1 /*
2 Teem: Tools to process and visualize scientific data and images .
3 Copyright (C) 2012, 2011, 2010, 2009 University of Chicago
4 Copyright (C) 2008, 2007, 2006, 2005 Gordon Kindlmann
5 Copyright (C) 2004, 2003, 2002, 2001, 2000, 1999, 1998 University of Utah
6
7 This library is free software; you can redistribute it and/or
8 modify it under the terms of the GNU Lesser General Public License
9 (LGPL) as published by the Free Software Foundation; either
10 version 2.1 of the License, or (at your option) any later version.
11 The terms of redistributing and/or modifying this software also
12 include exceptions to the LGPL that facilitate static linking.
13
14 This library is distributed in the hope that it will be useful,
15 but WITHOUT ANY WARRANTY; without even the implied warranty of
16 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
17 Lesser General Public License for more details.
18
19 You should have received a copy of the GNU Lesser General Public License
20 along with this library; if not, write to Free Software Foundation, Inc.,
21 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
22 */
23
24 #include "ten.h"
25 #include "privateTen.h"
26
27 #define INFO "Normalize tensor size"
28 static const char *_tend_normInfoL =
29 (INFO
30 ". This operates on the eigenvalues of the tensor, and allows "
31 "normalizing some user-defined weighting (\"-w\") of the eigenvalues by "
32 "some user-defined amount (\"-a\").");
33
34 int
tend_normMain(int argc,const char ** argv,const char * me,hestParm * hparm)35 tend_normMain(int argc, const char **argv, const char *me,
36 hestParm *hparm) {
37 int pret;
38 hestOpt *hopt = NULL;
39 char *perr, *err;
40 airArray *mop;
41
42 Nrrd *nin, *nout;
43 char *outS;
44 float amount, target;
45 double weight[3];
46
47 hestOptAdd(&hopt, "w", "w0 w1 w2", airTypeDouble, 3, 3, weight, NULL,
48 "relative weights to put on major, medium, and minor "
49 "eigenvalue when performing normalization (internally "
50 "rescaled to have a 1.0 L1 norm). These weightings determine "
51 "the tensors's \"size\".");
52 hestOptAdd(&hopt, "a", "amount", airTypeFloat, 1, 1, &amount, "1.0",
53 "how much of the normalization to perform");
54 hestOptAdd(&hopt, "t", "target", airTypeFloat, 1, 1, &target, "1.0",
55 "target size, post normalization");
56 hestOptAdd(&hopt, "i", "nin", airTypeOther, 1, 1, &nin, "-",
57 "input diffusion tensor volume", NULL, NULL, nrrdHestNrrd);
58 hestOptAdd(&hopt, "o", "nout", airTypeString, 1, 1, &outS, "-",
59 "output image (floating point)");
60
61 mop = airMopNew();
62 airMopAdd(mop, hopt, (airMopper)hestOptFree, airMopAlways);
63 USAGE(_tend_normInfoL);
64 PARSE();
65 airMopAdd(mop, hopt, (airMopper)hestParseFree, airMopAlways);
66
67 nout = nrrdNew();
68 airMopAdd(mop, nout, (airMopper)nrrdNuke, airMopAlways);
69 if (tenSizeNormalize(nout, nin, weight, amount, target)) {
70 airMopAdd(mop, err=biffGetDone(TEN), airFree, airMopAlways);
71 fprintf(stderr, "%s: trouble:\n%s\n", me, err);
72 airMopError(mop); return 1;
73 }
74 if (nrrdSave(outS, nout, NULL)) {
75 airMopAdd(mop, err=biffGetDone(NRRD), airFree, airMopAlways);
76 fprintf(stderr, "%s: trouble writing:\n%s\n", me, err);
77 airMopError(mop); return 1;
78 }
79
80 airMopOkay(mop);
81 return 0;
82 }
83 TEND_CMD(norm, INFO);
84