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/* |
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Teem: Tools to process and visualize scientific data and images . |
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Copyright (C) 2013, 2012, 2011, 2010, 2009 University of Chicago |
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Copyright (C) 2008, 2007, 2006, 2005 Gordon Kindlmann |
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Copyright (C) 2004, 2003, 2002, 2001, 2000, 1999, 1998 University of Utah |
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This library is free software; you can redistribute it and/or |
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modify it under the terms of the GNU Lesser General Public License |
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(LGPL) as published by the Free Software Foundation; either |
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version 2.1 of the License, or (at your option) any later version. |
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The terms of redistributing and/or modifying this software also |
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include exceptions to the LGPL that facilitate static linking. |
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This library is distributed in the hope that it will be useful, |
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but WITHOUT ANY WARRANTY; without even the implied warranty of |
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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Lesser General Public License for more details. |
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You should have received a copy of the GNU Lesser General Public License |
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along with this library; if not, write to Free Software Foundation, Inc., |
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51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA |
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*/ |
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#include "ten.h" |
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#include "privateTen.h" |
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#define INFO "Normalize tensor size" |
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static const char *_tend_normInfoL = |
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(INFO |
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". This operates on the eigenvalues of the tensor, and allows " |
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"normalizing some user-defined weighting (\"-w\") of the eigenvalues by " |
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"some user-defined amount (\"-a\")."); |
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int |
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tend_normMain(int argc, const char **argv, const char *me, |
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hestParm *hparm) { |
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int pret; |
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hestOpt *hopt = NULL; |
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char *perr, *err; |
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airArray *mop; |
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Nrrd *nin, *nout; |
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char *outS; |
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float amount, target; |
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double weight[3]; |
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hestOptAdd(&hopt, "w", "w0 w1 w2", airTypeDouble, 3, 3, weight, NULL, |
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"relative weights to put on major, medium, and minor " |
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"eigenvalue when performing normalization (internally " |
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"rescaled to have a 1.0 L1 norm). These weightings determine " |
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"the tensors's \"size\"."); |
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hestOptAdd(&hopt, "a", "amount", airTypeFloat, 1, 1, &amount, "1.0", |
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"how much of the normalization to perform"); |
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hestOptAdd(&hopt, "t", "target", airTypeFloat, 1, 1, &target, "1.0", |
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"target size, post normalization"); |
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hestOptAdd(&hopt, "i", "nin", airTypeOther, 1, 1, &nin, "-", |
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"input diffusion tensor volume", NULL, NULL, nrrdHestNrrd); |
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hestOptAdd(&hopt, "o", "nout", airTypeString, 1, 1, &outS, "-", |
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"output image (floating point)"); |
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mop = airMopNew(); |
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airMopAdd(mop, hopt, (airMopper)hestOptFree, airMopAlways); |
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✓✗ |
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USAGE(_tend_normInfoL); |
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PARSE(); |
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airMopAdd(mop, hopt, (airMopper)hestParseFree, airMopAlways); |
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nout = nrrdNew(); |
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airMopAdd(mop, nout, (airMopper)nrrdNuke, airMopAlways); |
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if (tenSizeNormalize(nout, nin, weight, amount, target)) { |
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airMopAdd(mop, err=biffGetDone(TEN), airFree, airMopAlways); |
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fprintf(stderr, "%s: trouble:\n%s\n", me, err); |
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airMopError(mop); return 1; |
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} |
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if (nrrdSave(outS, nout, NULL)) { |
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airMopAdd(mop, err=biffGetDone(NRRD), airFree, airMopAlways); |
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fprintf(stderr, "%s: trouble writing:\n%s\n", me, err); |
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airMopError(mop); return 1; |
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} |
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airMopOkay(mop); |
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return 0; |
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} |
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TEND_CMD(norm, INFO); |