Modified WolframAutomata to loop with new settings upon completing a simulation.

[screensavers] / hacks / WolframAutomata / WolframAutomata.c

/* (c) 2021 Aaron Taylor <ataylor at subgeniuskitty dot com>   */
/* See LICENSE.txt file for copyright and license details.     */


/* TODO: Write description explaining that this simulates all 1D NN CAs, and explain briefly what all those terms imply. */
/* TODO: Explain things like the topology of the space. */
/* TODO: Explain how the numbering for a CA expands to the actual rules. */
/* TODO: Briefly explain the four different classes of behavior and their implications. */
/* TODO: Include a link to Wikipedia. */
/* TODO: I suppose a lot of this stuff goes in the README instead. */
/* TODO: Explain the data structures in detail. */
/* TODO: Explain all the options, like the various starting conditions. */
/* TODO: Explain all the dependencies like libXpm. */
/* TODO: Explain that the program is inherently double-buffered but if you don't have VSync turned on, all those alternating lines are going to look terrible when they scroll upward. */

/* TODO: Add a #define for the hack version. */
/* TODO: Check manpage for all functions I use and ensure my includes are correct. I don't want to depend on picking up includes via screenhack.h. */
/* TODO: Verify everything in this file is C89. Get rid of things like '//' comments, pack all my declarations upfront, no stdint, etc. */

#include <X11/Intrinsic.h>
#include "screenhack.h"

/*
 * We do a few manual manipulations of X resources in this hack, like picking
 * random colors. In order to ensure our manual manipulations always use the
 * same X resource specification as Xscreensaver, we pass HACKNAME to
 * Xscreensaver via the XSCREENSAVER_MODULE() line at the bottom of this file,
 * and then always use HACKNAME or MAKE_STRING(HACKNAME) as the base of the
 * resource specification when making manual manipulations.
 */
#define HACKNAME WolframAutomata
#define MAKE_STRING_X(s) #s
#define MAKE_STRING(s) MAKE_STRING_X(s)

// Command line options
//        directory to output XBM files of each run (and call an external command to convert to PNGs?)
//              -save-dir STRING
//              (could use libXpm to save an XPM and then convert to PNG with ImageMagick) (this is a single function call to go from pixmap -> file)
//              (since it depends on an external library, make this whole feature optional at build-time?)
//        number of generations to simulate
//              -random-generations
//              -num-generations N
//        delay time (speed of simulation)
//              -random-delay
//              -delay-usec N
//        foreground and background color
//              -random-colors (highest precedence)
//              -foreground "COLORNAME"
//              -background "COLORNAME"
//              (default is black and white)
//              (mention sample color combinations in manpage, and link to: https://en.wikipedia.org/wiki/X11_color_names)
//              (note to the user that most color names they can naturally think of (e.g. red, purple, gray, pink, etc) are valid X11 color names for these CLI options.)
//        display info overlay with CA number and start conditions?
//              -overlay
//        which ruleset number to use? Or random? Or random from small set of hand-selected interesting examples?
//              In order of precedence:
//                  -rule-random (select a random rule on each run)
//                  -rule N (always simulate Rule N on each run)
//                  (if neither of the above two are specified, then a random CURATED rule is selected on each run)
//        which starting population to use, random or one bit? (for random: allow specifying a density)
//              In order of precedence:
//                  -population-single
//                  -population-random DENSITY
//                  (the two options above only apply to the simulation under the -rule-random or -rule N options. in curated mode, starting population is defined in the curation array)
//                  TODO: In the future, add the option for user to pass list of cell IDs to turn ON.
//        size of pixel square (e.g. 1x1, 2x2, 3x3, etc)
//              -random-pixel-size
//              -pixel-size N

/* -------------------------------------------------------------------------- */
/* Data Structures                                                            */
/* -------------------------------------------------------------------------- */

struct state {
    /* Various X resources */
    Display * dpy;
    Window    win;
    GC        gc;

    // TODO: Explain that this holds the whole evolution of the CA and the actual displayed visualization is simply a snapshot into this pixmap.
    Pixmap    evolution_history;

    // TODO: Explain all of these.
    unsigned long fg, bg;
    int xlim, ylim, ypos; // explain roughly how and where we use these. Note: I'm not thrilled xlim/ylim since they are actually the width of the display, not the limit of the index (off by one). Change those names.
    Bool display_info;

    Bool * current_generation;

    // TODO: Describe these.
    uint8_t rule_number;  // Note: This is not a CLI option. You're thinking of rule_requested.
    uint8_t rule_requested; // Note: Repurposing Rule 0 as a null value.
    Bool rule_random;

    // TODO: Describe these.
    int population_density;
    Bool population_single;

    /* Misc Commandline Options */
    int pixel_size; /* Size of CA cell in pixels (e.g. pixel_size=3 means 3x3 pixels per cell). */
    int delay_microsec; /* Requested delay to screenhack framework before next call to WolframAutomata_draw(). */
    int num_generations; /* Number of generations of the CA to simulate before restarting. */

    /* Expository Variables - Not strictly necessary, but makes some code easier to read. */
    size_t number_of_cells;
};

// TODO: Decorations
enum seed_population {
    random_cell,
    middle_cell,
    edge_cell
};

// TODO: Decorations
struct curated_ruleset {
    uint8_t              rule;
    enum seed_population seed;
};

// TODO: Decorations
static const struct curated_ruleset curated_ruleset_list[] = {
    {18, middle_cell},
    {30, middle_cell},
    {45, middle_cell},
    {54, middle_cell},
    {57, middle_cell},
    {73, middle_cell},
    {105, middle_cell},
    {109, middle_cell},
    {129, middle_cell},
    {133, middle_cell},
    {135, middle_cell},
    {150, middle_cell},
    {30, edge_cell},
    {45, edge_cell},
    {57, edge_cell},
    {60, edge_cell},
    {75, edge_cell},
    {107, edge_cell},
    {110, edge_cell},
    {133, edge_cell},
    {137, edge_cell},
    {169, edge_cell},
    {225, edge_cell},
    {22, random_cell},
    {30, random_cell},
    {54, random_cell},
    {62, random_cell},
    {90, random_cell},
    {105, random_cell},
    {108, random_cell},
    {110, random_cell},
    {126, random_cell},
    {146, random_cell},
    {150, random_cell},
    {182, random_cell},
    {184, random_cell},
    {225, random_cell},
    {240, random_cell}
};

// TODO: Decorations
struct color_pair {
    char * fg;
    char * bg;
};

// TODO: Decorations
static const struct color_pair color_list[] = {
    {"red", "black"},
    {"olive", "black"},
    {"teal", "black"},
    {"slateblue", "black"},
    {"violet", "black"},
    {"purple", "black"},
    {"white", "black"},
    {"white", "darkgreen"},
    {"white", "darkmagenta"},
    {"white", "darkred"},
    {"white", "darkblue"},
    {"darkslategray", "darkslategray1"},
    {"lightsteelblue", "darkslategray"},
    {"royalblue4", "royalblue"},
    {"antiquewhite2", "antiquewhite4"},
    {"darkolivegreen1", "darkolivegreen"},
    {"darkseagreen1", "darkseagreen4"},
    {"pink", "darkred"},
    {"lightblue", "darkgreen"},
    {"red", "blue"},
    {"red", "darkgreen"},
    {"aqua", "teal"},
    {"darkblue", "teal"},
    {"khaki", "seagreen"},
    {"khaki", "darkolivegreen"},
    {"lightslategray", "darkslategray"},
    {"tomato", "darkslategray"},
    {"tomato", "darkcyan"}
};

/* -------------------------------------------------------------------------- */
/* Helper Functions                                                           */
/* -------------------------------------------------------------------------- */

// TODO: decorations? inline?
void
generate_random_seed(struct state * state)
{
    int i;
    for (i = 0; i < state->number_of_cells; i++) {
        state->current_generation[i] = ((random() % 100) < state->population_density) ? True : False;
    }
}

// TODO: function decorations?
// TODO: Explain why this santizes the index for accessing current_generation (i.e. it creates a circular topology).
size_t
sindex(struct state * state, int index)
{
    while (index < 0) {
        index += state->number_of_cells;
    }
    while (index >= state->number_of_cells) {
        index -= state->number_of_cells;
    }
    return (size_t) index;
}

// TODO: function decorations?
// TODO: At least give a one-sentence explanation of the algorithm since this function is the core of the simulation.
Bool
calculate_cell(struct state * state, int cell_id)
{
    uint8_t cell_pattern = 0;
    int i;
    for (i = -1; i < 2; i++) {
        cell_pattern = cell_pattern << 1;
        if (state->current_generation[sindex(state, cell_id+i)] == True) {
            cell_pattern |= 1;
        }
    }
    if ((state->rule_number >> cell_pattern) & 1) {
        return True;
    } else {
        return False;
    }
}

// TODO: function decorations?
void
render_current_generation(struct state * state)
{
    size_t xpos;
    for (xpos = 0; xpos < state->number_of_cells; xpos++) {
        if (state->current_generation[xpos] == True) {
            XFillRectangle(state->dpy, state->evolution_history, state->gc, xpos*state->pixel_size, state->ypos, state->pixel_size, state->pixel_size);
        } else {
            XSetForeground(state->dpy, state->gc, state->bg);
            XFillRectangle(state->dpy, state->evolution_history, state->gc, xpos*state->pixel_size, state->ypos, state->pixel_size, state->pixel_size);
            XSetForeground(state->dpy, state->gc, state->fg);
        }
    }
}

/* -------------------------------------------------------------------------- */
/* Screenhack API Functions                                                   */
/* -------------------------------------------------------------------------- */

static Bool
WolframAutomata_event(Display * dpy, Window win, void * closure, XEvent * event)
{
    return False;
}

static void
WolframAutomata_free(Display * dpy, Window win, void * closure)
{
    struct state * state = closure;
    XFreeGC(state->dpy, state->gc);
    XFreePixmap(state->dpy, state->evolution_history);
    free(state->current_generation);
    free(state);
}

static void *
WolframAutomata_init(Display * dpy, Window win)
{
    struct state * state = calloc(1, sizeof(*state));
    if (!state) {
        fprintf(stderr, "ERROR: Failed to calloc() for state struct in WolframAutomata_init().\n");
        exit(EXIT_FAILURE);
    }

    XGCValues gcv;
    XWindowAttributes xgwa;
    const struct curated_ruleset * curated_ruleset = NULL;

    state->dpy = dpy;
    state->win = win;

    XGetWindowAttributes(state->dpy, state->win, &xgwa);
    state->xlim = xgwa.width;
    state->ylim = xgwa.height;
    state->ypos = 0; // TODO: Explain why.

    if (get_boolean_resource(state->dpy, "random-colors", "Boolean")) {
        XrmDatabase db = XtDatabase(state->dpy);
        size_t rand_i = random() % sizeof(color_list)/sizeof(color_list[0]);
        XrmPutStringResource(&db, MAKE_STRING(HACKNAME) ".background", color_list[rand_i].bg);
        XrmPutStringResource(&db, MAKE_STRING(HACKNAME) ".foreground", color_list[rand_i].fg);
    }

    state->fg = gcv.foreground = get_pixel_resource(state->dpy, xgwa.colormap, "foreground", "Foreground");
    state->bg = gcv.background = get_pixel_resource(state->dpy, xgwa.colormap, "background", "Background");
    state->gc = XCreateGC(state->dpy, state->win, GCForeground, &gcv);

    /* Set the size of each simulated cell as NxN pixels for pixel_size=N.    */
    if (get_boolean_resource(state->dpy, "random-pixel-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->pixel_size = 1 << (random() % 6);
    } else {
        state->pixel_size = get_integer_resource(state->dpy, "pixel-size", "Integer");
    }
    if (state->pixel_size < 1) state->pixel_size = 1;
    if (state->pixel_size > state->xlim) state->pixel_size = state->xlim;

    state->number_of_cells = state->xlim / state->pixel_size;
    // TODO: Do we want to enforce that number_of_cells > 0?

    /* 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->pixel_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->pixel_size=9, then it takes one right shift to  */
        /* reach state->pixel_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 pixel_size_temp = state->pixel_size;
        while (pixel_size_temp > 4) {
            pixel_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-usec", "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-num-generations", "Boolean")) {
        /* By empirical observation, keep the product                         */
        /*      state->num_generations * state->pixel_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->pixel_size);
        /* Ensure selected value is large enough to at least fill the screen. */
        /* Cast to avoid overflow.                                            */
        if ((long)state->num_generations * (long)state->pixel_size < state->ylim) {
            state->num_generations = (state->ylim / state->pixel_size) + 1;
        }
    } else {
        state->num_generations = get_integer_resource(state->dpy, "num-generations", "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 pixel_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->pixel_size > 10000) {
        state->num_generations = 10000 / state->pixel_size;
    }

    /* Time to figure out which rule to use for this simulation.              */
    /* We ignore any weirdness resulting from the following cast 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->rule_requested = (uint8_t) get_integer_resource(state->dpy, "rule-requested", "Integer");
    state->rule_random = get_boolean_resource(state->dpy, "rule-random", "Boolean");
    /* Through the following set of branches, we enforce CLI flag precedence. */
    if (state->rule_random) {
        /* 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->rule_requested != 0) {
        /* Rule 0 is terribly uninteresting, so we are reusing it as a 'null' */
        /* value and hoping nobody notices. Finding a non-zero value means    */
        /* the user requested a specific rule. Use it.                        */
        state->rule_number = state->rule_requested;
    } 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->population_single = get_boolean_resource(state->dpy, "population-single", "Boolean");
    state->population_density = get_integer_resource(state->dpy, "population-density", "Integer");
    if (state->population_density < 0 || state->population_density > 100) state->population_density = 50;
    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: 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 (state->population_single) {
            state->current_generation[0] = True;
        } else {
            generate_random_seed(state);
        }
    }

    // TODO: These should be command-line options, but I need to learn how the get_integer_resource() and similar functions work first.
    state->display_info = True;

    state->evolution_history = XCreatePixmap(state->dpy, state->win, state->xlim, state->num_generations*state->pixel_size, xgwa.depth);
    // Pixmap contents are undefined after creation. Explicitly set a black
    // background by drawing a black rectangle over the entire pixmap.
    XColor blackx, blacks;
    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->xlim, state->num_generations*state->pixel_size);
    XSetForeground(state->dpy, state->gc, state->fg);
    render_current_generation(state);
    state->ypos += state->pixel_size;

    return state;
}

static unsigned long
WolframAutomata_draw(Display * dpy, Window win, void * closure)
{
// TODO: Mark these basic sections of the function
//draw()
//    calculate (and store) new generation
//    draw new generation as line of pixels on pixmap
//    calculate current 'viewport' into pixmap
//    display on screen
//  check for termination condition

    struct state * state = closure;
    int xpos;
    int window_y_offset;

    Bool new_generation[state->xlim];
    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];
    }
    render_current_generation(state);

    // Was this the final generation of this particular simulation? If so, give
    // the user a moment to bask in the glory of our output and then start a
    // new simulation.
    if (state->ypos/state->pixel_size < state->num_generations-1) {
        state->ypos += state->pixel_size;
    } else {
        // TODO: Wait for a second or two, clear the screen and do a new iteration with suitably changed settings.
        // Note: Since we can't actually loop or sleep here, we need to add a flag to the state struct to indicate that we're in an 'admiration timewindow' (and indicate when it should end)
        WolframAutomata_free(dpy, win, state);
        closure = WolframAutomata_init(dpy, win);
    }

    // Calculate the vertical offset of the current 'window' into the history
    // of the CA. After the CA's evolution extends past what we can display, have
    // the window track the current generation and most recent history.
    if (state->ypos < state->ylim) {
        window_y_offset = 0;
    } else {
        window_y_offset = state->ypos - (state->ylim - 1);
    }

    // Render everything to the display.
    XCopyArea(state->dpy, state->evolution_history, state->win, state->gc, 0, window_y_offset, state->xlim, state->ylim, 0, 0);
    // TODO: Print info on screen if display_info is true. Will need fonts/etc. Do I want to create a separate pixmap for this during the init() function and then just copy the pixmap each time we draw the screen in draw()?

    return state->delay_microsec;
}

// TODO: Fix formatting
static const char * WolframAutomata_defaults[] = {
    ".background:    black",
    ".foreground:    white",
    "*random-colors: False",
    "*delay-usec:    25000",
    // TODO: Difference between dot and asterisk? Presumably the asterisk matches all resouces of attribute "pixelsize"? Apply answer to all new options.
    "*pixel-size:    2",
    "*num-generations:    5000",
    "*rule-requested:    0",
    "*rule-random:    False",
    "*population-density:    50",
    "*population-single:    False",
    "*random-delay:    False",
    "*random-pixel-size:    False",
    "*random-num-generations:    False",
    0
};

// TODO: Fix formatting
static XrmOptionDescRec WolframAutomata_options[] = {
    { "-background",        ".background",    XrmoptionSepArg, 0},
    { "-foreground",        ".foreground",    XrmoptionSepArg, 0},
    { "-random-colors",        ".random-colors",    XrmoptionNoArg, "True"},
    { "-delay-usec",        ".delay-usec",    XrmoptionSepArg, 0 },
    { "-pixel-size",    ".pixel-size",    XrmoptionSepArg, 0 },
    { "-num-generations",    ".num-generations",    XrmoptionSepArg, 0 },
    { "-rule",    ".rule-requested",    XrmoptionSepArg, 0 },
    { "-rule-random",    ".rule-random",    XrmoptionNoArg, "True" },
    { "-population-density",    ".population-density",    XrmoptionSepArg, 0 },
    { "-population-single",    ".population-single",    XrmoptionNoArg, "True" },
    { "-random-delay", ".random-delay", XrmoptionNoArg, "True" },
    { "-random-pixel-size", ".random-pixel-size", XrmoptionNoArg, "True" },
    { "-random-num-generations", ".random-num-generations", XrmoptionNoArg, "True" },

    { 0, 0, 0, 0 }
};

static void
WolframAutomata_reshape(Display * dpy, Window win, void * closure, unsigned int w, unsigned int h)
{
    WolframAutomata_free(dpy, win, closure);
    closure = WolframAutomata_init(dpy, win);
}

XSCREENSAVER_MODULE ("1D Nearest-Neighbor Cellular Automata", HACKNAME)