Hacking apgsearch

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2718281828
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Joined: August 8th, 2017, 5:38 pm

Re: Hacking apgsearch

Post by 2718281828 » December 13th, 2018, 7:34 pm

I would like to run a soup that has (diagonally) next to the standard 16x16 box a block,e.g. as in:

Code: Select all

x = 18, y = 18, rule = LifeHistory
2C$2C$2.A.A5.A.3A.A$3.A.A.2A2.3A.A$2.A2.A3.3A2.3A$2.3A2.A.A.2A.A.A$4.
2A.A.A3.4A$3.A.A.4A.3A.A$4.8A3.A$2.A5.A2.A.A.A.A$3.3A.A.2A3.A$3.A.A2.
2A3.3A.A$2.A3.A.5A.A.2A$4.4A.3A3.A.A$3.A.A.A2.4A.A.A$7.2A.A.A.A2.A$2.
A.A2.2A2.2A.2A.A$2.2A2.3A.4A.A.A!
But I struggle, with the bitworld format in apgsearch. I require some help on how I could initialise such a soup. Anyone a solution to it?

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wwei23
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Re: Hacking apgsearch

Post by wwei23 » December 13th, 2018, 9:18 pm

2718281828 wrote:I would like to run a soup that has (diagonally) next to the standard 16x16 box a block,e.g. as in:

Code: Select all

x = 18, y = 18, rule = LifeHistory
2C$2C$2.A.A5.A.3A.A$3.A.A.2A2.3A.A$2.A2.A3.3A2.3A$2.3A2.A.A.2A.A.A$4.
2A.A.A3.4A$3.A.A.4A.3A.A$4.8A3.A$2.A5.A2.A.A.A.A$3.3A.A.2A3.A$3.A.A2.
2A3.3A.A$2.A3.A.5A.A.2A$4.4A.3A3.A.A$3.A.A.A2.4A.A.A$7.2A.A.A.A2.A$2.
A.A2.2A2.2A.2A.A$2.2A2.3A.4A.A.A!
But I struggle, with the bitworld format in apgsearch. I require some help on how I could initialise such a soup. Anyone a solution to it?
Try the Golly script, it's a lot easier to make custon symmetries with.

wildmyron
Posts: 1397
Joined: August 9th, 2013, 12:45 am

Re: Hacking apgsearch

Post by wildmyron » December 14th, 2018, 5:27 am

2718281828 wrote:I would like to run a soup that has (diagonally) next to the standard 16x16 box a block,e.g. as in:

Code: Select all

x = 18, y = 18, rule = LifeHistory
2C$2C$2.A.A5.A.3A.A$3.A.A.2A2.3A.A$2.A2.A3.3A2.3A$2.3A2.A.A.2A.A.A$4.
2A.A.A3.4A$3.A.A.4A.3A.A$4.8A3.A$2.A5.A2.A.A.A.A$3.3A.A.2A3.A$3.A.A2.
2A3.3A.A$2.A3.A.5A.A.2A$4.4A.3A3.A.A$3.A.A.A2.4A.A.A$7.2A.A.A.A2.A$2.
A.A2.2A2.2A.2A.A$2.2A2.3A.4A.A.A!
But I struggle, with the bitworld format in apgsearch. I require some help on how I could initialise such a soup. Anyone a solution to it?
Here is a patch to apgmera which will allow you to search soups with an additional block on the diagonal and submit hauls to Catagolue. There are certainly better ways to do this with the tools in lifelib for more complex modifications of the soups (e.g. searching for alternate stabilisations of known puffer engines) but for simply adding a block this is sufficient.

Code: Select all

diff --git a/includes/hashsoup2.h b/includes/hashsoup2.h
index fb07b1f..8e23645 100644
--- a/includes/hashsoup2.h
+++ b/includes/hashsoup2.h
@@ -112,6 +112,15 @@ bitworld hashsoup_inner(std::string prehash, std::string symmetry) {
     bw.world[std::pair<int32_t, int32_t>(0, 1)] = d;
     bw.world[std::pair<int32_t, int32_t>(1, 1)] = c;

+    if (symmetry == "C1_Dblock_Test") {
+        bw.setcell(16, 16, 1);
+        bw.setcell(16, 17, 1);
+        bw.setcell(17, 16, 1);
+        bw.setcell(17, 17, 1);
+        return bw;
+    }
+
+
     if ((symmetry == "C1") || (symmetry == "D2_x")) { return bw; }

     bitworld dbw;
diff --git a/main.cpp b/main.cpp
index d32a8db..a4a70df 100755
--- a/main.cpp
+++ b/main.cpp
@@ -98,6 +98,7 @@ int main (int argc, char *argv[]) {

     // Disable verification by default if running on a HPC;
     // otherwise verify three hauls per uploaded haul:
+    verifications = 0; // Avoid verification with this modified client (it should be pretty safe though)
     if (verifications < 0) {
         verifications = (parallelisation <= 4) ? 3 : 0;
     }
diff --git a/mkparams.py b/mkparams.py
index 931b3c7..8c6208a 100644
--- a/mkparams.py
+++ b/mkparams.py
@@ -20,7 +20,8 @@ def main():
         validsyms = ["1x256", "2x128", "4x64", "8x32", "C1"]
     else:
         validsyms = ["1x256", "2x128", "4x64", "8x32", "C1", "C2_4", "C2_2", "C2_1", "C4_4", "C4_1",
-                 "D2_+2", "D2_+1", "D2_x", "D4_+4", "D4_+2", "D4_+1", "D4_x4", "D4_x1", "D8_4", "D8_1"]
+                 "D2_+2", "D2_+1", "D2_x", "D4_+4", "D4_+2", "D4_+1", "D4_x4", "D4_x1", "D8_4", "D8_1",
+                 "C1_Dblock_Test"]

     redsym = symmetry
     while ((len(redsym) > 0) and (redsym[0] == 'i')):
You can see the results of a test haul I submitted here. You will of course need to modify the sample soups to reproduce the census reported objects. The coordinates in the bitworld plane correspond directly to those in Golly when importing the soup's rle into Golly from the clipboard, so you should position a block at (16,16) to recreate the soup.

If you are interested in more complex modifications of the soup then a few functions which may be helpful are:
  • apg2vec() or rle2vec() to convert a pattern to a bitworld vector
  • shift_bitworld() to move this pattern around on the plane
  • bitworld.printrepr() to show the contents of a bitworld plane on the console (use in a test app, not in apgmera)
  • the bitworld type overloads +=, -=, ^=, and &= so that you can easily combine the soup with other patterns
This post is the result of a learning curve for me, so anyone (calcyman ;)) more knowledgeable please correct any bad advice provided here.
The latest version of the 5S Project contains over 226,000 spaceships. There is also a GitHub mirror of the collection. Tabulated pages up to period 160 (out of date) are available on the LifeWiki.

wildmyron
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Re: Hacking apgsearch

Post by wildmyron » May 17th, 2019, 2:08 am

Not really a hack, and not particularly useful at the moment, but I'm posting this here for reference.

I recently submitted a number of hauls to Catagolue with symmetry stdin_WM_4G. These hauls included the results of apgsearch processing a small subset of 4G collisions which were generated by a variation of chris_c's popseq.c. There were a few modifications I made to do this:
  • Modify popseq.c to remove the input pattern and output RLE for all collisions instead of evolving them.
  • Fix LifeAPI.h to not leak a LifeString for every call to PrintRLE().
  • Bypass the methuselah detection (which in combination with the 1024 minimum generations that all soups are run for resulted in a LOT of messless soups being reported.
The modified code is in a file named 4Gcolls.cpp (with an updated version of LifeAPI.h) which is attached to this post. The procedure to run the search which generated the results is as follows (but please don't run this verbatim as it will just duplicate the existing results):

Code: Select all

# Given commands assume 4Gcolls.cpp is in a directory named popseq alongside the apgmera directory
cd popseq
g++ -O3 -o 4Gcolls 4Gcolls.cpp
cd ../apgmera
./recompile.sh --symmetry stdin_WM_4G
mv apgluxe apgluxe_4g
../popseq/4Gcolls | ./apgluxe_4g -t 0 -L 0 -n 3000000 -k <key>
The choice for the haul size is a bit arbitrary - I tried to balance number of hauls against rare objects only having one sample soup per haul. The census also includes a second set of collisions with one of the gliders coming from a different direction. The other census I created was stdin_WM_sl+4G. This was intended to capture the results of 4G collisions adjacent to a still life object, but I accidentally submitted one set of 4G collisions without the SL object present during testing. I haven't proceeded further with this idea yet.

This experiment was inspired by simeks' 4G collision search. I think it would be worth replicating that, but there are a few issues to consider:
  • I initially tried generating 4G collisions with lifelib, but manipulating pattern2 (or upattern) objects has significantly poorer performance compared to LifeAPI (or presumably GoLGrid). A much better alternative would be to make a custom hashsoup function for apgsearch which generates collisions using the bitworld type (similar to the modification above).
  • More than one sample soup would automatically be submitted with a modified hashsoup function, but should soups be submitted as soupid's (which Catagolue wouldn't know how to recreate) or as RLEs in the same way as the stdin symmetry does (but without using stdin).
  • apgsearch doesn't distinguish between a 4G collision which synthesises a single object and one which evolves into a big mess in which the object appears several thousand gen later (along with a large amount of ash). Finding the 4G gems amongst the rest of the results is tedious, kudos to Ian07, Goldtiger, and anyone else who sifted through those results to find them. Any serious project along these lines should have some way of distinguishing the soups which produce objects that currently require > 4G to synthesise, optionally along with a small number of other ash objects. Perhaps a pseudo-object like the methuselah, messless, and megasized categorizations could be used.
Attachments
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Last edited by wildmyron on June 5th, 2019, 10:23 am, edited 3 times in total.
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Freywa
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Re: Hacking apgsearch

Post by Freywa » May 17th, 2019, 2:21 am

The modified code is in a file named 4Gcolls.cpp (with an updated version of LifeAPI.h) which is attached to this post.
There's no attachment!
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wildmyron
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Re: Hacking apgsearch

Post by wildmyron » May 17th, 2019, 2:25 am

Freywa wrote:
The modified code is in a file named 4Gcolls.cpp (with an updated version of LifeAPI.h) which is attached to this post.
There's no attachment!
Oops, now rectified. I spent so long writing the post I forgot to attach it!
The latest version of the 5S Project contains over 226,000 spaceships. There is also a GitHub mirror of the collection. Tabulated pages up to period 160 (out of date) are available on the LifeWiki.

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2718281828
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Re: Hacking apgsearch

Post by 2718281828 » May 17th, 2019, 5:57 pm

wildmyron wrote: apgsearch doesn't distinguish between a 4G collision which synthesises a single object and one which evolves into a big mess in which the object appears several thousand gen later (along with a large amount of ash). Finding the 4G gems amongst the rest of the results is tedious, kudos to Ian07, Goldtiger, and anyone else who sifted through those results to find them. Any serious project along these lines should have some way of distinguishing the soups which produce objects that currently require > 4G to synthesise, optionally along with a small number of other ash objects. Perhaps a pseudo-object like the methuselah, messless, and megasized categorizations could be used.
Yes, there are many useless long-lasting and large 3G collisions, where it seems useless to investigate all collisions.
I think for getting all relevant 4G collisions we should take all collisions with evolving 3G pattern that have a population below 120 and a bounding box below 30x50 [Something like this]. We can take those characteristics (pop bound and bounding box bound) from the upper bounds of meshless pattern.

Something related: Did someone investigate all 2G+2G collisions? It should be computationally doable.

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GUYTU6J
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Re: Hacking apgsearch

Post by GUYTU6J » July 8th, 2019, 5:15 am

dvgrn wrote:
GUYTU6J wrote:A small question: how to search for a monoengine/one-engine cordership?
A fairly efficient way to search for them is to simply run the lastest apgsearch on C1 soups. If there's one out there that can be found by dropping random objects near a switch engine, well, Catagolue might well stumble on it eventually, since it has recorded hundreds of millions of switch engines already.

If you want the search to go faster, you can use the stdin symmetry and some custom coding to make sure that every initial soup includes a switch engine.
How to make such symmetry?
Glimmering Garden是怎么回事呢?各向同性非总和性细胞自动机相信大家都很熟悉,但是Glimmering Garden是怎么回事呢,下面就让GUYTU6J带大家一起了解吧。
---
Someone please find a use for this:

Code: Select all

x = 9, y = 7, rule = B3/S23
6bo$6bobo$5bo2bo$b2o3b2o$o2bo$bobo$2bo!

wildmyron
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Re: Hacking apgsearch

Post by wildmyron » July 8th, 2019, 6:46 am

GUYTU6J wrote:
dvgrn wrote:If you want the search to go faster, you can use the stdin symmetry and some custom coding to make sure that every initial soup includes a switch engine.
How to make such symmetry?
You don't have to make such a symmetry - you just compile apgsearch with a symmetry that includes the string "stdin", e.g.

Code: Select all

./recompile.sh --rule b3s23 --symmetry stdin_GUYTU6J_SE
and then write a small program which generates random soups along with a switch engine as RLE and sends it to stdout. Run with something like:

Code: Select all

SE_soup_gen.py | apgluxe -t 0 -L 0 -n 1000000 -k <your_key>
Alternatively, you can modify the hashsoup function in lifelib to add a switch engine to every soup - similar to the C1_Dblock_test symmetry I posted earlier in the thread. See viewtopic.php?p=66471#p66471

The tradeoff is that the stdin symmetry will probably be slower and will have less soups per object (because only one sample soup per object is recorded in the census) but Catagolue won't be able to provide valid soup RLEs for the custom hashsoup symmetry.
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GUYTU6J
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Re: Hacking apgsearch

Post by GUYTU6J » July 8th, 2019, 8:28 am

wildmyron wrote: Alternatively, you can modify the hashsoup function in lifelib to add a switch engine to every soup - similar to the C1_Dblock_test symmetry I posted earlier in the thread. See viewtopic.php?p=66471#p66471
Is this similar to what codeholic did in the first page of the thread?
By the way, how to modify my apgluxe so that it doesn't notify me about every BLSE or GPSE?
Glimmering Garden是怎么回事呢?各向同性非总和性细胞自动机相信大家都很熟悉,但是Glimmering Garden是怎么回事呢,下面就让GUYTU6J带大家一起了解吧。
---
Someone please find a use for this:

Code: Select all

x = 9, y = 7, rule = B3/S23
6bo$6bobo$5bo2bo$b2o3b2o$o2bo$bobo$2bo!

Ian07
Posts: 551
Joined: September 22nd, 2018, 8:48 am

Re: Hacking apgsearch

Post by Ian07 » July 8th, 2019, 8:50 am

GUYTU6J wrote: By the way, how to modify my apgluxe so that it doesn't notify me about every BLSE or GPSE?
apgluxe automatically stops notifying you after the tenth instance of a specific object in a haul, but if you still find this annoying, go into includes/searcher.h and change this line of code, which is currently line 206 as of v5.09:

Code: Select all

if (census[apgcode] > 10) { continue; }
I'd recommend changing this to 1 so that you still get notified about the really rare objects while still receiving minimal notifications for everything else.

wildmyron
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Joined: August 9th, 2013, 12:45 am

Re: Hacking apgsearch

Post by wildmyron » July 8th, 2019, 9:39 am

GUYTU6J wrote:
wildmyron wrote: Alternatively, you can modify the hashsoup function in lifelib to add a switch engine to every soup - similar to the C1_Dblock_test symmetry I posted earlier in the thread. See viewtopic.php?p=66471#p66471
Is this similar to what codeholic did in the first page of the thread?
Indeed, however that modification was to the original Python version, so my comments are perhaps not as relevant. The frequent switch engines will also slow down your search, but probably not so drastic as to be intolerably slow. If you do want to survey a large number of SE soups though, then you may want to tune the stabilisation parameters.
The latest version of the 5S Project contains over 226,000 spaceships. There is also a GitHub mirror of the collection. Tabulated pages up to period 160 (out of date) are available on the LifeWiki.

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dvgrn
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Re: Hacking apgsearch

Post by dvgrn » January 6th, 2020, 7:50 am

Here's a non-ZIP-file copy of John Goodman's hacked apgsearch script from the basic questions thread -- objectsPerSoup.py. Statistics for a run of ten million soups can be found in the link.

Code: Select all

# objectsPerSoup.py
#
# A quick-and-dirty modification to apgsearch-2015-05-25.py, with
# Catagolue communications disabled and counts of the final object
# totals for each soup added to the final census file thusly:
#
# @FINAL_OBJECT_TOTALS
# 0,1988
# 1,10742
# 2,27685
# 3,43988
# ...
#
# In the above example, 1988 soups evolved to zero objects (messless);
# 10742 soups evolved to a single object, and so on.
#
#
# Note: Parallelization needed to be turned off to get a tally for each
# soup, so this script processes soups at less than 1/4 the speed of
# apgsearch (so on the order of 60 soups/sec).
#
# Modifications by John Goodman, 4-5 January 2020
#
# Based on:
# *************************************
# * Ash Pattern Generator (apgsearch) *
# *************************************
# * Version: v1.1  (beta release)     *
# *************************************
#
# By Adam P. Goucher, with contributions from Andrew Trevorrow, Tom Rokicki,
# Nathaniel Johnston, Dave Greene and Richard Schank.

import golly as g
from glife import rect, pattern
import time
import math
import operator
import hashlib
import datetime
import os
import urllib2



# Takes approximately 350 microseconds to construct a 16-by-16 soup based
# on a SHA-256 cryptographic hash in the obvious way.
def hashsoup(instring, sym):

    s = hashlib.sha256(instring).digest()

    thesoup = []

    if sym in ['D2_x', 'D8_1', 'D8_4']:
        d = 1
    elif sym in ['D4_x1', 'D4_x4']:
        d = 2
    else:
        d = 0

    for j in xrange(32):

        t = ord(s[j])

        for k in xrange(8):

            if (sym == '8x32'):
                x = k + 8*(j % 4)
                y = int(j / 4)
            else:
                x = k + 8*(j % 2)
                y = int(j / 2)

            if (t & (1 << (7 - k))):

                if ((d == 0) | (x >= y)):

                    thesoup.append(x)
                    thesoup.append(y)

                elif (sym == 'D4_x1'):

                    thesoup.append(y)
                    thesoup.append(-x)

                elif (sym == 'D4_x4'):

                    thesoup.append(y)
                    thesoup.append(-x-1)

                if ((sym == 'D4_x1') & (x == y)):

                    thesoup.append(y)
                    thesoup.append(-x)

                if ((sym == 'D4_x4') & (x == y)):

                    thesoup.append(y)
                    thesoup.append(-x-1)

    # Checks for diagonal symmetries:
    if (d >= 1):
        for x in xrange(0, len(thesoup), 2):
            thesoup.append(thesoup[x+1])
            thesoup.append(thesoup[x])
        if d == 2:
            if (sym == 'D4_x1'):
                for x in xrange(0, len(thesoup), 2):
                    thesoup.append(-thesoup[x+1])
                    thesoup.append(-thesoup[x])
            else:
                for x in xrange(0, len(thesoup), 2):
                    thesoup.append(-thesoup[x+1] - 1)
                    thesoup.append(-thesoup[x] - 1)
            return thesoup

    # Checks for orthogonal x symmetry:
    if sym in ['D2_+1', 'D4_+1', 'D4_+2']:
        for x in xrange(0, len(thesoup), 2):
            thesoup.append(thesoup[x])
            thesoup.append(-thesoup[x+1])
    elif sym in ['D2_+2', 'D4_+4']:
        for x in xrange(0, len(thesoup), 2):
            thesoup.append(thesoup[x])
            thesoup.append(-thesoup[x+1] - 1)

    # Checks for orthogonal y symmetry:
    if sym in ['D4_+1']:
        for x in xrange(0, len(thesoup), 2):
            thesoup.append(-thesoup[x])
            thesoup.append(thesoup[x+1])
    elif sym in ['D4_+2', 'D4_+4']:
        for x in xrange(0, len(thesoup), 2):
            thesoup.append(-thesoup[x] - 1)
            thesoup.append(thesoup[x+1])

    # Checks for rotate2 symmetry:
    if sym in ['C2_1', 'C4_1', 'D8_1']:
        for x in xrange(0, len(thesoup), 2):
            thesoup.append(-thesoup[x])
            thesoup.append(-thesoup[x+1])
    elif sym in ['C2_2']:
        for x in xrange(0, len(thesoup), 2):
            thesoup.append(-thesoup[x])
            thesoup.append(-thesoup[x+1]-1)
    elif sym in ['C2_4', 'C4_4', 'D8_4']:
        for x in xrange(0, len(thesoup), 2):
            thesoup.append(-thesoup[x]-1)
            thesoup.append(-thesoup[x+1]-1)

    # Checks for rotate4 symmetry:
    if (sym in ['C4_1', 'D8_1']):
        for x in xrange(0, len(thesoup), 2):
            thesoup.append(thesoup[x+1])
            thesoup.append(-thesoup[x])
    elif (sym in ['C4_4', 'D8_4']):
        for x in xrange(0, len(thesoup), 2):
            thesoup.append(thesoup[x+1])
            thesoup.append(-thesoup[x]-1)

    return thesoup



# Obtains a canonical representation of any oscillator/spaceship that (in
# some phase) fits within a 40-by-40 bounding box. This representation is
# alphanumeric and lowercase, and so much more compact than RLE. Compare:
#
# Common name: pentadecathlon
# Canonical representation: 4r4z4r4
# Equivalent RLE: 2bo4bo$2ob4ob2o$2bo4bo!
#
# It is a generalisation of a notation created by Allan Weschler in 1992.
def canonise(duration):

    representation = "#"

    # We need to compare each phase to find the one with the smallest
    # description:
    for t in xrange(duration):

        rect = g.getrect()
        if (len(rect) == 0):
            return "0"

        if ((rect[2] <= 40) & (rect[3] <= 40)):
            # Fits within a 40-by-40 bounding box, so eligible to be canonised.
            # Choose the orientation which results in the smallest description:
            representation = compare_representations(representation, canonise_orientation(rect[2], rect[3], rect[0], rect[1], 1, 0, 0, 1))
            representation = compare_representations(representation, canonise_orientation(rect[2], rect[3], rect[0]+rect[2]-1, rect[1], -1, 0, 0, 1))
            representation = compare_representations(representation, canonise_orientation(rect[2], rect[3], rect[0], rect[1]+rect[3]-1, 1, 0, 0, -1))
            representation = compare_representations(representation, canonise_orientation(rect[2], rect[3], rect[0]+rect[2]-1, rect[1]+rect[3]-1, -1, 0, 0, -1))
            representation = compare_representations(representation, canonise_orientation(rect[3], rect[2], rect[0], rect[1], 0, 1, 1, 0))
            representation = compare_representations(representation, canonise_orientation(rect[3], rect[2], rect[0]+rect[2]-1, rect[1], 0, -1, 1, 0))
            representation = compare_representations(representation, canonise_orientation(rect[3], rect[2], rect[0], rect[1]+rect[3]-1, 0, 1, -1, 0))
            representation = compare_representations(representation, canonise_orientation(rect[3], rect[2], rect[0]+rect[2]-1, rect[1]+rect[3]-1, 0, -1, -1, 0))

        g.run(1)

    return representation



# A subroutine used by canonise:
def canonise_orientation(length, breadth, ox, oy, a, b, c, d):

    representation = ""

    chars = "0123456789abcdefghijklmnopqrstuvwxyz"

    for v in xrange(int((breadth-1)/5)+1):
        zeroes = 0
        if (v != 0):
            representation += "z"
        for u in xrange(length):
            baudot = 0
            for w in xrange(5):
                x = ox + a*u + b*(5*v + w)
                y = oy + c*u + d*(5*v + w)
                baudot = (baudot >> 1) + 16*g.getcell(x, y)
            if (baudot == 0):
                zeroes += 1
            else:
                if (zeroes > 0):
                    if (zeroes == 1):
                        representation += "0"
                    elif (zeroes == 2):
                        representation += "w"
                    elif (zeroes == 3):
                        representation += "x"
                    else:
                        representation += "y"
                        representation += chars[zeroes - 4]
                zeroes = 0
                representation += chars[baudot]
    return representation



# Compares strings first by length, then by lexicographical ordering.
# A hash character is worse than anything else.
def compare_representations(a, b):

    if (a == "#"):
        return b
    elif (b == "#"):
        return a
    elif (len(a) < len(b)):
        return a
    elif (len(b) < len(a)):
        return b
    elif (a < b):
        return a
    else:
        return b



# Finds the gradient of the least-squares regression line corresponding
# to a list of ordered pairs:
def regress(pairlist):

    cumx = 0.0
    cumy = 0.0
    cumvar = 0.0
    cumcov = 0.0

    for x,y in pairlist:

        cumx += x
        cumy += y

    cumx = cumx / len(pairlist)
    cumy = cumy / len(pairlist)

    for x,y in pairlist:

        cumvar += (x - cumx)*(x - cumx)
        cumcov += (x - cumx)*(y - cumy)

    return (cumcov / cumvar)



# Analyses a pattern whose average population follows a power-law:
def powerlyse(stepsize, numsteps):

    g.setalgo("HashLife")
    g.setbase(2)
    g.setstep(stepsize)

    poplist = [0]*numsteps

    poplist[0] = int(g.getpop())

    pointlist = []

    for i in xrange(1, numsteps, 1):

        g.step()
        poplist[i] = int(g.getpop()) + poplist[i-1]

        if (i % 50 == 0):

            g.fit()
            g.update()

        if (i > numsteps/2):

            pointlist.append((math.log(i),math.log(poplist[i]+1.0)))

    power = regress(pointlist)

    if (power < 1.10):
        return "unidentified"
    elif (power < 1.65):
        return "zz_REPLICATOR"
    elif (power < 2.05):
        return "zz_LINEAR"
    elif (power < 2.8):
        return "zz_EXPLOSIVE"
    else:
        return "zz_QUADRATIC"



# Gets the period of an interleaving of degree-d polynomials:
def deepperiod(sequence, maxperiod, degree):

    for p in xrange(1, maxperiod, 1):

        good = True

        for i in xrange(maxperiod):

            diffs = [0] * (degree + 2)
            for j in xrange(degree + 2):

                diffs[j] = sequence[i + j*p]

            # Produce successive differences:
            for j in xrange(degree + 1):
                for k in xrange(degree + 1):
                    diffs[k] = diffs[k] - diffs[k + 1]

            if (diffs[0] != 0):
                good = False
                break

        if (good):
            return p
    return -1



# Analyses a linear-growth pattern, returning a hash:
def linearlyse(maxperiod):

    poplist = [0]*(3*maxperiod)

    for i in xrange(3*maxperiod):

        g.run(1)
        poplist[i] = int(g.getpop())

    p = deepperiod(poplist, maxperiod, 1)

    if (p == -1):
        return "unidentified"

    difflist = [0]*(2*maxperiod)

    for i in xrange(2*maxperiod):

        difflist[i] = poplist[i + p] - poplist[i]

    q = deepperiod(difflist, maxperiod, 0)

    moments = [0, 0, 0]

    for i in xrange(p):

        moments[0] += (poplist[i + q] - poplist[i])
        moments[1] += (poplist[i + q] - poplist[i]) ** 2
        moments[2] += (poplist[i + q] - poplist[i]) ** 3

    prehash = str(moments[1]) + "#" + str(moments[2])

    # Linear-growth patterns with growth rate zero are clearly errors!
    if (moments[0] == 0):
        return "unidentified"

    return "yl" + str(p) + "_" + str(q) + "_" + str(moments[0]) + "_" + hashlib.md5(prehash).hexdigest()



# This explodes pseudo-still-lifes and pseudo-oscillators into their
# constituent parts.
#
# -- Requires the period (if oscillatory) and graph-theoretic diameter
#    to not exceed 4096.
# -- Never mistakenly separates a true object.
# -- Correctly separates most pseudo-still-lifes, including the famous:
#    http://www.conwaylife.com/wiki/Quad_pseudo_still_life
# -- Works perfectly for all still-lifes of up to 17 bits.
# -- Doesn't separate 'locks', of which the smallest example has 18
#    bits and is unique:
#
#     ** **
#     ** **
#
#    * *** *
#    ** * **
#
# To use this function (standalone), merely copy it into a script of
# the following form:
#
#   import golly as g
#
#   def pseudo_bangbang():
#
#   [...]
#
#   pseudo_bangbang()
#
# and execute it in Golly with a B3/S23 universe containing any still-
# lifes or oscillators you want to separate. Pure objects correspond to
# connected components in the final state of the universe.
#
# This has dependencies on the rules ContagiousLife, PercolateInfection
# and EradicateInfection.
#
# Not to be confused with the Unix shell instruction for repeating the
# previous instruction as a superuser (sudo !!), or indeed with any
# parodies of this song: https://www.youtube.com/watch?v=YswhUHH6Ufc
#
# Adam P. Goucher, 2014-08-25
def pseudo_bangbang(alpharule):

    g.setrule("APG_ContagiousLife_" + alpharule)
    g.setbase(2)
    g.setstep(12)
    g.step()

    celllist = g.getcells(g.getrect())

    for i in xrange(0, len(celllist)-1, 3):
        
        # Only infect cells that haven't yet been infected:
        if (g.getcell(celllist[i], celllist[i+1]) <= 2):

            # Seed an initial 'infected' (red) cell:
            g.setcell(celllist[i], celllist[i+1], g.getcell(celllist[i], celllist[i+1]) + 2)

            prevpop = 0
            currpop = int(g.getpop())

            # Continue infecting until the entire component has been engulfed:
            while (prevpop != currpop):

                # Percolate the infection to every cell in the island:
                g.setrule("APG_PercolateInfection")
                g.setbase(2)
                g.setstep(12)
                g.step()

                # Transmit the infection across any bridges.
                g.setrule("APG_ContagiousLife_" + alpharule)
                g.setbase(2)
                g.setstep(12)
                g.step()

                prevpop = currpop
                currpop = int(g.getpop())
                
            g.fit()
            g.update()

            # Red becomes green:
            g.setrule("APG_EradicateInfection")
            g.step()



# Counts the number of live cells of each degree:
def degreecount():

    celllist = g.getcells(g.getrect())
    counts = [0,0,0,0,0,0,0,0,0]

    for i in xrange(0, len(celllist), 2):

        x = celllist[i]
        y = celllist[i+1]

        degree = -1

        for ux in xrange(x - 1, x + 2):
            for uy in xrange(y - 1, y + 2):

                degree += g.getcell(ux, uy)

        counts[degree] += 1

    return counts



# Counts the number of live cells of each degree in generations 1 and 2:
def degreecount2():

    g.run(1)
    a = degreecount()
    g.run(1)
    b = degreecount()

    return (a + b)



# If the universe consists only of disjoint *WSSes, this will return
# a triple (l, w, h) giving the quantities of each *WSS. Otherwise,
# this function will return (-1, -1, -1).
#
# This should only be used to separate period-4 moving objects which
# may contain multiple *WSSes.
def countxwsses():

    degcount = degreecount2()
    if (degreecount2() != degcount):
        # Degree counts are not period-2:
        return (-1, -1, -1)

    # Degree counts of each standard spaceship:
    hwssa = [1,4,6,2,0,0,0,0,0,0,0,0,4,4,6,1,2,1]
    mwssa = [2,2,5,2,0,0,0,0,0,0,0,0,4,4,4,1,2,0]
    lwssa = [1,2,4,2,0,0,0,0,0,0,0,0,4,4,2,2,0,0]
    hwssb = [0,0,0,4,4,6,1,2,1,1,4,6,2,0,0,0,0,0]
    mwssb = [0,0,0,4,4,4,1,2,0,2,2,5,2,0,0,0,0,0]
    lwssb = [0,0,0,4,4,2,2,0,0,1,2,4,2,0,0,0,0,0]

    # Calculate the number of standard spaceships in each phase:
    hacount = degcount[17]
    macount = degcount[16]/2 - hacount
    lacount = (degcount[15] - hacount - macount)/2
    hbcount = degcount[8]
    mbcount = degcount[7]/2 - hbcount
    lbcount = (degcount[6] - hbcount - mbcount)/2

    # Determine the expected degcount given the calculated quantities:
    pcounts = [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
    pcounts = map(lambda x, y: x + y, pcounts, map(lambda x: hacount*x, hwssa))
    pcounts = map(lambda x, y: x + y, pcounts, map(lambda x: macount*x, mwssa))
    pcounts = map(lambda x, y: x + y, pcounts, map(lambda x: lacount*x, lwssa))
    pcounts = map(lambda x, y: x + y, pcounts, map(lambda x: hbcount*x, hwssb))
    pcounts = map(lambda x, y: x + y, pcounts, map(lambda x: mbcount*x, mwssb))
    pcounts = map(lambda x, y: x + y, pcounts, map(lambda x: lbcount*x, lwssb))

    # Compare the observed and expected degcounts (to eliminate nonstandard spaceships):
    if (pcounts != degcount):
        # Expected and observed values do not match:
        return (-1, -1, -1)

    # Return the combined numbers of *WSSes:
    return(lacount + lbcount, macount + mbcount, hacount + hbcount)



# Generates the helper rules for apgsearch, given a base outer-totalistic rule.
class RuleGenerator:

    def __init__(self):

        # Unless otherwise specified, assume standard B3/S23 rule:
        self.bee = [False, False, False, True, False, False, False, False, False]
        self.ess = [False, False, True, True, False, False, False, False, False]
        self.alphanumeric = "B3S23"
        self.slashed = "B3/S23"

    # Save all helper rules:
    def saveAllRules(self):

        self.saveClassifyObjects()
        self.saveCoalesceObjects()
        self.saveExpungeObjects()
        self.saveExpungeGliders()
        self.saveIdentifyGliders()
        self.saveHandlePlumes()
        self.savePercolateInfection()
        self.saveEradicateInfection()
        self.saveContagiousLife()

    # Set outer-totalistic rule:
    def setrule(self, rulestring):

        mode = 0
        s = [False]*9
        b = [False]*9

        for c in rulestring:

            if ((c == 's') | (c == 'S')):
                mode = 0

            if ((c == 'b') | (c == 'B')):
                mode = 1

            if (c == '/'):
                mode = 1 - mode

            if ((ord(c) >= 48) & (ord(c) <= 56)):
                d = ord(c) - 48
                if (mode == 0):
                    s[d] = True
                else:
                    b[d] = True

        prefix = "B"
        suffix = "S"

        for i in xrange(9):
            if (b[i]):
                prefix += str(i)
            if (s[i]):
                suffix += str(i)

        self.alphanumeric = prefix + suffix
        self.slashed = prefix + "/" + suffix
        self.bee = b
        self.ess = s

    # Save a rule file:
    def saverule(self, name, comments, table, colours):

        ruledir = g.getdir("rules")
        filename = ruledir + name + ".rule"

        results = "@RULE " + name + "\n\n"
        results += "*** File autogenerated by saverule. ***\n\n"
        results += comments
        results += "\n\n@TABLE\n\n"
        results += table
        results += "\n\n@COLORS\n\n"
        results += colours

        # Only create a rule file if it doesn't already exist; this avoids
        # concurrency issues when booting an instance of apgsearch whilst
        # one is already running.
        if not os.path.exists(filename):
            try:
                f = open(filename, 'w')
                f.write(results)
                f.close()
            except:
                g.warn("Unable to create rule table:\n" + filename)

    # Defines a variable:
    def newvar(self, name, vallist):

        line = "var "+name+"={"
        for i in xrange(len(vallist)):
            if (i > 0):
                line += ','
            line += str(vallist[i])
        line += "}\n"

        return line

    # Defines a block of equivalent variables:
    def newvars(self, namelist, vallist):

        block = ""

        for name in namelist:
            block += self.newvar(name, vallist)

        block += "\n"

        return block

    def scoline(self, chara, charb, left, right, amount):

        line = str(left) + ","

        for i in xrange(8):
            if (i < amount):
                line += chara
            else:
                line += charb
            line += chr(97 + i)
            line += ","

        line += str(right) + "\n"

        return line

    def saveHandlePlumes(self):

        comments = """
This post-processes the output of ClassifyObjects to remove any
unwanted clustering of low-period objects appearing in puffer
exhaust.

state 0:  vacuum

state 7:  ON, still-life
state 8:  OFF, still-life

state 9:  ON, p2 oscillator
state 10: OFF, p2 oscillator

state 11: ON, higher-period object
state 12: OFF, higher-period object
"""
        table = """
n_states:17
neighborhood:Moore
symmetries:permute

var da={0,2,4,6,8,10,12,14,16}
var db={0,2,4,6,8,10,12,14,16}
var dc={0,2,4,6,8,10,12,14,16}
var dd={0,2,4,6,8,10,12,14,16}
var de={0,2,4,6,8,10,12,14,16}
var df={0,2,4,6,8,10,12,14,16}
var dg={0,2,4,6,8,10,12,14,16}
var dh={0,2,4,6,8,10,12,14,16}

var a={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var b={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var c={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var d={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var e={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var f={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var g={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var h={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}


8,da,db,dc,dd,de,df,dg,dh,0
10,da,db,dc,dd,de,df,dg,dh,0

9,a,b,c,d,e,f,g,h,1
10,a,b,c,d,e,f,g,h,2
"""
        colours = """
1  255  255  255
2  127  127  127
7    0    0  255
8    0    0  127
9  255    0    0
10 127    0    0
11   0  255    0
12   0  127    0
"""
        self.saverule("APG_HandlePlumesCorrected", comments, table, colours)

    def saveExpungeGliders(self):

        comments = """
This removes unwanted gliders.
It is mandatory that one first runs the rules CoalesceObjects,
IdentifyGliders and ClassifyObjects.

Run this for two generations, and observe the population
counts after 1 and 2 generations. This will give the
following data:

number of gliders = (p(1) - p(2))/5
"""
        table = """
n_states:17
neighborhood:Moore
symmetries:rotate4reflect

var a={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var b={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var c={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var d={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var e={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var f={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var g={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var h={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}

13,a,b,c,d,e,f,g,h,14
14,a,b,c,d,e,f,g,h,0
"""
        colours = """
0    0    0    0
1  255  255  255
2  127  127  127
7    0    0  255
8    0    0  127
9  255    0    0
10 127    0    0
11   0  255    0
12   0  127    0
13 255  255    0
14 127  127    0
"""
        self.saverule("APG_ExpungeGliders", comments, table, colours)

    def saveIdentifyGliders(self):

        comments = """
Run this after CoalesceObjects to find any gliders.

state 0:  vacuum
state 1:  ON
state 2:  OFF
"""
        table = """
n_states:17
neighborhood:Moore
symmetries:rotate4reflect

var a={0,2}
var b={0,2}
var c={0,2}
var d={0,2}
var e={0,2}
var f={0,2}
var g={0,2}
var h={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var i={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var j={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var k={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var l={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var m={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var n={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var o={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var p={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}
var q={3,4}
var r={9,10}
var s={11,12}

1,1,a,1,1,b,1,c,d,3
d,1,1,1,1,a,b,1,c,4

3,i,j,k,l,m,n,o,p,5
4,i,j,k,l,m,n,o,p,6

1,q,i,j,a,b,c,k,l,7
d,q,i,j,a,b,c,k,l,8
1,i,a,b,c,d,e,j,q,7
f,i,a,b,c,d,e,j,q,8

5,7,8,7,7,8,7,8,8,9
6,7,7,7,7,8,8,7,8,10
5,i,j,k,l,m,n,o,p,15
6,i,j,k,l,m,n,o,p,16
15,i,j,k,l,m,n,o,p,1
16,i,j,k,l,m,n,o,p,2

7,i,j,k,l,m,n,o,p,11
8,i,j,k,l,m,n,o,p,12

9,i,j,k,l,m,n,o,p,13
10,i,j,k,l,m,n,o,p,14
11,r,j,k,l,m,n,o,p,13
11,i,r,k,l,m,n,o,p,13
12,r,j,k,l,m,n,o,p,14
12,i,r,k,l,m,n,o,p,14

11,i,j,k,l,m,n,o,p,1
12,i,j,k,l,m,n,o,p,2
"""
        colours = """
0    0    0    0
1  255  255  255
2  127  127  127
7    0    0  255
8    0    0  127
9  255    0    0
10 127    0    0
11   0  255    0
12   0  127    0
13 255  255    0
14 127  127    0
"""
        self.saverule("APG_IdentifyGliders", comments, table, colours)

    def saveEradicateInfection(self):

        comments = """
To run after ContagiousLife to disinfect any cells in states 3 or 4.

state 0:  vacuum
state 1:  ON
state 2:  OFF
"""
        table = """
n_states:7
neighborhood:Moore
symmetries:permute

var a={0,1,2,3,4,5,6}
var b={0,1,2,3,4,5,6}
var c={0,1,2,3,4,5,6}
var d={0,1,2,3,4,5,6}
var e={0,1,2,3,4,5,6}
var f={0,1,2,3,4,5,6}
var g={0,1,2,3,4,5,6}
var h={0,1,2,3,4,5,6}
var i={0,1,2,3,4,5,6}

4,a,b,c,d,e,f,g,h,6
3,a,b,c,d,e,f,g,h,5
"""
        colours = """
0    0    0    0
1    0    0  255
2    0    0  127
3  255    0    0
4  127    0    0
5    0  255    0
6    0  127    0
"""
        self.saverule("APG_EradicateInfection", comments, table, colours)

    def savePercolateInfection(self):

        comments = """
Percolates any infection to all cells of that particular island.

state 0:  vacuum
state 1:  ON
state 2:  OFF
"""
        table = """
n_states:7
neighborhood:Moore
symmetries:permute

var a={0,1,2,3,4,5,6}
var b={0,1,2,3,4,5,6}
var c={0,1,2,3,4,5,6}
var d={0,1,2,3,4,5,6}
var e={0,1,2,3,4,5,6}
var f={0,1,2,3,4,5,6}
var g={0,1,2,3,4,5,6}
var h={0,1,2,3,4,5,6}
var i={0,1,2,3,4,5,6}

var q={3,4}
var da={2,4,6}
var la={1,3,5}

da,q,b,c,d,e,f,g,h,4
la,q,b,c,d,e,f,g,h,3
"""
        colours = """
0    0    0    0
1    0    0  255
2    0    0  127
3  255    0    0
4  127    0    0
5    0  255    0
6    0  127    0
"""
        self.saverule("APG_PercolateInfection", comments, table, colours)
        
    def saveExpungeObjects(self):

        comments = """
This removes unwanted monominos, blocks, blinkers and beehives.
It is mandatory that one first runs the rule ClassifyObjects.

Run this for four generations, and observe the population
counts after 0, 1, 2, 3 and 4 generations. This will give the
following data:

number of monominos = p(1) - p(0)
number of blocks = (p(2) - p(1))/4
number of blinkers = (p(3) - p(2))/5
number of beehives = (p(4) - p(3))/8
"""
        table = "n_states:17\n"
        table += "neighborhood:Moore\n"
        table += "symmetries:rotate4reflect\n\n"

        table += self.newvars(["a","b","c","d","e","f","g","h","i"], range(0, 17, 1))

        table += """
# Monomino
7,0,0,0,0,0,0,0,0,0

# Death
6,a,b,c,d,e,f,g,h,0
a,6,b,c,d,e,f,g,h,0

# Block
7,7,7,7,0,0,0,0,0,1
1,1,1,1,0,0,0,0,0,0
1,a,b,c,d,e,f,g,h,7

# Blinker
10,0,0,0,9,9,9,0,0,2
9,9,10,0,0,0,0,0,10,3
2,a,b,c,d,e,f,g,h,10
3,a,b,c,d,e,f,g,h,9
9,2,0,3,0,2,0,3,0,6

# Beehive
7,0,7,8,7,0,0,0,0,1
7,0,0,7,8,8,7,0,0,1
8,7,7,8,7,7,0,7,0,4
4,1,1,4,1,1,0,1,0,5
4,a,b,c,d,e,f,g,h,8
5,5,b,c,d,e,f,g,h,6
5,a,b,c,d,e,f,g,h,15
15,a,b,c,d,e,f,g,h,8
"""

        colours = """
0    0    0    0
1  255  255  255
2  127  127  127
7    0    0  255
8    0    0  127
9  255    0    0
10 127    0    0
11   0  255    0
12   0  127    0
13 255  255    0
14 127  127    0
"""
        self.saverule("APG_ExpungeObjects", comments, table, colours)

    def saveCoalesceObjects(self):

        comments = """
A variant of HistoricalLife which separates a field of ash into
distinct objects.

state 0:  vacuum
state 1:  ON
state 2:  OFF
"""
        table = "n_states:3\n"
        table += "neighborhood:Moore\n"
        table += "symmetries:permute\n\n"

        table += self.newvars(["a","b","c","d","e","f","g","h","i"], [0, 1, 2])
        table += self.newvars(["da","db","dc","dd","de","df","dg","dh","di"], [0, 2])
        table += self.newvars(["la","lb","lc","ld","le","lf","lg","lh","li"], [1])

        minperc = 10

        for i in xrange(9):
            if (self.bee[i]):
                if (minperc == 10):
                    minperc = i
                table += self.scoline("l","d",0,1,i)
                table += self.scoline("l","d",2,1,i)
            if (self.ess[i]):
                table += self.scoline("l","d",1,1,i)

        table += "\n# Bridge inductors\n"

        for i in xrange(9):
            if (i >= minperc):
                table += self.scoline("l","d",0,2,i)

        table += self.scoline("","",1,2,0)

        colours = """
0    0    0    0
1  255  255  255
2  127  127  127
"""
        self.saverule("APG_CoalesceObjects_"+self.alphanumeric, comments, table, colours)

    def saveClassifyObjects(self):

        comments = """
This passively classifies objects as either still-lifes, p2 oscillators
or higher-period oscillators. It is mandatory that one first runs the
rule CoalesceObjects.

state 0:  vacuum
state 1:  input ON
state 2:  input OFF

state 3:  ON, will die
state 4:  OFF, will remain off
state 5:  ON, will survive
state 6:  OFF, will become alive

state 7:  ON, still-life
state 8:  OFF, still-life

state 9:  ON, p2 oscillator
state 10: OFF, p2 oscillator

state 11: ON, higher-period object
state 12: OFF, higher-period object
"""
        table = "n_states:17\n"
        table += "neighborhood:Moore\n"
        table += "symmetries:permute\n\n"

        table += self.newvars(["a","b","c","d","e","f","g","h","i"], range(0, 17, 1))
        table += self.newvars(["la","lb","lc","ld","le","lf","lg","lh","li"], range(1, 17, 2))
        table += self.newvars(["da","db","dc","dd","de","df","dg","dh","di"], range(0, 17, 2))
        table += self.newvars(["pa","pb","pc","pd","pe","pf","pg","ph","pi"], [0, 3, 4])
        table += self.newvars(["qa","qb","qc","qd","qe","qf","qg","qh","qi"], [5, 6])

        for i in xrange(9):
            if (self.bee[i]):
                table += self.scoline("l","d",2,6,i)
                table += self.scoline("q","p",3,9,i)
                table += self.scoline("q","p",4,12,i)
            if (self.ess[i]):
                table += self.scoline("l","d",1,5,i)
                table += self.scoline("q","p",5,7,i)
                table += self.scoline("q","p",6,12,i)
        table += self.scoline("","",2,4,0)
        table += self.scoline("","",1,3,0)
        table += self.scoline("","",5,11,0)
        table += self.scoline("","",3,11,0)
        table += self.scoline("","",4,8,0)
        table += self.scoline("","",6,10,0)

        table += """
# Propagate interestingness
7,11,b,c,d,e,f,g,h,11
7,12,b,c,d,e,f,g,h,11
7,9,b,c,d,e,f,g,h,9
7,10,b,c,d,e,f,g,h,9
8,11,b,c,d,e,f,g,h,12
8,12,b,c,d,e,f,g,h,12
8,9,b,c,d,e,f,g,h,10
8,10,b,c,d,e,f,g,h,10

7,13,b,c,d,e,f,g,h,11
7,14,b,c,d,e,f,g,h,11
8,13,b,c,d,e,f,g,h,14
8,14,b,c,d,e,f,g,h,14
9,13,b,c,d,e,f,g,h,11
9,14,b,c,d,e,f,g,h,11
10,13,b,c,d,e,f,g,h,14
10,14,b,c,d,e,f,g,h,14

9,11,b,c,d,e,f,g,h,11
9,12,b,c,d,e,f,g,h,11
10,11,b,c,d,e,f,g,h,12
10,12,b,c,d,e,f,g,h,12

13,11,b,c,d,e,f,g,h,11
13,12,b,c,d,e,f,g,h,11
14,11,b,c,d,e,f,g,h,12
14,12,b,c,d,e,f,g,h,12
13,9,b,c,d,e,f,g,h,11
14,9,b,c,d,e,f,g,h,12
"""

        colours = """
0    0    0    0
1  255  255  255
2  127  127  127
7    0    0  255
8    0    0  127
9  255    0    0
10 127    0    0
11   0  255    0
12   0  127    0
13 255  255    0
14 127  127    0
"""
        self.saverule("APG_ClassifyObjects_"+self.alphanumeric, comments, table, colours)

    def saveContagiousLife(self):

        comments = """
A variant of HistoricalLife used for detecting dependencies between
islands.

state 0:  vacuum
state 1:  ON
state 2:  OFF
"""
        table = "n_states:7\n"
        table += "neighborhood:Moore\n"
        table += "symmetries:permute\n\n"

        table += self.newvars(["a","b","c","d","e","f","g","h","i"], range(0, 7, 1))
        table += self.newvars(["la","lb","lc","ld","le","lf","lg","lh","li"], range(1, 7, 2))
        table += self.newvars(["da","db","dc","dd","de","df","dg","dh","di"], range(0, 7, 2))
        table += self.newvar("p",[3, 4])
        table += self.newvars(["ta","tb","tc","td","te","tf","tg","th","ti"], [3])
        table += self.newvars(["qa","qb","qc","qd","qe","qf","qg","qh","qi"], [0, 1, 2, 4, 5, 6])

        for i in xrange(9):
            if (self.bee[i]):
                table += self.scoline("l","d",4,3,i)
                table += self.scoline("l","d",2,1,i)
                table += self.scoline("l","d",0,1,i)
                table += self.scoline("l","d",6,5,i)
                table += self.scoline("t","q",0,4,i)
            if (self.ess[i]):
                table += self.scoline("l","d",3,3,i)
                table += self.scoline("l","d",5,5,i)
                table += self.scoline("l","d",1,1,i)

        table += "# Default behaviour (death):\n"
        table += self.scoline("","",1,2,0)
        table += self.scoline("","",5,6,0)
        table += self.scoline("","",3,4,0)

        colours = """
0    0    0    0
1    0    0  255
2    0    0  127
3  255    0    0
4  127    0    0
5    0  255    0
6    0  127    0
"""
        self.saverule("APG_ContagiousLife_"+self.alphanumeric, comments, table, colours)



class Soup:

    def __init__(self):

        # The rule generator:
        self.rg = RuleGenerator()

        # Should we skip error-correction:
        self.skipErrorCorrection = False

        # A dict mapping binary representations of small possibly-pseudo-objects
        # to their equivalent canonised representation.
        #
        # This is many-to-one, as (for example) all of these will map to
        # the same pseudo-object (namely the beacon on block):
        #
        # ..**.**  ..**.**  **.....                           **.....
        # ..**.**  ...*.**  **.....                           *......
        # **.....  *......  ..**...                           ...*.**
        # **.....  **.....  ..**... [...12 others omitted...] ..**.**
        # .......  .......  .......                           .......
        # .......  .......  ..**...                           .......
        # .......  .......  ..**...                           .......
        #
        # The first few soups are much slower to process, as objects are being
        # entered into the cache.
        self.cache = {}

        # A dict to store memoized decompositions of possibly-pseudo-objects
        # into constituent parts. This is initialised with the unique minimal
        # pseudo-still-life (two blocks on lock) that cannot be automatically
        # separated by the routine pseudo_bangbang(). Any larger objects are
        # ambiguous, such as this one:
        #
        #     *
        #    * * **
        #     ** **
        #
        #    * *** *
        #    ** * **
        #
        # Is it a (block on (lock on boat)) or ((block on lock) on boat)?
        # Ahh, the joys of non-associativity.
        #
        # See http://paradise.caltech.edu/~cook/Workshop/CAs/2DOutTot/Life/StillLife/StillLifeTheory.html
        self.decompositions = {"xs18_3pq3qp3": ["xs14_3123qp3", "xs4_33"]}

        # A dict of objects in the form {"identifier": ("common name", points)}
        #
        # As a rough heuristic, an object is worth 15 + log2(n) points if it
        # is n times rarer than the pentadecathlon.
        #
        # Still-lifes are limited to 10 points.
        # p2 oscillators are limited to 20 points.
        # p3 and p4 oscillators are limited to 30 points.
        self.commonnames = {"xp3_co9nas0san9oczgoldlo0oldlogz1047210127401": ("pulsar", 8),
                       "xp15_4r4z4r4": ("pentadecathlon", 15),
                       "xp2_2a54": ("clock", 16),
                       "xp2_31ago": ("bipole", 17),
                       "xp2_0g0k053z32": ("quadpole", 18),
                       "xp2_g8gid1e8z1226": ("great on-off", 19),
                       "xp2_rhewehr": ("spark coil", 19),
                       "xp8_gk2gb3z11": ("figure-8", 20),
                       "xp4_37bkic": ("mold", 21),
                       "xp2_31a08zy0123cko": ("quadpole on ship", 20),
                       "xp2_g0k053z11": ("tripole", 20),
                       "xp4_ssj3744zw3": ("mazing", 23),
                       "xp8_g3jgz1ut": ("blocker", 24),
                       "xp3_695qc8zx33": ("jam", 24),
                       "xp30_w33z8kqrqk8zzzw33": ("cis-queen-bee-shuttle", 24),
                       "xp30_w33z8kqrqk8zzzx33": ("trans-queen-bee-shuttle", 24),
                       "xp4_8eh5e0e5he8z178a707a871": ("cloverleaf", 25),
                       "xp5_idiidiz01w1": ("octagon II", 26),
                       "xp6_ccb7w66z066": ("unix", 26),
                       "xp14_j9d0d9j": ("tumbler", 27),
                       "xp3_025qzrq221": ("trans-tub-eater", 28),
                       "xp3_4hh186z07": ("caterer", 29),
                       "xp3_025qz32qq1": ("cis-tub-eater", 30),
                       "xp8_wgovnz234z33": ("Tim Coe's p8", 31),
                       "xp5_3pmwmp3zx11": ("fumarole", 33),
                       "xp46_330279cx1aad3y833zx4e93x855bc": ("cis-twin-bees-shuttle", 35),
                       "xp46_330279cx1aad3zx4e93x855bcy8cc": ("trans-twin-bees-shuttle", 35),
                       "yl144_1_16_afb5f3db909e60548f086e22ee3353ac": ("block-laying switch engine", 16),
                       "yl384_1_59_7aeb1999980c43b4945fb7fcdb023326": ("glider-producing switch engine", 17),
                       "xp10_9hr": ("[HighLife] p10", 6),
                       "xp7_13090c8": ("[HighLife] p7", 9),
                       "xq48_07z8ca7zy1e531": ("[HighLife] bomber", 9),
                       "xq4_153": ("glider", 0),
                       "xq4_6frc": ("lightweight spaceship", 7),
                       "xq4_27dee6": ("middleweight spaceship", 9),
                       "xq4_27deee6": ("heavyweight spaceship", 12),
                       "xq7_3nw17862z6952": ("loafer", 70),
                       "xp2_7": ("blinker", 0),
                       "xs4_33": ("block", 0),
                       "xs4_252": ("tub", 0),
                       "xs5_253": ("boat", 0),
                       "xs6_bd": ("snake", 0),
                       "xs6_356": ("ship", 0),
                       "xs6_696": ("beehive", 0),
                       "xs6_25a4": ("barge", 0),
                       "xs6_39c": ("carrier", 0),
                       "xp2_7e": ("toad", 0),
                       "xp2_318c": ("beacon", 0),
                       "xs7_3lo": ("long snake", 0),
                       "xs7_25ac": ("long boat", 0),
                       "xs7_178c": ("eater", 0),
                       "xs7_2596": ("loaf", 0),
                       "xs8_178k8": ("twit", 0),
                       "xs8_32qk": ("hook with tail", 0),
                       "xs8_69ic": ("mango", 0),
                       "xs8_6996": ("pond", 0),
                       "xs8_25ak8": ("long barge", 0),
                       "xs8_3pm": ("shillelagh", 0),
                       "xs8_312ko": ("canoe", 0),
                       "xs8_31248c": ("very long snake", 0),
                       "xs8_35ac": ("long ship", 0),
                       "xs12_g8o653z11": ("ship-tie", 0),
                       "xs14_g88m952z121": ("half-bakery", 0),
                       "xs14_69bqic": ("paperclip", 0),
                       "xs9_31ego": ("integral sign", 0),
                       "xs10_g8o652z01": ("boat-tie", 0),
                       "xs14_g88b96z123": ("big ess", 0),
                       "xs16_g88m996z1221": ("bipond", 0),
                       "xs12_raar": ("table on table", 0),
                       "xs9_4aar": ("hat", 0),
                       "xs10_35ako": ("very long ship", 0),
                       "xs9_178ko": ("trans boat with tail", 0),
                       "xs15_354cgc453": ("moose antlers", 0),
                       "xs14_6970796": ("cis-mirrored r-bee", 0),
                       "xs10_32qr": ("block on table", 0),
                       "xs16_j1u0696z11": ("beehive on dock", 0),
                       "xs14_j1u066z11": ("block on dock", 0),
                       "xs11_g8o652z11": ("boat tie ship", 0),
                       "xs9_25ako": ("very long boat", 0),
                       "xs16_69egmiczx1": ("scorpion", 0),
                       "xs18_rhe0ehr": ("dead spark coil", 0),
                       "xs17_2ege1ege2": ("twinhat", 0),
                       "xs10_178kk8": ("beehive with tail", 0),
                       "xs10_69ar": ("loop", 0),
                       "xs14_69bo8a6": ("fourteener", 0),
                       "xs14_39e0e93": ("bookends", 0),
                       "xs9_178kc": ("cis boat with tail", 0),
                       "xs12_330f96": ("block and cap", 0),
                       "xs10_358gkc": ("10.003",0),
                       "xs12_330fho": ("trans block and longhook", 0),
                       "xs10_g0s252z11": ("prodigal sign", 0),
                       "xs11_g0s453z11": ("elevener", 0),
                       "xs14_6is079c": ("cis-rotated hook", 0),
                       "xs14_69e0eic": ("trans-mirrored R-bee", 0),
                       "xs11_ggm952z1": ("trans loaf with tail", 0),
                       "xs15_j1u06a4z11": ("cis boat and dock", 0),
                       "xs20_3lkkl3z32w23": ("mirrored dock", 0),
                       "xs12_178br": ("12.003",0),
                       "xs12_3hu066": ("cis block and longhook", 0),
                       "xs12_178c453": ("eater with nine", 0),
                       "xs10_0drz32": ("broken snake", 0),
                       "xs9_312453": ("long shillelagh", 0),
                       "xs10_3215ac": ("boat with long tail", 0),
                       "xs14_39e0e96": ("cis-hook and R-bee", 0),
                       "xs13_g88m96z121": ("beehive at loaf", 0),
                       "xs14_39e0eic": ("trans hook and R-bee", 0),
                       "xs10_3542ac": ("S-ten", 0),
                       "xs15_259e0eic": ("trans R-bee and R-loaf", 0),
                       "xs11_178jd": ("11-loop", 0),
                       "xs9_25a84c": ("tub with long tail", 0),
                       "xs15_3lkm96z01": ("bee-hat", 0),
                       "xs14_g8o0e96z121": ("cis-rotated R-bee", 0),
                       "xs13_69e0mq": ("R-bee and snake", 0),
                       "xs11_69lic": ("11.003", 0),
                       "xs12_6960ui": ("beehive and table", 0),
                       "xs16_259e0e952": ("cis-mirrored R-loaf", 0),
                       "xs10_1784ko": ("8-snake-eater", 0),
                       "xs13_4a960ui": ("ortho loaf and table", 0),
                       "xs9_g0g853z11": ("long canoe", 0),
                       "xs18_69is0si96": ("[cis-mirrored R-mango]", 0),
                       "xs11_178kic": ("cis loaf with tail", 0),
                       "xs16_69bob96": ("symmetric scorpion", 0),
                       "xs13_0g8o653z121": ("longboat on ship", 0),
                       "xs12_o4q552z01": ("beehive at beehive", 0),
                       "xs10_ggka52z1": ("trans barge with tail", 0),
                       "xs12_256o8a6": ("eater on boat", 0),
                       "xs14_6960uic": ("beehive with cap", 0),
                       "xs12_2egm93": ("snorkel loop", 0),
                       "xs12_2egm96": ("beehive bend tail", 0),
                       "xs11_g0s253z11": ("trans boat with nine", 0),
                       "xs15_3lk453z121": ("trans boat and dock", 0),
                       "xs19_69icw8ozxdd11": ("[mango with block on dock]", 0),
                       "xs13_2530f96": ("[cis boat and cap]", 0),
                       "xs11_2530f9": ("cis boat and table", 0),
                       "xs14_4a9m88gzx121": ("[bi-loaf2]", 0),
                       "xs11_ggka53z1": ("trans longboat with tail", 0),
                       "xs18_2egm9a4zx346": ("[loaf eater tail]", 0),
                       "xs15_4a9raic": ("[15-bent-paperclip]", 0),
                       "xs11_3586246": ("[11-snake]",0),
                       "xs11_178b52": ("[11-boat wrap tail]", 0),
                       "xs14_08u1e8z321": ("[hat join hook]", 0),
                       "xs14_g4s079cz11": ("[cis-mirrored offset hooks]", 0),
                       "xs13_31egma4": ("[13-boat wrap eater]", 0),
                       "xs14_69960ui": ("pond and table", 0),
                       "xs13_255q8a6": ("[eater tie beehive]", 0),
                       "xs15_09v0ccz321": ("[hook join table and block]",0)}

        # First soup to contain a particular object:
        self.alloccur = {}

        # A tally of objects that have occurred during this run of apgsearch:
        self.objectcounts = {}

        # Any soups with positive scores, and the number of points.
        self.soupscores = {}
        
        # Counts of final object totals (per soup)
        self.fots = {}
        
        self.thissoupfot = 0

        # Temporary list of unidentified objects:
        self.unids = []

        # Things like glider guns and large oscillators belong here:
        self.superunids = []
        self.gridsize = 0
        self.resets = 0

        # For profiling purposes:
        self.qlifetime = 0.0
        self.ruletime = 0.0
        self.gridtime = 0.0



    # Increment object count by given value:
    def incobject(self, obj, incval):
        if (incval > 0):
            if obj in self.objectcounts:
                self.objectcounts[obj] = self.objectcounts[obj] + incval
            else:
                self.objectcounts[obj] = incval



    # Increment soup score by given value:
    def awardpoints(self, soupid, incval):
        if (incval > 0):
            if soupid in self.soupscores:
                self.soupscores[soupid] = self.soupscores[soupid] + incval
            else:
                self.soupscores[soupid] = incval



    # Increment soup score by appropriate value:
    def awardpoints2(self, soupid, obj):

        # Record the occurrence of this object:
        if (obj in self.alloccur):
            if (len(self.alloccur[obj]) < 10):
                if (soupid not in self.alloccur[obj]):
                    self.alloccur[obj] += [soupid]
        else:
            self.alloccur[obj] = [soupid]
        
        if obj in self.commonnames:
            self.awardpoints(soupid, self.commonnames[obj][1])
        elif (obj[0] == 'x'):
            prefix = obj.split('_')[0]
            prenum = int(prefix[2:])
            if (obj[1] == 's'):
                self.awardpoints(soupid, min(prenum, 20)) # for still-lifes, award one point per constituent cell (max 20)
            elif (obj[1] == 'p'):
                if (prenum == 2):
                    self.awardpoints(soupid, 20) # p2 oscillators are limited to 20 points
                elif ((prenum == 3) | (prenum == 4)):
                    self.awardpoints(soupid, 30) # p3 and p4 oscillators are limited to 30 points
                else:
                    self.awardpoints(soupid, 40)
            else:
                self.awardpoints(soupid, 50)
        else:
            self.awardpoints(soupid, 60)

    # Increment count of final object total
    def incfots(self, total):
        if total in self.fots:
            self.fots[total] = self.fots[total] + 1
        else:
            self.fots[total] = 1



    # Assuming the pattern has stabilised, perform a census:
    def census(self, stepsize):

        g.setrule("APG_CoalesceObjects_" + self.rg.alphanumeric)
        g.setbase(2)
        g.setstep(stepsize)
        g.step()

        # apgsearch theoretically supports up to 2^14 rules, whereas the Guy
        # glider is only stable in 2^8 rules. Ensure that this is one of these
        # rules by doing some basic Boolean arithmetic.
        #
        # This should be parsed as `gliders exist', not `glider sexist':
        glidersexist = self.rg.ess[2] & self.rg.ess[3] & (not self.rg.ess[1]) & (not self.rg.ess[4])
        glidersexist = glidersexist & (not (self.rg.bee[4] | self.rg.bee[5]))

        if (glidersexist):
            g.setrule("APG_IdentifyGliders")
            g.setbase(2)
            g.setstep(2)
            g.step()

        g.setrule("APG_ClassifyObjects_" + self.rg.alphanumeric)
        g.setbase(2)
        g.setstep(max(8, stepsize))
        g.step()

        # Only do this if we have an infinite-growth pattern:
        if (stepsize > 8):
            g.setrule("APG_HandlePlumesCorrected")
            g.setbase(2)
            g.setstep(1)
            g.step()
            g.setrule("APG_ClassifyObjects_" + self.rg.alphanumeric)
            g.setstep(stepsize)
            g.step()

        # Remove any gliders:
        if (glidersexist):
            g.setrule("APG_ExpungeGliders")
            g.run(1)
            pop5 = int(g.getpop())
            g.run(1)
            pop6 = int(g.getpop())
            self.incobject("xq4_153", (pop5 - pop6)/5)
            self.thissoupfot += (pop5 - pop6)/5

        # Remove any blocks, blinkers and beehives:
        g.setrule("APG_ExpungeObjects")
        pop0 = int(g.getpop())
        g.run(1)
        pop1 = int(g.getpop())
        g.run(1)
        pop2 = int(g.getpop())
        g.run(1)
        pop3 = int(g.getpop())
        g.run(1)
        pop4 = int(g.getpop())

        # Blocks, blinkers and beehives removed by ExpungeObjects:
        self.incobject("xs1_1", (pop0-pop1))
        self.thissoupfot += (pop0-pop1)
        self.incobject("xs4_33", (pop1-pop2)/4)
        self.thissoupfot += (pop1-pop2)/4
        self.incobject("xp2_7", (pop2-pop3)/5)
        self.thissoupfot += (pop2-pop3)/5
        self.incobject("xs6_696", (pop3-pop4)/8)
        self.thissoupfot += (pop3-pop4)/8


    # Removes an object incident with (ix, iy) and returns the cell list:
    def grabobj(self, ix, iy):

        allcells = [ix, iy, g.getcell(ix, iy)]
        g.setcell(ix, iy, 0)
        livecells = []
        deadcells = []

        marker = 0
        ll = 3

        while (marker < ll):
            x = allcells[marker]
            y = allcells[marker+1]
            z = allcells[marker+2]
            marker += 3

            if ((z % 2) == 1):
                livecells.append(x)
                livecells.append(y)
            else:
                deadcells.append(x)
                deadcells.append(y)

            for nx in xrange(x - 1, x + 2):
                for ny in xrange(y - 1, y + 2):

                    nz = g.getcell(nx, ny)
                    if (nz > 0):
                        allcells.append(nx)
                        allcells.append(ny)
                        allcells.append(nz)
                        g.setcell(nx, ny, 0)
                        ll += 3

        return livecells



    # Command to Grab, Remove and IDentify an OBJect:
    def gridobj(self, ix, iy, gsize, gspacing, pos):

        allcells = [ix, iy, g.getcell(ix, iy)]
        g.setcell(ix, iy, 0)
        livecells = []
        deadcells = []

        # This tacitly assumes the object is smaller than 1000-by-1000.
        # But this is okay, since it is only used by the routing logic.
        dleft = ix + 1000
        dright = ix - 1000
        dtop = iy + 1000
        dbottom = iy - 1000

        lleft = ix + 1000
        lright = ix - 1000
        ltop = iy + 1000
        lbottom = iy - 1000

        lpop = 0
        dpop = 0

        marker = 0
        ll = 3

        while (marker < ll):
            x = allcells[marker]
            y = allcells[marker+1]
            z = allcells[marker+2]
            marker += 3

            if ((z % 2) == 1):
                livecells.append(x)
                livecells.append(y)
                lleft = min(lleft, x)
                lright = max(lright, x)
                ltop = min(ltop, y)
                lbottom = max(lbottom, y)
                lpop += 1
            else:
                deadcells.append(x)
                deadcells.append(y)
                dleft = min(dleft, x)
                dright = max(dright, x)
                dtop = min(dtop, y)
                dbottom = max(dbottom, y)
                dpop += 1

            for nx in xrange(x - 1, x + 2):
                for ny in xrange(y - 1, y + 2):

                    nz = g.getcell(nx, ny)
                    if (nz > 0):
                        allcells.append(nx)
                        allcells.append(ny)
                        allcells.append(nz)
                        g.setcell(nx, ny, 0)
                        ll += 3

        lwidth = max(0, 1 + lright - lleft)
        lheight = max(0, 1 + lbottom - ltop)
        dwidth = max(0, 1 + dright - dleft)
        dheight = max(0, 1 + dbottom - dtop)

        llength = max(lwidth, lheight)
        lbreadth = min(lwidth, lheight)
        dlength = max(dwidth, dheight)
        dbreadth = min(dwidth, dheight)

        self.gridsize = max(self.gridsize, llength)

        objid = "unidentified"
        bitstring = 0

        if (lpop == 0):
            objid = "nothing"
        else:
            if ((lwidth <= 7) & (lheight <= 7)):
                for i in xrange(0, lpop*2, 2):
                    bitstring += (1 << ((livecells[i] - lleft) + 7*(livecells[i + 1] - ltop)))

                if bitstring in self.cache:
                    objid = self.cache[bitstring]

        if (objid == "unidentified"):
            # This has passed through the routing logic without being identified,
            # so save it in a temporary list for later identification:
            self.unids.append(bitstring)
            self.unids.append(livecells)
            self.unids.append(lleft)
            self.unids.append(ltop)
        elif (objid != "nothing"):
            # The object is non-empty, so add it to the census:
            ux = int(0.5 + float(lleft)/float(gspacing))
            uy = int(0.5 + float(ltop)/float(gspacing))
            soupid = ux + (uy * gsize) + pos

            # Check whether the cached object is in the set of decompositions
            # (this is usually the case, unless for example it is a high-period
            # albeit small spaceship):
            if objid in self.decompositions:            
                for comp in self.decompositions[objid]:
                    self.incobject(comp, 1)
                    self.thissoupfot += 1
                    self.awardpoints2(soupid, comp)
            else:
                self.incobject(objid, 1)
                self.thissoupfot += 1
                self.awardpoints2(soupid, objid)




    # Tests for population periodicity:
    def naivestab(self, period, security, length):

        depth = 0
        prevpop = 0
        for i in xrange(length):
            g.run(period)
            currpop = int(g.getpop())
            if (currpop == prevpop):
                depth += 1
            else:
                depth = 0
            prevpop = currpop
            if (depth == security):
                # Population is periodic.
                return True

        return False



    # This should catch most short-lived soups with few gliders produced:
    def naivestab2(self, period, length):

        for i in xrange(length):
            r = g.getrect()
            if (len(r) == 0):
                return True
            pop0 = int(g.getpop())
            g.run(period)
            hash1 = g.hash(r)
            pop1 = int(g.getpop())
            g.run(period)
            hash2 = g.hash(r)
            pop2 = int(g.getpop())

            if ((hash1 == hash2) & (pop0 == pop1) & (pop1 == pop2)):

                if (g.getrect() == r):
                    return True
                
                g.run((2*int(max(r[2], r[3])/period)+1)*period)
                hash3 = g.hash(r)
                pop3 = int(g.getpop())
                if ((hash2 == hash3) & (pop2 == pop3)):
                    return True

        return False
           


    # Runs a pattern until stabilisation with a 99.99996% success rate.
    # False positives are handled by a later error-correction stage.
    def stabilise3(self):

        # Phase I of stabilisation detection, designed to weed out patterns
        # that stabilise into a cluster of low-period oscillators within
        # about 6000 generations.

        if (self.naivestab2(12, 10)):
            return 4;

        if (self.naivestab(12, 30, 200)):
            return 4;

        if (self.naivestab(30, 30, 200)):
            return 5;

        # Phase II of stabilisation detection, which is much more rigorous
        # and based on oscar.py.

        # Should be sufficient:
        prect = [-2000, -2000, 4000, 4000]

        # initialize lists
        hashlist = []        # for pattern hash values
        genlist = []         # corresponding generation counts

        for j in xrange(4000):

            g.run(30)

            h = g.hash(prect)

            # determine where to insert h into hashlist
            pos = 0
            listlen = len(hashlist)
            while pos < listlen:
                if h > hashlist[pos]:
                    pos += 1
                elif h < hashlist[pos]:
                    # shorten lists and append info below
                    del hashlist[pos : listlen]
                    del genlist[pos : listlen]
                    break
                else:
                    period = (int(g.getgen()) - genlist[pos])

                    prevpop = g.getpop()

                    for i in xrange(20):
                        g.run(period)
                        currpop = g.getpop()
                        if (currpop != prevpop):
                            period = max(period, 4000)
                            break
                        prevpop = currpop
                        
                    return max(1 + int(math.log(period, 2)),3)

            hashlist.insert(pos, h)
            genlist.insert(pos, int(g.getgen()))

        g.setalgo("HashLife")
        g.setrule(self.rg.slashed)
        g.setbase(2)
        g.setstep(16)
        g.step()
        stepsize = 12
        g.setalgo("QuickLife")
        g.setrule(self.rg.slashed)

        return 12



    # Differs from oscar.py in that it detects absolute cycles, not eventual cycles.
    def bijoscar(self, maxsteps):

        initpop = int(g.getpop())
        initrect = g.getrect()
        if (len(initrect) == 0):
            return 0
        inithash = g.hash(initrect)

        for i in xrange(maxsteps):

            g.run(1)

            if (int(g.getpop()) == initpop):

                prect = g.getrect()
                phash = g.hash(prect)

                if (phash == inithash):

                    period = i + 1

                    if (prect == initrect):
                        return period
                    else:
                        return -period
        return -1



    # For a non-moving unidentified object, we check the dictionary of
    # memoized decompositions of possibly-pseudo-objects. If the object is
    # not already in the dictionary, it will be memoized.
    #
    # Low-period spaceships are also separated by this routine, although
    # this is less important now that there is a more bespoke prodecure
    # to handle disjoint unions of standard spaceships.
    #
    # @param moving  a bool which specifies whether the object is moving
    def enter_unid(self, unidname, soupid, moving):

        if not(unidname in self.decompositions):

            # Separate into pure components:
            if (moving):
                g.setrule("APG_CoalesceObjects_" + self.rg.alphanumeric)
                g.setbase(2)
                g.setstep(3)
                g.step()
            else:
                pseudo_bangbang(self.rg.alphanumeric)

            listoflists = [] # which incidentally don't contain themselves.

            # Someone who plays the celllo:
            celllist = g.join(g.getcells(g.getrect()), [0])

            for i in xrange(0, len(celllist)-1, 3):
                if (g.getcell(celllist[i], celllist[i+1]) != 0):
                    livecells = self.grabobj(celllist[i], celllist[i+1])
                    if (len(livecells) > 0):
                        listoflists.append(livecells)

            listofobjs = []

            for livecells in listoflists:

                g.new("Subcomponent")
                g.setalgo("QuickLife")
                g.setrule(self.rg.slashed)
                g.putcells(livecells)
                period = self.bijoscar(1000)
                canonised = canonise(abs(period))
                if (period < 0):
                    listofobjs.append("xq"+str(0-period)+"_"+canonised)
                elif (period == 1):
                    listofobjs.append("xs"+str(len(livecells)/2)+"_"+canonised)
                else:
                    listofobjs.append("xp"+str(period)+"_"+canonised)

            self.decompositions[unidname] = listofobjs

        # Actually add to the census:
        for comp in self.decompositions[unidname]:
            self.incobject(comp, 1)
            self.thissoupfot += 1
            self.awardpoints2(soupid, comp)



    # This function has lots of arguments (hence the name):
    #
    # @param gsize     the square-root of the number of soups per page
    # @param gspacing  the minimum distance between centres of soups
    # @param ashes     a list of cell lists
    # @param stepsize  binary logarithm of amount of time to coalesce objects
    # @param intergen  binary logarithm of amount of time to run HashLife
    # @param pos       the index of the first soup on the page
    def teenager(self, gsize, gspacing, ashes, stepsize, intergen, pos):

        # For error-correction:
        if (intergen > 0):
            g.setalgo("HashLife")
            g.setrule(self.rg.slashed)

        # If this gets incremented, we panic and perform error-correction:
        pathological = 0

        # Draw the soups:
        for i in xrange(gsize * gsize):

            x = int(i % gsize)
            y = int(i / gsize)

            g.putcells(ashes[3*i], gspacing * x, gspacing * y)

        # Because why not?
        #g.fit()
        #g.update()

        # For error-correction:
        if (intergen > 0):
            g.setbase(2)
            g.setstep(intergen)
            g.step()

        # Apply rules to coalesce objects and expunge annoyances such as
        # blocks, blinkers, beehives and gliders:
        start_time = time.clock()
        self.census(stepsize)
        end_time = time.clock()
        self.ruletime += (end_time - start_time)

        # Now begin identifying objects:
        start_time = time.clock()
        celllist = g.join(g.getcells(g.getrect()), [0])

        if (len(celllist) > 2):
            for i in xrange(0, len(celllist)-1, 3):
                if (g.getcell(celllist[i], celllist[i+1]) != 0):
                    self.gridobj(celllist[i], celllist[i+1], gsize, gspacing, pos)

        # If we have leftover unidentified objects, attempt to canonise them:
        while (len(self.unids) > 0):
            ux = int(0.5 + float(self.unids[-2])/float(gspacing))
            uy = int(0.5 + float(self.unids[-1])/float(gspacing))
            soupid = ux + (uy * gsize) + pos
            unidname = self.process_unid()
            if (unidname == "PATHOLOGICAL"):
                pathological += 1
            if (unidname != "nothing"):

                if ((unidname[0] == 'U') & (unidname[1] == 'S') & (unidname[2] == 'S')):
                    
                    # Union of standard spaceships:
                    countlist = unidname.split('_')
                    
                    self.incobject("xq4_6frc", int(countlist[1]))
                    self.thissoupfot += int(countlist[1])
                    for i in xrange(int(countlist[1])):
                        self.awardpoints2(soupid, "xq4_6frc")

                    self.incobject("xq4_27dee6", int(countlist[2]))
                    self.thissoupfot += int(countlist[2])
                    for i in xrange(int(countlist[2])):
                        self.awardpoints2(soupid, "xq4_27dee6")
                        
                    self.incobject("xq4_27deee6", int(countlist[3]))
                    self.thissoupfot += int(countlist[3])
                    for i in xrange(int(countlist[3])):
                        self.awardpoints2(soupid, "xq4_27deee6")
                        
                elif ((unidname[0] == 'x') & ((unidname[1] == 's') | (unidname[1] == 'p'))):
                    self.enter_unid(unidname, soupid, False)
                else:
                    if ((unidname[0] == 'x') & (unidname[1] == 'q') & (unidname[3] == '_')):
                        # Separates low-period (<= 9) non-standard spaceships in medium proximity:
                        self.enter_unid(unidname, soupid, True)
                    else:
                        self.incobject(unidname, 1)
                        self.thissoupfot += 1
                        self.awardpoints2(soupid, unidname)

        end_time = time.clock()
        self.gridtime += (end_time - start_time)

        return pathological



    def stabilise_soups_parallel(self, root, pos, gsize, sym):

        souplist = [[sym, root + str(pos + i)] for i in xrange(gsize * gsize)]

        self.stabilise_soups_parallel_orig(gsize, souplist, pos)


    def stabilise_soups_parallel_list(self, gsize, stringlist, pos):

        souplist = [s.split('/') for s in stringlist]

        self.stabilise_soups_parallel_orig(gsize, souplist, pos)


    # This basically orchestrates everything:
    def stabilise_soups_parallel_orig(self, gsize, souplist, pos):

        ashes = []
        stepsize = 3

        g.new("Random soups")
        g.setalgo("QuickLife")
        g.setrule(self.rg.slashed)

        gspacing = 0

        # Generate and run the soups until stabilisation:
        for i in xrange(gsize * gsize):

            if (i < len(souplist)):

                sym = souplist[i][0]
                prehash = souplist[i][1]

                # Generate the soup from the SHA-256 of the concatenation of the
                # seed with the index:
                g.putcells(hashsoup(prehash, sym), 0, 0)

            # Run the soup until stabilisation:
            start_time = time.clock()
            stepsize = max(stepsize, self.stabilise3())
            end_time = time.clock()
            self.qlifetime += (end_time - start_time)

            # Ironically, the spelling of this variable is incurrrect:
            currrect = g.getrect()
            ashes.append(g.getcells(currrect))

            if (len(currrect) == 4):
                ashes.append(currrect[0])
                ashes.append(currrect[1])
                # Choose the grid spacing based on the size of the ash:
                gspacing = max(gspacing, 2*currrect[2])
                gspacing = max(gspacing, 2*currrect[3])
                g.select(currrect)
                g.clear(0)
            else:
                ashes.append(0)
                ashes.append(0)
            g.select([])

        # Account for any extra enlargement caused by running CoalesceObjects:
        gspacing += 2 ** (stepsize + 1) + 1000

        # Remember the dictionary, just in case we have a pathological object:
        prevdict = self.objectcounts.copy()
        prevfots = self.fots.copy()
        prevscores = self.soupscores.copy()
        prevunids = self.superunids[:]

        # Process the soups:
        returncode = self.teenager(gsize, gspacing, ashes, stepsize, 0, pos)

        if (returncode > 0):
            if (self.skipErrorCorrection == False):
                # Arrrggghhhh, there's a pathological object! Usually this means
                # that naive stabilisation detection returned a false positive.
                self.resets += 1
                
                # Reset the object counts:
                self.objectcounts = prevdict
                self.fots = prevfots
                self.soupscores = prevscores
                self.superunids = prevunids

                # 2^18 generations should suffice. This takes about 30 seconds in
                # HashLife, but error-correction only occurs very infrequently, so
                # this has a negligible impact on mean performance:
                gspacing += 2 ** 19
                stepsize = max(stepsize, 12)
                
                # Clear the universe:
                g.new("Error-correcting phase")
                self.teenager(gsize, gspacing, ashes, stepsize, 18, pos)

        # Erase any ashes. Not least because England usually loses...
        ashes = []



    def reset(self):

        self.objectcounts = {}
        self.soupscores = {}
        self.fots = {}
        self.alloccur = {}
        self.superunids = []
        self.unids = []



    # Pop the last unidentified object from the stack, and attempt to
    # ascertain its period and classify it.
    def process_unid(self):

        g.new("Unidentified object")
        g.setalgo("QuickLife")
        g.setrule(self.rg.slashed)
        y = self.unids.pop()
        x = self.unids.pop()
        livecells = self.unids.pop()
        bitstring = self.unids.pop()
        g.putcells(livecells, -x, -y, 1, 0, 0, 1, "or")
        period = self.bijoscar(1000)
        
        if (period == -1):
            # Infinite growth pattern, probably. Most infinite-growth
            # patterns are linear-growth (such as puffers, wickstretchers,
            # guns etc.) so we analyse to see whether we have a linear-
            # growth pattern:
            descriptor = linearlyse(1500)
            if (descriptor[0] == "y"):
                return descriptor

            # Similarly check for irregular power-law growth. This will
            # catch replicators, for instance. Spend around 375 000
            # generations; this seems like a reasonable amount of time.
            descriptor = powerlyse(8, 1500)
            if (descriptor[0] == "z"):
                return descriptor

            # It may be an unstabilised ember that slipped through the net,
            # but this will be handled by error-correction (unless it
            # persists another 2^18 gens, which is so unbelievably improbable
            # that you are more likely to be picked up by a passing ship in
            # the vacuum of space).
            self.superunids.append(livecells)
            self.superunids.append(x)
            self.superunids.append(y)
            
            return "PATHOLOGICAL"
        elif (period == 0):
            return "nothing"
        else:
            if (period == -4):

                triple = countxwsses()

                if (triple != (-1, -1, -1)):

                    # Union of Standard Spaceships:
                    return ("USS_" + str(triple[0]) + "_" + str(triple[1]) + "_" + str(triple[2]))

            
            canonised = canonise(abs(period))

            if (canonised == "#"):

                # Okay, we know that it's an oscillator or spaceship with
                # a non-astronomical period. But it's too large to canonise
                # in any of its phases (i.e. transcends a 40-by-40 box).
                self.superunids.append(livecells)
                self.superunids.append(x)
                self.superunids.append(y)
                
                # Append a suffix according to whether it is a still-life,
                # oscillator or moving object:
                if (period == 1):
                    descriptor = ("ov_s"+str(len(livecells)/2))
                elif (period > 0):
                    descriptor = ("ov_p"+str(period))
                else:
                    descriptor = ("ov_q"+str(0-period))

                return descriptor
            
            else:

                # Prepend a prefix according to whether it is a still-life,
                # oscillator or moving object:
                if (period == 1):
                    descriptor = ("xs"+str(len(livecells)/2)+"_"+canonised)
                elif (period > 0):
                    descriptor = ("xp"+str(period)+"_"+canonised)
                else:
                    descriptor = ("xq"+str(0-period)+"_"+canonised)

                if (bitstring > 0):
                    self.cache[bitstring] = descriptor

                return descriptor



    # This doesn't really do much, since unids should be empty and
    # actual pathological/oversized objects will rarely arise naturally.
    def display_unids(self):

        g.new("Unidentified objects")
        g.setalgo("QuickLife")
        g.setrule(self.rg.slashed)

        rowlength = 1 + int(math.sqrt(len(self.superunids)/3))

        for i in xrange(len(self.superunids)/3):

            xpos = i % rowlength
            ypos = int(i / rowlength)

            g.putcells(self.superunids[3*i], xpos * (self.gridsize + 8) - self.superunids[3*i + 1], ypos * (self.gridsize + 8) - self.superunids[3*i + 2], 1, 0, 0, 1, "or")

        g.fit()
        g.update()



    def compactify_scores(self):

        # Number of soups to record:
        highscores = 100
        ilist = sorted(self.soupscores.iteritems(), key=operator.itemgetter(1), reverse=True)

        # Empty the high score table:
        self.soupscores = {}
        
        for soupnum, score in ilist[:highscores]:
            self.soupscores[soupnum] = score



    # Saves a machine-readable textual file containing the census:
    def save_progress(self, numsoups, root, symmetry='C1', save_file=True, payosha256_key=None):

        g.show("Saving progress...")

        # Count the total number of objects:
        totobjs = 0
        censustable = "@CENSUS TABLE\n"
        tlist = sorted(self.objectcounts.iteritems(), key=operator.itemgetter(1), reverse=True)
        for objname, count in tlist:
            totobjs += count
            censustable += objname + " " + str(count) + "\n"

        g.show("Writing header information...")

        # The MD5 hash of the root string:
        md5root = hashlib.md5(root).hexdigest()

        # Header information:
        results = "@VERSION v1.1\n"
        results += "@MD5 "+md5root+"\n"
        results += "@ROOT "+root+"\n"
        results += "@RULE "+self.rg.alphanumeric+"\n"
        results += "@SYMMETRY "+symmetry+"\n"
        results += "@NUM_SOUPS "+str(numsoups)+"\n"
        results += "@NUM_OBJECTS "+str(totobjs)+"\n"

        results += "\n"

        # Census table:
        results += censustable

        g.show("Compactifying score table...")

        results += "\n"

        # Number of soups to record:
        highscores = 100

        results += "@TOP "+str(highscores)+"\n"

        ilist = sorted(self.soupscores.iteritems(), key=operator.itemgetter(1), reverse=True)

        # Empty the high score table:
        self.soupscores = {}
        
        for soupnum, score in ilist[:highscores]:
            self.soupscores[soupnum] = score
            results += str(soupnum) + " " + str(score) + "\n"

        g.show("Saving soupids for rare objects...")

        results += "\n@SAMPLE_SOUPIDS\n"
        for objname, count in tlist:
            # blinkers and gliders have no alloccur[] entry for some reason,
            # so the line below avoids errors in B3/S23, maybe other rules too?
            if objname in self.alloccur:
                results += objname
                for soup in self.alloccur[objname]:
                    results += " " + str(soup)
                results += "\n"
                
        results += "\n@FINAL_OBJECT_TOTALS\n"
        fotlist = sorted(self.fots.iteritems(), key=operator.itemgetter(0), reverse=False)
        for fot, count in fotlist:
            results += str(fot) + "," + str(count) + "\n"    
        

        g.show("Writing progress file...")

        dirname = g.getdir("data")
        separator = dirname[-1]
        progresspath = dirname + "apgsearch" + separator + "progress" + separator
        if not os.path.exists(progresspath):
            os.makedirs(progresspath)

        filename = progresspath + "search_" + md5root + ".txt"
        
        try:
            f = open(filename, 'w')
            f.write(results)
            f.close()
        except:
            g.warn("Unable to create progress file:\n" + filename)



    # Save soup RLE:
    def save_soup(self, root, soupnum, symmetry):

        # Soup pattern will be stored in a temporary directory:
        souphash = hashlib.sha256(root + str(soupnum))
        rlepath = souphash.hexdigest()
        rlepath = g.getdir("temp") + rlepath + ".rle"
        
        results = "<a href=\"open:" + rlepath + "\">"
        results += str(soupnum)
        results += "</a>"

        # Try to write soup patterns to file "rlepath":
        try:
            g.store(hashsoup(root + str(soupnum), symmetry), rlepath)
        except:
            g.warn("Unable to create soup pattern:\n" + rlepath)

        return results
 
 
        
    # Display results in Help window:
    def display_census(self, numsoups, root, symmetry):

        dirname = g.getdir("data")
        separator = dirname[-1]
        apgpath = dirname + "apgsearch" + separator
        objectspath = apgpath + "objects" + separator + self.rg.alphanumeric + separator
        if not os.path.exists(objectspath):
            os.makedirs(objectspath)

        results = "<html>\n<title>Census results</title>\n<body bgcolor=\"#FFFFCE\">\n"
        results += "<p>Census results after processing " + str(numsoups) + " soups (seed = " + root + ", symmetry = " + symmetry + "):\n"

        tlist = sorted(self.objectcounts.iteritems(), key=operator.itemgetter(1), reverse=True)    
        results += "<p><center>\n"
        results += "<table cellspacing=1 border=2 cols=2>\n"
        results += "<tr><td>&nbsp;Object&nbsp;</td><td align=center>&nbsp;Common name&nbsp;</td>\n"
        results += "<td align=right>&nbsp;Count&nbsp;</td><td>&nbsp;Sample occurrences&nbsp;</td></tr>\n"
        for objname, count in tlist:
            if (objname[0] == 'x'):
                if (objname[1] == 'p'):
                    results += "<tr bgcolor=\"#CECECF\">"
                elif (objname[1] == 'q'):
                    results += "<tr bgcolor=\"#CEFFCE\">"
                else:
                    results += "<tr>"
            else:
                results += "<tr bgcolor=\"#FFCECE\">"
            results += "<td>"
            results += "&nbsp;"
            
            # Using "open:" link enables one to click on the object name to open the pattern in Golly:
            rlepath = objectspath + objname + ".rle"
            if (objname[0] == 'x'):
                results += "<a href=\"open:" + rlepath + "\">"
            # If the name is longer than that of the block-laying switch engine:
            if len(objname) > 51:
                # Contract name and include ellipsis:
                results += objname[:40] + "&#8230;" + objname[-10:]
            else:
                results += objname
            if (objname[0] == 'x'):
                results += "</a>"
            results += "&nbsp;"

            if (objname[0] == 'x'):
                # save object in rlepath if it doesn't exist
                if not os.path.exists(rlepath):
                    # Canonised objects are at most 40-by-40:
                    rledata = "x = 40, y = 40, rule = " + self.rg.slashed + "\n"
                    # http://ferkeltongs.livejournal.com/15837.html
                    compact = objname.split('_')[1] + "z"
                    i = 0
                    strip = []
                    while (i < len(compact)):
                        c = ord2(compact[i])
                        if (c >= 0):
                            if (c < 32):
                                # Conventional character:
                                strip.append(c)
                            else:
                                if (c == 35):
                                    # End of line:
                                    if (len(strip) == 0):
                                        strip.append(0)
                                    for j in xrange(5):
                                        for d in strip:
                                            if ((d & (1 << j)) > 0):
                                                rledata += "o"
                                            else:
                                                rledata += "b"
                                        rledata += "$\n"
                                    strip = []
                                else:
                                    # Multispace character:
                                    strip.append(0)
                                    strip.append(0)
                                    if (c >= 33):
                                        strip.append(0)
                                    if (c == 34):
                                        strip.append(0)
                                        i += 1
                                        d = ord2(compact[i])
                                        for j in xrange(d):
                                            strip.append(0)
                        i += 1
                    # End of pattern representation:
                    rledata += "!\n"
                    try:
                        f = open(rlepath, 'w')
                        f.write(rledata)
                        f.close()
                    except:
                        g.warn("Unable to create object pattern:\n" + rlepath)
            
            results += "</td><td align=center>&nbsp;"
            if (objname in self.commonnames):
                results += self.commonnames[objname][0]
            results += "&nbsp;</td><td align=right>&nbsp;" + str(count) + "&nbsp;"
            results += "</td><td>"
            if objname in self.alloccur:
                results += "&nbsp;"
                for soup in self.alloccur[objname]:
                    results += self.save_soup(root, soup, symmetry) 
                    results += "&nbsp;"
            results += "</td></tr>\n"
        results += "</table>\n</center>\n"

        ilist = sorted(self.soupscores.iteritems(), key=operator.itemgetter(1), reverse=True)
        results += "<p><center>\n"
        results += "<table cellspacing=1 border=2 cols=2>\n"
        results += "<tr><td>&nbsp;Soup number&nbsp;</td><td align=right>&nbsp;Score&nbsp;</td></tr>\n"
        for soupnum, score in ilist[:50]:
            results += "<tr><td>&nbsp;"
            results += self.save_soup(root, soupnum, symmetry)
            results += "&nbsp;</td><td align=right>&nbsp;" + str(score) + "&nbsp;</td></tr>\n"
        
        results += "</table>\n</center>\n"
        results += "</body>\n</html>\n"
        
        htmlname = apgpath + "latest_census.html"
        try:
            f = open(htmlname, 'w')
            f.write(results)
            f.close()
            g.open(htmlname)
        except:
            g.warn("Unable to create html file:\n" + htmlname)
        


# Converts a base-36 case-insensitive alphanumeric character into a
# numerical value.
def ord2(char):

    x = ord(char)

    if ((x >= 48) & (x < 58)):
        return x - 48

    if ((x >= 65) & (x < 91)):
        return x - 55

    if ((x >= 97) & (x < 123)):
        return x - 87

    return -1



def apg_main():

    numberofsoups = int(g.getstring("How many soups to census?", "1000000"))
    rulestring = "B3/S23"
    symmstring = "C1"
    payoshakey = "#anon"

    # Create associated rule tables:
    soup = Soup()
    soup.rg.setrule(rulestring)
    soup.rg.saveAllRules()

    # Initialise the census:
    start_time = time.clock()
    f = (lambda x : 'abcdefghijkmnpqrstuvwxyzABCDEFGHJKLMNPQRSTUVWXYZ23456789'[ord(x) % 56])
    rootstring = ''.join(map(f, list(hashlib.sha256(payoshakey + datetime.datetime.now().isoformat()).digest()[:12])))
    scount = 0
    forcequit = False


    for i in xrange(numberofsoups):
    	
    	if (i % 100 == 0 ):
    		g.show(str(scount) + " soups processed")

        soup.stabilise_soups_parallel(rootstring, scount, 1, symmstring)
        
        soup.incfots(soup.thissoupfot)
        soup.thissoupfot = 0

        scount += 1
        
        event = g.getevent()
        if event.startswith("key"):
            evt, ch, mods = event.split()
            if ch == "q":
            	forcequit = True
                break


    soup.save_progress(scount, rootstring, symmstring)

    soup.display_unids()
    soup.display_census(scount, rootstring, symmstring)
    
    end_time = time.clock()
    
    total_time = int(end_time - start_time)
    speed = float(int(scount / total_time * 10))/10
    
    if (forcequit):
    	g.show("Run terminated (" + str(scount) + " soups completed) after " + str(total_time) + " seconds (" + str(speed) + " soups/sec)")
    else:
        g.show("Run complete (" + str(scount) + " soups) in " + str(total_time) + " seconds (" + str(speed) + " soups/sec)")


# Run the soup-searching script:
apg_main()

Hunting
Posts: 2949
Joined: September 11th, 2017, 2:54 am

Re: Hacking apgsearch

Post by Hunting » April 11th, 2020, 12:36 pm

Sorry for reviving this old thread.

Can anyone provide me a v1.0 version of the slow-salvo modification? I'm having trouble understanding the soup generator.
MLP will live on forever, so does John Horton Conway.
Moosey wrote:
February 5th, 2019, 7:51 pm
“New knightship tagalong!”
“Quick, hide it!”
My TODO list

LeapLife - DirtyLife - LispLife

I could make a rule in ten seconds flat

yujh
Posts: 977
Joined: February 27th, 2020, 11:23 pm
Location: China
Contact:

Re: Hacking apgsearch

Post by yujh » May 9th, 2020, 8:19 am

Anyone interested in this?(totally for newers, maybe)
https://conwaylife.com/ref/DRH/digits.html#spaceships
I would like to request an APGsearch like search which works for this(int rules needed)
Only c1 now(you need to say how many numbers you want, though)!!!
Soup should be saved as numbers.
B34kz5e7c8/S23-a4ityz5k!!!
Mission: find a rule with 2-5ob,7-15d,3-5o ships and 4 sparky hp osc.
B2ikn35j6i/S23-a8

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