int
nrrdSimpleResample(Nrrd *nout, Nrrd *nin,
const NrrdKernel *kernel, const double *parm,
const size_t *samples, const double *scalings) {
char me[]="nrrdSimpleResample", err[BIFF_STRLEN];
NrrdResampleInfo *info;
int p, np, center;
unsigned ai;
if (!(nout && nin && kernel && (samples || scalings))) {
sprintf(err, "%s: not NULL pointer", me);
biffAdd(NRRD, err); return 1;
}
if (!(info = nrrdResampleInfoNew())) {
sprintf(err, "%s: can't allocate resample info struct", me);
biffAdd(NRRD, err); return 1;
}
np = kernel->numParm;
for (ai=0; ai<nin->dim; ai++) {
info->kernel[ai] = kernel;
if (samples) {
info->samples[ai] = samples[ai];
} else {
center = _nrrdCenter(nin->axis[ai].center);
if (nrrdCenterCell == center) {
info->samples[ai] = (size_t)(nin->axis[ai].size*scalings[ai]);
} else {
info->samples[ai] = (size_t)((nin->axis[ai].size - 1)
*scalings[ai]) + 1;
}
}
for (p=0; p<np; p++)
info->parm[ai][p] = parm[p];
/* set the min/max for this axis if not already set to something */
if (!( AIR_EXISTS(nin->axis[ai].min) && AIR_EXISTS(nin->axis[ai].max) ))
nrrdAxisInfoMinMaxSet(nin, ai, nrrdDefaultCenter);
info->min[ai] = nin->axis[ai].min;
info->max[ai] = nin->axis[ai].max;
}
/* we go with the defaults (enstated by _nrrdResampleInfoInit())
for all the remaining fields */
if (nrrdSpatialResample(nout, nin, info)) {
sprintf(err, "%s:", me);
biffAdd(NRRD, err); return 1;
}
info = nrrdResampleInfoNix(info);
return 0;
}
int
unrrdu_resampleMain(int argc, char **argv, char *me, hestParm *hparm) {
hestOpt *opt = NULL;
char *out, *err;
Nrrd *nin, *nout;
int type, bb, pret, norenorm, older, E, defaultCenter, verbose;
unsigned int scaleLen, ai, samplesOut;
airArray *mop;
float *scale;
double padVal;
NrrdResampleInfo *info;
NrrdResampleContext *rsmc;
NrrdKernelSpec *unuk;
mop = airMopNew();
info = nrrdResampleInfoNew();
airMopAdd(mop, info, (airMopper)nrrdResampleInfoNix, airMopAlways);
hparm->elideSingleOtherDefault = AIR_FALSE;
hestOptAdd(&opt, "old", NULL, airTypeInt, 0, 0, &older, NULL,
"instead of using the new nrrdResampleContext implementation, "
"use the old nrrdSpatialResample implementation");
hestOptAdd(&opt, "s,size", "sz0", airTypeOther, 1, -1, &scale, NULL,
"For each axis, information about how many samples in output:\n "
"\b\bo \"=\": leave this axis completely untouched: no "
"resampling whatsoever\n "
"\b\bo \"x<float>\": multiply the number of input samples by "
"<float>, and round to the nearest integer, to get the number "
"of output samples. Use \"x1\" to resample the axis but leave "
"the number of samples unchanged\n "
"\b\bo \"<int>\": exact number of output samples",
&scaleLen, NULL, &unrrduHestScaleCB);
hestOptAdd(&opt, "k,kernel", "kern", airTypeOther, 1, 1, &unuk,
"cubic:0,0.5",
"The kernel to use for resampling. "
"Kernels logically live in the input index space for upsampling, "
"and in the output index space for downsampling. "
"Possibilities include:\n "
"\b\bo \"box\": nearest neighbor interpolation\n "
"\b\bo \"cheap\": nearest neighbor interpolation for upsampling, "
"and non-blurring sub-sampling (pick subset of input samples) "
"on downsampling\n "
"\b\bo \"tent\": linear interpolation\n "
"\b\bo \"cubic:B,C\": Mitchell/Netravali BC-family of "
"cubics:\n "
"\t\t\"cubic:1,0\": B-spline; maximal blurring\n "
"\t\t\"cubic:0,0.5\": Catmull-Rom; good interpolating kernel\n "
"\b\bo \"quartic:A\": 1-parameter family of "
"interpolating quartics (\"quartic:0.0834\" is most accurate)\n "
"\b\bo \"hann:R\": Hann (cosine bell) windowed sinc, radius R\n "
"\b\bo \"black:R\": Blackman windowed sinc, radius R\n "
"\b\bo \"gauss:S,C\": Gaussian blurring, with standard deviation "
"S and cut-off at C standard deviations",
NULL, NULL, nrrdHestKernelSpec);
hestOptAdd(&opt, "nrn", NULL, airTypeInt, 0, 0, &norenorm, NULL,
"don't do per-pass kernel weight renormalization. "
"Doing the renormalization is not a big performance hit, and "
"is sometimes needed to avoid \"grating\" on non-integral "
"down-sampling. Disabling the renormalization is needed for "
"correct results with artificially narrow kernels. ");
hestOptAdd(&opt, "b,boundary", "behavior", airTypeEnum, 1, 1, &bb, "bleed",
"How to handle samples beyond the input bounds:\n "
"\b\bo \"pad\": use some specified value\n "
"\b\bo \"bleed\": extend border values outward\n "
"\b\bo \"wrap\": wrap-around to other side",
NULL, nrrdBoundary);
hestOptAdd(&opt, "v,value", "value", airTypeDouble, 1, 1, &padVal, "0.0",
"for \"pad\" boundary behavior, pad with this value");
hestOptAdd(&opt, "t,type", "type", airTypeOther, 1, 1, &type, "default",
"type to save OUTPUT as. By default (not using this option), "
"the output type is the same as the input type",
NULL, NULL, &unrrduHestMaybeTypeCB);
hestOptAdd(&opt, "cheap", NULL, airTypeInt, 0, 0, &(info->cheap), NULL,
"DEPRECATED: the \"-k cheap\" option is the new (and more "
"reliable) way to access this functionality. \"-cheap\" is "
"only here for legacy use in combination with \"-old\".\n "
"When downsampling (reducing number of samples), don't "
"try to do correct filtering by scaling kernel to match "
"new (stretched) index space; keep it in old index space. "
"When used in conjunction with \"-k box\", this can implement "
"subsampling which chooses every Nth value. ");
hestOptAdd(&opt, "c,center", "center", airTypeEnum, 1, 1, &defaultCenter,
(nrrdCenterCell == nrrdDefaultCenter
? "cell"
: "node"),
"(not available with \"-old\") "
"default centering of axes when input nrrd "
"axes don't have a known centering: \"cell\" or \"node\" ",
NULL, nrrdCenter);
hestOptAdd(&opt, "verbose", NULL, airTypeInt, 0, 0, &verbose, NULL,
"(not available with \"-old\") "
"turn on verbosity ");
OPT_ADD_NIN(nin, "input nrrd");
OPT_ADD_NOUT(out, "output nrrd");
airMopAdd(mop, opt, (airMopper)hestOptFree, airMopAlways);
USAGE(_unrrdu_resampleInfoL);
PARSE();
airMopAdd(mop, opt, (airMopper)hestParseFree, airMopAlways);
nout = nrrdNew();
airMopAdd(mop, nout, (airMopper)nrrdNuke, airMopAlways);
if (scaleLen != nin->dim) {
fprintf(stderr, "%s: # sampling sizes (%d) != input nrrd dimension (%d)\n",
me, scaleLen, nin->dim);
airMopError(mop);
return 1;
}
if (!older) {
rsmc = nrrdResampleContextNew();
rsmc->verbose = verbose;
airMopAdd(mop, rsmc, (airMopper)nrrdResampleContextNix, airMopAlways);
E = AIR_FALSE;
if (!E) E |= nrrdResampleDefaultCenterSet(rsmc, defaultCenter);
if (!E) E |= nrrdResampleNrrdSet(rsmc, nin);
for (ai=0; ai<nin->dim; ai++) {
switch((int)scale[0 + 2*ai]) {
case 0:
/* no resampling */
if (!E) E |= nrrdResampleKernelSet(rsmc, ai, NULL, NULL);
break;
case 1:
/* scaling of input # samples */
if (!E) E |= nrrdResampleKernelSet(rsmc, ai, unuk->kernel, unuk->parm);
samplesOut = AIR_ROUNDUP(scale[1 + 2*ai]*nin->axis[ai].size);
if (!E) E |= nrrdResampleSamplesSet(rsmc, ai, samplesOut);
break;
case 2:
/* explicit # of samples */
if (!E) E |= nrrdResampleKernelSet(rsmc, ai, unuk->kernel, unuk->parm);
samplesOut = (size_t)scale[1 + 2*ai];
if (!E) E |= nrrdResampleSamplesSet(rsmc, ai, samplesOut);
break;
}
if (!E) E |= nrrdResampleRangeFullSet(rsmc, ai);
}
if (!E) E |= nrrdResampleBoundarySet(rsmc, bb);
if (!E) E |= nrrdResampleTypeOutSet(rsmc, type);
if (!E) E |= nrrdResamplePadValueSet(rsmc, padVal);
if (!E) E |= nrrdResampleRenormalizeSet(rsmc, !norenorm);
if (!E) E |= nrrdResampleExecute(rsmc, nout);
if (E) {
airMopAdd(mop, err = biffGetDone(NRRD), airFree, airMopAlways);
fprintf(stderr, "%s: error resampling nrrd:\n%s", me, err);
airMopError(mop);
return 1;
}
} else {
for (ai=0; ai<nin->dim; ai++) {
/* this may be over-written below */
info->kernel[ai] = unuk->kernel;
switch((int)scale[0 + 2*ai]) {
case 0:
/* no resampling */
info->kernel[ai] = NULL;
break;
case 1:
/* scaling of input # samples */
info->samples[ai] = AIR_ROUNDUP(scale[1 + 2*ai]*nin->axis[ai].size);
break;
case 2:
/* explicit # of samples */
info->samples[ai] = (size_t)scale[1 + 2*ai];
break;
}
memcpy(info->parm[ai], unuk->parm, NRRD_KERNEL_PARMS_NUM*sizeof(double));
if (info->kernel[ai] &&
(!( AIR_EXISTS(nin->axis[ai].min)
&& AIR_EXISTS(nin->axis[ai].max))) ) {
nrrdAxisInfoMinMaxSet(nin, ai,
(nin->axis[ai].center
? nin->axis[ai].center
: nrrdDefaultCenter));
}
info->min[ai] = nin->axis[ai].min;
info->max[ai] = nin->axis[ai].max;
}
info->boundary = bb;
info->type = type;
info->padValue = padVal;
info->renormalize = !norenorm;
if (nrrdSpatialResample(nout, nin, info)) {
airMopAdd(mop, err = biffGetDone(NRRD), airFree, airMopAlways);
fprintf(stderr, "%s: error resampling nrrd:\n%s", me, err);
airMopError(mop);
return 1;
}
}
SAVE(out, nout, NULL);
airMopOkay(mop);
return 0;
}