Пример #1
0
void joint_histogram(double* H, 
		     unsigned int clampI, 
		     unsigned int clampJ,  
		     PyArrayIterObject* iterI,
		     const PyArrayObject* imJ_padded, 
		     const double* Tvox, 
		     int affine, 
		     int interp)
{
  const signed short* J=(signed short*)imJ_padded->data; 
  size_t dimJX=imJ_padded->dimensions[0]-2;
  size_t dimJY=imJ_padded->dimensions[1]-2; 
  size_t dimJZ=imJ_padded->dimensions[2]-2;  
  signed short Jnn[8]; 
  double W[8]; 
  signed short *bufI, *bufJnn; 
  double *bufW; 
  signed short i, j;
  size_t off;
  size_t u2 = imJ_padded->dimensions[2]; 
  size_t u3 = u2+1; 
  size_t u4 = imJ_padded->dimensions[1]*u2;
  size_t u5 = u4+1; 
  size_t u6 = u4+u2; 
  size_t u7 = u6+1; 
  double wx, wy, wz, wxwy, wxwz, wywz; 
  double W0, W2, W3, W4; 
  size_t x, y, z; 
  int nn, nx, ny, nz;
  double Tx, Ty, Tz; 
  double *bufTvox = (double*)Tvox; 
  void (*interpolate)(unsigned int, double*, unsigned int, const signed short*, const double*, int, void*); 
  void* interp_params = NULL; 
  rk_state rng; 

  /* Reset the source image iterator */
  PyArray_ITER_RESET(iterI);

  /* Make sure the iterator the iterator will update coordinate values */ 
  UPDATE_ITERATOR_COORDS(iterI); 

  /* Set interpolation method */ 
  if (interp==0) 
    interpolate = &_pv_interpolation;
  else if (interp>0) 
    interpolate = &_tri_interpolation; 
  else { /* interp < 0 */ 
    interpolate = &_rand_interpolation;
    rk_seed(-interp, &rng); 
    interp_params = (void*)(&rng); 
  }

  /* Re-initialize joint histogram */ 
  memset((void*)H, 0, clampI*clampJ*sizeof(double));

  /* Looop over source voxels */
  while(iterI->index < iterI->size) {
  
    /* Source voxel intensity */
    bufI = (signed short*)PyArray_ITER_DATA(iterI); 
    i = bufI[0];

    /* Compute the transformed grid coordinates of current voxel */ 
    if (affine) {
      /* Get voxel coordinates and apply transformation on-the-fly*/
      x = iterI->coordinates[0];
      y = iterI->coordinates[1];
      z = iterI->coordinates[2];
      _affine_transform(&Tx, &Ty, &Tz, Tvox, x, y, z); 
    }
    else 
      /* Use precomputed transformed coordinates */ 
      bufTvox = _precomputed_transform(&Tx, &Ty, &Tz, (const double*)bufTvox);
       
    /* Test whether the current voxel is below the intensity
       threshold, or the transformed point is completly outside
       the reference grid */
    if ((i>=0) && 
	(Tx>-1) && (Tx<dimJX) && 
	(Ty>-1) && (Ty<dimJY) && 
	(Tz>-1) && (Tz<dimJZ)) {
	
      /* 
	 Nearest neighbor (floor coordinates in the padded
	 image, hence +1). 
	 
	 Notice that using the floor function doubles excetution time.
	 
	 FIXME: see if we can replace this with assembler instructions. 
      */
      nx = FLOOR(Tx) + 1;
      ny = FLOOR(Ty) + 1;
      nz = FLOOR(Tz) + 1;
      
      /* The convention for neighbor indexing is as follows:
       *
       *   Floor slice        Ceil slice
       *
       *     2----6             3----7                     y          
       *     |    |             |    |                     ^ 
       *     |    |             |    |                     |
       *     0----4             1----5                     ---> x
       */
      
      /*** Trilinear interpolation weights.  
	   Note: wx = nnx + 1 - Tx, where nnx is the location in
	   the NON-PADDED grid */ 
      wx = nx - Tx; 
      wy = ny - Ty;
      wz = nz - Tz;
      wxwy = wx*wy;    
      wxwz = wx*wz;
      wywz = wy*wz;
      
      /*** Prepare buffers */ 
      bufJnn = Jnn;
      bufW = W; 
      
      /*** Initialize neighbor list */
      off = nx*u4 + ny*u2 + nz; 
      nn = 0; 
      
      /*** Neighbor 0: (0,0,0) */ 
      W0 = wxwy*wz; 
      APPEND_NEIGHBOR(off, W0); 
      
      /*** Neighbor 1: (0,0,1) */ 
      APPEND_NEIGHBOR(off+1, wxwy-W0);
      
      /*** Neighbor 2: (0,1,0) */ 
      W2 = wxwz-W0; 
      APPEND_NEIGHBOR(off+u2, W2);  
      
      /*** Neightbor 3: (0,1,1) */
      W3 = wx-wxwy-W2;  
      APPEND_NEIGHBOR(off+u3, W3);  
      
      /*** Neighbor 4: (1,0,0) */
      W4 = wywz-W0;  
      APPEND_NEIGHBOR(off+u4, W4); 
      
      /*** Neighbor 5: (1,0,1) */ 
      APPEND_NEIGHBOR(off+u5, wy-wxwy-W4);   
      
      /*** Neighbor 6: (1,1,0) */ 
      APPEND_NEIGHBOR(off+u6, wz-wxwz-W4);  
      
      /*** Neighbor 7: (1,1,1) */ 
      APPEND_NEIGHBOR(off+u7, 1-W3-wy-wz+wywz);  
      
      /* Update the joint histogram using the desired interpolation technique */ 
      interpolate(i, H, clampJ, Jnn, W, nn, interp_params); 
      
      
    } /* End of IF TRANSFORMS INSIDE */
    
    /* Update source index */ 
    PyArray_ITER_NEXT(iterI); 
    
  } /* End of loop over voxels */ 
  

  return; 
}
Пример #2
0
int joint_histogram(PyArrayObject* JH, 
		    unsigned int clampI, 
		    unsigned int clampJ,  
		    PyArrayIterObject* iterI,
		    const PyArrayObject* imJ_padded, 
		    const PyArrayObject* Tvox, 
		    long interp)
{
  const signed short* J=(signed short*)imJ_padded->data; 
  size_t dimJX=imJ_padded->dimensions[0]-2;
  size_t dimJY=imJ_padded->dimensions[1]-2; 
  size_t dimJZ=imJ_padded->dimensions[2]-2;  
  signed short Jnn[8]; 
  double W[8]; 
  signed short *bufI, *bufJnn; 
  double *bufW; 
  signed short i, j;
  size_t off;
  size_t u2 = imJ_padded->dimensions[2]; 
  size_t u3 = u2+1; 
  size_t u4 = imJ_padded->dimensions[1]*u2;
  size_t u5 = u4+1; 
  size_t u6 = u4+u2; 
  size_t u7 = u6+1; 
  double wx, wy, wz, wxwy, wxwz, wywz; 
  double W0, W2, W3, W4; 
  int nn, nx, ny, nz;
  double *H = (double*)PyArray_DATA(JH);  
  double Tx, Ty, Tz; 
  double *tvox = (double*)PyArray_DATA(Tvox); 
  void (*interpolate)(unsigned int, double*, unsigned int, const signed short*, const double*, int, void*); 
  void* interp_params = NULL; 
  prng_state rng; 


  /* 
     Check assumptions regarding input arrays. If it fails, the
     function will return -1 without doing anything else. 
     
     iterI : assumed to iterate over a signed short encoded, possibly
     non-contiguous array.
     
     imJ_padded : assumed C-contiguous (last index varies faster) & signed
     short encoded.
     
     H : assumed C-contiguous. 
     
     Tvox : assumed C-contiguous: 
     
       either a 3x4=12-sized array (or bigger) for an affine transformation

       or a 3xN array for a pre-computed transformation, with N equal
       to the size of the array corresponding to iterI (no checking
       done)
  
  */
  if (PyArray_TYPE(iterI->ao) != NPY_SHORT) {
    fprintf(stderr, "Invalid type for the array iterator\n");
    return -1; 
  }
  if ( (!PyArray_ISCONTIGUOUS(imJ_padded)) || 
       (!PyArray_ISCONTIGUOUS(JH)) ||
       (!PyArray_ISCONTIGUOUS(Tvox)) ) {
    fprintf(stderr, "Some non-contiguous arrays\n");
    return -1; 
  }

  /* Reset the source image iterator */
  PyArray_ITER_RESET(iterI);

  /* Set interpolation method */ 
  if (interp==0) 
    interpolate = &_pv_interpolation;
  else if (interp>0) 
    interpolate = &_tri_interpolation; 
  else { /* interp < 0 */ 
    interpolate = &_rand_interpolation;
    prng_seed(-interp, &rng); 
    interp_params = (void*)(&rng); 
  }

  /* Re-initialize joint histogram */ 
  memset((void*)H, 0, clampI*clampJ*sizeof(double));

  /* Looop over source voxels */
  while(iterI->index < iterI->size) {
  
    /* Source voxel intensity */
    bufI = (signed short*)PyArray_ITER_DATA(iterI); 
    i = bufI[0];

    /* Compute the transformed grid coordinates of current voxel */ 
    Tx = *tvox; tvox++;
    Ty = *tvox; tvox++;
    Tz = *tvox; tvox++; 

    /* Test whether the current voxel is below the intensity
       threshold, or the transformed point is completly outside
       the reference grid */
    if ((i>=0) && 
	(Tx>-1) && (Tx<dimJX) && 
	(Ty>-1) && (Ty<dimJY) && 
	(Tz>-1) && (Tz<dimJZ)) {
	
      /* 
	 Nearest neighbor (floor coordinates in the padded
	 image, hence +1). 
	 
	 Notice that using the floor function doubles excetution time.
	 
	 FIXME: see if we can replace this with assembler instructions. 
      */
      nx = FLOOR(Tx) + 1;
      ny = FLOOR(Ty) + 1;
      nz = FLOOR(Tz) + 1;
      
      /* The convention for neighbor indexing is as follows:
       *
       *   Floor slice        Ceil slice
       *
       *     2----6             3----7                     y          
       *     |    |             |    |                     ^ 
       *     |    |             |    |                     |
       *     0----4             1----5                     ---> x
       */
      
      /*** Trilinear interpolation weights.  
	   Note: wx = nnx + 1 - Tx, where nnx is the location in
	   the NON-PADDED grid */ 
      wx = nx - Tx; 
      wy = ny - Ty;
      wz = nz - Tz;
      wxwy = wx*wy;    
      wxwz = wx*wz;
      wywz = wy*wz;
      
      /*** Prepare buffers */ 
      bufJnn = Jnn;
      bufW = W; 
      
      /*** Initialize neighbor list */
      off = nx*u4 + ny*u2 + nz; 
      nn = 0; 
      
      /*** Neighbor 0: (0,0,0) */ 
      W0 = wxwy*wz; 
      APPEND_NEIGHBOR(off, W0); 
      
      /*** Neighbor 1: (0,0,1) */ 
      APPEND_NEIGHBOR(off+1, wxwy-W0);
      
      /*** Neighbor 2: (0,1,0) */ 
      W2 = wxwz-W0; 
      APPEND_NEIGHBOR(off+u2, W2);  
      
      /*** Neightbor 3: (0,1,1) */
      W3 = wx-wxwy-W2;  
      APPEND_NEIGHBOR(off+u3, W3);  
      
      /*** Neighbor 4: (1,0,0) */
      W4 = wywz-W0;  
      APPEND_NEIGHBOR(off+u4, W4); 
      
      /*** Neighbor 5: (1,0,1) */ 
      APPEND_NEIGHBOR(off+u5, wy-wxwy-W4);   
      
      /*** Neighbor 6: (1,1,0) */ 
      APPEND_NEIGHBOR(off+u6, wz-wxwz-W4);  
      
      /*** Neighbor 7: (1,1,1) */ 
      APPEND_NEIGHBOR(off+u7, 1-W3-wy-wz+wywz);  
      
      /* Update the joint histogram using the desired interpolation technique */ 
      interpolate(i, H, clampJ, Jnn, W, nn, interp_params); 
      
      
    } /* End of IF TRANSFORMS INSIDE */
    
    /* Update source index */ 
    PyArray_ITER_NEXT(iterI); 
    
  } /* End of loop over voxels */ 
  

  return 0; 
}