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 "Estimate models from a set of DW images"
28 static const char *_tend_mfitInfoL =
29 (INFO
30 ". More docs here.");
31
32 int
tend_mfitMain(int argc,const char ** argv,const char * me,hestParm * hparm)33 tend_mfitMain(int argc, const char **argv, const char *me,
34 hestParm *hparm) {
35 int pret;
36 hestOpt *hopt = NULL;
37 char *perr, *err;
38 airArray *mop;
39
40 Nrrd *nin, *nout, *nterr, *nconv, *niter;
41 char *outS, *terrS, *convS, *iterS, *modS;
42 int knownB0, saveB0, verbose, mlfit, typeOut;
43 unsigned int maxIter, minIter, starts;
44 double sigma, eps;
45 const tenModel *model;
46 tenExperSpec *espec;
47
48 hestOptAdd(&hopt, "v", "verbose", airTypeInt, 1, 1, &verbose, "0",
49 "verbosity level");
50 hestOptAdd(&hopt, "m", "model", airTypeString, 1, 1, &modS, NULL,
51 "which model to fit. Use optional \"b0+\" prefix to "
52 "indicate that the B0 image should also be saved "
53 "(independent of whether it was known or had to be "
54 "estimated, according to \"-knownB0\").");
55 hestOptAdd(&hopt, "ns", "# starts", airTypeUInt, 1, 1, &starts, "1",
56 "number of random starting points at which to initialize "
57 "fitting");
58 hestOptAdd(&hopt, "ml", NULL, airTypeInt, 0, 0, &mlfit, NULL,
59 "do ML fitting, rather than least-squares, which also "
60 "requires setting \"-sigma\"");
61 hestOptAdd(&hopt, "sigma", "sigma", airTypeDouble, 1, 1, &sigma, "nan",
62 "Gaussian/Rician noise parameter");
63 hestOptAdd(&hopt, "eps", "eps", airTypeDouble, 1, 1, &eps, "0.01",
64 "convergence epsilon");
65 hestOptAdd(&hopt, "mini", "min iters", airTypeUInt, 1, 1, &minIter, "3",
66 "minimum required # iterations for fitting.");
67 hestOptAdd(&hopt, "maxi", "max iters", airTypeUInt, 1, 1, &maxIter, "100",
68 "maximum allowable # iterations for fitting.");
69 hestOptAdd(&hopt, "knownB0", "bool", airTypeBool, 1, 1, &knownB0, NULL,
70 "Indicates if the B=0 non-diffusion-weighted reference image "
71 "is known (\"true\") because it appears one or more times "
72 "amongst the DWIs, or, if it has to be estimated along with "
73 "the other model parameters (\"false\")");
74 /* (this is now specified as part of the "-m" model description)
75 hestOptAdd(&hopt, "saveB0", "bool", airTypeBool, 1, 1, &saveB0, NULL,
76 "Indicates if the B=0 non-diffusion-weighted value "
77 "should be saved in output, regardless of whether it was "
78 "known or had to be esimated");
79 */
80 hestOptAdd(&hopt, "t", "type", airTypeEnum, 1, 1, &typeOut, "float",
81 "output type of model parameters",
82 NULL, nrrdType);
83 hestOptAdd(&hopt, "i", "dwi", airTypeOther, 1, 1, &nin, "-",
84 "all the diffusion-weighted images in one 4D nrrd",
85 NULL, NULL, nrrdHestNrrd);
86 hestOptAdd(&hopt, "o", "nout", airTypeString, 1, 1, &outS, "-",
87 "output parameter vector image");
88 hestOptAdd(&hopt, "eo", "filename", airTypeString, 1, 1, &terrS, "",
89 "Giving a filename here allows you to save out the per-sample "
90 "fitting error. By default, no such error is saved.");
91 hestOptAdd(&hopt, "co", "filename", airTypeString, 1, 1, &convS, "",
92 "Giving a filename here allows you to save out the per-sample "
93 "convergence fraction. By default, no such error is saved.");
94 hestOptAdd(&hopt, "io", "filename", airTypeString, 1, 1, &iterS, "",
95 "Giving a filename here allows you to save out the per-sample "
96 "number of iterations needed for fitting. "
97 "By default, no such error is saved.");
98
99 mop = airMopNew();
100 airMopAdd(mop, hopt, (airMopper)hestOptFree, airMopAlways);
101 USAGE(_tend_mfitInfoL);
102 JUSTPARSE();
103 airMopAdd(mop, hopt, (airMopper)hestParseFree, airMopAlways);
104
105 nterr = NULL;
106 nconv = NULL;
107 niter = NULL;
108 espec = tenExperSpecNew();
109 airMopAdd(mop, espec, (airMopper)tenExperSpecNix, airMopAlways);
110 nout = nrrdNew();
111 airMopAdd(mop, nout, (airMopper)nrrdNuke, airMopAlways);
112 if (tenModelParse(&model, &saveB0, AIR_FALSE, modS)) {
113 airMopAdd(mop, err=biffGetDone(TEN), airFree, airMopAlways);
114 fprintf(stderr, "%s: trouble parsing model \"%s\":\n%s\n", me, modS, err);
115 airMopError(mop); return 1;
116 }
117 if (tenExperSpecFromKeyValueSet(espec, nin)) {
118 airMopAdd(mop, err=biffGetDone(TEN), airFree, airMopAlways);
119 fprintf(stderr, "%s: trouble getting exper from kvp:\n%s\n", me, err);
120 airMopError(mop); return 1;
121 }
122 if (tenModelSqeFit(nout,
123 airStrlen(terrS) ? &nterr : NULL,
124 airStrlen(convS) ? &nconv : NULL,
125 airStrlen(iterS) ? &niter : NULL,
126 model, espec, nin,
127 knownB0, saveB0, typeOut,
128 minIter, maxIter, starts, eps,
129 NULL, verbose)) {
130 airMopAdd(mop, err=biffGetDone(TEN), airFree, airMopAlways);
131 fprintf(stderr, "%s: trouble fitting:\n%s\n", me, err);
132 airMopError(mop); return 1;
133 }
134
135 if (nrrdSave(outS, nout, NULL)
136 || (airStrlen(terrS) && nrrdSave(terrS, nterr, NULL))
137 || (airStrlen(convS) && nrrdSave(convS, nconv, NULL))
138 || (airStrlen(iterS) && nrrdSave(iterS, niter, NULL))) {
139 airMopAdd(mop, err=biffGetDone(NRRD), airFree, airMopAlways);
140 fprintf(stderr, "%s: trouble writing output:\n%s\n", me, err);
141 airMopError(mop); return 1;
142 }
143
144 airMopOkay(mop);
145 return 0;
146 }
147 /* TEND_CMD(mfit, INFO); */
148 unrrduCmd tend_mfitCmd = { "mfit", INFO, tend_mfitMain };
149