source: tags/release-1.2.2/src/Cubes/CubicSearch.cc

Last change on this file was 1010, checked in by MatthewWhiting, 12 years ago

Correctly checking to see whether a given spectrum has at least one good channel. This should fix #153

File size: 7.8 KB
Line 
1// -----------------------------------------------------------------------
2// CubicSearch.cc: Searching a 3-dimensional Cube.
3// -----------------------------------------------------------------------
4// Copyright (C) 2006, Matthew Whiting, ATNF
5//
6// This program is free software; you can redistribute it and/or modify it
7// under the terms of the GNU General Public License as published by the
8// Free Software Foundation; either version 2 of the License, or (at your
9// option) any later version.
10//
11// Duchamp is distributed in the hope that it will be useful, but WITHOUT
12// ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
13// FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
14// for more details.
15//
16// You should have received a copy of the GNU General Public License
17// along with Duchamp; if not, write to the Free Software Foundation,
18// Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307, USA
19//
20// Correspondence concerning Duchamp may be directed to:
21//    Internet email: Matthew.Whiting [at] atnf.csiro.au
22//    Postal address: Dr. Matthew Whiting
23//                    Australia Telescope National Facility, CSIRO
24//                    PO Box 76
25//                    Epping NSW 1710
26//                    AUSTRALIA
27// -----------------------------------------------------------------------
28#include <iostream>
29#include <iomanip>
30#include <fstream>
31#include <vector>
32#include <duchamp/param.hh>
33#include <duchamp/PixelMap/Object3D.hh>
34#include <duchamp/Cubes/cubes.hh>
35#include <duchamp/Utils/utils.hh>
36#include <duchamp/Utils/feedback.hh>
37#include <duchamp/Utils/Statistics.hh>
38
39using std::vector;
40using namespace PixelInfo;
41using namespace Statistics;
42
43namespace duchamp
44{
45
46void Cube::CubicSearch()
47{
48  /// @details
49  ///  A front end to the cubic searching routine that does not
50  ///  involve any wavelet reconstruction.
51  ///  The statistics of the cube are calculated first of all.
52  ///  If baseline-removal is required that is done prior to searching.
53  ///  Once searching is complete, the detection map is updated and
54  ///  the intermediate detections are logged in the log file.
55
56  if(this->par.isVerbose()) std::cout << "  ";
57
58  this->setCubeStats();
59   
60  if(this->par.isVerbose()) std::cout << "  Searching... " << std::flush;
61 
62  *this->objectList = search3DArray(this->axisDim,this->array,
63                                    this->par,this->Stats);
64
65  if(this->par.isVerbose()) std::cout << "  Updating detection map... "
66                                      << std::flush;
67  this->updateDetectMap();
68  if(this->par.isVerbose()) std::cout << "Done.\n";
69
70  if(this->par.getFlagLog()){
71    if(this->par.isVerbose())
72      std::cout << "  Logging intermediate detections... " << std::flush;
73    this->logDetectionList();
74    if(this->par.isVerbose()) std::cout << "Done.\n";
75  }
76
77}
78//---------------------------------------------------------------
79
80std::vector <Detection> search3DArray(size_t *dim, float *Array, Param &par,
81                                      StatsContainer<float> &stats)
82{
83
84  if(par.getSearchType()=="spectral")
85    return search3DArraySpectral(dim,Array,par,stats);
86  else if(par.getSearchType()=="spatial")
87    return search3DArraySpatial(dim,Array,par,stats);
88  else{
89    DUCHAMPERROR("search3DArray","Unknown search type : " << par.getSearchType());
90    return std::vector<Detection>(0);
91  }
92}
93//---------------------------------------------------------------
94
95
96std::vector <Detection> search3DArraySpectral(size_t *dim, float *Array, Param &par,
97                                              StatsContainer<float> &stats)
98{
99  /// @details
100  ///  Takes a dimension array and data array as input (and Parameter set)
101  ///  and searches for detections in just the 1D spectra.
102  ///  Returns a vector list of Detections.
103  ///  No reconstruction is assumed to have taken place, so statistics are
104  ///  calculated (using robust methods) from the data array itself.
105  /// \param dim Array of dimension sizes for the data array.
106  /// \param Array Array of data.
107  /// \param par Param set defining how to do detection, and what a
108  /// BLANK pixel is etc.
109  /// \param stats The statistics that define what a detection is.
110  /// \return Vector of detected objects.
111
112  std::vector <Detection> outputList;
113  size_t zdim = dim[2];
114  size_t xySize = dim[0] * dim[1];
115  int num = 0;
116
117  if(zdim>1){
118   
119    ProgressBar bar;
120    if(par.isVerbose()) bar.init(xySize);
121
122    bool *doPixel = new bool[xySize];
123    for(size_t npix=0; npix<xySize; npix++){
124      doPixel[npix] = false;
125      for(size_t z=0;z<zdim;z++){
126        doPixel[npix] = doPixel[npix] ||
127          (!par.isBlank(Array[npix+xySize*z]) && !par.isInMW(z));
128      }
129      // doPixel[i] is false only when there are no good pixels in spectrum
130      //  of pixel #i.
131    }
132
133    size_t *specdim = new size_t[2];
134    specdim[0] = zdim; specdim[1]=1;
135    Image *spectrum = new Image(specdim);
136    delete [] specdim;
137    spectrum->saveParam(par);
138    spectrum->saveStats(stats);
139    //    spectrum->setMinSize(par.getMinChannels());
140    spectrum->setMinSize(1);
141
142    for(size_t y=0; y<dim[1]; y++){
143      for(size_t x=0; x<dim[0]; x++){
144
145        size_t npix = y*dim[0] + x;
146        if( par.isVerbose() ) bar.update(npix+1);
147       
148        if(doPixel[npix]){
149          spectrum->extractSpectrum(Array,dim,npix);
150          spectrum->removeMW(); // only works if flagMW is true
151          std::vector<Scan> objlist = spectrum->findSources1D();
152          std::vector<Scan>::iterator obj;
153          num += objlist.size();
154          for(obj=objlist.begin();obj<objlist.end();obj++){
155            Detection newObject;
156            // Fix up coordinates of each pixel to match original array
157            for(int z=obj->getX();z<=obj->getXmax();z++) {
158              newObject.addPixel(x,y,z);
159            }
160            newObject.setOffsets(par);
161            if(par.getFlagTwoStageMerging()) mergeIntoList(newObject,outputList,par);
162            else outputList.push_back(newObject);
163          }
164        }
165      }
166    }
167
168    delete spectrum;
169    delete [] doPixel;
170 
171
172    if(par.isVerbose()){
173      bar.remove();
174      std::cout << "Found " << num << ".\n";
175    }
176
177  }
178
179  return outputList;
180}
181//---------------------------------------------------------------
182
183std::vector <Detection> search3DArraySpatial(size_t *dim, float *Array,
184                                             Param &par,
185                                             StatsContainer<float> &stats)
186{
187  /// @details
188  ///  Takes a dimension array and data array as input (and Parameter
189  ///  set) and searches for detections just in the channel maps -- no
190  ///  1D searches are done. 
191  ///  Returns a vector list of Detections.
192  ///  No reconstruction is assumed to have taken place, so only the base
193  ///  data array is searched.
194  /// \param dim Array of dimension sizes for the data array.
195  /// \param Array Array of data.
196  /// \param par Param set defining how to do detection, and what a
197  ///              BLANK pixel is etc.
198  /// \param stats The statistics that define what a detection is.
199  /// \return A std::vector of detected objects.
200
201  std::vector <Detection> outputList;
202  size_t zdim = dim[2];
203  int num = 0;
204
205  ProgressBar bar;
206  bool useBar = (zdim>1);
207  if(useBar && par.isVerbose()) bar.init(zdim);
208 
209  size_t *imdim = new size_t[2];
210  imdim[0] = dim[0]; imdim[1] = dim[1];
211  Image *channelImage = new Image(imdim);
212  delete [] imdim;
213  channelImage->saveParam(par);
214  channelImage->saveStats(stats);
215  channelImage->setMinSize(1);
216
217  for(size_t z=0; z<zdim; z++){
218
219    if( par.isVerbose() && useBar ) bar.update(z+1);
220
221    if(!par.isInMW(z)){
222
223      channelImage->extractImage(Array,dim,z);
224      std::vector<Object2D> objlist = channelImage->findSources2D();
225      std::vector<Object2D>::iterator obj;
226      num += objlist.size();
227      for(obj=objlist.begin();obj!=objlist.end();obj++){
228        Detection newObject;
229        newObject.addChannel(z,*obj);
230        newObject.setOffsets(par);
231        if(par.getFlagTwoStageMerging()) mergeIntoList(newObject,outputList,par);
232        else outputList.push_back(newObject);
233      }
234    }
235
236  }
237
238  delete channelImage;
239
240  if(par.isVerbose()){
241    if(useBar) bar.remove();
242    std::cout << "Found " << num << ".\n";
243  }
244
245  return outputList;
246}
247
248
249}
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