for i1,i2 in d:
mtx[i1,i2] = 1
mtx[i2,i1] = 1
for i in range(256):
mtx[i,i] = 1
return mtx
def show_nonlinear(d):
print ("Linear automata are:", list(sorted(linear_automata)))
noticed = set()
for i1,i2 in d:
if i1 == 0 or i2 == 255: continue
if i1 in shift_automata or i2 in shift_automata: continue
if i1 not in linear_automata or i2 not in linear_automata:
print (i1, i2)
noticed.add(i1)
noticed.add(i2)
print ("All noticed automata:", list(sorted(noticed)))
if __name__=="__main__":
d = load_data("time2d_compatible_automata.csv")
#show_nonlinear(d)
pp.matshow(as_matrix(d))
pp.show()
from matplotlib import pyplot as pp
from collections import Counter
import json
from elementary_ca import is_linear, index2table, is_additive, table2index, mirror_ca
from time2d_ca import load_data
import os.path
mapped = dict()
all_pairs = set()
for a, b in load_data("time2d_compatible_automata.csv"):
all_pairs.add((a,b))
all_pairs.add((b,a))
akey = "%x"%a
bkey = "%x"%b
try:
a_rules = mapped[akey]
except KeyError:
a_rules = dict()
mapped[akey] = a_rules
a_rules[bkey] = 1
rule_props = dict()
byNumberOfDuals = Counter()
for rule in range(256):
rtable = index2table(rule)
