static
tenFiberContext *
_tenFiberContextCommonNew(const Nrrd *vol, int useDwi,
double thresh, double soft, double valueMin,
int ten1method, int ten2method) {
char me[]="_tenFiberContextCommonNew", err[BIFF_STRLEN];
tenFiberContext *tfx;
gageKind *kind;
if (!( tfx = (tenFiberContext *)calloc(1, sizeof(tenFiberContext)) )) {
sprintf(err, "%s: couldn't allocate new context", me);
biffAdd(TEN, err); return NULL;
}
if (useDwi) {
Nrrd *ngrad=NULL, *nbmat=NULL;
double bval=0;
unsigned int *skip, skipNum;
tfx->useDwi = AIR_TRUE;
/* default fiber type */
tfx->fiberType = tenDwiFiberTypeUnknown;
if (tenDWMRIKeyValueParse(&ngrad, &nbmat, &bval, &skip, &skipNum, vol)) {
sprintf(err, "%s: trouble parsing DWI info", me );
biffAdd(TEN, err); return NULL;
}
if (skipNum) {
sprintf(err, "%s: sorry, can't do DWI skipping here", me);
biffAdd(TEN, err); return NULL;
}
kind = tenDwiGageKindNew();
if (tenDwiGageKindSet(kind,
thresh, soft, bval, valueMin,
ngrad, NULL,
ten1method, ten2method, 42)) {
sprintf(err, "%s: trouble setting DWI kind", me);
biffAdd(TEN, err); return NULL;
}
} else {
/* it should be a tensor volume */
tfx->useDwi = AIR_FALSE;
/* default fiber type */
tfx->fiberType = tenFiberTypeUnknown;
if (tenTensorCheck(vol, nrrdTypeUnknown, AIR_TRUE, AIR_TRUE)) {
sprintf(err, "%s: didn't get a tensor volume", me);
biffAdd(TEN, err); return NULL;
}
kind = tenGageKind;
}
if ( !(tfx->gtx = gageContextNew())
|| !(tfx->pvl = gagePerVolumeNew(tfx->gtx, vol, kind))
|| (gagePerVolumeAttach(tfx->gtx, tfx->pvl)) ) {
sprintf(err, "%s: gage trouble", me);
biffMove(TEN, err, GAGE); free(tfx); return NULL;
}
tfx->nin = vol;
tfx->ksp = nrrdKernelSpecNew();
if (nrrdKernelSpecParse(tfx->ksp, tenDefFiberKernel)) {
sprintf(err, "%s: couldn't parse tenDefFiberKernel \"%s\"",
me, tenDefFiberKernel);
biffMove(TEN, err, NRRD); return NULL;
}
if (tenFiberKernelSet(tfx, tfx->ksp->kernel, tfx->ksp->parm)) {
sprintf(err, "%s: couldn't set default kernel", me);
biffAdd(TEN, err); return NULL;
}
/* looks to GK like GK says that we must set some stop criterion */
tfx->intg = tenDefFiberIntg;
tfx->anisoStopType = tenDefFiberAnisoStopType;
tfx->anisoSpeedType = tenAnisoUnknown;
tfx->stop = 0;
tfx->anisoThresh = tenDefFiberAnisoThresh;
/* so I'm not using the normal default mechanism, shoot me */
tfx->anisoSpeedFunc[0] = 0;
tfx->anisoSpeedFunc[1] = 0;
tfx->anisoSpeedFunc[2] = 0;
tfx->maxNumSteps = tenDefFiberMaxNumSteps;
tfx->minNumSteps = 0;
tfx->useIndexSpace = tenDefFiberUseIndexSpace;
tfx->verbose = 0;
tfx->stepSize = tenDefFiberStepSize;
tfx->maxHalfLen = tenDefFiberMaxHalfLen;
tfx->minWholeLen = 0.0;
tfx->confThresh = 0.5; /* why do I even bother setting these- they'll
only get read if the right tenFiberStopSet has
been called, in which case they'll be set... */
tfx->minRadius = 1; /* above lament applies here as well */
tfx->minFraction = 0.5; /* and here */
tfx->wPunct = tenDefFiberWPunct;
GAGE_QUERY_RESET(tfx->query);
tfx->mframe[0] = vol->measurementFrame[0][0];
tfx->mframe[1] = vol->measurementFrame[1][0];
tfx->mframe[2] = vol->measurementFrame[2][0];
tfx->mframe[3] = vol->measurementFrame[0][1];
tfx->mframe[4] = vol->measurementFrame[1][1];
tfx->mframe[5] = vol->measurementFrame[2][1];
tfx->mframe[6] = vol->measurementFrame[0][2];
tfx->mframe[7] = vol->measurementFrame[1][2];
tfx->mframe[8] = vol->measurementFrame[2][2];
if (ELL_3M_EXISTS(tfx->mframe)) {
tfx->mframeUse = AIR_TRUE;
ELL_3M_TRANSPOSE(tfx->mframeT, tfx->mframe);
} else {
tfx->mframeUse = AIR_FALSE;
}
tfx->gageAnisoStop = NULL;
tfx->gageAnisoSpeed = NULL;
tfx->ten2AnisoStop = AIR_NAN;
/* ... don't really see the point of initializing the ten2 stuff here;
its properly done in tenFiberTraceSet() ... */
tfx->radius = AIR_NAN;
return tfx;
}
int
main(int argc, char *argv[]) {
gageKind *kind;
char *me, *whatS, *err, *outS, *stackSavePath;
hestParm *hparm;
hestOpt *hopt = NULL;
NrrdKernelSpec *k00, *k11, *k22, *kSS, *kSSblur;
float pos[3], lineInfo[4];
double gmc, rangeSS[2], posSS, *scalePos;
unsigned int ansLen, numSS, ninSSIdx, lineStepNum;
int what, E=0, renorm, SSrenorm, SSuniform, verbose;
const double *answer;
Nrrd *nin, **ninSS=NULL, *nout=NULL;
gageContext *ctx;
gagePerVolume *pvl;
limnPolyData *lpld=NULL;
airArray *mop;
int worldSpace;
Nrrd *ngrad=NULL, *nbmat=NULL;
double bval, eps;
unsigned int *skip, skipNum;
mop = airMopNew();
me = argv[0];
hparm = hestParmNew();
airMopAdd(mop, hparm, (airMopper)hestParmFree, airMopAlways);
hparm->elideSingleOtherType = AIR_TRUE;
hestOptAdd(&hopt, "i", "nin", airTypeOther, 1, 1, &nin, NULL,
"input volume", NULL, NULL, nrrdHestNrrd);
hestOptAdd(&hopt, "k", "kind", airTypeOther, 1, 1, &kind, NULL,
"\"kind\" of volume (\"scalar\", \"vector\", or \"tensor\")",
NULL, NULL, &probeKindHestCB);
hestOptAdd(&hopt, "p", "x y z", airTypeFloat, 3, 3, pos, NULL,
"the position in space at which to probe");
hestOptAdd(&hopt, "wsp", NULL, airTypeInt, 0, 0, &worldSpace, NULL,
"if using this option, position (\"-p\") will be in world "
"space, instead of index space (the default)");
hestOptAdd(&hopt, "pi", "lpld in", airTypeOther, 1, 1, &lpld, "",
"input polydata (overrides \"-p\")",
NULL, NULL, limnHestPolyDataLMPD);
hestOptAdd(&hopt, "pl", "x y z s", airTypeFloat, 4, 4, lineInfo, "0 0 0 0",
"probe along line, instead of at point. "
"The \"-p\" three coords are the line start point. "
"If \"s\" is zero, (x,y,z) is the line end point. "
"If \"s\" is non-zero, (x,y,z) is the line direction, "
"which is scaled to have length \"s\", "
"and then used as the step between line samples. ");
hestOptAdd(&hopt, "pln", "num", airTypeUInt, 1, 1, &lineStepNum, "0",
"if non-zero, number of steps of probing to do along line, "
"which overrides \"-p\" and \"-pi\"");
hestOptAdd(&hopt, "v", "verbosity", airTypeInt, 1, 1, &verbose, "1",
"verbosity level");
hestOptAdd(&hopt, "q", "query", airTypeString, 1, 1, &whatS, NULL,
"the quantity (scalar, vector, or matrix) to learn by probing");
hestOptAdd(&hopt, "eps", "epsilon", airTypeDouble, 1, 1, &eps, "0",
"if non-zero, and if query is a scalar, epsilon around probe "
"location where we will do discrete differences to find the "
"gradient and hessian (for debugging)");
hestOptAdd(&hopt, "k00", "kern00", airTypeOther, 1, 1, &k00,
"tent", "kernel for gageKernel00",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "k11", "kern11", airTypeOther, 1, 1, &k11,
"cubicd:1,0", "kernel for gageKernel11",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "k22", "kern22", airTypeOther, 1, 1, &k22,
"cubicdd:1,0", "kernel for gageKernel22",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "ssn", "SS #", airTypeUInt, 1, 1, &numSS,
"0", "how many scale-space samples to evaluate, or, "
"0 to turn-off all scale-space behavior");
hestOptAdd(&hopt, "ssr", "scale range", airTypeDouble, 2, 2, rangeSS,
"nan nan", "range of scales in scale-space");
hestOptAdd(&hopt, "sss", "scale save path", airTypeString, 1, 1,
&stackSavePath, "",
"give a non-empty path string (like \"./\") to save out "
"the pre-blurred volumes computed for the stack");
hestOptAdd(&hopt, "ssp", "SS pos", airTypeDouble, 1, 1, &posSS, "0",
"position at which to sample in scale-space");
hestOptAdd(&hopt, "kssblur", "kernel", airTypeOther, 1, 1, &kSSblur,
"dgauss:1,5", "blurring kernel, to sample scale space",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "kss", "kernel", airTypeOther, 1, 1, &kSS,
"tent", "kernel for reconstructing from scale space samples",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "ssrn", "ssrn", airTypeInt, 1, 1, &SSrenorm, "0",
"enable derivative normalization based on scale space");
hestOptAdd(&hopt, "ssu", NULL, airTypeInt, 0, 0, &SSuniform, NULL,
"do uniform samples along sigma, and not (by default) "
"samples according to the logarithm of diffusion time");
hestOptAdd(&hopt, "rn", NULL, airTypeInt, 0, 0, &renorm, NULL,
"renormalize kernel weights at each new sample location. "
"\"Accurate\" kernels don't need this; doing it always "
"makes things go slower");
hestOptAdd(&hopt, "gmc", "min gradmag", airTypeDouble, 1, 1, &gmc,
"0.0", "For curvature-based queries, use zero when gradient "
"magnitude is below this");
hestOptAdd(&hopt, "o", "nout", airTypeString, 1, 1, &outS, "-",
"output array, when probing on polydata vertices");
hestParseOrDie(hopt, argc-1, argv+1, hparm,
me, probeInfo, AIR_TRUE, AIR_TRUE, AIR_TRUE);
airMopAdd(mop, hopt, (airMopper)hestOptFree, airMopAlways);
airMopAdd(mop, hopt, (airMopper)hestParseFree, airMopAlways);
what = airEnumVal(kind->enm, whatS);
if (!what) {
/* 0 indeed always means "unknown" for any gageKind */
fprintf(stderr, "%s: couldn't parse \"%s\" as measure of \"%s\" volume\n",
me, whatS, kind->name);
hestUsage(stderr, hopt, me, hparm);
hestGlossary(stderr, hopt, hparm);
airMopError(mop);
return 1;
}
if (ELL_4V_LEN(lineInfo) && !lineStepNum) {
fprintf(stderr, "%s: gave line info (\"-pl\") but not "
"# samples (\"-pln\")", me);
hestUsage(stderr, hopt, me, hparm);
hestGlossary(stderr, hopt, hparm);
airMopError(mop);
return 1;
}
/* special set-up required for DWI kind */
if (!strcmp(TEN_DWI_GAGE_KIND_NAME, kind->name)) {
if (tenDWMRIKeyValueParse(&ngrad, &nbmat, &bval, &skip, &skipNum, nin)) {
airMopAdd(mop, err = biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble parsing DWI info:\n%s\n", me, err);
airMopError(mop); return 1;
}
if (skipNum) {
fprintf(stderr, "%s: sorry, can't do DWI skipping in tenDwiGage", me);
airMopError(mop); return 1;
}
/* this could stand to use some more command-line arguments */
if (tenDwiGageKindSet(kind, 50, 1, bval, 0.001, ngrad, nbmat,
tenEstimate1MethodLLS,
tenEstimate2MethodQSegLLS,
/* randSeed */ 7919)) {
airMopAdd(mop, err = biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble parsing DWI info:\n%s\n", me, err);
airMopError(mop); return 1;
}
}
ansLen = kind->table[what].answerLength;
/* for setting up pre-blurred scale-space samples */
if (numSS) {
unsigned int vi;
ninSS = AIR_CAST(Nrrd **, calloc(numSS, sizeof(Nrrd *)));
scalePos = AIR_CAST(double *, calloc(numSS, sizeof(double)));
if (!(ninSS && scalePos)) {
fprintf(stderr, "%s: couldn't allocate ninSS", me);
airMopError(mop); return 1;
}
for (ninSSIdx=0; ninSSIdx<numSS; ninSSIdx++) {
ninSS[ninSSIdx] = nrrdNew();
airMopAdd(mop, ninSS[ninSSIdx], (airMopper)nrrdNuke, airMopAlways);
}
if (SSuniform) {
for (vi=0; vi<numSS; vi++) {
scalePos[vi] = AIR_AFFINE(0, vi, numSS-1, rangeSS[0], rangeSS[1]);
}
} else {
double rangeTau[2], tau;
rangeTau[0] = gageTauOfSig(rangeSS[0]);
rangeTau[1] = gageTauOfSig(rangeSS[1]);
for (vi=0; vi<numSS; vi++) {
tau = AIR_AFFINE(0, vi, numSS-1, rangeTau[0], rangeTau[1]);
scalePos[vi] = gageSigOfTau(tau);
}
}
if (verbose > 2) {
fprintf(stderr, "%s: sampling scale range %g--%g %suniformly:\n", me,
rangeSS[0], rangeSS[1], SSuniform ? "" : "non-");
for (vi=0; vi<numSS; vi++) {
fprintf(stderr, " scalePos[%u] = %g\n", vi, scalePos[vi]);
}
}
if (gageStackBlur(ninSS, scalePos, numSS,
nin, kind->baseDim, kSSblur,
nrrdBoundaryBleed, AIR_TRUE,
verbose)) {
airMopAdd(mop, err = biffGetDone(GAGE), airFree, airMopAlways);
fprintf(stderr, "%s: trouble pre-computing blurrings:\n%s\n", me, err);
airMopError(mop); return 1;
}
if (airStrlen(stackSavePath)) {
char fnform[AIR_STRLEN_LARGE];
sprintf(fnform, "%s/blur-%%02u.nrrd", stackSavePath);
fprintf(stderr, "%s: |%s|\n", me, fnform);
if (nrrdSaveMulti(fnform, AIR_CAST(const Nrrd *const *, ninSS),
numSS, 0, NULL)) {
airMopAdd(mop, err = biffGetDone(NRRD), airFree, airMopAlways);
fprintf(stderr, "%s: trouble saving blurrings:\n%s\n", me, err);
airMopError(mop); return 1;
}
}
} else {
int
tend_estimMain(int argc, char **argv, char *me, hestParm *hparm) {
int pret;
hestOpt *hopt = NULL;
char *perr, *err;
airArray *mop;
Nrrd **nin, *nin4d, *nbmat, *nterr, *nB0, *nout;
char *outS, *terrS, *bmatS, *eb0S;
float soft, scale, sigma;
int dwiax, EE, knownB0, oldstuff, estmeth, verbose, fixneg;
unsigned int ninLen, axmap[4], wlsi, *skip, skipNum, skipIdx;
double valueMin, thresh;
Nrrd *ngradKVP=NULL, *nbmatKVP=NULL;
double bKVP, bval;
tenEstimateContext *tec;
hestOptAdd(&hopt, "old", NULL, airTypeInt, 0, 0, &oldstuff, NULL,
"instead of the new tenEstimateContext code, use "
"the old tenEstimateLinear code");
hestOptAdd(&hopt, "sigma", "sigma", airTypeFloat, 1, 1, &sigma, "nan",
"Rician noise parameter");
hestOptAdd(&hopt, "v", "verbose", airTypeInt, 1, 1, &verbose, "0",
"verbosity level");
hestOptAdd(&hopt, "est", "estimate method", airTypeEnum, 1, 1, &estmeth,
"lls",
"estimation method to use. \"lls\": linear-least squares",
NULL, tenEstimate1Method);
hestOptAdd(&hopt, "wlsi", "WLS iters", airTypeUInt, 1, 1, &wlsi, "1",
"when using weighted-least-squares (\"-est wls\"), how "
"many iterations to do after the initial weighted fit.");
hestOptAdd(&hopt, "fixneg", NULL, airTypeInt, 0, 0, &fixneg, NULL,
"after estimating the tensor, ensure that there are no negative "
"eigenvalues by adding (to all eigenvalues) the amount by which "
"the smallest is negative (corresponding to increasing the "
"non-DWI image value).");
hestOptAdd(&hopt, "ee", "filename", airTypeString, 1, 1, &terrS, "",
"Giving a filename here allows you to save out the tensor "
"estimation error: a value which measures how much error there "
"is between the tensor model and the given diffusion weighted "
"measurements for each sample. By default, no such error "
"calculation is saved.");
hestOptAdd(&hopt, "eb", "filename", airTypeString, 1, 1, &eb0S, "",
"In those cases where there is no B=0 reference image given "
"(\"-knownB0 false\"), "
"giving a filename here allows you to save out the B=0 image "
"which is estimated from the data. By default, this image value "
"is estimated but not saved.");
hestOptAdd(&hopt, "t", "thresh", airTypeDouble, 1, 1, &thresh, "nan",
"value at which to threshold the mean DWI value per pixel "
"in order to generate the \"confidence\" mask. By default, "
"the threshold value is calculated automatically, based on "
"histogram analysis.");
hestOptAdd(&hopt, "soft", "soft", airTypeFloat, 1, 1, &soft, "0",
"how fuzzy the confidence boundary should be. By default, "
"confidence boundary is perfectly sharp");
hestOptAdd(&hopt, "scale", "scale", airTypeFloat, 1, 1, &scale, "1",
"After estimating the tensor, scale all of its elements "
"(but not the confidence value) by this amount. Can help with "
"downstream numerical precision if values are very large "
"or small.");
hestOptAdd(&hopt, "mv", "min val", airTypeDouble, 1, 1, &valueMin, "1.0",
"minimum plausible value (especially important for linear "
"least squares estimation)");
hestOptAdd(&hopt, "B", "B-list", airTypeString, 1, 1, &bmatS, NULL,
"6-by-N list of B-matrices characterizing "
"the diffusion weighting for each "
"image. \"tend bmat\" is one source for such a matrix; see "
"its usage info for specifics on how the coefficients of "
"the B-matrix are ordered. "
"An unadorned plain text file is a great way to "
"specify the B-matrix.\n **OR**\n "
"Can say just \"-B kvp\" to try to learn B matrices from "
"key/value pair information in input images.");
hestOptAdd(&hopt, "b", "b", airTypeDouble, 1, 1, &bval, "nan",
"\"b\" diffusion-weighting factor (units of sec/mm^2)");
hestOptAdd(&hopt, "knownB0", "bool", airTypeBool, 1, 1, &knownB0, NULL,
"Determines of the B=0 non-diffusion-weighted reference image "
"is known, or if it has to be estimated along with the tensor "
"elements.\n "
"\b\bo if \"true\": in the given list of diffusion gradients or "
"B-matrices, there are one or more with zero norm, which are "
"simply averaged to find the B=0 reference image value\n "
"\b\bo if \"false\": there may or may not be diffusion-weighted "
"images among the input; the B=0 image value is going to be "
"estimated along with the diffusion model");
hestOptAdd(&hopt, "i", "dwi0 dwi1", airTypeOther, 1, -1, &nin, "-",
"all the diffusion-weighted images (DWIs), as seperate 3D nrrds, "
"**OR**: One 4D nrrd of all DWIs stacked along axis 0",
&ninLen, NULL, nrrdHestNrrd);
hestOptAdd(&hopt, "o", "nout", airTypeString, 1, 1, &outS, "-",
"output tensor volume");
mop = airMopNew();
airMopAdd(mop, hopt, (airMopper)hestOptFree, airMopAlways);
USAGE(_tend_estimInfoL);
JUSTPARSE();
airMopAdd(mop, hopt, (airMopper)hestParseFree, airMopAlways);
nout = nrrdNew();
airMopAdd(mop, nout, (airMopper)nrrdNuke, airMopAlways);
nbmat = nrrdNew();
airMopAdd(mop, nbmat, (airMopper)nrrdNuke, airMopAlways);
/* figure out B-matrix */
if (strcmp("kvp", airToLower(bmatS))) {
/* its NOT coming from key/value pairs */
if (!AIR_EXISTS(bval)) {
fprintf(stderr, "%s: need to specify scalar b-value\n", me);
airMopError(mop); return 1;
}
if (nrrdLoad(nbmat, bmatS, NULL)) {
airMopAdd(mop, err=biffGetDone(NRRD), airFree, airMopAlways);
fprintf(stderr, "%s: trouble loading B-matrix:\n%s\n", me, err);
airMopError(mop); return 1;
}
nin4d = nin[0];
skip = NULL;
skipNum = 0;
} else {
/* it IS coming from key/value pairs */
if (1 != ninLen) {
fprintf(stderr, "%s: require a single 4-D DWI volume for "
"key/value pair based calculation of B-matrix\n", me);
airMopError(mop); return 1;
}
if (oldstuff) {
if (knownB0) {
fprintf(stderr, "%s: sorry, key/value-based DWI info not compatible "
"with older implementation of knownB0\n", me);
airMopError(mop); return 1;
}
}
if (tenDWMRIKeyValueParse(&ngradKVP, &nbmatKVP, &bKVP,
&skip, &skipNum, nin[0])) {
airMopAdd(mop, err=biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble parsing DWI info:\n%s\n", me, err);
airMopError(mop); return 1;
}
if (AIR_EXISTS(bval)) {
fprintf(stderr, "%s: WARNING: key/value pair derived b-value %g "
"over-riding %g from command-line", me, bKVP, bval);
}
bval = bKVP;
if (ngradKVP) {
airMopAdd(mop, ngradKVP, (airMopper)nrrdNuke, airMopAlways);
if (tenBMatrixCalc(nbmat, ngradKVP)) {
airMopAdd(mop, err=biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble finding B-matrix:\n%s\n", me, err);
airMopError(mop); return 1;
}
} else {
airMopAdd(mop, nbmatKVP, (airMopper)nrrdNuke, airMopAlways);
if (nrrdConvert(nbmat, nbmatKVP, nrrdTypeDouble)) {
airMopAdd(mop, err=biffGetDone(NRRD), airFree, airMopAlways);
fprintf(stderr, "%s: trouble converting B-matrix:\n%s\n", me, err);
airMopError(mop); return 1;
}
}
/* this will work because of the impositions of tenDWMRIKeyValueParse */
dwiax = ((nrrdKindList == nin[0]->axis[0].kind ||
nrrdKindVector == nin[0]->axis[0].kind)
? 0
: ((nrrdKindList == nin[0]->axis[1].kind ||
nrrdKindVector == nin[0]->axis[1].kind)
? 1
: ((nrrdKindList == nin[0]->axis[2].kind ||
nrrdKindVector == nin[0]->axis[2].kind)
? 2
: 3)));
if (0 == dwiax) {
nin4d = nin[0];
} else {
axmap[0] = dwiax;
axmap[1] = 1 > dwiax ? 1 : 0;
axmap[2] = 2 > dwiax ? 2 : 1;
axmap[3] = 3 > dwiax ? 3 : 2;
nin4d = nrrdNew();
airMopAdd(mop, nin4d, (airMopper)nrrdNuke, airMopAlways);
if (nrrdAxesPermute(nin4d, nin[0], axmap)) {
airMopAdd(mop, err=biffGetDone(NRRD), airFree, airMopAlways);
fprintf(stderr, "%s: trouble creating DWI volume:\n%s\n", me, err);
airMopError(mop); return 1;
}
}
}
nterr = NULL;
nB0 = NULL;
if (!oldstuff) {
if (1 != ninLen) {
fprintf(stderr, "%s: sorry, currently need single 4D volume "
"for new implementation\n", me);
airMopError(mop); return 1;
}
if (!AIR_EXISTS(thresh)) {
if (tend_estimThresholdFind(&thresh, nbmat, nin4d)) {
airMopAdd(mop, err=biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble finding threshold:\n%s\n", me, err);
airMopError(mop); return 1;
}
/* HACK to lower threshold a titch */
thresh *= 0.93;
fprintf(stderr, "%s: using mean DWI threshold %g\n", me, thresh);
}
tec = tenEstimateContextNew();
tec->progress = AIR_TRUE;
airMopAdd(mop, tec, (airMopper)tenEstimateContextNix, airMopAlways);
EE = 0;
if (!EE) tenEstimateVerboseSet(tec, verbose);
if (!EE) tenEstimateNegEvalShiftSet(tec, fixneg);
if (!EE) EE |= tenEstimateMethodSet(tec, estmeth);
if (!EE) EE |= tenEstimateBMatricesSet(tec, nbmat, bval, !knownB0);
if (!EE) EE |= tenEstimateValueMinSet(tec, valueMin);
for (skipIdx=0; skipIdx<skipNum; skipIdx++) {
/* fprintf(stderr, "%s: skipping %u\n", me, skip[skipIdx]); */
if (!EE) EE |= tenEstimateSkipSet(tec, skip[skipIdx], AIR_TRUE);
}
switch(estmeth) {
case tenEstimate1MethodLLS:
if (airStrlen(terrS)) {
tec->recordErrorLogDwi = AIR_TRUE;
/* tec->recordErrorDwi = AIR_TRUE; */
}
break;
case tenEstimate1MethodNLS:
if (airStrlen(terrS)) {
tec->recordErrorDwi = AIR_TRUE;
}
break;
case tenEstimate1MethodWLS:
if (!EE) tec->WLSIterNum = wlsi;
if (airStrlen(terrS)) {
tec->recordErrorDwi = AIR_TRUE;
}
break;
case tenEstimate1MethodMLE:
if (!(AIR_EXISTS(sigma) && sigma > 0.0)) {
fprintf(stderr, "%s: can't do %s w/out sigma > 0 (not %g)\n",
me, airEnumStr(tenEstimate1Method, tenEstimate1MethodMLE),
sigma);
airMopError(mop); return 1;
}
if (!EE) EE |= tenEstimateSigmaSet(tec, sigma);
if (airStrlen(terrS)) {
tec->recordLikelihoodDwi = AIR_TRUE;
}
break;
}
if (!EE) EE |= tenEstimateThresholdSet(tec, thresh, soft);
if (!EE) EE |= tenEstimateUpdate(tec);
if (EE) {
airMopAdd(mop, err=biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble setting up estimation:\n%s\n", me, err);
airMopError(mop); return 1;
}
if (tenEstimate1TensorVolume4D(tec, nout, &nB0,
airStrlen(terrS)
? &nterr
: NULL,
nin4d, nrrdTypeFloat)) {
airMopAdd(mop, err=biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble doing estimation:\n%s\n", me, err);
airMopError(mop); return 1;
}
if (airStrlen(terrS)) {
airMopAdd(mop, nterr, (airMopper)nrrdNuke, airMopAlways);
}
} else {
EE = 0;
if (1 == ninLen) {
EE = tenEstimateLinear4D(nout, airStrlen(terrS) ? &nterr : NULL, &nB0,
nin4d, nbmat, knownB0, thresh, soft, bval);
} else {
EE = tenEstimateLinear3D(nout, airStrlen(terrS) ? &nterr : NULL, &nB0,
(const Nrrd**)nin, ninLen, nbmat,
knownB0, thresh, soft, bval);
}
if (EE) {
airMopAdd(mop, err=biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble making tensor volume:\n%s\n", me, err);
airMopError(mop); return 1;
}
}
if (nterr) {
/* it was allocated by tenEstimate*, we have to clean it up */
airMopAdd(mop, nterr, (airMopper)nrrdNuke, airMopAlways);
}
if (nB0) {
/* it was allocated by tenEstimate*, we have to clean it up */
airMopAdd(mop, nB0, (airMopper)nrrdNuke, airMopAlways);
}
if (1 != scale) {
if (tenSizeScale(nout, nout, scale)) {
airMopAdd(mop, err=biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble doing scaling:\n%s\n", me, err);
airMopError(mop); return 1;
}
}
if (nterr) {
if (nrrdSave(terrS, nterr, NULL)) {
airMopAdd(mop, err=biffGetDone(NRRD), airFree, airMopAlways);
fprintf(stderr, "%s: trouble writing error image:\n%s\n", me, err);
airMopError(mop); return 1;
}
}
if (!knownB0 && airStrlen(eb0S)) {
if (nrrdSave(eb0S, nB0, NULL)) {
airMopAdd(mop, err=biffGetDone(NRRD), airFree, airMopAlways);
fprintf(stderr, "%s: trouble writing estimated B=0 image:\n%s\n",
me, err);
airMopError(mop); return 1;
}
}
if (nrrdSave(outS, nout, NULL)) {
airMopAdd(mop, err=biffGetDone(NRRD), airFree, airMopAlways);
fprintf(stderr, "%s: trouble writing:\n%s\n", me, err);
airMopError(mop); return 1;
}
airMopOkay(mop);
return 0;
}
int
tenExperSpecFromKeyValueSet(tenExperSpec *espec, const Nrrd *ndwi) {
static const char me[]="tenExperSpecFromKeyValueSet";
unsigned int *skip, skipNum, ii, imgNum, dwiax;
Nrrd *ngrad, *nbmat;
airArray *mop;
double len, singleBval, *bval, *grad;
for (dwiax=0; dwiax<ndwi->dim; dwiax++) {
if (nrrdKindList == ndwi->axis[dwiax].kind
|| nrrdKindVector == ndwi->axis[dwiax].kind) {
break;
}
}
if (ndwi->dim == dwiax) {
biffAddf(TEN, "%s: need dwis to have a kind %s or %s axis", me,
airEnumStr(nrrdKind, nrrdKindList),
airEnumStr(nrrdKind, nrrdKindVector));
return 1;
} else {
if (0 != dwiax) {
biffAddf(TEN, "%s: need dwis (kind %s or %s) along axis 0, not %u", me,
airEnumStr(nrrdKind, nrrdKindList),
airEnumStr(nrrdKind, nrrdKindVector), dwiax);
return 1;
}
}
for (ii=dwiax+1; ii<ndwi->dim; ii++) {
if (nrrdKindList == ndwi->axis[ii].kind
|| nrrdKindVector == ndwi->axis[ii].kind) {
break;
}
}
if (ii < ndwi->dim) {
biffAddf(TEN, "%s: saw on %u another %s or %s kind axis, after 0", me,
ii, airEnumStr(nrrdKind, nrrdKindList),
airEnumStr(nrrdKind, nrrdKindVector));
return 1;
}
if (tenDWMRIKeyValueParse(&ngrad, &nbmat, &singleBval,
&skip, &skipNum, ndwi)) {
biffAddf(TEN, "%s: trouble parsing DWI info from key/value pairs", me);
return 1;
}
mop = airMopNew();
if (ngrad) {
airMopAdd(mop, ngrad, (airMopper)nrrdNuke, airMopAlways);
}
if (nbmat) {
airMopAdd(mop, nbmat, (airMopper)nrrdNuke, airMopAlways);
}
if (skip) {
airMopAdd(mop, skip, airFree, airMopAlways);
}
if (nbmat) {
biffAddf(TEN, "%s: sorry, currently can't handle B-matrices here", me);
airMopError(mop);
return 1;
}
if (skipNum) {
biffAddf(TEN, "%s: sorry, currently can't handle skipping (%u) here", me,
skipNum);
airMopError(mop);
return 1;
}
imgNum = ngrad->axis[1].size;
bval = AIR_CALLOC(imgNum, double);
airMopAdd(mop, bval, airFree, airMopAlways);
grad = AIR_CAST(double *, ngrad->data);
for (ii=0; ii<imgNum; ii++) {
len = ELL_3V_LEN(grad + 3*ii);
bval[ii] = singleBval*len*len;
if (len) {
ELL_3V_SCALE(grad + 3*ii, 1/len, grad + 3*ii);
} else {
ELL_3V_SET(grad + 3*ii, 0, 0, -1);
}
}
if (tenExperSpecGradBValSet(espec, AIR_FALSE, bval, grad, imgNum)) {
biffAddf(TEN, "%s: trouble", me);
airMopError(mop);
return 1;
}
airMopOkay(mop);
return 0;
}
int
tend_epiregMain(int argc, const char **argv, const char *me,
hestParm *hparm) {
int pret, rret;
hestOpt *hopt = NULL;
char *perr, *err;
airArray *mop;
char *outS, *buff;
char *gradS;
NrrdKernelSpec *ksp;
Nrrd **nin, **nout3D, *nout4D, *ngrad, *ngradKVP, *nbmatKVP;
unsigned int ni, ninLen, *skip, skipNum;
int ref, noverbose, progress, nocc, baseNum;
float bw[2], thr, fitFrac;
double bvalue;
hestOptAdd(&hopt, "i", "dwi0 dwi1", airTypeOther, 1, -1, &nin, NULL,
"all the diffusion-weighted images (DWIs), as separate 3D nrrds, "
"**OR**: one 4D nrrd of all DWIs stacked along axis 0",
&ninLen, NULL, nrrdHestNrrd);
hestOptAdd(&hopt, "g", "grads", airTypeString, 1, 1, &gradS, NULL,
"array of gradient directions, in the same order as the "
"associated DWIs were given to \"-i\", "
"**OR** \"-g kvp\" signifies that gradient directions should "
"be read from the key/value pairs of the DWI",
NULL, NULL, nrrdHestNrrd);
hestOptAdd(&hopt, "r", "reference", airTypeInt, 1, 1, &ref, "-1",
"which of the DW volumes (zero-based numbering) should be used "
"as the standard, to which all other images are transformed. "
"Using -1 (the default) means that 9 intrinsic parameters "
"governing the relationship between the gradient direction "
"and the resulting distortion are estimated and fitted, "
"ensuring good registration with the non-diffusion-weighted "
"T2 image (which is never explicitly used in registration). "
"Otherwise, by picking a specific DWI, no distortion parameter "
"estimation is done. ");
hestOptAdd(&hopt, "nv", NULL, airTypeInt, 0, 0, &noverbose, NULL,
"turn OFF verbose mode, and "
"have no idea what stage processing is at.");
hestOptAdd(&hopt, "p", NULL, airTypeInt, 0, 0, &progress, NULL,
"save out intermediate steps of processing");
hestOptAdd(&hopt, "bw", "x,y blur", airTypeFloat, 2, 2, bw, "1.0 2.0",
"standard devs in X and Y directions of gaussian filter used "
"to blur the DWIs prior to doing segmentation. This blurring "
"does not effect the final resampling of registered DWIs. "
"Use \"0.0 0.0\" to say \"no blurring\"");
hestOptAdd(&hopt, "t", "DWI thresh", airTypeFloat, 1, 1, &thr, "nan",
"Threshold value to use on DWIs, "
"to do initial separation of brain and non-brain. By default, "
"the threshold is determined automatically by histogram "
"analysis. ");
hestOptAdd(&hopt, "ncc", NULL, airTypeInt, 0, 0, &nocc, NULL,
"do *NOT* do connected component (CC) analysis, after "
"thresholding and before moment calculation. Doing CC analysis "
"usually gives better results because it converts the "
"thresholding output into something much closer to a "
"real segmentation");
hestOptAdd(&hopt, "f", "fit frac", airTypeFloat, 1, 1, &fitFrac, "0.70",
"(only meaningful with \"-r -1\") When doing linear fitting "
"of the intrinsic distortion parameters, it is good "
"to ignore the slices for which the segmentation was poor. A "
"heuristic is used to rank the slices according to segmentation "
"quality. This option controls how many of the (best) slices "
"contribute to the fitting. Use \"0\" to disable distortion "
"parameter fitting. ");
hestOptAdd(&hopt, "k", "kernel", airTypeOther, 1, 1, &ksp, "cubic:0,0.5",
"kernel for resampling DWIs along the phase-encoding "
"direction during final registration stage",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "s", "start #", airTypeInt, 1, 1, &baseNum, "1",
"first number to use in numbered sequence of output files.");
hestOptAdd(&hopt, "o", "output/prefix", airTypeString, 1, 1, &outS, "-",
"For separate 3D DWI volume inputs: prefix for output filenames; "
"will save out one (registered) "
"DWI for each input DWI, using the same type as the input. "
"**OR**: For single 4D DWI input: output file name. ");
mop = airMopNew();
airMopAdd(mop, hopt, (airMopper)hestOptFree, airMopAlways);
USAGE(_tend_epiregInfoL);
JUSTPARSE();
airMopAdd(mop, hopt, (airMopper)hestParseFree, airMopAlways);
if (strcmp("kvp", gradS)) {
/* they're NOT coming from key/value pairs */
if (nrrdLoad(ngrad=nrrdNew(), gradS, NULL)) {
airMopAdd(mop, err=biffGetDone(NRRD), airFree, airMopAlways);
fprintf(stderr, "%s: trouble loading gradient list:\n%s\n", me, err);
airMopError(mop); return 1;
}
} else {
if (1 != ninLen) {
fprintf(stderr, "%s: can do key/value pairs only from single nrrd", me);
airMopError(mop); return 1;
}
/* they are coming from key/value pairs */
if (tenDWMRIKeyValueParse(&ngradKVP, &nbmatKVP, &bvalue,
&skip, &skipNum, nin[0])) {
airMopAdd(mop, err=biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble parsing gradient list:\n%s\n", me, err);
airMopError(mop); return 1;
}
if (nbmatKVP) {
fprintf(stderr, "%s: sorry, can only use gradients, not b-matrices", me);
airMopError(mop); return 1;
}
ngrad = ngradKVP;
}
airMopAdd(mop, ngrad, (airMopper)nrrdNuke, airMopAlways);
nout3D = AIR_CALLOC(ninLen, Nrrd *);
airMopAdd(mop, nout3D, airFree, airMopAlways);
nout4D = nrrdNew();
airMopAdd(mop, nout4D, (airMopper)nrrdNuke, airMopAlways);
buff = AIR_CALLOC(airStrlen(outS) + 10, char);
airMopAdd(mop, buff, airFree, airMopAlways);
if (!( nout3D && nout4D && buff )) {
fprintf(stderr, "%s: couldn't allocate buffers", me);
airMopError(mop); return 1;
}
for (ni=0; ni<ninLen; ni++) {
nout3D[ni]=nrrdNew();
airMopAdd(mop, nout3D[ni], (airMopper)nrrdNuke, airMopAlways);
}
if (1 == ninLen) {
rret = tenEpiRegister4D(nout4D, nin[0], ngrad,
ref,
bw[0], bw[1], fitFrac, thr, !nocc,
ksp->kernel, ksp->parm,
progress, !noverbose);
} else {
rret = tenEpiRegister3D(nout3D, nin, ninLen, ngrad,
ref,
bw[0], bw[1], fitFrac, thr, !nocc,
ksp->kernel, ksp->parm,
progress, !noverbose);
}
if (rret) {
airMopAdd(mop, err=biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble doing epireg:\n%s\n", me, err);
airMopError(mop); return 1;
}
if (1 == ninLen) {
if (nrrdSave(outS, nout4D, NULL)) {
airMopAdd(mop, err=biffGetDone(NRRD), airFree, airMopAlways);
fprintf(stderr, "%s: trouble writing \"%s\":\n%s\n", me, outS, err);
airMopError(mop); return 1;
}
} else {
for (ni=0; ni<ninLen; ni++) {
if (ninLen+baseNum > 99) {
sprintf(buff, "%s%05d.nrrd", outS, ni+baseNum);
} else if (ninLen+baseNum > 9) {
sprintf(buff, "%s%02d.nrrd", outS, ni+baseNum);
} else {
sprintf(buff, "%s%d.nrrd", outS, ni+baseNum);
}
if (nrrdSave(buff, nout3D[ni], NULL)) {
airMopAdd(mop, err=biffGetDone(NRRD), airFree, airMopAlways);
fprintf(stderr, "%s: trouble writing \"%s\":\n%s\n", me, buff, err);
airMopError(mop); return 1;
}
}
}
airMopOkay(mop);
return 0;
}
int
main(int argc, const char *argv[]) {
gageKind *kind;
const char *me;
char *whatS, *err, *outS, *stackReadFormat, *stackSaveFormat;
hestParm *hparm;
hestOpt *hopt = NULL;
NrrdKernelSpec *k00, *k11, *k22, *kSS, *kSSblur;
int what, E=0, renorm, SSuniform, SSoptim, verbose, zeroZ,
orientationFromSpacing, SSnormd;
unsigned int iBaseDim, oBaseDim, axi, numSS, ninSSIdx, seed;
const double *answer;
Nrrd *nin, *nout, **ninSS=NULL;
Nrrd *ngrad=NULL, *nbmat=NULL;
size_t ai, ansLen, idx, xi, yi, zi, six, siy, siz, sox, soy, soz;
double bval=0, gmc, rangeSS[2], wrlSS, idxSS=AIR_NAN,
dsix, dsiy, dsiz, dsox, dsoy, dsoz;
gageContext *ctx;
gagePerVolume *pvl=NULL;
double t0, t1, x, y, z, scale[3], rscl[3], min[3], maxOut[3], maxIn[3];
airArray *mop;
unsigned int hackZi, *skip, skipNum;
double (*ins)(void *v, size_t I, double d);
gageStackBlurParm *sbp;
char hackKeyStr[]="TEEM_VPROBE_HACK_ZI", *hackValStr;
int otype, hackSet;
char stmp[4][AIR_STRLEN_SMALL];
me = argv[0];
/* parse environment variables first, in case they break nrrdDefault*
or nrrdState* variables in a way that nrrdSanity() should see */
nrrdDefaultGetenv();
nrrdStateGetenv();
/* no harm done in making sure we're sane */
if (!nrrdSanity()) {
fprintf(stderr, "******************************************\n");
fprintf(stderr, "******************************************\n");
fprintf(stderr, "\n");
fprintf(stderr, " %s: nrrd sanity check FAILED.\n", me);
fprintf(stderr, "\n");
fprintf(stderr, " This means that either nrrd can't work on this "
"platform, or (more likely)\n");
fprintf(stderr, " there was an error in the compilation options "
"and variable definitions\n");
fprintf(stderr, " for how Teem was built here.\n");
fprintf(stderr, "\n");
fprintf(stderr, " %s\n", err = biffGetDone(NRRD));
fprintf(stderr, "\n");
fprintf(stderr, "******************************************\n");
fprintf(stderr, "******************************************\n");
free(err);
return 1;
}
mop = airMopNew();
hparm = hestParmNew();
airMopAdd(mop, hparm, AIR_CAST(airMopper, hestParmFree), airMopAlways);
hparm->elideSingleOtherType = AIR_TRUE;
hestOptAdd(&hopt, "i", "nin", airTypeOther, 1, 1, &nin, NULL,
"input volume", NULL, NULL, nrrdHestNrrd);
hestOptAdd(&hopt, "k", "kind", airTypeOther, 1, 1, &kind, NULL,
"\"kind\" of volume (\"scalar\", \"vector\", "
"\"tensor\", or \"dwi\")",
NULL, NULL, meetHestGageKind);
hestOptAdd(&hopt, "v", "verbosity", airTypeInt, 1, 1, &verbose, "1",
"verbosity level");
hestOptAdd(&hopt, "q", "query", airTypeString, 1, 1, &whatS, NULL,
"the quantity (scalar, vector, or matrix) to learn by probing");
hestOptAdd(&hopt, "s", "sclX sclY sxlZ", airTypeDouble, 3, 3, scale,
"1.0 1.0 1.0",
"scaling factor for resampling on each axis "
"(>1.0 : supersampling)");
hestOptAdd(&hopt, "k00", "kern00", airTypeOther, 1, 1, &k00,
"tent", "kernel for gageKernel00",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "k11", "kern11", airTypeOther, 1, 1, &k11,
"cubicd:1,0", "kernel for gageKernel11",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "k22", "kern22", airTypeOther, 1, 1, &k22,
"cubicdd:1,0", "kernel for gageKernel22",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "seed", "N", airTypeUInt, 1, 1, &seed, "42",
"RNG seed; mostly for debugging");
hestOptAdd(&hopt, "zz", "bool", airTypeBool, 1, 1, &zeroZ, "false",
"enable \"zeroZ\" behavior in gage that partially "
"implements working with 3D images as if they are 2D");
hestOptAdd(&hopt, "ssn", "SS #", airTypeUInt, 1, 1, &numSS,
"0", "how many scale-space samples to evaluate, or, "
"0 to turn-off all scale-space behavior");
hestOptAdd(&hopt, "ssr", "scale range", airTypeDouble, 2, 2, rangeSS,
"nan nan", "range of scales in scale-space");
hestOptAdd(&hopt, "ssrf", "SS read format", airTypeString, 1, 1,
&stackReadFormat, "",
"printf-style format (including a \"%u\") for the "
"filenames from which to *read* "
"pre-blurred volumes computed for the stack");
hestOptAdd(&hopt, "sssf", "SS save format", airTypeString, 1, 1,
&stackSaveFormat, "",
"printf-style format (including a \"%u\") for the "
"filenames in which to *save* "
"pre-blurred volumes computed for the stack");
hestOptAdd(&hopt, "ssw", "SS pos", airTypeDouble, 1, 1, &wrlSS, "0",
"\"world\"-space position (true sigma) "
"at which to sample in scale-space");
hestOptAdd(&hopt, "kssb", "kernel", airTypeOther, 1, 1, &kSSblur,
"dgauss:1,5", "blurring kernel, to sample scale space",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "kssr", "kernel", airTypeOther, 1, 1, &kSS,
"hermite", "kernel for reconstructing from scale space samples",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "ssu", NULL, airTypeInt, 0, 0, &SSuniform, NULL,
"do uniform samples along sigma, and not (by default) "
"samples according to the effective diffusion scale");
hestOptAdd(&hopt, "sso", NULL, airTypeInt, 0, 0, &SSoptim, NULL,
"if not using \"-ssu\", use pre-computed optimal "
"sigmas when possible");
hestOptAdd(&hopt, "ssnd", NULL, airTypeInt, 0, 0, &SSnormd, NULL,
"normalize derivatives by scale");
hestOptAdd(&hopt, "rn", NULL, airTypeInt, 0, 0, &renorm, NULL,
"renormalize kernel weights at each new sample location. "
"\"Accurate\" kernels don't need this; doing it always "
"makes things go slower");
hestOptAdd(&hopt, "gmc", "min gradmag", airTypeDouble, 1, 1, &gmc,
"0.0", "For curvature-based queries, use zero when gradient "
"magnitude is below this");
hestOptAdd(&hopt, "ofs", "ofs", airTypeInt, 0, 0, &orientationFromSpacing,
NULL, "If only per-axis spacing is available, use that to "
"contrive full orientation info");
hestOptAdd(&hopt, "t", "type", airTypeEnum, 1, 1, &otype, "float",
"type of output volume", NULL, nrrdType);
hestOptAdd(&hopt, "o", "nout", airTypeString, 1, 1, &outS, "-",
"output volume");
hestParseOrDie(hopt, argc-1, argv+1, hparm,
me, probeInfo, AIR_TRUE, AIR_TRUE, AIR_TRUE);
airMopAdd(mop, hopt, AIR_CAST(airMopper, hestOptFree), airMopAlways);
airMopAdd(mop, hopt, AIR_CAST(airMopper, hestParseFree), airMopAlways);
what = airEnumVal(kind->enm, whatS);
if (!what) {
/* 0 indeed always means "unknown" for any gageKind */
fprintf(stderr, "%s: couldn't parse \"%s\" as measure of \"%s\" volume\n",
me, whatS, kind->name);
hestUsage(stderr, hopt, me, hparm);
hestGlossary(stderr, hopt, hparm);
airMopError(mop);
return 1;
}
/* special set-up required for DWI kind */
if (!strcmp(TEN_DWI_GAGE_KIND_NAME, kind->name)) {
if (tenDWMRIKeyValueParse(&ngrad, &nbmat, &bval, &skip, &skipNum, nin)) {
airMopAdd(mop, err = biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble parsing DWI info:\n%s\n", me, err);
airMopError(mop); return 1;
}
if (skipNum) {
fprintf(stderr, "%s: sorry, can't do DWI skipping in tenDwiGage", me);
airMopError(mop); return 1;
}
/* this could stand to use some more command-line arguments */
if (tenDwiGageKindSet(kind, 50, 1, bval, 0.001, ngrad, nbmat,
tenEstimate1MethodLLS,
tenEstimate2MethodQSegLLS, seed)) {
airMopAdd(mop, err = biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble parsing DWI info:\n%s\n", me, err);
airMopError(mop); return 1;
}
}
/* for setting up pre-blurred scale-space samples */
if (numSS) {
unsigned int vi;
sbp = gageStackBlurParmNew();
airMopAdd(mop, sbp, (airMopper)gageStackBlurParmNix, airMopAlways);
ninSS = AIR_CAST(Nrrd **, calloc(numSS, sizeof(Nrrd *)));
if (!ninSS) {
fprintf(stderr, "%s: couldn't allocate ninSS", me);
airMopError(mop); return 1;
}
for (ninSSIdx=0; ninSSIdx<numSS; ninSSIdx++) {
ninSS[ninSSIdx] = nrrdNew();
airMopAdd(mop, ninSS[ninSSIdx], (airMopper)nrrdNuke, airMopAlways);
}
if (gageStackBlurParmScaleSet(sbp, numSS, rangeSS[0], rangeSS[1],
SSuniform, SSoptim)
|| gageStackBlurParmKernelSet(sbp, kSSblur)
|| gageStackBlurParmRenormalizeSet(sbp, AIR_TRUE)
|| gageStackBlurParmBoundarySet(sbp, nrrdBoundaryBleed, AIR_NAN)
|| gageStackBlurParmVerboseSet(sbp, verbose)) {
airMopAdd(mop, err = biffGetDone(GAGE), airFree, airMopAlways);
fprintf(stderr, "%s: trouble with stack blur info:\n%s\n", me, err);
airMopError(mop); return 1;
}
if (airStrlen(stackReadFormat)) {
if (nrrdLoadMulti(ninSS, numSS,
stackReadFormat, 0, NULL)) {
airMopAdd(mop, err = biffGetDone(NRRD), airFree, airMopAlways);
fprintf(stderr, "%s: trouble loading blurrings:\n%s\n", me, err);
airMopError(mop); return 1;
}
if (gageStackBlurCheck(AIR_CAST(const Nrrd *const*, ninSS),
sbp, nin, kind)) {
airMopAdd(mop, err = biffGetDone(GAGE), airFree, airMopAlways);
fprintf(stderr, "%s: trouble:\n%s\n", me, err);
airMopError(mop); return 1;
}
} else {
if (gageStackBlur(ninSS, sbp, nin, kind)) {
int
main(int argc, char *argv[]) {
gageKind *kind;
char *me, *outS, *whatS, *err, hackKeyStr[]="TEEM_VPROBE_HACK_ZI",
*hackValStr, *stackSavePath;
hestParm *hparm;
hestOpt *hopt = NULL;
NrrdKernelSpec *k00, *k11, *k22, *kSS, *kSSblur;
int what, E=0, otype, renorm, hackSet, SSrenorm, SSuniform, verbose;
unsigned int iBaseDim, oBaseDim, axi, numSS, ninSSIdx, seed;
const double *answer;
Nrrd *nin, *nout, **ninSS=NULL;
Nrrd *ngrad=NULL, *nbmat=NULL;
size_t ai, ansLen, idx, xi, yi, zi, six, siy, siz, sox, soy, soz;
double bval=0, gmc, rangeSS[2], wrlSS, idxSS=AIR_NAN, *scalePos;
gageContext *ctx;
gagePerVolume *pvl=NULL;
double t0, t1, x, y, z, scale[3], rscl[3], min[3], maxOut[3], maxIn[3];
airArray *mop;
unsigned int hackZi, *skip, skipNum;
double (*ins)(void *v, size_t I, double d);
mop = airMopNew();
me = argv[0];
hparm = hestParmNew();
airMopAdd(mop, hparm, AIR_CAST(airMopper, hestParmFree), airMopAlways);
hparm->elideSingleOtherType = AIR_TRUE;
hestOptAdd(&hopt, "i", "nin", airTypeOther, 1, 1, &nin, NULL,
"input volume", NULL, NULL, nrrdHestNrrd);
hestOptAdd(&hopt, "k", "kind", airTypeOther, 1, 1, &kind, NULL,
"\"kind\" of volume (\"scalar\", \"vector\", "
"\"tensor\", or \"dwi\")",
NULL, NULL, &probeKindHestCB);
hestOptAdd(&hopt, "v", "verbosity", airTypeInt, 1, 1, &verbose, "1",
"verbosity level");
hestOptAdd(&hopt, "q", "query", airTypeString, 1, 1, &whatS, NULL,
"the quantity (scalar, vector, or matrix) to learn by probing");
hestOptAdd(&hopt, "s", "sclX sclY sxlZ", airTypeDouble, 3, 3, scale,
"1.0 1.0 1.0",
"scaling factor for resampling on each axis "
"(>1.0 : supersampling)");
hestOptAdd(&hopt, "k00", "kern00", airTypeOther, 1, 1, &k00,
"tent", "kernel for gageKernel00",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "k11", "kern11", airTypeOther, 1, 1, &k11,
"cubicd:1,0", "kernel for gageKernel11",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "k22", "kern22", airTypeOther, 1, 1, &k22,
"cubicdd:1,0", "kernel for gageKernel22",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "seed", "N", airTypeUInt, 1, 1, &seed, "42",
"RNG seed; mostly for debugging");
hestOptAdd(&hopt, "ssn", "SS #", airTypeUInt, 1, 1, &numSS,
"0", "how many scale-space samples to evaluate, or, "
"0 to turn-off all scale-space behavior");
hestOptAdd(&hopt, "ssr", "scale range", airTypeDouble, 2, 2, rangeSS,
"nan nan", "range of scales in scale-space");
hestOptAdd(&hopt, "sss", "scale save path", airTypeString, 1, 1,
&stackSavePath, "",
"give a non-empty path string (like \"./\") to save out "
"the pre-blurred volumes computed for the stack");
hestOptAdd(&hopt, "ssw", "SS pos", airTypeDouble, 1, 1, &wrlSS, "0",
"\"world\"-space position (true sigma) "
"at which to sample in scale-space");
hestOptAdd(&hopt, "kssblur", "kernel", airTypeOther, 1, 1, &kSSblur,
"dgauss:1,5", "blurring kernel, to sample scale space",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "kss", "kernel", airTypeOther, 1, 1, &kSS,
"tent", "kernel for reconstructing from scale space samples",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&hopt, "ssrn", "ssrn", airTypeInt, 1, 1, &SSrenorm, "0",
"enable derivative normalization based on scale space");
hestOptAdd(&hopt, "ssu", NULL, airTypeInt, 0, 0, &SSuniform, NULL,
"do uniform samples along sigma, and not (by default) "
"samples according to the logarithm of diffusion time");
hestOptAdd(&hopt, "rn", NULL, airTypeInt, 0, 0, &renorm, NULL,
"renormalize kernel weights at each new sample location. "
"\"Accurate\" kernels don't need this; doing it always "
"makes things go slower");
hestOptAdd(&hopt, "gmc", "min gradmag", airTypeDouble, 1, 1, &gmc,
"0.0", "For curvature-based queries, use zero when gradient "
"magnitude is below this");
hestOptAdd(&hopt, "t", "type", airTypeEnum, 1, 1, &otype, "float",
"type of output volume", NULL, nrrdType);
hestOptAdd(&hopt, "o", "nout", airTypeString, 1, 1, &outS, "-",
"output volume");
hestParseOrDie(hopt, argc-1, argv+1, hparm,
me, probeInfo, AIR_TRUE, AIR_TRUE, AIR_TRUE);
airMopAdd(mop, hopt, AIR_CAST(airMopper, hestOptFree), airMopAlways);
airMopAdd(mop, hopt, AIR_CAST(airMopper, hestParseFree), airMopAlways);
what = airEnumVal(kind->enm, whatS);
if (!what) {
/* 0 indeed always means "unknown" for any gageKind */
fprintf(stderr, "%s: couldn't parse \"%s\" as measure of \"%s\" volume\n",
me, whatS, kind->name);
hestUsage(stderr, hopt, me, hparm);
hestGlossary(stderr, hopt, hparm);
airMopError(mop);
return 1;
}
/* special set-up required for DWI kind */
if (!strcmp(TEN_DWI_GAGE_KIND_NAME, kind->name)) {
if (tenDWMRIKeyValueParse(&ngrad, &nbmat, &bval, &skip, &skipNum, nin)) {
airMopAdd(mop, err = biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble parsing DWI info:\n%s\n", me, err);
airMopError(mop); return 1;
}
if (skipNum) {
fprintf(stderr, "%s: sorry, can't do DWI skipping in tenDwiGage", me);
airMopError(mop); return 1;
}
/* this could stand to use some more command-line arguments */
if (tenDwiGageKindSet(kind, 50, 1, bval, 0.001, ngrad, nbmat,
tenEstimate1MethodLLS,
tenEstimate2MethodQSegLLS, seed)) {
airMopAdd(mop, err = biffGetDone(TEN), airFree, airMopAlways);
fprintf(stderr, "%s: trouble parsing DWI info:\n%s\n", me, err);
airMopError(mop); return 1;
}
}
/* for setting up pre-blurred scale-space samples */
if (numSS) {
unsigned int vi;
ninSS = AIR_CAST(Nrrd **, calloc(numSS, sizeof(Nrrd *)));
scalePos = AIR_CAST(double *, calloc(numSS, sizeof(double)));
if (!(ninSS && scalePos)) {
fprintf(stderr, "%s: couldn't allocate ninSS", me);
airMopError(mop); return 1;
}
for (ninSSIdx=0; ninSSIdx<numSS; ninSSIdx++) {
ninSS[ninSSIdx] = nrrdNew();
airMopAdd(mop, ninSS[ninSSIdx], (airMopper)nrrdNuke, airMopAlways);
}
if (SSuniform) {
for (vi=0; vi<numSS; vi++) {
scalePos[vi] = AIR_AFFINE(0, vi, numSS-1, rangeSS[0], rangeSS[1]);
}
} else {
double rangeTau[2], tau;
rangeTau[0] = gageTauOfSig(rangeSS[0]);
rangeTau[1] = gageTauOfSig(rangeSS[1]);
for (vi=0; vi<numSS; vi++) {
tau = AIR_AFFINE(0, vi, numSS-1, rangeTau[0], rangeTau[1]);
scalePos[vi] = gageSigOfTau(tau);
}
}
if (verbose > 2) {
fprintf(stderr, "%s: sampling scale range %g--%g %suniformly:\n", me,
rangeSS[0], rangeSS[1], SSuniform ? "" : "non-");
for (vi=0; vi<numSS; vi++) {
fprintf(stderr, " scalePos[%u] = %g\n", vi, scalePos[vi]);
}
}
if (gageStackBlur(ninSS, scalePos, numSS,
nin, kind->baseDim, kSSblur,
nrrdBoundaryBleed, AIR_TRUE,
verbose)) {
airMopAdd(mop, err = biffGetDone(GAGE), airFree, airMopAlways);
fprintf(stderr, "%s: trouble pre-computing blurrings:\n%s\n", me, err);
airMopError(mop); return 1;
}
if (airStrlen(stackSavePath)) {
char fnform[AIR_STRLEN_LARGE];
sprintf(fnform, "%s/blur-%%02u.nrrd", stackSavePath);
fprintf(stderr, "%s: |%s|\n", me, fnform);
if (nrrdSaveMulti(fnform, AIR_CAST(const Nrrd *const *, ninSS),
numSS, 0, NULL)) {
airMopAdd(mop, err = biffGetDone(NRRD), airFree, airMopAlways);
fprintf(stderr, "%s: trouble saving blurrings:\n%s\n", me, err);
airMopError(mop); return 1;
}
}
/* there's actually work to do here, weirdly: gageProbe can either
work in index space, or in world space, but vprobe has
basically always been index-space-centric. For doing any kind
scale/stack space hacking for which vprobe is suited, its nicer
to have the stack position be in the stack's "world" space, not
the (potentially non-uniform) index space. So here, we have to
actually replicate work that is done by _gageProbeSpace() in
converting from world to index space */
for (vi=0; vi<numSS-1; vi++) {
if (AIR_IN_CL(scalePos[vi], wrlSS, scalePos[vi+1])) {
idxSS = vi + AIR_AFFINE(scalePos[vi], wrlSS, scalePos[vi+1], 0, 1);
if (verbose > 1) {
fprintf(stderr, "%s: scale pos %g -> idx %g = %u + %g\n", me,
wrlSS, idxSS, vi,
AIR_AFFINE(scalePos[vi], wrlSS, scalePos[vi+1], 0, 1));
}
break;
}
}
if (vi == numSS-1) {
fprintf(stderr, "%s: scale pos %g outside range %g=%g, %g=%g\n", me,
wrlSS, rangeSS[0], scalePos[0], rangeSS[1], scalePos[numSS-1]);
airMopError(mop); return 1;
}
} else {
