interactions = networks[letter]['interactions']
edges = interactions.keys()
thresholds = networks[letter]['thresholds']
IG = nx.DiGraph()
IG.add_edges_from(edges)
mc = dict_to_model(interactions, thresholds=thresholds, add_morphogene=True)
smallmc = dict_to_model(interactions, thresholds=thresholds, add_morphogene=False)
lpss = mc._psc._localParameterSets
print len(mc._psc), "parameter sets."
gpss = mc._psc.get_parameterSets()
countaccepted = 0
countrejected = 0
for gps in gpss:
#print gps
subgps = dict((combi, encode_gps_full(subparset(gps, is_m1_in=combi[0], is_m2_in=combi[1]))) for combi in combis)
parameter_set_IG_list = [decode_gps_full(subgps[combi]) for combi in combis]
parameter_sets = [elem[0] for elem in parameter_set_IG_list]
accepted = all(filter_byAL(smallmc, parameter_sets[i], ALformulas[i]) for i in range(3))*1
if accepted:
print "accepting:", gps
export_STG(mc, gps, filename="_nonboolean_"+letter+"_"+encode_gps(gps, base=10)+".gml", initialRules=None)
countaccepted += 1
else:
print "rejecting:", gps
countrejected += 1
print "accepted:", countaccepted
print "rejected:", countrejected
print "considering nwkey:", nwkey
#print networks[nwkey]
print networks[nwkey]
mc = dict_to_model(networks[nwkey], add_morphogene)
npsc = len(mc._psc)
print nwkey, ":", npsc, "parameter sets."
pstotal += npsc
print nwkey, ":", pstotal, "parameter sets in total."
gpss = mc._psc.get_parameterSets()
thesesubgpss = set()
#print "IG.edges() =", mc._IG.edges()
for gps in gpss:
for combi in combis:
#print subparset(gps, is_m1_in=combi[0], is_m2_in=combi[1])
subgps = encode_gps_full(subparset(gps, is_m1_in=combi[0], is_m2_in=combi[1])) # full means include edges in the encoding
thesesubgpss.add(subgps)
#print gps
#print encode_gps(gps)
allsubgpss = allsubgpss.union(thesesubgpss)
print "unique small gps to date:", len(allsubgpss)
small_gps_codes[nwkey] = [npsc, pstotal, len(allsubgpss)]
d[str(nwkey)] = thesesubgpss
# d[x] contains for network x for all gps for all regions the subgps
tend = datetime.now()
print "total execution time:", tend-tstart
d.close()
picklename = "small_gps_codes_from_unconstrained_excluding_overregulated.pkl"
print "pickling results to:", picklename
cPickle.dump(small_gps_codes, file(picklename, "w"))
