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GCC Code Coverage Report
Directory:	./		Exec	Total	Coverage
File:	src/ten/tensor.c	Lines:	7	523	1.3 %
Date:	2017-05-26	Branches:	7	288	2.4 %

/*
  Teem: Tools to process and visualize scientific data and images             .
  Copyright (C) 2013, 2012, 2011, 2010, 2009  University of Chicago
  Copyright (C) 2008, 2007, 2006, 2005  Gordon Kindlmann
  Copyright (C) 2004, 2003, 2002, 2001, 2000, 1999, 1998  University of Utah

  This library is free software; you can redistribute it and/or
  modify it under the terms of the GNU Lesser General Public License
  (LGPL) as published by the Free Software Foundation; either
  version 2.1 of the License, or (at your option) any later version.
  The terms of redistributing and/or modifying this software also
  include exceptions to the LGPL that facilitate static linking.

  This library is distributed in the hope that it will be useful,
  but WITHOUT ANY WARRANTY; without even the implied warranty of
  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
  Lesser General Public License for more details.

  You should have received a copy of the GNU Lesser General Public License
  along with this library; if not, write to Free Software Foundation, Inc.,
  51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
*/


#include "ten.h"
#include "privateTen.h"

int tenVerbose = 0;

void
tenRotateSingle_f(float tenOut[7], const float rot[9], const float tenIn[7]) {
  float rotT[9], matIn[9], tmp[9], matOut[9];

  ELL_3M_TRANSPOSE(rotT, rot);
  TEN_T2M(matIn, tenIn);
  ELL_3M_MUL(tmp, matIn, rotT);
  ELL_3M_MUL(matOut, rot, tmp);
  TEN_M2T_TT(tenOut, float, matOut);
  tenOut[0] = tenIn[0];
  return;
}

/*
******** tenTensorCheck()
**
** describes if the given nrrd could be a diffusion tensor dataset,
** either the measured DWI data or the calculated tensor data.
**
** We've been using 7 floats for BOTH kinds of tensor data- both the
** measured DWI and the calculated tensor matrices.  The measured data
** comes as one anatomical image and 6 DWIs.  For the calculated tensors,
** in addition to the 6 matrix components, we keep a "threshold" value
** which is based on the sum of all the DWIs, which describes if the
** calculated tensor means anything or not.
**
** useBiff controls if biff is used to describe the problem
*/
int
tenTensorCheck(const Nrrd *nin, int wantType, int want4D, int useBiff) {
  static const char me[]="tenTensorCheck";

  if (!nin) {
    if (useBiff) biffAddf(TEN, "%s: got NULL pointer", me);
    return 1;
  }
  if (wantType) {
    if (nin->type != wantType) {
      if (useBiff) biffAddf(TEN, "%s: wanted type %s, got type %s", me,
                            airEnumStr(nrrdType, wantType),
                            airEnumStr(nrrdType, nin->type));
      return 1;
    }
  }
  else {
    if (!(nin->type == nrrdTypeFloat || nin->type == nrrdTypeShort)) {
      if (useBiff) biffAddf(TEN, "%s: need data of type float or short", me);
      return 1;
    }
  }
  if (want4D && !(4 == nin->dim)) {
    if (useBiff)
      biffAddf(TEN, "%s: given dimension is %d, not 4", me, nin->dim);
    return 1;
  }
  if (!(7 == nin->axis[0].size)) {
    if (useBiff) {
      char stmp[AIR_STRLEN_SMALL];
      biffAddf(TEN, "%s: axis 0 has size %s, not 7", me,
               airSprintSize_t(stmp, nin->axis[0].size));
    }
    return 1;
  }
  return 0;
}

int
tenMeasurementFrameReduce(Nrrd *nout, const Nrrd *nin) {
  static const char me[]="tenMeasurementFrameReduce";
  double MF[9], MFT[9], tenMeasr[9], tenWorld[9];
  float *tdata;
  size_t ii, nn;
  unsigned int si, sj;

  if (!(nout && nin)) {
    biffAddf(TEN, "%s: got NULL pointer", me);
    return 1;
  }
  if (tenTensorCheck(nin, nrrdTypeFloat, AIR_TRUE, AIR_TRUE)) {
    biffAddf(TEN, "%s: ", me);
    return 1;
  }
  if (3 != nin->spaceDim) {
    biffAddf(TEN, "%s: input nrrd needs 3-D (not %u-D) space dimension",
             me, nin->spaceDim);
    return 1;
  }
  /*
   [0]  [1]  [2]     [0][0]   [1][0]   [2][0]
   [3]  [4]  [5]  =  [0][1]   [1][1]   [2][1]
   [6]  [7]  [8]     [0][2]   [1][2]   [2][2]
  */
  MF[0] = nin->measurementFrame[0][0];
  MF[1] = nin->measurementFrame[1][0];
  MF[2] = nin->measurementFrame[2][0];
  MF[3] = nin->measurementFrame[0][1];
  MF[4] = nin->measurementFrame[1][1];
  MF[5] = nin->measurementFrame[2][1];
  MF[6] = nin->measurementFrame[0][2];
  MF[7] = nin->measurementFrame[1][2];
  MF[8] = nin->measurementFrame[2][2];
  if (!ELL_3M_EXISTS(MF)) {
    biffAddf(TEN, "%s: 3x3 measurement frame doesn't exist", me);
    return 1;
  }
  ELL_3M_TRANSPOSE(MFT, MF);

  if (nout != nin) {
    if (nrrdCopy(nout, nin)) {
      biffAddf(TEN, "%s: trouble with initial copy", me);
      return 1;
    }
  }
  nn = nrrdElementNumber(nout)/nout->axis[0].size;
  tdata = (float*)(nout->data);
  for (ii=0; ii<nn; ii++) {
    TEN_T2M(tenMeasr, tdata);
    ell_3m_mul_d(tenWorld, MF, tenMeasr);
    ell_3m_mul_d(tenWorld, tenWorld, MFT);
    TEN_M2T_TT(tdata, float, tenWorld);
    tdata += 7;
  }
  for (si=0; si<NRRD_SPACE_DIM_MAX; si++) {
    for (sj=0; sj<NRRD_SPACE_DIM_MAX; sj++) {
      nout->measurementFrame[si][sj] = AIR_NAN;
    }
  }
  for (si=0; si<3; si++) {
    for (sj=0; sj<3; sj++) {
      nout->measurementFrame[si][sj] = (si == sj);
    }
  }

  return 0;
}

int
tenExpand2D(Nrrd *nout, const Nrrd *nin, double scale, double thresh) {
  static const char me[]="tenExpand2D";
  size_t N, I, sx, sy;
  float *masked, *redund;

  if (!( nout && nin && AIR_EXISTS(thresh) )) {
    biffAddf(TEN, "%s: got NULL pointer or non-existent threshold", me);
    return 1;
  }
  if (nout == nin) {
    biffAddf(TEN, "%s: sorry, need different nrrds for input and output", me);
    return 1;
  }
  /* HEY copy and paste and tweak of tenTensorCheck */
  if (!nin) {
    biffAddf(TEN, "%s: got NULL pointer", me);
    return 1;
  }
  if (nin->type != nrrdTypeFloat) {
    biffAddf(TEN, "%s: wanted type %s, got type %s", me,
             airEnumStr(nrrdType, nrrdTypeFloat),
             airEnumStr(nrrdType, nin->type));
    return 1;
  } else {
    if (!(nin->type == nrrdTypeFloat || nin->type == nrrdTypeShort)) {
      biffAddf(TEN, "%s: need data of type float or short", me);
      return 1;
    }
  }
  if (3 != nin->dim) {
    biffAddf(TEN, "%s: given dimension is %u, not 3", me, nin->dim);
    return 1;
  }
  if (!(4 == nin->axis[0].size)) {
    char stmp[AIR_STRLEN_SMALL];
    biffAddf(TEN, "%s: axis 0 has size %s, not 4", me,
               airSprintSize_t(stmp, nin->axis[0].size));
    return 1;
  }

  sx = nin->axis[1].size;
  sy = nin->axis[2].size;
  N = sx*sy;
  if (nrrdMaybeAlloc_va(nout, nrrdTypeFloat, 3,
                        AIR_CAST(size_t, 4), sx, sy)) {
    biffMovef(TEN, NRRD, "%s: trouble", me);
    return 1;
  }
  for (I=0; I<=N-1; I++) {
    masked = (float*)(nin->data) + I*4;
    redund = (float*)(nout->data) + I*4;
    if (masked[0] < thresh) {
      ELL_4V_ZERO_SET(redund);
      continue;
    }
    redund[0] = masked[1];
    redund[1] = masked[2];
    redund[2] = masked[2];
    redund[3] = masked[3];
    ELL_4V_SCALE(redund, AIR_CAST(float, scale), redund);
  }
  if (nrrdAxisInfoCopy(nout, nin, NULL,
                       NRRD_AXIS_INFO_SIZE_BIT)) {
    biffMovef(TEN, NRRD, "%s: trouble", me);
    return 1;
  }
  /* by call above we just copied axis-0 kind, which might be wrong;
     we actually know the output kind now, so we might as well set it */
  nout->axis[0].kind = nrrdKind2DMatrix;
  if (nrrdBasicInfoCopy(nout, nin,
                        NRRD_BASIC_INFO_ALL ^ NRRD_BASIC_INFO_SPACE)) {
    biffAddf(TEN, "%s:", me);
    return 1;
  }
  return 0;
}

int
tenExpand(Nrrd *nout, const Nrrd *nin, double scale, double thresh) {
  static const char me[]="tenExpand";
  size_t N, I, sx, sy, sz;
  float *seven, *nine;

  if (!( nout && nin && AIR_EXISTS(thresh) )) {
    biffAddf(TEN, "%s: got NULL pointer or non-existent threshold", me);
    return 1;
  }
  if (nout == nin) {
    biffAddf(TEN, "%s: sorry, need different nrrds for input and output", me);
    return 1;
  }
  if (tenTensorCheck(nin, nrrdTypeFloat, AIR_TRUE, AIR_TRUE)) {
    biffAddf(TEN, "%s: ", me);
    return 1;
  }

  sx = nin->axis[1].size;
  sy = nin->axis[2].size;
  sz = nin->axis[3].size;
  N = sx*sy*sz;
  if (nrrdMaybeAlloc_va(nout, nrrdTypeFloat, 4,
                        AIR_CAST(size_t, 9), sx, sy, sz)) {
    biffMovef(TEN, NRRD, "%s: trouble", me);
    return 1;
  }
  for (I=0; I<=N-1; I++) {
    seven = (float*)(nin->data) + I*7;
    nine = (float*)(nout->data) + I*9;
    if (seven[0] < thresh) {
      ELL_3M_ZERO_SET(nine);
      continue;
    }
    TEN_T2M(nine, seven);
    ELL_3M_SCALE(nine, AIR_CAST(float, scale), nine);
  }
  if (nrrdAxisInfoCopy(nout, nin, NULL,
                       NRRD_AXIS_INFO_SIZE_BIT)) {
    biffMovef(TEN, NRRD, "%s: trouble", me);
    return 1;
  }
  /* by call above we just copied axis-0 kind, which might be wrong;
     we actually know the output kind now, so we might as well set it */
  nout->axis[0].kind = nrrdKind3DMatrix;
  if (nrrdBasicInfoCopy(nout, nin,
                        NRRD_BASIC_INFO_ALL ^ NRRD_BASIC_INFO_SPACE)) {
    biffAddf(TEN, "%s:", me);
    return 1;
  }
  /* Tue Sep 13 18:36:45 EDT 2005: why did I do this?
  nout->axis[0].label = (char *)airFree(nout->axis[0].label);
  nout->axis[0].label = airStrdup("matrix");
  */

  return 0;
}

int
tenShrink(Nrrd *tseven, const Nrrd *nconf, const Nrrd *tnine) {
  static const char me[]="tenShrink";
  size_t I, N, sx, sy, sz;
  float *seven, *conf, *nine;

  if (!(tseven && tnine)) {
    biffAddf(TEN, "%s: got NULL pointer", me);
    return 1;
  }
  if (tseven == tnine) {
    biffAddf(TEN, "%s: sorry, need different nrrds for input and output", me);
    return 1;
  }
  if (!( nrrdTypeFloat == tnine->type &&
         4 == tnine->dim &&
         9 == tnine->axis[0].size )) {
    char stmp[AIR_STRLEN_SMALL];
    biffAddf(TEN, "%s: type not %s (was %s) or dim not 4 (was %d) "
             "or first axis size not 9 (was %s)", me,
             airEnumStr(nrrdType, nrrdTypeFloat),
             airEnumStr(nrrdType, tnine->type), tnine->dim,
             airSprintSize_t(stmp, tnine->axis[0].size));
    return 1;
  }
  sx = tnine->axis[1].size;
  sy = tnine->axis[2].size;
  sz = tnine->axis[3].size;
  if (nconf) {
    if (!( nrrdTypeFloat == nconf->type &&
           3 == nconf->dim &&
           sx == nconf->axis[0].size &&
           sy == nconf->axis[1].size &&
           sz == nconf->axis[2].size )) {
      biffAddf(TEN, "%s: confidence type not %s (was %s) or dim not 3 (was %d) "
               "or dimensions didn't match tensor volume", me,
               airEnumStr(nrrdType, nrrdTypeFloat),
               airEnumStr(nrrdType, nconf->type),
               nconf->dim);
      return 1;
    }
  }
  if (nrrdMaybeAlloc_va(tseven, nrrdTypeFloat, 4,
                        AIR_CAST(size_t, 7), sx, sy, sz)) {
    biffMovef(TEN, NRRD, "%s: trouble allocating output", me);
    return 1;
  }
  seven = (float *)tseven->data;
  conf = nconf ? (float *)nconf->data : NULL;
  nine = (float *)tnine->data;
  N = sx*sy*sz;
  for (I=0; I<N; I++) {
    TEN_M2T_TT(seven, float, nine);
    seven[0] = conf ? conf[I] : 1.0f;
    seven += 7;
    nine += 9;
  }
  if (nrrdAxisInfoCopy(tseven, tnine, NULL,
                       NRRD_AXIS_INFO_SIZE_BIT)) {
    biffMovef(TEN, NRRD, "%s: trouble", me);
    return 1;
  }
  /* by call above we just copied axis-0 kind, which might be wrong;
     we actually know the output kind now, so we might as well set it */
  tseven->axis[0].kind = nrrdKind3DMaskedSymMatrix;
  if (nrrdBasicInfoCopy(tseven, tnine,
                        NRRD_BASIC_INFO_ALL ^ NRRD_BASIC_INFO_SPACE)) {
    biffAddf(TEN, "%s:", me);
    return 1;
  }
  /* Wed Dec  3 11:22:32 EST 2008: no real need to set label string */

  return 0;
}

/*
******** tenEigensolve_f
**
** uses ell_3m_eigensolve_d to get the eigensystem of a single tensor
** disregards the confidence value t[0]
**
** return is same as ell_3m_eigensolve_d, which is same as ell_cubic
**
** NOTE: Even in the post-Teem-1.7 switch from column-major to
** row-major- its still the case that the eigenvectors are at
** evec+0, evec+3, evec+6: this means that they USED to be the
** "columns" of the matrix, and NOW they're the rows.
**
** This does NOT use biff
*/
int
tenEigensolve_f(float _eval[3], float _evec[9], const float t[7]) {
  double m[9], eval[3], evec[9], trc, iso[9];
  int ret;

  TEN_T2M(m, t);
  trc = ELL_3M_TRACE(m)/3.0;
  ELL_3M_IDENTITY_SET(iso);
  ELL_3M_SCALE_SET(iso, -trc, -trc, -trc);
  ELL_3M_ADD2(m, m, iso);
  if (_evec) {
    ret = ell_3m_eigensolve_d(eval, evec, m, AIR_TRUE);
    if (tenVerbose > 4) {
      fprintf(stderr, "---- cubic ret = %d\n", ret);
      fprintf(stderr, "tensor = {\n");
      fprintf(stderr, "    % 15.7f,\n", t[1]);
      fprintf(stderr, "    % 15.7f,\n", t[2]);
      fprintf(stderr, "    % 15.7f,\n", t[3]);
      fprintf(stderr, "    % 15.7f,\n", t[4]);
      fprintf(stderr, "    % 15.7f,\n", t[5]);
      fprintf(stderr, "    % 15.7f}\n", t[6]);
      fprintf(stderr, "roots = %d:\n", ret);
      fprintf(stderr, "    % 31.15f\n", trc + eval[0]);
      fprintf(stderr, "    % 31.15f\n", trc + eval[1]);
      fprintf(stderr, "    % 31.15f\n", trc + eval[2]);
    }
    ELL_3V_SET_TT(_eval, float, eval[0] + trc, eval[1] + trc, eval[2] + trc);
    ELL_3M_COPY_TT(_evec, float, evec);
    if (ell_cubic_root_single_double == ret) {
      /* this was added to fix a stupid problem with very nearly
         isotropic glyphs, used for demonstration figures */
      if (eval[0] == eval[1]) {
        ELL_3V_CROSS(_evec+6, _evec+0, _evec+3);
      } else {
        ELL_3V_CROSS(_evec+0, _evec+3, _evec+6);
      }
    }
    if ((tenVerbose > 1) && _eval[2] < 0) {
      fprintf(stderr, "tenEigensolve_f -------------\n");
      fprintf(stderr, "% 15.7f % 15.7f % 15.7f\n",
              t[1], t[2], t[3]);
      fprintf(stderr, "% 15.7f % 15.7f % 15.7f\n",
              t[2], t[4], t[5]);
      fprintf(stderr, "% 15.7f % 15.7f % 15.7f\n",
              t[3], t[5], t[6]);
      fprintf(stderr, " --> % 15.7f % 15.7f % 15.7f\n",
              _eval[0], _eval[1], _eval[2]);
    }
  } else {
    /* caller only wants eigenvalues */
    ret = ell_3m_eigenvalues_d(eval, m, AIR_TRUE);
    ELL_3V_SET_TT(_eval, float, eval[0] + trc, eval[1] + trc, eval[2] + trc);
  }
  return ret;
}

/* HEY: cut and paste !! */
int
tenEigensolve_d(double _eval[3], double evec[9], const double t[7]) {
  double m[9], eval[3], trc, iso[9];
  int ret;

  TEN_T2M(m, t);
  trc = ELL_3M_TRACE(m)/3.0;
  ELL_3M_SCALE_SET(iso, -trc, -trc, -trc);
  ELL_3M_ADD2(m, m, iso);
  /*
  printf("!%s: t = %g %g %g; %g %g; %g\n", "tenEigensolve_f",
         t[1], t[2], t[3], t[4], t[5], t[6]);
  printf("!%s: m = %g %g %g; %g %g %g; %g %g %g\n", "tenEigensolve_f",
         m[0], m[1], m[2], m[3], m[4], m[5], m[6], m[7], m[8]);
  */
  if (evec) {
    ret = ell_3m_eigensolve_d(eval, evec, m, AIR_TRUE);
    ELL_3V_SET(_eval, eval[0] + trc, eval[1] + trc, eval[2] + trc);
    if (ell_cubic_root_single_double == ret) {
      /* this was added to fix a stupid problem with very nearly
         isotropic glyphs, used for demonstration figures */
      if (eval[0] == eval[1]) {
        ELL_3V_CROSS(evec+6, evec+0, evec+3);
      } else {
        ELL_3V_CROSS(evec+0, evec+3, evec+6);
      }
    }
  } else {
    /* caller only wants eigenvalues */
    ret = ell_3m_eigenvalues_d(eval, m, AIR_TRUE);
    ELL_3V_SET(_eval, eval[0] + trc, eval[1] + trc, eval[2] + trc);
  }
  return ret;
}



/*  lop A
    fprintf(stderr, "###################################  I = %d\n", (int)I);
    tenEigensolve(teval, tevec, out);
    fprintf(stderr, "evals: (%g %g %g) %g %g %g --> %g %g %g\n",
            AIR_ABS(eval[0] - teval[0]) + 1,
            AIR_ABS(eval[1] - teval[1]) + 1,
            AIR_ABS(eval[2] - teval[2]) + 1,
            eval[0], eval[1], eval[2],
            teval[0], teval[1], teval[2]);
    fprintf(stderr, "   tevec lens: %g %g %g\n", ELL_3V_LEN(tevec+3*0),
            ELL_3V_LEN(tevec+3*1), ELL_3V_LEN(tevec+3*2));
    ELL_3V_CROSS(tmp1, evec+3*0, evec+3*1); tmp2[0] = ELL_3V_LEN(tmp1);
    ELL_3V_CROSS(tmp1, evec+3*0, evec+3*2); tmp2[1] = ELL_3V_LEN(tmp1);
    ELL_3V_CROSS(tmp1, evec+3*1, evec+3*2); tmp2[2] = ELL_3V_LEN(tmp1);
    fprintf(stderr, "   evec[0] = %g %g %g\n",
            (evec+3*0)[0], (evec+3*0)[1], (evec+3*0)[2]);
    fprintf(stderr, "   evec[1] = %g %g %g\n",
            (evec+3*1)[0], (evec+3*1)[1], (evec+3*1)[2]);
    fprintf(stderr, "   evec[2] = %g %g %g\n",
            (evec+3*2)[0], (evec+3*2)[1], (evec+3*2)[2]);
    fprintf(stderr, "   evec crosses: %g %g %g\n",
            tmp2[0], tmp2[1], tmp2[2]);
    ELL_3V_CROSS(tmp1, tevec+3*0, tevec+3*1); tmp2[0] = ELL_3V_LEN(tmp1);
    ELL_3V_CROSS(tmp1, tevec+3*0, tevec+3*2); tmp2[1] = ELL_3V_LEN(tmp1);
    ELL_3V_CROSS(tmp1, tevec+3*1, tevec+3*2); tmp2[2] = ELL_3V_LEN(tmp1);
    fprintf(stderr, "   tevec[0] = %g %g %g\n",
            (tevec+3*0)[0], (tevec+3*0)[1], (tevec+3*0)[2]);
    fprintf(stderr, "   tevec[1] = %g %g %g\n",
            (tevec+3*1)[0], (tevec+3*1)[1], (tevec+3*1)[2]);
    fprintf(stderr, "   tevec[2] = %g %g %g\n",
            (tevec+3*2)[0], (tevec+3*2)[1], (tevec+3*2)[2]);
    fprintf(stderr, "   tevec crosses: %g %g %g\n",
            tmp2[0], tmp2[1], tmp2[2]);
    if (tmp2[1] < 0.5) {
      fprintf(stderr, "(panic)\n");
      exit(0);
    }
*/

void
tenMakeSingle_f(float ten[7], float conf, const float eval[3], const float evec[9]) {
  double tmpMat1[9], tmpMat2[9], diag[9], evecT[9];

  ELL_3M_ZERO_SET(diag);
  ELL_3M_DIAG_SET(diag, eval[0], eval[1], eval[2]);
  ELL_3M_TRANSPOSE(evecT, evec);
  ELL_3M_MUL(tmpMat1, diag, evec);
  ELL_3M_MUL(tmpMat2, evecT, tmpMat1);
  ten[0] = conf;
  TEN_M2T_TT(ten, float, tmpMat2);
  return;
}

/* HEY: copy and paste! */
void
tenMakeSingle_d(double ten[7], double conf, const double eval[3], const double evec[9]) {
  double tmpMat1[9], tmpMat2[9], diag[9], evecT[9];

  ELL_3M_ZERO_SET(diag);
  ELL_3M_DIAG_SET(diag, eval[0], eval[1], eval[2]);
  ELL_3M_TRANSPOSE(evecT, evec);
  ELL_3M_MUL(tmpMat1, diag, evec);
  ELL_3M_MUL(tmpMat2, evecT, tmpMat1);
  ten[0] = conf;
  TEN_M2T_TT(ten, float, tmpMat2);
  return;
}

/*
******** tenMake
**
** create a tensor nrrd from nrrds of confidence, eigenvalues, and
** eigenvectors
*/
int
tenMake(Nrrd *nout, const Nrrd *nconf, const Nrrd *neval, const Nrrd *nevec) {
  static const char me[]="tenTensorMake";
  size_t I, N, sx, sy, sz;
  float *out, *conf, *eval, *evec;
  int map[4];
  /* float teval[3], tevec[9], tmp1[3], tmp2[3]; */
  char stmp[7][AIR_STRLEN_SMALL];

  if (!(nout && nconf && neval && nevec)) {
    biffAddf(TEN, "%s: got NULL pointer", me);
    return 1;
  }
  if (nrrdCheck(nconf) || nrrdCheck(neval) || nrrdCheck(nevec)) {
    biffMovef(TEN, NRRD, "%s: didn't get three valid nrrds", me);
    return 1;
  }
  if (!( 3 == nconf->dim && nrrdTypeFloat == nconf->type )) {
    biffAddf(TEN, "%s: first nrrd not a confidence volume "
             "(dim = %d, not 3; type = %s, not %s)", me,
             nconf->dim, airEnumStr(nrrdType, nconf->type),
             airEnumStr(nrrdType, nrrdTypeFloat));
    return 1;
  }
  sx = nconf->axis[0].size;
  sy = nconf->axis[1].size;
  sz = nconf->axis[2].size;
  if (!( 4 == neval->dim && 4 == nevec->dim &&
         nrrdTypeFloat == neval->type &&
         nrrdTypeFloat == nevec->type )) {
    biffAddf(TEN, "%s: second and third nrrd aren't both 4-D (%d and %d) "
             "and type %s (%s and %s)",
             me, neval->dim, nevec->dim,
             airEnumStr(nrrdType, nrrdTypeFloat),
             airEnumStr(nrrdType, neval->type),
             airEnumStr(nrrdType, nevec->type));
    return 1;
  }
  if (!( 3 == neval->axis[0].size &&
         sx == neval->axis[1].size &&
         sy == neval->axis[2].size &&
         sz == neval->axis[3].size )) {
    biffAddf(TEN, "%s: second nrrd sizes wrong: "
             "(%s,%s,%s,%s) not (3,%s,%s,%s)", me,
             airSprintSize_t(stmp[0], neval->axis[0].size),
             airSprintSize_t(stmp[1], neval->axis[1].size),
             airSprintSize_t(stmp[2], neval->axis[2].size),
             airSprintSize_t(stmp[3], neval->axis[3].size),
             airSprintSize_t(stmp[4], sx),
             airSprintSize_t(stmp[5], sy),
             airSprintSize_t(stmp[6], sz));
    return 1;
  }
  if (!( 9 == nevec->axis[0].size &&
         sx == nevec->axis[1].size &&
         sy == nevec->axis[2].size &&
         sz == nevec->axis[3].size )) {
    biffAddf(TEN, "%s: third nrrd sizes wrong: "
             "(%s,%s,%s,%s) not (9,%s,%s,%s)", me,
             airSprintSize_t(stmp[0], nevec->axis[0].size),
             airSprintSize_t(stmp[1], nevec->axis[1].size),
             airSprintSize_t(stmp[2], nevec->axis[2].size),
             airSprintSize_t(stmp[3], nevec->axis[3].size),
             airSprintSize_t(stmp[4], sx),
             airSprintSize_t(stmp[5], sy),
             airSprintSize_t(stmp[6], sz));
    return 1;
  }

  /* finally */
  if (nrrdMaybeAlloc_va(nout, nrrdTypeFloat, 4,
                        AIR_CAST(size_t, 7), sx, sy, sz)) {
    biffMovef(TEN, NRRD, "%s: couldn't allocate output", me);
    return 1;
  }
  N = sx*sy*sz;
  conf = (float *)(nconf->data);
  eval = (float *)neval->data;
  evec = (float *)nevec->data;
  out = (float *)nout->data;
  for (I=0; I<N; I++) {
    tenMakeSingle_f(out, conf[I], eval, evec);
    /* lop A */
    out += 7;
    eval += 3;
    evec += 9;
  }
  ELL_4V_SET(map, -1, 0, 1, 2);
  if (nrrdAxisInfoCopy(nout, nconf, map, NRRD_AXIS_INFO_SIZE_BIT)) {
    biffMovef(TEN, NRRD, "%s: trouble", me);
    return 1;
  }
  nout->axis[0].label = (char *)airFree(nout->axis[0].label);
  nout->axis[0].label = airStrdup("tensor");
  nout->axis[0].kind = nrrdKind3DMaskedSymMatrix;
  if (nrrdBasicInfoCopy(nout, nconf,
                        NRRD_BASIC_INFO_DATA_BIT
                        | NRRD_BASIC_INFO_TYPE_BIT
                        | NRRD_BASIC_INFO_BLOCKSIZE_BIT
                        | NRRD_BASIC_INFO_DIMENSION_BIT
                        | NRRD_BASIC_INFO_CONTENT_BIT
                        | NRRD_BASIC_INFO_COMMENTS_BIT
                        | (nrrdStateKeyValuePairsPropagate
                           ? 0
                           : NRRD_BASIC_INFO_KEYVALUEPAIRS_BIT))) {
    biffMovef(TEN, NRRD, "%s:", me);
    return 1;
  }

  return 0;
}

int
tenSlice(Nrrd *nout, const Nrrd *nten, unsigned int axis,
         size_t pos, unsigned int dim) {
  static const char me[]="tenSlice";
  Nrrd *nslice, **ncoeff=NULL;
  int ci[4];
  airArray *mop;
  char stmp[2][AIR_STRLEN_SMALL];

  if (!(nout && nten)) {
    biffAddf(TEN, "%s: got NULL pointer", me);
    return 1;
  }
  if (tenTensorCheck(nten, nrrdTypeDefault, AIR_TRUE, AIR_TRUE)) {
    biffAddf(TEN, "%s: didn't get a valid tensor field", me);
    return 1;
  }
  if (!(2 == dim || 3 == dim)) {
    biffAddf(TEN, "%s: given dim (%d) not 2 or 3", me, dim);
    return 1;
  }
  if (!( axis <= 2 )) {
    biffAddf(TEN, "%s: axis %u not in valid range [0,1,2]", me, axis);
    return 1;
  }
  if (!( pos < nten->axis[1+axis].size )) {
    biffAddf(TEN, "%s: slice position %s not in valid range [0..%s]", me,
             airSprintSize_t(stmp[0], pos),
             airSprintSize_t(stmp[1], nten->axis[1+axis].size-1));
    return 1;
  }

  /*
  ** threshold        0
  ** Dxx Dxy Dxz      1   2   3
  ** Dxy Dyy Dyz  =  (2)  4   5
  ** Dxz Dyz Dzz     (3) (5)  6
  */
  mop = airMopNew();
  airMopAdd(mop, nslice=nrrdNew(), (airMopper)nrrdNuke, airMopAlways);
  if (3 == dim) {
    if (nrrdSlice(nslice, nten, axis+1, pos)
        || nrrdAxesInsert(nout, nslice, axis+1)) {
      biffMovef(TEN, NRRD, "%s: trouble making slice", me);
      airMopError(mop); return 1;
    }
  } else {
    /* HEY: this used to be ncoeff[4], but its passing to nrrdJoin caused
       "dereferencing type-punned pointer might break strict-aliasing rules"
       warning; GLK not sure how else to fix it */
    ncoeff = AIR_CALLOC(4, Nrrd*);
    airMopAdd(mop, ncoeff, airFree, airMopAlways);
    airMopAdd(mop, ncoeff[0]=nrrdNew(), (airMopper)nrrdNuke, airMopAlways);
    airMopAdd(mop, ncoeff[1]=nrrdNew(), (airMopper)nrrdNuke, airMopAlways);
    airMopAdd(mop, ncoeff[2]=nrrdNew(), (airMopper)nrrdNuke, airMopAlways);
    airMopAdd(mop, ncoeff[3]=nrrdNew(), (airMopper)nrrdNuke, airMopAlways);
    switch(axis) {
    case 0:
      ELL_4V_SET(ci, 0, 4, 5, 6);
      break;
    case 1:
      ELL_4V_SET(ci, 0, 1, 3, 6);
      break;
    case 2:
      ELL_4V_SET(ci, 0, 1, 2, 4);
      break;
    default:
      biffAddf(TEN, "%s: axis %d bogus", me, axis);
      airMopError(mop); return 1;
      break;
    }
    if (nrrdSlice(nslice, nten, axis+1, pos)
        || nrrdSlice(ncoeff[0], nslice, 0, ci[0])
        || nrrdSlice(ncoeff[1], nslice, 0, ci[1])
        || nrrdSlice(ncoeff[2], nslice, 0, ci[2])
        || nrrdSlice(ncoeff[3], nslice, 0, ci[3])
        || nrrdJoin(nout, (const Nrrd *const*)ncoeff, 4, 0, AIR_TRUE)) {
      biffMovef(TEN, NRRD, "%s: trouble collecting coefficients", me);
      airMopError(mop); return 1;
    }
    nout->axis[0].kind = nrrdKind2DMaskedSymMatrix;
  }

  airMopOkay(mop);
  return 0;
}

#define Txx (ten[1])
#define Txy (ten[2])
#define Txz (ten[3])
#define Tyy (ten[4])
#define Tyz (ten[5])
#define Tzz (ten[6])

#define SQRT_1_OVER_2 0.70710678118654752440
#define SQRT_1_OVER_3 0.57735026918962576450
#define SQRT_2_OVER_3 0.81649658092772603272
#define SQRT_1_OVER_6 0.40824829046386301635

/*
** very special purpose: compute tensor-valued gradient
** of eigenvalue skewness, but have to be given two
** other invariant gradients, NORMALIZED, to which
** eigenvalue skewness should be perpendicular
*/
void
_tenEvalSkewnessGradient_d(double skw[7],
                           const double perp1[7],
                           const double perp2[7],
                           const double ten[7],
                           const double minnorm) {
  /* static const char me[]="_tenEvalSkewnessGradient_d"; */
  double dot, scl, norm;

  /* start with gradient of determinant */
  TEN_T_SET(skw, ten[0],
            Tyy*Tzz - Tyz*Tyz, Txz*Tyz - Txy*Tzz, Txy*Tyz - Txz*Tyy,
            Txx*Tzz - Txz*Txz, Txy*Txz - Tyz*Txx,
            Txx*Tyy - Txy*Txy);
  /* this normalization is so that minnorm comparison below
     is meaningful regardless of scale of input */
  /* HEY: should have better handling of case where determinant
     gradient magnitude is near zero */
  scl = 1.0/(DBL_EPSILON + TEN_T_NORM(skw));
  TEN_T_SCALE(skw, scl, skw);
  dot = TEN_T_DOT(skw, perp1);
  TEN_T_SCALE_INCR(skw, -dot, perp1);
  dot = TEN_T_DOT(skw, perp2);
  TEN_T_SCALE_INCR(skw, -dot, perp2);
  norm = TEN_T_NORM(skw);
  if (norm < minnorm) {
    /* skw is at an extremum, should diagonalize */
    double eval[3], evec[9], matA[9], matB[9], matC[9], mev, third;

    tenEigensolve_d(eval, evec, ten);
    mev = (eval[0] + eval[1] + eval[2])/3;
    eval[0] -= mev;
    eval[1] -= mev;
    eval[2] -= mev;
    third = (eval[0]*eval[0]*eval[0]
             + eval[1]*eval[1]*eval[1]
             + eval[2]*eval[2]*eval[2])/3;
    if (third > 0) {
      /* skw is positive: linear: eval[1] = eval[2] */
      ELL_3MV_OUTER(matA, evec + 1*3, evec + 1*3);
      ELL_3MV_OUTER(matB, evec + 2*3, evec + 2*3);
    } else {
      /* skw is negative: planar: eval[0] = eval[1] */
      ELL_3MV_OUTER(matA, evec + 0*3, evec + 0*3);
      ELL_3MV_OUTER(matB, evec + 1*3, evec + 1*3);
    }
    ELL_3M_SCALE_ADD2(matC, SQRT_1_OVER_2, matA, -SQRT_1_OVER_2, matB);
    TEN_M2T(skw, matC);
    /* have to make sure that this contrived tensor
       is indeed orthogonal to perp1 and perp2 */
    dot = TEN_T_DOT(skw, perp1);
    TEN_T_SCALE_INCR(skw, -dot, perp1);
    dot = TEN_T_DOT(skw, perp2);
    TEN_T_SCALE_INCR(skw, -dot, perp2);
    norm = TEN_T_NORM(skw);
  }
  TEN_T_SCALE(skw, 1.0/norm, skw);
  return;
}

void
tenInvariantGradientsK_d(double mu1[7], double mu2[7], double skw[7],
                         const double ten[7], const double minnorm) {
  double dot, norm;

  TEN_T_SET(mu1, ten[0],
            SQRT_1_OVER_3, 0, 0,
            SQRT_1_OVER_3, 0,
            SQRT_1_OVER_3);

  TEN_T_SET(mu2, ten[0],
            2*Txx - Tyy - Tzz, 3*Txy, 3*Txz,
            2*Tyy - Txx - Tzz, 3*Tyz,
            2*Tzz - Txx - Tyy);
  norm = TEN_T_NORM(mu2);
  if (norm < minnorm) {
    /* they gave us a diagonal matrix */
    TEN_T_SET(mu2, ten[0],
              SQRT_2_OVER_3, 0, 0,
              -SQRT_1_OVER_6, 0,
              -SQRT_1_OVER_6);
  }
  /* next two lines shouldn't really be necessary */
  dot = TEN_T_DOT(mu2, mu1);
  TEN_T_SCALE_INCR(mu2, -dot, mu1);
  norm = TEN_T_NORM(mu2);
  TEN_T_SCALE(mu2, 1.0/norm, mu2);
  _tenEvalSkewnessGradient_d(skw, mu1, mu2, ten, minnorm);

  return;
}

void
tenInvariantGradientsR_d(double R1[7], double R2[7], double R3[7],
                         const double ten[7], const double minnorm) {
  double dot, dev[7], norm, tenNorm, devNorm;

  TEN_T_COPY(R1, ten);
  tenNorm = norm = TEN_T_NORM(R1);
  if (norm < minnorm) {
    TEN_T_SET(R1, ten[0],
              SQRT_1_OVER_3, 0, 0,
              SQRT_1_OVER_3, 0,
              SQRT_1_OVER_3);
    norm = TEN_T_NORM(R1);
  }
  TEN_T_SCALE(R1, 1.0/norm, R1);

  TEN_T_SET(dev, ten[0],
            (2*Txx - Tyy - Tzz)/3, Txy, Txz,
            (2*Tyy - Txx - Tzz)/3, Tyz,
            (2*Tzz - Txx - Tyy)/3);
  devNorm = TEN_T_NORM(dev);
  if (devNorm < minnorm) {
    /* they gave us a diagonal matrix */
    TEN_T_SET(R2, ten[0],
              SQRT_2_OVER_3, 0, 0,
              -SQRT_1_OVER_6, 0,
              -SQRT_1_OVER_6);
  } else {
    TEN_T_SCALE_ADD2(R2, tenNorm/devNorm, dev, -devNorm/tenNorm, ten);
  }
  /* next two lines shouldn't really be necessary */
  dot = TEN_T_DOT(R2, R1);
  TEN_T_SCALE_INCR(R2, -dot, R1);
  norm = TEN_T_NORM(R2);
  if (norm < minnorm) {
    /* Traceless tensor */
    TEN_T_SET(R2, ten[0],
              SQRT_2_OVER_3, 0, 0,
              -SQRT_1_OVER_6, 0,
              -SQRT_1_OVER_6);
  } else {
    TEN_T_SCALE(R2, 1.0/norm, R2);
  }
  _tenEvalSkewnessGradient_d(R3, R1, R2, ten, minnorm);

  return;
}

/*
** evec must be pre-computed (unit-length eigenvectors) and given to us
*/
void
tenRotationTangents_d(double phi1[7],
                      double phi2[7],
                      double phi3[7],
                      const double evec[9]) {
  double outA[9], outB[9], mat[9];

  if (phi1) {
    phi1[0] = 1.0;
    ELL_3MV_OUTER(outA, evec + 1*3, evec + 2*3);
    ELL_3MV_OUTER(outB, evec + 2*3, evec + 1*3);
    ELL_3M_SCALE_ADD2(mat, SQRT_1_OVER_2, outA, SQRT_1_OVER_2, outB);
    TEN_M2T(phi1, mat);
  }

  if (phi2) {
    phi2[0] = 1.0;
    ELL_3MV_OUTER(outA, evec + 0*3, evec + 2*3);
    ELL_3MV_OUTER(outB, evec + 2*3, evec + 0*3);
    ELL_3M_SCALE_ADD2(mat, SQRT_1_OVER_2, outA, SQRT_1_OVER_2, outB);
    TEN_M2T(phi2, mat);
  }

  if (phi3) {
    phi3[0] = 1.0;
    ELL_3MV_OUTER(outA, evec + 0*3, evec + 1*3);
    ELL_3MV_OUTER(outB, evec + 1*3, evec + 0*3);
    ELL_3M_SCALE_ADD2(mat, SQRT_1_OVER_2, outA, SQRT_1_OVER_2, outB);
    TEN_M2T(phi3, mat);
  }

  return;
}

void
tenInv_f(float inv[7], const float ten[7]) {
  float det;

  TEN_T_INV(inv, ten, det);
}

void
tenInv_d(double inv[7], const double ten[7]) {
  double det;

  TEN_T_INV(inv, ten, det);
}

void
tenLogSingle_d(double logten[7], const double ten[7]) {
  double eval[3], evec[9];
  unsigned int ii;

  tenEigensolve_d(eval, evec, ten);
  for (ii=0; ii<3; ii++) {
    eval[ii] = log(eval[ii]);
    if (!AIR_EXISTS(eval[ii])) {
      eval[ii] = -FLT_MAX;  /* making stuff up */
    }
  }
  tenMakeSingle_d(logten, ten[0], eval, evec);
}

void
tenLogSingle_f(float logten[7], const float ten[7]) {
  float eval[3], evec[9];
  unsigned int ii;

  tenEigensolve_f(eval, evec, ten);
  for (ii=0; ii<3; ii++) {
    eval[ii] = AIR_CAST(float, log(eval[ii]));
    if (!AIR_EXISTS(eval[ii])) {
      eval[ii] = -FLT_MAX/10; /* still making stuff up */
    }
  }
  tenMakeSingle_f(logten, ten[0], eval, evec);
}

void
tenExpSingle_d(double expten[7], const double ten[7]) {
  double eval[3], evec[9];
  unsigned int ii;

  tenEigensolve_d(eval, evec, ten);
  for (ii=0; ii<3; ii++) {
    eval[ii] = exp(eval[ii]);
  }
  tenMakeSingle_d(expten, ten[0], eval, evec);
}

void
tenExpSingle_f(float expten[7], const float ten[7]) {
  float eval[3], evec[9];
  unsigned int ii;

  tenEigensolve_f(eval, evec, ten);
  for (ii=0; ii<3; ii++) {
    eval[ii] = AIR_CAST(float, exp(eval[ii]));
  }
  tenMakeSingle_f(expten, ten[0], eval, evec);
}

void
tenSqrtSingle_d(double sqrtten[7], const double ten[7]) {
  double eval[3], evec[9];
  unsigned int ii;

  tenEigensolve_d(eval, evec, ten);
  for (ii=0; ii<3; ii++) {
    eval[ii] = eval[ii] > 0 ? sqrt(eval[ii]) : 0;
  }
  tenMakeSingle_d(sqrtten, ten[0], eval, evec);
}

void
tenSqrtSingle_f(float sqrtten[7], const float ten[7]) {
  float eval[3], evec[9];
  unsigned int ii;

  tenEigensolve_f(eval, evec, ten);
  for (ii=0; ii<3; ii++) {
    eval[ii] = AIR_CAST(float, eval[ii] > 0 ? sqrt(eval[ii]) : 0);
  }
  tenMakeSingle_f(sqrtten, ten[0], eval, evec);
}

void
tenPowSingle_d(double powten[7], const double ten[7], double power) {
  double eval[3], _eval[3], evec[9];
  unsigned int ii;

  tenEigensolve_d(_eval, evec, ten);
  for (ii=0; ii<3; ii++) {
    eval[ii] = pow(_eval[ii], power);
  }
  tenMakeSingle_d(powten, ten[0], eval, evec);
}

void
tenPowSingle_f(float powten[7], const float ten[7], float power) {
  float eval[3], evec[9];
  unsigned int ii;

  tenEigensolve_f(eval, evec, ten);
  for (ii=0; ii<3; ii++) {
    eval[ii] = AIR_CAST(float, pow(eval[ii], power));
  }
  tenMakeSingle_f(powten, ten[0], eval, evec);
}

double
tenDoubleContract_d(double a[7], double T[21], double b[7]) {
  double ret;

  ret = (+ 1*1*T[ 0]*a[1]*b[1] + 1*2*T[ 1]*a[2]*b[1] + 1*2*T[ 2]*a[3]*b[1] + 1*1*T[ 3]*a[4]*b[1] + 1*2*T[ 4]*a[5]*b[1] + 1*1*T[ 5]*a[6]*b[1] +
         + 2*1*T[ 1]*a[1]*b[2] + 2*2*T[ 6]*a[2]*b[2] + 2*2*T[ 7]*a[3]*b[2] + 2*1*T[ 8]*a[4]*b[2] + 2*2*T[ 9]*a[5]*b[2] + 2*1*T[10]*a[6]*b[2] +
         + 2*1*T[ 2]*a[1]*b[3] + 2*2*T[ 7]*a[2]*b[3] + 2*2*T[11]*a[3]*b[3] + 2*1*T[12]*a[4]*b[3] + 2*2*T[13]*a[5]*b[3] + 2*1*T[14]*a[6]*b[3] +
         + 1*1*T[ 3]*a[1]*b[4] + 1*2*T[ 8]*a[2]*b[4] + 1*2*T[12]*a[3]*b[4] + 1*1*T[15]*a[4]*b[4] + 1*2*T[16]*a[5]*b[4] + 1*1*T[17]*a[6]*b[4] +
         + 2*1*T[ 4]*a[1]*b[5] + 2*2*T[ 9]*a[2]*b[5] + 2*2*T[13]*a[3]*b[5] + 2*1*T[16]*a[4]*b[5] + 2*2*T[18]*a[5]*b[5] + 2*1*T[19]*a[6]*b[5] +
         + 1*1*T[ 5]*a[1]*b[6] + 1*2*T[10]*a[2]*b[6] + 1*2*T[14]*a[3]*b[6] + 1*1*T[17]*a[4]*b[6] + 1*2*T[19]*a[5]*b[6] + 1*1*T[20]*a[6]*b[6]);

  return ret;
}

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