from cgp import Cgp
row = 1
col = 40
lback = 40
pop = 5
mut = 3
acc = 0.01
gen = 2000
print("Test: 1")
print("Benchmark Obvodu")
cgp = Cgp(row, col, lback)
cgp.file("../../data/adder3_3.txt")
cgp.run(gen, pop, mut)
print("adder 3+3 (64)", cgp.result["evalspersec"], "evals/sec")
cgp = Cgp(row, col, lback)
cgp.file("../../data/adder4_4.txt")
cgp.run(gen, pop, mut)
print("adder 4+4 (256)", cgp.result["evalspersec"], "evals/sec")
cgp = Cgp(row, col, lback)
cgp.file("../../data/adder5_5.txt")
cgp.run(gen, pop, mut)
print("adder 5+5 (1024)", cgp.result["evalspersec"], "evals/sec")
cgp = Cgp(row, col, lback)
cgp.file("../../data/adder6_6.txt")
cgp.run(gen, pop, mut)
print("adder 6+6 (4096)", cgp.result["evalspersec"], "evals/sec")
0xffffffffffffffffffffffffffffffff00000000000000000000000000000000,
0xffffffffffffffff0000000000000000ffffffffffffffff0000000000000000,
0xffffffff00000000ffffffff00000000ffffffff00000000ffffffff00000000,
0xffff0000ffff0000ffff0000ffff0000ffff0000ffff0000ffff0000ffff0000,
0xff00ff00ff00ff00ff00ff00ff00ff00ff00ff00ff00ff00ff00ff00ff00ff00,
0xf0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0f0,
0xcccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc,
0xaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
]
output = [
0xfffefffcfff8fff0ffe0ffc0ff80ff00fe00fc00f800f000e000c00080000000,
0xfe01fc03f807f00fe01fc03f807f00ff01fe03fc07f80ff01fe03fc07f80ff00,
0xe1e1c3c387870f0f1e1e3c3c7878f0f0e1e1c3c387870f0f1e1e3c3c7878f0f0,
0x999933336666cccc999933336666cccc999933336666cccc999933336666cccc,
0x5555aaaa5555aaaa5555aaaa5555aaaa5555aaaa5555aaaa5555aaaa5555aaaa
]
gen = 10000000
gen = 50000
pop = 5
mut = 1
cgp = Cgp(row, col, lback, input, output)
cgp.file("/home/flea/bakalarka/src/data/parity9.txt")
#cgp = cgp(1, 40, 40, input, output)
#cgp = cgp()
cgp.run(gen, pop, mut)
print(cgp.bestFitness, cgp.result["popFitness"])
print("Time:", cgp.result["elapsed"], "Elapsed:", cgp.result["evalspersec"])
print(cgp.showChromosome)
#print(cgp.pop[cgp.parent])
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from cgp import Cgp
row = 1
col = 40
lback = 40
input = [[-1, 0, 1, 2, 3]]
output = [[0.1, 1, 10, 100, 1000]]
gen = 10000000
gen = 10
pop = 5
mut = 3
#print(gen)
cgp = Cgp(row, col, lback) #, input, output)
#cgp.file("/home/flea/bakalarka/src/data/adder6_6.txt")
#cgp = cgp(1, 40, 40, input, output)
#cgp = cgp()
cgp.file("../../data/xxyz.txt")
cgp.run(gen, pop, mut, 10, 0.01)
cgp.symbolicRegressionWithSin()
print(cgp.bestFitness, cgp.result["popFitness"])
print("Time:", cgp.result["elapsed"])
print("Elapsed:", cgp.result["evalspersec"])
print(cgp.showChromosome)
print()
print()
print("maxfitness", cgp.result["bestFitness"])
for key, value in cgp.result.items():
print(key)
#print(cgp.pop[cgp.parent])
#from bezevaluace.py3.cgp_algorithm import Cgp_algorithm
from cgp import Cgp
import os
row = 1
col = 40
lback = 40
gen = 10000
pop = 5
mut = 3
cgp = Cgp(row, col, lback)
for filename in os.listdir('../../data-cir/'):
cgp.file("../../data-cir/" + filename)
print(os.path.splitext(filename)[0])
cgp.run(gen, pop, mut)
print(cgp.evalspersec, " evals/sec ", cgp.elapsed)
f.write(" Min best fitness: "+str(worstfit)+"\n")
f.write(" Average fitness: "+str(avgFit)+"\n")
f.write(" Average elapsed time: "+str(avgElapsed)+" s \n")
f.write("\n\n")
"""
###############################################################################
# SAD #
###############################################################################
# 3+3
f.write("----SAD----\n")
print("SAD " + filename)
k = -1
cgp = Cgp(row, col, lback)
cgp.file(filename)
cgp.runSAD(gen, pop, mut, runs)
#runes.append(sum(cgp.fit) / len(cgp.fit))
similar = 0
avgFit = 0
avgNodes = 0
avgError = 0
avgElapsed = 0
avgFound = 0
worstfit = cgp.results[0][2]
for result in cgp.results:
chrom = result[0]
elapsed = result[1]
fitness = result[2]
foundInGen = result[3]
#!/usr/bin/env python3 # -*- coding: utf-8 -*- from cgp import Cgp row = 5 col = 5 lback = 1 input = [0xffff0000, 0xff00ff00, 0xf0f0f0f0, 0xcccccccc, 0xaaaaaaaa] output = [0xfee8e880] gen = 50000 pop = 5 mut = 5 cgp = Cgp(row, col, lback, input, output) #cgp = cgp(1, 40, 40, input, output) #cgp = cgp() cgp.moje() cgp.run(gen, pop, mut) cgp.printResults() # Median 5 bit
8.398711847799682, 12.055254727758806, 10.976288348004047,
10.15009475871688, 13.57996555734801, 12.259916334267293,
11.547528047093557, 12.855143536002732, 7.95919030972522,
11.760176109197543, 7.195525239233067
]]
output = [[
1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, -1.0, -1.0, -1.0, -1.0,
-1.0, -1.0, -1.0, -1.0, -1.0, -1.0
]]
row = 1
col = 40
lback = 40
#gen = 1000
gen = 1000000
#gen = 1
pop = 5
#pop = 1
mut = 3
acc = 0.1
cgp = Cgp(row, col, lback, input, output)
cgp.run_classification(gen, pop, mut, acc)
print("DONE")
print(cgp.chrom)
print("printing eq")
print(cgp.eq())