def run(self):
"""
Compute normalized score
"""
self.norm_score=np.arange(float(len(self.interactions)))
self.pos=np.arange(len(self.interactions))
#Score to normalise
#listscore=self.dbmanage.getAllScore(self.interactions)
#Len sRNA
listlensRNA=self.dbmanage.getAllsRNAlenbyIntid(self.interactions)
listlenmRNA=self.dbmanage.getAllmRNAlenbyIntid(self.interactions)
funcspec=self.defnormfunction()
for i in xrange(len(self.interactions)):
if((i%500)==0): print("%d/%d"%(i+1,len(self.interactions)))
score=self.dbmanage.getScore(self.interactions[i][0])
#if(listscore[i]!=None):
# funcspec(listscore[i],np.log(float(listlensRNA[i]*listlenmRNA[i])),self.score_type,i)
if(score!=None):
funcspec(score,np.log(float(listlensRNA[i]*listlenmRNA[i])),self.score_type,i)
#Cas mfe / energy
if(self.score_type==2 or self.score_type==3): self.norm_score[i]=-self.norm_score[i]
#Nothing is predicted
else: self.norm_score[i]=np.nan
#Communication object
data=Communication()
data.norm_score=self.norm_score
data.pos=self.pos
return data
def getSendCom(self,computer,type_analysis,tab,dbmanage,rand_inf):
"""
Create communication object
"""
data=Communication()
data.type_analysis=type_analysis
if(type_analysis==0):
data.interactions=computer.interactions[tab[0]:tab[1]]
data.type_sol=computer.type_sol
data.score_type=computer.score_type
elif(type_analysis==1 or type_analysis==3):
data.interactions=computer.interactions[tab[0]:tab[1]]
data.type_sol=computer.type_sol
#Matrice partielle
data.pos=computer.pos[tab[0]:tab[1]]
elif(type_analysis==2):
data.softname=self.getCorrespondingSoft(computer,dbmanage,rand_inf)
data.norm_score=computer.norm_score[tab[0]:tab[1]]
data.interactions=computer.interactions[tab[0]:tab[1]]
#regression
elif(type_analysis==4):
data.unique_sRNAidinint=computer.unique_sRNAidinint[tab[0]:tab[1]]
data.norm_score=computer.norm_score
data.sRNAid_tab=computer.sRNAid_tab
data.pValue_type=computer.pValue_type
else:
raise NotImplementedError("")
return data
