apaap

class LCA:
    """Simulate the Linear CA (XOR CA rule) known as Rule 90 on a circular grid
    Usage: l = LCA(width) OR l = LCA(width, rule)
    where width is an integer > 1 and rule is one of [18, 90, 150]"""
    
    maxbuf = 8
    
    def __init__(self, width, rule=90):
        if rule == 18:
            self.stepfun = LCA.step18

apaap

#p392_pairs.py
# c/98 spaceship generator
# Usage: python p392_pairs.py [<start> [<stop>]]
# where <start> is the starting value and <stop> is the final value for the
# phase of the LHS (default is 0 <= phase < 196)
#
# Example usage with apgluxe:
# $ cd apgmera
# $ ./recompile.sh --rule b2k3acijr4ijqy6i7cs2aek3ijnqr4it5n --symmetry stdin_c98_pairs
# $ mv apgluxe apgluxe-stdin_c98_pairs

apaap

#sort-collisions.py
# Read in unsorted glider collisions lines from all files on command line
# Output sorted collisions to first file in synthesise-constellation.py format
# Collisions are in a modified version of Shinjuku's component format:
#   - single line containing apgcode of output constellation, followed by
#   - multiple lines containing components producing that constellation with
#     the out_apgcode omitted
# Input files can be in either format

# For Python3 print function

apaap

#4Gconstellation-gsets.py
"""Generate a batch of 4 glider collisions and report those which result
in stable constellations. Converts collisions to Shinjuku's gliderset format
and outputs comp lines. This version generates a subset of 4G collisions for
use with synthesise-constelation.py v2.0
Usage:
$ python 4Gconstellation-gsets.py > <compfile>.sjk

Based on popseq.c by Chris Cain
Includes a (slightly modified) version of shinjuku/glidersets.py and the

apaap

#include <iostream>
#include <cstring>
#include "LifeAPI.h"

int main(int argc, char *argv[]) {

    int pops[16], allpops[256];
    char s[1024], line[1024];
    s[0] = 0;

apaap

#count_active.py
# Count active cells within the envelope of a moving pattern
import golly as g
import numpy as np

r = g.getrect()
if not r:
  g.exit('No pattern')
patt = g.getcells(r)

apaap

#!/usr/bin/python

import re
import sys
import argparse

def fail(msg):
    sys.stderr.write(sys.argv[0] + ": " + msg + "\n")
    sys.exit(1)

apaap

# sssViewer.py v0.3
# Golly Python script to peview patterns in sss format
# Author: Arie Paap

import re
import time
from timeit import default_timer as timer 
import golly as g

# Check if pattern is in view and shift view / resize if necessary

apaap

# Random State Distribution

A rule generator for Golly to create a random state distributor rule
The rule is intended to convert a two state random soup pattern into an n-state random soup. The rule has (n+1)-states where the additional state is state 1. All state 1 cells will become cells with state 2 -> n after the first generation, with the resulting state being dependent on the neighbourhood configuration of the cell.
This could potentially be used with apgsearch to generate multi-state soups in rules where 2-sate soups don't show the full dynamics of the rule.

This project contains three separate files:
- rand_state_distribution.py
    A Golly Python script to generate a rule file (can be run from clipboard).
- test_rand_state_distribution.py