/*==========================================================================

  Portions (c) Copyright 2008 Brigham and Women's Hospital (BWH) All Rights Reserved.

  See Doc/copyright/copyright.txt
  or http://www.slicer.org/copyright/copyright.txt for details.

  Program:   3D Slicer
  Module:    $HeadURL: http://svn.slicer.org/Slicer3/trunk/Modules/OpenIGTLinkIF/vtkRobotRegistration.cxx $
  Date:      $Date: 2009-01-05 13:28:20 -0500 (Mon, 05 Jan 2009) $
  Version:   $Revision: 8267 $

==========================================================================*/

/*
 * ZFrame Fiducial Registration Algorithm
 * The method and code is originally developoed by Simon DiMaio from BWH.
 */

#include "vtkObjectFactory.h"

#include "vtkZFrameRobotToImageRegistration2.h"

#include "vtkMRMLModelNode.h"
#include "vtkMRMLModelDisplayNode.h"
#include "vtkMRMLLinearTransformNode.h"

#include "vtkMRMLVolumeNode.h"
#include "vtkMRMLScalarVolumeNode.h"
#include "vtkMRMLScalarVolumeDisplayNode.h"
#include "vtkMRMLVolumeHeaderlessStorageNode.h"
#include "vtkMRMLVolumeArchetypeStorageNode.h"

#include <string.h>


#define FORCE_SIZEX     256
#define FORCE_SIZEY     256
#define FORCE_FOV       160.0
#define MEPSILON        (1e-10)

vtkStandardNewMacro(vtkZFrameRobotToImageRegistration2);
vtkCxxRevisionMacro(vtkZFrameRobotToImageRegistration2, "$Revision: 8267 $");

//---------------------------------------------------------------------------
vtkZFrameRobotToImageRegistration2::vtkZFrameRobotToImageRegistration2()
{
  SliceRangeLow = -1;
  SliceRangeHigh = -1;
}


//---------------------------------------------------------------------------
vtkZFrameRobotToImageRegistration2::~vtkZFrameRobotToImageRegistration2()
{
}


//---------------------------------------------------------------------------
void vtkZFrameRobotToImageRegistration2::PrintSelf(ostream& os, vtkIndent indent)
{
}


//---------------------------------------------------------------------------
void vtkZFrameRobotToImageRegistration2::SetSliceRange(int param1, int param2)
{
  this->SliceRangeLow = param1;
  this->SliceRangeHigh = param2;
}


//---------------------------------------------------------------------------
int vtkZFrameRobotToImageRegistration2::DoRegistration()
{
  
  if (this->FiducialVolume && this->RobotToImageTransform)
    {
    Init(256, 256);
    //ZFrameRegistration(this->FiducialVolume, this->RobotToImageTransform, 0);
    if (ZFrameRegistration(this->FiducialVolume, this->RobotToImageTransform, this->SliceRangeLow, this->SliceRangeHigh))
      {
      return 1;
      }
    else
      {
      return 0;
      }
    }
  else
    {
    return 0;
    }

}


//----------------------------------------------------------------------------
// Z-frame registration algorithm
//----------------------------------------------------------------------------

#define  RT_CONTROL 1
#define  Z_TRANSFORM_OUT 0
#define  IMAGE_OUT 0
#ifndef M_PI
#define M_PI 3.14159
#endif

//----------------------------------------------------------------------------
void vtkZFrameRobotToImageRegistration2::Init(int xsize, int ysize)
{
  int i,j,m,n;

  // At present, the image dimensions are fixed to 256x256.
  // In the future, this should be flexible.
  // FORCE xsize and ysize for now.
  imgxsize = xsize = 256;
  imgysize = ysize = 256;

  // Define an 11x11 correlation kernel for fiducial detection.
  //Real kernel[11][11]={{0,0,0.0,0,0.0,0,0.0,0.0,0.0,0,0},
  //                     {0,0,0.0,0,0.0,0,0.0,0.0,0.0,0,0},
  //                     {0,0,0.0,0,0.5,0.5,0.5,0.0,0,0,0},
  //                     {0,0,0.0,1,1.0,1.0,1.0,1,0.0,0,0},
  //                     {0,0,0.5,1,1.0,1.0,1.0,1,0.5,0,0},
  //                     {0,0,0.5,1,1.0,1.0,1.0,1,0.5,0,0},
  //                     {0,0,0.5,1,1.0,1.0,1.0,1,0.5,0,0},
  //                     {0,0,0.0,1,1.0,1.0,1.0,1,0.0,0,0},
  //                     {0,0,0.0,0,0.5,0.5,0.5,0.0,0,0,0},
  //                     {0,0,0.0,0,0.0,0,0.0,0.0,0.0,0,0},
  //                     {0,0,0.0,0,0.0,0,0.0,0.0,0.0,0,0}};

  Real kernel[11][11]={{0.0, 0.0, 0.0, 0.0, 0.5, 0.5, 0.5, 0.0, 0.0, 0.0, 0.0},
                       {0.0, 0.0, 0.5, 1.0, 1.0, 1.0, 1.0, 1.0, 0.5, 0.0, 0.0},
                       {0.0, 0.5, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.5, 0.0},
                       {0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0},
                       {0.5, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.5},
                       {0.5, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.5},
                       {0.5, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.5},
                       {0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0},
                       {0.0, 0.5, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.5, 0.0},
                       {0.0, 0.0, 0.5, 1.0, 1.0, 1.0, 1.0, 1.0, 0.5, 0.0, 0.0},
                       {0.0, 0.0, 0.0, 0.0, 0.5, 0.5, 0.5, 0.0, 0.0, 0.0, 0.0}};


  // Create a mask image and initialize elements to zero.
  // The Matrix class is implemented in the newmat library:
  // see: http://www.robertnz.net/
  /*
  this->MaskImage = vtkImageData::New();
  this->MaskImage->SetDimensions(xsize, ysize, 1);
  this->MaskImage->SetExtent(0, xsize-1, 0, ysize-1, 0, 0 );
  this->MaskImage->SetSpacing(1.0, 1.0, 1.0);
  this->MaskImage->SetOrigin(0.0, 0.0, 0.0);
  this->MaskImage->SetNumberOfScalarComponents(1);
  this->MaskImage->SetScalarTypeToFloat();
  this->MaskImage->AllocateScalars();
  float* dest = (float*) this->MaskImage->GetScalarPointer();
  if (dest)
    {
    float* end = dest + xsize*ysize*1;
    float* p = dest;
    while (p < end)
      {
      *p = 0.0;
      p++;
      }
    }
  */
  MaskImage.ReSize(xsize,ysize);
  for(i=0; i<xsize; i++)
    for(j=0; j<ysize; j++)
        MaskImage.element(i,j) = 0;

  // Copy the correlation kernel to the centre of the mask image.
  for(i=((xsize/2)-5),m=0; i<=((xsize/2)+5); i++,m++)
    for(j=((ysize/2)-5),n=0; j<=((ysize/2)+5); j++,n++)
    {
        MaskImage.element(i,j) = kernel[m][n];
    }

  // Correlation will be computed using spatial convolution, and hence 
  // multiplication in the frequency domain. This dramatically accelerates 
  // fiducial detection. Transform mask to frequency domain; this only
  // has to be done once.
  // Before transforming the mask to the spatial frequency domain, need to
  // create an empty imaginary component, since the mask is real-valued.
  zeroimag.ReSize(xsize,ysize);
  for(i=0; i<xsize; i++)
    for(j=0; j<ysize; j++)
        zeroimag.element(i,j) = 0;

  // The Radix-2 FFT algorithm is implemented in the newmat library:
  // see: http://www.robertnz.net/
  FFT2(MaskImage, zeroimag, MFreal, MFimag);

  // Conjugate and normalize the mask.
  MFimag *= -1;
  Real maxabsolute = ComplexMax(MFreal, MFimag);
  MFreal *= (1/maxabsolute);
  MFimag *= (1/maxabsolute);

  // MFreal and MFimag now contain the real and imaginary matrix elements for
  // the frequency domain representation of the correlation mask.


}

/*----------------------------------------------------------------------------*/

/**
 * Method called by the SPL-OpenTracker child node when an event occurs.
 * @param event The event value passed.
 * @param generator The node that generated the event.
 */
int vtkZFrameRobotToImageRegistration2::ZFrameRegistration(vtkMRMLScalarVolumeNode* volumeNode,
                                                          vtkMRMLLinearTransformNode* transformNode, int slindex_s, int slindex_e)
{
  int           xsize;
  int           ysize;
  int           zsize;
  //Image         image_attrib;
  int           i,j;

//simond debug frame delay
  
  // Get the image size attributes from the event.
  /*
  xsize=event.getAttribute(string("xsize"),0);
  ysize=event.getAttribute(string("ysize"),0);
  */
  vtkImageData* image = volumeNode->GetImageData();
  int dimensions[3];
  image->GetDimensions(dimensions);
  xsize = dimensions[0];
  ysize = dimensions[1];
  zsize = dimensions[2];
  
  // Get image position and orientation
  vtkMatrix4x4* rtimgTransform = vtkMatrix4x4::New(); 
  Matrix4x4 matrix;
  volumeNode->GetIJKToRASMatrix(rtimgTransform);

  float tx = rtimgTransform->GetElement(0, 0);
  float ty = rtimgTransform->GetElement(1, 0);
  float tz = rtimgTransform->GetElement(2, 0);
  float sx = rtimgTransform->GetElement(0, 1);
  float sy = rtimgTransform->GetElement(1, 1);
  float sz = rtimgTransform->GetElement(2, 1);
  float nx = rtimgTransform->GetElement(0, 2);
  float ny = rtimgTransform->GetElement(1, 2);
  float nz = rtimgTransform->GetElement(2, 2);
  float px = rtimgTransform->GetElement(0, 3);
  float py = rtimgTransform->GetElement(1, 3);
  float pz = rtimgTransform->GetElement(2, 3);

  // normalize
  float psi = sqrt(tx*tx + ty*ty + tz*tz);
  float psj = sqrt(sx*sx + sy*sy + sz*sz);
  float psk = sqrt(nx*nx + ny*ny + nz*nz);
  float ntx = tx / psi;
  float nty = ty / psi;
  float ntz = tz / psi;
  float nsx = sx / psj;
  float nsy = sy / psj;
  float nsz = sz / psj;
  float nnx = nx / psk;
  float nny = ny / psk;
  float nnz = nz / psk;


  // Here we calculate 'average' quaternion from registration results from
  // multiple slices. The average quaternion here is defined as the eigenvector
  // corresponding to the largest eigenvalue of the sample moment of inertia
  // matrix given as:
  //            ____
  //         1  \   |
  //    T = ---  |     qi qi'
  //         n  /___|
  //              i

  int n = 0;
  SymmetricMatrix T;
  T.ReSize(4);
  float P[3]={0,0,0};
  for (i = 0; i < 4; i ++)
    for (j = 0; j < 4; j ++)
      T.element(i, j) = 0.0;

  float position[3];
  float quaternion[4];

  for (int slindex = slindex_s; slindex < slindex_e; slindex ++)
    {
    // Shift the center
    // NOTE: The center of the image should be shifted due to different
    // definitions of image origin between VTK (Slicer) and OpenIGTLink;
    // OpenIGTLink image has its origin at the center, while VTK image
    // has one at the corner.

    float hfovi = psi * (dimensions[0]-1) / 2.0;
    float hfovj = psj * (dimensions[1]-1) / 2.0;
    //float hfovk = psk * (dimensions[2]-1) / 2.0;
    
    // For slice (k) direction, we calculate slice offset based on
    // the slice index.
    float offsetk = psk * slindex;
    
    float cx = ntx * hfovi + nsx * hfovj + nnx * offsetk;
    float cy = nty * hfovi + nsy * hfovj + nny * offsetk;
    float cz = ntz * hfovi + nsz * hfovj + nnz * offsetk;
    
    matrix[0][0] = -ntx;
    matrix[1][0] = -nty;
    matrix[2][0] = -ntz;
    matrix[0][1] = -nsx;
    matrix[1][1] = -nsy;
    matrix[2][1] = -nsz;
    matrix[0][2] = nnx;
    matrix[1][2] = nny;
    matrix[2][2] = nnz;
    matrix[0][3] = px + cx;
    matrix[1][3] = py + cy;
    matrix[2][3] = pz + cz;
    
    MatrixToQuaternion(matrix, quaternion);
    position[0] = matrix[0][3];
    position[1] = matrix[1][3];
    position[2] = matrix[2][3];
    
    std::cerr << "=== Image position ===" << std::endl;
    std::cerr << "x = " << position[0] << std::endl; 
    std::cerr << "y = " << position[1] << std::endl;
    std::cerr << "z = " << position[2] << std::endl;
    
    // Get a pointer to the image array.
    image->SetScalarTypeToShort();
    image->Modified();
    InputImage=(short*)image->GetScalarPointer();
    if (slindex >= 0 && slindex < zsize)
      {
      InputImage = &InputImage[xsize*ysize*slindex];
      }
    else
      {
      return 0;
      }
    
    // Transfer image to a Matrix.
    SourceImage.ReSize(xsize,ysize);

    for(i=0; i<xsize; i++)
      for(j=0; j<ysize; j++)
        SourceImage.element(i,j) = InputImage[i*ysize+j];
    
    // if Z-frame position is determined from the slice
    if (ZFrameRegistrationQuaternion(position, quaternion, SourceImage, xsize, ysize))
      {
      P[0] += position[0];
      P[1] += position[1];
      P[2] += position[2];
      
      std::cerr << "position = ("
                << position[0] << ", "
                << position[1] << ", "
                << position[2] << ")" << std::endl;
      
      // Note that T is defined as SymmetricMatrix class 
      // and upper triangular part is updated.
      T.element(0, 0) = T.element(0, 0) + quaternion[0]*quaternion[0];
      T.element(0, 1) = T.element(0, 1) + quaternion[0]*quaternion[1];
      T.element(0, 2) = T.element(0, 2) + quaternion[0]*quaternion[2];
      T.element(0, 3) = T.element(0, 3) + quaternion[0]*quaternion[3];
      T.element(1, 1) = T.element(1, 1) + quaternion[1]*quaternion[1];
      T.element(1, 2) = T.element(1, 2) + quaternion[1]*quaternion[2];
      T.element(1, 3) = T.element(1, 3) + quaternion[1]*quaternion[3];
      T.element(2, 2) = T.element(2, 2) + quaternion[2]*quaternion[2];
      T.element(2, 3) = T.element(2, 3) + quaternion[2]*quaternion[3];
      T.element(3, 3) = T.element(3, 3) + quaternion[3]*quaternion[3];
      n ++;

      std::cerr << "quaternion = ("
                << quaternion[0] << ", "
                << quaternion[1] << ", "
                << quaternion[2] << ", "
                << quaternion[3] << ")" << std::endl;
      }
    }

  if (n <= 0)
    return 0;

  float fn = (float) n;
  for (i = 0; i < 3; i ++)
    {
    P[i] /= fn;
    }

  T.element(0, 0) = T.element(0, 0) / fn;
  T.element(0, 1) = T.element(0, 1) / fn;
  T.element(0, 2) = T.element(0, 2) / fn;
  T.element(0, 3) = T.element(0, 3) / fn;

  T.element(1, 1) = T.element(1, 1) / fn;
  T.element(1, 2) = T.element(1, 2) / fn;
  T.element(1, 3) = T.element(1, 3) / fn;

  T.element(2, 2) = T.element(2, 2) / fn;
  T.element(2, 3) = T.element(2, 3) / fn;

  T.element(3, 3) = T.element(3, 3) / fn;

  
  // calculate eigenvalues of T matrix
  DiagonalMatrix D;
  Matrix V;
  D.ReSize(4);
  V.ReSize(4, 4);
  eigenvalues(T, D, V);

  for (i = 0; i < 4; i ++)
    {
    std::cerr << "T[" << i << ", 0] = ("
              <<  T.element(i, 0) << ", "
              <<  T.element(i, 1) << ", "
              <<  T.element(i, 2) << ", "
              <<  T.element(i, 3) << ")" << std::endl;
    }

  std::cerr << "D[" << i << ", 0] = ("
            <<  D.element(0) << ", "
            <<  D.element(1) << ", "
            <<  D.element(2) << ", "
            <<  D.element(3) << ")" << std::endl;

  for (i = 0; i < 4; i ++)
    {
    std::cerr << "V[" << i << ", 0] = ("
              <<  V.element(i, 0) << ", "
              <<  V.element(i, 1) << ", "
              <<  V.element(i, 2) << ", "
              <<  V.element(i, 3) << ")" << std::endl;
    }

  // find the maximum eigen value
  int maxi = 0;
  float maxv = D.element(0);
  for (i = 1; i < 4; i ++)
    {
    if (D.element(i) > maxv)
      {
      maxi = i;
      }
    }

  // Substitute 'average' position and quaternion.
  position[0] = P[0];
  position[1] = P[1];
  position[2] = P[2];
  quaternion[0] = V.element(0, maxi);
  quaternion[1] = V.element(1, maxi);
  quaternion[2] = V.element(2, maxi);
  quaternion[3] = V.element(3, maxi);

  std::cerr << "average position = ("
            << position[0] << ", "
            << position[1] << ", "
            << position[2] << ")" << std::endl;

  std::cerr << "average quaternion = ("
            << quaternion[0] << ", "
            << quaternion[1] << ", "
            << quaternion[2] << ", "
            << quaternion[3] << ")" << std::endl;
  
  QuaternionToMatrix(quaternion, matrix);
  matrix[0][3] = position[0];
  matrix[1][3] = position[1];
  matrix[2][3] = position[2];

  std::cerr << "Result matrix:" << std::endl;
  PrintMatrix(matrix);

  vtkMatrix4x4* zMatrix = vtkMatrix4x4::New();
  zMatrix->Identity();
  /*
  zMatrix->SetElement(0, 0, -matrix[0][0]);
  zMatrix->SetElement(1, 0, -matrix[1][0]);
  zMatrix->SetElement(2, 0, -matrix[2][0]);
  zMatrix->SetElement(0, 1, matrix[0][1]);
  zMatrix->SetElement(1, 1, matrix[1][1]);
  zMatrix->SetElement(2, 1, matrix[2][1]);
  zMatrix->SetElement(0, 2, -matrix[0][2]);
  zMatrix->SetElement(1, 2, -matrix[1][2]);
  zMatrix->SetElement(2, 2, -matrix[2][2]);
  zMatrix->SetElement(0, 3, matrix[0][3]);
  zMatrix->SetElement(1, 3, matrix[1][3]);
  zMatrix->SetElement(2, 3, matrix[2][3]);
  */
  zMatrix->SetElement(0, 0, matrix[0][0]);
  zMatrix->SetElement(1, 0, matrix[1][0]);
  zMatrix->SetElement(2, 0, matrix[2][0]);
  zMatrix->SetElement(0, 1, matrix[0][1]);
  zMatrix->SetElement(1, 1, matrix[1][1]);
  zMatrix->SetElement(2, 1, matrix[2][1]);
  zMatrix->SetElement(0, 2, matrix[0][2]);
  zMatrix->SetElement(1, 2, matrix[1][2]);
  zMatrix->SetElement(2, 2, matrix[2][2]);
  zMatrix->SetElement(0, 3, matrix[0][3]);
  zMatrix->SetElement(1, 3, matrix[1][3]);
  zMatrix->SetElement(2, 3, matrix[2][3]);

  if (transformNode != NULL)
    {
    vtkMatrix4x4* transformToParent = transformNode->GetMatrixTransformToParent();
    transformToParent->DeepCopy(zMatrix);
    zMatrix->Delete();
    transformNode->Modified();
    return 1;
    }
  else
    {
    zMatrix->Delete();
    return 0;
    }

  

}


int vtkZFrameRobotToImageRegistration2::ZFrameRegistrationQuaternion(float position[3], float quaternion[4],
                                                                    Matrix& srcImage, int xsize, int ysize)
{

  Column3Vector Zposition;
  Quaternion    Zorientation;
  static Column3Vector Iposition;
  static Quaternion Iorientation;
  int           Zcoordinates[7][2];
  float         tZcoordinates[7][2];
  bool          frame_lock;
  float         pixel_size=FORCE_FOV/FORCE_SIZEX;
  float         tmpCoord;

  // Get current position and orientation of the imaging plane.
  // SPL OpenTracker events always contain Position and Orientation attributes.
  Iposition.setX( position[0] );
  Iposition.setY( position[1] );
  Iposition.setZ( position[2] );
  Iorientation.setX( quaternion[0] );
  Iorientation.setY( quaternion[1] );
  Iorientation.setZ( quaternion[2] );
  Iorientation.setW( quaternion[3] );

  /*
  FILE* fp;
  fp = fopen("dump_before.txt", "w");
  for(i=0; i<xsize; i++)
    for(j=0; j<ysize; j++)
      fprintf(fp, "%.2f\n", SourceImage.element(i,j));
  fclose(fp);
  */


  // Find the 7 Z-frame fiducial intercept artifacts in the image.
  std::cerr << "ZTrackerTransform - Searching fiducials...\n" << std::endl;
  if(LocateFiducials(SourceImage, xsize, ysize, Zcoordinates, tZcoordinates) == false)
  {
  std::cerr << "ZTrackerTransform::onEventGenerated - Ficudials not detected. No frame lock on this image.\n" << std::endl;
  frame_lock = false;
  return 0;
  }
  else frame_lock = true;

  // Check that the fiducial geometry makes sense.
  std::cerr << "ZTrackerTransform - Checking the fiducial geometries...\n" << std::endl;
  if(CheckFiducialGeometry(Zcoordinates, xsize, ysize) == true)
    frame_lock = true;
  else 
    {
    frame_lock = false;
    std::cerr << "ZTrackerTransform::onEventGenerated - Bad fiducial geometry. No frame lock on this image." << std::endl;
    return 0;
    }

  // Compute the pose of the Z-frame only if we have a lock on the fiducial points.
  if(frame_lock)
  {
  std::cerr << "ZTrackerTransform::onEventGenerated - frame lock." << std::endl;
    
    // Transform pixel coordinates into spatial coordinates.
    // 1) Put the image origin at the centre of the image,
    // 2) Re-align axes according to the IJK convention,
    // 3) Scale by pixel size.
    for(int i=0; i<7; i++)
    {
      // Move origin to centre of image and exchange axes for correct 
      // image frame orientation.
      tmpCoord = tZcoordinates[i][1];
      tZcoordinates[i][1] = (float)(tZcoordinates[i][0]) - (float)(xsize/2);
      tZcoordinates[i][0] = tmpCoord - (float)(ysize/2);

      // Flip the x-axis for IJK coordinates. 
      tZcoordinates[i][0] *= -1.0;
      
      // Flip the y-axis for IJK coordinates. 
      tZcoordinates[i][1] *= -1.0;

      // Scale coordinates by pixel size
      tZcoordinates[i][0] *= pixel_size;
      tZcoordinates[i][1] *= pixel_size;
    }

    // Compute relative pose between the Z-frame and the current image.
    if(LocalizeFrame(tZcoordinates, Zposition, Zorientation) == false)
    {
    frame_lock = 0;
    std::cerr << "ZTrackerTransform::onEventGenerated - Could not localize the frame. Skipping this one." << std::endl;
    return 0;
    }
  }

  if(frame_lock)
  {
    // Compute the new image position and orientation that will be centred to
    // the Z-frame.
    Update_Scan_Plane(Iposition, Iorientation, Zposition, Zorientation);
  }
  
  // Construct a new event to pass on to the child node.

#ifdef DEBUG_ZFRAME
  //simond Debug Image Output
  short output_image[FORCE_SIZEX*FORCE_SIZEY];
  if(frame_lock)
  {
    static int counter=7;
    for(i=0; i<counter; i++)
    {
      SourceImage.element((int)(Zcoordinates[i][0]),(int)(Zcoordinates[i][1])) = 0.0;
    }

    for(i=0; i<FORCE_SIZEX; i++)
      for(j=0; j<FORCE_SIZEY; j++)
      {
        output_image[i*FORCE_SIZEX+j] = (short)(SourceImage.element(i,j)*1);
      }
    //if(++counter >7) counter=1;
  }
#endif
//end simond

  position[0] = Iposition.getX();
  position[1] = Iposition.getY();
  position[2] = Iposition.getZ();
  quaternion[0] = Iorientation.getX();
  quaternion[1] = Iorientation.getY();
  quaternion[2] = Iorientation.getZ();
  quaternion[3] = Iorientation.getW();

  return 1;
}





/*----------------------------------------------------------------------------*/

/**
 * The Z-frame contains seven line fiducials arranged in such a manner that
 * its position and orientation in the MRI scanner can be determined from a
 * single image. This method detects the seven line fiducial intercepts.
 * @param SourceImage An image matrix containing the latest image.
 * @param xsize The width of the image in pixels.
 * @param ysize The height of the image in pixels.
 * @param Zcoordinates[][] The resulting list of seven fiducial coordinates.

*/
bool vtkZFrameRobotToImageRegistration2::LocateFiducials(Matrix &SourceImage, int xsize, 
                  int ysize, int Zcoordinates[7][2], float tZcoordinates[7][2])
{
  int    i,j;
  Real   peakval, offpeak1, offpeak2, offpeak3, offpeak4;

  // Transform the MR image to the frequency domain (k-space).
  FFT2(SourceImage, zeroimag, IFreal, IFimag);

  /*
  FILE* fp;
  fp = fopen("dump.txt", "w");
  for(i=0; i<xsize; i++)
    for(j=0; j<ysize; j++)
      fprintf(fp, "%.2f\n", SourceImage.element(i,j));
  fclose(fp);
  */


  // Normalize the image.
  Real maxabsolute = ComplexMax(IFreal,IFimag);
  // RISK: maxabsolute may be close to zero.
  if(maxabsolute<MEPSILON)
  {
  std::cerr << "ZTrackerTransform::LocateFiducials - divide by zero." << std::endl;
  } else
    {
      IFreal *= (1/maxabsolute);
      IFimag *= (1/maxabsolute);
    }

  // Pointwise multiply the Image and the Mask in k-space.
  PFreal.ReSize(xsize,ysize);
  PFimag.ReSize(xsize,ysize);
  for(i=0; i<xsize; i++)
    for(j=0; j<ysize; j++)
  {
    PFreal.element(i,j) = IFreal.element(i,j)*MFreal.element(i,j) -
                          IFimag.element(i,j)*MFimag.element(i,j);
    PFimag.element(i,j) = IFreal.element(i,j)*MFimag.element(i,j) +
                          IFimag.element(i,j)*MFreal.element(i,j);   
  }

  // Invert the product of the two k-space images back to spatial domain.
  // Regions of high correlation between the mask the image will appear
  // as sharp peaks in the inverted image.
  PIreal.ReSize(xsize,ysize);
  PIimag.ReSize(xsize,ysize);
  FFT2I(PFreal, PFimag, PIreal, PIimag);

  // FFTSHIFT: exchange diagonally-opposite image quadrants.
  Real swaptemp;
  for(i=0; i<(xsize/2); i++)
    for(j=0; j<ysize/2; j++)
    {
      // Exchange first and fourth quadrants.
      swaptemp = PIreal.element(i,j);
      PIreal.element(i,j) = PIreal.element(i+xsize/2,j+ysize/2);
      PIreal.element(i+xsize/2,j+ysize/2) = swaptemp; 

      // Exchange second and third quadrants.
      swaptemp = PIreal.element(i+xsize/2,j);
      PIreal.element(i+xsize/2,j) = PIreal.element(i,j+ysize/2);
      PIreal.element(i,j+ysize/2) = swaptemp; 
  }

  // Normalize result.
  maxabsolute = RealMax(PIreal);
  // RISK: maxabsolute may be close to zero.
  if(maxabsolute<MEPSILON)
  {
  std::cerr << "ZTrackerTransform::LocateFiducials - divide by zero." << std::endl;
  return(false);
  } else
    {
      PIreal *= (1/maxabsolute);
    }

  // Find the top 7 peak image values.
  int rstart, rstop, cstart, cstop;
  int peakcount=0;
  for(i=0; i<7; i++)
  {
    // Find the next peak value.
    peakval = FindMax(PIreal, Zcoordinates[i][0], Zcoordinates[i][1]); 

    // Define a block neighbourhood around the peak value.
    rstart = Zcoordinates[i][0]-10;
    if(rstart<0) 
    {
      rstart=0;
    }
    rstop = Zcoordinates[i][0]+10;
    if(rstop>=xsize) 
    {
      rstop=xsize-1;
    }
    cstart = Zcoordinates[i][1]-10;
    if(cstart<0) 
    {
      cstart=0;
    }
    cstop = Zcoordinates[i][1]+10;
    if(cstop>=ysize) 
    {
      cstop = ysize-1;
    }

    // Check that this is a local maximum.
    if(peakval<MEPSILON)
    {
    std::cerr << "vtkZFrameRobotToImageRegistration2::OrderFidPoints - peak value is zero." << std::endl;
      return(false);
    }
    else
      {
        offpeak1 = (peakval - PIreal.element(rstart,cstart))/peakval;
        offpeak2 = (peakval - PIreal.element(rstart,cstop))/peakval;
        offpeak3 = (peakval - PIreal.element(rstop,cstart))/peakval;
        offpeak4 = (peakval - PIreal.element(rstop,cstop))/peakval;
        if(offpeak1<0.3 || offpeak2<0.3 || offpeak3<0.3 || offpeak4<0.3)
        {
           // Ignore coordinate if the offpeak value is within 30% of the peak.
           i--;
           std::cerr << "vtkZFrameRobotToImageRegistration2::LocateFiducials - Bad Peak." << std::endl;
           if(++peakcount > 10)
             return(false);
        }
      }

    if (i >= 0)
      {
      // Find the subpixel coordinates of the peak.
      FindSubPixelPeak(&(Zcoordinates[i][0]), &(tZcoordinates[i][0]), 
                       PIreal.element(Zcoordinates[i][0],Zcoordinates[i][1]),
                       PIreal.element(Zcoordinates[i][0]-1,Zcoordinates[i][1]),
                       PIreal.element(Zcoordinates[i][0]+1,Zcoordinates[i][1]),
                       PIreal.element(Zcoordinates[i][0],Zcoordinates[i][1]-1),
                       PIreal.element(Zcoordinates[i][0],Zcoordinates[i][1]+1));
      }
    
    // Eliminate this peak and search for the next.
    for(int m=rstart; m<=rstop; m++)
      for(int n=cstart; n<=cstop; n++)
        PIreal.element(m,n) = 0.0;
  }

  //=== Determine the correct ordering of the detected fiducial points ===
  // Find the centre of the pattern
  float pmid[2];
  FindFidCentre(tZcoordinates, pmid[0], pmid[1]);

  // Find the corner points
  FindFidCorners(tZcoordinates, pmid);

  // Sequentially order all points
  OrderFidPoints(tZcoordinates, pmid[0], pmid[1]);

  // Update Zcoordinates
  for(i=0; i<7; i++)
  {
    Zcoordinates[i][0] = (int)(tZcoordinates[i][0]);
    Zcoordinates[i][1] = (int)(tZcoordinates[i][1]);
  }

  return(true);
}

/*----------------------------------------------------------------------------*/

/**
 * Find the subpixel coordinates of the peak. This implementation approximates
 * the location of the peak by fitting a parabola in each axis. This should be
 * revised to fit a paraboloid in 3D.
 * @param Zcoordinate[] A fiducial coordinate.
 * @param tZcoordinate[] A fiducial coordinate computed to sub-pixel accuracy. 
 */

void vtkZFrameRobotToImageRegistration2::FindSubPixelPeak(int Zcoordinate[2], 
                                         float tZcoordinate[2],
                                         Real Y0, Real Yx1, Real Yx2, Real Yy1, Real Yy2)
{
  float Xshift, Yshift;

  Xshift = (0.5*((float)Yx1 - (float)Yx2)) / 
           ((float)Yx1 + (float)Yx2 - 2.0*(float)Y0);

  Yshift = (0.5*((float)Yy1 - (float)Yy2)) / 
           ((float)Yy1 + (float)Yy2 - 2.0*(float)Y0);

  if(fabs(Xshift)>1.0 || fabs(Yshift)>1.0)
  {
  std::cerr << "vtkZFrameRobotToImageRegistration2::FindSubPixelPeak - subpixel peak out of range." << std::endl;
    tZcoordinate[0] = (float)(Zcoordinate[0]);
    tZcoordinate[1] = (float)(Zcoordinate[1]);
  }
  else
    {   
      tZcoordinate[0] = (float)(Zcoordinate[0]) + Xshift;
      tZcoordinate[1] = (float)(Zcoordinate[1]) + Yshift;
    }
}

/*----------------------------------------------------------------------------*/

/**
 * Check the geometry of the fiducial pattern to be sure that it is valid.
 * @param Zcoordinates[][] The list of seven fiducial coordinates.
 * @param xsize The width of the image in pixels.
 * @param ysize The height of the image in pixels.
 * @return true if the point geometry is ok, else false.
 */
bool vtkZFrameRobotToImageRegistration2::CheckFiducialGeometry(int Zcoordinates[7][2], 
                                              int xsize, int ysize)
{
  Column2Vector  P1, P3, P5, P7;
  Column2Vector  D71, D53, D13, D75;
  int            i;
  float          dotp;

  // First check that the coordinates are in range.
  for(i=0; i<7; i++)
  {
    if(Zcoordinates[i][0]<0 || Zcoordinates[i][0]>=ysize ||
       Zcoordinates[i][1]<0 || Zcoordinates[i][1]>=xsize)
    {
    std::cerr << "vtkZFrameRobotToImageRegistration2::onEventGenerated - fiducial coordinates out of range. No frame lock on this image." << std::endl;
      return(false);
    }
  }

  // Check that corner points form a parallelogram.
  P1.setvalues(Zcoordinates[0][0], Zcoordinates[0][1]);
  P3.setvalues(Zcoordinates[2][0], Zcoordinates[2][1]);
  P5.setvalues(Zcoordinates[4][0], Zcoordinates[4][1]);
  P7.setvalues(Zcoordinates[6][0], Zcoordinates[6][1]);
  D71 = P7 - P1;
  D53 = P5 - P3;
  D13 = P1 - P3;
  D75 = P7 - P5;
  D71.normalize();
  D53.normalize();
  D13.normalize();
  D75.normalize();
  // Check that opposite edges are within 10 degrees of parallel. 
  dotp = D71.getX()*D53.getX() + D71.getY()*D53.getY();
  if(dotp<0) dotp *= -1.0;
  if(dotp < cos(5.0*M_PI/180.0)) return(false);
  dotp = D13.getX()*D75.getX() + D13.getY()*D75.getY();
  if(dotp<0) dotp *= -1.0;
  if(dotp < cos(5.0*M_PI/180.0)) return(false);
   
  return(true);
}


/*----------------------------------------------------------------------------*/

/**
 * Find the centre of the fiducial pattern. A cross-sectional image will
 * intercept each of the Z-frame's seven line fiducials. Once these seven
 * intercepts are detected, this method computes the centre of the region
 * bounded by these points.
 * @param points[][] Image coordinates of the seven fiducial points.
 * @param rmid Row coordinate at centre.
 * @param cmid Column coordinate at centre.
 */
void vtkZFrameRobotToImageRegistration2::FindFidCentre(float points[7][2], float &rmid, float &cmid)
{
  int    i;
  float  minrow=0.0, maxrow=0.0, mincol=0.0, maxcol=0.0;

  // Find the bounding rectangle.
  for(i=0; i<7; i++)
  {
    // find minimum row coordinate
    if(points[i][0]<minrow || i==0)
      minrow = points[i][0];

    // find maximum row coordinate
    if(points[i][0]>maxrow || i==0)
      maxrow = points[i][0];

    // find minimum column coordinate
    if(points[i][1]<mincol || i==0)
      mincol = points[i][1];

    // find maximum column coordinate
    if(points[i][1]>maxcol || i==0)
      maxcol = points[i][1];
  }

  // Centre of bounding rectangle.
  rmid = (minrow + maxrow)/2.0;
  cmid = (mincol + maxcol)/2.0;
} 

/*----------------------------------------------------------------------------*/

/**
 * This method identifies the four corner fiducials, based on known geometry 
 * of the Z-frame.
 * @param points[][] The fiducial coordinates detected in the previous step. 
 * @param pmid The centre of the rectangular region bounded by the fiducial 
 *             points.
 */
void vtkZFrameRobotToImageRegistration2::FindFidCorners(float points[7][2], float *pmid)
{
  int    i;
  float  itemp[2];
  float  distances[7], dtemp;
  bool   swapped;

  // Compute distances between each fiducial and the midpoint.
  for(i=0; i<7; i++)
  {
    distances[i] = CoordDistance(pmid, &(points[i][0]));
  }

  // Sort distances in descending order. The four corner points will be 
  // furthest away from the centre and will be sorted to the top of the
  // coordinate list.
  swapped = true;
  // Loop until there are no more exchanges (Bubble Sort)
  while(swapped)
  {
    swapped = false;
    for(i=0; i<6; i++)
        if(distances[i]<distances[i+1])
        {
          // Swap distances.
          dtemp = distances[i];
          distances[i] = distances[i+1];
          distances[i+1] = dtemp;
  
          // Swap corresponding coordinates in the fiducial list.
          itemp[0] = points[i][0];
          itemp[1] = points[i][1];
          points[i][0] = points[i+1][0];
          points[i][1] = points[i+1][1];
          points[i+1][0] = itemp[0];
          points[i+1][1] = itemp[1];
  
          swapped = true;
        }
  }
  
  // Choose the order of the corners, based on their separation distance.
  // First find the closest point to first corner in the list. 
  // This must be an adjacent corner.
  float pdist1 = CoordDistance(&(points[0][0]), &(points[1][0]));
  float pdist2 = CoordDistance(&(points[0][0]), &(points[2][0]));
  if(pdist1>pdist2)
  {
    itemp[0] = points[1][0];
    itemp[1] = points[1][1];
    points[1][0] = points[2][0];
    points[1][1] = points[2][1];
    points[2][0] = itemp[0];
    points[2][1] = itemp[1];
  }
  // Now find closest point (of third or fourth) to second corner in list.
  // This will become the third corner in the sequence.
  pdist1 = CoordDistance(&(points[1][0]), &(points[2][0]));
  pdist2 = CoordDistance(&(points[1][0]), &(points[3][0]));
  if(pdist1>pdist2)
  {
    itemp[0] = points[2][0];
    itemp[1] = points[2][1];
    points[2][0] = points[3][0];
    points[2][1] = points[3][1];
    points[3][0] = itemp[0];
    points[3][1] = itemp[1];
  }
}

/*----------------------------------------------------------------------------*/

/**
 * Find the distance between two image points.
 * TO DO: this should be moved to ZLinAlg.
 * @param p1 First image point coordinates.
 * @param p2 Second image point coordinates.
 * @return Distance between points.
 */
float vtkZFrameRobotToImageRegistration2::CoordDistance(float *p1, float *p2)
{
  float sqdist;
  
  sqdist = (p1[0]-p2[0])*(p1[0]-p2[0]) + (p1[1]-p2[1])*(p1[1]-p2[1]);
  
  // RISK: Argument for SQRT may be negative. Overflow?
  if(sqdist<0)
  {
  std::cerr << "vtkZFrameRobotToImageRegistration2::CoordDistance - \
                              negative SQRT argument.\n" << std::endl;
      return(0);
  } else
    {
      return(sqrt((float)(sqdist)));
    }
}

/*----------------------------------------------------------------------------*/

/**
 * Put the fiducial coordinate point list in sequential order by matching the
 * three remaining points to their neighbouring ordered corner points.
 * TO DO: messy, need to improve readability.
 * @param points[][] The fiducial coordinate point list.
 * @param rmid The centre of the fiducial pattern in the row coordinate.
 * @param cmid The centre of the fiducial pattern in the column coordinate.
 */
void vtkZFrameRobotToImageRegistration2::OrderFidPoints(float points[7][2], float rmid, float cmid)
{
  int    pall[9]={0,-1,1,-1,2,-1,3,-1,0};  // prototype index list for all points
  int    pall2[7];
  int    pother[3]={4,5,6};                // indices of points other than corners
  int    i,j;
  float  points_temp[7][2];
  float  cdist, pdist1, pdist2;
  
  // Find fiducial points that fit between the corners.
  for(i=0; i<7; i+=2)
    for(j=0; j<3; j++)
    {
      if(pother[j]==-1)
      {
        // This point has already been placed. 
        continue;
      }
      cdist = CoordDistance(&(points[pall[i]][0]), &(points[pall[i+2]][0]));
      pdist1 = CoordDistance(&(points[pall[i]][0]), &(points[pother[j]][0]));
      pdist2 = CoordDistance(&(points[pall[i+2]][0]), &(points[pother[j]][0]));

      // RISK: divide by zero.
      if(cdist<MEPSILON)
      {
      std::cerr <<  "vtkZFrameRobotToImageRegistration2::OrderFidPoints - \
                                divide by zero." << std::endl;
        // TO DO: this should be detected in the first sanity check.
      } else
        {
          if(((pdist1+pdist2)/cdist)<1.05)
          {
            pall[i+1] = pother[j]; 
            pother[j] = -1;
            break;
          }
        }
    }
  
  // Re-order the points.
  // Find the -1. The last remaining -1 index marks the two corner points that 
  // do not have a fiducial lying between them. By convention, we start ordering
  // the coordinate points from one of these corners.
  for(i=1; i<9; i++)
      if(pall[i]==-1) break;
  
  // Find the direction to order the points 
  // (traverse points clockwise in the image).
  float d1x=(points[pall[0]][0]-rmid);
  float d1y=(points[pall[0]][1]-cmid);
  float d2x=(points[pall[2]][0]-rmid);
  float d2y=(points[pall[2]][1]-cmid); 
  float nvecz=(d1x*d2y-d2x*d1y);  
  int direction = 0;
  if(nvecz<0)
    direction = -1;
  else
    direction = 1;

  // Do the re-ordering in the clockwise direction.
  for(j=0; j<7; j++)
  {
      i += direction;
      if(i==-1) i=7;
      if(i==9) i=1;
      pall2[j] = pall[i];
  }

  // Create the new ordered point list.
  for(i=0; i<7; i++)
  {
      points_temp[i][0] = points[pall2[i]][0];
      points_temp[i][1] = points[pall2[i]][1];
  }
  for(i=0; i<7; i++)
  {
      points[i][0] = points_temp[i][0];
      points[i][1] = points_temp[i][1];
  }
}

/*----------------------------------------------------------------------------*/

/**
 * Compute the pose of the fiducial frame relative to the image plane, using
 * an adaptation of an algorithm presented by Susil et al.: "A Single image 
 * Registration Method for CT-Guided Interentions", MICCAI 1999.
 * @param Zcoordinates[][] Ordered Z-frame coordinates.
 * @param Zposition Estimated position of Z-frame origin w.r.t. image origin.
 * @param Zorientation Estimated orientation of the Z-frame w.r.t. the image
 *        frame--expressed as a quaternion.
 */
bool vtkZFrameRobotToImageRegistration2::LocalizeFrame(float Zcoordinates[7][2],
                                      Column3Vector &Zposition, 
                                      Quaternion &Zorientation)
{
  Column3Vector       Pz1, Pz2, Pz3;
  Column3Vector       Oz;
  Column3Vector       P2f, P4f, P6f;
  Column3Vector       Cf, Ci, Cfi;
  Column3Vector       Vx, Vy, Vz;
  Quaternion          Qft, Qit;
  float               angle;
  Column3Vector       axis;
  std::ostringstream  outs;
  
  
  //--- Compute diagonal points in the z-frame coordinates -------
  // Frame origin is at lower corner of Side 1,
  // y-axis is vertical, x-axis is horizontal.
  
  //--- SIDE 1
  // Map the three points for this z-fiducial.
  Pz1.setvalues( Zcoordinates[0][0], Zcoordinates[0][1], 0.0 );
  Pz2.setvalues( Zcoordinates[1][0], Zcoordinates[1][1], 0.0 );
  Pz3.setvalues( Zcoordinates[2][0], Zcoordinates[2][1], 0.0 );
  
  // Origin and direction vector of diagonal fiducial.
  //Oz.setvalues( -30.0, -30.0, 30.0 );
  //Vz.setvalues( 0.0, 1.0, -1.0 );
  //Oz.setvalues( 30.0, 30.0, -30.0 );
  //Vz.setvalues( 0.0,  -1.0, 1.0 );
  Oz.setvalues( -30.0, 30.0, 30.0 );
  Vz.setvalues( 0.0, -1.0, -1.0 );


  // Solve for the diagonal intercept in Z-frame coordinates.
  SolveZ(Pz1, Pz2, Pz3, Oz, Vz, P2f);
  
  //--- BASE
  // Map the three points for this z-fiducial.
  Pz1.setvalues( Zcoordinates[2][0], Zcoordinates[2][1], 0.0 );
  Pz2.setvalues( Zcoordinates[3][0], Zcoordinates[3][1], 0.0 );
  Pz3.setvalues( Zcoordinates[4][0], Zcoordinates[4][1], 0.0 );
  
  // Origin and direction vector of diagonal fiducial.
  //Oz.setvalues( 30.0, -30.0, 30.0 );
  //Vz.setvalues( -1.0, 0.0, -1.0 );
  //Oz.setvalues( -30.0, 30.0, -30.0 );
  //Vz.setvalues( 1.0, 0.0, 1.0 );
  Oz.setvalues( 30.0, 30.0, 30.0 );
  Vz.setvalues( -1.0, 0.0, -1.0 );
  
  // Solve for the diagonal intercept in Z-frame coordinates.
  SolveZ(Pz1, Pz2, Pz3, Oz, Vz, P4f);
  
  //--- SIDE 2
  // Map the three points for this z-fiducial.
  Pz1.setvalues( Zcoordinates[4][0], Zcoordinates[4][1], 0.0 );
  Pz2.setvalues( Zcoordinates[5][0], Zcoordinates[5][1], 0.0 );
  Pz3.setvalues( Zcoordinates[6][0], Zcoordinates[6][1], 0.0 );
  
  // Origin and direction vector of diagonal fiducial.
  //Oz.setvalues( 30.0, 30.0, 30.0 );
  //Vz.setvalues( 0.0, -1.0, -1.0 );
  //Oz.setvalues( -30.0, -30.0, -30.0 );
  //Vz.setvalues( 0.0, 1.0, 1.0 );
  Oz.setvalues( 30.0, -30.0, 30.0 );
  Vz.setvalues( 0.0,  1.0, -1.0 );

  // Solve for the diagonal intercept in Z-frame coordinates.
  SolveZ(Pz1, Pz2, Pz3, Oz, Vz, P6f);
  
  
  //--- Compute Transformation Between Image and Frame -----------
  
  // Compute orientation component first.
  // Compute z-frame cross section coordinate frame 
  //Vx = P4f - P2f;
  //Vy = P6f - P2f;
  //Vx = P4f - P6f;
  //Vy = P2f - P6f;
  Vx = P4f - P2f;
  Vy = P6f - P2f;

  Vz = Vx * Vy;
  Vy = Vz * Vx;
  Vx.normalize();
  if(Qft.ComputeFromRotationMatrix(Vx, Vy, Vz) == false)
    return(false);
  
  // Compute image cross-section coordinate frame 
  Pz1.setvalues( Zcoordinates[1][0], Zcoordinates[1][1], 0.0 );
  Pz2.setvalues( Zcoordinates[3][0], Zcoordinates[3][1], 0.0);
  Pz3.setvalues( Zcoordinates[5][0], Zcoordinates[5][1], 0.0);
  
  //Vx = Pz2 - Pz1;
  //Vy = Pz3 - Pz1;
  //Vx = Pz2 - Pz3;
  //Vy = Pz1 - Pz3;
  Vx = Pz2 - Pz1;
  Vy = Pz3 - Pz1;
  
  Vz = Vx * Vy;
  Vy = Vz * Vx;
  Vx.normalize();
  if(Qit.ComputeFromRotationMatrix(Vx, Vy, Vz) == false)
    return(false);
  
  // Rotation between frame and image: Qif = Qit/Qft
  Zorientation = Qit/Qft;

  // Compute axis-angle.
  angle = 2*acos(Zorientation.getW());
  if(fabs(angle)>15.0)
  {
  std::cerr << "vtkZFrameRobotToImageRegistration2::LocalizeFrame - Rotation angle too large, something is wrong." << std::endl;
     return(false);
  }
  if(angle==0.0)
  {
    axis.setX(1.0);
    axis.setY(0.0);
    axis.setZ(0.0); 
  }
  else axis.setvalues(Zorientation.getX()/
                      sqrt((float)(1-Zorientation.getW()*Zorientation.getW())),
                      Zorientation.getY()/
                      sqrt((float)(1-Zorientation.getW()*Zorientation.getW())),
                      Zorientation.getZ()/
                      sqrt((float)(1-Zorientation.getW()*Zorientation.getW())));
  // RISK: Negative argument for SQRT OR Divide By Zero.
  // TO DO: Overflow unlikely, but check for this condition.
  axis.normalize();
  
  outs.str(""); 
  outs << "Rotation Angle [degrees]: " << angle*180.0/3.14159 << endl;
  std::cerr << outs.str().c_str() << std::endl;
  outs.str(""); 
  outs  << "Rotation Axis: [" << axis.getX() << "," << axis.getY() << "," 
        << axis.getZ() << "]" << endl;
  std::cerr << outs.str().c_str() << std::endl;
  
  // Compute translational component.
  // Centroid of triangle in frame coordinates
  Cf = (P2f + P4f + P6f)/3.0;
  
  // Centroid of frame triangle in image coordinates
  Cfi = Zorientation.RotateVector(Cf);
  
  // Centroid of triangle in image coordinates
  Ci = (Pz1 + Pz2 + Pz3)/3.0;
  
  // Displacement of frame in image coordinates.
  Zposition = Ci - Cfi; 

  if(fabs(Zposition.getZ())>20.0)
  {
  std::cerr << "vtkZFrameRobotToImageRegistration2::LocalizeFrame - Displacement too large, something is wrong." << std::endl;
     return(false);
  }
  
  outs.str(""); 
  outs  << "Displacement [mm]: [" << Zposition.getX() << "," << Zposition.getY() 
        << "," << Zposition.getZ() << "]" << endl;
  std::cerr << outs.str().c_str() << std::endl;

  return(true);
}

/*----------------------------------------------------------------------------*/

/**
 * Find the the point at which the diagonal line fiducial is intercepted, 
 * using the three intercepts for a single set of planar line fiducials 
 * contained in one side of the Z-frame.
 * @param P1  Intercept point of first line fiducial in image.
 * @param P2  Intercept point of second line fiducial in image.
 * @param P3  Intercept point of third line fiducial in image.
 * @param Oz  Origin of this side of the Z-frame, in the Z-frame coordinates.
 * @param Vz  Vector representing the orientation of this side of the Z-frame, 
 *            in the Z-frame coordinates.
 * @param P2f Result: diagonal intercept in physical Z-frame coordinates. 
 */
void vtkZFrameRobotToImageRegistration2::SolveZ(Column3Vector P1, Column3Vector P2, 
                               Column3Vector P3, Column3Vector Oz, 
                               Column3Vector Vz, Column3Vector &P2f)
{
   Column3Vector  Vtmp;
   float          D12, D23, Ld, Lc;

   // Normalize the direction vector of the diagonal fiducial.
   Vz.normalize();

   // Compute intercept.
   Vtmp = P1 - P2;
   D12 = Vtmp.norm();
   Vtmp = P2 - P3;
   D23 = Vtmp.norm();
   Ld = 60.0*sqrt((float)2.0);
   Lc = Ld*D23/(D12+D23);

   // Compute P2 in frame coordinates.
   P2f = Oz + Vz*Lc;
}

/*----------------------------------------------------------------------------*/

/**
 * This method computes the new image plane position and orientation that will
 * align the next image with the centre of the Z-frame.
 * @param pcurrent The current image position that is to be updated.
 * @param ocurrent The current image orientation that is to be updated.
 * @param Zposition The position correction.
 * @param Zorientation The orientation correction
 */
void vtkZFrameRobotToImageRegistration2::Update_Scan_Plane(Column3Vector &pcurrent, 
                                          Quaternion &ocurrent, 
                                          Column3Vector Zposition, 
                                          Quaternion Zorientation)
{
   Quaternion Qcur, Qchg;

   // Update the scan plane position with the calculated offset in Zposition.
   //pcurrent = pcurrent - Zposition;
   double x = pcurrent.getX();
   double y = pcurrent.getY();
   double z = pcurrent.getZ();
   //pcurrent.setvalues(x - Zposition.getX(), y - Zposition.getY(), z + Zposition.getZ());
   pcurrent.setvalues(x + Zposition.getX(), y + Zposition.getY(), z + Zposition.getZ());


   // Compute the new image orientation.
   //ocurrent = Zorientation * ocurrent;
   ocurrent = Zorientation * ocurrent;
}

/*----------------------------------------------------------------------------*/

/**
 * Find the largest magnitude value in a complex k-space image.
 * @param realmat The matrix of real components.
 * @param imagmat The matrix of imaginary components.
 * @return The magnitude value of the largest k-space element.
 */
Real vtkZFrameRobotToImageRegistration2::ComplexMax(Matrix &realmat, Matrix &imagmat)
{
  Real maxabs=0.0, valabs=0.0, sqmag=0.0;
  
  for(int i=0; i<realmat.nrows(); i++)
    for(int j=0; j<realmat.ncols(); j++)
  {
      // Compute squared magnitude of the complex matrix element.
    sqmag = ((realmat.element(i,j)*realmat.element(i,j)) + 
        (imagmat.element(i,j)*imagmat.element(i,j)));

      // RISK: Argument for sqrt cannot be negative. Overflow?
    if(sqmag<0)
    {
    std::cerr << "vtkZFrameRobotToImageRegistration2::ComplexMax - \
                                negative sqrt argument." << std::endl;
    } else
      {
        // SQRT for magnitude of complex matrix element.
        valabs = sqrt((double)(sqmag));
      }

      // Find maximum magnitude.
    if(maxabs < valabs) 
    {
      maxabs = valabs;
    }
  }

  return(maxabs);
}

/*----------------------------------------------------------------------------*/
 
/**
 * Find the maximum value in a matrix.
 * @param realmat A matrix.
 * @return The value of the largest matrix element.
 */
Real vtkZFrameRobotToImageRegistration2::RealMax(Matrix &realmat)
{
  Real maxabs=0;
  
  
  for(int i=0; i<realmat.nrows(); i++)
    for(int j=0; j<realmat.ncols(); j++)
    {
        // Find the maximum element value.
      if(maxabs < realmat.element(i,j))
      {
        maxabs = realmat.element(i,j);
      } 
    }

  return(maxabs);
}

/*----------------------------------------------------------------------------*/
 
/**
 * Find the maximum value in a matrix, as well as its row and column
 * coordinates in the matrix.
 * @param inmatrix The input matrix.
 * @param row The Resulting row index at which the max value occurs.
 * @param col The Resulting column index at which the max value occurs.
 * @return The value of the largest matrix element.
 */
Real vtkZFrameRobotToImageRegistration2::FindMax(Matrix &inmatrix, int &row, int &col)
{
  Real maxabs=0;
  row = col = 0;
  
  // Avoid 10-pixel margin, due to image artifact.
  for(int i=10; i<inmatrix.nrows()-10; i++)
    for(int j=10; j<inmatrix.ncols()-10; j++)
  {
    if(maxabs < inmatrix.element(i,j))
    {
          // Record the maximum value, as well as the coordinates where it 
          // occurs.
      maxabs = inmatrix.element(i,j); 
      row = i;
      col = j;
    }
  }

  return(maxabs);
}

/*= END METHODS ==============================================================*/


void vtkZFrameRobotToImageRegistration2::PrintMatrix(Matrix4x4 &matrix)
{
  std::cout << "=============" << std::endl;
  std::cout << matrix[0][0] << ", " << matrix[0][1] << ", " << matrix[0][2] << ", " << matrix[0][3] << std::endl;
  std::cout << matrix[1][0] << ", " << matrix[1][1] << ", " << matrix[1][2] << ", " << matrix[1][3] << std::endl;
  std::cout << matrix[2][0] << ", " << matrix[2][1] << ", " << matrix[2][2] << ", " << matrix[2][3] << std::endl;
  std::cout << matrix[3][0] << ", " << matrix[3][1] << ", " << matrix[3][2] << ", " << matrix[3][3] << std::endl;
  std::cout << "=============" << std::endl;
}

void vtkZFrameRobotToImageRegistration2::QuaternionToMatrix(float* q, Matrix4x4& m)
{

  // normalize
  float mod = sqrt(q[0]*q[0]+q[1]*q[1]+q[2]*q[2]+q[3]*q[3]);

  // convert to the matrix
  const float x = q[0] / mod;
  const float y = q[1] / mod; 
  const float z = q[2] / mod; 
  const float w = q[3] / mod;
  
  const float xx = x * x * 2.0;
  const float xy = x * y * 2.0;
  const float xz = x * z * 2.0;
  const float xw = x * w * 2.0;
  const float yy = y * y * 2.0;
  const float yz = y * z * 2.0;
  const float yw = y * w * 2.0;
  const float zz = z * z * 2.0;
  const float zw = z * w * 2.0;
  
  m[0][0] = 1.0 - (yy + zz);
  m[1][0] = xy + zw;
  m[2][0] = xz - yw;
  
  m[0][1] = xy - zw;
  m[1][1] = 1.0 - (xx + zz);
  m[2][1] = yz + xw;
  
  m[0][2] = xz + yw;
  m[1][2] = yz - xw;
  m[2][2] = 1.0 - (xx + yy);

  m[3][0] = 0.0;
  m[3][1] = 0.0;
  m[3][2] = 0.0;
  m[3][3] = 1.0;

  m[0][3] = 0.0;
  m[1][3] = 0.0;
  m[2][3] = 0.0;

}


void vtkZFrameRobotToImageRegistration2::MatrixToQuaternion(Matrix4x4& m, float* q)
{
  float trace = m[0][0] + m[1][1] + m[2][2];

  if( trace > 0.0 ) {

    float s = 0.5f / sqrt(trace + 1.0f);

    q[3] = 0.25f / s;
    q[0] = ( m[2][1] - m[1][2] ) * s;
    q[1] = ( m[0][2] - m[2][0] ) * s;
    q[2] = ( m[1][0] - m[0][1] ) * s;

  } else {

    if ( m[0][0] > m[1][1] && m[0][0] > m[2][2] ) {

      float s = 2.0f * sqrt( 1.0f + m[0][0] - m[1][1] - m[2][2]);

      q[3] = (m[2][1] - m[1][2] ) / s;
      q[0] = 0.25f * s;
      q[1] = (m[0][1] + m[1][0] ) / s;
      q[2] = (m[0][2] + m[2][0] ) / s;

    } else if (m[1][1] > m[2][2]) {

      float s = 2.0f * sqrt( 1.0f + m[1][1] - m[0][0] - m[2][2]);

      q[3] = (m[0][2] - m[2][0] ) / s;
      q[0] = (m[0][1] + m[1][0] ) / s;
      q[1] = 0.25f * s;
      q[2] = (m[1][2] + m[2][1] ) / s;

    } else {

      float s = 2.0f * sqrt( 1.0f + m[2][2] - m[0][0] - m[1][1] );

      q[3] = (m[1][0] - m[0][1] ) / s;
      q[0] = (m[0][2] + m[2][0] ) / s;
      q[1] = (m[1][2] + m[2][1] ) / s;
      q[2] = 0.25f * s;

    }
  }
}
  

  
void vtkZFrameRobotToImageRegistration2::Cross(float *a, float *b, float *c)
{
    a[0] = b[1]*c[2] - c[1]*b[2];
    a[1] = c[0]*b[2] - b[0]*c[2];
    a[2] = b[0]*c[1] - c[0]*b[1];
}


void vtkZFrameRobotToImageRegistration2::IdentityMatrix(Matrix4x4 &matrix)
{
  matrix[0][0] = 1.0;
  matrix[1][0] = 0.0;
  matrix[2][0] = 0.0;
  matrix[3][0] = 0.0;

  matrix[0][1] = 0.0;
  matrix[1][1] = 1.0;
  matrix[2][1] = 0.0;
  matrix[3][1] = 0.0;

  matrix[0][2] = 0.0;
  matrix[1][2] = 0.0;
  matrix[2][2] = 1.0;
  matrix[3][2] = 0.0;

  matrix[0][3] = 0.0;
  matrix[1][3] = 0.0;
  matrix[2][3] = 0.0;
  matrix[3][3] = 1.0;
}


