| 1 |
#ifndef lint |
| 2 |
static const char RCSid[] = "$Id: rttree_reduce.c,v 2.4 2011/06/03 18:12:58 greg Exp $"; |
| 3 |
#endif |
| 4 |
/* |
| 5 |
* A utility called by genBSDF.pl to reduce tensor tree samples and output |
| 6 |
* in a standard format as required by XML specification for variable |
| 7 |
* resolution BSDF data. We are not meant to be run by the user directly. |
| 8 |
*/ |
| 9 |
|
| 10 |
#include "rtio.h" |
| 11 |
#include "rterror.h" |
| 12 |
#include "platform.h" |
| 13 |
#include <stdlib.h> |
| 14 |
#include <math.h> |
| 15 |
|
| 16 |
float *datarr; /* our loaded BSDF data array */ |
| 17 |
int ttrank = 4; /* tensor tree rank */ |
| 18 |
int log2g = 4; /* log2 of grid resolution */ |
| 19 |
int infmt = 'a'; /* input format ('a','f','d') */ |
| 20 |
double pctcull = 95.; /* target culling percentile */ |
| 21 |
|
| 22 |
#define dval3(ix,ox,oy) datarr[((((ix)<<log2g)+(ox))<<log2g)+(oy)] |
| 23 |
#define dval4(ix,iy,ox,oy) datarr[((((((ix)<<log2g)+(iy))<<log2g)+(ox))<<log2g)+(oy)] |
| 24 |
|
| 25 |
/* Tensor tree node */ |
| 26 |
typedef struct ttree_s { |
| 27 |
float vmin, vmax; /* value extrema */ |
| 28 |
float vavg; /* average */ |
| 29 |
struct ttree_s *kid; /* 2^ttrank children */ |
| 30 |
} TNODE; |
| 31 |
|
| 32 |
#define HISTLEN 300 /* histogram resolution */ |
| 33 |
#define HISTMAX 10. /* maximum recorded measure in histogram */ |
| 34 |
|
| 35 |
int histo[HISTLEN]; /* histogram freq. of variance measure */ |
| 36 |
|
| 37 |
double tthresh; /* acceptance threshold (TBD) */ |
| 38 |
|
| 39 |
#define var_measure(tp) ( ((tp)->vmax - (tp)->vmin) / \ |
| 40 |
(sqrt((tp)->vavg) + .03) ) |
| 41 |
#define above_threshold(tp) (var_measure(tp) > tthresh) |
| 42 |
|
| 43 |
/* Allocate a new set of children for the given node (no checks) */ |
| 44 |
static void |
| 45 |
new_kids(TNODE *pn) |
| 46 |
{ |
| 47 |
pn->kid = (TNODE *)calloc(1<<ttrank, sizeof(TNODE)); |
| 48 |
if (pn->kid == NULL) |
| 49 |
error(SYSTEM, "out of memory in new_kids"); |
| 50 |
} |
| 51 |
|
| 52 |
/* Free children for this node */ |
| 53 |
static void |
| 54 |
free_kids(TNODE *pn) |
| 55 |
{ |
| 56 |
int i; |
| 57 |
|
| 58 |
if (pn->kid == NULL) |
| 59 |
return; |
| 60 |
for (i = 1<<ttrank; i--; ) |
| 61 |
free_kids(pn->kid+i); |
| 62 |
free(pn->kid); |
| 63 |
pn->kid = NULL; |
| 64 |
} |
| 65 |
|
| 66 |
/* Build a tensor tree starting from the given hypercube */ |
| 67 |
static void |
| 68 |
build_tree(TNODE *tp, const int bmin[], int l2s) |
| 69 |
{ |
| 70 |
int bkmin[4]; |
| 71 |
int i, j; |
| 72 |
|
| 73 |
tp->vmin = 1e20; |
| 74 |
tp->vmax = 0; |
| 75 |
tp->vavg = 0; |
| 76 |
if (l2s <= 1) { /* reached upper leaves */ |
| 77 |
for (i = 1<<ttrank; i--; ) { |
| 78 |
float val; |
| 79 |
for (j = ttrank; j--; ) |
| 80 |
bkmin[j] = bmin[j] + (i>>j & 1); |
| 81 |
val = (ttrank == 3) ? dval3(bkmin[0],bkmin[1],bkmin[2]) |
| 82 |
: dval4(bkmin[0],bkmin[1],bkmin[2],bkmin[3]); |
| 83 |
if (val < tp->vmin) |
| 84 |
tp->vmin = val; |
| 85 |
if (val > tp->vmax) |
| 86 |
tp->vmax = val; |
| 87 |
tp->vavg += val; |
| 88 |
} |
| 89 |
tp->vavg /= (float)(1<<ttrank); |
| 90 |
/* record stats */ |
| 91 |
i = (HISTLEN/HISTMAX) * var_measure(tp); |
| 92 |
if (i >= HISTLEN) i = HISTLEN-1; |
| 93 |
++histo[i]; |
| 94 |
return; |
| 95 |
} |
| 96 |
--l2s; /* else still branching */ |
| 97 |
new_kids(tp); /* grow recursively */ |
| 98 |
for (i = 1<<ttrank; i--; ) { |
| 99 |
for (j = ttrank; j--; ) |
| 100 |
bkmin[j] = bmin[j] + ((i>>j & 1)<<l2s); |
| 101 |
build_tree(tp->kid+i, bkmin, l2s); |
| 102 |
if (tp->kid[i].vmin < tp->vmin) |
| 103 |
tp->vmin = tp->kid[i].vmin; |
| 104 |
if (tp->kid[i].vmax > tp->vmax) |
| 105 |
tp->vmax = tp->kid[i].vmax; |
| 106 |
tp->vavg += tp->kid[i].vavg; |
| 107 |
} |
| 108 |
tp->vavg /= (float)(1<<ttrank); |
| 109 |
} |
| 110 |
|
| 111 |
/* Set our trimming threshold */ |
| 112 |
static void |
| 113 |
set_threshold() |
| 114 |
{ |
| 115 |
int hsum = 0; |
| 116 |
int i; |
| 117 |
|
| 118 |
for (i = HISTLEN; i--; ) |
| 119 |
hsum += histo[i]; |
| 120 |
hsum = pctcull*.01 * (double)hsum; |
| 121 |
for (i = 0; hsum > 0; i++) |
| 122 |
hsum -= histo[i]; |
| 123 |
tthresh = (HISTMAX/HISTLEN) * i; |
| 124 |
} |
| 125 |
|
| 126 |
/* Trim our tree according to the current threshold */ |
| 127 |
static void |
| 128 |
trim_tree(TNODE *tp) |
| 129 |
{ |
| 130 |
if (tp->kid == NULL) |
| 131 |
return; |
| 132 |
if (above_threshold(tp)) { /* keeping branches? */ |
| 133 |
int i = 1<<ttrank; |
| 134 |
while (i--) |
| 135 |
trim_tree(tp->kid+i); |
| 136 |
return; |
| 137 |
} |
| 138 |
free_kids(tp); /* else trim at this point */ |
| 139 |
} |
| 140 |
|
| 141 |
/* Print a tensor tree from the given hypercube */ |
| 142 |
static void |
| 143 |
print_tree(const TNODE *tp, const int bmin[], int l2s) |
| 144 |
{ |
| 145 |
int bkmin[4]; |
| 146 |
int i, j; |
| 147 |
|
| 148 |
for (j = log2g-l2s; j--; ) /* indent based on branch level */ |
| 149 |
fputs(" ", stdout); |
| 150 |
fputc('{', stdout); /* special case for upper leaves */ |
| 151 |
if (l2s <= 1 && above_threshold(tp)) { |
| 152 |
for (i = 0; i < 1<<ttrank; i++) { |
| 153 |
float val; |
| 154 |
for (j = ttrank; j--; ) |
| 155 |
bkmin[j] = bmin[j] + (i>>(ttrank-1-j) & 1); |
| 156 |
val = (ttrank == 3) ? dval3(bkmin[0],bkmin[1],bkmin[2]) |
| 157 |
: dval4(bkmin[0],bkmin[1],bkmin[2],bkmin[3]); |
| 158 |
printf(" %.4e", val); |
| 159 |
} |
| 160 |
fputs(" }\n", stdout); |
| 161 |
return; |
| 162 |
} |
| 163 |
if (tp->kid == NULL) { /* trimmed limb */ |
| 164 |
printf(" %.6e }\n", tp->vavg); |
| 165 |
return; |
| 166 |
} |
| 167 |
--l2s; /* else still branching */ |
| 168 |
fputc('\n', stdout); |
| 169 |
for (i = 0; i < 1<<ttrank; i++) { |
| 170 |
for (j = ttrank; j--; ) |
| 171 |
bkmin[j] = bmin[j] + ((i>>j & 1)<<l2s); |
| 172 |
print_tree(tp->kid+i, bkmin, l2s); |
| 173 |
} |
| 174 |
++l2s; |
| 175 |
for (j = log2g-l2s; j--; ) |
| 176 |
fputs(" ", stdout); |
| 177 |
fputs("}\n", stdout); |
| 178 |
} |
| 179 |
|
| 180 |
/* Read a row of data in ASCII */ |
| 181 |
static int |
| 182 |
read_ascii(float *rowp, int n) |
| 183 |
{ |
| 184 |
int n2go; |
| 185 |
|
| 186 |
if ((rowp == NULL) | (n <= 0)) |
| 187 |
return(0); |
| 188 |
for (n2go = n; n2go; n2go--) |
| 189 |
if (scanf("%f", rowp++) != 1) |
| 190 |
break; |
| 191 |
if (n2go) |
| 192 |
error(USER, "unexpected EOD on ascii input"); |
| 193 |
return(n-n2go); |
| 194 |
} |
| 195 |
|
| 196 |
/* Read a row of float data */ |
| 197 |
static int |
| 198 |
read_float(float *rowp, int n) |
| 199 |
{ |
| 200 |
int nread; |
| 201 |
|
| 202 |
if ((rowp == NULL) | (n <= 0)) |
| 203 |
return(0); |
| 204 |
nread = fread(rowp, sizeof(float), n, stdin); |
| 205 |
if (nread != n) |
| 206 |
error(USER, "unexpected EOF on float input"); |
| 207 |
return(nread); |
| 208 |
} |
| 209 |
|
| 210 |
/* Read a row of double data */ |
| 211 |
static int |
| 212 |
read_double(float *rowp, int n) |
| 213 |
{ |
| 214 |
static double *rowbuf = NULL; |
| 215 |
static int rblen = 0; |
| 216 |
int nread, i; |
| 217 |
|
| 218 |
if ((rowp == NULL) | (n <= 0)) { |
| 219 |
if (rblen) { |
| 220 |
free(rowbuf); |
| 221 |
rowbuf = NULL; rblen = 0; |
| 222 |
} |
| 223 |
return(0); |
| 224 |
} |
| 225 |
if (rblen < n) { |
| 226 |
rowbuf = (double *)realloc(rowbuf, sizeof(double)*(rblen=n)); |
| 227 |
if (rowbuf == NULL) |
| 228 |
error(SYSTEM, "out of memory in read_double"); |
| 229 |
} |
| 230 |
nread = fread(rowbuf, sizeof(double), n, stdin); |
| 231 |
if (nread != n) |
| 232 |
error(USER, "unexpected EOF on double input"); |
| 233 |
for (i = 0; i < nread; i++) |
| 234 |
*rowp++ = rowbuf[i]; |
| 235 |
return(nread); |
| 236 |
} |
| 237 |
|
| 238 |
/* Load data array, filling zeroes for rank 3 demi-tensor */ |
| 239 |
static void |
| 240 |
load_data() |
| 241 |
{ |
| 242 |
int (*readf)(float *, int) = NULL; |
| 243 |
|
| 244 |
switch (infmt) { |
| 245 |
case 'a': |
| 246 |
readf = &read_ascii; |
| 247 |
break; |
| 248 |
case 'f': |
| 249 |
readf = &read_float; |
| 250 |
break; |
| 251 |
case 'd': |
| 252 |
readf = &read_double; |
| 253 |
break; |
| 254 |
default: |
| 255 |
error(COMMAND, "unsupported input format"); |
| 256 |
break; |
| 257 |
} |
| 258 |
datarr = (float *)calloc(1<<(log2g*ttrank), sizeof(float)); |
| 259 |
if (datarr == NULL) |
| 260 |
error(SYSTEM, "out of memory in load_data"); |
| 261 |
if (ttrank == 3) { |
| 262 |
int ix, ox; |
| 263 |
for (ix = 0; ix < 1<<(log2g-1); ix++) |
| 264 |
for (ox = 0; ox < 1<<log2g; ox++) |
| 265 |
(*readf)(datarr+(((ix<<log2g)+ox)<<log2g), |
| 266 |
1<<log2g); |
| 267 |
} else /* ttrank == 4 */ { |
| 268 |
int ix, iy, ox; |
| 269 |
for (ix = 0; ix < 1<<log2g; ix++) |
| 270 |
for (iy = 0; iy < 1<<log2g; iy++) |
| 271 |
for (ox = 0; ox < 1<<log2g; ox++) |
| 272 |
(*readf)(datarr + |
| 273 |
(((((ix<<log2g)+iy)<<log2g)+ox)<<log2g), |
| 274 |
1<<log2g); |
| 275 |
} |
| 276 |
(*readf)(NULL, 0); /* releases any buffers */ |
| 277 |
if (infmt == 'a') { |
| 278 |
int c; |
| 279 |
while ((c = getc(stdin)) != EOF) { |
| 280 |
switch (c) { |
| 281 |
case ' ': |
| 282 |
case '\t': |
| 283 |
case '\r': |
| 284 |
case '\n': |
| 285 |
continue; |
| 286 |
} |
| 287 |
error(WARNING, "data past end of expected input"); |
| 288 |
break; |
| 289 |
} |
| 290 |
} else if (getc(stdin) != EOF) |
| 291 |
error(WARNING, "binary data past end of expected input"); |
| 292 |
} |
| 293 |
|
| 294 |
/* Load BSDF array, coalesce uniform regions and format as tensor tree */ |
| 295 |
int |
| 296 |
main(int argc, char *argv[]) |
| 297 |
{ |
| 298 |
int doheader = 1; |
| 299 |
int bmin[4]; |
| 300 |
TNODE gtree; |
| 301 |
int i; |
| 302 |
/* get options and parameters */ |
| 303 |
for (i = 1; i < argc && argv[i][0] == '-'; i++) |
| 304 |
switch (argv[i][1]) { |
| 305 |
case 'h': |
| 306 |
doheader = !doheader; |
| 307 |
break; |
| 308 |
case 'r': |
| 309 |
ttrank = atoi(argv[++i]); |
| 310 |
if (ttrank != 3 && ttrank != 4) |
| 311 |
goto userr; |
| 312 |
break; |
| 313 |
case 'g': |
| 314 |
log2g = atoi(argv[++i]); |
| 315 |
if (log2g <= 1) |
| 316 |
goto userr; |
| 317 |
break; |
| 318 |
case 't': |
| 319 |
pctcull = atof(argv[++i]); |
| 320 |
if ((pctcull < 0) | (pctcull >= 100.)) |
| 321 |
goto userr; |
| 322 |
break; |
| 323 |
case 'f': |
| 324 |
infmt = argv[i][2]; |
| 325 |
if (!infmt || strchr("afd", infmt) == NULL) |
| 326 |
goto userr; |
| 327 |
break; |
| 328 |
default: |
| 329 |
goto userr; |
| 330 |
} |
| 331 |
if (i < argc-1) |
| 332 |
goto userr; |
| 333 |
/* load input data */ |
| 334 |
if (i == argc-1 && freopen(argv[i], "rb", stdin) == NULL) { |
| 335 |
sprintf(errmsg, "cannot open input file '%s'", argv[i]); |
| 336 |
error(SYSTEM, errmsg); |
| 337 |
} |
| 338 |
if (infmt != 'a') |
| 339 |
SET_FILE_BINARY(stdin); |
| 340 |
load_data(); |
| 341 |
if (doheader) { |
| 342 |
for (i = 0; i < argc; i++) { |
| 343 |
fputs(argv[i], stdout); |
| 344 |
fputc(i < argc-1 ? ' ' : '\n', stdout); |
| 345 |
} |
| 346 |
fputc('\n', stdout); |
| 347 |
} |
| 348 |
gtree.kid = NULL; /* create our tree */ |
| 349 |
bmin[0] = bmin[1] = bmin[2] = bmin[3] = 0; |
| 350 |
build_tree(>ree, bmin, log2g); |
| 351 |
/* compute threshold & trim tree */ |
| 352 |
set_threshold(); |
| 353 |
trim_tree(>ree); |
| 354 |
/* format to stdout */ |
| 355 |
print_tree(>ree, bmin, log2g); |
| 356 |
/* Clean up isn't necessary for main()... |
| 357 |
free_kids(>ree); |
| 358 |
free(datarr); |
| 359 |
*/ |
| 360 |
return(0); |
| 361 |
userr: |
| 362 |
fprintf(stderr, "Usage: %s [-h][-f{a|f|d}][-r {3|4}][-g log2grid][-t trim%%] [input]\n", |
| 363 |
argv[0]); |
| 364 |
return(1); |
| 365 |
} |
