def test_import():
grn = grns.ClassicGRN()
grn.random(10, 10, 10)
str_grn = str(grn)
grn2 = grns.ClassicGRN()
grn2.from_str(str_grn)
assert grn.num_input == grn2.num_input
assert grn.num_output == grn2.num_output
assert grn.num_regulatory == grn2.num_regulatory
assert np.all(grn.identifiers == grn2.identifiers)
assert np.all(grn.enhancers == grn2.enhancers)
assert np.all(grn.inhibitors == grn2.inhibitors)
assert grn.beta == grn2.beta
assert grn.delta == grn2.delta
def test_double_fit():
p = problems.DoubleFrequency()
g = grns.ClassicGRN()
g.random(p.nin, p.nout, 10)
fitness = p.eval(g)
print(fitness)
assert fitness <= 0.0
def test_double_evolution():
p = problems.DoubleFrequency()
g = grns.ClassicGRN()
config.POPULATION_SIZE = 30
g.random(p.nin, p.nout, 5)
random_fitness = p.eval(g)
evo = evolution.Evolution(p)
best_fit, best_ind = evo.run(5)
print(random_fitness, ", ", best_fit)
assert best_fit > random_fitness
def test_export():
grn = grns.ClassicGRN()
grn.random(10, 10, 10)
str_grn = str(grn)
assert str_grn == json.dumps({
'num_input': grn.num_input,
'num_output': grn.num_output,
'num_regulatory': grn.num_regulatory,
'ids': grn.identifiers.tolist(),
'enh': grn.enhancers.tolist(),
'inh': grn.inhibitors.tolist(),
'beta': grn.beta,
'delta': grn.delta
})
def test_classic_diff():
grn1 = grns.ClassicGRN()
grn2 = grns.DiffGRN()
compare_grns(grn1, grn2)
def test_classic_gpu():
grn1 = grns.ClassicGRN()
grn2 = grns.GPUGRN()
compare_grns(grn1, grn2)
def test_classic_matrix():
grn1 = grns.ClassicGRN()
grn2 = grns.MatrixGRN()
compare_grns(grn1, grn2)
def test_sanity():
grn1 = grns.ClassicGRN()
grn2 = grns.ClassicGRN()
compare_grns(grn1, grn2)
log_dir = os.path.join(args.root_dir, 'logs')
config.START_REGULATORY_SIZE = args.nreg
PROBLEM = "GymGRN"
log_file = os.path.join(log_dir, 'fits_' + args.id + '.log')
grn_dir = os.path.join(args.root_dir, 'grns')
data_dir = os.path.join(args.root_dir, 'data')
log_file = os.path.join(log_dir, 'fits_' + args.id + '.log')
p = eval('problems.' + args.problem)
p = p(args.env, args.nin, args.nout, args.ep_max)
print("..Init GRN..")
newgrn = grns.ClassicGRN() #DiffGRN()
newgrn2 = lambda: grns.ClassicGRN() #DiffGRN()
if args.evo:
print("..Evolv GRN..")
grneat = evolution.Evolution(p,
newgrn2,
run_id=args.id,
grn_dir=grn_dir,
log_dir=log_dir)
grneat.run(args.gens)
else:
for i in range(1):
print("..Init GRN", i, "..")
#grn = grns.ClassicGRN()
if args.grn_file:
print("..Load GRN..")