forked from neurodebian/afni_removeme_eventually
-
Notifications
You must be signed in to change notification settings - Fork 0
/
1ddot.c
311 lines (264 loc) · 9.03 KB
/
1ddot.c
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
#include "mrilib.h"
void usage_1ddot(int detail) {
printf("Usage: 1ddot [options] 1Dfile 1Dfile ...\n"
"* Prints out correlation matrix of the 1D files and\n"
" their inverse correlation matrix.\n"
"* Output appears on stdout.\n"
"* Program 1dCorrelate does something similar-ish.\n"
"\n"
"Options:\n"
" -one = Make 1st vector be all 1's.\n"
" -dem = Remove mean from all vectors (conflicts with '-one')\n"
" -cov = Compute with covariance matrix instead of correlation\n"
" -inn = Computed with inner product matrix instead\n"
" -rank = Compute Spearman rank correlation instead\n"
" (also implies '-terse')\n"
" -terse= Output only the correlation or covariance matrix\n"
" and without any of the garnish. \n"
" -okzero= Do not quit if a vector is all zeros.\n"
" The correlation matrix will have 0 where NaNs ought to go.\n"
" Expect rubbish in the inverse matrices if all zero \n"
" vectors exist.\n"
) ;
PRINT_COMPILE_DATE ;
return;
}
/*----------------------------------------------------------------------------*/
int main( int argc , char *argv[] )
{
int iarg , ii,jj,kk,mm , nvec , do_one=0 , nx=0,ny , ff, doterse = 0 ;
MRI_IMAGE *tim ;
MRI_IMARR *tar ;
double sum , *eval , *amat , **tvec , *bmat , *svec ;
float *far ;
int demean=0 , docov=0 ;
char *matname ;
int okzero = 0;
mainENTRY("1ddot main"); machdep();
/* options */
iarg = 1 ; nvec = 0 ;
while( iarg < argc && argv[iarg][0] == '-' ){
if (strcmp(argv[iarg],"-help") == 0 || strcmp(argv[iarg],"-h") == 0){
usage_1ddot(strlen(argv[iarg])>3 ? 2:1);
exit(0);
}
if( strcmp(argv[iarg],"-one") == 0 ){
demean = 0 ; do_one = 1 ; iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-okzero") == 0 ){
okzero = 1 ; iarg++ ; continue ;
}
if( strncmp(argv[iarg],"-dem",4) == 0 ){
demean = 1 ; do_one = 0 ; iarg++ ; continue ;
}
if( strncmp(argv[iarg],"-cov",4) == 0 ){
docov = 1 ; iarg++ ; continue ;
}
if( strncmp(argv[iarg],"-inn",4) == 0 ){
docov = 2 ; iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-rank") == 0 ||
strcasecmp(argv[iarg],"-spearman") == 0 ){
do_one = 0; docov = 3; demean = 0; doterse = 1; iarg++; continue;
}
if( strncmp(argv[iarg],"-terse",4) == 0 ){
doterse = 1 ; iarg++ ; continue ;
}
fprintf(stderr,"** Unknown option: %s\n",argv[iarg]);
suggest_best_prog_option(argv[0], argv[iarg]);
exit(1);
}
if( argc < 2 ){ usage_1ddot(1); exit(0) ; }
if( iarg == argc ) ERROR_exit("No 1D files on command line!?") ;
/* input 1D files */
ff = iarg ;
INIT_IMARR(tar) ; if( do_one ) nvec = 1 ;
for( ; iarg < argc ; iarg++ ){
tim = mri_read_1D( argv[iarg] ) ;
if( tim == NULL ){
fprintf(stderr,"** Can't read 1D file %s\n",argv[iarg]); exit(1);
}
if( nx == 0 ){
nx = tim->nx ;
} else if( tim->nx != nx ){
fprintf(stderr,"** 1D file %s doesn't match first file in length!\n",
argv[iarg]); exit(1);
}
nvec += tim->ny ;
ADDTO_IMARR(tar,tim) ;
}
if (!doterse) {
printf("\n") ;
printf("++ 1ddot input vectors:\n") ;
}
jj = 0 ;
if( do_one ){
if (!doterse) printf("00..00: all ones\n") ;
jj = 1 ;
}
for( mm=0 ; mm < IMARR_COUNT(tar) ; mm++ ){
tim = IMARR_SUBIM(tar,mm) ;
if (!doterse) printf("%02d..%02d: %s\n", jj,jj+tim->ny-1, argv[ff+mm] ) ;
jj += tim->ny ;
}
/* create vectors from 1D files */
tvec = (double **) malloc( sizeof(double *)*nvec ) ;
svec = (double * ) malloc( sizeof(double )*nvec ) ;
for( jj=0 ; jj < nvec ; jj++ )
tvec[jj] = (double *) malloc( sizeof(double)*nx ) ;
kk = 0 ;
if( do_one ){
svec[0] = 1.0 / sqrt((double)nx) ;
for( ii=0 ; ii < nx ; ii++ ) tvec[0][ii] = 1.0 ;
kk = 1 ;
}
for( mm=0 ; mm < IMARR_COUNT(tar) ; mm++ ){
tim = IMARR_SUBIM(tar,mm) ;
far = MRI_FLOAT_PTR(tim) ;
for( jj=0 ; jj < tim->ny ; jj++,kk++ ){
for( ii=0 ; ii < nx ; ii++ ) tvec[kk][ii] = far[ii+jj*nx] ;
if( demean ){
sum = 0.0 ;
for( ii=0 ; ii < nx ; ii++ ) sum += tvec[kk][ii] ;
sum /= nx ;
for( ii=0 ; ii < nx ; ii++ ) tvec[kk][ii] -= sum ;
}
sum = 0.0 ;
for( ii=0 ; ii < nx ; ii++ ) sum += tvec[kk][ii] * tvec[kk][ii] ;
if( sum == 0.0 ) {
if (okzero) svec[kk] = 0.0;
else ERROR_exit("Input column %02d is all zero!",kk) ;
} else {
svec[kk] = 1.0 / sqrt(sum) ;
}
}
}
DESTROY_IMARR(tar) ;
/* normalize vectors? (for ordinary correlation) */
if( !docov ){
for( kk=0 ; kk < nvec ; kk++ ){
sum = svec[kk] ;
for( ii=0 ; ii < nx ; ii++ ) tvec[kk][ii] *= sum ;
}
}
switch(docov){
default:
case 3: matname = "Spearman" ; break ;
case 2: matname = "InnerProduct" ; break ;
case 1: matname = "Covariance" ; break ;
case 0: matname = "Correlation" ; break ;
}
/* create matrix from dot product of vectors */
amat = (double *) calloc( sizeof(double) , nvec*nvec ) ;
if( docov != 3 ){
for( kk=0 ; kk < nvec ; kk++ ){
for( jj=0 ; jj <= kk ; jj++ ){
sum = 0.0 ;
for( ii=0 ; ii < nx ; ii++ ) sum += tvec[jj][ii] * tvec[kk][ii] ;
amat[jj+nvec*kk] = sum ;
if( jj < kk ) amat[kk+nvec*jj] = sum ;
}
}
} else { /* Spearman */
for( kk=0 ; kk < nvec ; kk++ ){
for( jj=0 ; jj <= kk ; jj++ ){
amat[jj+nvec*kk] = THD_spearman_corr_dble( nx , tvec[jj] , tvec[kk] ) ;
if( jj < kk ) amat[kk+nvec*jj] = amat[jj+nvec*kk] ;
}
}
}
/* normalize */
if (docov==1) {
for( kk=0 ; kk < nvec ; kk++ ){
for( jj=0 ; jj <= kk ; jj++ ){
sum = amat[jj+nvec*kk] / (double) (nx-1);
amat[jj+nvec*kk] = sum;
if( jj < kk ) amat[kk+nvec*jj] = sum ;
}
}
}
/* print matrix out */
if (!doterse) {
printf("\n"
"++ %s Matrix:\n ",matname) ;
for( jj=0 ; jj < nvec ; jj++ ) printf(" %02d ",jj) ;
printf("\n ") ;
for( jj=0 ; jj < nvec ; jj++ ) printf(" ---------") ;
printf("\n") ;
}
for( kk=0 ; kk < nvec ; kk++ ){
if (!doterse) printf("%02d:",kk) ;
for( jj=0 ; jj < nvec ; jj++ ) printf(" %9.5f",amat[jj+kk*nvec]) ;
printf("\n") ;
}
if (doterse) exit(0) ; /* au revoir */
/* compute eigendecomposition */
eval = (double *) malloc( sizeof(double)*nvec ) ;
symeig_double( nvec , amat , eval ) ;
printf("\n"
"++ Eigensolution of %s Matrix:\n " , matname ) ;
for( jj=0 ; jj < nvec ; jj++ ) printf(" %9.5f",eval[jj]) ;
printf("\n ") ;
for( jj=0 ; jj < nvec ; jj++ ) printf(" ---------") ;
printf("\n") ;
for( kk=0 ; kk < nvec ; kk++ ){
printf("%02d:",kk) ;
for( jj=0 ; jj < nvec ; jj++ ) printf(" %9.5f",amat[kk+jj*nvec]) ;
printf("\n") ;
}
/* compute matrix inverse */
if ( eval[0]/eval[nvec-1] < 1.0e-10) {
printf("\n"
"-- WARNING: Matrix is near singular,\n"
" rubbish likely for inverses ahead.\n");
}
for( jj=0 ; jj < nvec ; jj++ ) eval[jj] = 1.0 / eval[jj] ;
bmat = (double *) calloc( sizeof(double) , nvec*nvec ) ;
for( ii=0 ; ii < nvec ; ii++ ){
for( jj=0 ; jj < nvec ; jj++ ){
sum = 0.0 ;
for( kk=0 ; kk < nvec ; kk++ )
sum += amat[ii+kk*nvec] * amat[jj+kk*nvec] * eval[kk] ;
bmat[ii+jj*nvec] = sum ;
}
}
printf("\n") ;
printf("++ %s Matrix Inverse:\n " , matname ) ;
for( jj=0 ; jj < nvec ; jj++ ) printf(" %02d ",jj) ;
printf("\n ") ;
for( jj=0 ; jj < nvec ; jj++ ) printf(" ---------") ;
printf("\n") ;
for( kk=0 ; kk < nvec ; kk++ ){
printf("%02d:",kk) ;
for( jj=0 ; jj < nvec ; jj++ ) printf(" %9.5f",bmat[jj+kk*nvec]) ;
printf("\n") ;
}
/* square roots of diagonals of the above */
printf("\n") ;
printf("++ %s sqrt(diagonal)\n ",matname) ;
for( jj=0 ; jj < nvec ; jj++ ) printf(" %9.5f",sqrt(bmat[jj+jj*nvec])) ;
printf("\n") ;
/* normalize matrix inverse */
for( ii=0 ; ii < nvec ; ii++ ){
for( jj=0 ; jj < nvec ; jj++ ){
sum = bmat[ii+ii*nvec] * bmat[jj+jj*nvec] ;
if( sum > 0.0 )
amat[ii+jj*nvec] = bmat[ii+jj*nvec] / sqrt(sum) ;
else
amat[ii+jj*nvec] = 0.0 ;
}
}
printf("\n") ;
printf("++ %s Matrix Inverse Normalized:\n " , matname ) ;
for( jj=0 ; jj < nvec ; jj++ ) printf(" %02d ",jj) ;
printf("\n ") ;
for( jj=0 ; jj < nvec ; jj++ ) printf(" ---------") ;
printf("\n") ;
for( kk=0 ; kk < nvec ; kk++ ){
printf("%02d:",kk) ;
for( jj=0 ; jj < nvec ; jj++ ) printf(" %9.5f",amat[jj+kk*nvec]) ;
printf("\n") ;
}
/* done */
exit(0) ;
}