Issues concerning gun & guntrue submissions on Catagolue - solution discussion thread

[PK22]

To fix over-densification, I have created a modification of idgun.py and contrsynth.py, which should accept guns with the same bounding box but lower population.
For idgun.py, I added a new function, get_raw_population, which determines the population of a gun ignoring state-2 cells:

Code: Select all

def clip(pattern, rect):
    return pattern[rect[0]:rect[0]+rect[2], rect[1]:rect[1]+rect[3]]

def is_gun(pattern, true_period):
    """Test if the given pattern is a gun.

    A pattern is a gun only if the pattern and the resulting gliders after `true_period`
    are separately evolvable. This filters out non-guns having heisenburp-like reactions.
    """
    gliders = pattern[true_period] - pattern
    for phase in range(true_period):
        if (pattern[true_period + phase] == pattern[phase] + gliders[phase]
                and (pattern[phase] & gliders[phase]).population == 0):
            continue
        return False
    return True

def get_raw_population(pattern):
    #New function which might help fix the pointless densification.
    #It finds the raw population of a gun without any state-2 LifeHistory cells.
    #In contrsynth.py, this will be called to compare guns with the same bounding box.

    #Remove state-2 cells:
    pattern2 = pattern.replace('B', 'b')

    #Return new population:
    return pattern2.population
    
    
def get_bounding_box_naive(gun, true_period, period, naive_envelope, unclipped_envelope):
    """Get the bounding box with a naive algorithm or throw an error
    if the naive algorithm cannot be applied.

    We iterate the gun, remove the gliders whenever it crosses
    our minimal bounding box, and hope that the resulting phases
    match the actual phases of the gun.
    The phases would not match when there is a heisenburp-like reaction
    at the edge of the envelope.
    """
    envelope = naive_envelope
    gun_phases = [gun[i] for i in range(true_period)]
    output_gliders = gun[true_period] - gun
    to_be_glider = output_gliders[-period] - output_gliders

    for i in range(true_period):
        if (gun - gun_phases[i]).population != 0:
            raise Error("Naive bounding box algorithm failed.")
        # Remove gliders until there isn't or the gun fits inside envelope
        while (gun - envelope).population != 0:
            if (to_be_glider - gun).population != 0:
                envelope = clip(unclipped_envelope, (envelope + gun).getrect())
                break
            gun -= to_be_glider
            to_be_glider = to_be_glider[-period]
        gun = gun[1]
        to_be_glider = to_be_glider[1]
    return envelope.getrect()

def get_bounding_box(gun, true_period, period, envelope_lower_bound):
    """Get the bounding box with a slower but always succeeding algorithm. """
    output_gliders = gun[true_period] - gun
    to_be_glider = output_gliders[-period] - output_gliders
    envelope = gun
    for i in range(true_period):
        # For each phase, delete gliders while the resulting pattern is a gun
        # until the pattern fits in the known lower bound of the bounding box
        # or there isn't a glider to delete.
        while (gun - envelope_lower_bound).population != 0:
            if (to_be_glider - gun).population != 0:
                break
            if not is_gun(gun - to_be_glider, true_period):
                break
            gun -= to_be_glider
            to_be_glider = to_be_glider[-period]
        envelope += gun
        gun = gun[1]
        to_be_glider = to_be_glider[1]
    return envelope.getrect()

def identify_gun(rle, lt4):

    a = lt4.pattern(rle)

    if a.empty():
        return []

    a = a[524288]
    x = lt4.pattern('', 'LifeHistory')
    x += a
    x = x[524288]
    p = x.population

    if (p < 1000000):
        return None

    if (p > 1500000):
        return None

    envelope = x.layers()[1]
    livecells = x[8].layers()[0]
    y = livecells - envelope
    envelope = x[256].layers()[1]

    if (y.population != 5):
        return None

    z = lt4.pattern("", "b3s23")
    z += y

    if (z.apgcode != 'xq4_153'):
        return None

    geater = lt4.pattern("bo$2bo$3o4$5b2o$5bo$6b3o$8bo!", "b3s23")

    eater = z.replace(geater[:3, :3], geater[100], orientations='rotate4reflect', n_phases=2)

    if (eater.population != 7):
        return None

    x += eater

    x = x[128]

    true_period = x.oscar(eventual_oscillator=False, maxexp=20)['period']

    print('True period: %d' % true_period)

    if (true_period > 100000):
        print('Period too large')
        return []

    gun = lt4.pattern("", "b3s23")
    gun += livecells

    if ((gun - gun[true_period]).population > 0):
        return None

    salvo = gun[true_period] - gun

    if salvo.population != 5:
        y = z.destream(salvo)[1:-1]
        y.append(y[-1])
        print(y)

        if (len(set(y)) != 1) or (sum(y) != true_period):
            print('Warning: intermittent glider gun')
            return []

        period = y[-1]
    else:
        period = true_period

    print('Stream period: %d' % period)

    if (period > 10000):
        print('Period too large')
        return []

    w = lt4.pattern("", "LifeHistory")
    w += z[-2097152]
    w = w[4194304]


    band = w.layers()[1]

    pbb = envelope - band
    r1 = z.getrect()
    r2 = z[1024].getrect()

    pbb += pbb(r1[0] - r2[0], r1[1] - r2[1])

    # The bounding box related to `r` is a lower bound but is not exact.
    # It does not take into account the sparks at the output glider lane.
    r = pbb.getrect()
    if (r is None) or (len(r) != 4):
        return None

    envelope_lower_bound = clip(envelope, r)
    r = envelope_lower_bound.getrect()

    # Find and use the phase where the gun is totally inside the
    # lower bound of the bounding box.
    # There is a possibility that this test could fail,
    # but this doesn't seem to occur in practice.
    for _ in range(true_period):
        gun_clipped = gun & envelope_lower_bound
        if is_gun(gun_clipped, true_period):
            gun = gun_clipped
            break
        gun = gun[1]
    else:
        print('Failure 1!')
        return None

    # Performance optimization:
    # we try the naive but fast algorithm first
    # and then try the slow but accurate one
    try:
        bounding_box = get_bounding_box_naive(
                gun,
                true_period,
                period,
                naive_envelope=envelope_lower_bound,
                unclipped_envelope=envelope)
    except:
        bounding_box = get_bounding_box(
                gun,
                true_period,
                period,
                envelope_lower_bound=envelope_lower_bound)
    true_envelope = clip(envelope, bounding_box)

    gun_canonical_phase = gun
    for _ in range(true_period):
        if (gun[1] - true_envelope).population > 0:
            gun_canonical_phase = gun
            break
        gun = gun[1]
    else:
        print('Failure 2!')
        return None

    r = bounding_box
    multiple = true_period
    thing = lt4.pattern("", "LifeHistory")
    thing += gun_canonical_phase
    thing = thing[multiple]
    thing = clip(thing, bounding_box)
    thing = thing(-r[0], -r[1])

    res = '\n\n#CSYNTH gun_%d costs %d cells.\n#C period %d fullperiod %d bbox %d by %d\n' % (period, r[2] * r[3], period, multiple, r[2], r[3])
    print(res)
    res += thing.rle_string()

    to_update = [(('gun_%d' % period), r[2] * r[3], res)]

    if (period == multiple):
        to_update.append((('guntrue_%d' % period), r[2] * r[3], res.replace('gun_', 'guntrue_')))

    return to_update

For contrsynth.py, if a potential new gun and the old gun have equal bounding boxes, the old gun's RLE is downloaded from Catagolue, and then the populations are compared. This does mean slightly more processing, but if that turns out to be a problem, it could be implemented only as a temporary measure to fix the significantly over-dense guns, once staging has been fixed:

Code: Select all

from urllib.request import urlopen, Request
from sys import argv
import os

import idgun


def main():

    filename = os.path.join('shinjuku', 'comp', 'cached_contrib.sjk')

    with open(filename, 'w') as f:
        f.write('# ensure this is empty\n')

    address = argv[2]

    guncosts = []
    for tab in ['gun', 'guntrue']:
        gc = urlopen(address + '/textcensus/b3s23/synthesis-costs/' + tab).read().decode()
        gc = [tuple(s.replace('"', '').split(',')) for s in gc.split('\n') if ',' in s]
        guncosts += gc[1:]
    guncosts = {k : (int(v) % 100000000000000000) for (k, v) in guncosts}

    from shinjuku import lt4
    from shinjuku.search import read_components
    from shinjuku.gliderset import gset
    from shinjuku.transcode import encode_comp, decode_comp, realise_comp
    from shinjuku.checks import rewind_check
    from shinjuku.synthtools import split_mosaic as split_synthesis

    def is_good(synthline):

        out_str = decode_comp(synthline)[2]
        pat = realise_comp(synthline)
        actual_str = pat.oscar(verbose=False, return_apgcode=True).get('apgcode', 'rubbish')
        return (out_str == actual_str)

    knowns = read_components()

    print("%d components known" % len(knowns))

    # Download contrib.sjk:
    dl_address = address + "/textsamples/xs0_contrib/b3s23/synthesis"
    contrib_lines = urlopen(dl_address).read().decode()
    contrib_lines = [s for s in contrib_lines.split('\n') if '>' in s]

    # Download front of RLE queue
    dl_address = address + "/readsynth"
    rle_lines = urlopen(dl_address).read().decode()
    rle_lines = [s for s in rle_lines.split('\n\n') if 'x' in s]

    to_delete = len(rle_lines) - 1

    second_round = os.path.exists('cata.txt')

    if second_round:
        with open('cata.txt') as f:
            coapgcodes = [x.strip() for x in f]
        for x in coapgcodes:
            print('Downloading %s' % x)
            dl_address = address + "/textsamples/" + x + "/b3s23/synthesis"
            rle_lines.append(urlopen(dl_address).read().decode())

    engulfed = set([])

    # Utilise existing synthesis-uploading framework:
    payload = "%s SYNTH b3s23\n" % argv[1]

    # Parse RLEs
    for rle in rle_lines:

        print(rle)

        x = None

        try:
            x = idgun.identify_gun(rle, lt4)
        except (ValueError, KeyError, TypeError):
            print("# Not a gun")

        if x is not None:

            for (gunname, guncost, gunrle) in x:

                if (gunname in guncosts) and (guncosts[gunname] <= guncost):
                    print('New cost %d is no better than existing cost %d' % (guncost, guncosts[gunname]))
                    if guncosts[gunname] == guncost:
                        #(New code)
                        #Ok, the bounding boxes are the same, but we're not done yet.
                        #There exists an issue known as 'pointless over-densification', where some guns have
                        #additional still lifes/oscillators uselessly packed into their bounding box.
                        #Discussion can be found here: https://conwaylife.com/forums/viewtopic.php?f=4&t=6916
                        #To fix this, the populations need to be compared:
                        newgunpt = lt4.pattern(gunrle)
                        og = urlopen(address + '/textsamples/b3s23/'+gunname+'/synthesis')
                        oldgunpt = lt.pattern(og)
                        newpop = idgun.get_raw_population(newgunpt)
                        oldpop = idgun.get_raw_population(oldgunpt)
                        if newpop < oldpop:
                            print('New population of '+str(newpop)+' exceeds old population of '+str(oldpop))
                            #No need to update guncosts, since guncosts[gunname] has to equal guncost.
                            payload += ('\n' + gunrle + '\n')
                        
                        
                else:
                    guncosts[gunname] = guncost
                    payload += ('\n' + gunrle + '\n')

            # If it's a gun then don't waste time digesting it as though it were a glider synthesis:
            continue

        for radius in [5, 8, 13, 21]:
            print("# Filtering with radius %d" % radius)
            try:
                subpatterns = [c for c in split_synthesis(rle, radius=radius-1, maxtime=1024)]
                for s in subpatterns:

                    w = s.wechsler
                    if (w != '#'):
                        if w in engulfed:
                            continue
                        print("# Engulfing %s" % w)
                        engulfed.add(w)

                    try:
                        dst = s[4096].apgcode
                        if s[4096][-4096] == s:
                            print("# Null component")
                            continue

                        x = s
                        g = gset.extract(x)
                        src = (x - g.s()).apgcode

                        directions = 0

                        for salvo in g.l:
                            if salvo.nonempty():
                                directions += 1
                                if (salvo[4].centre() != salvo.centre()):
                                    print("# contains unstable salvo")
                                    raise ValueError("Invalid synthesis.")

                        if (src == 'xs0_0') and (directions <= 1):
                            print("# Unstable unidirectional salvo")
                        elif src[:2] == 'xg':
                            print('# src is a gun; skipping...')
                        elif dst[:2] == 'xg':
                            print('# dst is a gun; skipping...')
                        else:
                            print("# processing src=%s, dst=%s..." % (src, dst))
                            c = encode_comp(s, remove_spaceships=False)
                            print(c)
                            if rewind_check(*realise_comp(c, separate=True)):
                                contrib_lines.append(c)
                            else:
                                raise ValueError("Not rewindable.")
                            print("#     ...success.")
                    except (ValueError, KeyError, TypeError):
                        print("# Invalid component")
            except (ValueError, KeyError, TypeError):
                print("# Incomprehensible pattern!")

    # Deduplicate against repository:
    contrib_lines = [s for s in set(contrib_lines) if (s not in knowns) and ('ov_' not in s)]
    contrib_lines = [s for s in contrib_lines if is_good(s)]
    contrib_lines.sort()

    print("%d original contributions" % len(contrib_lines))

    # Save to file:
    if '.' in argv[1]:
        with open(argv[1], 'w') as f:
            for l in contrib_lines:
                f.write('%s\n' % l)
        return

    payload += "\n#CSYNTH xs0_contrib costs 0 gliders.\n"
    payload += '\n'.join(contrib_lines)
    payload += '\nThis line contains an exclamation mark!\n'

    req = Request(address + "/commonnames", payload.encode('utf-8'), {"Content-type": "text/plain"})
    f = urlopen(req)

    print(f.read())

    if second_round:
        return

    # Save contrib.sjk into components folder. This means that when we
    # subsequently run diffupdate.py (immediately after this script),
    # the user contributions will be included in Catagolue immediately,
    # instead of waiting until they are incorporated into the Shinjuku
    # repostory.
    with open(filename, 'w') as f:
        f.write('# Start of contrib.sjk\n')
        for x in contrib_lines:
            f.write('%s\n' % x)
        f.write('# End of contrib.sjk\n')

    print("Saved contributions into %s" % filename)

    if (to_delete >= 1):
        print("Deleting %d RLEs...\n" % to_delete)
        payload = "%s DELSYNTH %d\n" % (argv[1], to_delete)
        req = Request(address + "/commonnames", payload.encode('utf-8'), {"Content-type": "text/plain"})
        f = urlopen(req)

    print("The operation completed successfully.")

if __name__ == '__main__':

    main()

[WhiteHawk]

New strategy

Code: Select all

Code: Select all

Out of curiosity, who would actually be able to update and implement this code in Catagolue?
It also seems like killing two birds with one stone (the bounding box glitch) may also be worthwhile here.

[PK22]

Out of curiosity, who would actually be able to update and implement this code in Catagolue?
It also seems like killing two birds with one stone (the bounding box glitch) may also be worthwhile here.

It looks like I would need to create a separate fork of Catagolue, then submit a merge request and wait for that to be approved, or something along those lines. I agree that we should try to fix as many issues as possible, so I will also update some slightly outdated information with the same fork (such as making the new GPU symmetries official), as well as maybe fixing/adding some names.

I don’t know how to fix the bounding box glitch/detect glitched guns, but I’ll have some free time at the weekend, so I might be able to find a fix if someone knows what causes the glitch as well as the characteristics of glitched guns. I’m not too familiar with the idgun.py code that actually finds the bounding box, but it’s at least in a programming language I know, so I can probably figure it out.

[dvgrn]

I don’t know how to fix the bounding box glitch/detect glitched guns, but I’ll have some free time at the weekend, so I might be able to find a fix if someone knows what causes the glitch as well as the characteristics of glitched guns.

Scorbie came up with some good ideas for a patch to the bounding-box glitch, but I'm not clear that they were ever successfully turned into a pull request. Something Unclear Happened, as described higher in this thread. There are some links there to candidate code.

There was also some discussion of the code changes that would be needed to prefer lower-population guns over higher-population ones, given the same bounding box area.

[WhiteHawk]

I don’t know how to fix the bounding box glitch/detect glitched guns, but I’ll have some free time at the weekend, so I might be able to find a fix if someone knows what causes the glitch as well as the characteristics of glitched guns.

Scorbie came up with some good ideas for a patch to the bounding-box glitch, but I'm not clear that they were ever successfully turned into a pull request. Something Unclear Happened, as described higher in this thread. There are some links there to candidate code.

There was also some discussion of the code changes that would be needed to prefer lower-population guns over higher-population ones, given the same bounding box area.

But who is able to go in and implement the code fixes?

[dvgrn]

But who is able to go in and implement the code fixes?

Anybody could contribute a pull request to the repo, theoretically (it's not clear what happened with Scorbie's attempt to do that). Then apgoucher will have to review and approve the PR.

[PK22]

I've submitted two merge requests to Catagolue. The first one implements official support for the new GPU symmetries. The second one adds my changes to idgun.py and contrsynth.py (there was a minor syntax error in the latter, but my merge request features a fixed version). I haven't tested the new version, so in case something goes horribly wrong, I'm going to create a backup of every stored gun and guntrue and upload it here.

EDIT: Here's the aforementioned backup:

gunbackup.7z

(1.35 MiB) Downloaded 81 times

I note that file size is a good way to find over-densified guns - the largest one is guntrue_8423 at 6.92KB, and it hurts to look at:

Code: Select all

#CSYNTH guntrue_8423 costs 15892 cells.
#C period 8423 fullperiod 8423 bbox 137 by 116
#CLL state-numbering golly
x = 137, y = 116, rule = LifeHistory
9.2A5.A5.2A13.2A2.A8.A10.2A11.A9.2A15.A7.A.2A7.2A12.2A$.2A4.A2.A3.
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2A4.A6.A.A4.2A7.A11.A2.A9.2A3.2A4.A.A9.A6.A7.A.A10.2A7.A.2A3.2A4.
2A$.A.A9.2A5.2A5.A6.2A.7A5.2A7.A8.A3.A.A6.A11.A7.A21.A.A3.A$2.A26.
A2.A2.A.A3.B2.A8.2A2.A.A6.A5.A5.3A7.A4.A22.2A12.A$28.2A2.2A2.BA.2A
2.2A9.A3.A8.3A7.A9.A.A4.A2.2A18.A11.2A3.2A$12.2A6.2A6.A7.2AB2AB6.
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2A16.A.A2.A2.A4.A5.A.A$10.A10.A.A3.A6.15B3.2A12.A9.A11.A4.A3.A2.A
7.2A6.2A3.2A4.A7.A$9.A.A10.2A2.2A5.14B2A.A2.A11.A.A5.3A11.A6.A4.2A
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14.2A10.2A$2A.A2.5B2A8B7.A4.3A3.2A.A7.A4.4B16.A7.A4.2A17.A.A.A17.
2A$A2.4A3BA2BA5B.B2A4.A.A3.A5.A.A8.2A4.4B20.3A5.A2.A15.2A20.2A$.2A
2.BAB.2B2A6B.BA.A4.A.A26.4B19.A9.2A2.2A21.2A4.2A$3.2A6.7B5.A5.A.A
22.A3.4B4.2A19.A6.A4.2A15.A2.A3.A.A$3.A7.2B.4B5.2A5.A.A3.A16.A.A3.
4B3.A2.A16.A.A6.A2.B2AB6.A7.A2.A6.A$5.A9.4B12.A3.A.A5.2A9.A.A3.4B
4.2A4.A3.A3.2A2.A.A3.3A3.3B6.A.A7.2A8.A$4.2A10.4B15.2A6.A.A9.2A4.
4B7.3A2.A.A2.A2.2A.2A2.A6.B.B4.A2.A16.2A5.2A$17.4B24.A4.2A10.4B5.A
5.A.A3.A.A2.B8.5B5.2A24.A$9.2A7.4B6.2A11.4A.2A2.A2.A9.7B.2A5.A.4A
2.AB2A6.6B17.2A9.2A.A$9.A9.4B5.A7.2A3.A2.A.A.A.A.2A10.9B7.A3.A.A.
2A4.8B5.2A10.A.A8.A.A$.2A7.A9.4B5.3A4.A.A4.BABABA.A5.A8.6B8.A2.BA.
A2.13B6.A13.A4.A$.A.A2.A4.A.A.A5.4B6.A5.A.A4.B2ABA.A4.A.A8.5B7.A.
2BA.A5.13B5.A3.2A5.A.2A2.A.A$2.A3.3A3.2A.3A4.4B12.2A5.2B.BA6.A4.2A
2.7B6.2A.2BA5.15B3.2A2.A.A4.A.A4.2A5.2A.A$9.A8.A4.4B17.3B14.A4.6B
10.3B4.15B7.2A4.A2.A11.A.2A$8.2A7.2A5.4B7.2A6.4B15.A3.7B10.2B.B.
17B12.A.A5.2A$25.4B7.A6.B2A3B6.2A4.2A3.6B4.29B6.2A5.A3.A3.A$26.4B
6.A.AB3.B2A3B7.A9.7B2.16B2A13B6.A8.A.A2.A.2A5.A$3.A14.A8.4B6.2AB.
10B5.A.A7.7B2.16B2A14B4.A6.A3.A4.A.A4.A.A$3.3A11.A.A8.4B7.13B5.2A
6.9B.27B3.B2A3.2A4.A.A15.A$6.A4.2A4.A.A4.2A3.4B6.14B12.36B4.A2.A9.
A7.A5.3A$5.2A5.A5.A6.A4.4B5.15B6.B4.20B2.2B2.B3.6B5.2A.A5.3A7.A.A
4.A$11.A12.A6.4B6.8B2.4B4.2AB.19B14.6B7.A5.A9.A2.A$11.2A11.2A6.4B
5.6B5.4B3.2A19B14.9B6.2A15.A.A$18.2A13.4B3.9B4.4B3.B.17B8.2A5.2A4.
4B18.2A3.A6.2A$2.2A13.A.A9.2A3.4B.4B4.2A5.4B5.17B7.A.A5.A5.4B17.A
12.A$.A.A10.A.A8.A3.A.A3.7B5.A3.A3.4B4.17B8.A3.3A7.4B5.A12.A8.A$2.
A3.2A6.2A8.A.A4.A4.5B7.4A4.4B3.15B.B2A10.A10.4B3.A.A6.2A2.2A3.2A3.
2A$5.A.A15.A2.A4.2A3.5B16.4B2.12B4.BA.A14.2A.A3.4B3.A4.2A2.A7.A.A$
5.A4.2A12.2A9.7B4.4A8.15B9.A13.A2.2A4.4B7.A.2A9.A$2A4.A3.A23.4B.4B
3.A2.3A7.15B8.2A3.A4.A3.2A8.4B$A4.2A4.A6.2A13.4B3.4B8.A7.14B12.A.A
2.A.A8.2A3.4B$.A7.A.A6.A.A3.A7.4B5.4B6.A.A7.12B3.2A9.A.A2.A.A7.A.A
3.4B19.2A$2A7.2A8.2A2.A.A5.4B7.4B5.A.AB7.10B3.A2.A9.A4.A9.A.A3.4B
6.2A3.2A5.A.A.A$24.A.A3.4B9.4B5.A3B7.9B4.A2.A4.2A18.A5.4B4.A.A4.A
8.2A$13.2A10.A3.4B11.4B6.4B5.9B5.2A5.A.A12.2A10.4B4.A4.A$12.A.A4.
2A7.4B3.A9.4B5.6B5.6B14.A8.A5.A11.4B7.A10.2A$.A5.A3.A.A5.A7.4B3.A.
A4.A4.4B4.7B.2B2.5B22.A.A3.A13.4B6.2A3.2A3.A2.A$A.A3.A.A3.A8.A4.4B
5.2A3.A.A4.4B2.8B.9B6.2A15.A.A.A8.A6.4B10.A3.A2.A$.A.A3.2A6.A4.2A
3.4B12.A6.24B4.A2.A15.2A.2A6.A.A6.4B10.A3.2A$2.A.A10.3A6.4B21.24B
4.2A8.2A16.A.A.A6.4B8.2A$3.A.A12.A4.4B22.19B2.4B12.A.A16.A2.A.A6.
4B$4.A.A10.2A3.4B8.2A4.2A7.18B4.4B6.A3.A.A8.2A6.2A3.A8.4B10.2A$6.A
10.8B8.A.A3.A2.A6.16B7.4B4.A.A3.A3.2A4.2A2.2A17.4B9.A$6.2A5.2A4.5B
5.2A2.A5.A.A5.2AB.13B9.4B4.A7.A.A8.A.A17.4B10.A$12.A.BAB.5B6.A.A.
2A5.A5.A.AB2.11B11.4B4.3A3.A12.A.A10.2A5.4B5.5A$2A10.A.2AB2.5B6.2A
.A2.A9.A5.10B13.4B5.A2.A14.A6.2A4.A5.4B4.A$A10.2A.B.B3.5B3.3B.B2.
2A4.A3.2A5.2B2A6B8.2A4.4B7.2A5.A.A13.A4.A.AB.7B2.B3A$.A3.2A4.A2.2A
2B2.5B3.4B8.A.A8.3B2A6B8.2A5.4B7.A4.A.2A4.A7.A6.2AB.7B3.2B.A$2A2.A
2.A4.2A2.AB.13B.B5.A2.A5.A3.10B16.4B5.A5.A6.A.A3.A.A9.12B4A$5.2A7.
2ABA13B.B2A5.2A4.3A3.8B.B2A.A13.4B4.2A3.2A7.A.A2.2A10.7B2A3BAB2.2A
$12.2A2.A5BA10B2A10.A5.7B3.B2AB3A12.4B19.A14.7B2A2B.B3A2.A$2.2A7.A
2.A2.4BABA7B.2B12.A4.6B6.B4.A7.A4.4B11.2A5.2A13.10B3.B.A.2A$2.A.A
7.2A3.4BABA7B7.2A5.2A5.6B4.2A.3A8.3A3.4B10.A13.2A5.8B8.A$4.A13.4BA
7B6.A2.A12.5B4.A2.2A13.A3.4B7.A.A3.A9.A.A3.9B7.2A$4.2A14.9B3.2A2.
2A13.8B.A.A15.A.A3.4B6.2A3.A.A2.A.2A3.A3.4B2.3B$17.B.10B.B2.A8.A8.
8BA.A.2A.A12.A5.4B9.A2.A2.2A.A6.4B3.5B10.A$.A6.A7.2A12B3A9.3A6.6B.
2BAB.A.2A4.A.A.2A9.4B8.A.A12.4B7.2A8.3A$.3A3.A.A6.2AB.8B.BA6.2A6.A
4.7B2.2B2.A6.A.2A.A.A9.4B8.A12.4B8.A8.A$4.A3.A.A6.B3.6B4.2A3.A2.A
4.2A4.7B3.B.2A6.A5.A11.4B19.4B10.3A4.A.A$3.2A5.A11.4B6.A4.A.A4.4B.
8B2.A.A2.2A3.2A18.4B10.A6.4B13.A5.A$10.2A11.4B4.A6.A7.11B2.2A2.A2.
A12.2A3.A5.4B7.3A5.4B6.2A$19.2A3.2B2A3.2A12.12B7.2A13.A3.A.A5.4B5.
A7.4B8.A9.2A$18.A2.A3.BABA16.12B12.2A5.2A.A4.A7.4B4.2A5.4B8.A10.A.
A$3.A15.2A5.A3B5.2A8.11B13.A.A.A2.A.A6.3A5.9B4.4B6.A.A14.A$2.A.A
22.4B4.2A7.9B12.2A5.2A13.A6.6B5.4B7.2A16.A$.A.A4.A4.2A13.4B9.2B.
10B11.A17.A10.8B2.4B16.A8.2A$.2A4.A.A3.A.A7.2A4.4B7.16B.B4.BA.A3.
2A6.2A3.A.A7.15B5.2A8.3A5.A$8.A.A3.A.A5.A.A5.4B3.23B2.B2A5.A6.A3.A
.A.A6.14B3.2A2.A3.A3.A7.A.A$9.A.A3.A6.2A7.32B6.A5.A.A4.A2.A6.13B4.
A.2A3.A.A.A.A6.A2.A$10.A.A19.32B5.A.A3.2A6.2A5.2AB.10B13.A3.A8.A.A
2.2A$4.2A5.A13.2A6.31B6.2A17.A.AB3.B2A3B29.A3.A$4.A11.2A3.A4.A7.
30B25.A6.B2A3B5.2A5.2A20.A$6.A9.A3.A.A2.A10.28B24.2A6.4B7.A.A4.A.A
16.3A$2.A2.2A7.A.A2.A.A3.2A10.17B5.B.4B4.2A6.2A18.3B8.A.A4.2A8.A7.
A$.A.A10.2A3.2A16.14B11.4B4.A5.A2.A11.A6.2B.BA6.A13.3A$A.A26.A7.
14B12.4B3.A.2A3.2A3.2A5.3A5.B2ABA.A18.A$.A26.A.A10.3B4.2B14.4B3.A.
A7.A.A4.A7.BABABA.A19.A$13.A.2A3.2A.A5.A.A10.B6.2B5.A8.4B12.A7.A4.
A2.A.A.A.A.2A10.2A3.2A$.A11.2A.A2.A.A.3A4.A.A5.2A8.B2AB3.A.A8.4B4.
A.2A2.2A6.2A4.4A.2A2.A2.A2.2A5.A.A9.2A$A.A3.2A11.A6.A4.A.A3.A2.A8.
2A5.A5.2A3.3BA3.2A.A6.2A.A10.A4.2A4.2A5.2A10.A2.2A$A2.A2.A.A11.A4.
2A5.A.A3.A.A16.3A.A.A4.3BA11.A2.2A8.A.A30.2A.A$.2A4.2A10.2A12.A5.A
19.2A8.3AB10.2A11.2A!

[WhiteHawk]

Once Catagolue starts accepting population reductions and we start posting them in this thread, I think it might be a good idea to place them all in one code block (per post) for neatness.

Might it be a better idea to have a separate thread concerning potential population reductions to guns to avoid excessive cluttering in the Executions thread? (They could go here too, but that may clutter this thread)

EDIT: Just some examples of the many reductions that could be made (RED = Almost always suboptimal, YELLOW = contextually suboptiomal, WHITE = optimal population, suboptimal form, GREEN = optimal form)

31.4 in the snark/CP semi-snark

Code: Select all

x = 67, y = 37, rule = LifeHistory
3D3.D2.D13.3D5.D$3.D2.D2.D16.D3.2D$3.D2.D2.D16.D4.D$3D3.4D13.3D5.D$3.
D5.D16.D4.D$3.D5.D16.D4.D$3D6.D13.3D4.3D5$43.D$43.D6.2D$2E3.2E18.2A16.
D7.D$2E2.E.3E16.A.A15.D5.D.D.2D10.2D$4.E4.E17.A4.2A9.D5.2D2.D10.D.D$4E
.2E2.E13.4A.2A2.A2.A7.D9.D4.2D4.D$E2.E.E.E.2E12.A2.A.A.A.A.2A7.D5.4D.
2D2.D2.D.2D$3.E.E.E.E16.A.A.A.A10.D5.D2.D.D.D.D.2D.D$4.2E.E.E17.2A.A.
A10.D8.D.D.D.D4.D$8.E22.A11.D9.2D.D.D4.2D$43.D13.D$43.D$43.D$43.D$43.
D6.2A$25.2C16.D7.A$25.C.C5.2C8.D5.A.A.2A10.2A$27.C4.C.C8.D5.2A2.A5.2A
3.A.A$23.4C.2C2.C10.D9.A4.A.A3.A$23.C2.C.C.C.2C9.D5.4A.2A2.A4.2A$26.C
.C.C.C10.D5.A2.A.A.A.2A$27.2C.C.C10.D8.A.A.A.A$31.C11.D9.2A.A.A$43.D13.
A$43.D$43.D!

Chucklebaits

Code: Select all

x = 32, y = 40, rule = LifeHistory
.3D4.3D10.3D4.3D$D3.D2.D3.D8.D3.D2.D3.D$3.D3.D3.D11.D3.D3.D$2.D5.4D10.
D5.3D$.D9.D9.D5.D3.D$D6.D3.D8.D6.D3.D$5D3.3D9.5D3.3D3$21.2D$21.2D$3.D
.2D20.2D$.3D.D.D.2D.D8.4D2.D.D$D4.D.D.D.2D7.D4.D.D.D$D.D.D.D.D11.D.D.
D.D.D$.2D.D.D14.2D.D.D$5.D.D17.D.D$6.D19.D5$.3D3.5D9.3D4.3D$D3.D2.D12.
D3.D2.D3.D$3.D3.D15.D7.D$2.D5.3D11.D5.3D$.D9.D9.D9.D$D6.D3.D8.D6.D3.D
$5D3.3D9.5D3.3D4$24.A$3.2E3.E14.A.A$.3E.E.E.E11.3A.A$E4.E.E.E10.A4.A.
2A$E.E.E.E.E11.A.A.A.A.A$.2E.E.E14.2A.A.A$5.E.E17.A.A$6.E19.A!

Two-eater weld used in the stable/odd-period x7 multiplier

Code: Select all

x = 26, y = 9, rule = LifeHistory
6.2E14.2C$6.E15.C$2.2E3.3E8.2C3.3C$2.E.E5.E7.C.C4.C$E.E.6E6.C.C.5C$2E
14.2C$6.2E14.C$6.2E13.C.C$22.C!

Drifty Eater 3

Code: Select all

x = 46, y = 19, rule = LifeHistory
.3D5.D8.3D4.3D7.3D4.3D$D3.D3.2D7.D3.D2.D3.D5.D3.D2.D3.D$4.D2.D.D11.D2.
D3.D8.D3.D3.D$.3D5.D8.3D3.D.D.D7.D5.4D$4.D4.D11.D2.D3.D6.D9.D$D3.D4.D
7.D3.D2.D3.D5.D6.D3.D$.3D3.5D6.3D4.3D6.5D3.3D4$3.D$2.D.D.2D15.2E11.2A
$.D2.D.D.D9.2E2.E.E11.A.A2.2A$D3.D3.D9.E3.E4.E10.A3.A$.3D.3D11.3E.5E6.
4A.3A$3.D.D15.E.E10.A2.A.A$3.D.D.3D11.E.E.3E9.A.A.3A$4.2D.D2.D11.2E.E
2.E9.2A.A2.A$9.2D16.2E14.2A!

Eater welded to snake bridge eater

Code: Select all

x = 26, y = 8, rule = LifeHistory
7.2D15.2A$D.2D2.D.D10.2A2.A.A$2D.D2.D13.A2.A$3.D.2D13.A.2A$2D.D13.2A.
A$D.D.2D.D9.A.A.2A.A$2.D.D.2D11.A.A.2A$2.2D15.2A!

Beehive with tail

Code: Select all

x = 30, y = 7, rule = LifeHistory
13.2D$3.E8.D2.D$2.E.E8.3D8.2A$2.E.E20.A$.2E.2E9.3D7.A.2A$E2.E2.E8.D2.
D7.A2.A$2E2.2E10.2D9.2A!

Standard Syringe catalyst

Code: Select all

x = 102, y = 24, rule = LifeHistory
26.2E3.E24.2E3.E$26.E3.E.E23.E3.E.E20.2C3.C$27.E3.E.E23.E3.E.E19.C3.C
.C$28.E3.E.E.2E20.E3.E.E.2E16.C3.C.C$20.2F4.E.4E2.E.2E12.2D4.E.4E2.E.
2E17.C3.C.C.2C$20.F5.2E3.E.E16.D5.2E3.E.E19.C.4C2.C.2C$21.3F5.E.E.2E.
2E13.3D5.E.E.2E.2E14.C.C3.C.C10.D$23.F2.3E.E3.E.E16.D2.3E.E3.E.E15.C2.
C4.2C.2C5.2D$26.E2.E4.E.E19.E2.E4.E.E16.2C3.C2.C.C2.C2.3D$27.2E6.E21.
2E6.E16.6B2C5B2CB4D$82.19D3$2.2D3.D18.2D3.D$2.D3.D.D17.D2A.D.A23.2A3.
A21.2D3.D$3.D3.D.D17.A3.A.A22.A3.A.A20.D2A.D.A$4.D3.D.D.2D14.A3.A.A.2A
19.A3.A.A20.A3.A.A$2.D.4D2.D.2D6.2F7.A4.A.2A20.A3.A.A.2A17.A3.A.A.2A$
.D.D3.D.D10.F6.A.5A9.D6.2D4.A.4A2.A.2A18.A4.A.2A$.D2.D2.D.2D.2D7.3F2.
A.A4.A.2A.A.2A2D6.D4.A.A3.A.A10.F9.A.5A9.D$2D3.D.D2.D.D2.D7.F3.A2.2A.
A2.A.2A.A2D7.3D.A.A2.A2.2A.2A5.2F8.A.A4.A.2A.A.2A2D$4.2D.2D5.2D9.D2.2A
.A.2A5.4D9.D2.A3.2A2.A.A5.3F9.A2.2A.A2.A.2A.A2D$25.12D2.4D7.14BABAB3.
4F7.D2.2A.A.2A5.4D$50.15BA2B2.4F8.12D2.4D!

P5 bumpers (same goes for p5 gallus for the top left and 2 right sparkers)

Code: Select all

x = 64, y = 45, rule = LifeHistory
32D$D30.D$D30.D$D30.D31.E$D8.2E16.E3.D8.E20.3E$D7.E2.E13.3E3.D7.E.E18.
E$D2.E2.E2.E.E12.E6.D8.E19.2E$D2.5E.E.2E11.2E5.D9.2E.E4.E$D8.2E3.E16.
D11.E.E2.E.E5.E$D4.3E2.2E8.E10.D9.2E3.E.E2.E3.E.E$D3.E.E2.E.E3.E3.E.E
9.D11.E.2E.E5.E2.E$D3.E.2E2.2E6.E2.E9.D11.E.E.E2.E4.2E$D4.E3.2E3.E4.2E
10.D9.E.E.E.2E$D5.2E.E.2E18.D9.2E.E.E$D6.E.E.E19.D12.E.E$D5.E2.E.E11.
3D.D3.D12.2E11.3D.3D$D5.2E2.E12.D3.D3.D25.D5.D$D22.3D.D3.D25.3D.3D$D22.
D.D.D3.D27.D.D$D22.3D.D3.D25.3D.3D$D30.D$32D5$48.2A13.A$27.E19.A.A11.
3A$25.3E13.2A3.A13.A$10.2E12.E16.A.A.A.2A11.2A$8.3E.E11.2E17.A.A.A2.A
$7.E4.E30.A.2A.A7.A$8.3E.2E6.E20.2A3.A.A2.A3.A.A$10.2E3.E3.E.E21.A.A2.
A.A3.A2.A$12.E5.E2.E19.2A.A4.A5.2A$12.E6.2E19.A$9.3E3.E23.A.A$7.2E.E.
2E26.A$6.E3.E.E$5.E2.E.E.E$5.3E3.E12.3D.3D26.3D.D$8.3E13.D3.D28.D3.D$
7.E16.3D.3D26.3D.D$7.2E17.D.D.D28.D.D$24.3D.3D26.3D.D!

Lastly, p3 eaters

Code: Select all

x = 95, y = 39, rule = LifeHistory
3.3D3.4D12.3D3.4D11.3D3.D2.D3.F6.3D3.3D$6.D5.D15.D2.D17.D2.D2.D3.F9.D
5.D$6.D5.D15.D2.D17.D2.D2.D3.F9.D5.D$3.3D5.D13.3D3.3D12.3D3.4D3.F6.3D
3.3D$6.D4.D16.D5.D14.D5.D3.F9.D5.D$6.D3.D17.D5.D14.D5.D3.F9.D5.D$3.3D
4.D14.3D3.3D12.3D6.D3.F6.3D3.3D$59.F$59.F$59.F$4.D54.F$4.D2.E5.2E9.2E
.2E5.2E9.D.2E5.2E3.F4.D.2C5.2C9.4F2.4F$3.2E.E.E.EBEB.E9.E.E.E.E.E2.E8.
D.E.E.EBEB.E2.F4.D.C.C.CBCB.C11.F2.F2.F$3.2E.E.EBE2B.2E8.ED.E.E.E3.2E
8.D3.EBE2B.2E2.F4.D3.CBC2B.2C11.F2.F2.F$4.D.E.E2.B11.E.2E2.E15.D3.E2.
B6.F4.D3.C2.B12.4F2.4F$.6E.4E12.ED2.2E.E.E11.D4.3E6.F4.D4.3C15.F5.F$E
2.BD2.E.2B3.2F9.D4.E.E3.F8.D3.3B3.2F2.F4.D6.B3.F11.F5.F$2E2.D3E5.F11.
D2.E6.F9.D2.2E4.F4.F4.D2.4C4.F8.4F2.3F$4.DEB5.F10.F.D.B6.F10.D2.2B3.F
5.F4.D.C2.2B4.F$9D3F4D7.DF4D2E2DF3D7.2E2DE3DF4D2.F4.DCDC3DC3DF$4F4.F16.
F3.E3.F10.EDEBEB2.F6.F4.DC.C2.C.C2.F$4.4F17.F3.E3.F11.E3.E2.F6.F4.D.C
3.C.C2.F$25.F3.E3.F11.D3E3.F6.F4.D6.C3.F$44.EDE4.F7.F$44.2E13.F$59.F$
59.F$2.4F2.4F12.F3.F2.F13.4F2.4F4.F$5.F2.F2.F12.F3.F2.F16.F2.F2.F4.F24.
4F2.F3.F$5.F2.F2.F12.F3.F2.F16.F2.F2.F4.F4.D2.2A5.2A11.F2.F3.F$2.4F2.
4F12.5F2.F13.4F2.4F4.F4.D.A2.A.ABAB.A10.F2.F3.F$5.F5.F16.F2.F16.F2.F2.
F4.F4.D.2A.ABA2B.2A7.4F2.5F$5.F5.F16.F2.F16.F2.F2.F4.F4.D2.A.A2.B14.F
6.F$2.4F2.3F17.F2.F13.4F2.4F4.F4.D.BA.4A14.F6.F$59.F4.D3AB.2B3.2F7.4F
6.F$59.F4.DB2AB5.F$59.F3.BDA.A5.F$59.F2.3ADA3D4F3D$59.F3.BDB3.F!

[PK22]

My merge request fixing overdensification has been implemented! Unfortunately, there was a problem with the URL used to request old guns, so the update process is currently broken.

I've submitted a merge request to fix this issue, but once it's implemented, overdensification should be mostly solved.

It's probably a good idea for someone to compile known population reductions into one place so that submission is easier once lower-population guns are finally accepted, though full decontamination of the overdensification might take a while.

[WhiteHawk]

My merge request fixing overdensification has been implemented! Unfortunately, there was a problem with the URL used to request old guns, so the update process is currently broken.

I've submitted a merge request to fix this issue, but once it's implemented, overdensification should be mostly solved.

It's probably a good idea for someone to compile known population reductions into one place so that submission is easier once lower-population guns are finally accepted, though full decontamination of the overdensification might take a while.

And just to be clear, this allows for population reductions to be admitted as long as the bounding box is the same or lower than before, correct?

[PK22]

And just to be clear, this allows for population reductions to be admitted as long as the bounding box is the same or lower than before, correct?

Correct. The way it works is, if the bounding boxes are the same, it compares the populations of the new and old guns (only including state-1 LifeHistory cells), and if the new gun has a lower population, it will replace the old one. And if the bounding box is smaller, it will replace the old gun anyway, just like before.

[WhiteHawk]

And just to be clear, this allows for population reductions to be admitted as long as the bounding box is the same or lower than before, correct?

Correct. The way it works is, if the bounding boxes are the same, it compares the populations of the new and old guns (only including state-1 LifeHistory cells), and if the new gun has a lower population, it will replace the old one. And if the bounding box is smaller, it will replace the old gun anyway, just like before.

Great! Will there still need to be a future merge for guns which have incorrect bounding boxes anyway?

[PK22]

Great! Will there still need to be a future merge for guns which have incorrect bounding boxes anyway?

At some point, yes, but I don't know of any methods to determine if the bbox has been incorrectly calculated. However, once such a method is implemented, it has to be applied to all new guns, rather than just ones where the new bbox matches the old one, so it will add to processing time.

Ideally, it should be implemented after the collection has been purged of over-densification, since that's going to require the processing of hundreds of faulty guns.

[WhiteHawk]

My merge request fixing overdensification has been implemented! Unfortunately, there was a problem with the URL used to request old guns, so the update process is currently broken.

I've submitted a merge request to fix this issue, but once it's implemented, overdensification should be mostly solved.

It's probably a good idea for someone to compile known population reductions into one place so that submission is easier once lower-population guns are finally accepted, though full decontamination of the overdensification might take a while.

The submission issue is fixed!

Great! Will there still need to be a future merge for guns which have incorrect bounding boxes anyway?

At some point, yes, but I don't know of any methods to determine if the bbox has been incorrectly calculated. However, once such a method is implemented, it has to be applied to all new guns, rather than just ones where the new bbox matches the old one, so it will add to processing time.

Ideally, it should be implemented after the collection has been purged of over-densification, since that's going to require the processing of hundreds of faulty guns.

Would the approach to have both the BB of the current submission and new submission be (re)assesed for each gun when comparing entries work?

[PK22]

Would the approach to have both the BB of the current submission and new submission be (re)assesed for each gun when comparing entries work?

Could do, but since no new guns with faulty bounding boxes can be submitted, it might be easier to have a temporary patch that only checks it for the confirmed faulty guns, then remove that once they're fixed to save resources. Again, the issue is performing a download for every new submitted gun, rather than just the ones where the new bbox = old bbox.

[WhiteHawk]

Would the approach to have both the BB of the current submission and new submission be (re)assesed for each gun when comparing entries work?

Could do, but since no new guns with faulty bounding boxes can be submitted, it might be easier to have a temporary patch that only checks it for the confirmed faulty guns, then remove that once they're fixed to save resources. Again, the issue is performing a download for every new submitted gun, rather than just the ones where the new bbox = old bbox.

True. I do think that a temporary patch might be better for data purposes. Likewise it might be important to temporary disable gun submissions until it's over as well.

EDIT: Is something stuck currently. Guns I updated last night haven't been updated.

[WhiteHawk]

Once Catagolue starts accepting population reductions and we start posting them in this thread, I think it might be a good idea to place them all in one code block (per post) for neatness.

Might it be a better idea to have a separate thread concerning potential population reductions to guns to avoid excessive cluttering in the Executions thread? (They could go here too, but that may clutter this thread)

EDIT: Just some examples of the many reductions that could be made (RED = Almost always suboptimal, YELLOW = contextually suboptiomal, WHITE = optimal population, suboptimal form, GREEN = optimal form)

31.4 in the snark/CP semi-snark

Code: Select all

x = 67, y = 37, rule = LifeHistory
3D3.D2.D13.3D5.D$3.D2.D2.D16.D3.2D$3.D2.D2.D16.D4.D$3D3.4D13.3D5.D$3.
D5.D16.D4.D$3.D5.D16.D4.D$3D6.D13.3D4.3D5$43.D$43.D6.2D$2E3.2E18.2A16.
D7.D$2E2.E.3E16.A.A15.D5.D.D.2D10.2D$4.E4.E17.A4.2A9.D5.2D2.D10.D.D$4E
.2E2.E13.4A.2A2.A2.A7.D9.D4.2D4.D$E2.E.E.E.2E12.A2.A.A.A.A.2A7.D5.4D.
2D2.D2.D.2D$3.E.E.E.E16.A.A.A.A10.D5.D2.D.D.D.D.2D.D$4.2E.E.E17.2A.A.
A10.D8.D.D.D.D4.D$8.E22.A11.D9.2D.D.D4.2D$43.D13.D$43.D$43.D$43.D$43.
D6.2A$25.2C16.D7.A$25.C.C5.2C8.D5.A.A.2A10.2A$27.C4.C.C8.D5.2A2.A5.2A
3.A.A$23.4C.2C2.C10.D9.A4.A.A3.A$23.C2.C.C.C.2C9.D5.4A.2A2.A4.2A$26.C
.C.C.C10.D5.A2.A.A.A.2A$27.2C.C.C10.D8.A.A.A.A$31.C11.D9.2A.A.A$43.D13.
A$43.D$43.D!

Chucklebaits

Code: Select all

x = 32, y = 40, rule = LifeHistory
.3D4.3D10.3D4.3D$D3.D2.D3.D8.D3.D2.D3.D$3.D3.D3.D11.D3.D3.D$2.D5.4D10.
D5.3D$.D9.D9.D5.D3.D$D6.D3.D8.D6.D3.D$5D3.3D9.5D3.3D3$21.2D$21.2D$3.D
.2D20.2D$.3D.D.D.2D.D8.4D2.D.D$D4.D.D.D.2D7.D4.D.D.D$D.D.D.D.D11.D.D.
D.D.D$.2D.D.D14.2D.D.D$5.D.D17.D.D$6.D19.D5$.3D3.5D9.3D4.3D$D3.D2.D12.
D3.D2.D3.D$3.D3.D15.D7.D$2.D5.3D11.D5.3D$.D9.D9.D9.D$D6.D3.D8.D6.D3.D
$5D3.3D9.5D3.3D4$24.A$3.2E3.E14.A.A$.3E.E.E.E11.3A.A$E4.E.E.E10.A4.A.
2A$E.E.E.E.E11.A.A.A.A.A$.2E.E.E14.2A.A.A$5.E.E17.A.A$6.E19.A!

Two-eater weld used in the stable/odd-period x7 multiplier

Code: Select all

x = 26, y = 9, rule = LifeHistory
6.2E14.2C$6.E15.C$2.2E3.3E8.2C3.3C$2.E.E5.E7.C.C4.C$E.E.6E6.C.C.5C$2E
14.2C$6.2E14.C$6.2E13.C.C$22.C!

Drifty Eater 3

Code: Select all

x = 46, y = 19, rule = LifeHistory
.3D5.D8.3D4.3D7.3D4.3D$D3.D3.2D7.D3.D2.D3.D5.D3.D2.D3.D$4.D2.D.D11.D2.
D3.D8.D3.D3.D$.3D5.D8.3D3.D.D.D7.D5.4D$4.D4.D11.D2.D3.D6.D9.D$D3.D4.D
7.D3.D2.D3.D5.D6.D3.D$.3D3.5D6.3D4.3D6.5D3.3D4$3.D$2.D.D.2D15.2E11.2A
$.D2.D.D.D9.2E2.E.E11.A.A2.2A$D3.D3.D9.E3.E4.E10.A3.A$.3D.3D11.3E.5E6.
4A.3A$3.D.D15.E.E10.A2.A.A$3.D.D.3D11.E.E.3E9.A.A.3A$4.2D.D2.D11.2E.E
2.E9.2A.A2.A$9.2D16.2E14.2A!

Eater welded to snake bridge eater

Code: Select all

x = 26, y = 8, rule = LifeHistory
7.2D15.2A$D.2D2.D.D10.2A2.A.A$2D.D2.D13.A2.A$3.D.2D13.A.2A$2D.D13.2A.
A$D.D.2D.D9.A.A.2A.A$2.D.D.2D11.A.A.2A$2.2D15.2A!

Beehive with tail

Code: Select all

x = 30, y = 7, rule = LifeHistory
13.2D$3.E8.D2.D$2.E.E8.3D8.2A$2.E.E20.A$.2E.2E9.3D7.A.2A$E2.E2.E8.D2.
D7.A2.A$2E2.2E10.2D9.2A!

Standard Syringe catalyst

Code: Select all

P5 bumpers (same goes for p5 gallus for the top left and 2 right sparkers)

Code: Select all

x = 64, y = 45, rule = LifeHistory
32D$D30.D$D30.D$D30.D31.E$D8.2E16.E3.D8.E20.3E$D7.E2.E13.3E3.D7.E.E18.
E$D2.E2.E2.E.E12.E6.D8.E19.2E$D2.5E.E.2E11.2E5.D9.2E.E4.E$D8.2E3.E16.
D11.E.E2.E.E5.E$D4.3E2.2E8.E10.D9.2E3.E.E2.E3.E.E$D3.E.E2.E.E3.E3.E.E
9.D11.E.2E.E5.E2.E$D3.E.2E2.2E6.E2.E9.D11.E.E.E2.E4.2E$D4.E3.2E3.E4.2E
10.D9.E.E.E.2E$D5.2E.E.2E18.D9.2E.E.E$D6.E.E.E19.D12.E.E$D5.E2.E.E11.
3D.D3.D12.2E11.3D.3D$D5.2E2.E12.D3.D3.D25.D5.D$D22.3D.D3.D25.3D.3D$D22.
D.D.D3.D27.D.D$D22.3D.D3.D25.3D.3D$D30.D$32D5$48.2A13.A$27.E19.A.A11.
3A$25.3E13.2A3.A13.A$10.2E12.E16.A.A.A.2A11.2A$8.3E.E11.2E17.A.A.A2.A
$7.E4.E30.A.2A.A7.A$8.3E.2E6.E20.2A3.A.A2.A3.A.A$10.2E3.E3.E.E21.A.A2.
A.A3.A2.A$12.E5.E2.E19.2A.A4.A5.2A$12.E6.2E19.A$9.3E3.E23.A.A$7.2E.E.
2E26.A$6.E3.E.E$5.E2.E.E.E$5.3E3.E12.3D.3D26.3D.D$8.3E13.D3.D28.D3.D$
7.E16.3D.3D26.3D.D$7.2E17.D.D.D28.D.D$24.3D.3D26.3D.D!

Lastly, p3 eaters

Code: Select all

x = 95, y = 39, rule = LifeHistory
3.3D3.4D12.3D3.4D11.3D3.D2.D3.F6.3D3.3D$6.D5.D15.D2.D17.D2.D2.D3.F9.D
5.D$6.D5.D15.D2.D17.D2.D2.D3.F9.D5.D$3.3D5.D13.3D3.3D12.3D3.4D3.F6.3D
3.3D$6.D4.D16.D5.D14.D5.D3.F9.D5.D$6.D3.D17.D5.D14.D5.D3.F9.D5.D$3.3D
4.D14.3D3.3D12.3D6.D3.F6.3D3.3D$59.F$59.F$59.F$4.D54.F$4.D2.E5.2E9.2E
.2E5.2E9.D.2E5.2E3.F4.D.2C5.2C9.4F2.4F$3.2E.E.E.EBEB.E9.E.E.E.E.E2.E8.
D.E.E.EBEB.E2.F4.D.C.C.CBCB.C11.F2.F2.F$3.2E.E.EBE2B.2E8.ED.E.E.E3.2E
8.D3.EBE2B.2E2.F4.D3.CBC2B.2C11.F2.F2.F$4.D.E.E2.B11.E.2E2.E15.D3.E2.
B6.F4.D3.C2.B12.4F2.4F$.6E.4E12.ED2.2E.E.E11.D4.3E6.F4.D4.3C15.F5.F$E
2.BD2.E.2B3.2F9.D4.E.E3.F8.D3.3B3.2F2.F4.D6.B3.F11.F5.F$2E2.D3E5.F11.
D2.E6.F9.D2.2E4.F4.F4.D2.4C4.F8.4F2.3F$4.DEB5.F10.F.D.B6.F10.D2.2B3.F
5.F4.D.C2.2B4.F$9D3F4D7.DF4D2E2DF3D7.2E2DE3DF4D2.F4.DCDC3DC3DF$4F4.F16.
F3.E3.F10.EDEBEB2.F6.F4.DC.C2.C.C2.F$4.4F17.F3.E3.F11.E3.E2.F6.F4.D.C
3.C.C2.F$25.F3.E3.F11.D3E3.F6.F4.D6.C3.F$44.EDE4.F7.F$44.2E13.F$59.F$
59.F$2.4F2.4F12.F3.F2.F13.4F2.4F4.F$5.F2.F2.F12.F3.F2.F16.F2.F2.F4.F24.
4F2.F3.F$5.F2.F2.F12.F3.F2.F16.F2.F2.F4.F4.D2.2A5.2A11.F2.F3.F$2.4F2.
4F12.5F2.F13.4F2.4F4.F4.D.A2.A.ABAB.A10.F2.F3.F$5.F5.F16.F2.F16.F2.F2.
F4.F4.D.2A.ABA2B.2A7.4F2.5F$5.F5.F16.F2.F16.F2.F2.F4.F4.D2.A.A2.B14.F
6.F$2.4F2.3F17.F2.F13.4F2.4F4.F4.D.BA.4A14.F6.F$59.F4.D3AB.2B3.2F7.4F
6.F$59.F4.DB2AB5.F$59.F3.BDA.A5.F$59.F2.3ADA3D4F3D$59.F3.BDB3.F!

(Moving discussion here)

It missed a couple chucklebaits which are reacting at gen 0.

Unrelated, but could lifelib be run to reduce gun populations in Catagolue?

Probably. If you provide me with a list of catalysts that can usually/sometimes be reduced, I can write a script that attempts to replace them using lifelib (ideally trying at five random points in the gun's evolution to account for reacting catalysts), and then automatically submits reduced guns to Catagolue. It should also attempt to remove components automatically to purge the last overdensified guns. I'll make a start on the latter function now.

(Moving discussion again)

One step ahead of you! Remember to orient guns so their gliders travel southeast

Oh, a few more for good measure (mostly syringe related)

Code: Select all

x = 88, y = 62, rule = LifeHistory
24.4D2.5D2.D2.D3.4D2.3D4.3D$24.D2.D4.D4.D2.D3.D5.D2.D2.D$24.D2.D4.D4.
4D3.D5.D2.D3.2D$24.D2.D4.D4.D2.D3.4D2.3D6.D$24.D2.D4.D4.D2.D3.D5.D2.D
5.D$24.4D4.D4.D2.D3.4D2.D2.D2.3D3$24.4D3.2D3.D2.D$24.D5.D2.D2.D2.D$24.
4D2.D2.D2.D2.D$24.D5.4D2.D2.D$24.D5.D2.D2.D2.D$24.D5.D2.D2.D2.3D2$32.
D$32.D$32.D$30.D.D.D$31.3D$20.3D9.D17.4D2.4D2.5D2.D2.D3.D3.2D3.D$20.D
.D27.D2.D2.D2.D4.D4.D2.2D.2D2.D2.D2.D$20.3D27.D2.D2.D2.D4.D4.D2.D.D.D
2.D2.D2.D$20.D5.2E3.E18.D2.D2.4D4.D4.D2.D.D.D2.4D2.D$20.D5.E3.E.E17.D
2.D2.D7.D4.D2.D3.D2.D2.D2.D$27.E3.E.E16.4D2.D7.D4.D2.D3.D2.D2.D2.3D$28.
E3.E.E.2E$20.2F4.E.4E2.E.2E$20.F.A3.2E3.E.E10.F6.D8.D$21.3F5.E.E.2E.2E
5.2F5.D9.D$22.AF2.3E.E3.E.E5.3F4.D10.D$26.E2.E4.E.E4.4F3.D11.D$27.2E6.
E4.4FD2.D9.D2.D2.D$44.D.D11.D.D.D$44.2D13.3D$45.5D$2.2D3.D18.2D3.D$2.
D3.D.D17.D2A.D.A23.2A3.A$3.D3.D.D17.A3.A.A22.A3.A.A$4.D3.D.D.2D14.A3.
A.A.2A19.A3.A.A$2.D.4D2.D.2D6.2F7.A4.A.2A20.A3.A.A.2A$.D.D3.D.D10.F.A
4.A.5A9.D6.2D4.A.4A2.A.2A$.D2.D2.D.2D.2D7.3F2.A.A4.A.2A.A.2A2D6.D.A2.
A.A3.A.A10.F$2D3.D.D2.D.D2.D6.AF3.A2.2A.A2.A.2A.A2D7.3D.A.A2.A2.2A.2A
5.2F$4.2D.2D5.2D9.D2.2A.A.2A5.4D8.AD2.A3.2A2.A.A5.3F$25.12D2.4D7.14BA
BAB3.4F$11.D38.15BA2B2.4F$10.3D$9.D.D.D6.D30.2D$11.D9.D28.D2.D$11.D10.
D2.D24.D2.D$11.D11.D.D24.4D$24.2D.2C3.C17.D2.D$22.4D.C3.C.C16.D2.D$13.
D2.D2.2A7.C3.C.C$13.2D.D.A2.A7.C3.C.C.2C$13.D.2D.A2.A5.C.4C2.C.2C$13.
D2.D.A2.A4.C.C3.C.C10.D$13.D2.D2.2A5.C2.C4.2C.2C5.2D$27.2C3.C2.C.C2.C
2.3D$26.6B2C5B2CB4D$26.19D!

Code: Select all

x = 34, y = 25, rule = LifeHistory
13.2C$13.C4.D$15.C3D$14.2C$15.2D$2A$.A$.A.2A$2.A2.A$3.2A$18.2A$18.2A4$
27.A3.2A$26.A.A3.A$25.A.A3.A$21.2A.A.A3.A$21.2A.A2.4A.A$25.A.A3.A.A$21.
2A.2A2.A2.A.A$22.A.A2.2A3.A$10.2A10.A.A$10.2A11.A!

Code: Select all

x = 34, y = 27, rule = LifeHistory
11.2E2.2C$11.E.E2.ED$13.EC.D$13.E2D2.D$15.C3D$14.CE$15.2D$2A$.A$.A.2A
$2.A2.A$3.2A$18.2A$18.2A4$27.A3.2A$26.A.A3.A$25.A.A3.A$21.2A.A.A3.A$21.
2A.A2.4A.A$25.A.A3.A.A$21.2A.2A2.A2.A.A$22.A.A2.2A3.A$10.2A10.A.A$10.
2A11.A!

EDIT: More

Code: Select all

x = 19, y = 19, rule = LifeHistory
15.A$13.3A$12.A$4.DA6.2A$4.A.A$5.A2$10.2A$10.2A5.2A$17.2A3$2A$2A2$15.
2A$15.A.A$17.A$17.2A!

Code: Select all

x = 22, y = 14, rule = LifeHistory
D6.2A$D5.A.A$D5.A7.2A$D6.4A3.A$D4.A.A3.A4.A$D3.A.A3.2A3.2A$DC2.A6.2A.
A2.2A$CDE.A7.A.A2.A$DE2.A12.2A.2A$D.D.A.2A3.2A.A2.A$3D2.A2.A.A.A.A2.2A
$D2.A.A2.2A.A3.2A$D2.2A6.A.2A2.4A$D10.2A.A2.A2.A!

Code: Select all

x = 20, y = 18, rule = LifeHistory
7D2A3D2A6D$7DA.ADA.A6D$9.A.A$4.2A2.A2.2A$3.A.A2.A.2A$2.A2.A.2A$3.3A3.
A$6.5A$5.A2.A2.A$5.2A$9.2A3$9.2A$2A6.A2.A6.2A$.A7.2A7.A$.A.A12.A.A$2.
2A12.2A!

EDIT: Here is a comparison of the two most optimal p3 domino sparkers for the x5 (some instances)/x6 multiplier. Left is 59 cells and has better clearance, right is 58 cells

Code: Select all

x = 34, y = 11, rule = LifeHistory
23.A4.A$2.2E3.E2.E11.A.A2.A.A$2.E2.6E11.A.4A.A$3.2E6.2E8.2A6.2A$3E2.E
.2E.E2.E6.A2.A.2A.A2.A$E2.2E2.2E2.2E.E4.A.2A2.2A2.2A.A$.E.E2.4E2.E.E4.
A.A2.4A2.A.A$2E.3E4.3E.2E2.2A.3A4.3A.2A$.E.E8.E.E4.A.A8.A.A$.E.E3.2E3.
E.E4.A.A3.2A3.A.A$2.E10.E6.A10.A!

[Sokwe]

Just some examples of the many reductions that could be made

If you provide me with a list of catalysts that can usually/sometimes be reduced, I can write a script that attempts to replace them using lifelib

For the stator parts of the gun, I think it makes more sense to run a stator optimizer script. Jeremy Dover wrote a Python script using the ortools package for this purpose, although the model was inefficient, so it took too long and used too much memory for high-period guns. I made a fork of the project (which I discuss a little more here) that simplifies the model, but breaks many of the features. However, it should fairly quickly minimize the stator of guns in the collection up to period 1000 (higher periods will probably still take too long). When run with only the input gun and the period it will minimize the stator while keeping the pattern within the original bounding box.

After cloning the repository (and installing the ortools Python package if you don't have it), here's how to use it to "efficiently" reduce a gun from the gun collection (if the period is less that ~50 just skip steps 2 and 3):

1. Copy the gun (in LifeHistory) and paste it into Golly
2. Select the whole pattern (ctrl+A) and run it until the glider fully leaves the initial bounding box (24 generations to deal with edge cases in the guns that still suffer from the bounding box glitch).
3. Use shift+delete to remove the cells outside of the initial bounding box.
4. Save the file in RLE format to the CGOL-Stator-Reducer folder
5. Run stator_reducer.py with just the name of the RLE file and the period. None of the other options should be used (including --gun, as it's broken).

The reason for running the pattern for 24 generations and deleting the glider and history cells outside of the initial bounding box is because this causes the pre-solver pattern evolution and analysis to run much faster. The pattern evolution code is inefficient and spends a lot of time expanding the bounding box as the first output gilder moves outward and subsequently analyzing all of the empty cells in the expanded bounding box. This should be rewritten as well (or rather, probably the whole program should be redone from scratch with the original as a guide), but I don't intend to do this.

As an example, I tried the above process with the current (over-densified) guntrue_660. Here is the input pattern after applying step 3:

Code: Select all

x = 46, y = 41, rule = LifeHistory
2A.2A.A4.2A10.A7.2A7.A3.2A$2A.A.4A.A.A9.A.A2.2A.A.A5.3A3.2A$9.2A5.2A
4.A.A2.2A.A6.A$7.A4.A2.A.3A3.A6.ABA4.2A5.2A$.A4.A.8A4.A6.2A4BAB.3B4.A
.A$A.A3.A9.3A.A6.A.BAB.4B6.2A$.A2.2A.8A2B2A.ABA5.B9A$5.A.A2.B2.A.B2.B
A2.BA5.6B3A$3.A2B.AB.A2BA2B2.2B2A2B7.2B3.B$2.B2AB2A2.A2BA4B.2BA3B4.3B
8.A.A$3.BA.AB4.A2.B2A2B2A4B.4B9.2A.A$14.BA.B4A8B2A11.A$15.2A.A2.A2B.
2B2AB2AB5.5A.2A$.A14.A.A.2A3.4BAB2A4.BA3.A.A$A.A13.A.A.A5.8B3.B3A2B.A
$.A3.A5.B2A3.A2.A6.8B3.3AB2.2A$4.A.A4.3AB3.2A5.10B3.BAB.2A$.A3.A4.A.
2AB9.10BA3B2.2A.A$A.A6.A.A.2B8.A9BABA2B3.A.A.A$.A7.A2.A2.2B5.BABA7BAB
AB4.A2.2A$10.2A3.3B3.2B2A2.7BAB4.2A$4.2A9.3B.5B5.6B$3.A.A8.9B4.5B12.B
$3.A8.B.8B5.2A7.B6.3A$2A.AB.B3.11B7.A6.3A6.B$.A.A.2AB.12B4.3A8.B4.B$.
A.A.2A14B4.A14.3A$2A.A2.5B2A8B12.2B6.B$A2.4A3BA2BA5B.B2A8.6B7.B$.2A2.
BAB.2B2A6B.BA.A5.10B4.3A$3.2A6.7B5.A3.A2B2A4B2A2BA3.B$3.A7.2B.4B5.2A.
A3B3A2B3A3BA$.2A2.A.A7.4B8.A2B2A4B2A2BA$A2.3A.3A6.4B9.10B$.2A3.A3.A6.
4B10.6B5.A$2.A2.A2.A2.A.2A3.4B11.2B6.BAB$A4.A.2A.2A.A5.4B7.A2B2.2BA4.
A$6A.A2.A2.A2.A3.4B4.BABA4BABAB$7.A2.A2.A.A.A3.5B.B3A6B3AB$2A2.A.A4.
2A2.A.A4.7BABA4BABAB4.2A$2A2.2A9.2A6.6B.AB4.BA6.2A!

I then ran

Code: Select all

python3 stator_reducer.py guntrue_660.rle 660

which gave the following pattern after about 14 seconds:

Code: Select all

x = 46, y = 41, rule = B3/S23
31b2o7bo5b$27b2obobo5b3o5b$16b2o9b2obo6bo8b$7bobo2bo2bob3o10bobo4b2o
7b$6bob2o2b4o4bo6b2o4bo12b$6bo9b3obo6bo2bo15b$4b2ob8o2b2obobo6b9o8b$
5bobo5bo5bo3bo11b3o8b$3bo3bo2bo2bo6b2o24b$3b2ob2o2bo2bo7bo18bobo3b$4b
obo5bo3b2o2b2o18b2obo2b$15bo2b4o8b2o11bo2b$15b2obo2bo5b2ob2o6b5ob2o$
16bobob2o7bob2o5bo3bobob$16bobobo17b3o3bob$12b2o3bo2bo17b3o3b2o$11b3o
4b2o19bo2b2o2b$10bob2o20bo5b2obo2b$9bobo11bo9bobo5bobobo$9bo2bo10bobo
7bobo5bo2b2o$10b2o11b2o9bo5b2o4b$4b2o40b$3bobo40b$3bo23b2o14b3o$2obo
24bo6b3o8b$bobob2o18b3o18b$bobob2o18bo14b3o3b$2obo7b2o33b$o2b4o3bo2bo
7b2o23b$b2o3bo4b2o8bobo19b3o$3b2o18bo3bo2b2o4b2o2bo5b$3bo19b2obo3b3o
2b3o3bo4b$5bo21bo2b2o4b2o2bo5b$4b2o40b$42bo3b$42bo3b$30bo6bo4bo3b$29b
obo4bobo7b$28b3o6b3o6b$29bobo4bobo7b$30bo6bo8b!

Since it's a stator reducer, it obviously couldn't remove the unnecessary blinkers, so those would need to be removed by some other method. The optimizer also doesn't care about consistent use of equivalently-sized stator variants for patterns, so if someone cares about that sort of thing, they will need to run some post-processing to replace catalyst variants with a preferred standard form.

Obviously, the above steps can be automated to run through all of the guns up to period 1000, if someone has a mind to do that.

As a further test, I ran it on some difficult cases, which took the following times to complete:

• gun_31: 3m 43s
• guntrue_991: 1m 30s
• guntrue_4337: 16m 10s

guntrue_991 was already optimal, but gun_31 and guntrue_4337 were slightly reduced, with guntrue_4337 actually having a smaller bounding box, although this is only due to the lucky accident that the minimal stator population results in a smaller bounding box, and not some feature of the program.

gun_31:

Code: Select all

x = 147, y = 99, rule = B3/S23
55b2o$55bobo56b2o$57bo4b2o50bobo$53b4ob2o2bo2bo50bo4b2o$53bo2bobobobob
2o46b4ob2o2bo2bo$56bobobobo49bo2bobobobob2o$57b2obobo52bobobobo$61bo
54b2obobo16bo$120bo16bobo$47b2o$48bo7b2o10bo37b2o29bo2bo$48bobo5b2o10b
3o36bo7b2o21bobobob2o$49b2o20bo35bobo5b2o11bo10bo3b2obo$70bobo35b2o18b
3o10bo4bo$70bobo58bo10b4o$71bo58bobo11bo$130bobo8bo2bo$131bo10b3o$68bo
75b2o$59b2o5bobo76bo$59bo7b2o17b2o30b2o24bobo$60b3o23b2o30bo25b2o$62bo
56b3o$34b2o71b3o11bo7bobo$34bo2bo9bo61bo20b2o$35b5o6b2o6b2o10b2o40bo
21bo$40bo4bo2bo5bo10bobo$37b3o5bo6bobo10bo60b2o$36bo6b2o2b2o3b2o10b2o
59bobo$36b4o2bo4b2o25bo50bo$34b2o3bob3o2bobo23b2ob2o7b2o38b2o7b2o$33bo
2b3o3bo4b2o32b2o2bo3b2o42b2o10b2o$33b2obo6b2o3bo22bobo7b2obo4b2o55bo$
36bo8bo2b3o20bo3bo8bobo54b2obo$36b2o7bobobo21b2o2bo5b2obob5o14b2o34b2o
b2o$46b3o23b3o5bo2bobo5bo13bo$39bobo3b3o25bo5bobobobo2b3o12bobo35b2ob
2o$31b2o5bob2o2b2o15bo16bobobo2bobo15b2o27bob2o4bo2b2o$31bobo4bo6bo15b
3o15bo2bobo2b4o40b5o3bobo4bo$33bo2b2ob6o19bo17bobobo3bo3b2o35b4o3bobob
2ob2o$32b2obobobo2bo20b2o16b2o2bob3o4b2o25b2o16bo2bo$33bobobobo38bobo
2bobobo34bo9b3o7bo$33bobob2o39b2o2bobo2bo34bobo7b3o6b2obo$34bo48bo3b2o
34b2o8bo4bobo2bobo$138b2o2bo2bo$47b2o36bo19b2o36b2o$37b3o7bo35b3o9b2o
7b2o$36bo3bo4bobo34bo13bo9bo$35bo5bo3b2o18b3o14b2o9b3o$34bo3bo3bo10bo
11bo27bo$34bo2bobo2bo10b3o10bo$34bo3bo3bo13bo$35bo5bo13bo$40bo14b2o26b
o$35bo3bo13b2o2bo23bobo$35bo16bo2b3o24b2o40b2o$36bo16bo23bo46b2o14b2o$
33b3o18b4o6b2o3b2o5bobo61bo$9bo23bo22bo7b2o3b2o6bo63b3o$9b3o46bo84bo$
12bo44b2o$11b2o3$3b2o120bo2bo$3bo119b4o9b2o$2obo9b3o66bo46bo6bo$o2b3o
7b3o64b3o40b2o2b2o5bobo$b2o3bo5bo3bo62bo54b2o$3b4o6b2obo40b2o20b2o46b
2o$3bo9b3o3b2o35b2o19b3o48b2o$4b3o12bobo36bo17bobo10b2o33bo2b2o9bo$7bo
13bo54bo2bo9bobo2b2o41bobo$2b5o14b2o16bo37b2o7bo4bo3bo41bobo$2bo36b3o
36b2o6b5ob3o41b2ob2o$4bo37bo30bo4b2o10bobo$3b2o24bo11b2o30bo3bo8b3obob
o12bo30b2ob2o$27b3o15bo8b2o17bobo3bo5bo2bob2o14b2o28b2obo2bo$26bo21bo
28bobo5b2o18b2o28b2o4b2o$26b2o20b3obob2o78b2o7b2o$11b2o31bo3b5ob2o19bo
3bo43b2o9b2o7bo$12bo32bo4b2o4bo19bo2bo42bobo16bobo$12bob2o37bobo21bo
44bo18b2o$13bo2bo33b2obo25bob2o38b2o$15bo35b3o29bo30bo$15bobo5b2o27bo
30bo23b2o3bobo$17bo2b6o40b2o13b3o18b2o3bo5b2o$17bobo2bo44bo34bobo3b3o$
19bo2bo2b2obo35b3o33bobob4o2bo$19b2o2b2o4bo9bo24bo35b2o5bo$6b3obo8b3ob
2o3bo9bo3b2o62bo$9bobo12bob2o9bo5bo39b2o21b2o22b2o$10b2o24bob2o2bo12b
2o27bo44b3obo$9b3o9bo2bo7b2obobo3bo13bobo23b3o44bo4bo$11bob4o4b3o8b2ob
o2b4obo13bo23bo45b2o$11bobo6b3o13bobo3bobo12b2o58b2o9b3o5b2o$10b2obobo
3b2o11b2ob2o4bo2bo71bobo10b2o5bobo$10bo2bobobo2bo9bo2bobo2bo3b2o72bo
21bo$11b2o5b2o10b2o5b2o76b2o21b2o!

guntrue_4337:

Code: Select all

x = 136, y = 133, rule = B3/S23
136b$136b$82b2obo50b$82bob4o48b$88bo47b$83b2o2bobo46b$83bo3b2o47b$84b
o51b$81b3o52b$81bo54b$62b2o5b2o65b$62bobo4b2o65b$63b2o71b$59b2o75b$
58bobo75b$58bo77b$57b2o77b$85b2o49b$84bo2bo48b$84bo2bo48b$63bo21b2o
12b2obo33b$60bobobo34b2ob3o31b$60b2obo41bo30b$22b2o11bo27bobo2bo30b2o
b3o31b$22b2o10bobo26bob4o31bobo33b$34bobo2b2o3bo19bo29b2o4bo35b$33b2o
b2o2bo2bobo20bo26bo2bo2b2o35b$37bobo3bobo19b2o26bobo4bob2o32b$33b2obo
2b4obo49bo5bob2o32b$33b2obobo3bo54b2obo35b$37bobo3bo15b2o36bo2bo35b$
38bobo3bo14bo34bo4bo36b$39bo3b2o12bobo34b5o37b$53b2o2b2o77b$53b2o41bo
39b$95bobo38b$30b2o8b2o2bobo49bo39b$30b2o10b2o2bo31b2o56b$15b2o22bo2b
2o2bo31b2o56b$14bo2bo21bobo2b2o90b$13bob2o119b$13bo65b2o55b$12b2o64bo
2bo54b$78bobo55b$26b2o48bobobobo53b$27bo47bobobobobo52b$26bo14b2o33bo
2bo2bo53b$26b2o12bobo34b2ob2o54b$b2o37bo37bobo55b$bo2bo34b2o37bobo55b
$2b5o14b2o56bo56b$7bo13bo24b2o88b$4b3o12bobo23bobo88b$3bo15b2o24bo90b
$3b4o35b2obo7b2o81b$b2o3bo3b2o25b2o3bobo8b2o81b$o2b3o4b2o16bo3b2o3bo
2bobo93b$2obo22b3o2bo2bo4b2ob2o92b$3bo21bo5bobo3bobo86bo9b$3b2o20b2o
5bob4o2bob2o80b3o9b$34bo3bobob2o79bo12b$33bo3bobo83b2o11b$11b2o19bo3b
obo97b$12bo19b2o3bo98b$9b3o119b2o3b$9bo122bo3b$132bob2o$45b2o77b2o4b
3o2bo$45b2o77b2o3bo3b2ob$60b2o67b4o3b$59bo2bo52b2o15bo3b$60b2obo50bob
o12b3o4b$13b2o48bo50bo13bo7b$13b2o48b2o48b2o14b5o2b$131bo2bob$49b2o
82b2ob$49bo86b$50bo85b$49b2o85b$136b$136b$136b$136b$136b$136b$136b$
136b$116b2o18b$117bo18b$116bo5b2o12b$116b2o5bo12b$123bob2o9b$116b2o2b
2obo2bo9b$116b2o3bob2o11b$121bo14b$120b2o14b$115bo20b$114bobo9b2o8b$
115bo11bo8b$127bob2o5b$119b2o4b3o2bo5b$119b2o3bo3b2o6b$124b4o8b$110b
2o15bo8b$109bobo12b3o9b$109bo13bo12b$108b2o14b5o7b$75bo50bo2bo6b$75b
3o50b2o6b$78bo57b$77b2o21bo35b$100b3o33b$103bo32b$102b2o32b$136b$136b
$109bo26b$87b2o19bobo25b$80b2o5bobo19bo3b2ob2o18b$80b2o7bo23b2obo2bo
16b$89b2o27b2o16b$105b2o29b$76bo28b2o4bo2bo21b$75bobob2o30b4o21b$75bo
bobobo35bo18b$74b2obobobo2bo16bo11b5o18b$75bo2b2ob4o15bobob2o7bo22b$
73bobo4bo19bobobobo8bo20b$73b2o5bobo16b2obobobo2bo4b2o20b$81b2o17bo2b
2ob4o26b$98bobo4bo30b$98b2o5bobo28b$106b2o28b!

[WhiteHawk]

As an example, I tried the above process with the current (over-densified) guntrue_660. Here is the input pattern after applying step 3:

Code: Select all

I then ran

Code: Select all

python3 stator_reducer.py guntrue_660.rle 660

which gave the following pattern after about 14 seconds:

Code: Select all

Note again that the bounding box for guntrue_660 is broken, so any update won't be submitted regardless

EDIT: gun_31 is also has a miscalculated BB. This is therefore a minimum population variant

Code: Select all

x = 147, y = 100, rule = B3/S23
55b2o$55bobo56b2o$57bo4b2o50bobo$53b4ob2o2bo2bo50bo4b2o$53bo2bobobobo
b2o46b4ob2o2bo2bo$56bobobobo49bo2bobobobob2o$57b2obobo52bobobobo$61bo
54b2obobo$120bo16b3o$47b2o89b2o$48bo7b2o10bo37b2o30b2obo$48bobo5b2o10b
3o36bo7b2o21bo5b2o$49b2o20bo35bobo5b2o11bo10bo2b3obo$70bobo35b2o18b3o
9bo5bo$70bobo58bo10b4o$71bo58bobo8b2o$130bobo8b2o$113b2o16bo11b3o$114b
2o$59b2o52bo32bo$50b3o6bo26b2o30b2o24bobo$52bo7b3o23b2o30bo25b2o$51bo
10bo56b3o$34b2o85bo11b3o$34bo2bo34bobo58b3o$35b5o14b2o10b2o5b2o57bo3b
o$40bo13bo10bobo5bo49b2obo5b2ob2o$37b3o12bobo10bo57bob2o$36bo15b2o10b
2o7b2o$36b4o33b2o69b2o$34b2o3bo3b2o39b2o58bo$33bo2b3o4b2o36b2o2bo3b2o
54bo$33b2obo44b2obo4b2o53b2o$36bo47bobo54b2o$36b2o43b2obob5o14b2o34b2o
b2o$80bo2bobo5bo13bo38bo$39bobo37bobobobo2b3o12bobo35b2o3bo$38bob2o2b
2o15bo10bo5bobobo2bobo15b2o35bo2b4o$32b2o4bo6bo15b3o7b3o5bo2bobo2b4o48b
obobo$30bo2bo2b2ob6o19bo9bo7bobobo3bo3b2o3b2o39bo2bob2o$30b2obobobobo
2bo20b2o6b2ob2o5b2o2bob3o4b2o3bobo19b2o8bo11bobo$33bobobobo30b2ob2o3b
obo2bobobo11bo22bo8bo10b2o2bo$33bobob2o21b2o8b2ob2o3b2o2bobo2bo34bobo
7bo6bobo2bobo$34bo24b2o10bo2bo8bo3b2o34b2o5b2o7b2o2bobo$61bo10b3o53b4o
12bo$47b2o23b2o11bo41bo2bo$38b2o7bo35b3o9b2o30bo2bo$38b2o5bobo34bo13b
o31b3o$45b2o35b2o9b3o$53bo39bo$53b3o$56bo$30bo24bo$28b2o25b2o$29b2o22b
2o2bo$35b2o15bo2b3o66b2o$36bo16bo23bo46b2o14b2o$33b3o18b4o6b2o3b2o5bo
bo61bo$9bo23bo22bo7b2o3b2o6bo63b3o$9b3o46bo28bobo53bo$12bo44b2o29b2o$
11b2o75bo$123bo$51b2o69b2o$3b2o46bobo68bobo$3bo47bo84b2o$2obo78bo53bo
$o2b3o4b2o68b3o51bobo$b2o3bo3b2o67bo54b2o$3b4o72b2o50bo$3bo15b2o110b2o
$4b3o12bobo67b2o41bo5bo$7bo13bo67bobo2b2o41bobo$2b5o14b2o16bo46bo4bo3b
o32bobo6bobo$2bo13bo22b3o14bo29b5ob3o34b2o5b2ob3o$4bo12bo7b2o15bo13bo
2b2o29bobo36bo12bo$3b2o10b3o7bo15b2o12bo5bo24b3obobo43b2ob3o$26bo29bo
bo2b2o22bo2bob2o35bo8b2obo$25b2o29bo3b2o23b2o40b2ob2o$58b3o67b3o12b2o
$11b2o110b2o4bo13bo$12bo109bobo16bobo$12bob2o96bo9bo18b2o$13bo2bo73b2o
18bobo8b2o$14b2o73b2ob2o17b2o$30bo48b2o8b2ob2o13b2o$29b3o34b2o11b2o10b
3o8b2o3bo$28bobo36bo34bobo3b3o$25b2o25b3o9b3o33bobob4o2bo$27bo24b3o9b
o35b2o5bo$38bo3b2o8bo53bo11bobo$37bobo3bo39b2o21b2o11b2o11bo$36bobo3b
o12b2o27bo34bo11bobo$32b2obobo3bo13bobo23b3o47bobo$32b2obo2b4obo13bo23b
o50bo$36bobo3bobo12b2o58b2o17b2o$32b2ob2o2bo2bobo71bobo17bobo$33bobo2b
2o3bo72bo10bo10bo$21b2o10bobo79b2o11bo9b2o$21b2o11bo91b3o!

As a further test, I ran it on some difficult cases, which took the following times to complete:

• gun_31: 3m 43s
• guntrue_991: 1m 30s
• guntrue_4337: 16m 10s

It's pretty customary to use the following version of the Snark in most gun designs it seems (same population as the other one, though), so using it will probably be IMO a more consistent choice

Code: Select all

x = 13, y = 8, rule = B3/S23
2b2o$2bobo$4bo4b2o$4ob2o2bo2bo$o2bobobobob2o$3bobobobo$4b2obobo$8bo!

Same with this high-clearance syringe catalyst variant

Code: Select all

x = 16, y = 8, rule = B3/S23
9bo3b2o$8bobo3bo$4b2obobo3bo$4b2obo4bo$8b5obo$2obob2obo4bobo$ob2obo2b
ob2o2bo$7b2obob2o!

[Sokwe]

Jeremy Dover wrote a Python script using the ortools package for [stator reduction]... I made a fork of the project that simplifies the model

I've written a new OR-Tools-based stator optimizer which is quite a bit faster at analyzing the pattern and setting up the search. It currently lacks any useful features, but it can now minimize the guns from catagolue without needing to remove the initial glider. Just save the LifeHistory pattern from Catagolue to the same folder as the script (e.g., as guntrue_660.rle) and run with

Code: Select all

./stator_optimizer.py guntrue_660.rle 660

Where the 660 at the end is the period of the gun. It will either output a gun with a smaller stator (in the same bounding box), or it will tell you that the stator is already optimal (for that bounding box).

I tried it on what seemed likely to be the worst-case scenario in the Catagolue collection, guntrue_9281, and it finished with the following time:

Setup time: 25s
Solver real (wall-clock) time: 2m 55s
Solver CPU time: 10m 2s
Total real time: 3m 20s

It found a slightly smaller weld between a syringe catalyst and an eater:

Code: Select all

x = 145, y = 123, rule = B3/S23
79b2o$79bobo$81bo4b2o$77b4ob2o2bo2bo$77bo2bobobobob2o$80bobobobo$81b2o
bobo$85bo2$71b2o$72bo7b2o28bo$72bobo5b2o27bobo$73b2o34bobo$108b2ob3o$
96b2o11bo4bo$96b2o10bo2b3o$22b2o11bo61bo5b3o2bo2bo$22b2o10bobo66bobo$
34bobo2b2o3bo52b3o2bo$33b2ob2o2bo2bobo37b2o10b5o3bobo$37bobo3bobo37bo
12bob2o3b2o$33b2obo2b4obo39b3o9bo2bo$33b2obobo3bo43bo15b3o$37bobo3bo
15b2o29bo5b3o2bo3bo5b2o$38bobo3bo14bo30bo10bo3bo5b2o$39bo3b2o12bobo41b
o2bo$53b2o2b2o43bo$53b2o46bobo$33b2o50b2o$32b2ob2o47bobo7bo$33bo2bo41b
2o4bo4bo4bobo12b2o$15b2o16bo2bo41b2o3b2o4bo2bo3bo12b2o$14bo2bo16b2o53b
o5bo$13bob2o73bo3bo10bo$13bo65b2o10b3o9b2o$12b2o64bo2bo$78bobo19b2o$
26b2o48bobobobo17b2o$27bo47bobobobobo$25bo15b2o33bo2bo2bo$3b2o20b2o13b
obo34b2ob2o$4bo35bo37bobo$2bo36b2o37bobo$2b5o14b2o56bo$7bo13bo24b2o$4b
3o12bobo23bobo$3bo15b2o24bo$3b4o35b2obo7b2o$b2o3bo3b2o25b2o2bo2bo8b2o$
o2b3o4b2o16bo3b2o3bo2bobo$2obo22b3o2bo2bo4b2ob2o$3bo21bo5bobo3bobo$3b
2o20b2o5bob4o2bob2o$34bo3bobob2o$33bo3bobo$11b2o19bo3bobo$12bo19b2o3bo
$9b3o$9bo119b2o$130bo$45b2o81bo5b2o$45b2o81b2o5bo$60b2o73bob2o$59bo2bo
65b2o2b2obo2bo$60b2obo64b2o3bob2o$13b2o48bo69bo$13b2o48b2o67b2o$127bo
11b2o$32b2o15b2o75bobo10bobo$32b2o15bo56bo20bo13bo$51bo52b3o34bob2o$
50b2o51bo34b2obobo$103b2o33b2obobo$132b2o7bob2o$122b2o7bo2bo3b4o2bo$
111b2o8bobo8b2o4bo3b2o$112bo8bo18b2o$112bob2o4b2o19bo$104b2o4b3o2bo23b
o$104b2o3bo3b2o24b2o$109b4o$95b2o15bo$94bobo12b3o$94bo13bo$93b2o14b5o$
100bo12bo$98b2o11bo$99b2o10b2o11$95bo$74bo20b3o$74b3o21bo$77bo19b2o$
76b2o6$107b2o$86b2o10bo8bobo$79b2o5bobo8bobo9bo$79b2o7bo8bobo9b2o$88b
2o8bo2$75bo$74bobob2o$74bobobobo16b2ob2o$71b2obobobobo2bo9b2o3bob2o2b
2o$71bo2bo2b2ob4o9bo2bobo6bo$73b2o4bo15b2ob7o$63bo15bobo15bo$64bo15b2o
15bob4o$62b3o33b2o2bo!

I ran it on some difficult cases, which took the following times to complete:

• gun_31: 3m 43s
• guntrue_991: 1m 30s
• guntrue_4337: 16m 10s

I ran these again for comparison with the previous version. Here are the total wall-clock times:

• gun_31: 2m 23s
• guntrue_991: 32s
• guntrue_4337: 3m 20s (same as guntrue_9281)

If someone wants to, I'm sure they could easily adapt the code to run through all of the current guns up to period 1000 in Catagolue. I don't intend to do this myself. As before, the optimizer doesn't care about using consistent versions of catalysts, so if we care about that, these optimized guns would need some sort of post-processing to ensure the preferred catalyst variants are used.

It's pretty customary to use the following version of the Snark in most gun designs it seems (same population as the other one, though), so using it will probably be IMO a more consistent choice

Code: Select all

x = 13, y = 8, rule = B3/S23
2b2o$2bobo$4bo4b2o$4ob2o2bo2bo$o2bobobobob2o$3bobobobo$4b2obobo$8bo!

Is there any reason for this? That's the original variant, and I think the one that's easiest to synthesize, but aesthetically I prefer the other one. What criteria, if any, should be used to pick the "standard" catalysts. I'm willing to just let whoever wants to put in the work to minimize everything choose what they want to use.

Note again that the bounding box for guntrue_660 is broken

I'm well aware. I was the one who submitted the (correct) p660 gun, but someone took advantage of the bounding box glitch to overdensify it, which I thought wasn't very classy.

p660 (the tub is there on purpose; don't delete it):

[WhiteHawk]

It's pretty customary to use the following version of the Snark in most gun designs it seems (same population as the other one, though), so using it will probably be IMO a more consistent choice

Code: Select all

Is there any reason for this? That's the original variant, and I think the one that's easiest to synthesize, but aesthetically I prefer the other one. What criteria, if any, should be used to pick the "standard" catalysts. I'm willing to just let whoever wants to put in the work to minimize everything choose what they want to use.

It's mostly a tradition reason I say that this variant should be used, which means that it is involved in most guns already.

Maybe randomizing which variant is used would be a better idea and show that they're interchangeable in terms of minipop?

[Sokwe]

I've written a new OR-Tools-based stator optimizer which is quite a bit faster at analyzing the pattern and setting up the search....

If someone wants to, I'm sure they could easily adapt the code to run through all of the current guns up to period 1000 in Catagolue.

I fixed a bug that would cause misalignment of the search box if there were rotor cells that went beyond the stator bounding box at the top or left of the pattern. If anyone has already started this project, they should update to the latest version.

Edit (Feb. 24, 2026): I noticed that a recent shinjuki job added a lot of gun improvements. Has somebody finally run an automated reduction on the whole gun collection? If so, I'm curious to know what method they used.

[WhiteHawk]

I've written a new OR-Tools-based stator optimizer which is quite a bit faster at analyzing the pattern and setting up the search....

If someone wants to, I'm sure they could easily adapt the code to run through all of the current guns up to period 1000 in Catagolue.

I fixed a bug that would cause misalignment of the search box if there were rotor cells that went beyond the stator bounding box at the top or left of the pattern. If anyone has already started this project, they should update to the latest version.

Edit (Feb. 24, 2026): I noticed that a recent shinjuki job added a lot of gun improvements. Has somebody finally run an automated reduction on the whole gun collection? If so, I'm curious to know what method they used.

I don't know, but there are still a lot of guns that are overdensified (including some of those below).

Historical note so that future readers will be able to know what people in 2025 were talking about: here are the six mentioned glider guns as they currently appear on Catagolue. Looks like an exercise in pointless densification:

Code: Select all

Someone did the same thing with guntrue_9760, a gun I revealed yesterday.

EDIT: Same with Guntrue_285

Found more today with guntrue_3457, guntrue_3449, guntrue_3433, guntrue_3271, guntrue_3607, guntrue_3719, guntrue_3943, guntrue_3947, guntrue_4111, guntrue_4951, guntrue_3391, guntrue_3343, guntrue_3511, guntrue_3623, guntrue_3847, guntrue_4127, guntrue_3407, guntrue_3463, guntrue_3631, guntrue_3911, guntrue_3967, guntrue_4079, guntrue_3359, guntrue_3527, guntrue_3583, guntrue_3863, guntrue_3919, guntrue_3319, guntrue_3767, guntrue_3823, guntrue_4271, guntrue_4327.

I got this list by checking all the primes mentioned in the three most recent posts on the "Small Four-Digit Prime Period Guns" thread.

[WhiteHawk]

Uploaded a bunch of new fixes to some of the increasingly few overdensified Bounding Boxes. Is there a way to check which glider gun periods still need fixes?

[dvgrn]

EDIT: See also the next post on the next page.

Uploaded a bunch of new fixes to some of the increasingly few overdensified Bounding Boxes. Is there a way to check which glider gun periods still need fixes?

I had Copilot write a bounding-box density surveyor -- currently it's set up to scan just the "guntrue" guns, but a quick search-and-replace would make it work for the regular "gun" collection instead.

Code: Select all

# gun-density-calculator.py
#
# Downloads current guntrue entries from Catagolue and calculates pattern bounding box densities

import golly as g

import csv
import re
import requests
from io import StringIO

CENSUS_URL = "https://catagolue.hatsya.com/textcensus/b3s23/synthesis-costs/guntrue"
OBJECT_URL = "https://catagolue.hatsya.com/object/{}/b3s23"
OUTPUT_PATH = "C:/REPLACE/WITH/YOUR/PATH/gun_densities.csv"

# Regexes for parsing
RE_BBOX = re.compile(r"bbox\s+(\d+)\s+by\s+(\d+)")
RE_POP = re.compile(r"([0-9]+)A")  # count literal A's in RLE lines

def fetch_text_census():
    r = requests.get(CENSUS_URL, timeout=20)
    r.raise_for_status()
    return list(csv.DictReader(StringIO(r.text)))

def fetch_rle(apgcode):
    url = OBJECT_URL.format(apgcode)
    r = requests.get(url, timeout=20)
    r.raise_for_status()
    text = r.text

    # Extract the LifeHistory RLE block
    # It is inside <code id="code2"> ... </code>
    m = re.search(r'<code id="code2">(.*?)</code>', text, re.S)
    if not m:
        return None
    return m.group(1)

def parse_bbox(rle_block):
    """Extract bounding box from the #C period line."""
    for line in rle_block.splitlines():
        if "bbox" in line:
            m = RE_BBOX.search(line)
            if m:
                return int(m.group(1)), int(m.group(2))
    return None, None

def count_population(rle_block):
    """Count state-1 cells (A) in the RLE."""
    pop = 0
    for line in rle_block.splitlines():
        if line.startswith("#") or line.startswith("x ="):
            continue
        # Count occurrences of A, including run-length encoded forms
        # e.g. "12A" ? 12
        parts = re.findall(r"(\d*)A", line)
        for p in parts:
            pop += int(p) if p else 1
    return pop

census = fetch_text_census()
results = []

count = len(census)
for row in census:
    count  -= 1
    apgcode = row["apgcode"]
    g.show(f"{count}: Processing {apgcode}...")


    rle = fetch_rle(apgcode)
    if not rle:
        g.note(f"  No RLE found for {apgcode}")
        continue

    bbox_x, bbox_y = parse_bbox(rle)
    if not bbox_x or not bbox_y:
        g.note(f"  No bbox found for {apgcode}")
        continue

    pop = count_population(rle)
    density = pop / (bbox_x * bbox_y)

    results.append({
        "apgcode": apgcode,
        "bbox_x": bbox_x,
        "bbox_y": bbox_y,
        "population": pop,
        "density": density
    })

# Sort by density descending
results.sort(key=lambda r: r["density"], reverse=True)

# Write CSV
with open(OUTPUT_PATH, "w", newline="") as f:
    writer = csv.DictWriter(
        f,
        fieldnames=["apgcode", "bbox_x", "bbox_y", "population", "density"]
    )
    writer.writeheader()
    writer.writerows(results)

g.show("Done. Results written to gun_densities.csv")

It seemed to work very nicely once I installed the requests library with "pip install requests", and turned it into a Golly Python script (just because I always do that, and because maybe Version 2 of the script could do a bunch more processing on each gun pattern, to look for isolated islands that are completely unconnected to the output glider stream, instead of relying on a rough density measure).

It takes about fifteen minutes to complete the survey -- pulls quite a lot of data from Catagolue, so maybe don't run it too often. Here is the sorted output:

Code: Select all

apgcode,bbox_x,bbox_y,population,density
guntrue_18,68,50,854,0.2511764705882353
guntrue_35,61,40,574,0.23524590163934425
guntrue_20,44,27,271,0.2281144781144781
guntrue_100,39,32,273,0.21875
guntrue_114,47,44,444,0.21470019342359767
guntrue_228,47,44,442,0.2137330754352031
guntrue_200,39,33,271,0.21056721056721056
guntrue_60,23,25,120,0.20869565217391303
guntrue_81,68,46,646,0.20652173913043478
guntrue_171,47,44,420,0.20309477756286268
guntrue_27,48,33,317,0.20012626262626262
guntrue_300,40,34,269,0.19779411764705881
guntrue_28,31,23,140,0.19635343618513323
guntrue_40,27,19,99,0.19298245614035087
guntrue_770,70,44,587,0.19058441558441558
guntrue_600,40,40,296,0.185
guntrue_24,20,20,74,0.185
guntrue_56,31,29,166,0.1846496106785317
guntrue_25,22,22,88,0.18181818181818182
guntrue_54,37,17,113,0.17965023847376788
guntrue_14,72,60,776,0.17962962962962964
guntrue_400,46,39,322,0.1794871794871795
guntrue_1368,59,47,495,0.17850703209520374
guntrue_36,31,32,177,0.17842741935483872
guntrue_55,29,31,160,0.17797552836484984
guntrue_110,41,29,208,0.17493692178301093
guntrue_456,50,47,410,0.17446808510638298
guntrue_342,59,47,480,0.1730977280923188
guntrue_684,59,47,479,0.17273710782545978
guntrue_120,23,32,126,0.17119565217391305
guntrue_52,33,26,146,0.17016317016317017
guntrue_1000,52,39,345,0.17011834319526628
guntrue_513,59,47,470,0.1694915254237288
guntrue_500,52,39,343,0.16913214990138067
guntrue_57,47,40,316,0.16808510638297872
guntrue_900,52,39,338,0.16666666666666666
guntrue_50,36,22,132,0.16666666666666666
guntrue_30,36,9,54,0.16666666666666666
guntrue_1800,55,39,354,0.16503496503496504
guntrue_70,24,30,118,0.1638888888888889
guntrue_360,40,23,150,0.16304347826086957
guntrue_2280,63,47,480,0.16210739614994935
guntrue_1200,48,41,318,0.16158536585365854
guntrue_275,51,43,352,0.16051071591427268
guntrue_15,32,31,159,0.16028225806451613
guntrue_912,61,47,458,0.15974886641088246
guntrue_243,68,65,705,0.1595022624434389
guntrue_1728,56,37,330,0.15926640926640925
guntrue_182,44,42,294,0.1590909090909091
guntrue_63,34,30,161,0.15784313725490196
guntrue_68,39,33,203,0.15773115773115773
guntrue_1140,63,47,464,0.15670381627828436
guntrue_432,48,33,248,0.15656565656565657
guntrue_2736,68,48,511,0.1565563725490196
guntrue_216,33,37,191,0.15642915642915642
guntrue_2000,67,42,440,0.15636105188343993
guntrue_112,35,35,189,0.15428571428571428
guntrue_972,53,40,326,0.15377358490566037
guntrue_162,35,40,214,0.15285714285714286
guntrue_440,36,40,220,0.1527777777777778
guntrue_1026,63,47,452,0.15265113137453562
guntrue_4000,67,44,449,0.1523066485753053
guntrue_616,80,32,389,0.151953125
guntrue_250,54,41,336,0.15176151761517614
guntrue_1250,55,63,522,0.15064935064935064
guntrue_1944,57,40,342,0.15
guntrue_140,43,30,193,0.1496124031007752
guntrue_224,46,35,240,0.14906832298136646
guntrue_324,50,34,253,0.14882352941176472
guntrue_160,49,25,182,0.14857142857142858
guntrue_5000,59,52,455,0.1483050847457627
guntrue_16,36,24,128,0.14814814814814814
guntrue_3200,44,64,417,0.14808238636363635
guntrue_2400,53,47,368,0.14773183460457648
guntrue_21,36,27,143,0.147119341563786
guntrue_364,45,42,278,0.14708994708994708
guntrue_8000,64,52,488,0.1466346153846154
guntrue_750,51,43,321,0.146374829001368
guntrue_729,79,67,769,0.14528622709238617
guntrue_350,52,42,317,0.14514652014652016
guntrue_550,57,43,355,0.1448388412892697
guntrue_6400,46,66,437,0.14393939393939395
guntrue_165,46,29,192,0.14392803598200898
guntrue_48,31,16,71,0.1431451612903226
guntrue_2311,128,107,1959,0.14303446261682243
guntrue_7883,124,104,1844,0.14299007444168735
guntrue_2912,57,45,366,0.14269005847953217
guntrue_6561,88,68,853,0.14254679144385027
guntrue_234,56,34,271,0.14233193277310924
guntrue_3389,130,111,2053,0.14227304227304227
guntrue_3301,127,108,1950,0.14216972878390202
guntrue_8011,126,105,1878,0.1419501133786848
guntrue_2399,131,110,2043,0.1417765440666204
guntrue_108,37,33,173,0.1416871416871417
guntrue_2351,129,108,1973,0.14161642262417456
guntrue_2187,88,68,846,0.1413770053475936
guntrue_117,42,29,172,0.1412151067323481
guntrue_2203,124,104,1821,0.14120657568238212
guntrue_6079,126,105,1866,0.14104308390022677
guntrue_4133,123,107,1855,0.14094673657016943
guntrue_6779,135,114,2168,0.14087069525666016
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guntrue_1961,130,91,412,0.03482671174978867
guntrue_2012,118,83,341,0.03481723504186236
guntrue_4273,134,131,611,0.03480688162242224
guntrue_1004,80,78,217,0.03477564102564103
guntrue_1871,118,86,352,0.034686637761135196
guntrue_2071,108,96,358,0.03452932098765432
guntrue_4289,135,130,604,0.034415954415954415
guntrue_2008,80,85,234,0.03441176470588235
guntrue_2209,132,82,372,0.03436807095343681
guntrue_8641,141,113,541,0.03395468524446118
guntrue_5051,123,126,519,0.03348819202477739
guntrue_1621,112,87,326,0.03345648604269294
guntrue_2053,137,99,453,0.0333996903339969
guntrue_1637,113,88,326,0.03278358809332261
guntrue_8737,143,115,535,0.03253268470659775
guntrue_8087,127,122,502,0.03239963856976894
guntrue_2273,136,86,372,0.03180574555403557
guntrue_9257,148,120,557,0.03136261261261261
guntrue_9161,146,118,540,0.03134432319479916
guntrue_7446,94,76,222,0.031075027995520716
guntrue_9001,146,118,533,0.030938007894125843
guntrue_5244,77,64,151,0.030641233766233768
guntrue_2417,145,95,372,0.027005444646098005
guntrue_2438,113,113,295,0.023102827159526978
guntrue_3634,114,108,264,0.021442495126705652

This may not look very useful right off, because the top densities are all small-bounding-box guns with big spacedusty custom oscillators filling up a lot of the space.

However, I was able to pick out 3301 and and 8011 from the list as suspiciously high density, and indeed they were both over-densified. I think maybe if we just filter this list to remove all the small bounding boxes, the remaining ugly trash-littered guns will end up at the top.

-------------------------

Have I mentioned that large language models have recently gotten spookily competent at writing Conway's Life utility scripts? They still hallucinate wildly if you ask direct questions about patterns, or ask them to generate RLE directly to answer questions.

But they know how to write Golly Python and Golly Lua scripts, with just the occasional small hiccup about things like how to call g.store() -- they used it the way that it probably _should_ work (direct conversion of a selection to an RLE string) but it doesn't actually work that way.