[299] | 1 | // ----------------------------------------------------------------------- |
---|
| 2 | // cubes.cc: Member functions for the DataArray, Cube and Image classes. |
---|
| 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 | // ----------------------------------------------------------------------- |
---|
[136] | 28 | #include <unistd.h> |
---|
[3] | 29 | #include <iostream> |
---|
| 30 | #include <iomanip> |
---|
| 31 | #include <vector> |
---|
[212] | 32 | #include <algorithm> |
---|
[3] | 33 | #include <string> |
---|
[211] | 34 | #include <math.h> |
---|
[136] | 35 | |
---|
[394] | 36 | #include <wcslib/wcs.h> |
---|
[136] | 37 | |
---|
[393] | 38 | #include <duchamp/pgheader.hh> |
---|
[263] | 39 | |
---|
[393] | 40 | #include <duchamp/duchamp.hh> |
---|
| 41 | #include <duchamp/param.hh> |
---|
| 42 | #include <duchamp/fitsHeader.hh> |
---|
| 43 | #include <duchamp/Cubes/cubes.hh> |
---|
| 44 | #include <duchamp/PixelMap/Voxel.hh> |
---|
| 45 | #include <duchamp/PixelMap/Object3D.hh> |
---|
| 46 | #include <duchamp/Detection/detection.hh> |
---|
| 47 | #include <duchamp/Detection/columns.hh> |
---|
| 48 | #include <duchamp/Utils/utils.hh> |
---|
| 49 | #include <duchamp/Utils/mycpgplot.hh> |
---|
| 50 | #include <duchamp/Utils/Statistics.hh> |
---|
[378] | 51 | |
---|
[146] | 52 | using namespace mycpgplot; |
---|
[190] | 53 | using namespace Statistics; |
---|
[258] | 54 | using namespace PixelInfo; |
---|
[3] | 55 | |
---|
[263] | 56 | #ifdef TEST_DEBUG |
---|
| 57 | const bool TESTING=true; |
---|
| 58 | #else |
---|
| 59 | const bool TESTING=false; |
---|
| 60 | #endif |
---|
| 61 | |
---|
[378] | 62 | namespace duchamp |
---|
| 63 | { |
---|
[3] | 64 | |
---|
[378] | 65 | using namespace Column; |
---|
[220] | 66 | |
---|
[378] | 67 | /****************************************************************/ |
---|
| 68 | /////////////////////////////////////////////////// |
---|
| 69 | //// Functions for DataArray class: |
---|
| 70 | /////////////////////////////////////////////////// |
---|
[220] | 71 | |
---|
[378] | 72 | DataArray::DataArray(){ |
---|
| 73 | /** |
---|
| 74 | * Fundamental constructor for DataArray. |
---|
| 75 | * Number of dimensions and pixels are set to 0. Nothing else allocated. |
---|
| 76 | */ |
---|
| 77 | this->numDim=0; |
---|
| 78 | this->numPixels=0; |
---|
| 79 | this->objectList = new std::vector<Detection>; |
---|
| 80 | }; |
---|
| 81 | //-------------------------------------------------------------------- |
---|
[139] | 82 | |
---|
[378] | 83 | DataArray::DataArray(short int nDim){ |
---|
| 84 | /** |
---|
| 85 | * N-dimensional constructor for DataArray. |
---|
| 86 | * Number of dimensions defined, and dimension array allocated. |
---|
| 87 | * Number of pixels are set to 0. |
---|
| 88 | * \param nDim Number of dimensions. |
---|
| 89 | */ |
---|
[139] | 90 | if(nDim>0) this->axisDim = new long[nDim]; |
---|
[378] | 91 | this->numDim=nDim; |
---|
| 92 | this->numPixels=0; |
---|
| 93 | this->objectList = new std::vector<Detection>; |
---|
| 94 | }; |
---|
| 95 | //-------------------------------------------------------------------- |
---|
[3] | 96 | |
---|
[378] | 97 | DataArray::DataArray(short int nDim, long size){ |
---|
| 98 | /** |
---|
| 99 | * N-dimensional constructor for DataArray. |
---|
| 100 | * Number of dimensions and number of pixels defined. |
---|
| 101 | * Arrays allocated based on these values. |
---|
| 102 | * \param nDim Number of dimensions. |
---|
| 103 | * \param size Number of pixels. |
---|
| 104 | * |
---|
| 105 | * Note that we can assign values to the dimension array. |
---|
| 106 | */ |
---|
| 107 | |
---|
[139] | 108 | if(size<0) |
---|
[378] | 109 | duchampError("DataArray(nDim,size)", |
---|
| 110 | "Negative size -- could not define DataArray"); |
---|
| 111 | else if(nDim<0) |
---|
| 112 | duchampError("DataArray(nDim,size)", |
---|
| 113 | "Negative number of dimensions: could not define DataArray"); |
---|
| 114 | else { |
---|
| 115 | if(size>0) this->array = new float[size]; |
---|
[139] | 116 | this->numPixels = size; |
---|
| 117 | if(nDim>0) this->axisDim = new long[nDim]; |
---|
[378] | 118 | this->numDim = nDim; |
---|
[139] | 119 | } |
---|
[378] | 120 | this->objectList = new std::vector<Detection>; |
---|
[3] | 121 | } |
---|
[378] | 122 | //-------------------------------------------------------------------- |
---|
[3] | 123 | |
---|
[378] | 124 | DataArray::DataArray(short int nDim, long *dimensions) |
---|
| 125 | { |
---|
| 126 | /** |
---|
| 127 | * Most robust constructor for DataArray. |
---|
| 128 | * Number and sizes of dimensions are defined, and hence the number of |
---|
| 129 | * pixels. Arrays allocated based on these values. |
---|
| 130 | * \param nDim Number of dimensions. |
---|
| 131 | * \param dimensions Array giving sizes of dimensions. |
---|
| 132 | */ |
---|
| 133 | if(nDim<0) |
---|
| 134 | duchampError("DataArray(nDim,dimArray)", |
---|
| 135 | "Negative number of dimensions: could not define DataArray"); |
---|
| 136 | else { |
---|
| 137 | int size = dimensions[0]; |
---|
| 138 | for(int i=1;i<nDim;i++) size *= dimensions[i]; |
---|
| 139 | if(size<0) |
---|
| 140 | duchampError("DataArray(nDim,dimArray)", |
---|
| 141 | "Negative size: could not define DataArray"); |
---|
| 142 | else{ |
---|
| 143 | this->numPixels = size; |
---|
| 144 | if(size>0) this->array = new float[size]; |
---|
| 145 | this->numDim=nDim; |
---|
| 146 | if(nDim>0) this->axisDim = new long[nDim]; |
---|
| 147 | for(int i=0;i<nDim;i++) this->axisDim[i] = dimensions[i]; |
---|
| 148 | } |
---|
| 149 | } |
---|
| 150 | } |
---|
| 151 | //-------------------------------------------------------------------- |
---|
[137] | 152 | |
---|
[378] | 153 | DataArray::~DataArray() |
---|
| 154 | { |
---|
| 155 | /** |
---|
| 156 | * Destructor -- arrays deleted if they have been allocated, and the |
---|
| 157 | * object list is deleted. |
---|
| 158 | */ |
---|
| 159 | if(this->numPixels>0) delete [] this->array; |
---|
| 160 | if(this->numDim>0) delete [] this->axisDim; |
---|
| 161 | delete this->objectList; |
---|
| 162 | } |
---|
| 163 | //-------------------------------------------------------------------- |
---|
| 164 | //-------------------------------------------------------------------- |
---|
[220] | 165 | |
---|
[378] | 166 | void DataArray::getDim(long &x, long &y, long &z){ |
---|
| 167 | /** |
---|
| 168 | * The sizes of the first three dimensions (if they exist) are returned. |
---|
| 169 | * \param x The first dimension. Defaults to 0 if numDim \f$\le\f$ 0. |
---|
| 170 | * \param y The second dimension. Defaults to 1 if numDim \f$\le\f$ 1. |
---|
| 171 | * \param z The third dimension. Defaults to 1 if numDim \f$\le\f$ 2. |
---|
| 172 | */ |
---|
| 173 | if(this->numDim>0) x=this->axisDim[0]; |
---|
| 174 | else x=0; |
---|
| 175 | if(this->numDim>1) y=this->axisDim[1]; |
---|
| 176 | else y=1; |
---|
| 177 | if(this->numDim>2) z=this->axisDim[2]; |
---|
| 178 | else z=1; |
---|
| 179 | } |
---|
| 180 | //-------------------------------------------------------------------- |
---|
[3] | 181 | |
---|
[378] | 182 | void DataArray::getDimArray(long *output){ |
---|
| 183 | /** |
---|
| 184 | * The axisDim array is written to output. This needs to be defined |
---|
| 185 | * beforehand: no checking is done on the memory. |
---|
| 186 | * \param output The array that is written to. |
---|
| 187 | */ |
---|
| 188 | for(int i=0;i<this->numDim;i++) output[i] = this->axisDim[i]; |
---|
| 189 | } |
---|
| 190 | //-------------------------------------------------------------------- |
---|
[3] | 191 | |
---|
[378] | 192 | void DataArray::getArray(float *output){ |
---|
| 193 | /** |
---|
| 194 | * The pixel value array is written to output. This needs to be defined |
---|
| 195 | * beforehand: no checking is done on the memory. |
---|
| 196 | * \param output The array that is written to. |
---|
| 197 | */ |
---|
| 198 | for(int i=0;i<this->numPixels;i++) output[i] = this->array[i]; |
---|
[139] | 199 | } |
---|
[378] | 200 | //-------------------------------------------------------------------- |
---|
[3] | 201 | |
---|
[378] | 202 | void DataArray::saveArray(float *input, long size){ |
---|
| 203 | /** |
---|
| 204 | * Saves the array in input to the pixel array DataArray::array. |
---|
| 205 | * The size of the array given must be the same as the current number of |
---|
| 206 | * pixels, else an error message is returned and nothing is done. |
---|
| 207 | * \param input The array of values to be saved. |
---|
| 208 | * \param size The size of input. |
---|
| 209 | */ |
---|
| 210 | if(size != this->numPixels) |
---|
| 211 | duchampError("DataArray::saveArray", |
---|
| 212 | "Input array different size to existing array. Cannot save."); |
---|
| 213 | else { |
---|
| 214 | if(this->numPixels>0) delete [] this->array; |
---|
| 215 | this->numPixels = size; |
---|
| 216 | this->array = new float[size]; |
---|
| 217 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
---|
| 218 | } |
---|
| 219 | } |
---|
| 220 | //-------------------------------------------------------------------- |
---|
[3] | 221 | |
---|
[378] | 222 | void DataArray::addObject(Detection object){ |
---|
| 223 | /** |
---|
| 224 | * \param object The object to be added to the object list. |
---|
| 225 | */ |
---|
| 226 | // objectList is a vector, so just use push_back() |
---|
| 227 | this->objectList->push_back(object); |
---|
| 228 | } |
---|
| 229 | //-------------------------------------------------------------------- |
---|
[3] | 230 | |
---|
[378] | 231 | void DataArray::addObjectList(std::vector <Detection> newlist) { |
---|
| 232 | /** |
---|
| 233 | * \param newlist The list of objects to be added to the object list. |
---|
| 234 | */ |
---|
| 235 | for(int i=0;i<newlist.size();i++) this->objectList->push_back(newlist[i]); |
---|
| 236 | } |
---|
| 237 | //-------------------------------------------------------------------- |
---|
[3] | 238 | |
---|
[378] | 239 | // void DataArray::addObjectOffsets(){ |
---|
| 240 | // /** |
---|
| 241 | // * Add the pixel offsets (that is, offsets from the corner of the cube to the |
---|
| 242 | // * corner of the utilised part) that are stored in the Param set to the |
---|
| 243 | // * coordinate values of each object in the object list. |
---|
| 244 | // */ |
---|
| 245 | // for(int i=0;i<this->objectList->size();i++){ |
---|
| 246 | // for(int p=0;p<this->objectList->at(i).getSize();p++){ |
---|
| 247 | // this->objectList->at(i).setX(p,this->objectList->at(i).getX(p)+ |
---|
| 248 | // this->par.getXOffset()); |
---|
| 249 | // this->objectList->at(i).setY(p,this->objectList->at(i).getY(p)+ |
---|
| 250 | // this->par.getYOffset()); |
---|
| 251 | // this->objectList->at(i).setZ(p,this->objectList->at(i).getZ(p)+ |
---|
| 252 | // this->par.getZOffset()); |
---|
| 253 | // } |
---|
| 254 | // } |
---|
| 255 | // } |
---|
| 256 | // //-------------------------------------------------------------------- |
---|
[220] | 257 | |
---|
[378] | 258 | bool DataArray::isDetection(float value){ |
---|
| 259 | /** |
---|
| 260 | * Is a given value a detection, based on the statistics in the |
---|
| 261 | * DataArray's StatsContainer? |
---|
| 262 | * \param value The pixel value to test. |
---|
| 263 | */ |
---|
| 264 | if(par.isBlank(value)) return false; |
---|
| 265 | else return Stats.isDetection(value); |
---|
| 266 | }; |
---|
| 267 | //-------------------------------------------------------------------- |
---|
[220] | 268 | |
---|
[378] | 269 | bool DataArray::isDetection(long voxel){ |
---|
| 270 | /** |
---|
| 271 | * Is a given pixel a detection, based on the statistics in the |
---|
| 272 | * DataArray's StatsContainer? |
---|
| 273 | * If the pixel lies outside the valid range for the data array, return false. |
---|
| 274 | * \param voxel Location of the DataArray's pixel to be tested. |
---|
| 275 | */ |
---|
| 276 | if((voxel<0)||(voxel>this->numPixels)) return false; |
---|
| 277 | else if(par.isBlank(this->array[voxel])) return false; |
---|
| 278 | else return Stats.isDetection(this->array[voxel]); |
---|
| 279 | }; |
---|
| 280 | //-------------------------------------------------------------------- |
---|
| 281 | |
---|
| 282 | std::ostream& operator<< ( std::ostream& theStream, DataArray &array) |
---|
| 283 | { |
---|
| 284 | /** |
---|
| 285 | * A way to print out the pixel coordinates & flux values of the |
---|
| 286 | * list of detected objects belonging to the DataArray. |
---|
| 287 | * These are formatted nicely according to the << operator for Detection, |
---|
| 288 | * with a line indicating the number of detections at the start. |
---|
| 289 | * \param theStream The ostream object to which the output should be sent. |
---|
| 290 | * \param array The DataArray containing the list of objects. |
---|
| 291 | */ |
---|
| 292 | for(int i=0;i<array.numDim;i++){ |
---|
| 293 | if(i>0) theStream<<"x"; |
---|
| 294 | theStream<<array.axisDim[i]; |
---|
| 295 | } |
---|
| 296 | theStream<<std::endl; |
---|
| 297 | theStream<<array.objectList->size()<<" detections:\n--------------\n"; |
---|
| 298 | for(int i=0;i<array.objectList->size();i++){ |
---|
| 299 | theStream << "Detection #" << array.objectList->at(i).getID()<<std::endl; |
---|
| 300 | Detection *obj = new Detection; |
---|
| 301 | *obj = array.objectList->at(i); |
---|
| 302 | obj->addOffsets(); |
---|
| 303 | theStream<<*obj; |
---|
| 304 | delete obj; |
---|
| 305 | } |
---|
| 306 | theStream<<"--------------\n"; |
---|
| 307 | return theStream; |
---|
[3] | 308 | } |
---|
| 309 | |
---|
[378] | 310 | /****************************************************************/ |
---|
| 311 | ///////////////////////////////////////////////////////////// |
---|
| 312 | //// Functions for Cube class |
---|
| 313 | ///////////////////////////////////////////////////////////// |
---|
[3] | 314 | |
---|
[378] | 315 | Cube::Cube(){ |
---|
| 316 | /** |
---|
| 317 | * Basic Constructor for Cube class. |
---|
| 318 | * numDim set to 3, but numPixels to 0 and all bool flags to false. |
---|
| 319 | * No allocation done. |
---|
| 320 | */ |
---|
[220] | 321 | numPixels=0; numDim=3; |
---|
| 322 | reconExists = false; reconAllocated = false; baselineAllocated = false; |
---|
| 323 | }; |
---|
[378] | 324 | //-------------------------------------------------------------------- |
---|
[3] | 325 | |
---|
[378] | 326 | Cube::Cube(long size){ |
---|
| 327 | /** |
---|
| 328 | * Alternative Cube constructor, where size is given but not individual |
---|
| 329 | * dimensions. Arrays are allocated as appropriate (according to the |
---|
| 330 | * relevant flags in Param set), but the Cube::axisDim array is not. |
---|
| 331 | */ |
---|
| 332 | this->reconAllocated = false; |
---|
| 333 | this->baselineAllocated = false; |
---|
| 334 | this->numPixels = this->numDim = 0; |
---|
| 335 | if(size<0) |
---|
| 336 | duchampError("Cube(size)","Negative size -- could not define Cube"); |
---|
| 337 | else{ |
---|
| 338 | if(size>0){ |
---|
| 339 | this->array = new float[size]; |
---|
| 340 | if(this->par.getFlagATrous()||this->par.getFlagSmooth()){ |
---|
| 341 | this->recon = new float[size]; |
---|
| 342 | this->reconAllocated = true; |
---|
| 343 | } |
---|
| 344 | if(this->par.getFlagBaseline()){ |
---|
| 345 | this->baseline = new float[size]; |
---|
| 346 | this->baselineAllocated = true; |
---|
| 347 | } |
---|
[219] | 348 | } |
---|
[378] | 349 | this->numPixels = size; |
---|
| 350 | this->axisDim = new long[2]; |
---|
| 351 | this->numDim = 3; |
---|
| 352 | this->reconExists = false; |
---|
[139] | 353 | } |
---|
[3] | 354 | } |
---|
[378] | 355 | //-------------------------------------------------------------------- |
---|
[3] | 356 | |
---|
[378] | 357 | Cube::Cube(long *dimensions){ |
---|
| 358 | /** |
---|
| 359 | * Alternative Cube constructor, where sizes of dimensions are given. |
---|
| 360 | * Arrays are allocated as appropriate (according to the |
---|
| 361 | * relevant flags in Param set), as is the Cube::axisDim array. |
---|
| 362 | */ |
---|
| 363 | int size = dimensions[0] * dimensions[1] * dimensions[2]; |
---|
| 364 | int imsize = dimensions[0] * dimensions[1]; |
---|
| 365 | this->reconAllocated = false; |
---|
| 366 | this->baselineAllocated = false; |
---|
| 367 | this->numPixels = this->numDim = 0; |
---|
| 368 | if((size<0) || (imsize<0) ) |
---|
| 369 | duchampError("Cube(dimArray)","Negative size -- could not define Cube"); |
---|
| 370 | else{ |
---|
| 371 | this->numPixels = size; |
---|
| 372 | if(size>0){ |
---|
| 373 | this->array = new float[size]; |
---|
| 374 | this->detectMap = new short[imsize]; |
---|
| 375 | if(this->par.getFlagATrous()||this->par.getFlagSmooth()){ |
---|
| 376 | this->recon = new float[size]; |
---|
| 377 | this->reconAllocated = true; |
---|
| 378 | } |
---|
| 379 | if(this->par.getFlagBaseline()){ |
---|
| 380 | this->baseline = new float[size]; |
---|
| 381 | this->baselineAllocated = true; |
---|
| 382 | } |
---|
[205] | 383 | } |
---|
[378] | 384 | this->numDim = 3; |
---|
| 385 | this->axisDim = new long[3]; |
---|
| 386 | for(int i=0;i<3 ;i++) this->axisDim[i] = dimensions[i]; |
---|
| 387 | for(int i=0;i<imsize;i++) this->detectMap[i] = 0; |
---|
| 388 | this->reconExists = false; |
---|
[139] | 389 | } |
---|
[3] | 390 | } |
---|
[378] | 391 | //-------------------------------------------------------------------- |
---|
[3] | 392 | |
---|
[378] | 393 | Cube::~Cube() |
---|
| 394 | { |
---|
| 395 | /** |
---|
| 396 | * The destructor deletes the memory allocated for Cube::detectMap, and, |
---|
| 397 | * if these have been allocated, Cube::recon and Cube::baseline. |
---|
| 398 | */ |
---|
| 399 | delete [] this->detectMap; |
---|
| 400 | if(this->reconAllocated) delete [] this->recon; |
---|
| 401 | if(this->baselineAllocated) delete [] this->baseline; |
---|
| 402 | } |
---|
| 403 | //-------------------------------------------------------------------- |
---|
[137] | 404 | |
---|
[378] | 405 | void Cube::initialiseCube(long *dimensions) |
---|
| 406 | { |
---|
| 407 | /** |
---|
| 408 | * This function will set the sizes of all arrays that will be used by Cube. |
---|
| 409 | * It will also define the values of the axis dimensions: this will be done |
---|
| 410 | * using the WCS in the FitsHeader class, so the WCS needs to be good and |
---|
| 411 | * have three axes. If this is not the case, the axes are assumed to be |
---|
| 412 | * ordered in the sense of lng,lat,spc. |
---|
| 413 | * |
---|
| 414 | * \param dimensions An array of values giving the dimensions (sizes) for |
---|
| 415 | * all axes. |
---|
| 416 | */ |
---|
[186] | 417 | |
---|
[378] | 418 | int lng,lat,spc,size,imsize; |
---|
[365] | 419 | |
---|
[378] | 420 | if(this->head.isWCS() && (this->head.getNumAxes()>=3)){ |
---|
| 421 | // if there is a WCS and there is at least 3 axes |
---|
| 422 | lng = this->head.WCS().lng; |
---|
| 423 | lat = this->head.WCS().lat; |
---|
| 424 | spc = this->head.WCS().spec; |
---|
| 425 | } |
---|
| 426 | else{ |
---|
| 427 | // just take dimensions[] at face value |
---|
| 428 | lng = 0; |
---|
| 429 | lat = 1; |
---|
| 430 | spc = 2; |
---|
| 431 | } |
---|
[186] | 432 | |
---|
[378] | 433 | size = dimensions[lng]; |
---|
| 434 | if(this->head.getNumAxes()>1) size *= dimensions[lat]; |
---|
| 435 | // if(this->head.isSpecOK()) size *= dimensions[spc]; |
---|
| 436 | if(this->head.canUseThirdAxis()) size *= dimensions[spc]; |
---|
| 437 | imsize = dimensions[lng]; |
---|
| 438 | if(this->head.getNumAxes()>1) imsize *= dimensions[lat]; |
---|
[271] | 439 | |
---|
[378] | 440 | this->reconAllocated = false; |
---|
| 441 | this->baselineAllocated = false; |
---|
[186] | 442 | |
---|
[378] | 443 | if((size<0) || (imsize<0) ) |
---|
| 444 | duchampError("Cube::initialiseCube(dimArray)", |
---|
| 445 | "Negative size -- could not define Cube.\n"); |
---|
| 446 | else{ |
---|
| 447 | this->numPixels = size; |
---|
| 448 | if(size>0){ |
---|
| 449 | this->array = new float[size]; |
---|
| 450 | this->detectMap = new short[imsize]; |
---|
| 451 | if(this->par.getFlagATrous() || this->par.getFlagSmooth()){ |
---|
| 452 | this->recon = new float[size]; |
---|
| 453 | this->reconAllocated = true; |
---|
| 454 | } |
---|
| 455 | if(this->par.getFlagBaseline()){ |
---|
| 456 | this->baseline = new float[size]; |
---|
| 457 | this->baselineAllocated = true; |
---|
| 458 | } |
---|
[205] | 459 | } |
---|
[378] | 460 | this->numDim = 3; |
---|
| 461 | this->axisDim = new long[this->numDim]; |
---|
| 462 | this->axisDim[0] = dimensions[lng]; |
---|
| 463 | if(this->head.getNumAxes()>1) this->axisDim[1] = dimensions[lat]; |
---|
| 464 | else this->axisDim[1] = 1; |
---|
| 465 | // if(this->head.isSpecOK()) this->axisDim[2] = dimensions[spc]; |
---|
| 466 | if(this->head.canUseThirdAxis()) this->axisDim[2] = dimensions[spc]; |
---|
| 467 | else this->axisDim[2] = 1; |
---|
| 468 | for(int i=0;i<imsize;i++) this->detectMap[i] = 0; |
---|
| 469 | this->reconExists = false; |
---|
[139] | 470 | } |
---|
[3] | 471 | } |
---|
[378] | 472 | //-------------------------------------------------------------------- |
---|
[3] | 473 | |
---|
[378] | 474 | int Cube::getCube(){ |
---|
[220] | 475 | /** |
---|
| 476 | * A front-end to the Cube::getCube() function, that does |
---|
| 477 | * subsection checks. |
---|
| 478 | * Assumes the Param is set up properly. |
---|
| 479 | */ |
---|
[232] | 480 | std::string fname = par.getImageFile(); |
---|
[220] | 481 | if(par.getFlagSubsection()) fname+=par.getSubsection(); |
---|
| 482 | return getCube(fname); |
---|
| 483 | }; |
---|
[378] | 484 | //-------------------------------------------------------------------- |
---|
[220] | 485 | |
---|
[378] | 486 | void Cube::saveArray(float *input, long size){ |
---|
| 487 | if(size != this->numPixels){ |
---|
| 488 | std::stringstream errmsg; |
---|
| 489 | errmsg << "Input array different size to existing array (" |
---|
| 490 | << size << " cf. " << this->numPixels << "). Cannot save.\n"; |
---|
| 491 | duchampError("Cube::saveArray",errmsg.str()); |
---|
| 492 | } |
---|
| 493 | else { |
---|
| 494 | if(this->numPixels>0) delete [] array; |
---|
| 495 | this->numPixels = size; |
---|
| 496 | this->array = new float[size]; |
---|
| 497 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
---|
| 498 | } |
---|
[160] | 499 | } |
---|
[378] | 500 | //-------------------------------------------------------------------- |
---|
[3] | 501 | |
---|
[378] | 502 | void Cube::saveRecon(float *input, long size){ |
---|
| 503 | /** |
---|
| 504 | * Saves the array in input to the reconstructed array Cube::recon |
---|
| 505 | * The size of the array given must be the same as the current number of |
---|
| 506 | * pixels, else an error message is returned and nothing is done. |
---|
| 507 | * If the recon array has already been allocated, it is deleted first, and |
---|
| 508 | * then the space is allocated. |
---|
| 509 | * Afterwards, the appropriate flags are set. |
---|
| 510 | * \param input The array of values to be saved. |
---|
| 511 | * \param size The size of input. |
---|
| 512 | */ |
---|
| 513 | if(size != this->numPixels){ |
---|
| 514 | std::stringstream errmsg; |
---|
| 515 | errmsg << "Input array different size to existing array (" |
---|
| 516 | << size << " cf. " << this->numPixels << "). Cannot save.\n"; |
---|
| 517 | duchampError("Cube::saveRecon",errmsg.str()); |
---|
[205] | 518 | } |
---|
[378] | 519 | else { |
---|
| 520 | if(this->numPixels>0){ |
---|
| 521 | if(this->reconAllocated) delete [] this->recon; |
---|
| 522 | this->numPixels = size; |
---|
| 523 | this->recon = new float[size]; |
---|
| 524 | this->reconAllocated = true; |
---|
| 525 | for(int i=0;i<size;i++) this->recon[i] = input[i]; |
---|
| 526 | this->reconExists = true; |
---|
| 527 | } |
---|
| 528 | } |
---|
[139] | 529 | } |
---|
[378] | 530 | //-------------------------------------------------------------------- |
---|
[3] | 531 | |
---|
[378] | 532 | void Cube::getRecon(float *output){ |
---|
| 533 | /** |
---|
| 534 | * The reconstructed array is written to output. The output array needs to |
---|
| 535 | * be defined beforehand: no checking is done on the memory. |
---|
| 536 | * \param output The array that is written to. |
---|
| 537 | */ |
---|
| 538 | // Need check for change in number of pixels! |
---|
| 539 | for(int i=0;i<this->numPixels;i++){ |
---|
| 540 | if(this->reconExists) output[i] = this->recon[i]; |
---|
| 541 | else output[i] = 0.; |
---|
| 542 | } |
---|
[3] | 543 | } |
---|
[378] | 544 | //-------------------------------------------------------------------- |
---|
[3] | 545 | |
---|
[378] | 546 | void Cube::removeMW() |
---|
| 547 | { |
---|
| 548 | /** |
---|
| 549 | * The channels corresponding to the Milky Way range (as given by the Param |
---|
| 550 | * set) are all set to 0 in the pixel array. |
---|
| 551 | * Only done if the appropriate flag is set, and the pixels are not BLANK. |
---|
| 552 | * \deprecated |
---|
| 553 | */ |
---|
| 554 | if(this->par.getFlagMW()){ |
---|
| 555 | for(int pix=0;pix<this->axisDim[0]*this->axisDim[1];pix++){ |
---|
| 556 | for(int z=0;z<this->axisDim[2];z++){ |
---|
| 557 | int pos = z*this->axisDim[0]*this->axisDim[1] + pix; |
---|
| 558 | if(!this->isBlank(pos) && this->par.isInMW(z)) this->array[pos]=0.; |
---|
| 559 | } |
---|
[103] | 560 | } |
---|
[86] | 561 | } |
---|
| 562 | } |
---|
[378] | 563 | //-------------------------------------------------------------------- |
---|
[86] | 564 | |
---|
[378] | 565 | void Cube::setCubeStatsOld() |
---|
| 566 | { |
---|
| 567 | /** |
---|
| 568 | * \deprecated |
---|
| 569 | * |
---|
| 570 | * Calculates the full statistics for the cube: mean, rms, median, madfm. |
---|
| 571 | * Only do this if the threshold has not been defined (ie. is still 0., |
---|
| 572 | * its default). |
---|
| 573 | * Also work out the threshold and store it in the Param set. |
---|
| 574 | * |
---|
| 575 | * For the stats calculations, we ignore BLANKs and MW channels. |
---|
| 576 | */ |
---|
[189] | 577 | |
---|
[378] | 578 | if(!this->par.getFlagFDR() && this->par.getFlagUserThreshold() ){ |
---|
| 579 | // if the user has defined a threshold, set this in the StatsContainer |
---|
| 580 | this->Stats.setThreshold( this->par.getThreshold() ); |
---|
| 581 | } |
---|
| 582 | else{ |
---|
| 583 | // only work out the mean etc if we need to. |
---|
| 584 | // the only reason we don't is if the user has specified a threshold. |
---|
[204] | 585 | |
---|
[378] | 586 | std::cout << "Calculating the cube statistics... " << std::flush; |
---|
[204] | 587 | |
---|
[378] | 588 | // get number of good pixels; |
---|
| 589 | int goodSize = 0; |
---|
| 590 | for(int p=0;p<this->axisDim[0]*this->axisDim[1];p++){ |
---|
| 591 | for(int z=0;z<this->axisDim[2];z++){ |
---|
| 592 | int vox = z * this->axisDim[0] * this->axisDim[1] + p; |
---|
| 593 | if(!this->isBlank(vox) && !this->par.isInMW(z)) goodSize++; |
---|
| 594 | } |
---|
[204] | 595 | } |
---|
[189] | 596 | |
---|
[378] | 597 | float *tempArray = new float[goodSize]; |
---|
[204] | 598 | |
---|
| 599 | goodSize=0; |
---|
| 600 | for(int p=0;p<this->axisDim[0]*this->axisDim[1];p++){ |
---|
| 601 | for(int z=0;z<this->axisDim[2];z++){ |
---|
| 602 | int vox = z * this->axisDim[0] * this->axisDim[1] + p; |
---|
| 603 | if(!this->isBlank(vox) && !this->par.isInMW(z)) |
---|
[378] | 604 | tempArray[goodSize++] = this->array[vox]; |
---|
[204] | 605 | } |
---|
| 606 | } |
---|
[378] | 607 | if(!this->reconExists){ |
---|
| 608 | // if there's no recon array, calculate everything from orig array |
---|
| 609 | this->Stats.calculate(tempArray,goodSize); |
---|
| 610 | } |
---|
| 611 | else{ |
---|
| 612 | // just get mean & median from orig array, and rms & madfm from recon |
---|
| 613 | StatsContainer<float> origStats,reconStats; |
---|
| 614 | origStats.calculate(tempArray,goodSize); |
---|
| 615 | goodSize=0; |
---|
| 616 | for(int p=0;p<this->axisDim[0]*this->axisDim[1];p++){ |
---|
| 617 | for(int z=0;z<this->axisDim[2];z++){ |
---|
| 618 | int vox = z * this->axisDim[0] * this->axisDim[1] + p; |
---|
| 619 | if(!this->isBlank(vox) && !this->par.isInMW(z)) |
---|
| 620 | tempArray[goodSize++] = this->array[vox] - this->recon[vox]; |
---|
| 621 | } |
---|
| 622 | } |
---|
| 623 | reconStats.calculate(tempArray,goodSize); |
---|
[190] | 624 | |
---|
[378] | 625 | // Get the "middle" estimators from the original array. |
---|
| 626 | this->Stats.setMean(origStats.getMean()); |
---|
| 627 | this->Stats.setMedian(origStats.getMedian()); |
---|
| 628 | // Get the "spread" estimators from the residual (orig-recon) array |
---|
| 629 | this->Stats.setStddev(reconStats.getStddev()); |
---|
| 630 | this->Stats.setMadfm(reconStats.getMadfm()); |
---|
| 631 | } |
---|
[190] | 632 | |
---|
[378] | 633 | delete [] tempArray; |
---|
[204] | 634 | |
---|
[378] | 635 | this->Stats.setUseFDR( this->par.getFlagFDR() ); |
---|
| 636 | // If the FDR method has been requested |
---|
| 637 | if(this->par.getFlagFDR()) this->setupFDR(); |
---|
| 638 | else{ |
---|
| 639 | // otherwise, calculate one based on the requested SNR cut level, and |
---|
| 640 | // then set the threshold parameter in the Par set. |
---|
| 641 | this->Stats.setThresholdSNR( this->par.getCut() ); |
---|
| 642 | this->par.setThreshold( this->Stats.getThreshold() ); |
---|
| 643 | } |
---|
[204] | 644 | |
---|
| 645 | |
---|
[378] | 646 | } |
---|
| 647 | std::cout << "Using "; |
---|
| 648 | if(this->par.getFlagFDR()) std::cout << "effective "; |
---|
| 649 | std::cout << "flux threshold of: "; |
---|
| 650 | float thresh = this->Stats.getThreshold(); |
---|
| 651 | if(this->par.getFlagNegative()) thresh *= -1.; |
---|
| 652 | std::cout << thresh << std::endl; |
---|
| 653 | |
---|
[190] | 654 | } |
---|
[378] | 655 | //-------------------------------------------------------------------- |
---|
[189] | 656 | |
---|
[378] | 657 | void Cube::setCubeStats() |
---|
| 658 | { |
---|
| 659 | /** |
---|
| 660 | * Calculates the full statistics for the cube: |
---|
| 661 | * mean, rms, median, madfm |
---|
| 662 | * Only do this if the threshold has not been defined (ie. is still 0., |
---|
| 663 | * its default). |
---|
| 664 | * Also work out the threshold and store it in the par set. |
---|
| 665 | * |
---|
| 666 | * Different from Cube::setCubeStatsOld() as it doesn't use the |
---|
| 667 | * getStats functions but has own versions of them hardcoded to |
---|
| 668 | * ignore BLANKs and MW channels. This saves on memory usage -- necessary |
---|
| 669 | * for dealing with very big files. |
---|
| 670 | * |
---|
| 671 | * Three cases exist: |
---|
| 672 | * <ul><li>Simple case, with no reconstruction/smoothing: all stats |
---|
| 673 | * calculated from the original array. |
---|
| 674 | * <li>Wavelet reconstruction: mean & median calculated from the |
---|
| 675 | * original array, and stddev & madfm from the residual. |
---|
| 676 | * <li>Smoothing: all four stats calculated from the recon array |
---|
| 677 | * (which holds the smoothed data). |
---|
| 678 | * </ul> |
---|
| 679 | */ |
---|
[189] | 680 | |
---|
[385] | 681 | this->Stats.setRobust(this->par.getFlagRobustStats()); |
---|
| 682 | |
---|
[378] | 683 | if(!this->par.getFlagFDR() && this->par.getFlagUserThreshold() ){ |
---|
| 684 | // if the user has defined a threshold, set this in the StatsContainer |
---|
| 685 | this->Stats.setThreshold( this->par.getThreshold() ); |
---|
| 686 | } |
---|
| 687 | else{ |
---|
| 688 | // only work out the stats if we need to. |
---|
| 689 | // the only reason we don't is if the user has specified a threshold. |
---|
[205] | 690 | |
---|
[378] | 691 | if(this->par.isVerbose()) |
---|
| 692 | std::cout << "Calculating the cube statistics... " << std::flush; |
---|
[205] | 693 | |
---|
[378] | 694 | long xysize = this->axisDim[0]*this->axisDim[1]; |
---|
[211] | 695 | |
---|
[378] | 696 | bool *mask = new bool[this->numPixels]; |
---|
| 697 | int vox,goodSize = 0; |
---|
| 698 | for(int x=0;x<this->axisDim[0];x++){ |
---|
| 699 | for(int y=0;y<this->axisDim[1];y++){ |
---|
| 700 | for(int z=0;z<this->axisDim[2];z++){ |
---|
| 701 | vox = z * xysize + y*this->axisDim[0] + x; |
---|
| 702 | mask[vox] = (!this->isBlank(vox) && |
---|
| 703 | !this->par.isInMW(z) && |
---|
| 704 | this->par.isStatOK(x,y,z) ); |
---|
| 705 | if(mask[vox]) goodSize++; |
---|
| 706 | } |
---|
[211] | 707 | } |
---|
[205] | 708 | } |
---|
[212] | 709 | |
---|
[378] | 710 | float mean,median,stddev,madfm; |
---|
| 711 | if( this->par.getFlagATrous() ){ |
---|
| 712 | // Case #2 -- wavelet reconstruction |
---|
| 713 | // just get mean & median from orig array, and rms & madfm from |
---|
| 714 | // residual recompute array values to be residuals & then find |
---|
| 715 | // stddev & madfm |
---|
| 716 | if(!this->reconExists) |
---|
| 717 | duchampError("setCubeStats", |
---|
| 718 | "Reconstruction not yet done!\nCannot calculate stats!\n"); |
---|
| 719 | else{ |
---|
| 720 | float *tempArray = new float[goodSize]; |
---|
[211] | 721 | |
---|
[378] | 722 | goodSize=0; |
---|
| 723 | for(int x=0;x<this->axisDim[0];x++){ |
---|
| 724 | for(int y=0;y<this->axisDim[1];y++){ |
---|
| 725 | for(int z=0;z<this->axisDim[2];z++){ |
---|
| 726 | vox = z * xysize + y*this->axisDim[0] + x; |
---|
| 727 | if(mask[vox]) tempArray[goodSize++] = this->array[vox]; |
---|
| 728 | } |
---|
[275] | 729 | } |
---|
| 730 | } |
---|
[258] | 731 | |
---|
[378] | 732 | // First, find the mean of the original array. Store it. |
---|
| 733 | mean = tempArray[0]; |
---|
| 734 | for(int i=1;i<goodSize;i++) mean += tempArray[i]; |
---|
| 735 | mean /= float(goodSize); |
---|
| 736 | mean = findMean(tempArray,goodSize); |
---|
| 737 | this->Stats.setMean(mean); |
---|
[275] | 738 | |
---|
[378] | 739 | // Now sort it and find the median. Store it. |
---|
| 740 | std::sort(tempArray,tempArray+goodSize); |
---|
| 741 | if((goodSize%2)==0) |
---|
| 742 | median = (tempArray[goodSize/2-1] + tempArray[goodSize/2])/2; |
---|
| 743 | else median = tempArray[goodSize/2]; |
---|
| 744 | this->Stats.setMedian(median); |
---|
[275] | 745 | |
---|
[378] | 746 | // Now calculate the residuals and find the mean & median of |
---|
| 747 | // them. We don't store these, but they are necessary to find |
---|
| 748 | // the sttdev & madfm. |
---|
| 749 | goodSize = 0; |
---|
| 750 | for(int p=0;p<xysize;p++){ |
---|
| 751 | for(int z=0;z<this->axisDim[2];z++){ |
---|
| 752 | vox = z * xysize + p; |
---|
| 753 | if(mask[vox]) |
---|
| 754 | tempArray[goodSize++] = this->array[vox] - this->recon[vox]; |
---|
| 755 | } |
---|
[211] | 756 | } |
---|
[378] | 757 | mean = tempArray[0]; |
---|
| 758 | for(int i=1;i<goodSize;i++) mean += tempArray[i]; |
---|
| 759 | mean /= float(goodSize); |
---|
| 760 | std::sort(tempArray,tempArray+goodSize); |
---|
| 761 | if((goodSize%2)==0) |
---|
| 762 | median = (tempArray[goodSize/2-1] + tempArray[goodSize/2])/2; |
---|
| 763 | else median = tempArray[goodSize/2]; |
---|
[206] | 764 | |
---|
[378] | 765 | // Now find the standard deviation of the residuals. Store it. |
---|
| 766 | stddev = (tempArray[0]-mean) * (tempArray[0]-mean); |
---|
| 767 | for(int i=1;i<goodSize;i++) |
---|
| 768 | stddev += (tempArray[i]-mean)*(tempArray[i]-mean); |
---|
| 769 | stddev = sqrt(stddev/float(goodSize-1)); |
---|
| 770 | this->Stats.setStddev(stddev); |
---|
[275] | 771 | |
---|
[378] | 772 | // Now find the madfm of the residuals. Store it. |
---|
| 773 | for(int i=0;i<goodSize;i++){ |
---|
| 774 | if(tempArray[i]>median) tempArray[i] = tempArray[i]-median; |
---|
| 775 | else tempArray[i] = median - tempArray[i]; |
---|
| 776 | } |
---|
| 777 | std::sort(tempArray,tempArray+goodSize); |
---|
| 778 | if((goodSize%2)==0) |
---|
| 779 | madfm = (tempArray[goodSize/2-1] + tempArray[goodSize/2])/2; |
---|
| 780 | else madfm = tempArray[goodSize/2]; |
---|
| 781 | this->Stats.setMadfm(madfm); |
---|
| 782 | |
---|
| 783 | delete [] tempArray; |
---|
[275] | 784 | } |
---|
[378] | 785 | } |
---|
| 786 | else if(this->par.getFlagSmooth()) { |
---|
| 787 | // Case #3 -- smoothing |
---|
| 788 | // get all four stats from the recon array, which holds the |
---|
| 789 | // smoothed data. This can just be done with the |
---|
| 790 | // StatsContainer::calculate function, using the mask generated |
---|
| 791 | // earlier. |
---|
| 792 | if(!this->reconExists) |
---|
| 793 | duchampError("setCubeStats","Smoothing not yet done!\nCannot calculate stats!\n"); |
---|
| 794 | else this->Stats.calculate(this->recon,this->numPixels,mask); |
---|
| 795 | } |
---|
| 796 | else{ |
---|
| 797 | // Case #1 -- default case, with no smoothing or reconstruction. |
---|
| 798 | // get all four stats from the original array. This can just be |
---|
| 799 | // done with the StatsContainer::calculate function, using the |
---|
| 800 | // mask generated earlier. |
---|
| 801 | this->Stats.calculate(this->array,this->numPixels,mask); |
---|
[211] | 802 | } |
---|
[205] | 803 | |
---|
[378] | 804 | this->Stats.setUseFDR( this->par.getFlagFDR() ); |
---|
| 805 | // If the FDR method has been requested, define the P-value |
---|
| 806 | // threshold |
---|
| 807 | if(this->par.getFlagFDR()) this->setupFDR(); |
---|
| 808 | else{ |
---|
| 809 | // otherwise, calculate threshold based on the requested SNR cut |
---|
| 810 | // level, and then set the threshold parameter in the Par set. |
---|
| 811 | this->Stats.setThresholdSNR( this->par.getCut() ); |
---|
| 812 | this->par.setThreshold( this->Stats.getThreshold() ); |
---|
| 813 | } |
---|
| 814 | |
---|
| 815 | delete [] mask; |
---|
| 816 | |
---|
[275] | 817 | } |
---|
[206] | 818 | |
---|
[378] | 819 | if(this->par.isVerbose()){ |
---|
| 820 | std::cout << "Using "; |
---|
| 821 | if(this->par.getFlagFDR()) std::cout << "effective "; |
---|
| 822 | std::cout << "flux threshold of: "; |
---|
| 823 | float thresh = this->Stats.getThreshold(); |
---|
| 824 | if(this->par.getFlagNegative()) thresh *= -1.; |
---|
| 825 | std::cout << thresh << std::endl; |
---|
[205] | 826 | } |
---|
[309] | 827 | |
---|
[205] | 828 | } |
---|
[378] | 829 | //-------------------------------------------------------------------- |
---|
[211] | 830 | |
---|
[378] | 831 | void Cube::setupFDR() |
---|
| 832 | { |
---|
| 833 | /** |
---|
| 834 | * Call the setupFDR(float *) function on the pixel array of the |
---|
| 835 | * cube. This is the usual way of running it. |
---|
| 836 | * |
---|
| 837 | * However, if we are in smoothing mode, we calculate the FDR |
---|
| 838 | * parameters using the recon array, which holds the smoothed |
---|
| 839 | * data. Gives an error message if the reconExists flag is not set. |
---|
| 840 | * |
---|
| 841 | */ |
---|
| 842 | if(this->par.getFlagSmooth()) |
---|
| 843 | if(this->reconExists) this->setupFDR(this->recon); |
---|
| 844 | else{ |
---|
| 845 | duchampError("setupFDR", |
---|
| 846 | "Smoothing not done properly! Using original array for defining threshold.\n"); |
---|
| 847 | this->setupFDR(this->array); |
---|
| 848 | } |
---|
| 849 | else if( this->par.getFlagATrous() ){ |
---|
| 850 | this->setupFDR(this->recon); |
---|
| 851 | } |
---|
[275] | 852 | else{ |
---|
| 853 | this->setupFDR(this->array); |
---|
| 854 | } |
---|
| 855 | } |
---|
[378] | 856 | //-------------------------------------------------------------------- |
---|
[275] | 857 | |
---|
[378] | 858 | void Cube::setupFDR(float *input) |
---|
| 859 | { |
---|
| 860 | /** |
---|
| 861 | * Determines the critical Probability value for the False |
---|
| 862 | * Discovery Rate detection routine. All pixels in the given arry |
---|
| 863 | * with Prob less than this value will be considered detections. |
---|
| 864 | * |
---|
| 865 | * Note that the Stats of the cube need to be calculated first. |
---|
| 866 | * |
---|
| 867 | * The Prob here is the probability, assuming a Normal |
---|
| 868 | * distribution, of obtaining a value as high or higher than the |
---|
| 869 | * pixel value (ie. only the positive tail of the PDF). |
---|
| 870 | * |
---|
| 871 | * The probabilities are calculated using the |
---|
| 872 | * StatsContainer::getPValue(), which calculates the z-statistic, |
---|
| 873 | * and then the probability via |
---|
| 874 | * \f$0.5\operatorname{erfc}(z/\sqrt{2})\f$ -- giving the positive |
---|
| 875 | * tail probability. |
---|
| 876 | */ |
---|
[189] | 877 | |
---|
[378] | 878 | // first calculate p-value for each pixel -- assume Gaussian for now. |
---|
[190] | 879 | |
---|
[378] | 880 | float *orderedP = new float[this->numPixels]; |
---|
| 881 | int count = 0; |
---|
| 882 | for(int x=0;x<this->axisDim[0];x++){ |
---|
| 883 | for(int y=0;y<this->axisDim[1];y++){ |
---|
| 884 | for(int z=0;z<this->axisDim[2];z++){ |
---|
| 885 | int pix = z * this->axisDim[0]*this->axisDim[1] + |
---|
| 886 | y*this->axisDim[0] + x; |
---|
[190] | 887 | |
---|
[378] | 888 | if(!(this->par.isBlank(this->array[pix])) && !this->par.isInMW(z)){ |
---|
| 889 | // only look at non-blank, valid pixels |
---|
| 890 | // orderedP[count++] = this->Stats.getPValue(this->array[pix]); |
---|
| 891 | orderedP[count++] = this->Stats.getPValue(input[pix]); |
---|
| 892 | } |
---|
[263] | 893 | } |
---|
| 894 | } |
---|
[190] | 895 | } |
---|
[3] | 896 | |
---|
[378] | 897 | // now order them |
---|
| 898 | std::stable_sort(orderedP,orderedP+count); |
---|
[190] | 899 | |
---|
[378] | 900 | // now find the maximum P value. |
---|
| 901 | int max = 0; |
---|
| 902 | float cN = 0.; |
---|
| 903 | int numVox = int(ceil(this->par.getBeamSize())); |
---|
| 904 | // if(this->head.isSpecOK()) numVox *= 2; |
---|
| 905 | if(this->head.canUseThirdAxis()) numVox *= 2; |
---|
| 906 | // why beamSize*2? we are doing this in 3D, so spectrally assume just the |
---|
| 907 | // neighbouring channels are correlated, but spatially all those within |
---|
| 908 | // the beam, so total number of voxels is 2*beamSize |
---|
| 909 | for(int psfCtr=1;psfCtr<=numVox;psfCtr++) cN += 1./float(psfCtr); |
---|
[190] | 910 | |
---|
[378] | 911 | double slope = this->par.getAlpha()/cN; |
---|
| 912 | for(int loopCtr=0;loopCtr<count;loopCtr++) { |
---|
| 913 | if( orderedP[loopCtr] < (slope * double(loopCtr+1)/ double(count)) ){ |
---|
| 914 | max = loopCtr; |
---|
| 915 | } |
---|
[190] | 916 | } |
---|
| 917 | |
---|
[378] | 918 | this->Stats.setPThreshold( orderedP[max] ); |
---|
[190] | 919 | |
---|
| 920 | |
---|
[378] | 921 | // Find real value of the P threshold by finding the inverse of the |
---|
| 922 | // error function -- root finding with brute force technique |
---|
| 923 | // (relatively slow, but we only do it once). |
---|
| 924 | double zStat = 0.; |
---|
| 925 | double deltaZ = 0.1; |
---|
| 926 | double tolerance = 1.e-6; |
---|
| 927 | double initial = 0.5 * erfc(zStat/M_SQRT2) - this->Stats.getPThreshold(); |
---|
| 928 | do{ |
---|
| 929 | zStat+=deltaZ; |
---|
| 930 | double current = 0.5 * erfc(zStat/M_SQRT2) - this->Stats.getPThreshold(); |
---|
| 931 | if((initial*current)<0.){ |
---|
| 932 | zStat-=deltaZ; |
---|
| 933 | deltaZ/=2.; |
---|
| 934 | } |
---|
| 935 | }while(deltaZ>tolerance); |
---|
| 936 | this->Stats.setThreshold( zStat*this->Stats.getSpread() + |
---|
| 937 | this->Stats.getMiddle() ); |
---|
[192] | 938 | |
---|
[378] | 939 | /////////////////////////// |
---|
| 940 | // if(TESTING){ |
---|
| 941 | // std::stringstream ss; |
---|
| 942 | // float *xplot = new float[2*max]; |
---|
| 943 | // for(int i=0;i<2*max;i++) xplot[i]=float(i)/float(count); |
---|
| 944 | // cpgopen("latestFDR.ps/vcps"); |
---|
| 945 | // cpgpap(8.,1.); |
---|
| 946 | // cpgslw(3); |
---|
| 947 | // cpgenv(0,float(2*max)/float(count),0,orderedP[2*max],0,0); |
---|
| 948 | // cpglab("i/N (index)", "p-value",""); |
---|
| 949 | // cpgpt(2*max,xplot,orderedP,DOT); |
---|
[263] | 950 | |
---|
[378] | 951 | // ss.str(""); |
---|
| 952 | // ss << "\\gm = " << this->Stats.getMiddle(); |
---|
| 953 | // cpgtext(max/(4.*count),0.9*orderedP[2*max],ss.str().c_str()); |
---|
| 954 | // ss.str(""); |
---|
| 955 | // ss << "\\gs = " << this->Stats.getSpread(); |
---|
| 956 | // cpgtext(max/(4.*count),0.85*orderedP[2*max],ss.str().c_str()); |
---|
| 957 | // ss.str(""); |
---|
| 958 | // ss << "Slope = " << slope; |
---|
| 959 | // cpgtext(max/(4.*count),0.8*orderedP[2*max],ss.str().c_str()); |
---|
| 960 | // ss.str(""); |
---|
| 961 | // ss << "Alpha = " << this->par.getAlpha(); |
---|
| 962 | // cpgtext(max/(4.*count),0.75*orderedP[2*max],ss.str().c_str()); |
---|
| 963 | // ss.str(""); |
---|
| 964 | // ss << "c\\dN\\u = " << cN; |
---|
| 965 | // cpgtext(max/(4.*count),0.7*orderedP[2*max],ss.str().c_str()); |
---|
| 966 | // ss.str(""); |
---|
| 967 | // ss << "max = "<<max << " (out of " << count << ")"; |
---|
| 968 | // cpgtext(max/(4.*count),0.65*orderedP[2*max],ss.str().c_str()); |
---|
| 969 | // ss.str(""); |
---|
| 970 | // ss << "Threshold = "<<zStat*this->Stats.getSpread()+this->Stats.getMiddle(); |
---|
| 971 | // cpgtext(max/(4.*count),0.6*orderedP[2*max],ss.str().c_str()); |
---|
[263] | 972 | |
---|
[378] | 973 | // cpgslw(1); |
---|
| 974 | // cpgsci(RED); |
---|
| 975 | // cpgmove(0,0); |
---|
| 976 | // cpgdraw(1,slope); |
---|
| 977 | // cpgsci(BLUE); |
---|
| 978 | // cpgsls(DOTTED); |
---|
| 979 | // cpgmove(0,orderedP[max]); |
---|
| 980 | // cpgdraw(2*max/float(count),orderedP[max]); |
---|
| 981 | // cpgmove(max/float(count),0); |
---|
| 982 | // cpgdraw(max/float(count),orderedP[2*max]); |
---|
| 983 | // cpgsci(GREEN); |
---|
| 984 | // cpgsls(SOLID); |
---|
| 985 | // for(int i=1;i<=10;i++) { |
---|
| 986 | // ss.str(""); |
---|
| 987 | // ss << float(i)/2. << "\\gs"; |
---|
| 988 | // float prob = 0.5*erfc((float(i)/2.)/M_SQRT2); |
---|
| 989 | // cpgtick(0, 0, 0, orderedP[2*max], |
---|
| 990 | // prob/orderedP[2*max], |
---|
| 991 | // 0, 1, 1.5, 90., ss.str().c_str()); |
---|
| 992 | // } |
---|
| 993 | // cpgend(); |
---|
| 994 | // delete [] xplot; |
---|
| 995 | // } |
---|
| 996 | delete [] orderedP; |
---|
[263] | 997 | |
---|
[378] | 998 | } |
---|
| 999 | //-------------------------------------------------------------------- |
---|
[87] | 1000 | |
---|
[378] | 1001 | bool Cube::isDetection(long x, long y, long z) |
---|
| 1002 | { |
---|
| 1003 | /** |
---|
| 1004 | * Is a given voxel at position (x,y,z) a detection, based on the statistics |
---|
| 1005 | * in the Cube's StatsContainer? |
---|
| 1006 | * If the pixel lies outside the valid range for the data array, |
---|
| 1007 | * return false. |
---|
| 1008 | * \param x X-value of the Cube's voxel to be tested. |
---|
| 1009 | * \param y Y-value of the Cube's voxel to be tested. |
---|
| 1010 | * \param z Z-value of the Cube's voxel to be tested. |
---|
| 1011 | */ |
---|
[220] | 1012 | long voxel = z*axisDim[0]*axisDim[1] + y*axisDim[0] + x; |
---|
| 1013 | return DataArray::isDetection(array[voxel]); |
---|
| 1014 | }; |
---|
[378] | 1015 | //-------------------------------------------------------------------- |
---|
[220] | 1016 | |
---|
[378] | 1017 | void Cube::calcObjectWCSparams() |
---|
| 1018 | { |
---|
| 1019 | /** |
---|
| 1020 | * A function that calculates the WCS parameters for each object in the |
---|
| 1021 | * Cube's list of detections. |
---|
| 1022 | * Each object gets an ID number assigned to it (which is simply its order |
---|
| 1023 | * in the list), and if the WCS is good, the WCS paramters are calculated. |
---|
| 1024 | */ |
---|
[220] | 1025 | |
---|
[378] | 1026 | for(int i=0;i<this->objectList->size();i++){ |
---|
| 1027 | this->objectList->at(i).setID(i+1); |
---|
| 1028 | this->objectList->at(i).setCentreType(this->par.getPixelCentre()); |
---|
| 1029 | this->objectList->at(i).calcFluxes(this->array,this->axisDim); |
---|
| 1030 | this->objectList->at(i).calcWCSparams(this->array,this->axisDim,this->head); |
---|
[258] | 1031 | |
---|
[378] | 1032 | if(this->par.getFlagUserThreshold()) |
---|
| 1033 | this->objectList->at(i).setPeakSNR( this->objectList->at(i).getPeakFlux() / this->Stats.getThreshold() ); |
---|
| 1034 | else |
---|
| 1035 | this->objectList->at(i).setPeakSNR( (this->objectList->at(i).getPeakFlux() - this->Stats.getMiddle()) / this->Stats.getSpread() ); |
---|
[258] | 1036 | |
---|
[378] | 1037 | } |
---|
[220] | 1038 | |
---|
[378] | 1039 | if(!this->head.isWCS()){ |
---|
| 1040 | // if the WCS is bad, set the object names to Obj01 etc |
---|
| 1041 | int numspaces = int(log10(this->objectList->size())) + 1; |
---|
| 1042 | std::stringstream ss; |
---|
| 1043 | for(int i=0;i<this->objectList->size();i++){ |
---|
| 1044 | ss.str(""); |
---|
| 1045 | ss << "Obj" << std::setfill('0') << std::setw(numspaces) << i+1; |
---|
| 1046 | this->objectList->at(i).setName(ss.str()); |
---|
| 1047 | } |
---|
[220] | 1048 | } |
---|
[378] | 1049 | |
---|
[220] | 1050 | } |
---|
[378] | 1051 | //-------------------------------------------------------------------- |
---|
[220] | 1052 | |
---|
[378] | 1053 | void Cube::updateDetectMap() |
---|
| 1054 | { |
---|
| 1055 | /** |
---|
| 1056 | * A function that, for each detected object in the cube's list, increments |
---|
| 1057 | * the cube's detection map by the required amount at each pixel. |
---|
| 1058 | */ |
---|
[220] | 1059 | |
---|
[378] | 1060 | Scan temp; |
---|
| 1061 | for(int obj=0;obj<this->objectList->size();obj++){ |
---|
| 1062 | long numZ=this->objectList->at(obj).pixels().getNumChanMap(); |
---|
| 1063 | for(int iz=0;iz<numZ;iz++){ // for each channel map |
---|
| 1064 | Object2D *chanmap = new Object2D; |
---|
| 1065 | *chanmap = this->objectList->at(obj).pixels().getChanMap(iz).getObject(); |
---|
| 1066 | for(int iscan=0;iscan<chanmap->getNumScan();iscan++){ |
---|
| 1067 | temp = chanmap->getScan(iscan); |
---|
| 1068 | for(int x=temp.getX(); x <= temp.getXmax(); x++) |
---|
| 1069 | this->detectMap[temp.getY()*this->axisDim[0] + x]++; |
---|
| 1070 | } // end of loop over scans |
---|
| 1071 | delete chanmap; |
---|
| 1072 | } // end of loop over channel maps |
---|
| 1073 | } // end of loop over objects. |
---|
| 1074 | |
---|
| 1075 | } |
---|
| 1076 | //-------------------------------------------------------------------- |
---|
| 1077 | |
---|
| 1078 | void Cube::updateDetectMap(Detection obj) |
---|
| 1079 | { |
---|
| 1080 | /** |
---|
| 1081 | * A function that, for the given object, increments the cube's |
---|
| 1082 | * detection map by the required amount at each pixel. |
---|
| 1083 | * |
---|
| 1084 | * \param obj A Detection object that is being incorporated into the map. |
---|
| 1085 | */ |
---|
| 1086 | |
---|
| 1087 | Scan temp; |
---|
| 1088 | long numZ=obj.pixels().getNumChanMap(); |
---|
[258] | 1089 | for(int iz=0;iz<numZ;iz++){ // for each channel map |
---|
[378] | 1090 | Object2D chanmap = obj.pixels().getChanMap(iz).getObject(); |
---|
| 1091 | for(int iscan=0;iscan<chanmap.getNumScan();iscan++){ |
---|
| 1092 | temp = chanmap.getScan(iscan); |
---|
[258] | 1093 | for(int x=temp.getX(); x <= temp.getXmax(); x++) |
---|
| 1094 | this->detectMap[temp.getY()*this->axisDim[0] + x]++; |
---|
| 1095 | } // end of loop over scans |
---|
| 1096 | } // end of loop over channel maps |
---|
| 1097 | |
---|
[378] | 1098 | } |
---|
| 1099 | //-------------------------------------------------------------------- |
---|
[220] | 1100 | |
---|
[378] | 1101 | float Cube::enclosedFlux(Detection obj) |
---|
| 1102 | { |
---|
| 1103 | /** |
---|
| 1104 | * A function to calculate the flux enclosed by the range |
---|
| 1105 | * of pixels detected in the object obj (not necessarily all |
---|
| 1106 | * pixels will have been detected). |
---|
| 1107 | * |
---|
| 1108 | * \param obj The Detection under consideration. |
---|
| 1109 | */ |
---|
| 1110 | obj.calcFluxes(this->array, this->axisDim); |
---|
| 1111 | int xsize = obj.getXmax()-obj.getXmin()+1; |
---|
| 1112 | int ysize = obj.getYmax()-obj.getYmin()+1; |
---|
| 1113 | int zsize = obj.getZmax()-obj.getZmin()+1; |
---|
| 1114 | std::vector <float> fluxArray(xsize*ysize*zsize,0.); |
---|
| 1115 | for(int x=0;x<xsize;x++){ |
---|
| 1116 | for(int y=0;y<ysize;y++){ |
---|
| 1117 | for(int z=0;z<zsize;z++){ |
---|
| 1118 | fluxArray[x+y*xsize+z*ysize*xsize] = |
---|
| 1119 | this->getPixValue(x+obj.getXmin(), |
---|
| 1120 | y+obj.getYmin(), |
---|
| 1121 | z+obj.getZmin()); |
---|
| 1122 | if(this->par.getFlagNegative()) |
---|
| 1123 | fluxArray[x+y*xsize+z*ysize*xsize] *= -1.; |
---|
| 1124 | } |
---|
[87] | 1125 | } |
---|
| 1126 | } |
---|
[378] | 1127 | float sum = 0.; |
---|
| 1128 | for(int i=0;i<fluxArray.size();i++) |
---|
| 1129 | if(!this->par.isBlank(fluxArray[i])) sum+=fluxArray[i]; |
---|
| 1130 | return sum; |
---|
[87] | 1131 | } |
---|
[378] | 1132 | //-------------------------------------------------------------------- |
---|
[87] | 1133 | |
---|
[378] | 1134 | void Cube::setupColumns() |
---|
| 1135 | { |
---|
| 1136 | /** |
---|
| 1137 | * A front-end to the two setup routines in columns.cc. |
---|
| 1138 | * This first calculates the WCS parameters for all objects, then |
---|
| 1139 | * sets up the columns (calculates their widths and precisions and so on). |
---|
| 1140 | * The precisions are also stored in each Detection object. |
---|
| 1141 | */ |
---|
| 1142 | this->calcObjectWCSparams(); |
---|
| 1143 | // need this as the colSet functions use vel, RA, Dec, etc... |
---|
[187] | 1144 | |
---|
[378] | 1145 | this->fullCols.clear(); |
---|
| 1146 | this->fullCols = getFullColSet(*(this->objectList), this->head); |
---|
[136] | 1147 | |
---|
[378] | 1148 | this->logCols.clear(); |
---|
| 1149 | this->logCols = getLogColSet(*(this->objectList), this->head); |
---|
[136] | 1150 | |
---|
[378] | 1151 | int vel,fpeak,fint,pos,xyz,snr; |
---|
| 1152 | vel = fullCols[VEL].getPrecision(); |
---|
| 1153 | fpeak = fullCols[FPEAK].getPrecision(); |
---|
| 1154 | snr = fullCols[SNRPEAK].getPrecision(); |
---|
| 1155 | xyz = fullCols[X].getPrecision(); |
---|
| 1156 | xyz = std::max(xyz, fullCols[Y].getPrecision()); |
---|
| 1157 | xyz = std::max(xyz, fullCols[Z].getPrecision()); |
---|
| 1158 | if(this->head.isWCS()) fint = fullCols[FINT].getPrecision(); |
---|
| 1159 | else fint = fullCols[FTOT].getPrecision(); |
---|
| 1160 | pos = fullCols[WRA].getPrecision(); |
---|
| 1161 | pos = std::max(pos, fullCols[WDEC].getPrecision()); |
---|
[144] | 1162 | |
---|
[378] | 1163 | for(int obj=0;obj<this->objectList->size();obj++){ |
---|
| 1164 | this->objectList->at(obj).setVelPrec(vel); |
---|
| 1165 | this->objectList->at(obj).setFpeakPrec(fpeak); |
---|
| 1166 | this->objectList->at(obj).setXYZPrec(xyz); |
---|
| 1167 | this->objectList->at(obj).setPosPrec(pos); |
---|
| 1168 | this->objectList->at(obj).setFintPrec(fint); |
---|
| 1169 | this->objectList->at(obj).setSNRPrec(snr); |
---|
| 1170 | } |
---|
| 1171 | |
---|
[144] | 1172 | } |
---|
[378] | 1173 | //-------------------------------------------------------------------- |
---|
[136] | 1174 | |
---|
[378] | 1175 | bool Cube::objAtSpatialEdge(Detection obj) |
---|
| 1176 | { |
---|
| 1177 | /** |
---|
| 1178 | * A function to test whether the object obj |
---|
| 1179 | * lies at the edge of the cube's spatial field -- |
---|
| 1180 | * either at the boundary, or next to BLANKs. |
---|
| 1181 | * |
---|
| 1182 | * \param obj The Detection under consideration. |
---|
| 1183 | */ |
---|
[136] | 1184 | |
---|
[378] | 1185 | bool atEdge = false; |
---|
[87] | 1186 | |
---|
[378] | 1187 | int pix = 0; |
---|
| 1188 | std::vector<Voxel> voxlist = obj.pixels().getPixelSet(); |
---|
| 1189 | while(!atEdge && pix<voxlist.size()){ |
---|
| 1190 | // loop over each pixel in the object, until we find an edge pixel. |
---|
| 1191 | for(int dx=-1;dx<=1;dx+=2){ |
---|
| 1192 | if( ((voxlist[pix].getX()+dx)<0) || |
---|
| 1193 | ((voxlist[pix].getX()+dx)>=this->axisDim[0]) ) |
---|
| 1194 | atEdge = true; |
---|
| 1195 | else if(this->isBlank(voxlist[pix].getX()+dx, |
---|
| 1196 | voxlist[pix].getY(), |
---|
| 1197 | voxlist[pix].getZ())) |
---|
| 1198 | atEdge = true; |
---|
| 1199 | } |
---|
| 1200 | for(int dy=-1;dy<=1;dy+=2){ |
---|
| 1201 | if( ((voxlist[pix].getY()+dy)<0) || |
---|
| 1202 | ((voxlist[pix].getY()+dy)>=this->axisDim[1]) ) |
---|
| 1203 | atEdge = true; |
---|
| 1204 | else if(this->isBlank(voxlist[pix].getX(), |
---|
| 1205 | voxlist[pix].getY()+dy, |
---|
| 1206 | voxlist[pix].getZ())) |
---|
| 1207 | atEdge = true; |
---|
| 1208 | } |
---|
| 1209 | pix++; |
---|
| 1210 | } |
---|
[87] | 1211 | |
---|
[378] | 1212 | return atEdge; |
---|
[192] | 1213 | } |
---|
[378] | 1214 | //-------------------------------------------------------------------- |
---|
[192] | 1215 | |
---|
[378] | 1216 | bool Cube::objAtSpectralEdge(Detection obj) |
---|
| 1217 | { |
---|
| 1218 | /** |
---|
| 1219 | * A function to test whether the object obj |
---|
| 1220 | * lies at the edge of the cube's spectral extent -- |
---|
| 1221 | * either at the boundary, or next to BLANKs. |
---|
| 1222 | * |
---|
| 1223 | * /param obj The Detection under consideration. |
---|
| 1224 | */ |
---|
[192] | 1225 | |
---|
[378] | 1226 | bool atEdge = false; |
---|
[192] | 1227 | |
---|
[378] | 1228 | int pix = 0; |
---|
| 1229 | std::vector<Voxel> voxlist = obj.pixels().getPixelSet(); |
---|
| 1230 | while(!atEdge && pix<voxlist.size()){ |
---|
| 1231 | // loop over each pixel in the object, until we find an edge pixel. |
---|
| 1232 | for(int dz=-1;dz<=1;dz+=2){ |
---|
| 1233 | if( ((voxlist[pix].getZ()+dz)<0) || |
---|
| 1234 | ((voxlist[pix].getZ()+dz)>=this->axisDim[2])) |
---|
| 1235 | atEdge = true; |
---|
| 1236 | else if(this->isBlank(voxlist[pix].getX(), |
---|
| 1237 | voxlist[pix].getY(), |
---|
| 1238 | voxlist[pix].getZ()+dz)) |
---|
| 1239 | atEdge = true; |
---|
| 1240 | } |
---|
| 1241 | pix++; |
---|
| 1242 | } |
---|
[192] | 1243 | |
---|
[378] | 1244 | return atEdge; |
---|
[87] | 1245 | } |
---|
[378] | 1246 | //-------------------------------------------------------------------- |
---|
[87] | 1247 | |
---|
[378] | 1248 | void Cube::setObjectFlags() |
---|
| 1249 | { |
---|
| 1250 | /** |
---|
| 1251 | * A function to set any warning flags for all the detected objects |
---|
| 1252 | * associated with the cube. |
---|
| 1253 | * Flags to be looked for: |
---|
| 1254 | * <ul><li> Negative enclosed flux (N) |
---|
| 1255 | * <li> Detection at edge of field (spatially) (E) |
---|
| 1256 | * <li> Detection at edge of spectral region (S) |
---|
| 1257 | * </ul> |
---|
| 1258 | */ |
---|
[87] | 1259 | |
---|
[378] | 1260 | for(int i=0;i<this->objectList->size();i++){ |
---|
[87] | 1261 | |
---|
[378] | 1262 | if( this->enclosedFlux(this->objectList->at(i)) < 0. ) |
---|
| 1263 | this->objectList->at(i).addToFlagText("N"); |
---|
[87] | 1264 | |
---|
[378] | 1265 | if( this->objAtSpatialEdge(this->objectList->at(i)) ) |
---|
| 1266 | this->objectList->at(i).addToFlagText("E"); |
---|
[87] | 1267 | |
---|
[378] | 1268 | if( this->objAtSpectralEdge(this->objectList->at(i)) && |
---|
| 1269 | (this->axisDim[2] > 2)) |
---|
| 1270 | this->objectList->at(i).addToFlagText("S"); |
---|
[87] | 1271 | |
---|
[378] | 1272 | } |
---|
[192] | 1273 | |
---|
[87] | 1274 | } |
---|
[378] | 1275 | //-------------------------------------------------------------------- |
---|
[87] | 1276 | |
---|
[129] | 1277 | |
---|
[220] | 1278 | |
---|
[378] | 1279 | /****************************************************************/ |
---|
| 1280 | ///////////////////////////////////////////////////////////// |
---|
| 1281 | //// Functions for Image class |
---|
| 1282 | ///////////////////////////////////////////////////////////// |
---|
[220] | 1283 | |
---|
[378] | 1284 | Image::Image(long size){ |
---|
| 1285 | // need error handling in case size<0 !!! |
---|
| 1286 | this->numPixels = this->numDim = 0; |
---|
| 1287 | if(size<0) |
---|
| 1288 | duchampError("Image(size)","Negative size -- could not define Image"); |
---|
| 1289 | else{ |
---|
| 1290 | if(size>0) this->array = new float[size]; |
---|
| 1291 | this->numPixels = size; |
---|
| 1292 | this->axisDim = new long[2]; |
---|
| 1293 | this->numDim = 2; |
---|
| 1294 | } |
---|
[220] | 1295 | } |
---|
[378] | 1296 | //-------------------------------------------------------------------- |
---|
[220] | 1297 | |
---|
[378] | 1298 | Image::Image(long *dimensions){ |
---|
| 1299 | this->numPixels = this->numDim = 0; |
---|
| 1300 | int size = dimensions[0] * dimensions[1]; |
---|
| 1301 | if(size<0) |
---|
| 1302 | duchampError("Image(dimArray)","Negative size -- could not define Image"); |
---|
| 1303 | else{ |
---|
| 1304 | this->numPixels = size; |
---|
| 1305 | if(size>0) this->array = new float[size]; |
---|
| 1306 | this->numDim=2; |
---|
| 1307 | this->axisDim = new long[2]; |
---|
| 1308 | for(int i=0;i<2;i++) this->axisDim[i] = dimensions[i]; |
---|
| 1309 | } |
---|
[220] | 1310 | } |
---|
[378] | 1311 | //-------------------------------------------------------------------- |
---|
| 1312 | //-------------------------------------------------------------------- |
---|
[220] | 1313 | |
---|
[378] | 1314 | void Image::saveArray(float *input, long size) |
---|
| 1315 | { |
---|
| 1316 | /** |
---|
| 1317 | * Saves the array in input to the pixel array Image::array. |
---|
| 1318 | * The size of the array given must be the same as the current number of |
---|
| 1319 | * pixels, else an error message is returned and nothing is done. |
---|
| 1320 | * \param input The array of values to be saved. |
---|
| 1321 | * \param size The size of input. |
---|
| 1322 | */ |
---|
| 1323 | if(size != this->numPixels) |
---|
| 1324 | duchampError("Image::saveArray", |
---|
| 1325 | "Input array different size to existing array. Cannot save."); |
---|
| 1326 | else { |
---|
| 1327 | if(this->numPixels>0) delete [] array; |
---|
| 1328 | this->numPixels = size; |
---|
| 1329 | if(this->numPixels>0) this->array = new float[size]; |
---|
| 1330 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
---|
| 1331 | } |
---|
[220] | 1332 | } |
---|
[378] | 1333 | //-------------------------------------------------------------------- |
---|
[220] | 1334 | |
---|
[378] | 1335 | void Image::extractSpectrum(float *Array, long *dim, long pixel) |
---|
| 1336 | { |
---|
| 1337 | /** |
---|
| 1338 | * A function to extract a 1-D spectrum from a 3-D array. |
---|
| 1339 | * The array is assumed to be 3-D with the third dimension the spectral one. |
---|
| 1340 | * The spectrum extracted is the one lying in the spatial pixel referenced |
---|
| 1341 | * by the third argument. |
---|
| 1342 | * The extracted spectrum is stored in the pixel array Image::array. |
---|
| 1343 | * \param Array The array containing the pixel values, from which |
---|
| 1344 | * the spectrum is extracted. |
---|
| 1345 | * \param dim The array of dimension values. |
---|
| 1346 | * \param pixel The spatial pixel that contains the desired spectrum. |
---|
| 1347 | */ |
---|
| 1348 | if((pixel<0)||(pixel>=dim[0]*dim[1])) |
---|
| 1349 | duchampError("Image::extractSpectrum", |
---|
| 1350 | "Requested spatial pixel outside allowed range. Cannot save."); |
---|
| 1351 | else if(dim[2] != this->numPixels) |
---|
| 1352 | duchampError("Image::extractSpectrum", |
---|
| 1353 | "Input array different size to existing array. Cannot save."); |
---|
| 1354 | else { |
---|
| 1355 | if(this->numPixels>0) delete [] array; |
---|
| 1356 | this->numPixels = dim[2]; |
---|
| 1357 | if(this->numPixels>0) this->array = new float[dim[2]]; |
---|
| 1358 | for(int z=0;z<dim[2];z++) this->array[z] = Array[z*dim[0]*dim[1] + pixel]; |
---|
| 1359 | } |
---|
[258] | 1360 | } |
---|
[378] | 1361 | //-------------------------------------------------------------------- |
---|
[220] | 1362 | |
---|
[378] | 1363 | void Image::extractSpectrum(Cube &cube, long pixel) |
---|
| 1364 | { |
---|
| 1365 | /** |
---|
| 1366 | * A function to extract a 1-D spectrum from a Cube class |
---|
| 1367 | * The spectrum extracted is the one lying in the spatial pixel referenced |
---|
| 1368 | * by the second argument. |
---|
| 1369 | * The extracted spectrum is stored in the pixel array Image::array. |
---|
| 1370 | * \param cube The Cube containing the pixel values, from which the spectrum is extracted. |
---|
| 1371 | * \param pixel The spatial pixel that contains the desired spectrum. |
---|
| 1372 | */ |
---|
| 1373 | long zdim = cube.getDimZ(); |
---|
| 1374 | long spatSize = cube.getDimX()*cube.getDimY(); |
---|
| 1375 | if((pixel<0)||(pixel>=spatSize)) |
---|
| 1376 | duchampError("Image::extractSpectrum", |
---|
| 1377 | "Requested spatial pixel outside allowed range. Cannot save."); |
---|
| 1378 | else if(zdim != this->numPixels) |
---|
| 1379 | duchampError("Image::extractSpectrum", |
---|
| 1380 | "Input array different size to existing array. Cannot save."); |
---|
| 1381 | else { |
---|
| 1382 | if(this->numPixels>0) delete [] array; |
---|
| 1383 | this->numPixels = zdim; |
---|
| 1384 | if(this->numPixels>0) this->array = new float[zdim]; |
---|
| 1385 | for(int z=0;z<zdim;z++) |
---|
| 1386 | this->array[z] = cube.getPixValue(z*spatSize + pixel); |
---|
| 1387 | } |
---|
[258] | 1388 | } |
---|
[378] | 1389 | //-------------------------------------------------------------------- |
---|
[220] | 1390 | |
---|
[378] | 1391 | void Image::extractImage(float *Array, long *dim, long channel) |
---|
| 1392 | { |
---|
| 1393 | /** |
---|
| 1394 | * A function to extract a 2-D image from a 3-D array. |
---|
| 1395 | * The array is assumed to be 3-D with the third dimension the spectral one. |
---|
| 1396 | * The dimensions of the array are in the dim[] array. |
---|
| 1397 | * The image extracted is the one lying in the channel referenced |
---|
| 1398 | * by the third argument. |
---|
| 1399 | * The extracted image is stored in the pixel array Image::array. |
---|
| 1400 | * \param Array The array containing the pixel values, from which the image is extracted. |
---|
| 1401 | * \param dim The array of dimension values. |
---|
| 1402 | * \param channel The spectral channel that contains the desired image. |
---|
| 1403 | */ |
---|
[258] | 1404 | |
---|
[378] | 1405 | long spatSize = dim[0]*dim[1]; |
---|
| 1406 | if((channel<0)||(channel>=dim[2])) |
---|
| 1407 | duchampError("Image::extractImage", |
---|
| 1408 | "Requested channel outside allowed range. Cannot save."); |
---|
| 1409 | else if(spatSize != this->numPixels) |
---|
| 1410 | duchampError("Image::extractImage", |
---|
| 1411 | "Input array different size to existing array. Cannot save."); |
---|
| 1412 | else { |
---|
| 1413 | if(this->numPixels>0) delete [] array; |
---|
| 1414 | this->numPixels = spatSize; |
---|
| 1415 | if(this->numPixels>0) this->array = new float[spatSize]; |
---|
| 1416 | for(int npix=0; npix<spatSize; npix++) |
---|
| 1417 | this->array[npix] = Array[channel*spatSize + npix]; |
---|
| 1418 | } |
---|
[220] | 1419 | } |
---|
[378] | 1420 | //-------------------------------------------------------------------- |
---|
[220] | 1421 | |
---|
[378] | 1422 | void Image::extractImage(Cube &cube, long channel) |
---|
| 1423 | { |
---|
| 1424 | /** |
---|
| 1425 | * A function to extract a 2-D image from Cube class. |
---|
| 1426 | * The image extracted is the one lying in the channel referenced |
---|
| 1427 | * by the second argument. |
---|
| 1428 | * The extracted image is stored in the pixel array Image::array. |
---|
| 1429 | * \param cube The Cube containing the pixel values, from which the image is extracted. |
---|
| 1430 | * \param channel The spectral channel that contains the desired image. |
---|
| 1431 | */ |
---|
| 1432 | long spatSize = cube.getDimX()*cube.getDimY(); |
---|
| 1433 | if((channel<0)||(channel>=cube.getDimZ())) |
---|
| 1434 | duchampError("Image::extractImage", |
---|
| 1435 | "Requested channel outside allowed range. Cannot save."); |
---|
| 1436 | else if(spatSize != this->numPixels) |
---|
| 1437 | duchampError("Image::extractImage", |
---|
| 1438 | "Input array different size to existing array. Cannot save."); |
---|
| 1439 | else { |
---|
| 1440 | if(this->numPixels>0) delete [] array; |
---|
| 1441 | this->numPixels = spatSize; |
---|
| 1442 | if(this->numPixels>0) this->array = new float[spatSize]; |
---|
| 1443 | for(int npix=0; npix<spatSize; npix++) |
---|
| 1444 | this->array[npix] = cube.getPixValue(channel*spatSize + npix); |
---|
| 1445 | } |
---|
[258] | 1446 | } |
---|
[378] | 1447 | //-------------------------------------------------------------------- |
---|
[220] | 1448 | |
---|
[378] | 1449 | void Image::removeMW() |
---|
| 1450 | { |
---|
| 1451 | /** |
---|
| 1452 | * A function to remove the Milky Way range of channels from a 1-D spectrum. |
---|
| 1453 | * The array in this Image is assumed to be 1-D, with only the first axisDim |
---|
| 1454 | * equal to 1. |
---|
| 1455 | * The values of the MW channels are set to 0, unless they are BLANK. |
---|
| 1456 | */ |
---|
| 1457 | if(this->par.getFlagMW() && (this->axisDim[1]==1) ){ |
---|
| 1458 | for(int z=0;z<this->axisDim[0];z++){ |
---|
| 1459 | if(!this->isBlank(z) && this->par.isInMW(z)) this->array[z]=0.; |
---|
| 1460 | } |
---|
[220] | 1461 | } |
---|
| 1462 | } |
---|
[378] | 1463 | |
---|
[220] | 1464 | } |
---|