+static void *
+WolframAutomata_init(Display * dpy, Window win)
+{
+ struct state * state;
+ XGCValues gcv;
+ XWindowAttributes xgwa;
+ XColor fg, bg;
+ XColor blackx, blacks;
+ size_t color_index;
+ const struct curated_ruleset * curated_ruleset = NULL;
+
+ state = calloc(1, sizeof(*state));
+ if (!state) {
+ fprintf(stderr, "ERROR: Failed to calloc() for state struct in WolframAutomata_init().\n");
+ exit(EXIT_FAILURE);
+ }
+
+ state->dpy = dpy;
+ state->win = win;
+
+ XGetWindowAttributes(state->dpy, state->win, &xgwa);
+ state->dpy_width = xgwa.width;
+ state->dpy_height = xgwa.height;
+ state->ypos = 0;
+
+ state->admiration_delay = get_integer_resource(state->dpy, "admiration-delay", "Integer");
+ state->admiration_in_progress = False;
+
+ /* Set foreground and background colors for active/inactive cells. Either */
+ /* the user provided an index into the pre-defined color_list[] or a */
+ /* random entry from that same array should be selected. */
+ color_index = get_integer_resource(state->dpy, "color-index", "Integer");
+ if (color_index == -1) {
+ color_index = random() % sizeof(color_list)/sizeof(color_list[0]);
+ } else if (color_index >= sizeof(color_list)/sizeof(color_list[0])) {
+ fprintf(stderr, "WARNING: Color index out of range.\n");
+ color_index = 0;
+ }
+ fg.red = color_list[color_index].fg_red;
+ fg.green = color_list[color_index].fg_green;
+ fg.blue = color_list[color_index].fg_blue;
+ bg.red = color_list[color_index].bg_red;
+ bg.green = color_list[color_index].bg_green;
+ bg.blue = color_list[color_index].bg_blue;
+ XAllocColor(state->dpy, xgwa.colormap, &fg);
+ XAllocColor(state->dpy, xgwa.colormap, &bg);
+ state->fg = gcv.foreground = fg.pixel;
+ state->bg = gcv.background = bg.pixel;
+
+ state->gc = XCreateGC(state->dpy, state->win, GCForeground, &gcv);
+
+ /* Set the size of each simulated cell to NxN pixels for cell_size=N. */
+ if (get_boolean_resource(state->dpy, "random-cell-size", "Boolean")) {
+ /* Although we are choosing the pixel size 'randomly', a truly random */
+ /* selection would bias toward large numbers since there are more of */
+ /* them. To avoid this, we select a random number for a bit shift, */
+ /* resulting in a pixel size of 1, 2, 4, 8, 16 or 32, equally likely. */
+ state->cell_size = 1 << (random() % 6);
+ } else {
+ state->cell_size = get_integer_resource(state->dpy, "cell-size", "Integer");
+ }
+ if (state->cell_size < 1) state->cell_size = 1;
+ if (state->cell_size > state->dpy_width) state->cell_size = state->dpy_width;
+
+ /* Larger cell sizes won't always evenly divide the number of pixels in */
+ /* our window. In order to avoid a black stripe down the edge, '+1' here */
+ /* to ensure we are slightly oversize rather than undersize. */
+ state->number_of_cells = (state->dpy_width / state->cell_size) + 1;
+
+ /* Set the delay (in microseconds) between simulation of each generation */
+ /* of the simulation, also known as the delay between calls to */
+ /* WolframAutomata_draw(), which simulates one generation per call. */
+ if (get_boolean_resource(state->dpy, "random-delay", "Boolean")) {
+ /* When randomly setting the delay, the problem is to avoid being too */
+ /* fast or too slow, as well as ensuring slower speeds are chosen */
+ /* with the same likelihood as faster speeds, as perceived by a */
+ /* human. By empirical observation, we note that for 1x1 up to 4x4 */
+ /* pixel cell sizes, values for state->delay_microsec between */
+ /* 2048 (2^11) and 16556 (2^14) produce pleasant scroll rates. To */
+ /* maintain this appearance, we bitshift state->cell_size down until */
+ /* it is a maximum of 4x4 pixels in size, record how many bitshifts */
+ /* took place, and then shift our valid window for */
+ /* state->delay_microsec up by an equal number of bitshifts. For */
+ /* example, if state->cell_size=9, then it takes one right shift to */
+ /* reach state->cell_size=4. Thus, the valid window for */
+ /* state->delay_microsec becomes 4096 (2^12) up to 32768 (2^15). */
+ size_t pixel_shift_range = 1;
+ size_t cell_size_temp = state->cell_size;
+ while (cell_size_temp > 4) {
+ cell_size_temp >>= 1;
+ pixel_shift_range++;
+ }
+ /* In the below line, '3' represents the total range, namely '14-11' */
+ /* from '2^14' and '2^11' as the endpoints. Similarly, the '11' in */
+ /* the below line represents the starting point of this range, from */
+ /* the exponent in '2^11'. */
+ state->delay_microsec = 1 << ((random() % 3) + 11 + pixel_shift_range);
+ } else {
+ state->delay_microsec = get_integer_resource(state->dpy, "delay", "Integer");
+ }
+ if (state->delay_microsec < 0) state->delay_microsec = 0;
+
+ /* Set the number of generations to simulate before wiping the simulation */
+ /* and re-running with new settings. */
+ if (get_boolean_resource(state->dpy, "random-length", "Boolean")) {
+ /* By empirical observation, keep the product */
+ /* state->num_generations * state->cell_size */
+ /* below 10,000 to avoid BadAlloc errors from the X server due to */
+ /* requesting an enormous pixmap. This value works on both a 12 core */
+ /* Xeon with 108 GiB of RAM and a Sun Ultra 2 with 2 GiB of RAM. */
+ state->num_generations = random() % (10000 / state->cell_size);
+ /* Ensure selected value is large enough to at least fill the screen. */
+ /* Cast to avoid overflow. */
+ if ((long)state->num_generations * (long)state->cell_size < state->dpy_height) {
+ state->num_generations = (state->dpy_height / state->cell_size) + 1;
+ }
+ } else {
+ state->num_generations = get_integer_resource(state->dpy, "length", "Integer");
+ }
+ /* The minimum number of generations is 2 since we must allocate enough */
+ /* space to hold the seed generation and at least one pass through */
+ /* WolframAutomata_draw(), which is where we check whether or not we've */
+ /* reached the end of the pixmap. */
+ if (state->num_generations < 0) state->num_generations = 2;
+ /* The maximum number of generations is cell_size dependent. This is a */
+ /* soft limit and may be increased if you have plenty of RAM (and a */
+ /* cooperative X server). The value 10,000 was determined empirically. */
+ if ((long)state->num_generations * (long)state->cell_size > 10000) {
+ state->num_generations = 10000 / state->cell_size;
+ }
+
+ /* Time to figure out which rule to use for this simulation. */
+ /* We ignore any weirdness resulting from the following casts since every */
+ /* bit pattern is also a valid rule; if the user provides weird input, */
+ /* then we'll return weird (but well-defined!) output. */
+ state->requested_rule = get_integer_resource(state->dpy, "rule", "Integer");
+ state->random_rule = get_boolean_resource(state->dpy, "random-rule", "Boolean");
+ /* Through the following set of branches, we enforce CLI flag precedence. */
+ if (state->random_rule) {
+ /* If this flag is set, the user wants truly random rules rather than */
+ /* random rules from a curated list. */
+ state->rule_number = (uint8_t) random();
+ } else if (state->requested_rule != -1) {
+ /* The user requested a specific rule. Use it. */
+ state->rule_number = (uint8_t) state->requested_rule;
+ } else {
+ /* No command-line options were specified, so select rules randomly */
+ /* from a curated list. */
+ size_t number_of_array_elements = sizeof(curated_ruleset_list)/sizeof(curated_ruleset_list[0]);
+ curated_ruleset = &curated_ruleset_list[random() % number_of_array_elements];
+ state->rule_number = curated_ruleset->rule;
+ }
+
+ /* Time to construct the seed generation for this simulation. */
+ state->current_generation = calloc(1, sizeof(*state->current_generation)*state->number_of_cells);
+ if (!state->current_generation) {
+ fprintf(stderr, "ERROR: Failed to calloc() for cell generation in WolframAutomata_init().\n");
+ exit(EXIT_FAILURE);
+ }
+ if (curated_ruleset) {
+ /* If we're using a curated ruleset, ignore any CLI flags related to */
+ /* setting the seed generation, instead drawing that information from */
+ /* the curated ruleset. */
+ switch (curated_ruleset->seed) {
+ case random_cell: randomize_seed_density(state); generate_random_seed(state); break;
+ case middle_cell: state->current_generation[state->number_of_cells/2] = True; break;
+ case edge_cell : state->current_generation[0] = True; break;
+ }
+ } else {
+ /* If we're not using a curated ruleset, process any relevant flags */
+ /* from the user, falling back to a random seed generation if nothing */
+ /* else is specified. */
+ if (get_boolean_resource(state->dpy, "seed-left", "Boolean")) {
+ state->current_generation[0] = True;
+ } else if (get_boolean_resource(state->dpy, "seed-center", "Boolean")) {
+ state->current_generation[state->number_of_cells/2] = True;
+ } else if (get_boolean_resource(state->dpy, "seed-right", "Boolean")) {
+ state->current_generation[state->number_of_cells-1] = True;
+ } else if (get_integer_resource(state->dpy, "seed-density", "Integer") != -1) {
+ state->seed_density = get_integer_resource(state->dpy, "seed-density", "Integer");
+ if (state->seed_density < 0 || state->seed_density > 100) state->seed_density = 50;
+ generate_random_seed(state);
+ } else {
+ randomize_seed_density(state);
+ generate_random_seed(state);
+ }
+ }
+
+ state->evolution_history = XCreatePixmap(state->dpy, state->win, state->dpy_width, state->num_generations*state->cell_size, xgwa.depth);
+ /* Pixmap contents are undefined after creation. Explicitly set a black */
+ /* background by drawing a black rectangle over the entire pixmap. */
+ XAllocNamedColor(state->dpy, DefaultColormapOfScreen(DefaultScreenOfDisplay(state->dpy)), "black", &blacks, &blackx);
+ XSetForeground(state->dpy, state->gc, blacks.pixel);
+ XFillRectangle(state->dpy, state->evolution_history, state->gc, 0, 0, state->dpy_width, state->num_generations*state->cell_size);
+ XSetForeground(state->dpy, state->gc, state->fg);
+ render_current_generation(state);
+ state->ypos += state->cell_size;
+
+ return state;
+}
+
+static unsigned long
+WolframAutomata_draw(Display * dpy, Window win, void * closure)
+{
+ struct state * state = closure;
+ int xpos;
+ int window_y_offset;
+
+ /* Calculate and record new generation. */
+ Bool * new_generation = malloc(state->dpy_width * sizeof(Bool));
+ if (new_generation == NULL) {
+ fprintf(stderr, "ERROR: Failed to malloc() when calculating new generation.\n");
+ exit(EXIT_FAILURE);
+ }
+ for (xpos = 0; xpos < state->number_of_cells; xpos++) {
+ new_generation[xpos] = calculate_cell(state, xpos);
+ }
+ for (xpos = 0; xpos < state->number_of_cells; xpos++) {
+ state->current_generation[xpos] = new_generation[xpos];
+ }
+ free(new_generation);
+ render_current_generation(state);
+
+ /* Check for end of simulation. */
+ if (state->ypos/state->cell_size < state->num_generations-1) {
+ /* Life continues. */
+ state->ypos += state->cell_size;
+ } else {
+ /* We have reached the end of this simulation. Give the user a moment */
+ /* to bask in the glory of our output, then reset. */
+ if (state->admiration_in_progress) {
+ WolframAutomata_free(dpy, win, state);
+ closure = WolframAutomata_init(dpy, win);
+ } else {
+ state->admiration_in_progress = True;
+ return 1000000 * state->admiration_delay;
+ }
+ }
+
+ /* Calculate vertical offset of current 'window' into the CA's history. */
+ /* After the CA evolution exceeds our display extents, make window track */
+ /* current generation, scrolling display to follow newest generation. */
+ if (state->ypos < state->dpy_height) {
+ window_y_offset = 0;
+ } else {
+ window_y_offset = state->ypos - (state->dpy_height - 1);
+ }
+
+ /* Render a window into the CA history. */
+ XCopyArea(state->dpy, state->evolution_history, state->win, state->gc, 0, window_y_offset, state->dpy_width, state->dpy_height, 0, 0);
+
+ return state->delay_microsec;
+}
+