def buildNetwork(self):
net = GRNetwork(self.nodes)
c = np.random.random(len(self.nodes))
self.buildPaStore()
for index in range(len(self.nodes)):
ntempDist = self.buildPaDistribution(index)
pachoice = mysample(ntempDist, c[index], self.paStore[index])
net.initializeParent(self.nodes[index], pachoice)
return net
def buildNetwork2(gdict, paDict, logWeightMap):
net = GRNetwork(list(gdict.values()))
for k, v in gdict.items():
allPaSets = paDict[k]
dist1 = []
for paSet in allPaSets:
hkey = buildHKey(v, paSet)
dist1.append(logWeightMap[hkey])
dist2 = np.array(dist1)
distribution = dist2 / np.sum(dist2)
initPa = mysample(distribution, np.random.random(), allPaSets)
net.initializeParent(v, initPa)
return net
def buildNetwork(gdict, paDict, weightMap):
net = GRNetwork(list(gdict.values()))
for k, v in gdict.items():
allPaSets = paDict[k]
distribution = []
for paSet in allPaSets:
speciesId = v.getSpeciesId()
gid = v.getGeneId()
pasId = ':'.join([pa.getGeneId() for pa in paSet])
distribution.append(weightMap[buildKey(speciesId, gid, pasId)])
initPa = mysample(distribution, np.random.random(), allPaSets)
net.initializeParent(v, initPa)
return net
def parseNetwork(gdict, netfile):
net = GRNetwork(list(gdict.values()))
for line in netfile:
temp = line.strip()
if temp == '<end>':
break
elif temp == '<begin>' or temp == '':
continue
else:
parts = temp.strip().split(',')
currGene = gdict[parts[0].strip()]
paSet = [gdict[gid.strip()] for gid in parts[1:]]
net.updateParent(currGene, paSet)
return net