf_exhaustive";
00077 const string RTFSlowExhaustiveAligner::NAME = "rtf_slow_exhaustive";
00078 const string RefineAligner::NAME = "refine";
00079 const string RefineAlignerCG::NAME = "refinecg";
00080 const string SymAlignProcessorQuat::NAME = "symalignquat";
00081 const string SymAlignProcessor::NAME = "symalign";
00082 const string Refine3DAlignerGrid::NAME = "refine_3d_grid";
00083 const string Refine3DAlignerQuaternion::NAME = "refine_3d";
00084 const string RT3DGridAligner::NAME = "rotate_translate_3d_grid";
00085 const string RT3DSphereAligner::NAME = "rotate_translate_3d";
00086 const string RT3DSymmetryAligner::NAME = "rotate_symmetry_3d";
00087 const string FRM2DAligner::NAME = "frm2d";
00088 const string ScaleAligner::NAME = "scale";
00089 
00090 
00091 template <> Factory < Aligner >::Factory()
00092 {
00093         force_add<TranslationalAligner>();
00094         force_add<RotationalAligner>();
00095         force_add<RotationalAlignerIterative>();
00096         force_add<RotatePrecenterAligner>();
00097         force_add<RotateTranslateAligner>();
00098         force_add<RotateTranslateScaleAligner>();
00099         force_add<RotateTranslateAlignerIterative>();
00100         force_add<RotateTranslateScaleAlignerIterative>();
00101         force_add<RotateTranslateAlignerPawel>();
00102         force_add<RotateFlipAligner>();
00103         force_add<RotateFlipAlignerIterative>();
00104         force_add<RotateTranslateFlipAligner>();
00105         force_add<RotateTranslateFlipScaleAligner>();
00106         force_add<RotateTranslateFlipAlignerIterative>();
00107         force_add<RotateTranslateFlipScaleAlignerIterative>();
00108         force_add<RotateTranslateFlipAlignerPawel>();
00109         force_add<RTFExhaustiveAligner>();
00110         force_add<RTFSlowExhaustiveAligner>();
00111         force_add<SymAlignProcessor>();
00112         force_add<RefineAligner>();
00113         force_add<RefineAlignerCG>();
00114         force_add<SymAlignProcessorQuat>();
00115         force_add<Refine3DAlignerGrid>();
00116         force_add<Refine3DAlignerQuaternion>();
00117         force_add<RT3DGridAligner>();
00118         force_add<RT3DSphereAligner>();
00119         force_add<RT3DSymmetryAligner>();
00120         force_add<FRM2DAligner>();
00121         force_add<ScaleAligner>();
00122 //      force_add<XYZAligner>();
00123 }
00124 
00125 vector<Dict> Aligner::xform_align_nbest(EMData *, EMData *, const unsigned int, const string &, const Dict&) const
00126 {
00127         vector<Dict> solns;
00128         return solns;
00129 }
00130 
00131 EMData* ScaleAlignerABS::align_using_base(EMData * this_img, EMData * to,
00132                         const string & cmp_name, const Dict& cmp_params) const
00133 {
00134         //get the scale range
00135         float min =  params.set_default("min",0.95f);
00136         float max = params.set_default("max",1.05f);
00137         float step = params.set_default("step",0.01f);
00138         
00139         // crate the starting transform
00140         Transform t = Transform();
00141         t.set_scale(max);
00142         
00143         //save orignal data
00144         float* oridata = this_img->get_data();
00145         
00146         //get the transform processor and cast to correct factory product
00147         Processor* proc = Factory <Processor>::get("xform", Dict());
00148         TransformProcessor* xform = dynamic_cast<TransformProcessor*>(proc);
00149         
00150         // Using the following method we only create one EMdata object. If I just used the processor, then I would create many EMdata objects
00151         EMData* result = 0;
00152 //      float bestscore = numeric_limits<float>::infinity();
00153         float bestscore = 1.0e37;
00154         
00155         for(float i = max; i > min; i-=step){
00156                 
00157                 //scale the image
00158                 float* des_data = xform->transform(this_img,t);
00159                 this_img->set_data(des_data);
00160                 this_img->update();
00161                 
00162                 //check compairsion
00163                 EMData* aligned = this_img->align(basealigner, to, basealigner_params, cmp_name, cmp_params);
00164                 float score = aligned->cmp(cmp_name, to, cmp_params);
00165                 if(score < bestscore){
00166                         bestscore = score;
00167                         //If we just reassign w/o cleaing up we will get memory leaks!
00168                         if(result != 0) delete result;
00169                         result = aligned;
00170                         result->set_attr("scalefactor",i);
00171                 }else{
00172                         delete aligned;
00173                 }
00174                 //clean up scaled image data
00175                 delete des_data;
00176 
00177                 t.set_scale(i);
00178                 
00179                 //reset original data
00180                 this_img->set_data(oridata);
00181         }       
00182         
00183         if (!result) throw UnexpectedBehaviorException("Alignment score is infinity! Something is seriously wrong with the data!");
00184         if (proc != 0) delete proc;
00185         
00186         return result;  
00187         
00188 };
00189 
00190 EMData* ScaleAligner::align(EMData * this_img, EMData *to,
00191                         const string& cmp_name, const Dict& cmp_params) const
00192 {
00193         
00194         //get the scale range
00195         float min =  params.set_default("min",0.95f);
00196         float max = params.set_default("max",1.05f);
00197         float step = params.set_default("step",0.01f);
00198         
00199         Transform t = Transform();
00200         t.set_scale(max);
00201         float* oridata = this_img->get_data();
00202         
00203         //get the transform processor and cast to correct factory product
00204         Processor* proc = Factory <Processor>::get("xform", Dict());
00205         TransformProcessor* xform = dynamic_cast<TransformProcessor*>(proc);
00206         
00207         // Using the following method we only create one EMdata object. If I just used the processor, then I would create many EMdata objects
00208         float bestscale = 1.0;
00209         float bestscore = 1.0e37;
00210 
00211         for(float i = max; i > min; i-=step){
00212                         
00213                 float* des_data = xform->transform(this_img,t);
00214                 this_img->set_data(des_data);
00215                 this_img->update();
00216                 
00217                 //check compairsion
00218                 float score = this_img->cmp(cmp_name, to, cmp_params);
00219                 if(score < bestscore){
00220                         bestscore = score;
00221                         bestscale = i;
00222                 }
00223                 //clean up scaled image data
00224                 delete des_data;
00225                 
00226                 t.set_scale(i);
00227                 
00228                 //reset original data
00229                 this_img->set_data(oridata);
00230         }
00231 
00232 
00233         
00234         //Return scaled image
00235         t.set_scale(bestscale);
00236         EMData* result = this_img->process("xform",Dict("transform",&t));
00237         result->set_attr("scalefactor",bestscale);
00238         if (proc != 0) delete proc;
00239         
00240         return result;
00241         
00242 }
00243 
00244 // Note, the translational aligner assumes that the correlation image
00245 // generated by the calc_ccf function is centered on the bottom left corner
00246 // That is, if you did at calc_cff using identical images, the
00247 // peak would be at 0,0
00248 EMData *TranslationalAligner::align(EMData * this_img, EMData *to,
00249                                         const string&, const Dict&) const
00250 {
00251         if (!this_img) {
00252                 return 0;
00253         }
00254 
00255         if (to && !EMUtil::is_same_size(this_img, to))
00256                 throw ImageDimensionException("Images must be the same size to perform translational alignment");
00257 
00258         EMData *cf = 0;
00259         int nx = this_img->get_xsize();
00260         int ny = this_img->get_ysize();
00261         int nz = this_img->get_zsize();
00262 
00263         int masked = params.set_default("masked",0);
00264         int useflcf = params.set_default("useflcf",0);
00265         bool use_cpu = true;
00266 
00267 #ifdef EMAN2_USING_CUDA
00268         if(EMData::usecuda == 1) {
00269                 //if(!this_img->getcudarwdata()) this_img->copy_to_cuda();
00270                 //if(to && !to->getcudarwdata()) to->copy_to_cuda();
00271                 //if (masked) throw UnexpectedBehaviorException("Masked is not yet supported in CUDA");
00272                 //if (useflcf) throw UnexpectedBehaviorException("Useflcf is not yet supported in CUDA");
00273                 //cout << "Translate on GPU" << endl;
00274                 //use_cpu = false;
00275                 //cf = this_img->calc_ccf(to);
00276         }
00277 #endif // EMAN2_USING_CUDA
00278         
00279         if (use_cpu) {
00280                 if (useflcf) cf = this_img->calc_flcf(to);
00281                 else cf = this_img->calc_ccf(to);
00282         }
00283         //return cf;
00284         // This is too expensive, esp for CUDA(we we can fix later
00285         if (masked) {
00286                 EMData *msk=this_img->process("threshold.notzero");
00287                 EMData *sqr=to->process("math.squared");
00288                 EMData *cfn=msk->calc_ccf(sqr);
00289                 cfn->process_inplace("math.sqrt");
00290                 float *d1=cf->get_data();
00291                 float *d2=cfn->get_data();
00292                 for (size_t i=0; i<(size_t)nx*ny*nz; ++i) {
00293                         if (d2[i]!=0) d1[i]/=d2[i];
00294                 }
00295                 cf->update();
00296                 delete msk;
00297                 delete sqr;
00298                 delete cfn;
00299         }
00300 
00301         int maxshiftx = params.set_default("maxshift",-1);
00302         int maxshifty = params["maxshift"];
00303         int maxshiftz = params["maxshift"];
00304         int nozero = params["nozero"];
00305 
00306         if (maxshiftx <= 0) {
00307                 maxshiftx = nx / 4;
00308                 maxshifty = ny / 4;
00309                 maxshiftz = nz / 4;
00310         }
00311 
00312         if (maxshiftx > nx / 2 - 1) maxshiftx = nx / 2 - 1;
00313         if (maxshifty > ny / 2 - 1)     maxshifty = ny / 2 - 1;
00314         if (maxshiftz > nz / 2 - 1) maxshiftz = nz / 2 - 1;
00315 
00316         if (nx == 1) maxshiftx = 0; // This is justhere for completeness really... plus it saves errors
00317         if (ny == 1) maxshifty = 0;
00318         if (nz == 1) maxshiftz = 0;
00319 
00320         // If nozero the portion of the image in the center (and its 8-connected neighborhood) is zeroed
00321         if (nozero) {
00322                 cf->zero_corner_circulant(1);
00323         }
00324         
00325         IntPoint peak;
00326 #ifdef EMAN2_USING_CUDA
00327         if (!use_cpu) {
00328                 cout << "USe CUDA TA 2" << endl;
00329                 if (nozero) throw UnexpectedBehaviorException("Nozero is not yet supported in CUDA");
00330                 CudaPeakInfo* data = calc_max_location_wrap_cuda(cf->getcudarwdata(), cf->get_xsize(), cf->get_ysize(), cf->get_zsize(), maxshiftx, maxshifty, maxshiftz);
00331                 peak = IntPoint(data->px,data->py,data->pz);
00332                 free(data);
00333         }
00334 #endif // EMAN2_USING_CUDA
00335         
00336         if (use_cpu) {
00337                 peak = cf->calc_max_location_wrap(maxshiftx, maxshifty, maxshiftz);
00338         }
00339         //cout << -peak[0] << " " << -peak[1] << " " << -peak[2] << endl;
00340         Vec3f cur_trans = Vec3f ( (float)-peak[0], (float)-peak[1], (float)-peak[2]);
00341         //cout << peak[0] << " " << peak[1] << endl;
00342 
00343         if (!to) {
00344                 cur_trans /= 2.0f; // If aligning theimage to itself then only go half way -
00345                 int intonly = params.set_default("intonly",false);
00346                 if (intonly) {
00347                         cur_trans[0] = floor(cur_trans[0] + 0.5f);
00348                         cur_trans[1] = floor(cur_trans[1] + 0.5f);
00349                         cur_trans[2] = floor(cur_trans[2] + 0.5f);
00350                 }
00351         }
00352 
00353         if( cf ){
00354                 delete cf;
00355                 cf = 0;
00356         }
00357         
00358         Dict params("trans",static_cast< vector<int> >(cur_trans));
00359         if (use_cpu){
00360                 cf=this_img->process("xform.translate.int",params);
00361         }
00362         Transform t;
00363         t.set_trans(cur_trans);
00364         
00365 #ifdef EMAN2_USING_CUDA
00366         if (!use_cpu) {
00367                 cout << "USe CUDA TA 3" << endl;
00368                 //this will work just fine....
00369                 cf = this_img->process("xform",Dict("transform",&t));
00370         }
00371 #endif // EMAN2_USING_CUDA
00372 
00373         if ( nz != 1 ) {
00374 //              Transform* t = get_set_align_attr("xform.align3d",cf,this_img);
00375 //              t->set_trans(cur_trans);
00376                 cf->set_attr("xform.align3d",&t);
00377         } else if ( ny != 1 ) {
00378                 //Transform* t = get_set_align_attr("xform.align2d",cf,this_img);
00379                 cur_trans[2] = 0; // just make sure of it
00380                 t.set_trans(cur_trans);
00381                 cf->set_attr("xform.align2d",&t);
00382         }
00383         return cf;
00384 }
00385 
00386 EMData * RotationalAligner::align_180_ambiguous(EMData * this_img, EMData * to, int rfp_mode,int zscore) {
00387 
00388         // Make translationally invariant rotational footprints
00389         EMData* this_img_rfp, * to_rfp;
00390         if (rfp_mode == 0) {
00391                 this_img_rfp = this_img->make_rotational_footprint_e1();
00392                 to_rfp = to->make_rotational_footprint_e1();
00393         } else if (rfp_mode == 1) {
00394                 this_img_rfp = this_img->make_rotational_footprint();
00395                 to_rfp = to->make_rotational_footprint();
00396         } else if (rfp_mode == 2) {
00397                 this_img_rfp = this_img->make_rotational_footprint_cmc();
00398                 to_rfp = to->make_rotational_footprint_cmc();
00399         } else {
00400                 throw InvalidParameterException("rfp_mode must be 0,1 or 2");
00401         }
00402         int this_img_rfp_nx = this_img_rfp->get_xsize();
00403 
00404         // Do row-wise correlation, returning a sum.
00405         EMData *cf = this_img_rfp->calc_ccfx(to_rfp, 0, this_img->get_ysize(),false,false,zscore);
00406 // cf->process_inplace("normalize");
00407 // cf->write_image("ralisum.hdf",-1);
00408 //      
00409 // EMData *cf2 = this_img_rfp->calc_ccfx(to_rfp, 0, this_img->get_ysize(),true);
00410 // cf2->write_image("ralistack.hdf",-1);
00411 // delete cf2;
00412 
00413         // Delete them, they're no longer needed
00414         delete this_img_rfp; this_img_rfp = 0;
00415         delete to_rfp; to_rfp = 0;
00416 
00417         // Now solve the rotational alignment by finding the max in the column sum
00418         float *data = cf->get_data();
00419         
00420         float peak = 0;
00421         int peak_index = 0;
00422         Util::find_max(data, this_img_rfp_nx, &peak, &peak_index);
00423 
00424         if( cf ) {
00425                 delete cf;
00426                 cf = 0;
00427         }
00428         float rot_angle = (float) (peak_index * 180.0f / this_img_rfp_nx);
00429 
00430         // Return the result
00431         Transform tmp(Dict("type","2d","alpha",rot_angle));
00432         cf=this_img->process("xform",Dict("transform",(Transform*)&tmp));
00433 //      Transform* t = get_set_align_attr("xform.align2d",cf,this_img);
00434 //      Dict d("type","2d","alpha",rot_angle);
00435 //      t->set_rotation(d);
00436         cf->set_attr("xform.align2d",&tmp);
00437         return cf;
00438 }
00439 
00440 EMData *RotationalAligner::align(EMData * this_img, EMData *to,
00441                         const string& cmp_name, const Dict& cmp_params) const
00442 {
00443         if (!to) throw InvalidParameterException("Can not rotational align - the image to align to is NULL");
00444         
00445 #ifdef EMAN2_USING_CUDA
00446         if(EMData::usecuda == 1) {
00447                 //if(!this_img->getcudarwdata()) this_img->copy_to_cuda();
00448                 //if(!to->getcudarwdata()) to->copy_to_cuda();
00449         }
00450 #endif
00451 
00452         // Perform 180 ambiguous alignment
00453         int rfp_mode = params.set_default("rfp_mode",2);
00454         int zscore = params.set_default("zscore",0);
00455         int ambig180 = params.set_default("ambig180",0);
00456         
00457         EMData* rot_aligned = RotationalAligner::align_180_ambiguous(this_img,to,rfp_mode,zscore);
00458         Transform * tmp = rot_aligned->get_attr("xform.align2d");
00459         Dict rot = tmp->get_rotation("2d");
00460         float rotate_angle_solution = rot["alpha"];
00461         delete tmp;
00462 
00463         // Don't resolve the 180 degree ambiguity here
00464         if (ambig180) {
00465                 return rot_aligned;
00466         }
00467         
00468         EMData *rot_align_180 = rot_aligned->process("math.rotate.180");
00469 
00470         // Generate the comparison metrics for both rotational candidates
00471         float rot_cmp = rot_aligned->cmp(cmp_name, to, cmp_params);
00472         float rot_180_cmp = rot_align_180->cmp(cmp_name, to, cmp_params);
00473 
00474         // Decide on the result
00475         float score = 0.0;
00476         EMData* result = NULL;
00477         if (rot_cmp < rot_180_cmp){
00478                 result = rot_aligned;
00479                 score = rot_cmp;
00480                 delete rot_align_180; rot_align_180 = 0;
00481         } else {
00482                 result = rot_align_180;
00483                 score = rot_180_cmp;
00484                 delete rot_aligned; rot_aligned = 0;
00485                 rotate_angle_solution = rotate_angle_solution-180.0f;
00486         }
00487 
00488 //      Transform* t = get_align_attr("xform.align2d",result);
00489 //      t->set_rotation(Dict("type","2d","alpha",rotate_angle_solution));
00490         Transform tmp2(Dict("type","2d","alpha",rotate_angle_solution));
00491         result->set_attr("xform.align2d",&tmp2);
00492         return result;
00493 }
00494 
00495 
00496 EMData *RotatePrecenterAligner::align(EMData * this_img, EMData *to,
00497                         const string&, const Dict&) const
00498 {
00499         if (!to) {
00500                 return 0;
00501         }
00502 
00503         int ny = this_img->get_ysize();
00504         int size = Util::calc_best_fft_size((int) (M_PI * ny * 1.5));
00505         EMData *e1 = this_img->unwrap(4, ny * 7 / 16, size, 0, 0, 1);
00506         EMData *e2 = to->unwrap(4, ny * 7 / 16, size, 0, 0, 1);
00507         EMData *cf = e1->calc_ccfx(e2, 0, ny);
00508 
00509         float *data = cf->get_data();
00510 
00511         float peak = 0;
00512         int peak_index = 0;
00513         Util::find_max(data, size, &peak, &peak_index);
00514         float a = (float) ((1.0f - 1.0f * peak_index / size) * 180. * 2);
00515 
00516         Transform rot;
00517         rot.set_rotation(Dict("type","2d","alpha",(float)(a*180./M_PI)));
00518         EMData* rslt = this_img->process("xform",Dict("transform",&rot));
00519         rslt->set_attr("xform.align2d",&rot);
00520 //
00521 //      Transform* t = get_set_align_attr("xform.align2d",rslt,this_img);
00522 //      t->set_rotation(Dict("type","2d","alpha",-a));
00523 //
00524 //      EMData* result this_img->transform(Dict("type","2d","alpha",(float)(a*180./M_PI)));
00525 //
00526 //      cf->set_attr("xform.align2d",t);
00527 //      delete t;
00528 //      cf->update();
00529 
00530         if( e1 )
00531         {
00532                 delete e1;
00533                 e1 = 0;
00534         }
00535 
00536         if( e2 )
00537         {
00538                 delete e2;
00539                 e2 = 0;
00540         }
00541 
00542         if (cf) {
00543                 delete cf;
00544                 cf = 0;
00545         }
00546         return rslt;
00547 }
00548 
00549 EMData *RotationalAlignerIterative::align(EMData * this_img, EMData *to,
00550                         const string &, const Dict&) const
00551 {
00552         int r1 = params.set_default("r1",-1);
00553         int r2 = params.set_default("r2",-1);
00554         //to start lest try the original size image. If needed, we can pad it....
00555         EMData * to_polar = to->unwrap(r1,r2,-1,0,0,true);
00556         EMData * this_img_polar = this_img->unwrap(r1,r2,-1,0,0,true);
00557         int this_img_polar_nx = this_img_polar->get_xsize();
00558         
00559         EMData * cf = this_img_polar->calc_ccfx(to_polar, 0, this_img->get_ysize());
00560         
00561         //take out the garbage
00562         delete to_polar; to_polar = 0;
00563         delete this_img_polar; this_img_polar = 0;
00564         
00565         float * data = cf->get_data();
00566         float peak = 0;
00567         int peak_index = 0;
00568         Util::find_max(data, this_img_polar_nx, &peak, &peak_index);
00569 
00570         delete cf; cf = 0;
00571         float rot_angle = (float) (peak_index * 360.0f / this_img_polar_nx);
00572         
00573         //return the result
00574         //cout << rot_angle << endl;
00575         Transform tmp(Dict("type","2d","alpha",rot_angle));
00576         EMData * rotimg=this_img->process("xform",Dict("transform",(Transform*)&tmp));
00577         rotimg->set_attr("xform.align2d",&tmp);
00578         
00579         return rotimg;
00580         
00581 }
00582 
00583 EMData *RotateTranslateAlignerIterative::align(EMData * this_img, EMData *to,
00584                         const string & cmp_name, const Dict& cmp_params) const
00585 {
00586         int maxiter = params.set_default("maxiter", 3);
00587         
00588         Dict trans_params;
00589         trans_params["intonly"] = 0;
00590         trans_params["maxshift"] = params.set_default("maxshift", -1);
00591         trans_params["useflcf"] = params.set_default("useflcf",0);
00592         trans_params["nozero"] = params.set_default("nozero",false);
00593         
00594         Dict rot_params;
00595         rot_params["r1"] = params.set_default("r1", -1);
00596         rot_params["r2"] = params.set_default("r2", -1);
00597         
00598         Transform t;
00599         EMData * moving_img = this_img;
00600         for(int it = 0; it < maxiter; it++){
00601                 
00602                 // First do a translational alignment
00603                 EMData * trans_align = moving_img->align("translational", to, trans_params, cmp_name, cmp_params);
00604                 Transform * tt = trans_align->get_attr("xform.align2d");
00605                 t = *tt*t;
00606                 delete tt;
00607 
00608                 //now do rotation
00609                 EMData * rottrans_align = trans_align->align("rotational_iterative", to, rot_params, cmp_name, cmp_params);
00610                 Transform * rt = rottrans_align->get_attr("xform.align2d");
00611                 t = *rt*t;
00612                 delete trans_align; trans_align = 0;
00613                 delete rottrans_align; rottrans_align = 0;
00614                 delete rt;
00615                 
00616                 //this minimizes interpolation errors (all images that are futher processed will be interpolated at most twice)
00617                 if(it > 0){delete moving_img;}
00618                 
00619                 moving_img = this_img->process("xform",Dict("transform",&t));  //iterate
00620         }
00621         
00622         //write the total transformation; Avoids interpolation erros    
00623         moving_img->set_attr("xform.align2d", &t);
00624         
00625         return moving_img;
00626 }
00627 
00628 EMData *RotateTranslateScaleAlignerIterative::align(EMData * this_img, EMData *to,
00629                         const string & cmp_name, const Dict& cmp_params) const
00630 {
00631         
00632         //Basically copy params into rotate_translate
00633         basealigner_params["maxshift"] = params.set_default("maxshift", -1);
00634         basealigner_params["r1"] = params.set_default("r1",-1);
00635         basealigner_params["r2"] = params.set_default("r2",-1);
00636         basealigner_params["maxiter"] = params.set_default("maxiter",3);
00637         basealigner_params["nozero"] = params.set_default("nozero",false);
00638         basealigner_params["useflcf"] = params.set_default("useflcf",0);
00639         
00640         //return the correct results
00641         return align_using_base(this_img, to, cmp_name, cmp_params);
00642         
00643 }
00644 
00645 EMData *RotateTranslateAlignerPawel::align(EMData * this_img, EMData *to,
00646                         const string & cmp_name, const Dict& cmp_params) const
00647 {
00648         if (cmp_name != "dot" && cmp_name != "ccc") throw InvalidParameterException("Resample aligner only works for dot and ccc");
00649         
00650         int maxtx = params.set_default("tx", 0);
00651         int maxty = params.set_default("ty", 0);
00652         int r1 = params.set_default("r1",-1);
00653         int r2 = params.set_default("r2",-1);
00654         
00655         if(this_img->get_xsize()/2 - 1 - r2 - maxtx <= 0 || (r2 == -1 && maxtx > 0)) throw InvalidParameterException("nx/2 - 1 - r2 - tx must be greater than or = 0");
00656         if(this_img->get_ysize()/2 - 1 - r2 - maxty <= 0 || (r2 == -1 && maxty > 0)) throw InvalidParameterException("ny/2 - 1 - r2 - ty must be greater than or = 0");
00657         
00658 //      float best_peak = -numeric_limits<float>::infinity();
00659         float best_peak = -1.0e37;
00660         int best_peak_index = 0;
00661         int best_tx = 0;
00662         int best_ty = 0;
00663         int polarxsize = 0;
00664                 
00665         for(int x = -maxtx; x <= maxtx; x++){
00666                 for(int y = -maxty; y <= maxty; y++){
00667 
00668                         EMData * to_polar = to->unwrap(r1,r2,-1,0,0,true);
00669                         EMData * this_img_polar = this_img->unwrap(r1,r2,-1,x,y,true);
00670                         EMData * cf = this_img_polar->calc_ccfx(to_polar, 0, this_img_polar->get_ysize());
00671                         
00672                         polarxsize = this_img_polar->get_xsize();
00673                         
00674                         //take out the garbage
00675                         delete to_polar; to_polar = 0;
00676                         delete this_img_polar; this_img_polar = 0;
00677         
00678                         float *data = cf->get_data();
00679                         float peak = 0;
00680                         int peak_index = 0;
00681                         Util::find_max(data, polarxsize, &peak, &peak_index);
00682                         delete cf; cf = 0;
00683 
00684                         if(peak > best_peak) {
00685                                 best_peak = peak;
00686                                 best_peak_index = peak_index;
00687                                 best_tx = x;
00688                                 best_ty = y;
00689                         }
00690                 }
00691         }
00692         
00693         float rot_angle = (float) (best_peak_index * 360.0f / polarxsize);
00694                                 
00695         //return the result
00696         Transform tmptt(Dict("type","2d","alpha",0,"tx",-best_tx,"ty",-best_ty));
00697         Transform tmprot(Dict("type","2d","alpha",rot_angle,"tx",0,"ty",0));
00698         Transform total = tmprot*tmptt;
00699         EMData* rotimg=this_img->process("xform",Dict("transform",(Transform*)&total));
00700         rotimg->set_attr("xform.align2d",&total);
00701         
00702         return rotimg;
00703         
00704 }
00705 
00706 EMData *RotateTranslateAligner::align(EMData * this_img, EMData *to,
00707                         const string & cmp_name, const Dict& cmp_params) const
00708 {
00709 
00710 #ifdef EMAN2_USING_CUDA
00711         if(EMData::usecuda == 1) {
00712                 //if(!this_img->getcudarwdata()) this_img->copy_to_cuda();
00713                 //if(!to->getcudarwdata()) to->copy_to_cuda();
00714         }
00715 #endif
00716 
00717         // Get the 180 degree ambiguously rotationally aligned and its 180 degree rotation counterpart
00718         int zscore = params.set_default("zscore",0);
00719         int rfp_mode = params.set_default("rfp_mode",2);
00720         EMData *rot_align  =  RotationalAligner::align_180_ambiguous(this_img,to,rfp_mode,zscore);
00721         Transform * tmp = rot_align->get_attr("xform.align2d");
00722         Dict rot = tmp->get_rotation("2d");
00723         float rotate_angle_solution = rot["alpha"];
00724         delete tmp;
00725 
00726         EMData *rot_align_180 = rot_align->process("math.rotate.180");
00727 
00728         Dict trans_params;
00729         trans_params["intonly"]  = 0;
00730         trans_params["maxshift"] = params.set_default("maxshift", -1);
00731         trans_params["useflcf"]=params.set_default("useflcf",0);
00732 
00733         // Do the first case translational alignment
00734         trans_params["nozero"]   = params.set_default("nozero",false);
00735         EMData* rot_trans = rot_align->align("translational", to, trans_params, cmp_name, cmp_params);
00736         if( rot_align ) { // Clean up
00737                 delete rot_align;
00738                 rot_align = 0;
00739         }
00740 
00741         // Do the second case translational alignment
00742         EMData*  rot_180_trans = rot_align_180->align("translational", to, trans_params, cmp_name, cmp_params);
00743         if( rot_align_180 )     { // Clean up
00744                 delete rot_align_180;
00745                 rot_align_180 = 0;
00746         }
00747 
00748         // Finally decide on the result
00749         float cmp1 = rot_trans->cmp(cmp_name, to, cmp_params);
00750         float cmp2 = rot_180_trans->cmp(cmp_name, to, cmp_params);
00751 
00752         EMData *result = 0;
00753         if (cmp1 < cmp2) { // All comparators are defined so default return is "smaller is better"
00754                 if( rot_180_trans )     {
00755                         delete rot_180_trans;
00756                         rot_180_trans = 0;
00757                 }
00758                 result = rot_trans;
00759         }
00760         else {
00761                 if( rot_trans ) {
00762                         delete rot_trans;
00763                         rot_trans = 0;
00764                 }
00765                 result = rot_180_trans;
00766                 rotate_angle_solution -= 180.f;
00767         }
00768 
00769         Transform* t = result->get_attr("xform.align2d");
00770         t->set_rotation(Dict("type","2d","alpha",rotate_angle_solution));
00771         result->set_attr("xform.align2d",t);
00772         delete t;
00773 
00774         return result;
00775 }
00776 
00777 
00778 EMData *RotateTranslateScaleAligner::align(EMData * this_img, EMData *to,
00779                         const string & cmp_name, const Dict& cmp_params) const
00780 {
00781         
00782         //Basically copy params into rotate_translate
00783         basealigner_params["maxshift"] = params.set_default("maxshift", -1);
00784         basealigner_params["rfp_mode"] = params.set_default("rfp_mode",2);
00785         basealigner_params["useflcf"] = params.set_default("useflcf",0);
00786         basealigner_params["zscore"] = params.set_default("zscore",0);
00787         
00788         //return the correct results
00789         return align_using_base(this_img, to, cmp_name, cmp_params);
00790         
00791 }
00792 
00793 EMData* RotateTranslateFlipAligner::align(EMData * this_img, EMData *to,
00794                                                                                   const string & cmp_name, const Dict& cmp_params) const
00795 {
00796         // Get the non flipped rotational, tranlsationally aligned image
00797         Dict rt_params("maxshift", params["maxshift"], "rfp_mode", params.set_default("rfp_mode",2),"useflcf",params.set_default("useflcf",0),"zscore",params.set_default("zscore",0));
00798         EMData *rot_trans_align = this_img->align("rotate_translate",to,rt_params,cmp_name, cmp_params);
00799         
00800         // Do the same alignment, but using the flipped version of the image
00801         EMData *flipped = params.set_default("flip", (EMData *) 0);
00802         bool delete_flag = false;
00803         if (flipped == 0) {
00804                 flipped = to->process("xform.flip", Dict("axis", "x"));
00805                 delete_flag = true;
00806         }
00807 
00808         EMData * rot_trans_align_flip = this_img->align("rotate_translate", flipped, rt_params, cmp_name, cmp_params);
00809         Transform * t = rot_trans_align_flip->get_attr("xform.align2d");
00810         t->set_mirror(true);
00811         rot_trans_align_flip->set_attr("xform.align2d",t);
00812         delete t;
00813 
00814         // Now finally decide on what is the best answer
00815         float cmp1 = rot_trans_align->cmp(cmp_name, to, cmp_params);
00816         float cmp2 = rot_trans_align_flip->cmp(cmp_name, flipped, cmp_params);
00817 
00818         if (delete_flag){
00819                 if(flipped) {
00820                         delete flipped;
00821                         flipped = 0;
00822                 }
00823         }
00824 
00825         EMData *result = 0;
00826         if (cmp1 < cmp2 )  {
00827 
00828                 if( rot_trans_align_flip ) {
00829                         delete rot_trans_align_flip;
00830                         rot_trans_align_flip = 0;
00831                 }
00832                 result = rot_trans_align;
00833         }
00834         else {
00835                 if( rot_trans_align ) {
00836                         delete rot_trans_align;
00837                         rot_trans_align = 0;
00838                 }
00839                 result = rot_trans_align_flip;
00840                 result->process_inplace("xform.flip",Dict("axis","x"));
00841         }
00842 
00843         return result;
00844 }
00845 
00846 EMData *RotateTranslateFlipScaleAligner::align(EMData * this_img, EMData *to,
00847                         const string & cmp_name, const Dict& cmp_params) const
00848 {
00849         
00850         //Basically copy params into rotate_translate
00851         basealigner_params["flip"] = params.set_default("flip", (EMData *) 0);
00852         basealigner_params["maxshift"] = params.set_default("maxshift", -1);
00853         basealigner_params["rfp_mode"] = params.set_default("rfp_mode",2);
00854         basealigner_params["useflcf"] = params.set_default("useflcf",0);
00855         basealigner_params["zscore"] = params.set_default("zscore",0);
00856         
00857         //return the correct results
00858         return align_using_base(this_img, to, cmp_name, cmp_params);
00859         
00860 }
00861 
00862 EMData* RotateTranslateFlipAlignerIterative::align(EMData * this_img, EMData *to,
00863                                                                                   const string & cmp_name, const Dict& cmp_params) const
00864 {
00865         // Get the non flipped rotational, tranlsationally aligned image
00866         Dict rt_params("maxshift", params["maxshift"],"r1",params.set_default("r1",-1),"r2",params.set_default("r2",-1));
00867         EMData *rot_trans_align = this_img->align("rotate_translate_iterative",to,rt_params,cmp_name, cmp_params);
00868 
00869         // Do the same alignment, but using the flipped version of the image
00870         EMData *flipped = params.set_default("flip", (EMData *) 0);
00871         bool delete_flag = false;
00872         if (flipped == 0) {
00873                 flipped = to->process("xform.flip", Dict("axis", "x"));
00874                 delete_flag = true;
00875         }
00876 
00877         EMData * rot_trans_align_flip = this_img->align("rotate_translate_iterative", flipped, rt_params, cmp_name, cmp_params);
00878         Transform* t = rot_trans_align_flip->get_attr("xform.align2d");
00879         t->set_mirror(true);
00880         rot_trans_align_flip->set_attr("xform.align2d",t);
00881         delete t;
00882 
00883         // Now finally decide on what is the best answer
00884         float cmp1 = rot_trans_align->cmp(cmp_name, to, cmp_params);
00885         float cmp2 = rot_trans_align_flip->cmp(cmp_name, flipped, cmp_params);
00886 
00887         if (delete_flag){
00888                 if(flipped) {
00889                         delete flipped;
00890                         flipped = 0;
00891                 }
00892         }
00893 
00894         EMData *result = 0;
00895         if (cmp1 < cmp2 )  {
00896 
00897                 if( rot_trans_align_flip ) {
00898                         delete rot_trans_align_flip;
00899                         rot_trans_align_flip = 0;
00900                 }
00901                 result = rot_trans_align;
00902         }
00903         else {
00904                 if( rot_trans_align ) {
00905                         delete rot_trans_align;
00906                         rot_trans_align = 0;
00907                 }
00908                 result = rot_trans_align_flip;
00909                 result->process_inplace("xform.flip",Dict("axis","x"));
00910         }
00911 
00912         return result;
00913 }
00914 
00915 EMData *RotateTranslateFlipScaleAlignerIterative::align(EMData * this_img, EMData *to,
00916                         const string & cmp_name, const Dict& cmp_params) const
00917 {
00918         
00919         //Basically copy params into rotate_translate
00920         basealigner_params["flip"] = params.set_default("flip", (EMData *) 0);
00921         basealigner_params["maxshift"] = params.set_default("maxshift", -1);
00922         basealigner_params["r1"] = params.set_default("r1",-1);
00923         basealigner_params["r2"] = params.set_default("r2",-1);
00924         basealigner_params["maxiter"] = params.set_default("maxiter",3);
00925         
00926         //return the correct results
00927         return align_using_base(this_img, to, cmp_name, cmp_params);
00928         
00929 }
00930 
00931 EMData *RotateTranslateFlipAlignerPawel::align(EMData * this_img, EMData *to,
00932                         const string & cmp_name, const Dict& cmp_params) const
00933 {
00934         if (cmp_name != "dot" && cmp_name != "ccc") throw InvalidParameterException("Resample aligner only works for dot and ccc");
00935         
00936         int maxtx = params.set_default("tx", 0);
00937         int maxty = params.set_default("ty", 0);
00938         int r1 = params.set_default("r1",-1);
00939         int r2 = params.set_default("r2",-1);
00940         
00941         if(this_img->get_xsize()/2 - 1 - r2 - maxtx <= 0 || (r2 == -1 && maxtx > 0)){
00942                 cout << "\nRunTimeError: nx/2 - 1 - r2 - tx must be greater than or = 0\n" << endl; // For some reason the expection message is not being print, stupid C++
00943                 throw InvalidParameterException("nx/2 - 1 - r2 - tx must be greater than or = 0");
00944         }
00945         if(this_img->get_ysize()/2 - 1 - r2 - maxty <= 0 || (r2 == -1 && maxty > 0)){
00946                 cout << "\nRunTimeError:ny/2 - 1 - r2 - ty must be greater than or = 0\n" << endl; // For some reason the expection message is not being print, stupid C++
00947                 throw InvalidParameterException("ny/2 - 1 - r2 - ty must be greater than or = 0");
00948         }
00949         
00950 //      float best_peak = -numeric_limits<float>::infinity();
00951         float best_peak = -1.0e37;
00952         int best_peak_index = 0;
00953         int best_tx = 0;
00954         int best_ty = 0;
00955         int polarxsize = 0;
00956         bool flip = false;
00957         
00958         for(int x = -maxtx; x <= maxtx; x++){
00959                 for(int y = -maxty; y <= maxty; y++){
00960 
00961                         EMData * to_polar = to->unwrap(r1,r2,-1,0,0,true);
00962                         EMData * this_img_polar = this_img->unwrap(r1,r2,-1,x,y,true);
00963                         EMData * cfflip = this_img_polar->calc_ccfx(to_polar, 0, this_img_polar->get_ysize(), false, true);
00964                         EMData * cf = this_img_polar->calc_ccfx(to_polar, 0, this_img_polar->get_ysize());
00965                         
00966                         polarxsize = this_img_polar->get_xsize();
00967                         
00968                         //take out the garbage
00969                         delete to_polar; to_polar = 0;
00970                         delete this_img_polar; this_img_polar = 0;
00971         
00972                         float *data = cf->get_data();
00973                         float peak = 0;
00974                         int peak_index = 0;
00975                         Util::find_max(data, polarxsize, &peak, &peak_index);
00976                         delete cf; cf = 0;
00977 
00978                         if(peak > best_peak) {
00979                                 best_peak = peak;
00980                                 best_peak_index = peak_index;
00981                                 best_tx = x;
00982                                 best_ty = y;
00983                                 flip = false;
00984                         }
00985                         
00986                         data = cfflip->get_data();
00987                         Util::find_max(data, polarxsize, &peak, &peak_index);
00988                         delete cfflip; cfflip = 0;
00989 
00990                         if(peak > best_peak) {
00991                                 best_peak = peak;
00992                                 best_peak_index = peak_index;
00993                                 best_tx = x;
00994                                 best_ty = y;
00995                                 flip = true;
00996                         }
00997                 }
00998         }
00999         
01000         float rot_angle = (float) (best_peak_index * 360.0f / polarxsize);
01001                                 
01002         //return the result
01003         Transform tmptt(Dict("type","2d","alpha",0,"tx",-best_tx,"ty",-best_ty));
01004         Transform tmprot(Dict("type","2d","alpha",rot_angle,"tx",0,"ty",0));
01005         Transform total = tmprot*tmptt;
01006         EMData * rotimg=this_img->process("xform",Dict("transform",(Transform*)&total));
01007         rotimg->set_attr("xform.align2d",&total);
01008         if(flip == true) {
01009                 rotimg->process_inplace("xform.flip",Dict("axis", "x"));
01010         }
01011         
01012         return rotimg;
01013         
01014 }
01015 
01016 EMData *RotateFlipAligner::align(EMData * this_img, EMData *to,
01017                         const string& cmp_name, const Dict& cmp_params) const
01018 {
01019         Dict rot_params("rfp_mode",params.set_default("rfp_mode",2));
01020         EMData *r1 = this_img->align("rotational", to, rot_params,cmp_name, cmp_params);
01021 
01022 
01023         EMData* flipped =to->process("xform.flip", Dict("axis", "x"));
01024         EMData *r2 = this_img->align("rotational", flipped,rot_params, cmp_name, cmp_params);
01025         Transform* t = r2->get_attr("xform.align2d");
01026         t->set_mirror(true);
01027         r2->set_attr("xform.align2d",t);
01028         delete t;
01029 
01030         float cmp1 = r1->cmp(cmp_name, to, cmp_params);
01031         float cmp2 = r2->cmp(cmp_name, flipped, cmp_params);
01032 
01033         delete flipped; flipped = 0;
01034 
01035         EMData *result = 0;
01036 
01037         if (cmp1 < cmp2) {
01038                 if( r2 )
01039                 {
01040                         delete r2;
01041                         r2 = 0;
01042                 }
01043                 result = r1;
01044         }
01045         else {
01046                 if( r1 )
01047                 {
01048                         delete r1;
01049                         r1 = 0;
01050                 }
01051                 result = r2;
01052                 result->process_inplace("xform.flip",Dict("axis","x"));
01053         }
01054 
01055         return result;
01056 }
01057 
01058 EMData *RotateFlipAlignerIterative::align(EMData * this_img, EMData *to,
01059                         const string& cmp_name, const Dict& cmp_params) const
01060 {
01061         Dict rot_params("r1",params.set_default("r1",-1),"r2",params.set_default("r2",-1));
01062         EMData * r1 = this_img->align("rotational_iterative", to, rot_params,cmp_name, cmp_params);
01063 
01064         EMData * flipped =to->process("xform.flip", Dict("axis", "x"));
01065         EMData * r2 = this_img->align("rotational_iterative", flipped,rot_params, cmp_name, cmp_params);
01066         Transform* t = r2->get_attr("xform.align2d");
01067         t->set_mirror(true);
01068         r2->set_attr("xform.align2d",t);
01069         delete t;
01070 
01071         float cmp1 = r1->cmp(cmp_name, to, cmp_params);
01072         float cmp2 = r2->cmp(cmp_name, flipped, cmp_params);
01073 
01074         delete flipped; flipped = 0;
01075 
01076         EMData *result = 0;
01077 
01078         if (cmp1 < cmp2) {
01079                 if( r2 )
01080                 {
01081                         delete r2;
01082                         r2 = 0;
01083                 }
01084                 result = r1;
01085         }
01086         else {
01087                 if( r1 )
01088                 {
01089                         delete r1;
01090                         r1 = 0;
01091                 }
01092                 result = r2;
01093                 result->process_inplace("xform.flip",Dict("axis","x"));
01094         }
01095 
01096         return result;
01097 }
01098 
01099 // David Woolford says FIXME
01100 // You will note the excessive amount of EMData copying that's going in this function
01101 // This is because functions that are operating on the EMData objects are changing them
01102 // and if you do not use copies the whole algorithm breaks. I did not have time to go
01103 // through and rectify this situation.
01104 // David Woolford says - this problem is related to the fact that many functions that
01105 // take EMData pointers as arguments do not take them as constant pointers to constant
01106 // objects, instead they are treated as raw (completely changeable) pointers. This means
01107 // it's hard to track down which functions are changing the EMData objects, because they
01108 // all do (in name). If this behavior is unavoidable then ignore this comment, however if possible it would
01109 // be good to make things const as much as possible. For example in alignment, technically
01110 // the argument EMData objects (raw pointers) should not be altered... should they?
01111 //
01112 // But const can be very annoying sometimes...
01113 EMData *RTFExhaustiveAligner::align(EMData * this_img, EMData *to,
01114                         const string & cmp_name, const Dict& cmp_params) const
01115 {
01116         EMData *flip = params.set_default("flip", (EMData *) 0);
01117         int maxshift = params.set_default("maxshift", this_img->get_xsize()/8);
01118         if (maxshift < 2) throw InvalidParameterException("maxshift must be greater than or equal to 2");
01119 
01120         int ny = this_img->get_ysize();
01121         int xst = (int) floor(2 * M_PI * ny);
01122         xst = Util::calc_best_fft_size(xst);
01123 
01124         Dict d("n",2);
01125         EMData *to_shrunk_unwrapped = to->process("math.medianshrink",d);
01126 
01127         int to_copy_r2 = to_shrunk_unwrapped->get_ysize() / 2 - 2 - maxshift / 2;
01128         EMData *tmp = to_shrunk_unwrapped->unwrap(4, to_copy_r2, xst / 2, 0, 0, true);
01129         if( to_shrunk_unwrapped )
01130         {
01131                 delete to_shrunk_unwrapped;
01132                 to_shrunk_unwrapped = 0;
01133         }
01134         to_shrunk_unwrapped = tmp;
01135 
01136         EMData *to_shrunk_unwrapped_copy = to_shrunk_unwrapped->copy();
01137         EMData* to_unwrapped = to->unwrap(4, to->get_ysize() / 2 - 2 - maxshift, xst, 0, 0, true);
01138         EMData *to_unwrapped_copy = to_unwrapped->copy();
01139 
01140         bool delete_flipped = true;
01141         EMData *flipped = 0;
01142         if (flip) {
01143                 delete_flipped = false;
01144                 flipped = flip;
01145         }
01146         else {
01147                 flipped = to->process("xform.flip", Dict("axis", "x"));
01148         }
01149         EMData *to_shrunk_flipped_unwrapped = flipped->process("math.medianshrink",d);
01150         tmp = to_shrunk_flipped_unwrapped->unwrap(4, to_copy_r2, xst / 2, 0, 0, true);
01151         if( to_shrunk_flipped_unwrapped )
01152         {
01153                 delete to_shrunk_flipped_unwrapped;
01154                 to_shrunk_flipped_unwrapped = 0;
01155         }
01156         to_shrunk_flipped_unwrapped = tmp;
01157         EMData *to_shrunk_flipped_unwrapped_copy = to_shrunk_flipped_unwrapped->copy();
01158         EMData* to_flip_unwrapped = flipped->unwrap(4, to->get_ysize() / 2 - 2 - maxshift, xst, 0, 0, true);
01159         EMData* to_flip_unwrapped_copy = to_flip_unwrapped->copy();
01160 
01161         if (delete_flipped && flipped != 0) {
01162                 delete flipped;
01163                 flipped = 0;
01164         }
01165 
01166         EMData *this_shrunk_2 = this_img->process("math.medianshrink",d);
01167 
01168         float bestval = FLT_MAX;
01169         float bestang = 0;
01170         int bestflip = 0;
01171         float bestdx = 0;
01172         float bestdy = 0;
01173 
01174         int half_maxshift = maxshift / 2;
01175 
01176         int ur2 = this_shrunk_2->get_ysize() / 2 - 2 - half_maxshift;
01177         for (int dy = -half_maxshift; dy <= half_maxshift; dy += 1) {
01178                 for (int dx = -half_maxshift; dx <= half_maxshift; dx += 1) {
01179 #ifdef  _WIN32
01180                         if (_hypot(dx, dy) <= half_maxshift) {
01181 #else
01182                         if (hypot(dx, dy) <= half_maxshift) {
01183 #endif
01184                                 EMData *uw = this_shrunk_2->unwrap(4, ur2, xst / 2, dx, dy, true);
01185                                 EMData *uwc = uw->copy();
01186                                 EMData *a = uw->calc_ccfx(to_shrunk_unwrapped);
01187 
01188                                 uwc->rotate_x(a->calc_max_index());
01189                                 float cm = uwc->cmp(cmp_name, to_shrunk_unwrapped_copy, cmp_params);
01190                                 if (cm < bestval) {
01191                                         bestval = cm;
01192                                         bestang = (float) (2.0 * M_PI * a->calc_max_index() / a->get_xsize());
01193                                         bestdx = (float)dx;
01194                                         bestdy = (float)dy;
01195                                         bestflip = 0;
01196                                 }
01197 
01198 
01199                                 if( a )
01200                                 {
01201                                         delete a;
01202                                         a = 0;
01203                                 }
01204                                 if( uw )
01205                                 {
01206                                         delete uw;
01207                                         uw = 0;
01208                                 }
01209                                 if( uwc )
01210                                 {
01211                                         delete uwc;
01212                                         uwc = 0;
01213                                 }
01214                                 uw = this_shrunk_2->unwrap(4, ur2, xst / 2, dx, dy, true);
01215                                 uwc = uw->copy();
01216                                 a = uw->calc_ccfx(to_shrunk_flipped_unwrapped);
01217 
01218                                 uwc->rotate_x(a->calc_max_index());
01219                                 cm = uwc->cmp(cmp_name, to_shrunk_flipped_unwrapped_copy, cmp_params);
01220                                 if (cm < bestval) {
01221                                         bestval = cm;
01222                                         bestang = (float) (2.0 * M_PI * a->calc_max_index() / a->get_xsize());
01223                                         bestdx = (float)dx;
01224                                         bestdy = (float)dy;
01225                                         bestflip = 1;
01226                                 }
01227 
01228                                 if( a )
01229                                 {
01230                                         delete a;
01231                                         a = 0;
01232                                 }
01233 
01234                                 if( uw )
01235                                 {
01236                                         delete uw;
01237                                         uw = 0;
01238                                 }
01239                                 if( uwc )
01240                                 {
01241                                         delete uwc;
01242                                         uwc = 0;
01243                                 }
01244                         }
01245                 }
01246         }
01247         if( this_shrunk_2 )
01248         {
01249                 delete this_shrunk_2;
01250                 this_shrunk_2 = 0;
01251         }
01252         if( to_shrunk_unwrapped )
01253         {
01254                 delete to_shrunk_unwrapped;
01255                 to_shrunk_unwrapped = 0;
01256         }
01257         if( to_shrunk_unwrapped_copy )
01258         {
01259                 delete to_shrunk_unwrapped_copy;
01260                 to_shrunk_unwrapped_copy = 0;
01261         }
01262         if( to_shrunk_flipped_unwrapped )
01263         {
01264                 delete to_shrunk_flipped_unwrapped;
01265                 to_shrunk_flipped_unwrapped = 0;
01266         }
01267         if( to_shrunk_flipped_unwrapped_copy )
01268         {
01269                 delete to_shrunk_flipped_unwrapped_copy;
01270                 to_shrunk_flipped_unwrapped_copy = 0;
01271         }
01272         bestdx *= 2;
01273         bestdy *= 2;
01274         bestval = FLT_MAX;
01275 
01276         float bestdx2 = bestdx;
01277         float bestdy2 = bestdy;
01278         // Note I tried steps less than 1.0 (sub pixel precision) and it actually appeared detrimental
01279         // So my advice is to stick with dx += 1.0 etc unless you really are looking to fine tune this
01280         // algorithm
01281         for (float dy = bestdy2 - 3; dy <= bestdy2 + 3; dy += 1.0 ) {
01282                 for (float dx = bestdx2 - 3; dx <= bestdx2 + 3; dx += 1.0 ) {
01283 
01284 #ifdef  _WIN32
01285                         if (_hypot(dx, dy) <= maxshift) {
01286 #else
01287                         if (hypot(dx, dy) <= maxshift) {
01288 #endif
01289                                 EMData *uw = this_img->unwrap(4, this_img->get_ysize() / 2 - 2 - maxshift, xst, (int)dx, (int)dy, true);
01290                                 EMData *uwc = uw->copy();
01291                                 EMData *a = uw->calc_ccfx(to_unwrapped);
01292 
01293                                 uwc->rotate_x(a->calc_max_index());
01294                                 float cm = uwc->cmp(cmp_name, to_unwrapped_copy, cmp_params);
01295 
01296                                 if (cm < bestval) {
01297                                         bestval = cm;
01298                                         bestang = (float)(2.0 * M_PI * a->calc_max_index() / a->get_xsize());
01299                                         bestdx = dx;
01300                                         bestdy = dy;
01301                                         bestflip = 0;
01302                                 }
01303 
01304                                 if( a )
01305                                 {
01306                                         delete a;
01307                                         a = 0;
01308                                 }
01309                                 if( uw )
01310                                 {
01311                                         delete uw;
01312                                         uw = 0;
01313                                 }
01314                                 if( uwc )
01315                                 {
01316                                         delete uwc;
01317                                         uwc = 0;
01318                                 }
01319                                 uw = this_img->unwrap(4, this_img->get_ysize() / 2 - 2 - maxshift, xst, (int)dx, (int)dy, true);
01320                                 uwc = uw->copy();
01321                                 a = uw->calc_ccfx(to_flip_unwrapped);
01322 
01323                                 uwc->rotate_x(a->calc_max_index());
01324                                 cm = uwc->cmp(cmp_name, to_flip_unwrapped_copy, cmp_params);
01325 
01326                                 if (cm < bestval) {
01327                                         bestval = cm;
01328                                         bestang = (float)(2.0 * M_PI * a->calc_max_index() / a->get_xsize());
01329                                         bestdx = dx;
01330                                         bestdy = dy;
01331                                         bestflip = 1;
01332                                 }
01333 
01334                                 if( a )
01335                                 {
01336                                         delete a;
01337                                         a = 0;
01338                                 }
01339                                 if( uw )
01340                                 {
01341                                         delete uw;
01342                                         uw = 0;
01343                                 }
01344                                 if( uwc )
01345                                 {
01346                                         delete uwc;
01347                                         uwc = 0;
01348                                 }
01349                         }
01350                 }
01351         }
01352         if( to_unwrapped ) {delete to_unwrapped;to_unwrapped = 0;}
01353         if( to_shrunk_unwrapped ) {     delete to_shrunk_unwrapped;     to_shrunk_unwrapped = 0;}
01354         if (to_unwrapped_copy) { delete to_unwrapped_copy; to_unwrapped_copy = 0; }
01355         if (to_flip_unwrapped) { delete to_flip_unwrapped; to_flip_unwrapped = 0; }
01356         if (to_flip_unwrapped_copy) { delete to_flip_unwrapped_copy; to_flip_unwrapped_copy = 0;}
01357 
01358         bestang *= (float)EMConsts::rad2deg;
01359         Transform t(Dict("type","2d","alpha",(float)bestang));
01360         t.set_pre_trans(Vec2f(-bestdx,-bestdy));
01361         if (bestflip) {
01362                 t.set_mirror(true);
01363         }
01364 
01365         EMData* ret = this_img->process("xform",Dict("transform",&t));
01366         ret->set_attr("xform.align2d",&t);
01367 
01368         return ret;
01369 }
01370 
01371 
01372 EMData *RTFSlowExhaustiveAligner::align(EMData * this_img, EMData *to,
01373                         const string & cmp_name, const Dict& cmp_params) const
01374 {
01375 
01376         EMData *flip = params.set_default("flip", (EMData *) 0);
01377         int maxshift = params.set_default("maxshift", -1);
01378 
01379         EMData *flipped = 0;
01380 
01381         bool delete_flipped = true;
01382         if (flip) {
01383                 delete_flipped = false;
01384                 flipped = flip;
01385         }
01386         else {
01387                 flipped = to->process("xform.flip", Dict("axis", "x"));
01388         }
01389 
01390         int nx = this_img->get_xsize();
01391 
01392         if (maxshift < 0) {
01393                 maxshift = nx / 10;
01394         }
01395 
01396         float angle_step =  params.set_default("angstep", 0.0f);
01397         if ( angle_step == 0 ) angle_step = atan2(2.0f, (float)nx);
01398         else {
01399                 angle_step *= (float)EMConsts::deg2rad; //convert to radians
01400         }
01401         float trans_step =  params.set_default("transtep",1.0f);
01402 
01403         if (trans_step <= 0) throw InvalidParameterException("transstep must be greater than 0");
01404         if (angle_step <= 0) throw InvalidParameterException("angstep must be greater than 0");
01405 
01406 
01407         Dict shrinkfactor("n",2);
01408         EMData *this_img_shrink = this_img->process("math.medianshrink",shrinkfactor);
01409         EMData *to_shrunk = to->process("math.medianshrink",shrinkfactor);
01410         EMData *flipped_shrunk = flipped->process("math.medianshrink",shrinkfactor);
01411 
01412         int bestflip = 0;
01413         float bestdx = 0;
01414         float bestdy = 0;
01415 
01416         float bestang = 0;
01417         float bestval = FLT_MAX;
01418 
01419         int half_maxshift = maxshift / 2;
01420 
01421 
01422         for (int dy = -half_maxshift; dy <= half_maxshift; ++dy) {
01423                 for (int dx = -half_maxshift; dx <= half_maxshift; ++dx) {
01424                         if (hypot(dx, dy) <= maxshift) {
01425                                 for (float ang = -angle_step * 2.0f; ang <= (float)2 * M_PI; ang += angle_step * 4.0f) {
01426                                         EMData v(*this_img_shrink);
01427                                         Transform t(Dict("type","2d","alpha",static_cast<float>(ang*EMConsts::rad2deg)));
01428                                         t.set_trans((float)dx,(float)dy);
01429                                         v.transform(t);
01430 //                                      v.rotate_translate(ang*EMConsts::rad2deg, 0.0f, 0.0f, (float)dx, (float)dy, 0.0f);
01431 
01432                                         float lc = v.cmp(cmp_name, to_shrunk, cmp_params);
01433 
01434                                         if (lc < bestval) {
01435                                                 bestval = lc;
01436                                                 bestang = ang;
01437                                                 bestdx = (float)dx;
01438                                                 bestdy = (float)dy;
01439                                                 bestflip = 0;
01440                                         }
01441 
01442                                         lc = v.cmp(cmp_name,flipped_shrunk , cmp_params);
01443                                         if (lc < bestval) {
01444                                                 bestval = lc;
01445                                                 bestang = ang;
01446                                                 bestdx = (float)dx;
01447                                                 bestdy = (float)dy;
01448                                                 bestflip = 1;
01449                                         }
01450                                 }
01451                         }
01452                 }
01453         }
01454 
01455         if( to_shrunk )
01456         {
01457                 delete to_shrunk;
01458                 to_shrunk = 0;
01459         }
01460         if( flipped_shrunk )
01461         {
01462                 delete flipped_shrunk;
01463                 flipped_shrunk = 0;
01464         }
01465         if( this_img_shrink )
01466         {
01467                 delete this_img_shrink;
01468                 this_img_shrink = 0;
01469         }
01470 
01471         bestdx *= 2;
01472         bestdy *= 2;
01473         bestval = FLT_MAX;
01474 
01475         float bestdx2 = bestdx;
01476         float bestdy2 = bestdy;
01477         float bestang2 = bestang;
01478 
01479         for (float dy = bestdy2 - 3; dy <= bestdy2 + 3; dy += trans_step) {
01480                 for (float dx = bestdx2 - 3; dx <= bestdx2 + 3; dx += trans_step) {
01481                         if (hypot(dx, dy) <= maxshift) {
01482                                 for (float ang = bestang2 - angle_step * 6.0f; ang <= bestang2 + angle_step * 6.0f; ang += angle_step) {
01483                                         EMData v(*this_img);
01484                                         Transform t(Dict("type","2d","alpha",static_cast<float>(ang*EMConsts::rad2deg)));
01485                                         t.set_trans(dx,dy);
01486                                         v.transform(t);
01487 //                                      v.rotate_translate(ang*EMConsts::rad2deg, 0.0f, 0.0f, (float)dx, (float)dy, 0.0f);
01488 
01489                                         float lc = v.cmp(cmp_name, to, cmp_params);
01490 
01491                                         if (lc < bestval) {
01492                                                 bestval = lc;
01493                                                 bestang = ang;
01494                                                 bestdx = dx;
01495                                                 bestdy = dy;
01496                                                 bestflip = 0;
01497                                         }
01498 
01499                                         lc = v.cmp(cmp_name, flipped, cmp_params);
01500 
01501                                         if (lc < bestval) {
01502                                                 bestval = lc;
01503                                                 bestang = ang;
01504                                                 bestdx = dx;
01505                                                 bestdy = dy;
01506                                                 bestflip = 1;
01507                                         }
01508                                 }
01509                         }
01510                 }
01511         }
01512 
01513         if (delete_flipped) { delete flipped; flipped = 0; }
01514 
01515         bestang *= (float)EMConsts::rad2deg;
01516         Transform t(Dict("type","2d","alpha",(float)bestang));
01517         t.set_trans(bestdx,bestdy);
01518 
01519         if (bestflip) {
01520                 t.set_mirror(true);
01521         }
01522 
01523         EMData* rslt = this_img->process("xform",Dict("transform",&t));
01524         rslt->set_attr("xform.align2d",&t);
01525 
01526         return rslt;
01527 }
01528 
01529 EMData* SymAlignProcessor::align(EMData * this_img, EMData *to, const string & cmp_name, const Dict& cmp_params) const
01530 {
01531         
01532         // Set parms
01533         float dphi = params.set_default("dphi",10.f);
01534         float lphi = params.set_default("lphi",0.0f);
01535         float uphi = params.set_default("uphi",359.9f);
01536         
01537         Dict d;
01538         d["inc_mirror"] = true;
01539         d["delta"] = params.set_default("delta",10.f);
01540         
01541         //Genrate points on a sphere in an asymmetric unit
01542         Symmetry3D* sym = Factory<Symmetry3D>::get((string)params.set_default("sym","c1"));
01543         vector<Transform> transforms = sym->gen_orientations((string)params.set_default("orientgen","eman"),d);
01544         
01545         //Genrate symmetry related orritenations
01546         vector<Transform> syms = Symmetry3D::get_symmetries((string)params["sym"]);
01547         
01548         float bestquality = 0.0f;
01549         EMData* bestimage = 0;
01550         for(vector<Transform>::const_iterator trans_it = transforms.begin(); trans_it != transforms.end(); trans_it++) {
01551                 Dict tparams = trans_it->get_params("eman");
01552                 Transform t(tparams);
01553                 for( float phi = lphi; phi < uphi; phi += dphi ) {
01554                         tparams["phi"] = phi;
01555                         t.set_rotation(tparams);
01556                         
01557                         //Get the averagaer
01558                         Averager* imgavg = Factory<Averager>::get((string)params.set_default("avger","mean")); 
01559                         //Now make the averages
01560                         for ( vector<Transform>::const_iterator it = syms.begin(); it != syms.end(); ++it ) {
01561                                 Transform sympos = (*it)*t;
01562                                 EMData* transformed = this_img->process("xform",Dict("transform",&sympos));
01563                                 imgavg->add_image(transformed);
01564                                 delete transformed;
01565                         }
01566                         
01567                         EMData* symptcl=imgavg->finish();
01568                         delete imgavg;
01569                         //See which average is the best
01570                         float quality = symptcl->get_attr("sigma");
01571                         cout << quality << " " << phi << endl;
01572                         if(quality > bestquality) {
01573                                 bestquality = quality;
01574                                 bestimage = symptcl;
01575                         } else {
01576                                 delete symptcl;
01577                         }
01578                 }
01579         }
01580         if(sym != 0) delete sym;
01581         
01582         return bestimage;
01583 }
01584 
01585 static double refalifn(const gsl_vector * v, void *params)
01586 {
01587         Dict *dict = (Dict *) params;
01588 
01589         double x = gsl_vector_get(v, 0);
01590         double y = gsl_vector_get(v, 1);
01591         double a = gsl_vector_get(v, 2);
01592 
01593         EMData *this_img = (*dict)["this"];
01594         EMData *with = (*dict)["with"];
01595         bool mirror = (*dict)["mirror"];
01596 
01597         Transform t(Dict("type","2d","alpha",static_cast<float>(a)));
01598         t.set_trans((float)x,(float)y);
01599         t.set_mirror(mirror);
01600         if (v->size>3) {
01601                 float sca=(float)gsl_vector_get(v, 3);
01602                 if (sca<.7 || sca>1.3) return 1.0e20;
01603                 t.set_scale((float)gsl_vector_get(v, 3));
01604         }
01605         EMData *tmp = this_img->process("xform",Dict("transform",&t));
01606         if (dict->has_key("mask")) tmp->mult(*(EMData *)((*dict)["mask"]));
01607 
01608 //      printf("GSL %f %f %f %d %f\n",x,y,a,mirror,(float)gsl_vector_get(v, 3));
01609         Cmp* c = (Cmp*) ((void*)(*dict)["cmp"]);
01610         double result = c->cmp(tmp,with);
01611 
01612         if (tmp != 0) delete tmp;
01613         
01614         return result;
01615 }
01616 
01617 static void refalidf(const gsl_vector * v, void *params,gsl_vector * df) {
01618         // we do this using a simple local difference estimate due to the expense of the calculation. 
01619         // The step has to be large enough for the similarity metric
01620         // To provide an accurate change in value. 
01621         static double lstep[4] = { 0.05, 0.05, 0.1, 0.01 }; 
01622         
01623         gsl_vector *vc = gsl_vector_alloc(v->size);
01624         gsl_vector_memcpy(vc,v);
01625         
01626         double f = refalifn(v,params);
01627         for (unsigned int i=0; i<v->size; i++) {
01628                 double *vp = gsl_vector_ptr(vc,i);
01629                 *vp+=lstep[i];
01630                 double f2 = refalifn(vc,params);
01631                 *vp-=lstep[i];
01632                 
01633                 gsl_vector_set(df,i,(f2-f)/lstep[i]);
01634         }
01635         
01636         gsl_vector_free(vc);
01637         return;
01638 }
01639 
01640 static void refalifdf(const gsl_vector * v, void *params, double * f, gsl_vector * df) {
01641         // we do this using a simple local difference estimate due to the expense of the calculation. 
01642         // The step has to be large enough for the similarity metric
01643         // To provide an accurate change in value. 
01644         static double lstep[4] = { 0.05, 0.05, 0.1, 0.01 }; 
01645         
01646         gsl_vector *vc = gsl_vector_alloc(v->size);
01647         gsl_vector_memcpy(vc,v);
01648         
01649         *f = refalifn(v,params);
01650         for (unsigned int i=0; i<v->size; i++) {
01651                 double *vp = gsl_vector_ptr(vc,i);
01652                 *vp+=lstep[i];
01653                 double f2 = refalifn(vc,params);
01654                 *vp-=lstep[i];
01655                 
01656                 gsl_vector_set(df,i,(f2-*f)/lstep[i]);
01657         }
01658         
01659         gsl_vector_free(vc);
01660         return;
01661 
01662 }
01663 
01664 static double refalifnfast(const gsl_vector * v, void *params)
01665 {
01666         Dict *dict = (Dict *) params;
01667         EMData *this_img = (*dict)["this"];
01668         EMData *img_to = (*dict)["with"];
01669         bool mirror = (*dict)["mirror"];
01670 
01671         double x = gsl_vector_get(v, 0);
01672         double y = gsl_vector_get(v, 1);
01673         double a = gsl_vector_get(v, 2);
01674 
01675         double r = this_img->dot_rotate_translate(img_to, (float)x, (float)y, (float)a, mirror);
01676         int nsec = this_img->get_xsize() * this_img->get_ysize();
01677         double result = 1.0 - r / nsec;
01678 
01679 //      cout << result << " x " << x << " y " << y << " az " << a <<  endl;
01680         return result;
01681 }
01682 
01683 EMData *RefineAligner::align(EMData * this_img, EMData *to,
01684         const string & cmp_name, const Dict& cmp_params) const
01685 {
01686 
01687         if (!to) {
01688                 return 0;
01689         }
01690 
01691         EMData *result;
01692         int mode = params.set_default("mode", 0);
01693         float saz = 0.0;
01694         float sdx = 0.0;
01695         float sdy = 0.0;
01696         float sscale = 1.0;
01697         bool mirror = false;
01698         Transform* t;
01699         if (params.has_key("xform.align2d") ) {
01700                 t = params["xform.align2d"];
01701                 Dict params = t->get_params("2d");
01702                 saz = params["alpha"];
01703                 sdx = params["tx"];
01704                 sdy = params["ty"];
01705                 mirror = params["mirror"];
01706                 sscale = params["scale"];
01707         } else {
01708                 t = new Transform(); // is the identity
01709         }
01710 
01711         // We do this to prevent the GSL routine from crashing on an invalid alignment
01712         if ((float)(this_img->get_attr("sigma"))==0.0 || (float)(to->get_attr("sigma"))==0.0) {
01713                 result = this_img->process("xform",Dict("transform",t));
01714                 result->set_attr("xform.align2d",t);
01715                 delete t;
01716                 return result;
01717         }
01718         
01719         float stepx = params.set_default("stepx",1.0f);
01720         float stepy = params.set_default("stepy",1.0f);
01721         // Default step is 5 degree - note in EMAN1 it was 0.1 radians
01722         float stepaz = params.set_default("stepaz",5.0f);
01723         float stepscale = params.set_default("stepscale",0.0f);
01724 
01725         int np = 3;
01726         if (stepscale!=0.0) np++;
01727         Dict gsl_params;
01728         gsl_params["this"] = this_img;
01729         gsl_params["with"] = to;
01730         gsl_params["snr"]  = params["snr"];
01731         gsl_params["mirror"] = mirror;
01732         if (params.has_key("mask")) gsl_params["mask"]=params["mask"];
01733         
01734         const gsl_multimin_fminimizer_type *T = gsl_multimin_fminimizer_nmsimplex;
01735         gsl_vector *ss = gsl_vector_alloc(np);
01736 
01737 
01738         gsl_vector_set(ss, 0, stepx);
01739         gsl_vector_set(ss, 1, stepy);
01740         gsl_vector_set(ss, 2, stepaz);
01741         if (stepscale!=0.0) gsl_vector_set(ss,3,stepscale);
01742         
01743         gsl_vector *x = gsl_vector_alloc(np);
01744         gsl_vector_set(x, 0, sdx);
01745         gsl_vector_set(x, 1, sdy);
01746         gsl_vector_set(x, 2, saz);
01747         if (stepscale!=0.0) gsl_vector_set(x,3,1.0);
01748         
01749         Cmp *c = 0;
01750 
01751         gsl_multimin_function minex_func;
01752         if (mode == 2) {
01753                 minex_func.f = &refalifnfast;
01754         }
01755         else {
01756                 c = Factory < Cmp >::get(cmp_name, cmp_params);
01757                 gsl_params["cmp"] = (void *) c;
01758                 minex_func.f = &refalifn;
01759         }
01760 
01761         minex_func.n = np;
01762         minex_func.params = (void *) &gsl_params;
01763 
01764         gsl_multimin_fminimizer *s = gsl_multimin_fminimizer_alloc(T, np);
01765         gsl_multimin_fminimizer_set(s, &minex_func, x, ss);
01766 
01767         int rval = GSL_CONTINUE;
01768         int status = GSL_SUCCESS;
01769         int iter = 1;
01770 
01771         float precision = params.set_default("precision",0.04f);
01772         int maxiter = params.set_default("maxiter",28);
01773 
01774 //      printf("Refine sx=%1.2f sy=%1.2f sa=%1.2f prec=%1.4f maxit=%d\n",stepx,stepy,stepaz,precision,maxiter);
01775 //      printf("%1.2f %1.2f %1.1f  ->",(float)gsl_vector_get(s->x, 0),(float)gsl_vector_get(s->x, 1),(float)gsl_vector_get(s->x, 2));
01776 
01777         while (rval == GSL_CONTINUE && iter < maxiter) {
01778                 iter++;
01779                 status = gsl_multimin_fminimizer_iterate(s);
01780                 if (status) {
01781                         break;
01782                 }
01783                 rval = gsl_multimin_test_size(gsl_multimin_fminimizer_size(s), precision);
01784         }
01785 
01786         int maxshift = params.set_default("maxshift",-1);
01787 
01788         if (maxshift <= 0) {
01789                 maxshift = this_img->get_xsize() / 4;
01790         }
01791         float fmaxshift = static_cast<float>(maxshift);
01792         if ( fmaxshift >= fabs((float)gsl_vector_get(s->x, 0)) && fmaxshift >= fabs((float)gsl_vector_get(s->x, 1)) && (stepscale==0 || (((float)gsl_vector_get(s->x, 3))<1.3 && ((float)gsl_vector_get(s->x, 3))<0.7))  )
01793         {
01794 //              printf(" Refine good %1.2f %1.2f %1.1f\n",(float)gsl_vector_get(s->x, 0),(float)gsl_vector_get(s->x, 1),(float)gsl_vector_get(s->x, 2));
01795                 Transform  tsoln(Dict("type","2d","alpha",(float)gsl_vector_get(s->x, 2)));
01796                 tsoln.set_mirror(mirror);
01797                 tsoln.set_trans((float)gsl_vector_get(s->x, 0),(float)gsl_vector_get(s->x, 1));
01798                 if (stepscale!=0.0) tsoln.set_scale((float)gsl_vector_get(s->x, 3));
01799                 result = this_img->process("xform",Dict("transform",&tsoln));
01800                 result->set_attr("xform.align2d",&tsoln);
01801         } else { // The refine aligner failed - this shift went beyond the max shift
01802 //              printf(" Refine Failed %1.2f %1.2f %1.1f\n",(float)gsl_vector_get(s->x, 0),(float)gsl_vector_get(s->x, 1),(float)gsl_vector_get(s->x, 2));
01803                 result = this_img->process("xform",Dict("transform",t));
01804                 result->set_attr("xform.align2d",t);
01805         }
01806 
01807         delete t;
01808         t = 0;
01809 
01810         gsl_vector_free(x);
01811         gsl_vector_free(ss);
01812         gsl_multimin_fminimizer_free(s);
01813 
01814         if (c != 0) delete c;
01815         return result;
01816 }
01817 
01818 EMData *RefineAlignerCG::align(EMData * this_img, EMData *to,
01819         const string & cmp_name, const Dict& cmp_params) const
01820 {
01821 
01822         if (!to) {
01823                 return 0;
01824         }
01825 
01826         EMData *result;
01827         int mode = params.set_default("mode", 0);
01828         float saz = 0.0;
01829         float sdx = 0.0;
01830         float sdy = 0.0;
01831         float sscale = 1.0;
01832         bool mirror = false;
01833         Transform* t;
01834         if (params.has_key("xform.align2d") ) {
01835                 t = params["xform.align2d"];
01836                 Dict params = t->get_params("2d");
01837                 saz = params["alpha"];
01838                 sdx = params["tx"];
01839                 sdy = params["ty"];
01840                 mirror = params["mirror"];
01841                 sscale = params["scale"];
01842         } else {
01843                 t = new Transform(); // is the identity
01844         }
01845 
01846         // We do this to prevent the GSL routine from crashing on an invalid alignment
01847         if ((float)(this_img->get_attr("sigma"))==0.0 || (float)(to->get_attr("sigma"))==0.0) {
01848                 result = this_img->process("xform",Dict("transform",t));
01849                 result->set_attr("xform.align2d",t);
01850                 delete t;
01851                 return result;
01852         }
01853         
01854         float step = params.set_default("step",0.1f);
01855         float stepscale = params.set_default("stepscale",0.0f);
01856 
01857         int np = 3;
01858         if (stepscale!=0.0) np++;
01859         Dict gsl_params;
01860         gsl_params["this"] = this_img;
01861         gsl_params["with"] = to;
01862         gsl_params["snr"]  = params["snr"];
01863         gsl_params["mirror"] = mirror;
01864         if (params.has_key("mask")) gsl_params["mask"]=params["mask"];
01865 
01866         const gsl_multimin_fdfminimizer_type *T = gsl_multimin_fdfminimizer_vector_bfgs;
01867         
01868         gsl_vector *x = gsl_vector_alloc(np);
01869         gsl_vector_set(x, 0, sdx);
01870         gsl_vector_set(x, 1, sdy);
01871         gsl_vector_set(x, 2, saz);
01872         if (stepscale!=0.0) gsl_vector_set(x,3,1.0);
01873         
01874         Cmp *c = 0;
01875 
01876         gsl_multimin_function_fdf minex_func;
01877         if (mode == 2) {
01878                 minex_func.f = &refalifnfast;
01879         }
01880         else {
01881                 c = Factory < Cmp >::get(cmp_name, cmp_params);
01882                 gsl_params["cmp"] = (void *) c;
01883                 minex_func.f = &refalifn;
01884         }
01885 
01886         minex_func.df = &refalidf;
01887         minex_func.fdf = &refalifdf;
01888         minex_func.n = np;
01889         minex_func.params = (void *) &gsl_params;
01890 
01891         gsl_multimin_fdfminimizer *s = gsl_multimin_fdfminimizer_alloc(T, np);
01892         gsl_multimin_fdfminimizer_set(s, &minex_func, x, step, 0.001f);
01893 
01894         int rval = GSL_CONTINUE;
01895         int status = GSL_SUCCESS;
01896         int iter = 1;
01897 
01898         float precision = params.set_default("precision",0.02f);
01899         int maxiter = params.set_default("maxiter",12);
01900         int verbose = params.set_default("verbose",0);
01901 
01902 //      printf("Refine sx=%1.2f sy=%1.2f sa=%1.2f prec=%1.4f maxit=%d\n",stepx,stepy,stepaz,precision,maxiter);
01903 //      printf("%1.2f %1.2f %1.1f  ->",(float)gsl_vector_get(s->x, 0),(float)gsl_vector_get(s->x, 1),(float)gsl_vector_get(s->x, 2));
01904 
01905         while (rval == GSL_CONTINUE && iter < maxiter) {
01906                 iter++;
01907                 status = gsl_multimin_fdfminimizer_iterate(s);
01908                 if (status) {
01909                         break;
01910                 }
01911                 rval = gsl_multimin_test_gradient (s->gradient, precision);
01912 //              if (verbose>2) printf("GSL %d. %1.3f %1.3f %1.3f   %1.3f\n",iter,gsl_vector_get(s->x,0),gsl_vector_get(s->x,1),gsl_vector_get(s->x,2),s->gradient[0]);
01913         }
01914 
01915         int maxshift = params.set_default("maxshift",-1);
01916 
01917         if (maxshift <= 0) {
01918                 maxshift = this_img->get_xsize() / 4;
01919         }
01920         float fmaxshift = static_cast<float>(maxshift);
01921         if ( fmaxshift >= fabs((float)gsl_vector_get(s->x, 0)) && fmaxshift >= fabs((float)gsl_vector_get(s->x, 1)) && (stepscale==0 || (((float)gsl_vector_get(s->x, 3))<1.3 && ((float)gsl_vector_get(s->x, 3))<0.7))  )
01922         {
01923                 if (verbose>0) printf(" Refine good (%d) %1.2f %1.2f %1.1f\n",iter,(float)gsl_vector_get(s->x, 0),(float)gsl_vector_get(s->x, 1),(float)gsl_vector_get(s->x, 2));
01924                 Transform  tsoln(Dict("type","2d","alpha",(float)gsl_vector_get(s->x, 2)));
01925                 tsoln.set_mirror(mirror);
01926                 tsoln.set_trans((float)gsl_vector_get(s->x, 0),(float)gsl_vector_get(s->x, 1));
01927                 if (stepscale!=0.0) tsoln.set_scale((float)gsl_vector_get(s->x, 3));
01928                 result = this_img->process("xform",Dict("transform",&tsoln));
01929                 result->set_attr("xform.align2d",&tsoln);
01930         } else { // The refine aligner failed - this shift went beyond the max shift
01931                 if (verbose>1) printf(" Refine Failed %1.2f %1.2f %1.1f\n",(float)gsl_vector_get(s->x, 0),(float)gsl_vector_get(s->x, 1),(float)gsl_vector_get(s->x, 2));
01932                 result = this_img->process("xform",Dict("transform",t));
01933                 result->set_attr("xform.align2d",t);
01934         }
01935 
01936         delete t;
01937         t = 0;
01938 
01939         gsl_vector_free(x);
01940         gsl_multimin_fdfminimizer_free(s);
01941 
01942         if (c != 0) delete c;
01943         return result;
01944 }
01945 
01946 static Transform refalin3d_perturbquat(const Transform*const t, const float& spincoeff, const float& n0, const float& n1, const float& n2, const float& x, const float& y, const float& z)
01947 {
01948         Vec3f normal(n0,n1,n2);
01949         normal.normalize();
01950         
01951         float omega = spincoeff*sqrt(n0*n0 + n1*n1 + n2*n2); // Here we compute the spin by the rotation axis vector length
01952         Dict d;
01953         d["type"] = "spin";
01954         d["omega"] = omega;
01955         d["n1"] = normal[0];
01956         d["n2"] = normal[1];
01957         d["n3"] = normal[2];
01958         //cout << omega << " " << normal[0] << " " << normal[1] << " " << normal[2] << " " << n0 << " " << n1 << " " << n2 << endl;
01959         
01960         Transform q(d);
01961         q.set_trans((float)x,(float)y,(float)z);
01962         
01963         q = q*(*t); //compose transforms        
01964         
01965         return q;
01966 }
01967 
01968 static double symquat(const gsl_vector * v, void *params)
01969 {
01970         Dict *dict = (Dict *) params;
01971 
01972         double n0 = gsl_vector_get(v, 0);
01973         double n1 = gsl_vector_get(v, 1);
01974         double n2 = gsl_vector_get(v, 2);
01975         double x = gsl_vector_get(v, 3);
01976         double y = gsl_vector_get(v, 4);
01977         double z = gsl_vector_get(v, 5);
01978 
01979         EMData* volume = (*dict)["volume"];
01980         float spincoeff = (*dict)["spincoeff"];
01981         Transform* t = (*dict)["transform"];
01982 
01983         Transform soln = refalin3d_perturbquat(t,spincoeff,(float)n0,(float)n1,(float)n2,(float)x,(float)y,(float)z);
01984 
01985         EMData *tmp = volume->process("xform",Dict("transform",&soln));
01986         EMData *symtmp = tmp->process("xform.applysym",Dict("sym",(*dict)["sym"]));
01987         Cmp* c = (Cmp*) ((void*)(*dict)["cmp"]);
01988         double result = c->cmp(symtmp,tmp);
01989         delete tmp;
01990         delete symtmp;
01991 
01992         //cout << result << endl;
01993         return result;
01994 }
01995 
01996 static double refalifn3dquat(const gsl_vector * v, void *params)
01997 {
01998         Dict *dict = (Dict *) params;
01999 
02000         double n0 = gsl_vector_get(v, 0);
02001         double n1 = gsl_vector_get(v, 1);
02002         double n2 = gsl_vector_get(v, 2);
02003         double x = gsl_vector_get(v, 3);
02004         double y = gsl_vector_get(v, 4);
02005         double z = gsl_vector_get(v, 5);
02006 
02007         EMData *this_img = (*dict)["this"];
02008         EMData *with = (*dict)["with"];
02009 
02010         Transform* t = (*dict)["transform"];
02011         float spincoeff = (*dict)["spincoeff"];
02012 
02013         Transform soln = refalin3d_perturbquat(t,spincoeff,(float)n0,(float)n1,(float)n2,(float)x,(float)y,(float)z);
02014 
02015         EMData *tmp = this_img->process("xform",Dict("transform",&soln));
02016         Cmp* c = (Cmp*) ((void*)(*dict)["cmp"]);
02017         double result = c->cmp(tmp,with);
02018         if ( tmp != 0 ) delete tmp;
02019 
02020         //cout << result << endl;
02021         return result;
02022 }
02023 
02024 EMData* SymAlignProcessorQuat::align(EMData * volume, EMData *to, const string & cmp_name, const Dict& cmp_params) const
02025 {
02026         //Get pretransform
02027         Transform* t;
02028         if (params.has_key("xform.align3d") ) {
02029                 t = params["xform.align3d"];
02030         }else {
02031                 t = new Transform(); // is the identity
02032         }
02033         
02034         float sdi = 0.0;
02035         float sdj = 0.0;
02036         float sdk = 0.0;
02037         float sdx = 0.0;
02038         float sdy = 0.0;
02039         float sdz = 0.0;
02040 
02041         float spincoeff =  params.set_default("spin_coeff",10.0f); // spin coefficient, controls speed of convergence (sort of)
02042         
02043         int np = 6; // the number of dimensions
02044         Dict gsl_params;
02045         gsl_params["volume"] = volume;
02046         gsl_params["transform"] = t;
02047         gsl_params["sym"] = params.set_default("sym","c1");
02048         gsl_params["spincoeff"] = spincoeff;
02049         
02050         const gsl_multimin_fminimizer_type *T = gsl_multimin_fminimizer_nmsimplex;
02051         gsl_vector *ss = gsl_vector_alloc(np);
02052 
02053         float stepi = params.set_default("stepn0",1.0f); // doesn't really matter b/c the vecor part will be normalized anyway
02054         float stepj = params.set_default("stepn1",1.0f); // doesn't really matter b/c the vecor part will be normalized anyway
02055         float stepk = params.set_default("stepn2",1.0f); // doesn't really matter b/c the vecor part will be normalized anyway
02056         float stepx = params.set_default("stepx",1.0f);
02057         float stepy = params.set_default("stepy",1.0f);
02058         float stepz = params.set_default("stepz",1.0f);
02059 
02060         gsl_vector_set(ss, 0, stepi);
02061         gsl_vector_set(ss, 1, stepj);
02062         gsl_vector_set(ss, 2, stepk);
02063         gsl_vector_set(ss, 3, stepx);
02064         gsl_vector_set(ss, 4, stepy);
02065         gsl_vector_set(ss, 5, stepz);
02066 
02067         gsl_vector *x = gsl_vector_alloc(np);
02068         gsl_vector_set(x, 0, sdi);
02069         gsl_vector_set(x, 1, sdj);
02070         gsl_vector_set(x, 2, sdk);
02071         gsl_vector_set(x, 3, sdx);
02072         gsl_vector_set(x, 4, sdy);
02073         gsl_vector_set(x, 5, sdz);
02074         
02075         gsl_multimin_function minex_func;
02076         Cmp *c = Factory < Cmp >::get(cmp_name, cmp_params);
02077         gsl_params["cmp"] = (void *) c;
02078         minex_func.f = &symquat;
02079         minex_func.n = np;
02080         minex_func.params = (void *) &gsl_params;
02081         gsl_multimin_fminimizer *s = gsl_multimin_fminimizer_alloc(T, np);
02082         gsl_multimin_fminimizer_set(s, &minex_func, x, ss);
02083         
02084         int rval = GSL_CONTINUE;
02085         int status = GSL_SUCCESS;
02086         int iter = 1;
02087         
02088         float precision = params.set_default("precision",0.01f);
02089         int maxiter = params.set_default("maxiter",100);
02090         while (rval == GSL_CONTINUE && iter < maxiter) {
02091                 iter++;
02092                 status = gsl_multimin_fminimizer_iterate(s);
02093                 if (status) {
02094                         break;
02095                 }
02096                 rval = gsl_multimin_test_size(gsl_multimin_fminimizer_size(s), precision);
02097         }
02098 
02099         int maxshift = params.set_default("maxshift",-1);
02100 
02101         if (maxshift <= 0) {
02102                 maxshift = volume->get_xsize() / 4;
02103         }
02104         float fmaxshift = static_cast<float>(maxshift);
02105         
02106         EMData *result;
02107         if ( fmaxshift >= (float)gsl_vector_get(s->x, 0) && fmaxshift >= (float)gsl_vector_get(s->x, 1)  && fmaxshift >= (float)gsl_vector_get(s->x, 2))
02108         {
02109                 float n0 = (float)gsl_vector_get(s->x, 0);
02110                 float n1 = (float)gsl_vector_get(s->x, 1);
02111                 float n2 = (float)gsl_vector_get(s->x, 2);
02112                 float x = (float)gsl_vector_get(s->x, 3);
02113                 float y = (float)gsl_vector_get(s->x, 4);
02114                 float z = (float)gsl_vector_get(s->x, 5);
02115                 
02116                 Transform tsoln = refalin3d_perturbquat(t,spincoeff,n0,n1,n2,x,y,z);
02117                         
02118                 result = volume->process("xform",Dict("transform",&tsoln));
02119                 result->set_attr("xform.align3d",&tsoln);
02120                 EMData *tmpsym = result->process("xform.applysym",Dict("sym",gsl_params["sym"]));
02121                 result->set_attr("score", result->cmp(cmp_name,tmpsym,cmp_params));
02122                 delete tmpsym;
02123         } else { // The refine aligner failed - this shift went beyond the max shift
02124                 result = volume->process("xform",Dict("transform",t));
02125                 result->set_attr("xform.align3d",t);
02126                 result->set_attr("score",0.0);
02127         }
02128         
02129         gsl_vector_free(x);
02130         gsl_vector_free(ss);
02131         gsl_multimin_fminimizer_free(s);
02132 
02133         if (c != 0) delete c;
02134         delete t;
02135                                       
02136         return result;
02137 }
02138 
02139 EMData* Refine3DAlignerQuaternion::align(EMData * this_img, EMData *to,
02140         const string & cmp_name, const Dict& cmp_params) const
02141 {
02142         
02143         if (!to || !this_img) throw NullPointerException("Input image is null"); // not sure if this is necessary, it was there before I started
02144 
02145         if (to->get_ndim() != 3 || this_img->get_ndim() != 3) throw ImageDimensionException("The Refine3D aligner only works for 3D images");
02146 
02147 #ifdef EMAN2_USING_CUDA 
02148         if(EMData::usecuda == 1) {
02149                 if(!this_img->getcudarwdata()) this_img->copy_to_cuda();
02150                 if(!to->getcudarwdata()) to->copy_to_cuda();
02151         }
02152 #endif
02153 
02154         float sdi = 0.0;
02155         float sdj = 0.0;
02156         float sdk = 0.0;
02157         float sdx = 0.0;
02158         float sdy = 0.0;
02159         float sdz = 0.0;
02160         bool mirror = false;
02161         
02162         Transform* t;
02163         if (params.has_key("xform.align3d") ) {
02164                 // Unlike the 2d refine aligner, this class doesn't require the starting transform's
02165                 // parameters to form the starting guess. Instead the Transform itself
02166                 // is perturbed carefully (using quaternion rotation) to overcome problems that arise
02167                 // when you use orthogonally-based Euler angles
02168                 t = params["xform.align3d"];
02169         }else {
02170                 t = new Transform(); // is the identity
02171         }
02172         
02173         float spincoeff =  params.set_default("spin_coeff",10.0f); // spin coefficient, controls speed of convergence (sort of)
02174         
02175         int np = 6; // the number of dimensions
02176         Dict gsl_params;
02177         gsl_params["this"] = this_img;
02178         gsl_params["with"] = to;
02179         gsl_params["snr"]  = params["snr"];
02180         gsl_params["mirror"] = mirror;
02181         gsl_params["transform"] = t;    
02182         gsl_params["spincoeff"] = spincoeff;
02183         Dict altered_cmp_params(cmp_params);
02184         
02185         const gsl_multimin_fminimizer_type *T = gsl_multimin_fminimizer_nmsimplex;
02186         gsl_vector *ss = gsl_vector_alloc(np);
02187         
02188         float stepi = params.set_default("stepn0",1.0f); // doesn't really matter b/c the vecor part will be normalized anyway
02189         float stepj = params.set_default("stepn1",1.0f); // doesn't really matter b/c the vecor part will be normalized anyway
02190         float stepk = params.set_default("stepn2",1.0f); // doesn't really matter b/c the vecor part will be normalized anyway
02191         float stepx = params.set_default("stepx",1.0f);
02192         float stepy = params.set_default("stepy",1.0f);
02193         float stepz = params.set_default("stepz",1.0f);
02194         
02195         //gsl_vector_set(ss, 0, stepw);
02196         gsl_vector_set(ss, 0, stepi);
02197         gsl_vector_set(ss, 1, stepj);
02198         gsl_vector_set(ss, 2, stepk);
02199         gsl_vector_set(ss, 3, stepx);
02200         gsl_vector_set(ss, 4, stepy);
02201         gsl_vector_set(ss, 5, stepz);
02202         
02203         gsl_vector *x = gsl_vector_alloc(np);
02204         gsl_vector_set(x, 0, sdi);
02205         gsl_vector_set(x, 1, sdj);
02206         gsl_vector_set(x, 2, sdk);
02207         gsl_vector_set(x, 3, sdx);
02208         gsl_vector_set(x, 4, sdy);
02209         gsl_vector_set(x, 5, sdz);
02210         
02211         gsl_multimin_function minex_func;
02212         Cmp *c = Factory < Cmp >::get(cmp_name, altered_cmp_params);
02213                 
02214         gsl_params["cmp"] = (void *) c;
02215         minex_func.f = &refalifn3dquat;
02216 
02217         minex_func.n = np;
02218         minex_func.params = (void *) &gsl_params;
02219         
02220         gsl_multimin_fminimizer *s = gsl_multimin_fminimizer_alloc(T, np);
02221         gsl_multimin_fminimizer_set(s, &minex_func, x, ss);
02222         
02223         int rval = GSL_CONTINUE;
02224         int status = GSL_SUCCESS;
02225         int iter = 1;
02226         
02227         float precision = params.set_default("precision",0.01f);
02228         int maxiter = params.set_default("maxiter",100);
02229         while (rval == GSL_CONTINUE && iter < maxiter) {
02230                 iter++;
02231                 status = gsl_multimin_fminimizer_iterate(s);
02232                 if (status) {
02233                         break;
02234                 }
02235                 rval = gsl_multimin_test_size(gsl_multimin_fminimizer_size(s), precision);
02236         }
02237 
02238         int maxshift = params.set_default("maxshift",-1);
02239 
02240         if (maxshift <= 0) {
02241                 maxshift = this_img->get_xsize() / 4;
02242         }
02243         float fmaxshift = static_cast<float>(maxshift);
02244         
02245         EMData *result;
02246         if ( fmaxshift >= (float)gsl_vector_get(s->x, 0) && fmaxshift >= (float)gsl_vector_get(s->x, 1)  && fmaxshift >= (float)gsl_vector_get(s->x, 2))
02247         {
02248                 float n0 = (float)gsl_vector_get(s->x, 0);
02249                 float n1 = (float)gsl_vector_get(s->x, 1);
02250                 float n2 = (float)gsl_vector_get(s->x, 2);
02251                 float x = (float)gsl_vector_get(s->x, 3);
02252                 float y = (float)gsl_vector_get(s->x, 4);
02253                 float z = (float)gsl_vector_get(s->x, 5);
02254                 
02255                 Transform tsoln = refalin3d_perturbquat(t,spincoeff,n0,n1,n2,x,y,z);
02256                         
02257                 result = this_img->process("xform",Dict("transform",&tsoln));
02258                 result->set_attr("xform.align3d",&tsoln);
02259                 result->set_attr("score", result->cmp(cmp_name,to,cmp_params));
02260                 
02261          //coda goes here
02262         } else { // The refine aligner failed - this shift went beyond the max shift
02263                 result = this_img->process("xform",Dict("transform",t));
02264                 result->set_attr("xform.align3d",t);
02265                 result->set_attr("score",0.0);
02266         }
02267         
02268         //EMData *result = this_img->process("xform",Dict("transform",t));
02269         delete t;
02270         gsl_vector_free(x);
02271         gsl_vector_free(ss);
02272         gsl_multimin_fminimizer_free(s);
02273 
02274         if (c != 0) delete c;
02275         
02276         return result;
02277 }
02278 
02279 EMData* Refine3DAlignerGrid::align(EMData * this_img, EMData *to,
02280         const string & cmp_name, const Dict& cmp_params) const
02281 {
02282         if ( this_img->get_ndim() != 3 || to->get_ndim() != 3 ) {
02283                 throw ImageDimensionException("This aligner only works for 3D images");
02284         }
02285 
02286         Transform* t;
02287         if (params.has_key("xform.align3d") ) {
02288                 // Unlike the 2d refine aligner, this class doesn't require the starting transform's
02289                 // parameters to form the starting guess. Instead the Transform itself
02290                 // is perturbed carefully (using quaternion rotation) to overcome problems that arise
02291                 // when you use orthogonally-based Euler angles
02292                 t = params["xform.align3d"];
02293         }else {
02294                 t = new Transform(); // is the identity
02295         }
02296 
02297         int searchx = 0;
02298         int searchy = 0;
02299         int searchz = 0;
02300         bool dotrans = params.set_default("dotrans",1);
02301         if (params.has_key("search")) {
02302                 vector<string> check;
02303                 check.push_back("searchx");
02304                 check.push_back("searchy");
02305                 check.push_back("searchz");
02306                 for(vector<string>::const_iterator cit = check.begin(); cit != check.end(); ++cit) {
02307                         if (params.has_key(*cit)) throw InvalidParameterException("The search parameter is mutually exclusive of the searchx, searchy, and searchz parameters");
02308                 }
02309                 int search  = params["search"];
02310                 searchx = search;
02311                 searchy = search;
02312                 searchz = search;
02313         } else {
02314                 searchx = params.set_default("searchx",3);
02315                 searchy = params.set_default("searchy",3);
02316                 searchz = params.set_default("searchz",3);
02317         }       
02318 
02319         float delta = params.set_default("delta",1.0f);
02320         float range = params.set_default("range",10.0f);
02321         bool verbose = params.set_default("verbose",false);
02322         
02323         bool tomography = (cmp_name == "ccc.tomo") ? 1 : 0;
02324         EMData * tofft = 0;
02325         if(dotrans || tomography){
02326                 tofft = to->do_fft();
02327         }
02328 
02329 #ifdef EMAN2_USING_CUDA 
02330         if(EMData::usecuda == 1) {
02331                 if(!this_img->getcudarodata()) this_img->copy_to_cudaro(); // This is safer
02332                 if(!to->getcudarwdata()) to->copy_to_cuda();
02333                 if(to->getcudarwdata()){if(tofft) tofft->copy_to_cuda();}
02334         }
02335 #endif
02336 
02337         Dict d;
02338         d["type"] = "eman"; // d is used in the loop below
02339         Dict best;
02340 //      best["score"] = numeric_limits<float>::infinity();
02341         best["score"] = 1.0e37;
02342         bool use_cpu = true;
02343         Transform tran = Transform();
02344         Cmp* c = Factory <Cmp>::get(cmp_name, cmp_params);
02345         
02346         for ( float alt = 0; alt < range; alt += delta) {
02347                 // now compute a sane az step size 
02348                 float saz = 360;
02349                 if(alt != 0) saz = delta/sin(alt*M_PI/180.0f); // This gives consistent az step sizes(arc lengths)
02350                 for ( float az = 0; az < 360; az += saz ){
02351                         if (verbose) {
02352                                 cout << "Trying angle alt " << alt << " az " << az << endl;
02353                         }
02354                         // account for any changes in az
02355                         for( float phi = -range-az; phi < range-az; phi += delta ) {
02356                                 d["alt"] = alt;
02357                                 d["phi"] = phi; 
02358                                 d["az"] = az;
02359                                 Transform tr(d);
02360                                 tr = tr*(*t);   // compose transforms, this moves to the pole (aprox)
02361                                 
02362                                 //EMData* transformed = this_img->process("xform",Dict("transform",&tr));
02363                                 EMData* transformed;
02364                                 transformed = this_img->process("xform",Dict("transform",&tr));
02365                                 
02366                                 //need to do things a bit diffrent if we want to compare two tomos
02367                                 float score = 0.0f;
02368                                 if(dotrans || tomography){
02369                                         EMData* ccf = transformed->calc_ccf(tofft);
02370 #ifdef EMAN2_USING_CUDA 
02371                                         if(EMData::usecuda == 1){
02372                                                 use_cpu = false;
02373                                                 CudaPeakInfo* data = calc_max_location_wrap_cuda(ccf->getcudarwdata(), ccf->get_xsize(), ccf->get_ysize(), ccf->get_zsize(), searchx, searchy, searchz);
02374                                                 tran.set_trans((float)-data->px, (float)-data->py, (float)-data->pz);
02375                                                 //CudaPeakInfoFloat* data = calc_max_location_wrap_intp_cuda(ccf->getcudarwdata(), ccf->get_xsize(), ccf->get_ysize(), ccf->get_zsize(), searchx, searchy, searchz);
02376                                                 //tran.set_trans(-data->xintp, -data->yintp, -data->zintp);
02377                                                 tr = tran*tr; // to reflect the fact that we have done a rotation first and THEN a transformation
02378                                                 if (tomography) {
02379                                                         float2 stats = get_stats_cuda(ccf->getcudarwdata(), ccf->get_xsize(), ccf->get_ysize(), ccf->get_zsize());
02380                                                         score = -(data->peak - stats.x)/sqrt(stats.y); // Normalize, this is better than calling the norm processor since we only need to normalize one point
02381                                                 } else {
02382                                                         score = -data->peak;
02383                                                 }
02384                                                 delete data;
02385                                         }
02386 #endif
02387                                         if(use_cpu){
02388                                                 if(tomography) ccf->process_inplace("normalize");
02389                                                 //vector<float> fpoint = ccf->calc_max_location_wrap_intp(searchx,searchy,searchz);
02390                                                 //tran.set_trans(-fpoint[0], -fpoint[1], -fpoint[2]);
02391                                                 //score = -fpoint[3];
02392                                                 IntPoint point = ccf->calc_max_location_wrap(searchx,searchy,searchz);
02393                                                 tran.set_trans((float)-point[0], (float)-point[1], (float)-point[2]);
02394                                                 score = -ccf->get_value_at_wrap(point[0], point[1], point[2]);
02395                                                 tr = tran*tr;// to reflect the fact that we have done a rotation first and THEN a transformation
02396                                                 
02397                                         }
02398                                         delete ccf; ccf =0;
02399                                         delete transformed; transformed = 0;// this is to stop a mem leak
02400                                 }
02401 
02402                                 if(!tomography){
02403                                         if(!transformed) transformed = this_img->process("xform",Dict("transform",&tr)); // we are returning a map
02404                                         score = c->cmp(to,transformed);
02405                                         delete transformed; transformed = 0;// this is to stop a mem leak
02406                                 }
02407                                 
02408                                 if(score < float(best["score"])) {
02409 //                                      printf("%f\n",score);
02410                                         best["score"] = score;
02411                                         best["xform.align3d"] = &tr; // I wonder if this will cause a mem leak?
02412                                 }       
02413                         }
02414                 }
02415         }
02416 
02417         if(tofft) {delete tofft; tofft = 0;}
02418         if (c != 0) delete c;
02419         
02420         //make aligned map;
02421         EMData* best_match = this_img->process("xform",Dict("transform", best["xform.align3d"])); // we are returning a map
02422         best_match->set_attr("xform.align3d", best["xform.align3d"]);
02423         best_match->set_attr("score", float(best["score"]));
02424         
02425         return best_match;
02426         
02427 }
02428 
02429 EMData* RT3DGridAligner::align(EMData * this_img, EMData *to, const string & cmp_name, const Dict& cmp_params) const
02430 {
02431 
02432         vector<Dict> alis = xform_align_nbest(this_img,to,1,cmp_name,cmp_params);
02433 
02434         Dict t;
02435         Transform* tr = (Transform*) alis[0]["xform.align3d"];
02436         t["transform"] = tr;
02437         EMData* soln = this_img->process("xform",t);
02438         soln->set_attr("xform.align3d",tr);
02439         delete tr; tr = 0;
02440 
02441         return soln;
02442 
02443 }
02444 
02445 vector<Dict> RT3DGridAligner::xform_align_nbest(EMData * this_img, EMData * to, const unsigned int nsoln, const string & cmp_name, const Dict& cmp_params) const {
02446 
02447         if ( this_img->get_ndim() != 3 || to->get_ndim() != 3 ) {
02448                 throw ImageDimensionException("This aligner only works for 3D images");
02449         }
02450 
02451         int searchx = 0;
02452         int searchy = 0;
02453         int searchz = 0;
02454         
02455         bool dotrans = params.set_default("dotrans",1);
02456         if (params.has_key("search")) {
02457                 vector<string> check;
02458                 check.push_back("searchx");
02459                 check.push_back("searchy");
02460                 check.push_back("searchz");
02461                 for(vector<string>::const_iterator cit = check.begin(); cit != check.end(); ++cit) {
02462                         if (params.has_key(*cit)) throw InvalidParameterException("The search parameter is mutually exclusive of the searchx, searchy, and searchz parameters");
02463                 }
02464                 int search  = params["search"];
02465                 searchx = search;
02466                 searchy = search;
02467                 searchz = search;
02468         } else {
02469                 searchx = params.set_default("searchx",3);
02470                 searchy = params.set_default("searchy",3);
02471                 searchz = params.set_default("searchz",3);
02472         }
02473         
02474         Transform* initxform;
02475         if (params.has_key("initxform") ) {
02476                 // Unlike the 2d refine aligner, this class doesn't require the starting transform's
02477                 // parameters to form the starting guess. Instead the Transform itself
02478                 // is perturbed carefully (using quaternion rotation) to overcome problems that arise
02479                 // when you use orthogonally-based Euler angles
02480                 initxform = params["initxform"];
02481         }else {
02482                 initxform = new Transform(); // is the identity
02483         }
02484         
02485         float lalt = params.set_default("alt0",0.0f);
02486         float laz = params.set_default("az0",0.0f);
02487         float lphi = params.set_default("phi0",0.0f);
02488         float ualt = params.set_default("alt1",180.0f); // I am using 179.9 rather than 180 to avoid resampling
02489         float uphi = params.set_default("phi1",360.0f); // I am using 359.9 rather than 180 to avoid resampling 0 = 360 (for perodic functions)
02490         float uaz = params.set_default("az1",360.0f);   // I am using 359.9 rather than 180 to avoid resampling 0 = 360 (for perodic functions)
02491         float dalt = params.set_default("dalt",10.f);
02492         float daz = params.set_default("daz",10.f);
02493         float dphi = params.set_default("dphi",10.f);
02494         bool verbose = params.set_default("verbose",false);
02495         
02496         //in case we arre aligning tomos
02497         Dict altered_cmp_params(cmp_params);
02498         if (cmp_name == "ccc.tomo") {
02499                 altered_cmp_params.set_default("searchx", searchx);
02500                 altered_cmp_params.set_default("searchy", searchy);
02501                 altered_cmp_params.set_default("searchz", searchz);
02502                 altered_cmp_params.set_default("norm", true);
02503         }
02504 
02505         vector<Dict> solns;
02506         if (nsoln == 0) return solns; // What was the user thinking?
02507         for (unsigned int i = 0; i < nsoln; ++i ) {
02508                 Dict d;
02509                 d["score"] = 1.e24;
02510                 Transform t; // identity by default
02511                 d["xform.align3d"] = &t; // deep copy is going on here
02512                 solns.push_back(d);
02513         }
02514         
02515         bool tomography = (cmp_name == "ccc.tomo") ? 1 : 0;
02516         EMData * tofft = 0;
02517         if(dotrans || tomography){
02518                 tofft = to->do_fft();
02519         }
02520         
02521 #ifdef EMAN2_USING_CUDA 
02522         if(EMData::usecuda == 1) {
02523                 if(!this_img->getcudarodata()) this_img->copy_to_cudaro();  // safer call
02524                 if(!to->getcudarwdata()) to->copy_to_cuda();
02525                 if(to->getcudarwdata()){if(tofft) tofft->copy_to_cuda();}
02526         }
02527 #endif
02528 
02529         Dict d;
02530         d["type"] = "eman"; // d is used in the loop below
02531         Transform trans = Transform();
02532         Cmp* c = Factory <Cmp>::get(cmp_name, cmp_params);
02533         bool use_cpu = true;
02534         for ( float alt = lalt; alt <= ualt; alt += dalt) {
02535                 // An optimization for the range of az is made at the top of the sphere
02536                 // If you think about it, this is just a coarse way of making this approach slightly more efficient
02537                 for ( float az = laz; az < uaz; az += daz ){
02538                         if (verbose) {
02539                                 cout << "Trying angle alt " << alt << " az " << az << endl;
02540                         }
02541                         for( float phi = lphi; phi < uphi; phi += dphi ) {
02542                                 d["alt"] = alt;
02543                                 d["phi"] = phi; 
02544                                 d["az"] = az;
02545                                 Transform t(d);
02546                                 t = t*(*initxform);
02547                                 EMData* transformed = this_img->process("xform",Dict("transform",&t));
02548                         
02549                                 //need to do things a bit diffrent if we want to compare two tomos
02550                                 float best_score = 0.0f;
02551                                 if(dotrans || tomography){
02552                                         EMData* ccf = transformed->calc_ccf(tofft);
02553 #ifdef EMAN2_USING_CUDA 
02554                                         if(EMData::usecuda == 1){
02555                                                 use_cpu = false;;
02556                                                 CudaPeakInfo* data = calc_max_location_wrap_cuda(ccf->getcudarwdata(), ccf->get_xsize(), ccf->get_ysize(), ccf->get_zsize(), searchx, searchy, searchz);
02557                                                 trans.set_trans((float)-data->px, (float)-data->py, (float)-data->pz);
02558                                                 t = trans*t;    //composite transfrom to reflect the fact that we have done a rotation first and THEN a transformation
02559                                                 if (tomography) {
02560                                                         float2 stats = get_stats_cuda(ccf->getcudarwdata(), ccf->get_xsize(), ccf->get_ysize(), ccf->get_zsize());
02561                                                         best_score = -(data->peak - stats.x)/sqrt(stats.y); // Normalize, this is better than calling the norm processor since we only need to normalize one point
02562                                                 } else {
02563                                                         best_score = -data->peak;
02564                                                 }
02565                                                 delete data;
02566                                         }
02567 #endif
02568                                         if(use_cpu){
02569                                                 if(tomography) ccf->process_inplace("normalize");       
02570                                                 IntPoint point = ccf->calc_max_location_wrap(searchx,searchy,searchz);
02571                                                 trans.set_trans((float)-point[0], (float)-point[1], (float)-point[2]);
02572                                                 t = trans*t;    //composite transfrom to reflect the fact that we have done a rotation first and THEN a transformation
02573                                                 best_score = -ccf->get_value_at_wrap(point[0], point[1], point[2]);
02574                                         }
02575                                         delete ccf; ccf =0;
02576                                         delete transformed; transformed = 0;
02577                                 }
02578 
02579                                 if(!tomography){
02580                                         if(!transformed) transformed = this_img->process("xform",Dict("transform",&t));
02581                                         best_score = c->cmp(to,transformed);
02582                                         delete transformed; transformed = 0;
02583                                 }
02584                                 
02585                                 unsigned int j = 0;
02586                                 for ( vector<Dict>::iterator it = solns.begin(); it != solns.end(); ++it, ++j ) {
02587                                         if ( (float)(*it)["score"] > best_score ) {  // Note greater than - EMAN2 preferes minimums as a matter of policy
02588                                                 vector<Dict>::reverse_iterator rit = solns.rbegin();
02589                                                 copy(rit+1,solns.rend()-j,rit);
02590                                                 Dict& d = (*it);
02591                                                 d["score"] = best_score;
02592                                                 d["xform.align3d"] = &t;
02593                                                 break;
02594                                         }
02595                                 }
02596                         }
02597                 }
02598         }
02599         
02600         if(tofft) {delete tofft; tofft = 0;}
02601         if (c != 0) delete c;
02602         
02603         return solns;
02604 
02605 }
02606 
02607 EMData* RT3DSphereAligner::align(EMData * this_img, EMData *to, const string & cmp_name, const Dict& cmp_params) const
02608 {
02609 
02610         vector<Dict> alis = xform_align_nbest(this_img,to,1,cmp_name,cmp_params);
02611 
02612         Dict t;
02613         Transform* tr = (Transform*) alis[0]["xform.align3d"];
02614         t["transform"] = tr;
02615         EMData* soln = this_img->process("xform",t);
02616         soln->set_attr("xform.align3d",tr);
02617         delete tr; tr = 0;
02618 
02619         return soln;
02620 
02621 }
02622 
02623 vector<Dict> RT3DSphereAligner::xform_align_nbest(EMData * this_img, EMData * to, const unsigned int nsoln, const string & cmp_name, const Dict& cmp_params) const {
02624 
02625         if ( this_img->get_ndim() != 3 || to->get_ndim() != 3 ) {
02626                 throw ImageDimensionException("This aligner only works for 3D images");
02627         }
02628 
02629         int searchx = 0;
02630         int searchy = 0;
02631         int searchz = 0;
02632          
02633         bool dotrans = params.set_default("dotrans",1);
02634         if (params.has_key("search")) {
02635                 vector<string> check;
02636                 check.push_back("searchx");
02637                 check.push_back("searchy");
02638                 check.push_back("searchz");
02639                 for(vector<string>::const_iterator cit = check.begin(); cit != check.end(); ++cit) {
02640                         if (params.has_key(*cit)) throw InvalidParameterException("The search parameter is mutually exclusive of the searchx, searchy, and searchz parameters");
02641                 }
02642                 int search  = params["search"];
02643                 searchx = search;
02644                 searchy = search;
02645                 searchz = search;
02646         } else {
02647                 searchx = params.set_default("searchx",3);
02648                 searchy = params.set_default("searchy",3);
02649                 searchz = params.set_default("searchz",3);
02650         }
02651 
02652         Transform* initxform;
02653         if (params.has_key("initxform") ) {
02654                 // Unlike the 2d refine aligner, this class doesn't require the starting transform's
02655                 // parameters to form the starting guess. Instead the Transform itself
02656                 // is perturbed carefully (using quaternion rotation) to overcome problems that arise
02657                 // when you use orthogonally-based Euler angles
02658                 initxform = params["initxform"];
02659         }else {
02660                 initxform = new Transform(); // is the identity
02661         }
02662         
02663         float lphi = params.set_default("phi0",0.0f);
02664         float uphi = params.set_default("phi1",360.0f);
02665         float dphi = params.set_default("dphi",10.f);
02666         float threshold = params.set_default("threshold",0.f);
02667         if (threshold < 0.0f) throw InvalidParameterException("The threshold parameter must be greater than or equal to zero");
02668         bool verbose = params.set_default("verbose",false);
02669         
02670         //in case we arre aligning tomos
02671         Dict altered_cmp_params(cmp_params);
02672         if (cmp_name == "ccc.tomo") {
02673                 altered_cmp_params.set_default("searchx", searchx);
02674                 altered_cmp_params.set_default("searchy", searchy);
02675                 altered_cmp_params.set_default("searchz", searchz);
02676                 altered_cmp_params.set_default("norm", true);
02677         }
02678 
02679         vector<Dict> solns;
02680         if (nsoln == 0) return solns; // What was the user thinking?
02681         for (unsigned int i = 0; i < nsoln; ++i ) {
02682                 Dict d;
02683                 d["score"] = 1.e24;
02684                 Transform t; // identity by default
02685                 d["xform.align3d"] = &t; // deep copy is going on here
02686                 solns.push_back(d);
02687         }
02688 
02689         Dict d;
02690         d["inc_mirror"] = true; // This should probably always be true for 3D case. If it ever changes we might have to make inc_mirror a parameter
02691         if ( params.has_key("delta") && params.has_key("n") ) {
02692                 throw InvalidParameterException("The delta and n parameters are mutually exclusive in the RT3DSphereAligner aligner");
02693         } else if ( params.has_key("n") ) {
02694                 d["n"] = params["n"];
02695         } else {
02696                 // If they didn't specify either then grab the default delta - if they did supply delta we're still safe doing this
02697                 d["delta"] = params.set_default("delta",10.f);
02698         }
02699 
02700         if ((string)params.set_default("orientgen","eman")=="eman") d["perturb"]=0;
02701         Symmetry3D* sym = Factory<Symmetry3D>::get((string)params.set_default("sym","c1"));
02702         vector<Transform> transforms = sym->gen_orientations((string)params.set_default("orientgen","eman"),d);
02703 
02704         bool tomography = (cmp_name == "ccc.tomo") ? 1 : 0;
02705         
02706         //precompute fixed FT, saves a LOT of time!!!
02707         EMData * this_imgfft = 0;
02708         if(dotrans || tomography){
02709                 this_imgfft = this_img->do_fft();
02710         }
02711         
02712 #ifdef EMAN2_USING_CUDA 
02713         if(EMData::usecuda == 1) {
02714                 cout << "Using CUDA for 3D alignment" << endl;
02715                 if(!to->getcudarodata()) to->copy_to_cudaro(); // Safer call
02716                 if(!this_img->getcudarwdata()) this_img->copy_to_cuda();
02717                 if(this_imgfft) this_imgfft->copy_to_cuda();
02718         }
02719 #endif
02720 
02721         Transform trans = Transform();
02722         Cmp* c = Factory <Cmp>::get(cmp_name, cmp_params);
02723         
02724         bool use_cpu = true;
02725         for(vector<Transform>::const_iterator trans_it = transforms.begin(); trans_it != transforms.end(); trans_it++) {
02726                 Dict params = trans_it->get_params("eman");
02727                 
02728                 if (verbose) {
02729                         float alt = params["alt"];
02730                         float az = params["az"];
02731                         cout << "Trying angle alt: " << alt << " az: " << az << endl;
02732                 }
02733 
02734                 for( float phi = lphi; phi < uphi; phi += dphi ) { 
02735                         params["phi"] = phi;
02736                         Transform t(params);
02737                         t = t*(*initxform);
02738                         
02739                         EMData* transformed;
02740                         transformed = to->process("xform",Dict("transform",&t));
02741                                 
02742                         //need to do things a bit diffrent if we want to compare two tomos
02743                         float best_score = 0.0f;
02744                         // Dotrans is effectievly ignored for tomography
02745                         if(dotrans || tomography){
02746                                 EMData* ccf = transformed->calc_ccf(this_imgfft);
02747 #ifdef EMAN2_USING_CUDA 
02748                                 if(EMData::usecuda == 1){
02749                                         // I use the following code rather than ccc.tomo to avoid doing two CCCs
02750                                         use_cpu = false;
02751                                         CudaPeakInfo* data = calc_max_location_wrap_cuda(ccf->getcudarwdata(), ccf->get_xsize(), ccf->get_ysize(), ccf->get_zsize(), searchx, searchy, searchz);
02752                                         trans.set_trans((float)-data->px, (float)-data->py, (float)-data->pz);
02753                                         t = trans*t;    //composite transform to reflect the fact that we have done a rotation first and THEN a transformation
02754                                         if (tomography) {
02755                                                 float2 stats = get_stats_cuda(ccf->getcudarwdata(), ccf->get_xsize(), ccf->get_ysize(), ccf->get_zsize());
02756                                                 best_score = -(data->peak - stats.x)/sqrt(stats.y); // Normalize, this is better than calling the norm processor since we only need to normalize one point
02757                                         } else {
02758                                                 best_score = -data->peak;
02759                                         }
02760                                         delete data;
02761                                 }
02762 #endif
02763                                 if(use_cpu){
02764                                         // I use the following code rather than ccc.tomo to avoid doing two CCCs
02765                                         if(tomography) ccf->process_inplace("normalize");
02766                                         IntPoint point = ccf->calc_max_location_wrap(searchx,searchy,searchz);
02767                                         trans.set_trans((float)-point[0], (float)-point[1], (float)-point[2]);
02768                                         t = trans*t;    //composite transform to reflect the fact that we have done a rotation first and THEN a transformation
02769                                         best_score = -ccf->get_value_at_wrap(point[0], point[1], point[2]);
02770                                 }
02771                                 delete ccf; ccf =0;
02772                                 delete transformed; transformed = 0;// this is to stop a mem leak
02773                         }
02774 
02775                         if(!tomography){
02776                                 if(!transformed) transformed = to->process("xform",Dict("transform",&t));
02777                                 best_score = c->cmp(this_img,transformed);
02778                                 delete transformed; transformed = 0;
02779                         }
02780 
02781                         unsigned int j = 0;
02782                         //cout << "alt " <<float(t.get_rotation("eman").get("alt")) << " az " << float(t.get_rotation("eman").get("az")) << " phi " << float(t.get_rotation("eman").get("phi")) << endl;
02783                         for ( vector<Dict>::iterator it = solns.begin(); it != solns.end(); ++it, ++j ) {
02784                                 if ( (float)(*it)["score"] > best_score ) { // Note greater than - EMAN2 preferes minimums as a matter of policy
02785                                         vector<Dict>::reverse_iterator rit = solns.rbegin();
02786                                         copy(rit+1,solns.rend()-j,rit);
02787                                         Dict& d = (*it);
02788                                         d["score"] = best_score;
02789                                         t.invert(); //We actually moved the ref onto the moving, so we need to invert to do the opposite(this is done b/c the ref is aligned to the sym axis, whereas the mvoing is not)
02790                                         d["xform.align3d"] = &t; // deep copy is going on here
02791                                         break;
02792                                 }
02793                         }
02794 
02795                 }
02796         }
02797         
02798         if(this_imgfft) {delete this_imgfft; this_imgfft = 0;}
02799         if(sym!=0) delete sym;
02800         if (c != 0) delete c;
02801         
02802         return solns;
02803 
02804 }
02805 
02806 //Could refactor the code here......(But not really woth it)
02807 EMData* RT3DSymmetryAligner::align(EMData * this_img, EMData *to, const string & cmp_name, const Dict& cmp_params) const
02808 {
02809 
02810         vector<Dict> alis = xform_align_nbest(this_img,to,1,cmp_name,cmp_params);
02811 
02812         Transform* tr = (Transform*) alis[0]["xform.align3d"];
02813         EMData* soln = this_img->process("xform",Dict("transform",tr));
02814         soln->set_attr("xform.align3d",tr);
02815         delete tr; tr = 0;
02816 
02817         return soln;
02818 
02819 }
02820 
02821 vector<Dict> RT3DSymmetryAligner::xform_align_nbest(EMData * this_img, EMData * to, const unsigned int nsoln, const string & cmp_name, const Dict& cmp_params) const 
02822 {
02823         
02824         bool verbose = params.set_default("verbose",false);
02825         Transform* ixform;
02826         if (params.has_key("transform") ) {
02827                 ixform = params["transform"];
02828         }else{
02829                 ixform = new Transform(); // is the identity
02830         }
02831         
02832         //Initialize a soln dict
02833         vector<Dict> solns;
02834         if (nsoln == 0) return solns; // What was the user thinking?
02835         for (unsigned int i = 0; i < nsoln; ++i ) {
02836                 Dict d;
02837                 d["score"] = 1.e24;
02838                 Transform t; // identity by default
02839                 d["xform.align3d"] = &t; // deep copy is going on here
02840                 solns.push_back(d);
02841         }
02842         
02843         #ifdef EMAN2_USING_CUDA 
02844         if(EMData::usecuda == 1) {
02845                 cout << "Using CUDA for 3D sym alignment" << endl;
02846                 if(!this_img->getcudarwdata()) this_img->copy_to_cudaro();
02847                 if(!to->getcudarwdata()) to->copy_to_cuda();
02848         }
02849         #endif
02850 
02851         //Generate symmetry related orientations
02852         vector<Transform> syms = Symmetry3D::get_symmetries((string)params.set_default("sym","icos"));
02853         Cmp* c = Factory <Cmp>::get(cmp_name, cmp_params);
02854         
02855         float score = 0.0f;
02856         for ( vector<Transform>::const_iterator symit = syms.begin(); symit != syms.end(); ++symit ) {
02857                 //Here move to sym position and compute the score
02858                 Transform sympos = (*symit)*(*ixform);
02859                 EMData* transformed = this_img->process("xform",Dict("transform", &sympos));
02860                 score = c->cmp(transformed,to);
02861                 delete transformed; transformed = 0;
02862                 
02863                 if (verbose) {
02864                         Dict rots = sympos.get_rotation("eman");
02865                         cout <<"Score is: " << score << " az " << float(rots["az"]) << " alt " << float(rots["alt"]) << " phi " << float(rots["phi"]) << endl;
02866                 }
02867                 
02868                 unsigned int j = 0;
02869                 for ( vector<Dict>::iterator it = solns.begin(); it != solns.end(); ++it, ++j ) {
02870                         if ( (float)(*it)["score"] > score ) { // Note greater than - EMAN2 preferes minimums as a matter of policy
02871                                 vector<Dict>::reverse_iterator rit = solns.rbegin();
02872                                 copy(rit+1,solns.rend()-j,rit);
02873                                 Dict& d = (*it);
02874                                 d["score"] = score;
02875                                 d["xform.align3d"] = &sympos; // deep copy is going on here
02876                                 break;
02877                         }
02878                 }
02879         }
02880         
02881         if (c != 0) delete c;
02882         
02883         return solns;
02884 }
02885 
02886 namespace {
02887 float frm_2d_Align(EMData *this_img, EMData *to, float *frm2dhhat, EMData* selfpcsfft, int p_max_input,int rsize, float &com_this_x, float &com_this_y, float &com_with_x, float &com_with_y,const string & cmp_name, const Dict& cmp_params)
02888 {
02889         int size=rsize;
02890         float dx,dy;
02891         int bw=size/2;
02892         int MAXR=this_img->get_ysize()/2;
02893         //int MAXR=size;
02894         unsigned long tsize=2*size;
02895         unsigned long ind1=0, ind2=0, ind3=0, ind4=0, ind41=0;
02896         unsigned long index0=0;
02897         int i=0, j=0, m=0, n=0, r=0;
02898         int loop_rho=0, rho_best=0;
02899 
02900         float* gnr2   = new float[size*2];
02901         float* maxcor = new float[size+1];                  // MAXR need change
02902 
02903         int p_max=p_max_input;
02904         float* result = new float[5*(p_max+1)];
02905         float* cr=new float[size*(bw+1)];
02906         float* ci=new float[size*(bw+1)];
02907         EMData *data_in=new EMData;
02908         data_in->set_complex(true);
02909         data_in->set_fftodd(false);
02910         data_in->set_ri(true);
02911         data_in->set_size(size+2,size,1);
02912         float *in=data_in->get_data();
02913 
02914         float *self_sampl_fft = selfpcsfft->get_data(); // ming f(r)
02915 
02916         float maxcor_sofar=0.0f;
02917         int p=0;
02918 
02919         for(p=0; p<=p_max; ++p){
02920                 ind1=p*size*bw;
02921                 for (i=0;i<size;++i)
02922                         for (j=0;j<bw+1;++j){
02923                                 cr[i*(bw+1)+j]=0.0;
02924                                 ci[i*(bw+1)+j]=0.0;
02925                         }
02926         for(n=0;n<bw;++n){                                // loop for n
02927                 ind2=(ind1+n);
02928                 index0=n*(bw+1);
02929                         for(r=0;r<=MAXR;++r) {
02930                         ind3=(ind2+r*bw)*size;
02931                         for(m=0;m<size;m++){              // take back hat{h(n,r,p)}(m)
02932                                 ind4=(ind3+m)*2;
02933                                     ind41=ind4+1;
02934                                     gnr2[2*m]=frm2dhhat[ind4];
02935                                     gnr2[2*m+1]=frm2dhhat[ind41];
02936                                 }
02937                         for(m=0;m<bw;++m){
02938                                         float tempr=self_sampl_fft[2*m+r*(size+2)]*r;
02939                                 float tempi=self_sampl_fft[2*m+1+r*(size+2)]*r;
02940                                 float gnr2_r=gnr2[2*m];
02941                                 float gnr2_i=gnr2[2*m+1];
02942                                 cr[n*(bw+1)+m]+=gnr2_r*tempr+gnr2_i*tempi;
02943                                         ci[n*(bw+1)+m]+=gnr2_i*tempr-gnr2_r*tempi;
02944                                         if(n!=0){                                       // m,-n
02945                                         if(m!= 0){
02946                                                 int ssize=tsize-2*m;    // ssize = 2*size-2m
02947                                                 int ssize1=ssize+1;
02948                                                 float gnr2_r=gnr2[ssize];
02949                                                 float gnr2_i=gnr2[ssize1];
02950                                                         cr[(size-n)*(bw+1)+m]+=gnr2_r*tempr-gnr2_i*tempi;
02951                                                 ci[(size-n)*(bw+1)+m]-=gnr2_i*tempr+gnr2_r*tempi;
02952                                         }
02953                                                 else{
02954                                                         cr[(size-n)*(bw+1)+m]+=*(gnr2)*tempr-*(gnr2+1)*tempi;
02955                                                         ci[(size-n)*(bw+1)+m]-=*(gnr2+1)*tempr+*(gnr2)*tempi;
02956                                                 }
02957                                 }
02958                                 }
02959                         }
02960         }
02961         for (int cii=0; cii<size*(bw+1);++cii){
02962                         in[2*cii]=cr[cii];
02963                         in[2*cii+1]=ci[cii];
02964                         //printf("cii=%d,in[2i+1]=%f\n",cii, cr[cii]);
02965         }
02966 
02967         EMData *data_out;
02968                 data_out=data_in->do_ift();
02969                 float *c=data_out->get_data();
02970                 float tempr=0.0f, corre_fcs=999.0f;
02971 
02972             int n_best=0, m_best=0;
02973         float temp=-100.0f;
02974                 for(n=0;n<size;++n){// move Tri_2D to Tri = c(phi,phi';rho)
02975                         for(m=0;m<size;++m){
02976                                 temp=c[n*size+m];
02977                                 if(temp>tempr) {
02978                                         tempr=temp;
02979                                         n_best=n;
02980                                         m_best=m;
02981                                 }
02982                         }
02983                 }
02984                 delete data_out;
02985 
02986                 float corre,Phi2,Phi,Tx,Ty,Vx, Vy;
02987 
02988                 //for (n_best=0;n_best<bw;n_best++)
02989                   //  for (m_best=0;m_best<2*bw;m_best++){
02990                 //n_best=0;
02991                 //m_best=70;
02992                 Phi2=n_best*M_PI/bw;  // ming this is reference image rotation angle
02993                 Phi=m_best*M_PI/bw;   // ming this is particle image rotation angle
02994                 Vx=p*cos(Phi);//should use the angle of the centered one
02995                 Vy=-p*sin(Phi);
02996                 Tx=Vx+(floor(com_this_x+0.5f)-floor(com_with_x+0.5f));
02997                 Ty=Vy+(floor(com_this_y+0.5f)-floor(com_with_y+0.5f));
02998 
02999                 dx=-Tx; // the Rota & Trans value (Tx,Ty, ang_keep) are for the projection image,
03000                 dy=-Ty; // need to convert to raw image
03001 
03002                 EMData *this_tmp=this_img->copy();//ming change to to
03003                 this_tmp->rotate(-(Phi2-Phi)*180.0f,0.0f,0.0f);
03004                 this_tmp->translate(dx,dy,0.0);
03005 
03006                 corre=this_tmp->cmp(cmp_name,to,cmp_params);
03007                 //printf("corre=%f\n",corre);
03008                 delete this_tmp;
03009                 if(corre<=corre_fcs) { //ming, cmp use smaller value stands for more similarity
03010                         corre_fcs=corre;
03011                         result[0+5*p] = float(p);       // rho
03012                         result[1+5*p] = corre;          // correlation_fcs
03013                         result[2+5*p] = (Phi2-Phi)*180.0f;      // rotation angle
03014                         result[3+5*p] = Tx;             // Translation_x
03015                         result[4+5*p] = Ty;             // Translation_y
03016                 }
03017                 maxcor[p]=corre_fcs;                            //  maximum correlation for current rho
03018                 if(corre_fcs<maxcor_sofar) {
03019                         maxcor_sofar=corre_fcs;                 // max correlation up to current rho
03020                     rho_best=p;                         // the rho value with maxinum correlation value
03021                 }
03022                 if(p>=4){
03023                         if(maxcor[p] < maxcor[p-1] && maxcor[p-1] < maxcor[p-2]&& maxcor[p-2] < maxcor[p-3] && maxcor[p-3] < maxcor[p-4]){
03024                                 loop_rho=1;
03025                                 break; //exit p loop
03026                         }
03027                 }
03028         } // end for p
03029         //}//test my method
03030         if(loop_rho == 1)
03031                 p=p+1;
03032         int rb5=5*rho_best;
03033         float fsc      = result[1+rb5];
03034         float ang_keep = result[2+rb5];
03035         float Tx       = result[3+rb5];
03036         float Ty       = result[4+rb5];
03037         delete[] gnr2;
03038         delete[] maxcor;
03039         delete[] result;
03040         delete cr;
03041         cr=0;
03042         delete ci;
03043         ci=0;
03044         delete data_in; // ming add
03045         dx = -Tx;               // the Rota & Trans value (Tx,Ty, ang_keep) are for the projection image,
03046         dy = -Ty;               // need to convert to raw image
03047         this_img->rotate(-ang_keep,0,0); // ming change this to this_img??
03048         this_img->translate(dx,dy,0.0); // ming change this to this_img
03049 
03050 
03051         Transform  tsoln(Dict("type","2d","alpha",ang_keep));
03052         tsoln.set_trans(dx,dy);
03053         this_img->set_attr("xform.align2d",&tsoln);
03054 #ifdef DEBUG
03055         float fsc_best=this_img->cmp(cmp_name,to,cmp_params);
03056         printf("rho_best=%d fsc=%f fsc_best=%f dx=%f dy=%f ang_keep=%f com_withx=%f com_selfx=%f com_selfy=%f\n",rho_best,fsc,fsc_best,dx,dy,ang_keep,com_with_x,com_this_x,com_this_y);
03057 #endif
03058         return fsc;     // return the fsc coefficients
03059 } // FRM2D aligner sub_class
03060 } // end namespace
03061 
03062 
03063 EMData *FRM2DAligner::align(EMData * this_img, EMData * to,
03064                         const string & cmp_name, const Dict& cmp_params) const
03065 {
03066         if (!this_img) {
03067                 return 0;
03068         }
03069         if (to && !EMUtil::is_same_size(this_img, to))
03070                 throw ImageDimensionException("Images must be the same size to perform translational alignment");
03071 
03072         int nx=this_img->get_xsize();
03073         int ny=this_img->get_ysize();
03074         int size =(int)floor(M_PI*ny/4.0);
03075         size =Util::calc_best_fft_size(size);//ming   bestfftsize(size);
03076         int MAXR=ny/2;
03077         //int MAXR=size;
03078         EMData *this_temp=this_img->copy(); // ming change avg to to
03079         FloatPoint com_test,com_test1;
03080         com_test=this_temp->calc_center_of_mass();//ming add
03081         float com_this_x=com_test[0];
03082         float com_this_y=com_test[1];
03083         delete this_temp;
03084 
03085 
03086         EMData *that_temp=to->copy();
03087         com_test1=that_temp->calc_center_of_mass();
03088         float com_with_x=com_test1[0];
03089         float com_with_y=com_test1[1];
03090         delete that_temp;
03091 
03092         EMData *avg_frm=to->copy();
03093         float dx,dy;
03094         //float dx=-(com_with_x-nx/2); //ming
03095         //float dy=-(com_with_y-ny/2); //ming
03096         //avg_frm->translate(dx,dy,0.0);
03097         EMData *withpcs=avg_frm->unwrap_largerR(0,MAXR,size,float(MAXR)); // ming, something wrong inside this subroutine
03098         //EMData *withpcs=avg_frm->unwrap(-1,-1,-1,0,0,1);
03099         EMData *withpcsfft=withpcs->oneDfftPolar(size, float(MAXR), float(MAXR));
03100 
03101         float *sampl_fft=withpcsfft->get_data(); //
03102         delete avg_frm;
03103         delete withpcs;
03104 
03105         int bw=size/2;
03106         unsigned long ind1=0, ind2=0, ind3=0, ind4=0, ind41=0;
03107         float pi2=2.0*M_PI, r2;
03108 
03109         EMData *data_in=new EMData;
03110         data_in->set_complex(true);
03111         data_in->set_ri(1);
03112         data_in->set_size(2*size,1,1);
03113         float * comp_in=data_in->get_data();
03114 
03115         int p_max=3;
03116         float *frm2dhhat=0;
03117 
03118         if( (frm2dhhat=(float *)malloc((p_max+1)*(size+2)*bw*size*2* sizeof(float)))==NULL){
03119                 cout <<"Error in allocating memory 13. \n";
03120                 exit(1);
03121         }
03122         //printf("p_max=%d\n",p_max);
03123         float *sb=0, *cb=0;             // sin(beta) and cos(beta) for get h_hat, 300>size
03124         if((sb=new float[size])==NULL||(cb=new float[size])==NULL) {
03125                 cout <<"can't allocate more memory, terminating. \n";
03126                 exit(1);
03127         }
03128         for(int i=0;i<size;++i) {        // beta sampling, to calculate beta' and r'
03129                 float beta=i*M_PI/bw;
03130                 sb[i]=sin(beta);
03131                 cb[i]=cos(beta);
03132         }
03133 
03134         for(int p=0; p<=p_max; ++p){
03135                 ind1=p*size*bw;
03136         float pp2=(float)(p*p);
03137                 for(int n=0;n<bw;++n){         /* loop for n */
03138                 ind2=ind1+n;
03139                 for(int r=0;r<=MAXR;++r) {
03140                                 ind3=(ind2+r*bw)*size;
03141                         float rr2=(float)(r*r);
03142                                 float rp2=(float)(r*p);
03143                         for(int i=0;i<size;++i){                            // beta sampling, to get beta' and r'
03144                                 r2=std::sqrt((float)(rr2+pp2-2.0*rp2*cb[i]));   // r2->r'
03145                                 int r1=(int)floor(r2+0.5f);                        // for computing gn(r')
03146                                 if(r1>MAXR){
03147                                         comp_in[2*i]=0.0f;
03148                                         comp_in[2*i+1]=0.0f;
03149                                 }
03150                                 else{
03151                                         float gn_r=sampl_fft[2*n+r1*(size+2)];           // real part of gn(r')
03152                                         float gn_i=sampl_fft[2*n+1+r1*(size+2)];           // imaginary part of gn(r')
03153                                                 float sb2, cb2, cn, sn;
03154                                                 if(n!=0){
03155                                                         if(r2 != 0.0){
03156                                                                 sb2=r*sb[i]/r2;
03157                                                                 cb2=(r*cb[i]-p)/r2;
03158                                                         }
03159                                                 else{
03160                                                                 sb2=0.0;
03161                                                                 cb2=1.0;
03162                                                         }
03163                                                 if(sb2>1.0) sb2= 1.0f;
03164                                                 if(sb2<-1.0)sb2=-1.0f;
03165                                                 if(cb2>1.0) cb2= 1.0f;
03166                                                 if(cb2<-1.0)cb2=-1.0f;
03167                                                 float beta2=atan2(sb2,cb2);
03168                                                 if(beta2<0.0) beta2+=pi2;
03169                                                 float nb2=n*beta2;
03170                                                 cn=cos(nb2);
03171                                                         sn=sin(nb2);
03172                                                 }
03173                                         else{
03174                                                         cn=1.0f; sn=0.0f;
03175                                                 }
03176                                                 comp_in[2*i]=cn*gn_r-sn*gn_i;
03177                                                 comp_in[2*i+1]=-(cn*gn_i+sn*gn_r);
03178                                 }
03179                         }
03180                         EMData *data_out;
03181                         data_out=data_in->do_fft();
03182                         float * comp_out=data_out->get_data();
03183                         for(int m=0;m<size;m++){                                     // store hat{h(n,r,p)}(m)
03184                                         ind4=(ind3+m)*2;
03185                                         ind41=ind4+1;
03186                                         frm2dhhat[ind4]=comp_out[2*m];
03187                                         frm2dhhat[ind41]=comp_out[2*m+1];
03188                                 }
03189                         delete data_out;
03190                         }
03191                 }
03192         }
03193 
03194         delete[] sb;
03195         delete[] cb;
03196         delete data_in;
03197         delete withpcsfft;
03198 
03199         float dot_frm0=0.0f, dot_frm1=0.0f;
03200         EMData *da_nFlip=0, *da_yFlip=0, *dr_frm=0;
03201         //dr_frm=this_img->copy();
03202         for (int iFlip=0;iFlip<=1;++iFlip){
03203                 if (iFlip==0){dr_frm=this_img->copy();  da_nFlip=this_img->copy();}
03204                 else {dr_frm=this_img->copy(); da_yFlip=this_img->copy();}
03205                 if(iFlip==1) {com_this_x=nx-com_this_x; } //ming   // image mirror about Y axis, so y keeps the same
03206 
03207                 dx=-(com_this_x-nx/2); //ming
03208                 dy=-(com_this_y-ny/2); //ming
03209                 dr_frm->translate(dx,dy,0.0); // this
03210                 EMData *selfpcs = dr_frm->unwrap_largerR(0,MAXR,size, (float)MAXR);
03211                 //EMData *selfpcs=dr_frm->unwrap(-1,-1,-1,0,0,1);
03212                 EMData *selfpcsfft = selfpcs->oneDfftPolar(size, (float)MAXR, (float)MAXR);
03213                 delete selfpcs;
03214                 delete dr_frm;
03215                 if(iFlip==0)
03216                         dot_frm0=frm_2d_Align(da_nFlip,to, frm2dhhat, selfpcsfft, p_max, size, com_this_x, com_this_y, com_with_x, com_with_y,cmp_name,cmp_params);
03217                 else
03218                         dot_frm1=frm_2d_Align(da_yFlip,to, frm2dhhat, selfpcsfft, p_max, size, com_this_x, com_this_y, com_with_x, com_with_y,cmp_name,cmp_params);
03219                 delete selfpcsfft;
03220         }
03221 
03222         delete[] frm2dhhat;
03223         if(dot_frm0 <=dot_frm1) {
03224 #ifdef DEBUG
03225                 printf("best_corre=%f, no flip\n",dot_frm0);
03226 #endif
03227                 delete da_yFlip;
03228                 return da_nFlip;
03229         }
03230         else {
03231 #ifdef DEBUG
03232                 printf("best_corre=%f, flipped\n",dot_frm1);
03233 #endif
03234                 delete da_nFlip;
03235                 return da_yFlip;
03236         }
03237 }
03238 
03239 #ifdef SPARX_USING_CUDA
03240 
03241 CUDA_Aligner::CUDA_Aligner(int id) {
03242         image_stack = NULL;
03243         image_stack_filtered = NULL;
03244         ccf = NULL;
03245         if (id != -1) cudasetup(id);
03246 }
03247 
03248 void CUDA_Aligner::finish() {
03249         if (image_stack) free(image_stack);
03250         if (image_stack_filtered) free(image_stack_filtered);
03251         if (ccf) free(ccf);
03252         image_stack = NULL;
03253         image_stack_filtered = NULL;
03254         ccf = NULL;
03255 }
03256 
03257 void CUDA_Aligner::setup(int nima, int nx, int ny, int ring_length, int nring, int ou, float step, int kx, int ky, bool ctf) {
03258 
03259         NIMA = nima;
03260         NX = nx;
03261         NY = ny;
03262         RING_LENGTH = ring_length;
03263         NRING = nring;
03264         STEP = step;
03265         KX = kx;
03266         KY = ky;
03267         OU = ou;
03268         CTF = ctf;
03269         
03270         image_stack = (float *)malloc(NIMA*NX*NY*sizeof(float));
03271         if (CTF == 1) image_stack_filtered = (float *)malloc(NIMA*NX*NY*sizeof(float));
03272         ccf = (float *)malloc(2*(2*KX+1)*(2*KY+1)*NIMA*(RING_LENGTH+2)*sizeof(float));
03273 }
03274 
03275 void CUDA_Aligner::insert_image(EMData *image, int num) {
03276 
03277         int base_address = num*NX*NY;
03278 
03279         for (int y=0; y<NY; y++)
03280                 for (int x=0; x<NX; x++)
03281                         image_stack[base_address+y*NX+x] = (*image)(x, y);
03282 }
03283 
03284 void CUDA_Aligner::filter_stack(vector<float> ctf_params) {
03285         
03286         float *params;
03287         
03288         params = (float *)malloc(NIMA*6*sizeof(float)); 
03289         
03290         for (int i=0; i<NIMA*6; i++) params[i] = ctf_params[i];
03291 
03292         filter_image(image_stack, image_stack_filtered, NIMA, NX, NY, params);
03293 
03294         free(params);
03295 }
03296 
03297 void CUDA_Aligner::sum_oe(vector<float> ctf_params, vector<float> ali_params, EMData *ave1, EMData *ave2) {
03298         
03299         float *ctf_p, *ali_p, *av1, *av2;
03300         
03301         ctf_p = (float *)malloc(NIMA*6*sizeof(float));
03302         ali_p = (float *)malloc(NIMA*4*sizeof(float));
03303         
03304         if (CTF == 1) {
03305                 for (int i=0; i<NIMA*6; i++)  ctf_p[i] = ctf_params[i];
03306         }
03307         for (int i=0; i<NIMA*4; i++)   ali_p[i] = ali_params[i];
03308         
03309         av1 = ave1->get_data();
03310         av2 = ave2->get_data();
03311         
03312         rot_filt_sum(image_stack, NIMA, NX, NY, CTF, ctf_p, ali_p, av1, av2);
03313         
03314         free(ctf_p);
03315         free(ali_p);
03316 }
03317 
03318 vector<float> CUDA_Aligner::alignment_2d(EMData *ref_image_em, vector<float> sx_list, vector<float> sy_list, int silent) {
03319 
03320         float *ref_image, max_ccf;
03321         int base_address, ccf_offset;
03322         float ts, tm;
03323         float ang, sx = 0, sy = 0, mirror, co, so, sxs, sys;
03324         float *sx2, *sy2;
03325         vector<float> align_result;
03326 
03327         sx2 = (float *)malloc(NIMA*sizeof(float));
03328         sy2 = (float *)malloc(NIMA*sizeof(float));
03329 
03330         ref_image = ref_image_em->get_data();
03331         
03332         for (int i=0; i<NIMA; i++) {
03333                 sx2[i] = sx_list[i];
03334                 sy2[i] = sy_list[i];
03335         }
03336         
03337         if (CTF == 1) {
03338                 calculate_ccf(image_stack_filtered, ref_image, ccf, NIMA, NX, NY, RING_LENGTH, NRING, OU, STEP, KX, KY, sx2, sy2, silent);
03339         } else {
03340                 calculate_ccf(image_stack, ref_image, ccf, NIMA, NX, NY, RING_LENGTH, NRING, OU, STEP, KX, KY, sx2, sy2, silent);
03341         }
03342 
03343         ccf_offset = NIMA*(RING_LENGTH+2)*(2*KX+1)*(2*KY+1);
03344 
03345         for (int im=0; im<NIMA; im++) {
03346                 max_ccf = -1.0e22;
03347                 for (int kx=-KX; kx<=KX; kx++) {
03348                         for (int ky=-KY; ky<=KY; ky++) {
03349                                 base_address = (((ky+KY)*(2*KX+1)+(kx+KX))*NIMA+im)*(RING_LENGTH+2);
03350                                 for (int l=0; l<RING_LENGTH; l++) {
03351                                         ts = ccf[base_address+l];
03352                                         tm = ccf[base_address+l+ccf_offset];
03353                                         if (ts > max_ccf) {
03354                                                 ang = float(l)/RING_LENGTH*360.0;
03355                                                 sx = -kx*STEP;
03356                                                 sy = -ky*STEP;
03357                                                 mirror = 0;
03358                                                 max_ccf = ts;
03359                                         }
03360                                         if (tm > max_ccf) {
03361                                                 ang = float(l)/RING_LENGTH*360.0; 
03362                                                 sx = -kx*STEP;
03363                                                 sy = -ky*STEP;
03364                                                 mirror = 1;
03365                                                 max_ccf = tm;
03366                                         }
03367                                 }
03368                         }
03369                 }
03370                 co =  cos(ang*M_PI/180.0);
03371                 so = -sin(ang*M_PI/180.0);
03372                 sxs = sx*co - sy*so;
03373                 sys = sx*so + sy*co;
03374 
03375                 align_result.push_back(ang);
03376                 align_result.push_back(sxs);
03377                 align_result.push_back(sys);
03378                 align_result.push_back(mirror);
03379         }
03380         
03381         free(sx2);
03382         free(sy2);
03383         
03384         return align_result;
03385 }
03386 
03387 
03388 vector<float> CUDA_Aligner::ali2d_single_iter(EMData *ref_image_em, vector<float> ali_params, float csx, float csy, int silent, float delta) {
03389 
03390         float *ref_image, max_ccf;
03391         int base_address, ccf_offset;
03392         float ts, tm;
03393         float ang = 0.0, sx = 0.0, sy = 0.0, co, so, sxs, sys;
03394         int mirror;
03395         float *sx2, *sy2;
03396         vector<float> align_result;
03397 
03398         sx2 = (float *)malloc(NIMA*sizeof(float));
03399         sy2 = (float *)malloc(NIMA*sizeof(float));
03400 
03401         ref_image = ref_image_em->get_data();
03402         
03403         for (int i=0; i<NIMA; i++) {
03404                 ang = ali_params[i*4]/180.0*M_PI;
03405                 sx = (ali_params[i*4+3] < 0.5)?(ali_params[i*4+1]-csx):(ali_params[i*4+1]+csx);
03406                 sy = ali_params[i*4+2]-csy;
03407                 co = cos(ang);
03408                 so = sin(ang);
03409                 sx2[i] = -(sx*co-sy*so);
03410                 sy2[i] = -(sx*so+sy*co);
03411         }
03412         
03413         if (CTF == 1) {
03414                 calculate_ccf(image_stack_filtered, ref_image, ccf, NIMA, NX, NY, RING_LENGTH, NRING, OU, STEP, KX, KY, sx2, sy2, silent);
03415         } else {
03416                 calculate_ccf(image_stack, ref_image, ccf, NIMA, NX, NY, RING_LENGTH, NRING, OU, STEP, KX, KY, sx2, sy2, silent);
03417         }
03418 
03419         ccf_offset = NIMA*(RING_LENGTH+2)*(2*KX+1)*(2*KY+1);
03420 
03421         float sx_sum = 0.0f;
03422         float sy_sum = 0.0f;
03423 
03424         int dl;
03425         dl = static_cast<int>(delta/360.0*RING_LENGTH);
03426         if (dl<1) { dl = 1; }   
03427         
03428         for (int im=0; im<NIMA; im++) {
03429                 max_ccf = -1.0e22;
03430                 for (int kx=-KX; kx<=KX; kx++) {
03431                         for (int ky=-KY; ky<=KY; ky++) {
03432                                 base_address = (((ky+KY)*(2*KX+1)+(kx+KX))*NIMA+im)*(RING_LENGTH+2);
03433                                 for (int l=0; l<RING_LENGTH; l+=dl) {
03434                                         ts = ccf[base_address+l];
03435                                         tm = ccf[base_address+l+ccf_offset];
03436                                         if (ts > max_ccf) {
03437                                                 ang = float(l)/RING_LENGTH*360.0;
03438                                                 sx = -kx*STEP;
03439                                                 sy = -ky*STEP;
03440                                                 mirror = 0;
03441                                                 max_ccf = ts;
03442                                         }
03443                                         if (tm > max_ccf) {
03444                                                 ang = float(l)/RING_LENGTH*360.0; 
03445                                                 sx = -kx*STEP;
03446                                                 sy = -ky*STEP;
03447                                                 mirror = 1;
03448                                                 max_ccf = tm;
03449                                         }
03450                                 }
03451                         }
03452                 }
03453                 co =  cos(ang*M_PI/180.0);
03454                 so = -sin(ang*M_PI/180.0);
03455                 
03456                 sxs = (sx-sx2[im])*co-(sy-sy2[im])*so;
03457                 sys = (sx-sx2[im])*so+(sy-sy2[im])*co;
03458 
03459                 //if (sxs*sxs+sys*sys >= 7*7) { sxs=0; sys=0; }
03460 
03461                 align_result.push_back(ang);
03462                 align_result.push_back(sxs);
03463                 align_result.push_back(sys);
03464                 align_result.push_back(mirror);
03465                 
03466                 if (mirror == 0)  { sx_sum += sxs; }  else { sx_sum -= sxs; }
03467                 sy_sum += sys;
03468         }
03469         
03470         align_result.push_back(sx_sum);
03471         align_result.push_back(sy_sum);
03472         
03473         free(sx2);
03474         free(sy2);
03475         
03476         return align_result;
03477 }
03478 
03479 
03480 CUDA_multiref_aligner::CUDA_multiref_aligner(int id) {
03481         image_stack = NULL;
03482         ref_image_stack = NULL;
03483         ref_image_stack_filtered = NULL;
03484         ccf = NULL;
03485         ctf_params = NULL;
03486         ali_params = NULL;
03487         cudasetup(id);
03488 }
03489 
03490 
03491 void CUDA_multiref_aligner::finish() {
03492         if (image_stack) free(image_stack);
03493         if (ref_image_stack) free(ref_image_stack);
03494         if (ref_image_stack_filtered) free(ref_image_stack_filtered);
03495         if (ccf) free(ccf);
03496         if (ctf_params) free(ctf_params);
03497         if (ali_params) free(ali_params);
03498         image_stack = NULL;
03499         ref_image_stack = NULL;
03500         ref_image_stack_filtered = NULL;
03501         ccf = NULL;
03502         ctf_params = NULL;
03503         ali_params = NULL;
03504 }       
03505 
03506 void CUDA_multiref_aligner::setup(int nima, int nref, int nx, int ny, int ring_length, int nring, int ou, float step, int kx, int ky, bool ctf) {
03507 
03508         NIMA = nima;
03509         NREF = nref;
03510         NX = nx;
03511         NY = ny;
03512         RING_LENGTH = ring_length;
03513         NRING = nring;
03514         STEP = step;
03515         KX = kx;
03516         KY = ky;
03517         OU = ou;
03518         CTF = ctf;
03519         // This number can be increased according to the GPU memory. But my tests has shown the speedup 
03520         // is limited (~5%) even if I increased the size 10 times, so it's better to be on the safe side.
03521         MAX_IMAGE_BATCH = 10;
03522         
03523         image_stack = (float *)malloc(NIMA*NX*NY*sizeof(float));
03524         ref_image_stack = (float *)malloc(NREF*NX*NY*sizeof(float));
03525         if (CTF == 1) ref_image_stack_filtered = (float *)malloc(NREF*NX*NY*sizeof(float));
03526         ccf = (float *)malloc(2*(2*KX+1)*(2*KY+1)*NREF*(RING_LENGTH+2)*MAX_IMAGE_BATCH*sizeof(float));
03527 }
03528 
03529 void CUDA_multiref_aligner::setup_params(vector<float> all_ali_params, vector<float> all_ctf_params) {
03530         
03531         ali_params = (float *)malloc(NIMA*4*sizeof(float));
03532         for (int i=0; i<NIMA*4; i++)   ali_params[i] = all_ali_params[i];
03533         if (CTF == 1) {
03534                 ctf_params = (float *)malloc(NIMA*6*sizeof(float));
03535                 for (int i=0; i<NIMA*6; i++)  ctf_params[i] = all_ctf_params[i];
03536         }
03537 }
03538 
03539 void CUDA_multiref_aligner::insert_image(EMData *image, int num) {
03540 
03541         int base_address = num*NX*NY;
03542 
03543         for (int y=0; y<NY; y++)
03544                 for (int x=0; x<NX; x++)
03545                         image_stack[base_address+y*NX+x] = (*image)(x, y);
03546 }
03547 
03548 void CUDA_multiref_aligner::insert_ref_image(EMData *image, int num) {
03549 
03550         int base_address = num*NX*NY;
03551 
03552         for (int y=0; y<NY; y++)
03553                 for (int x=0; x<NX; x++)
03554                         ref_image_stack[base_address+y*NX+x] = (*image)(x, y);
03555 }
03556 
03557 vector<float> CUDA_multiref_aligner::multiref_ali2d(int silent) {
03558 
03559         float *ctf_params_ref = (float *)malloc(NREF*6*sizeof(float));  
03560         float *sx2 = (float *)malloc(NIMA*sizeof(float));
03561         float *sy2 = (float *)malloc(NIMA*sizeof(float));
03562         vector<float> align_results;
03563         int ccf_offset = NREF*(RING_LENGTH+2)*(2*KX+1)*(2*KY+1);
03564 
03565         vector<int> batch_size;
03566         vector<int> batch_begin;
03567         
03568         if (CTF == 1) {
03569                 float previous_defocus = ctf_params[0];
03570                 int current_size = 1;
03571                 for (int i=1; i<NIMA; i++) {
03572                         if (ctf_params[i*6] != previous_defocus || current_size >= MAX_IMAGE_BATCH) {
03573                                 batch_size.push_back(current_size);
03574                                 current_size = 1;
03575                                 previous_defocus = ctf_params[i*6];
03576                         } else current_size++;                  
03577                 }
03578                 batch_size.push_back(current_size);
03579         } else {
03580                 batch_size.resize(NIMA/MAX_IMAGE_BATCH, MAX_IMAGE_BATCH);
03581                 if (NIMA%MAX_IMAGE_BATCH != 0)  batch_size.push_back(NIMA%MAX_IMAGE_BATCH);
03582         }
03583         int num_batch = batch_size.size();
03584         batch_begin.resize(num_batch, 0);
03585         for (int i=1; i<num_batch; i++) batch_begin[i] = batch_size[i-1]+batch_begin[i-1];
03586         assert(batch_begin[num_batch-1]+batch_size[num_batch-1] == NIMA-1);
03587 
03588         for (int i=0; i<NIMA; i++) {
03589                 float ang = ali_params[i*4]/180.0*M_PI;
03590                 float sx = ali_params[i*4+1];
03591                 float sy = ali_params[i*4+2];
03592                 float co = cos(ang);
03593                 float so = sin(ang);
03594                 sx2[i] = -(sx*co-sy*so);
03595                 sy2[i] = -(sx*so+sy*co);
03596         }
03597 
03598         for (int i=0; i<num_batch; i++) {
03599                 if (CTF == 1) {
03600                         for (int p=0; p<NREF; p++)
03601                                 for (int q=0; q<6; q++)
03602                                         ctf_params_ref[p*6+q] = ctf_params[batch_begin[i]*6+q];
03603                         filter_image(ref_image_stack, ref_image_stack_filtered, NREF, NX, NY, ctf_params_ref);
03604                         calculate_multiref_ccf(image_stack+batch_begin[i]*NX*NY, ref_image_stack_filtered, ccf, batch_size[i], NREF, NX, NY, RING_LENGTH, NRING, OU, STEP, KX, KY,
03605                                 sx2+batch_begin[i], sy2+batch_begin[i], silent);
03606                 } else {
03607                         calculate_multiref_ccf(image_stack+batch_begin[i]*NX*NY, ref_image_stack, ccf, batch_size[i], NREF, NX, NY, RING_LENGTH, NRING, OU, STEP, KX, KY,
03608                                 sx2+batch_begin[i], sy2+batch_begin[i], silent);
03609                 }
03610 
03611                 for (int j=0; j<batch_size[i]; j++) {
03612                         for (int im=0; im<NREF; im++) {
03613                                 float max_ccf = -1.0e22;
03614                                 float ang = 0.0, sx = 0.0, sy = 0.0;
03615                                 int mirror = 0;
03616                                 for (int kx=-KX; kx<=KX; kx++) {
03617                                         for (int ky=-KY; ky<=KY; ky++) {
03618                                                 int base_address = (((ky+KY)*(2*KX+1)+(kx+KX))*NREF+im)*(RING_LENGTH+2)+ccf_offset*2*j;                 
03619                                                 for (int l=0; l<RING_LENGTH; l++) {
03620                                                         float ts = ccf[base_address+l];
03621                                                         float tm = ccf[base_address+l+ccf_offset];
03622                                                         if (ts > max_ccf) {
03623                                                                 ang = 360.0-float(l)/RING_LENGTH*360.0;
03624                                                                 sx = -kx*STEP;
03625                                                                 sy = -ky*STEP;
03626                                                                 mirror = 0;
03627                                                                 max_ccf = ts;
03628                                                         }
03629                                                         if (tm > max_ccf) {
03630                                                                 ang = float(l)/RING_LENGTH*360.0; 
03631                                                                 sx = -kx*STEP;
03632                                                                 sy = -ky*STEP;
03633                                                                 mirror = 1;
03634                                                                 max_ccf = tm;
03635                                                         }
03636                                                 }
03637                                         }
03638                                 }
03639                                 float co =  cos(ang*M_PI/180.0);
03640                                 float so = -sin(ang*M_PI/180.0);
03641                 
03642                                 int img_num = batch_begin[i]+j;
03643                                 float sxs = (sx-sx2[img_num])*co-(sy-sy2[img_num])*so;
03644                                 float sys = (sx-sx2[img_num])*so+(sy-sy2[img_num])*co;
03645 
03646                                 align_results.push_back(max_ccf);
03647                                 align_results.push_back(ang);
03648                                 align_results.push_back(sxs);
03649                                 align_results.push_back(sys);
03650                                 align_results.push_back(mirror);
03651                         }
03652                 }
03653         }
03654         
03655         free(ctf_params_ref);
03656         free(sx2);
03657         free(sy2);
03658         
03659         return align_results;
03660 }
03661 
03662 #endif
03663 
03664 
03665 void EMAN::dump_aligners()
03666 {
03667         dump_factory < Aligner > ();
03668 }
03669 
03670 map<string, vector<string> > EMAN::dump_aligners_list()
03671 {
03672         return dump_factory_list < Aligner > ();
03673 }

Generated on Tue Jun 11 12:40:21 2013 for EMAN2 by  doxygen 1.4.7