/* flame - cosmic recursive fractal flames Copyright (C) 1992 Scott Draves This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. */ #include "rect.h" #include /* for batch * interpolate * compute colormap * for subbatch * compute samples * buckets += cmap[samples] * accum += time_filter[batch] * log(buckets) * image = filter(accum) */ typedef short bucket[4]; /* if you use longs instead of shorts, you get higher quality, and spend more memory */ #if 1 typedef short accum_t; #define MAXBUCKET (1<<14) #define SUB_BATCH_SIZE 10000 #else typedef long accum_t; #define MAXBUCKET (1<<30) #define SUB_BATCH_SIZE 10000 #endif typedef accum_t abucket[4]; /* allow this many iterations for settling into attractor */ #define FUSE 15 /* clamp spatial filter to zero at this std dev (2.5 ~= 0.0125) */ #define FILTER_CUTOFF 2.5 /* should be MAXBUCKET / (OVERSAMPLE^2) */ #define PREFILTER_WHITE (MAXBUCKET>>4) #define bump_no_overflow(dest, delta, type) { \ type tt_ = dest + delta; \ if (tt_ > dest) dest = tt_; \ } /* sum of entries of vector to 1 */ static void normalize_vector(v, n) double *v; int n; { double t = 0.0; int i; for (i = 0; i < n; i++) t += v[i]; t = 1.0 / t; for (i = 0; i < n; i++) v[i] *= t; } void render_rectangle(spec, out, out_width, field, nchan, progress) frame_spec *spec; unsigned char *out; int out_width; int field; int nchan; int progress(double); { int i, j, k, nsamples, nbuckets, batch_size, batch_num, sub_batch; bucket *buckets; abucket *accumulate; point *points; double *filter, *temporal_filter, *temporal_deltas; double bounds[4], size[2], ppux, ppuy; int image_width, image_height; /* size of the image to produce */ int width, height; /* size of histogram */ int filter_width; int oversample = spec->cps[0].spatial_oversample; int nbatches = spec->cps[0].nbatches; bucket cmap[CMAP_SIZE]; int gutter_width; int sbc; image_width = spec->cps[0].width; if (field) { image_height = spec->cps[0].height / 2; if (field == field_odd) out += nchan * out_width; out_width *= 2; } else image_height = spec->cps[0].height; if (1) { filter_width = (2.0 * FILTER_CUTOFF * oversample * spec->cps[0].spatial_filter_radius); /* make sure it has same parity as oversample */ if ((filter_width ^ oversample) & 1) filter_width++; filter = (double *) malloc(sizeof(double) * filter_width * filter_width); /* fill in the coefs */ for (i = 0; i < filter_width; i++) for (j = 0; j < filter_width; j++) { double ii = ((2.0 * i + 1.0) / filter_width - 1.0) * FILTER_CUTOFF; double jj = ((2.0 * j + 1.0) / filter_width - 1.0) * FILTER_CUTOFF; if (field) jj *= 2.0; filter[i + j * filter_width] = exp(-2.0 * (ii * ii + jj * jj)); } normalize_vector(filter, filter_width * filter_width); } temporal_filter = (double *) malloc(sizeof(double) * nbatches); temporal_deltas = (double *) malloc(sizeof(double) * nbatches); if (nbatches > 1) { double t; /* fill in the coefs */ for (i = 0; i < nbatches; i++) { t = temporal_deltas[i] = (2.0 * ((double) i / (nbatches - 1)) - 1.0) * spec->temporal_filter_radius; temporal_filter[i] = exp(-2.0 * t * t); } normalize_vector(temporal_filter, nbatches); } else { temporal_filter[0] = 1.0; temporal_deltas[0] = 0.0; } #if 0 for (j = 0; j < nbatches; j++) fprintf(stderr, "%4f %4f\n", temporal_deltas[j], temporal_filter[j]); fprintf(stderr, "\n"); #endif /* the number of additional rows of buckets we put at the edge so that the filter doesn't go off the edge */ gutter_width = (filter_width - oversample) / 2; height = oversample * image_height + 2 * gutter_width; width = oversample * image_width + 2 * gutter_width; nbuckets = width * height; if (1) { static char *last_block = NULL; static int last_block_size = 0; int memory_rqd = (sizeof(bucket) * nbuckets + sizeof(abucket) * nbuckets + sizeof(point) * SUB_BATCH_SIZE); if (memory_rqd > last_block_size) { if (last_block != NULL) free(last_block); last_block = (char *) malloc(memory_rqd); if (NULL == last_block) { fprintf(stderr, "render_rectangle: cannot malloc %d bytes.\n", memory_rqd); exit(1); } /* else fprintf(stderr, "render_rectangle: mallocked %dMb.\n", Mb); */ last_block_size = memory_rqd; } buckets = (bucket *) last_block; accumulate = (abucket *) (last_block + sizeof(bucket) * nbuckets); points = (point *) (last_block + (sizeof(bucket) + sizeof(abucket)) * nbuckets); } memset((char *) accumulate, 0, sizeof(abucket) * nbuckets); for (batch_num = 0; batch_num < nbatches; batch_num++) { double batch_time; double sample_density; control_point cp; memset((char *) buckets, 0, sizeof(bucket) * nbuckets); batch_time = spec->time + temporal_deltas[batch_num]; /* interpolate and get a control point */ interpolate(spec->cps, spec->ncps, batch_time, &cp); /* compute the colormap entries. the input colormap is 256 long with entries from 0 to 1.0 */ for (j = 0; j < CMAP_SIZE; j++) { for (k = 0; k < 3; k++) { #if 1 cmap[j][k] = (int) (cp.cmap[(j * 256) / CMAP_SIZE][k] * cp.white_level); #else /* monochrome if you don't have any cmaps */ cmap[j][k] = cp.white_level; #endif } cmap[j][3] = cp.white_level; } /* compute camera */ if (1) { double t0, t1, shift = 0.0, corner0, corner1; double scale; scale = pow(2.0, cp.zoom); sample_density = cp.sample_density * scale * scale; ppux = cp.pixels_per_unit * scale; ppuy = field ? (ppux / 2.0) : ppux; switch (field) { case field_both: shift = 0.0; break; case field_even: shift = -0.5; break; case field_odd: shift = 0.5; break; } shift = shift / ppux; t0 = (double) gutter_width / (oversample * ppux); t1 = (double) gutter_width / (oversample * ppuy); corner0 = cp.center[0] - image_width / ppux / 2.0; corner1 = cp.center[1] - image_height / ppuy / 2.0; bounds[0] = corner0 - t0; bounds[1] = corner1 - t1 + shift; bounds[2] = corner0 + image_width / ppux + t0; bounds[3] = corner1 + image_height / ppuy + t1 + shift; size[0] = 1.0 / (bounds[2] - bounds[0]); size[1] = 1.0 / (bounds[3] - bounds[1]); } nsamples = (int) (sample_density * nbuckets / (oversample * oversample)); batch_size = nsamples / cp.nbatches; sbc = 0; for (sub_batch = 0; sub_batch < batch_size; sub_batch += SUB_BATCH_SIZE) { if (progress && (sbc++ % 32) == 0) (*progress)(0.5*sub_batch/(double)batch_size); /* generate a sub_batch_size worth of samples */ points[0][0] = random_uniform11(); points[0][1] = random_uniform11(); points[0][2] = random_uniform01(); iterate(&cp, SUB_BATCH_SIZE, FUSE, points); /* merge them into buckets, looking up colors */ for (j = 0; j < SUB_BATCH_SIZE; j++) { int k, color_index; double *p = points[j]; bucket *b; if (p[0] < bounds[0] || p[1] < bounds[1] || p[0] > bounds[2] || p[1] > bounds[3]) continue; color_index = (int) (p[2] * CMAP_SIZE); if (color_index < 0) color_index = 0; else if (color_index > (CMAP_SIZE-1)) color_index = CMAP_SIZE-1; b = buckets + (int) (width * (p[0] - bounds[0]) * size[0]) + width * (int) (height * (p[1] - bounds[1]) * size[1]); for (k = 0; k < 4; k++) bump_no_overflow(b[0][k], cmap[color_index][k], short); } } if (1) { double k1 =(cp.contrast * cp.brightness * PREFILTER_WHITE * 268.0 * temporal_filter[batch_num]) / 256; double area = image_width * image_height / (ppux * ppuy); double k2 = (oversample * oversample * nbatches) / (cp.contrast * area * cp.white_level * sample_density); /* log intensity in hsv space */ for (j = 0; j < height; j++) for (i = 0; i < width; i++) { abucket *a = accumulate + i + j * width; bucket *b = buckets + i + j * width; double c[4], ls; c[0] = (double) b[0][0]; c[1] = (double) b[0][1]; c[2] = (double) b[0][2]; c[3] = (double) b[0][3]; if (0.0 == c[3]) continue; ls = (k1 * log(1.0 + c[3] * k2))/c[3]; c[0] *= ls; c[1] *= ls; c[2] *= ls; c[3] *= ls; bump_no_overflow(a[0][0], c[0] + 0.5, accum_t); bump_no_overflow(a[0][1], c[1] + 0.5, accum_t); bump_no_overflow(a[0][2], c[2] + 0.5, accum_t); bump_no_overflow(a[0][3], c[3] + 0.5, accum_t); } } } /* * filter the accumulation buffer down into the image */ if (1) { int x, y; double t[4]; double g = 1.0 / spec->cps[0].gamma; y = 0; for (j = 0; j < image_height; j++) { if (progress && (j % 32) == 0) (*progress)(0.5+0.5*j/(double)image_height); x = 0; for (i = 0; i < image_width; i++) { int ii, jj, a; unsigned char *p; t[0] = t[1] = t[2] = t[3] = 0.0; for (ii = 0; ii < filter_width; ii++) for (jj = 0; jj < filter_width; jj++) { double k = filter[ii + jj * filter_width]; abucket *a = accumulate + x + ii + (y + jj) * width; t[0] += k * a[0][0]; t[1] += k * a[0][1]; t[2] += k * a[0][2]; t[3] += k * a[0][3]; } p = out + nchan * (i + j * out_width); a = 256.0 * pow((double) t[0] / PREFILTER_WHITE, g) + 0.5; if (a < 0) a = 0; else if (a > 255) a = 255; p[0] = a; a = 256.0 * pow((double) t[1] / PREFILTER_WHITE, g) + 0.5; if (a < 0) a = 0; else if (a > 255) a = 255; p[1] = a; a = 256.0 * pow((double) t[2] / PREFILTER_WHITE, g) + 0.5; if (a < 0) a = 0; else if (a > 255) a = 255; p[2] = a; if (nchan > 3) { a = 256.0 * pow((double) t[3] / PREFILTER_WHITE, g) + 0.5; if (a < 0) a = 0; else if (a > 255) a = 255; p[3] = a; } x += oversample; } y += oversample; } } free(filter); }