File Coverage

lib/PDL/ImageND-pp-convolveND.c

Criterion	Covered	Total	%
statement	60	513	11.7
branch	42	634	6.6
condition			n/a
subroutine			n/a
pod			n/a
total	102	1147	8.8

#line 453 "lib/PDL/PP.pm"
/*
 * THIS FILE WAS GENERATED BY PDL::PP from lib/PDL/ImageND.pd! Do not modify!
 */

#define PDL_FREE_CODE(trans, destroy, comp_free_code, ntpriv_free_code) \
    if (destroy) { \
	comp_free_code \
    } \
    if ((trans)->dims_redone) { \
	ntpriv_free_code \
    }

#include "EXTERN.h"
#include "perl.h"
#include "XSUB.h"
#include "pdl.h"
#include "pdlcore.h"
#define PDL PDL_ImageND
extern Core* PDL; /* Structure hold core C functions */

#line 1846 "lib/PDL/PP.pm"
typedef struct pdl_params_convolveND {
#line 26 "lib/PDL/ImageND-pp-convolveND.c"
  pdl  *k;
  pdl  *aa;
  pdl  *a;
} pdl_params_convolveND;


#line 1857 "lib/PDL/PP.pm"
pdl_error pdl_convolveND_readdata(pdl_trans *__privtrans) {
  pdl_error PDL_err = {0, NULL, 0};
#line 36 "lib/PDL/ImageND-pp-convolveND.c"
  pdl_params_convolveND *__params = __privtrans->params; (void)__params;
  if (!__privtrans->broadcast.incs) return PDL->make_error(PDL_EUSERERROR, "Error in convolveND:" "broadcast.incs NULL");
  /* broadcastloop declarations */
  int __brcloopval;
  register PDL_Indx __tind0,__tind1; /* counters along dim */
  register PDL_Indx __tnpdls = __privtrans->broadcast.npdls;
  /* dims here are how many steps along those dims */
  register PDL_Indx __tinc0_k0 = PDL_BRC_INC(__privtrans->broadcast.incs,__tnpdls,0,0);
  register PDL_Indx __tinc1_k0 = PDL_BRC_INC(__privtrans->broadcast.incs,__tnpdls,0,1);
  #define PDL_BROADCASTLOOP_START_convolveND_readdata PDL_BROADCASTLOOP_START( \
    readdata, \
    __privtrans->broadcast, \
    __privtrans->vtable, \
    k0_datap += __offsp[0]; \
    , \
    (  ,k0_datap += __tinc1_k0 - __tinc0_k0 * __tdims0 \
    ), \
    (  ,k0_datap += __tinc0_k0 \
    ) \
  )
  #define PDL_BROADCASTLOOP_END_convolveND_readdata PDL_BROADCASTLOOP_END( \
    __privtrans->broadcast, \
    k0_datap -= __tinc1_k0 * __tdims1 + __offsp[0]; \
  )
  #ifndef PDL_DECLARE_PARAMS_convolveND_1
  #define PDL_DECLARE_PARAMS_convolveND_1(PDL_TYPE_OP,PDL_PPSYM_OP) \
    PDL_DECLARE_PARAMETER(PDL_TYPE_OP, k0, (__privtrans->pdls[0]), 1, PDL_PPSYM_OP)
  #endif
  #define PDL_IF_BAD(t,f) f
  switch (__privtrans->__datatype) { /* Start generic switch */
    case PDL_SB: {
      PDL_DECLARE_PARAMS_convolveND_1(PDL_SByte,A)
      PDL_BROADCASTLOOP_START_convolveND_readdata    {/*
           * Direct convolution
           *
           * Because the kernel is usually the smaller of the two arrays to be convolved,
           * we broadcast kernel-first to keep it in the processor's cache.  The strategy:
           * work on a padded copy of the original image, so that (even with boundary
           * conditions) the geometry of the kernel is linearly related to the input
           * array.  Otherwise, follow the path blazed by Karl in convolve(): keep track
           * of the offsets for each kernel element in a flattened original PDL.
           *
           * The first (PP) argument is a dummy that's only used to set the GENERIC()
           * macro.  The other three arguments should all have the same type as the
           * first arguments, and are all passed in as SVs.  They are: the kernel,
           * the padded copy of the input PDL, and a pre-allocated output PDL.  The
           * input PDL should be padded by the dimensionality of the kernel.
           *
           */

            PDL_Indx i;
            pdl *k = __params->k, *a = __params->a, *aa = __params->aa;
            PDL_RETERROR(PDL_err, PDL->make_physical(aa));
            PDL_RETERROR(PDL_err, PDL->make_physical(a));
            PDL_RETERROR(PDL_err, PDL->make_physical(k));

            PDL_Indx ndims = aa->ndims;
            if(ndims != k->ndims || ndims != aa->ndims)
               return PDL->make_error(PDL_EUSERERROR, "Error in convolveND:" "convolveND: dims don't agree - should never happen\n");

            PDL_Indx koffs[k->nvals];
            PDL_SByte kvals[k->nvals];
            PDL_Indx ivec[ndims];

            /************************************/
            /* Fill up the koffs & kvals arrays */
            /* koffs gets relative offsets into aa for each kernel value; */
            /* kvals gets the kernel values in the same order (flattened) */
            PDL_Indx *koff = koffs;
            PDL_SByte *kval = kvals;
            PDL_SByte *aptr = (PDL_SByte *)k->data + k->nvals - 1;

            for (i=0; i < ndims; i++) ivec[i] = 0;
            PDL_Indx npdls = 2, incs[npdls*ndims], offs[npdls];
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) {
              incs[i*npdls + 0] = k->dimincs[i];
              incs[i*npdls + 1] = aa->dimincs[i];
            }
            do {
              *kval++ = aptr[-offs[0]]; /* Copy kernel value into kernel list */
              *koff++ = offs[1];	  /* Copy current aa offset into koffs list */
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, k->dims, ivec)) break;
            } while (1);

            /******************************/
            /* Now do the actual convolution: for each vector in a,   */
            /* accumulate the appropriate aa-sum and stick it into a. */
            for (i=0; i < ndims; i++) ivec[i] = 0;
            aptr  = a->data;
            PDL_SByte *aaptr = aa->data;
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) incs[i*npdls + 0] = a->dimincs[i]; /* got aa already */
            do {
              PDL_SByte acc = 0;
              koff = koffs;
              kval = kvals;
              for (i=0;invals;i++)
                acc += aaptr[offs[1] + *koff++] * (*kval++);
              aptr[offs[0]] = acc;
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, a->dims, ivec)) break;
            } while (1);
            PDL->changed(a, PDL_PARENTDATACHANGED, 0);
          }PDL_BROADCASTLOOP_END_convolveND_readdata
    } break;
    case PDL_B: {
      PDL_DECLARE_PARAMS_convolveND_1(PDL_Byte,B)
      PDL_BROADCASTLOOP_START_convolveND_readdata    {/*
           * Direct convolution
           *
           * Because the kernel is usually the smaller of the two arrays to be convolved,
           * we broadcast kernel-first to keep it in the processor's cache.  The strategy:
           * work on a padded copy of the original image, so that (even with boundary
           * conditions) the geometry of the kernel is linearly related to the input
           * array.  Otherwise, follow the path blazed by Karl in convolve(): keep track
           * of the offsets for each kernel element in a flattened original PDL.
           *
           * The first (PP) argument is a dummy that's only used to set the GENERIC()
           * macro.  The other three arguments should all have the same type as the
           * first arguments, and are all passed in as SVs.  They are: the kernel,
           * the padded copy of the input PDL, and a pre-allocated output PDL.  The
           * input PDL should be padded by the dimensionality of the kernel.
           *
           */

            PDL_Indx i;
            pdl *k = __params->k, *a = __params->a, *aa = __params->aa;
            PDL_RETERROR(PDL_err, PDL->make_physical(aa));
            PDL_RETERROR(PDL_err, PDL->make_physical(a));
            PDL_RETERROR(PDL_err, PDL->make_physical(k));

            PDL_Indx ndims = aa->ndims;
            if(ndims != k->ndims || ndims != aa->ndims)
               return PDL->make_error(PDL_EUSERERROR, "Error in convolveND:" "convolveND: dims don't agree - should never happen\n");

            PDL_Indx koffs[k->nvals];
            PDL_Byte kvals[k->nvals];
            PDL_Indx ivec[ndims];

            /************************************/
            /* Fill up the koffs & kvals arrays */
            /* koffs gets relative offsets into aa for each kernel value; */
            /* kvals gets the kernel values in the same order (flattened) */
            PDL_Indx *koff = koffs;
            PDL_Byte *kval = kvals;
            PDL_Byte *aptr = (PDL_Byte *)k->data + k->nvals - 1;

            for (i=0; i < ndims; i++) ivec[i] = 0;
            PDL_Indx npdls = 2, incs[npdls*ndims], offs[npdls];
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) {
              incs[i*npdls + 0] = k->dimincs[i];
              incs[i*npdls + 1] = aa->dimincs[i];
            }
            do {
              *kval++ = aptr[-offs[0]]; /* Copy kernel value into kernel list */
              *koff++ = offs[1];	  /* Copy current aa offset into koffs list */
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, k->dims, ivec)) break;
            } while (1);

            /******************************/
            /* Now do the actual convolution: for each vector in a,   */
            /* accumulate the appropriate aa-sum and stick it into a. */
            for (i=0; i < ndims; i++) ivec[i] = 0;
            aptr  = a->data;
            PDL_Byte *aaptr = aa->data;
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) incs[i*npdls + 0] = a->dimincs[i]; /* got aa already */
            do {
              PDL_Byte acc = 0;
              koff = koffs;
              kval = kvals;
              for (i=0;invals;i++)
                acc += aaptr[offs[1] + *koff++] * (*kval++);
              aptr[offs[0]] = acc;
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, a->dims, ivec)) break;
            } while (1);
            PDL->changed(a, PDL_PARENTDATACHANGED, 0);
          }PDL_BROADCASTLOOP_END_convolveND_readdata
    } break;
    case PDL_S: {
      PDL_DECLARE_PARAMS_convolveND_1(PDL_Short,S)
      PDL_BROADCASTLOOP_START_convolveND_readdata    {/*
           * Direct convolution
           *
           * Because the kernel is usually the smaller of the two arrays to be convolved,
           * we broadcast kernel-first to keep it in the processor's cache.  The strategy:
           * work on a padded copy of the original image, so that (even with boundary
           * conditions) the geometry of the kernel is linearly related to the input
           * array.  Otherwise, follow the path blazed by Karl in convolve(): keep track
           * of the offsets for each kernel element in a flattened original PDL.
           *
           * The first (PP) argument is a dummy that's only used to set the GENERIC()
           * macro.  The other three arguments should all have the same type as the
           * first arguments, and are all passed in as SVs.  They are: the kernel,
           * the padded copy of the input PDL, and a pre-allocated output PDL.  The
           * input PDL should be padded by the dimensionality of the kernel.
           *
           */

            PDL_Indx i;
            pdl *k = __params->k, *a = __params->a, *aa = __params->aa;
            PDL_RETERROR(PDL_err, PDL->make_physical(aa));
            PDL_RETERROR(PDL_err, PDL->make_physical(a));
            PDL_RETERROR(PDL_err, PDL->make_physical(k));

            PDL_Indx ndims = aa->ndims;
            if(ndims != k->ndims || ndims != aa->ndims)
               return PDL->make_error(PDL_EUSERERROR, "Error in convolveND:" "convolveND: dims don't agree - should never happen\n");

            PDL_Indx koffs[k->nvals];
            PDL_Short kvals[k->nvals];
            PDL_Indx ivec[ndims];

            /************************************/
            /* Fill up the koffs & kvals arrays */
            /* koffs gets relative offsets into aa for each kernel value; */
            /* kvals gets the kernel values in the same order (flattened) */
            PDL_Indx *koff = koffs;
            PDL_Short *kval = kvals;
            PDL_Short *aptr = (PDL_Short *)k->data + k->nvals - 1;

            for (i=0; i < ndims; i++) ivec[i] = 0;
            PDL_Indx npdls = 2, incs[npdls*ndims], offs[npdls];
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) {
              incs[i*npdls + 0] = k->dimincs[i];
              incs[i*npdls + 1] = aa->dimincs[i];
            }
            do {
              *kval++ = aptr[-offs[0]]; /* Copy kernel value into kernel list */
              *koff++ = offs[1];	  /* Copy current aa offset into koffs list */
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, k->dims, ivec)) break;
            } while (1);

            /******************************/
            /* Now do the actual convolution: for each vector in a,   */
            /* accumulate the appropriate aa-sum and stick it into a. */
            for (i=0; i < ndims; i++) ivec[i] = 0;
            aptr  = a->data;
            PDL_Short *aaptr = aa->data;
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) incs[i*npdls + 0] = a->dimincs[i]; /* got aa already */
            do {
              PDL_Short acc = 0;
              koff = koffs;
              kval = kvals;
              for (i=0;invals;i++)
                acc += aaptr[offs[1] + *koff++] * (*kval++);
              aptr[offs[0]] = acc;
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, a->dims, ivec)) break;
            } while (1);
            PDL->changed(a, PDL_PARENTDATACHANGED, 0);
          }PDL_BROADCASTLOOP_END_convolveND_readdata
    } break;
    case PDL_US: {
      PDL_DECLARE_PARAMS_convolveND_1(PDL_Ushort,U)
      PDL_BROADCASTLOOP_START_convolveND_readdata    {/*
           * Direct convolution
           *
           * Because the kernel is usually the smaller of the two arrays to be convolved,
           * we broadcast kernel-first to keep it in the processor's cache.  The strategy:
           * work on a padded copy of the original image, so that (even with boundary
           * conditions) the geometry of the kernel is linearly related to the input
           * array.  Otherwise, follow the path blazed by Karl in convolve(): keep track
           * of the offsets for each kernel element in a flattened original PDL.
           *
           * The first (PP) argument is a dummy that's only used to set the GENERIC()
           * macro.  The other three arguments should all have the same type as the
           * first arguments, and are all passed in as SVs.  They are: the kernel,
           * the padded copy of the input PDL, and a pre-allocated output PDL.  The
           * input PDL should be padded by the dimensionality of the kernel.
           *
           */

            PDL_Indx i;
            pdl *k = __params->k, *a = __params->a, *aa = __params->aa;
            PDL_RETERROR(PDL_err, PDL->make_physical(aa));
            PDL_RETERROR(PDL_err, PDL->make_physical(a));
            PDL_RETERROR(PDL_err, PDL->make_physical(k));

            PDL_Indx ndims = aa->ndims;
            if(ndims != k->ndims || ndims != aa->ndims)
               return PDL->make_error(PDL_EUSERERROR, "Error in convolveND:" "convolveND: dims don't agree - should never happen\n");

            PDL_Indx koffs[k->nvals];
            PDL_Ushort kvals[k->nvals];
            PDL_Indx ivec[ndims];

            /************************************/
            /* Fill up the koffs & kvals arrays */
            /* koffs gets relative offsets into aa for each kernel value; */
            /* kvals gets the kernel values in the same order (flattened) */
            PDL_Indx *koff = koffs;
            PDL_Ushort *kval = kvals;
            PDL_Ushort *aptr = (PDL_Ushort *)k->data + k->nvals - 1;

            for (i=0; i < ndims; i++) ivec[i] = 0;
            PDL_Indx npdls = 2, incs[npdls*ndims], offs[npdls];
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) {
              incs[i*npdls + 0] = k->dimincs[i];
              incs[i*npdls + 1] = aa->dimincs[i];
            }
            do {
              *kval++ = aptr[-offs[0]]; /* Copy kernel value into kernel list */
              *koff++ = offs[1];	  /* Copy current aa offset into koffs list */
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, k->dims, ivec)) break;
            } while (1);

            /******************************/
            /* Now do the actual convolution: for each vector in a,   */
            /* accumulate the appropriate aa-sum and stick it into a. */
            for (i=0; i < ndims; i++) ivec[i] = 0;
            aptr  = a->data;
            PDL_Ushort *aaptr = aa->data;
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) incs[i*npdls + 0] = a->dimincs[i]; /* got aa already */
            do {
              PDL_Ushort acc = 0;
              koff = koffs;
              kval = kvals;
              for (i=0;invals;i++)
                acc += aaptr[offs[1] + *koff++] * (*kval++);
              aptr[offs[0]] = acc;
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, a->dims, ivec)) break;
            } while (1);
            PDL->changed(a, PDL_PARENTDATACHANGED, 0);
          }PDL_BROADCASTLOOP_END_convolveND_readdata
    } break;
    case PDL_L: {
      PDL_DECLARE_PARAMS_convolveND_1(PDL_Long,L)
      PDL_BROADCASTLOOP_START_convolveND_readdata    {/*
           * Direct convolution
           *
           * Because the kernel is usually the smaller of the two arrays to be convolved,
           * we broadcast kernel-first to keep it in the processor's cache.  The strategy:
           * work on a padded copy of the original image, so that (even with boundary
           * conditions) the geometry of the kernel is linearly related to the input
           * array.  Otherwise, follow the path blazed by Karl in convolve(): keep track
           * of the offsets for each kernel element in a flattened original PDL.
           *
           * The first (PP) argument is a dummy that's only used to set the GENERIC()
           * macro.  The other three arguments should all have the same type as the
           * first arguments, and are all passed in as SVs.  They are: the kernel,
           * the padded copy of the input PDL, and a pre-allocated output PDL.  The
           * input PDL should be padded by the dimensionality of the kernel.
           *
           */

            PDL_Indx i;
            pdl *k = __params->k, *a = __params->a, *aa = __params->aa;
            PDL_RETERROR(PDL_err, PDL->make_physical(aa));
            PDL_RETERROR(PDL_err, PDL->make_physical(a));
            PDL_RETERROR(PDL_err, PDL->make_physical(k));

            PDL_Indx ndims = aa->ndims;
            if(ndims != k->ndims || ndims != aa->ndims)
               return PDL->make_error(PDL_EUSERERROR, "Error in convolveND:" "convolveND: dims don't agree - should never happen\n");

            PDL_Indx koffs[k->nvals];
            PDL_Long kvals[k->nvals];
            PDL_Indx ivec[ndims];

            /************************************/
            /* Fill up the koffs & kvals arrays */
            /* koffs gets relative offsets into aa for each kernel value; */
            /* kvals gets the kernel values in the same order (flattened) */
            PDL_Indx *koff = koffs;
            PDL_Long *kval = kvals;
            PDL_Long *aptr = (PDL_Long *)k->data + k->nvals - 1;

            for (i=0; i < ndims; i++) ivec[i] = 0;
            PDL_Indx npdls = 2, incs[npdls*ndims], offs[npdls];
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) {
              incs[i*npdls + 0] = k->dimincs[i];
              incs[i*npdls + 1] = aa->dimincs[i];
            }
            do {
              *kval++ = aptr[-offs[0]]; /* Copy kernel value into kernel list */
              *koff++ = offs[1];	  /* Copy current aa offset into koffs list */
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, k->dims, ivec)) break;
            } while (1);

            /******************************/
            /* Now do the actual convolution: for each vector in a,   */
            /* accumulate the appropriate aa-sum and stick it into a. */
            for (i=0; i < ndims; i++) ivec[i] = 0;
            aptr  = a->data;
            PDL_Long *aaptr = aa->data;
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) incs[i*npdls + 0] = a->dimincs[i]; /* got aa already */
            do {
              PDL_Long acc = 0;
              koff = koffs;
              kval = kvals;
              for (i=0;invals;i++)
                acc += aaptr[offs[1] + *koff++] * (*kval++);
              aptr[offs[0]] = acc;
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, a->dims, ivec)) break;
            } while (1);
            PDL->changed(a, PDL_PARENTDATACHANGED, 0);
          }PDL_BROADCASTLOOP_END_convolveND_readdata
    } break;
    case PDL_UL: {
      PDL_DECLARE_PARAMS_convolveND_1(PDL_ULong,K)
      PDL_BROADCASTLOOP_START_convolveND_readdata    {/*
           * Direct convolution
           *
           * Because the kernel is usually the smaller of the two arrays to be convolved,
           * we broadcast kernel-first to keep it in the processor's cache.  The strategy:
           * work on a padded copy of the original image, so that (even with boundary
           * conditions) the geometry of the kernel is linearly related to the input
           * array.  Otherwise, follow the path blazed by Karl in convolve(): keep track
           * of the offsets for each kernel element in a flattened original PDL.
           *
           * The first (PP) argument is a dummy that's only used to set the GENERIC()
           * macro.  The other three arguments should all have the same type as the
           * first arguments, and are all passed in as SVs.  They are: the kernel,
           * the padded copy of the input PDL, and a pre-allocated output PDL.  The
           * input PDL should be padded by the dimensionality of the kernel.
           *
           */

            PDL_Indx i;
            pdl *k = __params->k, *a = __params->a, *aa = __params->aa;
            PDL_RETERROR(PDL_err, PDL->make_physical(aa));
            PDL_RETERROR(PDL_err, PDL->make_physical(a));
            PDL_RETERROR(PDL_err, PDL->make_physical(k));

            PDL_Indx ndims = aa->ndims;
            if(ndims != k->ndims || ndims != aa->ndims)
               return PDL->make_error(PDL_EUSERERROR, "Error in convolveND:" "convolveND: dims don't agree - should never happen\n");

            PDL_Indx koffs[k->nvals];
            PDL_ULong kvals[k->nvals];
            PDL_Indx ivec[ndims];

            /************************************/
            /* Fill up the koffs & kvals arrays */
            /* koffs gets relative offsets into aa for each kernel value; */
            /* kvals gets the kernel values in the same order (flattened) */
            PDL_Indx *koff = koffs;
            PDL_ULong *kval = kvals;
            PDL_ULong *aptr = (PDL_ULong *)k->data + k->nvals - 1;

            for (i=0; i < ndims; i++) ivec[i] = 0;
            PDL_Indx npdls = 2, incs[npdls*ndims], offs[npdls];
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) {
              incs[i*npdls + 0] = k->dimincs[i];
              incs[i*npdls + 1] = aa->dimincs[i];
            }
            do {
              *kval++ = aptr[-offs[0]]; /* Copy kernel value into kernel list */
              *koff++ = offs[1];	  /* Copy current aa offset into koffs list */
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, k->dims, ivec)) break;
            } while (1);

            /******************************/
            /* Now do the actual convolution: for each vector in a,   */
            /* accumulate the appropriate aa-sum and stick it into a. */
            for (i=0; i < ndims; i++) ivec[i] = 0;
            aptr  = a->data;
            PDL_ULong *aaptr = aa->data;
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) incs[i*npdls + 0] = a->dimincs[i]; /* got aa already */
            do {
              PDL_ULong acc = 0;
              koff = koffs;
              kval = kvals;
              for (i=0;invals;i++)
                acc += aaptr[offs[1] + *koff++] * (*kval++);
              aptr[offs[0]] = acc;
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, a->dims, ivec)) break;
            } while (1);
            PDL->changed(a, PDL_PARENTDATACHANGED, 0);
          }PDL_BROADCASTLOOP_END_convolveND_readdata
    } break;
    case PDL_IND: {
      PDL_DECLARE_PARAMS_convolveND_1(PDL_Indx,N)
      PDL_BROADCASTLOOP_START_convolveND_readdata    {/*
           * Direct convolution
           *
           * Because the kernel is usually the smaller of the two arrays to be convolved,
           * we broadcast kernel-first to keep it in the processor's cache.  The strategy:
           * work on a padded copy of the original image, so that (even with boundary
           * conditions) the geometry of the kernel is linearly related to the input
           * array.  Otherwise, follow the path blazed by Karl in convolve(): keep track
           * of the offsets for each kernel element in a flattened original PDL.
           *
           * The first (PP) argument is a dummy that's only used to set the GENERIC()
           * macro.  The other three arguments should all have the same type as the
           * first arguments, and are all passed in as SVs.  They are: the kernel,
           * the padded copy of the input PDL, and a pre-allocated output PDL.  The
           * input PDL should be padded by the dimensionality of the kernel.
           *
           */

            PDL_Indx i;
            pdl *k = __params->k, *a = __params->a, *aa = __params->aa;
            PDL_RETERROR(PDL_err, PDL->make_physical(aa));
            PDL_RETERROR(PDL_err, PDL->make_physical(a));
            PDL_RETERROR(PDL_err, PDL->make_physical(k));

            PDL_Indx ndims = aa->ndims;
            if(ndims != k->ndims || ndims != aa->ndims)
               return PDL->make_error(PDL_EUSERERROR, "Error in convolveND:" "convolveND: dims don't agree - should never happen\n");

            PDL_Indx koffs[k->nvals];
            PDL_Indx kvals[k->nvals];
            PDL_Indx ivec[ndims];

            /************************************/
            /* Fill up the koffs & kvals arrays */
            /* koffs gets relative offsets into aa for each kernel value; */
            /* kvals gets the kernel values in the same order (flattened) */
            PDL_Indx *koff = koffs;
            PDL_Indx *kval = kvals;
            PDL_Indx *aptr = (PDL_Indx *)k->data + k->nvals - 1;

            for (i=0; i < ndims; i++) ivec[i] = 0;
            PDL_Indx npdls = 2, incs[npdls*ndims], offs[npdls];
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) {
              incs[i*npdls + 0] = k->dimincs[i];
              incs[i*npdls + 1] = aa->dimincs[i];
            }
            do {
              *kval++ = aptr[-offs[0]]; /* Copy kernel value into kernel list */
              *koff++ = offs[1];	  /* Copy current aa offset into koffs list */
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, k->dims, ivec)) break;
            } while (1);

            /******************************/
            /* Now do the actual convolution: for each vector in a,   */
            /* accumulate the appropriate aa-sum and stick it into a. */
            for (i=0; i < ndims; i++) ivec[i] = 0;
            aptr  = a->data;
            PDL_Indx *aaptr = aa->data;
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) incs[i*npdls + 0] = a->dimincs[i]; /* got aa already */
            do {
              PDL_Indx acc = 0;
              koff = koffs;
              kval = kvals;
              for (i=0;invals;i++)
                acc += aaptr[offs[1] + *koff++] * (*kval++);
              aptr[offs[0]] = acc;
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, a->dims, ivec)) break;
            } while (1);
            PDL->changed(a, PDL_PARENTDATACHANGED, 0);
          }PDL_BROADCASTLOOP_END_convolveND_readdata
    } break;
    case PDL_ULL: {
      PDL_DECLARE_PARAMS_convolveND_1(PDL_ULongLong,P)
      PDL_BROADCASTLOOP_START_convolveND_readdata    {/*
           * Direct convolution
           *
           * Because the kernel is usually the smaller of the two arrays to be convolved,
           * we broadcast kernel-first to keep it in the processor's cache.  The strategy:
           * work on a padded copy of the original image, so that (even with boundary
           * conditions) the geometry of the kernel is linearly related to the input
           * array.  Otherwise, follow the path blazed by Karl in convolve(): keep track
           * of the offsets for each kernel element in a flattened original PDL.
           *
           * The first (PP) argument is a dummy that's only used to set the GENERIC()
           * macro.  The other three arguments should all have the same type as the
           * first arguments, and are all passed in as SVs.  They are: the kernel,
           * the padded copy of the input PDL, and a pre-allocated output PDL.  The
           * input PDL should be padded by the dimensionality of the kernel.
           *
           */

            PDL_Indx i;
            pdl *k = __params->k, *a = __params->a, *aa = __params->aa;
            PDL_RETERROR(PDL_err, PDL->make_physical(aa));
            PDL_RETERROR(PDL_err, PDL->make_physical(a));
            PDL_RETERROR(PDL_err, PDL->make_physical(k));

            PDL_Indx ndims = aa->ndims;
            if(ndims != k->ndims || ndims != aa->ndims)
               return PDL->make_error(PDL_EUSERERROR, "Error in convolveND:" "convolveND: dims don't agree - should never happen\n");

            PDL_Indx koffs[k->nvals];
            PDL_ULongLong kvals[k->nvals];
            PDL_Indx ivec[ndims];

            /************************************/
            /* Fill up the koffs & kvals arrays */
            /* koffs gets relative offsets into aa for each kernel value; */
            /* kvals gets the kernel values in the same order (flattened) */
            PDL_Indx *koff = koffs;
            PDL_ULongLong *kval = kvals;
            PDL_ULongLong *aptr = (PDL_ULongLong *)k->data + k->nvals - 1;

            for (i=0; i < ndims; i++) ivec[i] = 0;
            PDL_Indx npdls = 2, incs[npdls*ndims], offs[npdls];
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) {
              incs[i*npdls + 0] = k->dimincs[i];
              incs[i*npdls + 1] = aa->dimincs[i];
            }
            do {
              *kval++ = aptr[-offs[0]]; /* Copy kernel value into kernel list */
              *koff++ = offs[1];	  /* Copy current aa offset into koffs list */
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, k->dims, ivec)) break;
            } while (1);

            /******************************/
            /* Now do the actual convolution: for each vector in a,   */
            /* accumulate the appropriate aa-sum and stick it into a. */
            for (i=0; i < ndims; i++) ivec[i] = 0;
            aptr  = a->data;
            PDL_ULongLong *aaptr = aa->data;
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) incs[i*npdls + 0] = a->dimincs[i]; /* got aa already */
            do {
              PDL_ULongLong acc = 0;
              koff = koffs;
              kval = kvals;
              for (i=0;invals;i++)
                acc += aaptr[offs[1] + *koff++] * (*kval++);
              aptr[offs[0]] = acc;
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, a->dims, ivec)) break;
            } while (1);
            PDL->changed(a, PDL_PARENTDATACHANGED, 0);
          }PDL_BROADCASTLOOP_END_convolveND_readdata
    } break;
    case PDL_LL: {
      PDL_DECLARE_PARAMS_convolveND_1(PDL_LongLong,Q)
      PDL_BROADCASTLOOP_START_convolveND_readdata    {/*
           * Direct convolution
           *
           * Because the kernel is usually the smaller of the two arrays to be convolved,
           * we broadcast kernel-first to keep it in the processor's cache.  The strategy:
           * work on a padded copy of the original image, so that (even with boundary
           * conditions) the geometry of the kernel is linearly related to the input
           * array.  Otherwise, follow the path blazed by Karl in convolve(): keep track
           * of the offsets for each kernel element in a flattened original PDL.
           *
           * The first (PP) argument is a dummy that's only used to set the GENERIC()
           * macro.  The other three arguments should all have the same type as the
           * first arguments, and are all passed in as SVs.  They are: the kernel,
           * the padded copy of the input PDL, and a pre-allocated output PDL.  The
           * input PDL should be padded by the dimensionality of the kernel.
           *
           */

            PDL_Indx i;
            pdl *k = __params->k, *a = __params->a, *aa = __params->aa;
            PDL_RETERROR(PDL_err, PDL->make_physical(aa));
            PDL_RETERROR(PDL_err, PDL->make_physical(a));
            PDL_RETERROR(PDL_err, PDL->make_physical(k));

            PDL_Indx ndims = aa->ndims;
            if(ndims != k->ndims || ndims != aa->ndims)
               return PDL->make_error(PDL_EUSERERROR, "Error in convolveND:" "convolveND: dims don't agree - should never happen\n");

            PDL_Indx koffs[k->nvals];
            PDL_LongLong kvals[k->nvals];
            PDL_Indx ivec[ndims];

            /************************************/
            /* Fill up the koffs & kvals arrays */
            /* koffs gets relative offsets into aa for each kernel value; */
            /* kvals gets the kernel values in the same order (flattened) */
            PDL_Indx *koff = koffs;
            PDL_LongLong *kval = kvals;
            PDL_LongLong *aptr = (PDL_LongLong *)k->data + k->nvals - 1;

            for (i=0; i < ndims; i++) ivec[i] = 0;
            PDL_Indx npdls = 2, incs[npdls*ndims], offs[npdls];
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) {
              incs[i*npdls + 0] = k->dimincs[i];
              incs[i*npdls + 1] = aa->dimincs[i];
            }
            do {
              *kval++ = aptr[-offs[0]]; /* Copy kernel value into kernel list */
              *koff++ = offs[1];	  /* Copy current aa offset into koffs list */
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, k->dims, ivec)) break;
            } while (1);

            /******************************/
            /* Now do the actual convolution: for each vector in a,   */
            /* accumulate the appropriate aa-sum and stick it into a. */
            for (i=0; i < ndims; i++) ivec[i] = 0;
            aptr  = a->data;
            PDL_LongLong *aaptr = aa->data;
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) incs[i*npdls + 0] = a->dimincs[i]; /* got aa already */
            do {
              PDL_LongLong acc = 0;
              koff = koffs;
              kval = kvals;
              for (i=0;invals;i++)
                acc += aaptr[offs[1] + *koff++] * (*kval++);
              aptr[offs[0]] = acc;
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, a->dims, ivec)) break;
            } while (1);
            PDL->changed(a, PDL_PARENTDATACHANGED, 0);
          }PDL_BROADCASTLOOP_END_convolveND_readdata
    } break;
    case PDL_F: {
      PDL_DECLARE_PARAMS_convolveND_1(PDL_Float,F)
      PDL_BROADCASTLOOP_START_convolveND_readdata    {/*
           * Direct convolution
           *
           * Because the kernel is usually the smaller of the two arrays to be convolved,
           * we broadcast kernel-first to keep it in the processor's cache.  The strategy:
           * work on a padded copy of the original image, so that (even with boundary
           * conditions) the geometry of the kernel is linearly related to the input
           * array.  Otherwise, follow the path blazed by Karl in convolve(): keep track
           * of the offsets for each kernel element in a flattened original PDL.
           *
           * The first (PP) argument is a dummy that's only used to set the GENERIC()
           * macro.  The other three arguments should all have the same type as the
           * first arguments, and are all passed in as SVs.  They are: the kernel,
           * the padded copy of the input PDL, and a pre-allocated output PDL.  The
           * input PDL should be padded by the dimensionality of the kernel.
           *
           */

            PDL_Indx i;
            pdl *k = __params->k, *a = __params->a, *aa = __params->aa;
            PDL_RETERROR(PDL_err, PDL->make_physical(aa));
            PDL_RETERROR(PDL_err, PDL->make_physical(a));
            PDL_RETERROR(PDL_err, PDL->make_physical(k));

            PDL_Indx ndims = aa->ndims;
            if(ndims != k->ndims || ndims != aa->ndims)
               return PDL->make_error(PDL_EUSERERROR, "Error in convolveND:" "convolveND: dims don't agree - should never happen\n");

            PDL_Indx koffs[k->nvals];
            PDL_Float kvals[k->nvals];
            PDL_Indx ivec[ndims];

            /************************************/
            /* Fill up the koffs & kvals arrays */
            /* koffs gets relative offsets into aa for each kernel value; */
            /* kvals gets the kernel values in the same order (flattened) */
            PDL_Indx *koff = koffs;
            PDL_Float *kval = kvals;
            PDL_Float *aptr = (PDL_Float *)k->data + k->nvals - 1;

            for (i=0; i < ndims; i++) ivec[i] = 0;
            PDL_Indx npdls = 2, incs[npdls*ndims], offs[npdls];
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) {
              incs[i*npdls + 0] = k->dimincs[i];
              incs[i*npdls + 1] = aa->dimincs[i];
            }
            do {
              *kval++ = aptr[-offs[0]]; /* Copy kernel value into kernel list */
              *koff++ = offs[1];	  /* Copy current aa offset into koffs list */
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, k->dims, ivec)) break;
            } while (1);

            /******************************/
            /* Now do the actual convolution: for each vector in a,   */
            /* accumulate the appropriate aa-sum and stick it into a. */
            for (i=0; i < ndims; i++) ivec[i] = 0;
            aptr  = a->data;
            PDL_Float *aaptr = aa->data;
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) incs[i*npdls + 0] = a->dimincs[i]; /* got aa already */
            do {
              PDL_Float acc = 0;
              koff = koffs;
              kval = kvals;
              for (i=0;invals;i++)
                acc += aaptr[offs[1] + *koff++] * (*kval++);
              aptr[offs[0]] = acc;
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, a->dims, ivec)) break;
            } while (1);
            PDL->changed(a, PDL_PARENTDATACHANGED, 0);
          }PDL_BROADCASTLOOP_END_convolveND_readdata
    } break;
    case PDL_D: {
      PDL_DECLARE_PARAMS_convolveND_1(PDL_Double,D)
      PDL_BROADCASTLOOP_START_convolveND_readdata    {/*
           * Direct convolution
           *
           * Because the kernel is usually the smaller of the two arrays to be convolved,
           * we broadcast kernel-first to keep it in the processor's cache.  The strategy:
           * work on a padded copy of the original image, so that (even with boundary
           * conditions) the geometry of the kernel is linearly related to the input
           * array.  Otherwise, follow the path blazed by Karl in convolve(): keep track
           * of the offsets for each kernel element in a flattened original PDL.
           *
           * The first (PP) argument is a dummy that's only used to set the GENERIC()
           * macro.  The other three arguments should all have the same type as the
           * first arguments, and are all passed in as SVs.  They are: the kernel,
           * the padded copy of the input PDL, and a pre-allocated output PDL.  The
           * input PDL should be padded by the dimensionality of the kernel.
           *
           */

            PDL_Indx i;
            pdl *k = __params->k, *a = __params->a, *aa = __params->aa;
            PDL_RETERROR(PDL_err, PDL->make_physical(aa));
            PDL_RETERROR(PDL_err, PDL->make_physical(a));
            PDL_RETERROR(PDL_err, PDL->make_physical(k));

            PDL_Indx ndims = aa->ndims;
            if(ndims != k->ndims || ndims != aa->ndims)
               return PDL->make_error(PDL_EUSERERROR, "Error in convolveND:" "convolveND: dims don't agree - should never happen\n");

            PDL_Indx koffs[k->nvals];
            PDL_Double kvals[k->nvals];
            PDL_Indx ivec[ndims];

            /************************************/
            /* Fill up the koffs & kvals arrays */
            /* koffs gets relative offsets into aa for each kernel value; */
            /* kvals gets the kernel values in the same order (flattened) */
            PDL_Indx *koff = koffs;
            PDL_Double *kval = kvals;
            PDL_Double *aptr = (PDL_Double *)k->data + k->nvals - 1;

            for (i=0; i < ndims; i++) ivec[i] = 0;
            PDL_Indx npdls = 2, incs[npdls*ndims], offs[npdls];
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) {
              incs[i*npdls + 0] = k->dimincs[i];
              incs[i*npdls + 1] = aa->dimincs[i];
            }
            do {
              *kval++ = aptr[-offs[0]]; /* Copy kernel value into kernel list */
              *koff++ = offs[1];	  /* Copy current aa offset into koffs list */
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, k->dims, ivec)) break;
            } while (1);

            /******************************/
            /* Now do the actual convolution: for each vector in a,   */
            /* accumulate the appropriate aa-sum and stick it into a. */
            for (i=0; i < ndims; i++) ivec[i] = 0;
            aptr  = a->data;
            PDL_Double *aaptr = aa->data;
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) incs[i*npdls + 0] = a->dimincs[i]; /* got aa already */
            do {
              PDL_Double acc = 0;
              koff = koffs;
              kval = kvals;
              for (i=0;invals;i++)
                acc += aaptr[offs[1] + *koff++] * (*kval++);
              aptr[offs[0]] = acc;
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, a->dims, ivec)) break;
            } while (1);
            PDL->changed(a, PDL_PARENTDATACHANGED, 0);
          }PDL_BROADCASTLOOP_END_convolveND_readdata
    } break;
    case PDL_LD: {
      PDL_DECLARE_PARAMS_convolveND_1(PDL_LDouble,E)
      PDL_BROADCASTLOOP_START_convolveND_readdata    {/*
           * Direct convolution
           *
           * Because the kernel is usually the smaller of the two arrays to be convolved,
           * we broadcast kernel-first to keep it in the processor's cache.  The strategy:
           * work on a padded copy of the original image, so that (even with boundary
           * conditions) the geometry of the kernel is linearly related to the input
           * array.  Otherwise, follow the path blazed by Karl in convolve(): keep track
           * of the offsets for each kernel element in a flattened original PDL.
           *
           * The first (PP) argument is a dummy that's only used to set the GENERIC()
           * macro.  The other three arguments should all have the same type as the
           * first arguments, and are all passed in as SVs.  They are: the kernel,
           * the padded copy of the input PDL, and a pre-allocated output PDL.  The
           * input PDL should be padded by the dimensionality of the kernel.
           *
           */

            PDL_Indx i;
            pdl *k = __params->k, *a = __params->a, *aa = __params->aa;
            PDL_RETERROR(PDL_err, PDL->make_physical(aa));
            PDL_RETERROR(PDL_err, PDL->make_physical(a));
            PDL_RETERROR(PDL_err, PDL->make_physical(k));

            PDL_Indx ndims = aa->ndims;
            if(ndims != k->ndims || ndims != aa->ndims)
               return PDL->make_error(PDL_EUSERERROR, "Error in convolveND:" "convolveND: dims don't agree - should never happen\n");

            PDL_Indx koffs[k->nvals];
            PDL_LDouble kvals[k->nvals];
            PDL_Indx ivec[ndims];

            /************************************/
            /* Fill up the koffs & kvals arrays */
            /* koffs gets relative offsets into aa for each kernel value; */
            /* kvals gets the kernel values in the same order (flattened) */
            PDL_Indx *koff = koffs;
            PDL_LDouble *kval = kvals;
            PDL_LDouble *aptr = (PDL_LDouble *)k->data + k->nvals - 1;

            for (i=0; i < ndims; i++) ivec[i] = 0;
            PDL_Indx npdls = 2, incs[npdls*ndims], offs[npdls];
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) {
              incs[i*npdls + 0] = k->dimincs[i];
              incs[i*npdls + 1] = aa->dimincs[i];
            }
            do {
              *kval++ = aptr[-offs[0]]; /* Copy kernel value into kernel list */
              *koff++ = offs[1];	  /* Copy current aa offset into koffs list */
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, k->dims, ivec)) break;
            } while (1);

            /******************************/
            /* Now do the actual convolution: for each vector in a,   */
            /* accumulate the appropriate aa-sum and stick it into a. */
            for (i=0; i < ndims; i++) ivec[i] = 0;
            aptr  = a->data;
            PDL_LDouble *aaptr = aa->data;
            for (i=0; i < npdls; i++) offs[i] = 0;
            for (i=0; i < ndims; i++) incs[i*npdls + 0] = a->dimincs[i]; /* got aa already */
            do {
              PDL_LDouble acc = 0;
              koff = koffs;
              kval = kvals;
              for (i=0;invals;i++)
                acc += aaptr[offs[1] + *koff++] * (*kval++);
              aptr[offs[0]] = acc;
              if (!pdl_broadcast_nd_step(npdls, offs, 0, ndims, incs, a->dims, ivec)) break;
            } while (1);
            PDL->changed(a, PDL_PARENTDATACHANGED, 0);
          }PDL_BROADCASTLOOP_END_convolveND_readdata
    } break;
    default: return PDL->make_error(PDL_EUSERERROR, "PP INTERNAL ERROR in convolveND: unhandled datatype(%d), only handles (ABSULKNPQFDE)! PLEASE MAKE A BUG REPORT\n", __privtrans->__datatype);
  }
  #undef PDL_IF_BAD
  return PDL_err;
}

static pdl_datatypes pdl_convolveND_vtable_gentypes[] = { PDL_SB, PDL_B, PDL_S, PDL_US, PDL_L, PDL_UL, PDL_IND, PDL_ULL, PDL_LL, PDL_F, PDL_D, PDL_LD, -1 };
static PDL_Indx pdl_convolveND_vtable_realdims[] = { 0 };
static char *pdl_convolveND_vtable_parnames[] = { "k0" };
static short pdl_convolveND_vtable_parflags[] = {
  0
};
static pdl_datatypes pdl_convolveND_vtable_partypes[] = { -1 };
static PDL_Indx pdl_convolveND_vtable_realdims_starts[] = { 0 };
static PDL_Indx pdl_convolveND_vtable_realdims_ind_ids[] = { 0 };
static char *pdl_convolveND_vtable_indnames[] = { "" };
pdl_transvtable pdl_convolveND_vtable = {
  PDL_TRANS_DO_BROADCAST, 0, pdl_convolveND_vtable_gentypes, 1, 1, NULL /*CORE21*/,
  pdl_convolveND_vtable_realdims, pdl_convolveND_vtable_parnames,
  pdl_convolveND_vtable_parflags, pdl_convolveND_vtable_partypes,
  pdl_convolveND_vtable_realdims_starts, pdl_convolveND_vtable_realdims_ind_ids, 0,
  0, pdl_convolveND_vtable_indnames,
  NULL, pdl_convolveND_readdata, NULL,
  NULL,
  sizeof(pdl_params_convolveND),"PDL::ImageND::convolveND"
};


pdl_error pdl_run_convolveND(pdl  *k0,pdl  *k,pdl  *aa,pdl  *a) {
  pdl_error PDL_err = {0, NULL, 0};
  if (!PDL) return (pdl_error){PDL_EFATAL, "PDL core struct is NULL, can't continue",0};
  pdl_trans *__privtrans = PDL->create_trans(&pdl_convolveND_vtable);
  if (!__privtrans) return PDL->make_error_simple(PDL_EFATAL, "Couldn't create trans");
  pdl_params_convolveND *__params = __privtrans->params;
  __privtrans->pdls[0] = k0;
  PDL_RETERROR(PDL_err, PDL->type_coerce(__privtrans));
  (__params->k) = (k); /* CType.get_copy */
  (__params->aa) = (aa); /* CType.get_copy */
  (__params->a) = (a); /* CType.get_copy */
  PDL_RETERROR(PDL_err, PDL->make_trans_mutual(__privtrans));
  return PDL_err;
}