source: tags/release-1.0.5/src/Cubes/cubes.cc @ 178

#include <unistd.h>
#include <iostream>
#include <iomanip>
#include <vector>
#include <string>

#include <wcs.h>

#include <duchamp.hh>
#include <param.hh>
#include <Cubes/cubes.hh>
#include <Detection/detection.hh>
#include <Detection/columns.hh>
#include <Utils/utils.hh>
#include <Utils/mycpgplot.hh>
using std::endl;
using namespace Column;
using namespace mycpgplot;

/****************************************************************/
///////////////////////////////////////////////////
//// Functions for DataArray class:
///////////////////////////////////////////////////

DataArray::DataArray(short int nDim, long size){

  if(size<0)
    duchampError("DataArray(nDim,size)",
                 "Negative size -- could not define DataArray");
  else if(nDim<0)
    duchampError("DataArray(nDim,size)",
                 "Negative number of dimensions: could not define DataArray");
  else {
    if(size>0) this->array = new float[size];
    this->numPixels = size;
    if(nDim>0) this->axisDim = new long[nDim];
    this->numDim = nDim;
  }
}

DataArray::DataArray(short int nDim, long *dimensions){
  if(nDim<0)
    duchampError("DataArray(nDim,dimArray)",
                 "Negative number of dimensions: could not define DataArray");
  else {
    int size = dimensions[0];
    for(int i=1;i<nDim;i++) size *= dimensions[i];
    if(size<0)
      duchampError("DataArray(nDim,dimArray)",
                   "Negative size: could not define DataArray");
    else{
      this->numPixels = size;
      if(size>0){
        this->array = new float[size];
      }
      this->numDim=nDim;
      if(nDim>0) this->axisDim = new long[nDim];
      for(int i=0;i<nDim;i++) this->axisDim[i] = dimensions[i];
    }
  }
}

DataArray::~DataArray()
{
  delete [] array;
  delete [] axisDim;
  objectList.clear();
}

void DataArray::getDimArray(long *output){
  for(int i=0;i<this->numDim;i++) output[i] = this->axisDim[i];
}

void DataArray::getArray(float *output){
  for(int i=0;i<this->numPixels;i++) output[i] = this->array[i];
}

void DataArray::saveArray(float *input, long size){
  if(size != this->numPixels)
    duchampError("DataArray::saveArray",
                 "Input array different size to existing array. Cannot save.");
  else {
    if(this->numPixels>0) delete [] this->array;
    this->numPixels = size;
    this->array = new float[size];
    for(int i=0;i<size;i++) this->array[i] = input[i];
  }
}

void DataArray::getDim(long &x, long &y, long &z){
  if(numDim>0) x=axisDim[0]; 
  else x=0;
  if(numDim>1) y=axisDim[1]; 
  else y=0;
  if(numDim>2) z=axisDim[2]; 
  else z=0;
}

void DataArray::addObject(Detection object){ 
  // adds a single detection to the object list
  // objectList is a vector, so just use push_back()
  this->objectList.push_back(object);
}

void DataArray::addObjectList(vector <Detection> newlist) {
  for(int i=0;i<newlist.size();i++) this->objectList.push_back(newlist[i]);
}

void DataArray::addObjectOffsets(){
  for(int i=0;i<this->objectList.size();i++){
    for(int p=0;p<this->objectList[i].getSize();p++){
      this->objectList[i].setX(p,this->objectList[i].getX(p)+
                               this->par.getXOffset());
      this->objectList[i].setY(p,this->objectList[i].getY(p)+
                               this->par.getYOffset());
      this->objectList[i].setZ(p,this->objectList[i].getZ(p)+
                               this->par.getZOffset());
    }
  }
}


std::ostream& operator<< ( std::ostream& theStream, DataArray &array)
{
  for(int i=0;i<array.numDim;i++){
    if(i>0) theStream<<"x";
    theStream<<array.axisDim[i];
  }
  theStream<<endl;
  theStream<<array.objectList.size()<<" detections:"<<endl<<"--------------\n";
  for(int i=0;i<array.objectList.size();i++){
    theStream << "Detection #" << array.objectList[i].getID()<<endl;
    Detection *obj = new Detection;
    *obj = array.objectList[i];
    for(int j=0;j<obj->getSize();j++){
      obj->setX(j,obj->getX(j)+obj->getXOffset());
      obj->setY(j,obj->getY(j)+obj->getYOffset());
      obj->setZ(j,obj->getZ(j)+obj->getZOffset());
    }
    theStream<<*obj;
    delete obj;
  }
  theStream<<"--------------\n";
}

/****************************************************************/
/////////////////////////////////////////////////////////////
//// Functions for Image class
/////////////////////////////////////////////////////////////

Image::Image(long size){
  // need error handling in case size<0 !!!
  if(size<0)
    duchampError("Image(size)","Negative size -- could not define Image");
  else{
    if(size>0){
      this->array = new float[size];
      this->pValue = new float[size];
      this->mask = new short int[size];
    }
    this->numPixels = size;
    this->axisDim = new long[2];
    this->numDim = 2;
  }
}

Image::Image(long *dimensions){
  int size = dimensions[0] * dimensions[1];
  if(size<0)
    duchampError("Image(dimArray)","Negative size -- could not define Image");
  else{
    this->numPixels = size;
    if(size>0){
      this->array = new float[size];
      this->pValue = new float[size];
      this->mask = new short int[size];
    }
    this->numDim=2;
    this->axisDim = new long[2];
    for(int i=0;i<2;i++) this->axisDim[i] = dimensions[i];
    for(int i=0;i<size;i++) this->mask[i] = 0;
  }
}

Image::~Image(){
  if(this->numPixels > 0){
    delete [] this->pValue;
    delete [] this->mask;
  }
}


void Image::saveArray(float *input, long size){
  if(size != this->numPixels)
    duchampError("Image::saveArray",
                 "Input array different size to existing array. Cannot save.");
  else {
    if(this->numPixels>0){
      delete [] array;
      delete [] pValue;
      delete [] mask;
    }
    this->numPixels = size;
    if(this->numPixels>0){
      this->array = new float[size];
      this->pValue = new float[size];
      this->mask = new short int[size];
    }
    for(int i=0;i<size;i++) this->array[i] = input[i];
    for(int i=0;i<size;i++) this->mask[i] = 0;
  }
}

void Image::maskObject(Detection &object)
{
  /**
   * Image::maskObject(Detection &)
   *  A function that increments the mask for each pixel of the detection.
   */
  for(long i=0;i<object.getSize();i++){
    this->setMaskValue(object.getX(i),object.getY(i),1);
  }
}

void Image::extractSpectrum(float *Array, long *dim, long pixel)
{
  /**
   * Image::extractSpectrum(float *, long *, int)
   *  A function to extract a 1-D spectrum from a 3-D array.
   *  The array is assumed to be 3-D with the third dimension the spectral one.
   *  The dimensions of the array are in the dim[] array.
   *  The spectrum extracted is the one lying in the spatial pixel referenced
   *    by the third argument.
   */ 
  float *spec = new float[dim[2]];
  for(int z=0;z<dim[2];z++) spec[z] = Array[z*dim[0]*dim[1] + pixel];
  this->saveArray(spec,dim[2]);
  delete [] spec;
}

void Image::extractSpectrum(Cube &cube, long pixel)
{
  /**
   * Image::extractSpectrum(Cube &, int)
   *  A function to extract a 1-D spectrum from a Cube class
   *  The spectrum extracted is the one lying in the spatial pixel referenced
   *    by the second argument.
   */ 
  long zdim = cube.getDimZ();
  long spatSize = cube.getDimX()*cube.getDimY();
  float *spec = new float[zdim];
  for(int z=0;z<zdim;z++) spec[z] = cube.getPixValue(z*spatSize + pixel);
  this->saveArray(spec,zdim);
  delete [] spec;
}

void Image::extractImage(float *Array, long *dim, long channel)
{
  /**
   * Image::extractImage(float *, long *, int)
   *  A function to extract a 2-D image from a 3-D array.
   *  The array is assumed to be 3-D with the third dimension the spectral one.
   *  The dimensions of the array are in the dim[] array.
   *  The image extracted is the one lying in the channel referenced
   *    by the third argument.
   */ 
  float *image = new float[dim[0]*dim[1]];
  for(int npix=0; npix<dim[0]*dim[1]; npix++){ 
    image[npix] = Array[channel*dim[0]*dim[1] + npix];
  }
  this->saveArray(image,dim[0]*dim[1]);
  delete [] image;
}

void Image::extractImage(Cube &cube, long channel)
{
  /**
   * Image::extractImage(Cube &, int)
   *  A function to extract a 2-D image from Cube class.
   *  The image extracted is the one lying in the channel referenced
   *    by the second argument.
   */ 
  long spatSize = cube.getDimX()*cube.getDimY();
  float *image = new float[spatSize];
  for(int npix=0; npix<spatSize; npix++) 
    image[npix] = cube.getPixValue(channel*spatSize + npix);
  this->saveArray(image,spatSize);
  delete [] image;
}

void Image::removeMW()
{
  /**
   * Image::removeMW()
   *  A function to remove the Milky Way range of channels from a 1-D spectrum.
   *  The array in this Image is assumed to be 1-D, with only the first axisDim
   *    equal to 1.
   *  The values of the MW channels are set to 0, unless they are BLANK.
   */ 
  if(this->par.getFlagMW()){
    int maxMW = this->par.getMaxMW();
    int minMW = this->par.getMinMW();
    if(this->axisDim[1]==1){
      for(int z=0;z<this->axisDim[0];z++){
        if(!this->isBlank(z) && this->par.isInMW(z)) this->array[z]=0.;
      }
    }
  }
}

void Image::findStats(int code)
{
  /**
   *  Image::findStats(int code)
   *    Front-end to function to find the stats (mean/median & sigma/madfm) and
   *     store them in the "mean" and "sigma" members of Image.
   *    The choice of normal(mean & sigma) or robust (median & madfm) is made 
   *      via the code parameter. This is stored as a decimal number, with 0s 
   *      representing normal stats, and 1s representing robust. 
   *      The 10s column is the mean, the 1s column the sigma.
   *      Eg: 00 -- mean&sigma;   01 -- mean&madfm; 
   *          10 -- median&sigma; 11 -- median&madfm
   *    If calculated, the madfm value is corrected to sigma units.
   *    The Image member "cut" is also assigned using the parameter in Image's 
   *     par (needs to be defined first -- also for the blank pixel 
   *          determination).
   */
  float *tempArray = new float[this->numPixels];
  int goodSize=0;
  for(int i=0; i<this->numPixels; i++) 
    if(!this->isBlank(i)) tempArray[goodSize++] = this->array[i];
  float tempMean,tempSigma,tempMedian,tempMADFM;
  if(code != 0) findMedianStats(tempArray,goodSize,tempMedian,tempMADFM);
  if(code != 11) findNormalStats(tempArray,goodSize,tempMean,tempSigma);
  switch(code)
    {
    case 0:
      findNormalStats(tempArray,goodSize,tempMean,tempSigma);
      this->mean = tempMean;
      this->sigma = tempSigma;
      break;
    case 10:
      this->mean  = findMedian(tempArray,goodSize);;
      this->sigma = findStddev(tempArray,goodSize);
      break;
    case 1:
      this->mean  = findMean(tempArray,goodSize);
      this->sigma = findMADFM(tempArray,goodSize)/correctionFactor;
      break;
    case 11:
    default:
      if(code!=11) {
        std::stringstream errmsg;
        errmsg << "Invalid code ("<<code<<") in findStats. Using robust method.\n";
        duchampWarning("Image::findStats", errmsg.str());
      }
      findMedianStats(tempArray,goodSize,tempMedian,tempMADFM);
      this->mean = tempMedian;
      this->sigma = tempMADFM/correctionFactor;
      break;
    }
  this->cutLevel = this->par.getCut();
  delete [] tempArray;
}

/****************************************************************/
/////////////////////////////////////////////////////////////
//// Functions for Cube class
/////////////////////////////////////////////////////////////

Cube::Cube(long size){
  // need error handling in case size<0 !!!
  if(size<0)
    duchampError("Cube(size)","Negative size -- could not define Cube");
  else{
    if(size>0){
      this->array = new float[size];
      this->recon = new float[size];
    }
    this->numPixels = size;
    this->axisDim = new long[2];
    this->numDim = 3;
    this->reconExists = false;
  }
}

Cube::Cube(long *dimensions){
  int size   = dimensions[0] * dimensions[1] * dimensions[2];
  int imsize = dimensions[0] * dimensions[1];
  if((size<0) || (imsize<0) )
    duchampError("Cube(dimArray)","Negative size -- could not define Cube");
  else{
    this->numPixels = size;
    if(size>0){
      this->array      = new float[size];
      this->detectMap  = new short[imsize];
      if(this->par.getFlagATrous())
        this->recon    = new float[size];
      if(this->par.getFlagBaseline())
        this->baseline = new float[size];
    }
    this->numDim  = 3;
    this->axisDim = new long[3];
    for(int i=0;i<3     ;i++) this->axisDim[i]   = dimensions[i];
    for(int i=0;i<imsize;i++) this->detectMap[i] = 0;
  }
}

Cube::~Cube()
{
  delete [] detectMap;
  if(this->par.getFlagATrous())   delete [] recon;
  if(this->par.getFlagBaseline()) delete [] baseline;
  delete [] specMean,specSigma,chanMean,chanSigma;
}

void Cube::initialiseCube(long *dimensions)
{
  /**
   *  Cube::initialiseCube(long *dim)
   *   A function that defines the sizes of all the necessary
   *    arrays in the Cube class.
   *   It also defines the values of the axis dimensions.
   *   This is done with the WCS in the FitsHeader class, so the 
   *    WCS needs to be good and have three axes.
   */ 
  if(!this->head.isWCS()){
    duchampError("Cube::initialiseCube",
 "The WCS is not sufficiently defined. Not able to define Cube.");
  }
  else if(this->head.getWCS()->naxis<3){
    duchampError("Cube::initialiseCube",
 "The WCS does not have three axes defined. Not able to define Cube.");
  }
  else{
    int lng = this->head.getWCS()->lng;
    int lat = this->head.getWCS()->lat;
    int spc = this->head.getWCS()->spec;
    int size   = dimensions[lng] * dimensions[lat] * dimensions[spc];
    int imsize = dimensions[lng] * dimensions[lat];
    if((size<0) || (imsize<0) )
      duchampError("Cube::initialiseCube(dimArray)",
                   "Negative size -- could not define Cube");
    else{
      this->numPixels = size;
      if(size>0){
        this->array      = new float[size];
        this->detectMap  = new short[imsize];
        this->specMean   = new float[imsize];
        this->specSigma  = new float[imsize];
        this->chanMean   = new float[dimensions[spc]];
        this->chanSigma  = new float[dimensions[spc]];
        if(this->par.getFlagATrous())
          this->recon    = new float[size];
        if(this->par.getFlagBaseline())
          this->baseline = new float[size];
      }
      this->numDim  = 3;
      this->axisDim = new long[3];
      this->axisDim[0] = dimensions[lng];
      this->axisDim[1] = dimensions[lat];
      this->axisDim[2] = dimensions[spc];
      for(int i=0;i<imsize;i++) this->detectMap[i] = 0;
    }
  }
}

int Cube::getopts(int argc, char ** argv)
{
  /**
   *   Cube::getopt
   *    A front-end to read in the command-line options,
   *     and then read in the correct parameters to the cube->par
   */

  int returnValue;
  if(argc==1){
    std::cout << ERR_USAGE_MSG;
    returnValue = FAILURE;
  }
  else {
    string file;
    Param *par = new Param;
    char c;
    while( ( c = getopt(argc,argv,"p:f:hv") )!=-1){
      switch(c) {
      case 'p':
        file = optarg;
        if(this->readParam(file)==FAILURE){
          stringstream errmsg;
          errmsg << "Could not open parameter file " << file << ".\n";
          duchampError("Duchamp",errmsg.str());
          returnValue = FAILURE;
        }
        else returnValue = SUCCESS;
        break;
      case 'f':
        file = optarg;
        par->setImageFile(file);
        this->saveParam(*par);
        returnValue = SUCCESS;
        break;
      case 'v':
        std::cout << PROGNAME << " version " << VERSION << std::endl;
        returnValue = FAILURE;
        break;
      case 'h':
      default :
        std::cout << ERR_USAGE_MSG;
        returnValue = FAILURE;
        break;
      }
    }
    delete par;
  }
  return returnValue;
}

void Cube::saveArray(float *input, long size){
  if(size != this->numPixels){
    stringstream errmsg;
    errmsg << "Input array different size to existing array ("
           << size << " cf. " << this->numPixels << "). Cannot save.\n";
    duchampError("Cube::saveArray",errmsg.str());
  }
  else {
    if(this->numPixels>0) delete [] array;
    this->numPixels = size;
    this->array = new float[size];
    for(int i=0;i<size;i++) this->array[i] = input[i];
  }
}

void Cube::saveRecon(float *input, long size){
  if(size != this->numPixels){
    stringstream errmsg;
    errmsg << "Input array different size to existing array ("
           << size << " cf. " << this->numPixels << "). Cannot save.\n";
    duchampError("Cube::saveRecon",errmsg.str());
  }
  else {
    if(this->numPixels>0) delete [] this->recon;
    this->numPixels = size;
    this->recon = new float[size];
    for(int i=0;i<size;i++) this->recon[i] = input[i];
    this->reconExists = true;
  }
}

void Cube::getRecon(float *output){
  // Need check for change in number of pixels!
  long size = this->numPixels;
  for(int i=0;i<size;i++){
    if(this->reconExists) output[i] = this->recon[i];
    else output[i] = 0.;
  }
}

void Cube::removeMW()
{
  if(this->par.getFlagMW()){
    for(int pix=0;pix<this->axisDim[0]*this->axisDim[1];pix++){
      for(int z=0;z<this->axisDim[2];z++){
        int pos = z*this->axisDim[0]*this->axisDim[1] + pix;
        if(!this->isBlank(pos) && this->par.isInMW(z)) this->array[pos]=0.;
      }
    }
  }
}

void Cube::calcObjectWCSparams()
{
  /** 
   * Cube::calcObjectWCSparams()
   *  A function that calculates the WCS parameters for each object in the 
   *  cube's list of detections.
   *  Each object gets an ID number set (just the order in the list), and if 
   *   the WCS is good, the WCS paramters are calculated.
   */
  
  for(int i=0; i<this->objectList.size();i++){
    this->objectList[i].setID(i+1);
    this->objectList[i].calcWCSparams(this->head);
  }  

  
}

void Cube::sortDetections()
{
  /** 
   * Cube::sortDetections()
   *  A front end to the sort-by functions.
   *  If there is a good WCS, the detection list is sorted by velocity.
   *  Otherwise, it is sorted by increasing z-pixel value.
   *  The ID numbers are then re-calculated.
   */
  
  if(this->head.isWCS()) SortByVel(this->objectList);
  else SortByZ(this->objectList);
  for(int i=0; i<this->objectList.size();i++) this->objectList[i].setID(i+1);

}

void Cube::updateDetectMap()
{
  /** 
   * Cube::updateDetectMap()
   *  A function that, for each detected object in the cube's list, increments 
   *   the cube's detection map by the required amount at each pixel.
   */

  for(int obj=0;obj<this->objectList.size();obj++){
    for(int pix=0;pix<this->objectList[obj].getSize();pix++) {
      int spatialPos = this->objectList[obj].getX(pix)+
        this->objectList[obj].getY(pix)*this->axisDim[0];
      this->detectMap[spatialPos]++;
    }
  }
}

void Cube::updateDetectMap(Detection obj)
{
  /** 
   * Cube::updateDetectMap(Detection)
   *  A function that, for the given object, increments the cube's
   *  detection map by the required amount at each pixel.
   */
  for(int pix=0;pix<obj.getSize();pix++) {
    int spatialPos = obj.getX(pix)+obj.getY(pix)*this->axisDim[0];
    this->detectMap[spatialPos]++;
  }
}

void Cube::setCubeStats()
{
  // First set the stats for each spectrum (ie. each spatial pixel)
  long xySize = this->axisDim[0]*this->axisDim[1];
  float *spec = new float[this->axisDim[2]];
  for(int i=0;i<xySize;i++){
    for(int z=0;z<this->axisDim[2];z++){
      //Two cases: i) have reconstructed -- use residuals 
      //          ii) otherwise          -- use original array
      if(this->reconExists) 
        spec[z] = this->array[z*xySize+i] - this->recon[z*xySize+1];
      else
        spec[z] = this->array[z*xySize+i];
    }
    findMedianStats(spec, this->axisDim[2],
                    this->specMean[i], this->specSigma[i]);
  }
  delete spec;
  // Then set the stats for each channel map
  float *im = new float[xySize];
  for(int z=0;z<this->axisDim[2];z++){
    for(int i=0;i<xySize;i++){
      if(this->reconExists) 
        im[i] = this->array[z*xySize+i] - this->recon[z*xySize+1];
      else 
        im[i] = this->array[z*xySize+i];
    }
    findMedianStats(im,this->axisDim[2],this->chanMean[z],this->chanSigma[z]);
    this->chanSigma[z] /= correctionFactor;
  }
  delete im;

}

float Cube::enclosedFlux(Detection obj)
{
  /** 
   *  float Cube::enclosedFlux(Detection obj)
   *   A function to calculate the flux enclosed by the range
   *    of pixels detected in the object obj (not necessarily all
   *    pixels will have been detected).
   */
  obj.calcParams();
  int xsize = obj.getXmax()-obj.getXmin()+1;
  int ysize = obj.getYmax()-obj.getYmin()+1;
  int zsize = obj.getZmax()-obj.getZmin()+1; 
  vector <float> fluxArray(xsize*ysize*zsize,0.);
  for(int x=0;x<xsize;x++){
    for(int y=0;y<ysize;y++){
      for(int z=0;z<zsize;z++){
        fluxArray[x+y*xsize+z*ysize*xsize] = 
          this->getPixValue(x+obj.getXmin(),
                            y+obj.getYmin(),
                            z+obj.getZmin());
        if(this->par.getFlagNegative()) 
          fluxArray[x+y*xsize+z*ysize*xsize] *= -1.;
      }
    }
  }
  float sum = 0.;
  for(int i=0;i<fluxArray.size();i++) 
    if(!this->par.isBlank(fluxArray[i])) sum+=fluxArray[i];
  return sum;
}

void Cube::setupColumns()
{
  /**
   *  Cube::setupColumns()
   *   A front-end to the two setup routines in columns.cc.
   */ 
  for(int i=0; i<this->objectList.size();i++) this->objectList[i].setID(i+1);
  this->fullCols.clear();
  this->fullCols = getFullColSet(this->objectList, this->head);

  this->logCols.clear();
  this->logCols = getLogColSet(this->objectList, this->head);

  int vel,fpeak,fint,pos,xyz,temp;
  vel = fullCols[VEL].getPrecision();
  fpeak = fullCols[FPEAK].getPrecision();
  xyz = fullCols[X].getPrecision();
  if(temp=fullCols[Y].getPrecision() > xyz) xyz = temp;
  if(temp=fullCols[Z].getPrecision() > xyz) xyz = temp;
  if(this->head.isWCS()) fint = fullCols[FINT].getPrecision();
  else fint = fullCols[FTOT].getPrecision();
  pos = fullCols[WRA].getPrecision();
  if(temp=fullCols[WDEC].getPrecision() > pos) pos = temp;
  
  for(int obj=0;obj<this->objectList.size();obj++){
    this->objectList[obj].setVelPrec(vel);
    this->objectList[obj].setFpeakPrec(fpeak);
    this->objectList[obj].setXYZPrec(xyz);
    this->objectList[obj].setPosPrec(pos);
    this->objectList[obj].setFintPrec(fint);
  }

}

bool Cube::objAtEdge(Detection obj)
{
  /**
   *  bool Cube::objAtEdge()
   *   A function to test whether the object obj
   *    lies at the edge of the cube's field --
   *    either at the boundary, or next to BLANKs
   */

  bool atEdge = false;

  int pix = 0;
  while(!atEdge && pix<obj.getSize()){
    // loop over each pixel in the object, until we find an edge pixel.
    Voxel vox = obj.getPixel(pix);
    for(int dx=-1;dx<=1;dx+=2){
      if(((vox.getX()+dx)<0) || ((vox.getX()+dx)>=this->axisDim[0])) 
        atEdge = true;
      else if(this->isBlank(vox.getX()+dx,vox.getY(),vox.getZ())) 
        atEdge = true;
    }
    for(int dy=-1;dy<=1;dy+=2){
      if(((vox.getY()+dy)<0) || ((vox.getY()+dy)>=this->axisDim[1])) 
        atEdge = true;
      else if(this->isBlank(vox.getX(),vox.getY()+dy,vox.getZ())) 
        atEdge = true;
    }
    for(int dz=-1;dz<=1;dz+=2){
      if(((vox.getZ()+dz)<0) || ((vox.getZ()+dz)>=this->axisDim[2])) 
        atEdge = true;
      else if(this->isBlank(vox.getX(),vox.getY(),vox.getZ()+dz)) 
        atEdge = true;
    }
    pix++;
  }

  return atEdge;
}

void Cube::setObjectFlags()
{
  /**
   *  void Cube::setObjectFlags()
   *   A function to set any warning flags for all the detected objects
   *    associated with the cube.
   *   Flags to be looked for:
   *       * Negative enclosed flux (N)
   *       * Object at edge of field (E)
   */

  for(int i=0;i<this->objectList.size();i++){

    if( this->enclosedFlux(this->objectList[i]) < 0. )  
      this->objectList[i].addToFlagText("N");

    if( this->objAtEdge(this->objectList[i]) ) 
      this->objectList[i].addToFlagText("E");

  }

}

void Cube::plotBlankEdges()
{
  if(this->par.drawBlankEdge()){
    int colour;
    cpgqci(&colour);
    cpgsci(MAGENTA);
    drawBlankEdges(this->array,this->axisDim[0],this->axisDim[1],this->par);
    cpgsci(colour);
  }
}