def select(rr, dirToExamine, dirNotAnalyze, others):
#to create the directory for models we don't care to study
BaseFunctions.createDirectoryExit(dirNotAnalyze)
#to create the directory for others files
BaseFunctions.createDirectoryExit(others)
#list of files into directory
files=os.listdir(dirToExamine)
#to examine one file at a time
for file in files:
if file.endswith('.xml'):
print(file)
try:
#to load the file with roadrunner
rr.load(dirToExamine+'\\'+file)
except:
#if an error occurs we can't examine the file
shutil.move(dirToExamine+'\\'+file, dirNotAnalyze)
print('An error occurs during file load: To not analyze')
continue
#to get the model using libSBML
model = libsbml.SBMLReader().readSBMLFromString(rr.getSBML()).getModel()
#we don't want to analyze models with rules or events or qualitative models
#we can't analyze in a correct way models which are bad read from libroadrunner.
if model.getNumRules()>0 or model.getNumEvents()>0 or model.getPlugin('qual')!=None or model.getNumSpecies()!=rr.model.getNumFloatingSpecies() or model.getNumReactions()!=rr.model.getNumReactions():
shutil.move(dirToExamine+'\\'+file, dirNotAnalyze)
print('To not analyze')
else:
#we don't care other files
shutil.move(dirToExamine+'\\'+file, others)
def selectErrorLoad(rr, dirToExamine, dirNotAnalyze, others):
#to create the directory for models we don't care to study
BaseFunctions.createDirectoryExit(dirNotAnalyze)
#to create the directory for others files
BaseFunctions.createDirectoryExit(others)
#list of files into directory
files=os.listdir(dirToExamine)
#to examine one file at a time
for file in files:
if file.endswith('.xml'):
print(file)
try:
#to load the file with roadrunner
rr.load(dirToExamine+'\\'+file)
except:
#if an error occurs we can't examine the file
shutil.move(dirToExamine+'\\'+file, dirNotAnalyze)
print('An error occurs during file load: To not analyze')
continue
else:
#we don't care other files
shutil.move(dirToExamine+'\\'+file, others)
def selectModifiers(rr, dirToExamine, dirNotAnalyze):
#to create the directory for models we don't care to study
BaseFunctions.createDirectoryExit(dirNotAnalyze)
f = open("modifiers_models.txt", "a")
#list of files into directory
files=os.listdir(dirToExamine)
#to examine one file at a time
for file in files:
if file.endswith('.xml'):
print(file)
try:
#to load the file with roadrunner
rr.load(dirToExamine+'\\'+file)
except:
#if an error occurs we can't examine the file
shutil.move(dirToExamine+'\\'+file, dirNotAnalyze)
print('An error occurs during file load: To not analyze')
continue
#to get the model using libSBML
model = libsbml.SBMLReader().readSBMLFromString(rr.getSBML()).getModel()
#we don't want to analyze models with rules or events or qualitative models
#we can't analyze in a correct way models which are bad read from libroadrunner.
for i in range(model.getNumReactions()):
if model.getReaction(i).getNumModifiers() > 0:
f.write(file + "\n")
#shutil.move(dirToExamine+'\\'+file, dirNotAnalyze)
print('Modifiers!')
break
f.close()
def analysisTheorems(rr, dirToExamine, dirNotAnalyze, dirToSimulation,
dirTheorems):
BaseFunctions.createDirectoryExit(dirToSimulation)
BaseFunctions.createDirectoryExit(dirTheorems)
BaseFunctions.createDirectoryExit(dirTheorems + "\\not_known")
BaseFunctions.createDirectoryExit(dirTheorems + "\\SteadyState")
#analyze each file into the directory
files = os.listdir(dirToExamine)
for file in files:
if file.endswith('.xml'):
print(file)
rr.clearModel()
try:
rr.load(dirToExamine + '\\' + file)
except:
shutil.move(dirToExamine + '\\' + file, dirNotAnalyze)
print('Not_Analyze')
continue
#check of use of mass action
if Simulation.toSimulate(rr) == 1:
#theorems are not applicable
shutil.move(dirToExamine + '\\' + file, dirToSimulation)
continue
#study of model with Feinberg's theorems
results = Deficiency_Calculation.deficiency_calculation(rr)
if results[1] == 1:
print("Cannot use Feinberg's theorems")
shutil.move(dirToExamine + '\\' + file, dirToSimulation)
elif results[0] == 0 or results[0] == 1:
print("Model reaches steady state")
shutil.move(dirToExamine + '\\' + file,
dirTheorems + "\\SteadyState")
else:
print("Unknown behavior")
shutil.move(dirToExamine + '\\' + file,
dirTheorems + "\\not_known")
def main(interval=-1, maxInterval=20, dirToExamine="models", func=0):
#for use the library libRoadRunner
rr=roadrunner.RoadRunner()
simulationTime=20000
mintime=0
nTest=10
increase=5
dirNotAnalyze="Not_Analyze"
dirOtherFiles="Other_Files"
dirPetriNets=os.getcwd()+'\\PetriNets'
dirTheorems=os.getcwd()+'\\Theorems_Models'
dirResultsTheorems=os.getcwd()+'\\Results_Theorems'
dirToSimulation=os.getcwd()+'\\Simulate_Models'
dirResultsSimulation=os.getcwd()+'\\Results_Simulations'
if func==1:
SelectFiles.select(rr, dirToExamine, dirNotAnalyze, dirOtherFiles)
elif func==2:
analysisTheorems(rr, dirToExamine, dirNotAnalyze, dirToSimulation, dirTheorems)
elif func==4:
PetriNets.createPetriNets(rr, dirToExamine, dirPetriNets, nTest, increase)
elif func in [0, 3]:
if interval<=0:
interval=BaseFunctions.numericalInput('Range of initial perturbation (X %) : ',[])
if interval<=0 or maxInterval<=0 or interval>maxInterval:
exit("Error: invalid interval parameters")
#contains the percentages to modify the quantities of species
percent=[]
i=interval
while i<=maxInterval:
percent.append(i)
i=i+interval
if func==3:
Simulation.simulateAllModels(rr, dirToExamine, dirResultsSimulation, dirNotAnalyze, simulationTime, mintime, percent)
else:
#select models with certain characteristics
SelectFiles.select(rr, dirToExamine, dirNotAnalyze, dirOtherFiles)
analysisTheorems(rr, dirToExamine, dirNotAnalyze, dirToSimulation, dirTheorems)
BaseFunctions.createDirectoryExit(dirResultsTheorems)
#model's simulations
files=os.listdir(dirTheorems+"\\SteadyState")
for file in files:
Simulation.simulationWithSteadyState(rr, percent, dirResultsTheorems+"\\SteadyState", dirTheorems+"\\SteadyState", file)
Simulation.simulateAllModels(rr, dirTheorems+"\\not_known", dirResultsTheorems+"\\not_known", dirNotAnalyze, simulationTime, mintime, percent)
Simulation.simulateAllModels(rr, dirToSimulation, dirResultsSimulation, dirNotAnalyze, simulationTime, mintime, percent)
#creation of Petri nets
print("Petri Nets")
PetriNets.createPetriNets(rr, dirToSimulation, dirPetriNets, nTest, increase)
PetriNets.createPetriNets(rr, dirTheorems+"\\not_known", dirPetriNets, nTest, increase)
PetriNets.createPetriNets(rr, dirTheorems+"\\SteadyState", dirPetriNets, nTest, increase)
else:
print("Invalid parameter")
def simulationWithSteadyState(rr, percent, dirResults, dirToExamine, file, points=_points):
nameDir=file[0:(len(file)-4)]
if BaseFunctions.createDirectory(dirResults)==1 or BaseFunctions.createDirectory(dirResults+"\\"+nameDir)==1:
#an error has occured
return
path=dirResults+"\\"+nameDir+"\\"
try:
rr.load(dirToExamine+'\\'+file)
except:
print('Error')
return
originalQuantities=rr.model.getFloatingSpeciesAmounts()
withValues=True
values=[]
try:
rr.conservedMoietyAnalysis = True
except:
withValues=False
print('Error during studying of steady state')
if withValues:
try:
#to calculate values at steady state. It can be return values
#also for models that show oscillations
values=rr.getSteadyStateValues()
rr.resetAll()
except:
#an error has occured
print('Error during studying of steady state')
withValues=False
rr.conservedMoietyAnalysis = False
simulationSteps(rr, path, "Results_Original"+_extension, points, values)
for i in range(rr.model.getNumFloatingSpecies()):
for j in range(len(percent)):
rr.resetAll()
values=[]
if withValues:
try:
rr.conservedMoietyAnalysis = True
rr.model.setFloatingSpeciesAmounts([i],[originalQuantities[i]+originalQuantities[i]*percent[j]/100])
values=rr.getSteadyStateValues()
rr.resetAll()
except:
print('Error during studying of steady state')
rr.model.setFloatingSpeciesAmounts([i],[originalQuantities[i]+originalQuantities[i]*percent[j]/100])
simulationSteps(rr, path, "Results_species_"+str(i+1)+"_plus_"+str(percent[j])+"_p"+_extension, points, values)
rr.resetAll()
values=[]
if withValues:
try:
rr.conservedMoietyAnalysis = True
rr.model.setFloatingSpeciesAmounts([i], [originalQuantities[i]-originalQuantities[i]*percent[j]/100])
values=rr.getSteadyStateValues()
rr.resetAll()
except:
print('Error during studying of steady state')
rr.model.setFloatingSpeciesAmounts([i], [originalQuantities[i]-originalQuantities[i]*percent[j]/100])
simulationSteps(rr, path, "Results_species_"+str(i+1)+"_minus_"+str(percent[j])+"_p"+_extension, points, values)
rr.conservedMoietyAnalysis = False
def simulateModel(rr, path, file, toPath, dirReject, simulationTime, time, percent, points=_points):
#creation of directories used
if BaseFunctions.createDirectory(dirReject)==1 or BaseFunctions.createDirectory(toPath)==1 or \
BaseFunctions.createDirectory(toPath+"\\Oscillation")==1 or \
BaseFunctions.createDirectory(toPath+"\\Steady_State")==1 or \
BaseFunctions.createDirectory(toPath+"\\Others")==1:
return 1
rr.conservedMoietyAnalysis = False
rr.clearModel()
step=_step
max=simulationTime/step
#name of file
nameDir=file[0:(len(file)-4)]
rr.clearModel()
try:
rr.load(path+'\\'+file)
except:
shutil.move(path+'\\'+file, dirReject)
print('To not analyze')
return 1
#original quantities of species
originalQuantities=rr.model.getFloatingSpeciesAmounts()
originalPath=toPath
#files to memorize the results
allResults=open(originalPath+"\\Results_Original"+_extension, "w")
smallResults=open(originalPath+"\\Small_Results_Original"+_extension, "w")
oldSimulations=np.array(np.zeros(rr.model.getNumFloatingSpecies()), dtype=int)
stop=False
steadyState=False
start=-(step/points)
i=0
while(i<max and not stop):
try:
sim=rr.simulate(start+(step/points),start+step,points)
except:
#an error has occured during the simulation
break
if i==0:
np.savetxt(allResults, sim, fmt='%.8f',header=str(rr.timeCourseSelections))
np.savetxt(smallResults, [sim[0,:]], fmt='%.5f',header=str(rr.timeCourseSelections))
j=_interval
while j<len(sim):
np.savetxt(smallResults, [sim[j,:]], fmt='%.5f')
j=j+_interval
else:
np.savetxt(allResults, sim, fmt='%.8f')
j=0
while j<len(sim):
np.savetxt(smallResults, [sim[j,:]], fmt='%.5f')
j=j+_interval*2
#the behaviour of models is studying
if start>time:
first=sim[0,1:].round(decimals=5)
last=sim[points-1,1:].round(decimals=5)
j=0
while j<len(last) and last[j]>=0:
j=j+1
if j<len(last):
break
if not (first==last).all():
for j in range(np.shape(oldSimulations)[0]):
if (not (np.array(first, dtype=int)==np.array(last, dtype=int)).all()) and (np.array(last, dtype=int)==oldSimulations[j]).all():
toPath=toPath+"\\Oscillation"
stop=True
print("Oscillation")
break
else:
for j in range(points-1):
if not (sim[j,1:].round(decimals=5)==last).all():
stop=True
toPath=toPath+"\\Oscillation"
print("Oscillation")
break
if not stop:
stop=True
steadyState=True
toPath=toPath+"\\Steady_State"
print("Steady state")
oldSimulations = np.vstack((oldSimulations, np.array(sim[:,1:], dtype=int)))
start=start+step
i=i+1
#if the behaviour of model is not identified
if stop==False:
print("Behaviour not known")
toPath=toPath+"\\Others"
allResults.close()
smallResults.close()
#creation of directory for store the results
if BaseFunctions.createDirectory(toPath+'\\'+nameDir)==1 or \
BaseFunctions.removeFile(toPath+"\\"+nameDir+'\\'+"Results_Original"+_extension)==1 or\
BaseFunctions.removeFile(toPath+"\\"+nameDir+'\\'+"Small_Results_Original"+_extension)==1:
#if an error has occured
return 1
shutil.move(originalPath+"\\Results_Original"+_extension, toPath+"\\"+nameDir)
shutil.move(originalPath+"\\Small_Results_Original"+_extension, toPath+"\\"+nameDir)
toPath=toPath+"\\"+nameDir+'\\'
#simulations with different quantities of species
for i in range(rr.model.getNumFloatingSpecies()):
for j in range(len(percent)):
rr.resetAll()
#new quantity is setting
rr.model.setFloatingSpeciesAmounts([i],[originalQuantities[i]+originalQuantities[i]*percent[j]/100])
if not steadyState:
#files to store the results
allResults=open(toPath+"Results_species_"+str(i+1)+"_plus_"+str(percent[j])+"_p"+_extension, "w")
smallResults=open(toPath+"Small_Results_species_"+str(i+1)+"_plus_"+str(percent[j])+"_p"+_extension, "w")
try:
sim=rr.simulate(0, simulationTime, simulationTime*int(points/step))
np.savetxt(allResults, sim, fmt='%.8f',header=str(rr.timeCourseSelections))
np.savetxt(smallResults, [sim[0,:]], fmt='%.5f',header=str(rr.timeCourseSelections))
k=_interval
while k<len(sim):
np.savetxt(smallResults, [sim[k,:]], fmt='%.5f')
k=k+_interval
except:
print("Error")
#files are closed
allResults.close()
smallResults.close()
else:
#simulation for models with steady state
simulationSteps(rr, toPath, "Results_species_"+str(i+1)+"_plus_"+str(percent[j])+"_p"+_extension, points)
rr.resetAll()
#new quantity is setting
rr.model.setFloatingSpeciesAmounts([i],[originalQuantities[i]-originalQuantities[i]*percent[j]/100])
if not steadyState:
#files to store the results
allResults=open(toPath+"Results_species_"+str(i+1)+"_minus_"+str(percent[j])+"_p"+_extension, "w")
smallResults=open(toPath+"Small_Results_species_"+str(i+1)+"_minus_"+str(percent[j])+"_p"+_extension, "w")
try:
sim=rr.simulate(0, simulationTime, simulationTime*int(points/step))
np.savetxt(allResults, sim, fmt='%.8f',header=str(rr.timeCourseSelections))
np.savetxt(smallResults, [sim[0,:]], fmt='%.5f',header=str(rr.timeCourseSelections))
k=_interval
while k<len(sim):
np.savetxt(smallResults, [sim[k,:]], fmt='%.5f')
k=k+_interval
except:
print("Error")
allResults.close()
smallResults.close()
else:
simulationSteps(rr, toPath, "Results_species_"+str(i+1)+"_minus_"+str(percent[j])+"_p"+_extension, points)
def simulateWithTime(rr, nameDir, simulationTime, toPath, percent, points):
if BaseFunctions.createDirectory(toPath+"\\"+nameDir)==1:
#an error has occured
return
path=toPath+"\\"+nameDir+"\\"
originalQuantities=rr.model.getFloatingSpeciesAmounts()
allResults=open(path+"Results_Original"+_extension, "w")
smallResults=open(path+"Small_Results_Original"+_extension, "w")
try:
sim=rr.simulate(0,simulationTime, points)
np.savetxt(allResults, sim, fmt='%.8f',header=str(rr.timeCourseSelections))
np.savetxt(smallResults, [sim[0,:]], fmt='%.5f', header=str(rr.timeCourseSelections))
i=_interval
while i<len(sim):
np.savetxt(smallResults, [sim[i,:]], fmt='%.5f')
i=i+_interval
except:
print("Error")
allResults.close()
smallResults.close()
for i in range(rr.model.getNumFloatingSpecies()):
for j in range(len(percent)):
rr.resetAll()
rr.model.setFloatingSpeciesAmounts([i], [originalQuantities[i]+originalQuantities[i]*percent[j]/100])
allResults=open(path+"Results_species_"+str(i+1)+"_plus_"+str(percent[j])+"_p"+_extension, "w")
smallResults=open(path+"Small_Results_species_"+str(i+1)+"_plus_"+str(percent[j])+"_p"+_extension, "w")
try:
sim=rr.simulate(0,simulationTime, points)
np.savetxt(allResults, sim, fmt='%.8f',header=str(rr.timeCourseSelections))
np.savetxt(smallResults, [sim[0,:]], fmt='%.5f',header=str(rr.timeCourseSelections))
k=_interval
while k<len(sim):
np.savetxt(smallResults, [sim[k,:]], fmt='%.5f')
k=k+_interval
except:
print("Error")
allResults.close()
smallResults.close()
rr.resetAll()
rr.model.setFloatingSpeciesAmounts([i], [originalQuantities[i]-originalQuantities[i]*percent[j]/100])
allResults=open(path+"Results_species_"+str(i+1)+"_minus_"+str(percent[j])+"_p"+_extension, "w")
smallResults=open(path+"Small_Results_species_"+str(i+1)+"_minus_"+str(percent[j])+"_p"+_extension, "w")
try:
sim=rr.simulate(0,simulationTime, points)
np.savetxt(allResults, sim, fmt='%.8f',\
header=str(rr.timeCourseSelections))
np.savetxt(smallResults, [sim[0,:]], fmt='%.5f',\
header=str(rr.timeCourseSelections))
k=_interval
while k<len(sim):
np.savetxt(smallResults, [sim[k,:]], fmt='%.5f')
k=k+_interval
except:
print("Error")
allResults.close()
smallResults.close()
def createOnePetriNet(rr, path, file, pathResult, nTest, valueIncrease):
if BaseFunctions.createDirectory(pathResult)==1:
return 1
#it clears the currently loaded model and all associated memory
rr.clearModel()
path=path+"\\"
try:
#to load the file with roadrunner
rr.load(path+file)
except:
print("An error occurs during file load")
return 1
#to get the model using libSBML
model = libsbml.SBMLReader().readSBMLFromString(rr.getSBML()).getModel()
nameFile=file[0:(len(file)-4)]
try:
f=open(pathResult+"\\"+nameFile+".gv", "w")
except IOError:
print("An error occurs during opening file")
return 1
#string that will contains petri net of model
graph='digraph "'+str(file)+'"{\n'
#to create a node for each specie
for i in range(model.getNumSpecies()):
graph=graph+str(model.getSpecies(i).getId())+" [shape=circle];\n"
#to examine one reaction at a time
for i in range(model.getNumReactions()):
#to create a box (node) for each reaction
graph=graph+str(model.getListOfReactions().get(i).getId())+" [shape=box];\n"
#to get reaction's reactants
for reactant in model.getReaction(i).getListOfReactants():
graph=graph+str(reactant.getSpecies())+" -> "+str(model.getReaction(i).getId())+" [arrowhead=vee, label="+str(reactant.getStoichiometry())+"];\n"
#to get reaction's products
for product in model.getListOfReactions().get(i).getListOfProducts():
graph=graph+str(model.getReaction(i).getId())+" -> "+str(product.getSpecies())+" [arrowhead=vee, label="+str(product.getStoichiometry())+"];\n"
#to get reaction's modifiers and establish if they are promoter or inhibitor
for j in range(model.getReaction(i).getNumModifiers()):
response=functionality(rr, model, j, i, nTest, valueIncrease)
#if it's a promoter
if response==1:
graph=graph+str(model.getReaction(i).getModifier(j).getSpecies())+" -> "+str(model.getReaction(i).getId())+" [arrowhead=dot];\n"
#if it's a inhibitor
elif response==0:
graph=graph+str(model.getReaction(i).getModifier(j).getSpecies())+" -> "+str(model.getReaction(i).getId())+" [arrowhead=tee];\n"
#if there is the inverse reaction
if model.getReaction(i).getReversible():
#to create a box (node) for the inverse reaction
graph=graph+str(model.getReaction(i).getId())+"_Reverse [shape=box];\n"
#to get inverse reaction's reactants
for reactant in model.getListOfReactions().get(i).getListOfReactants():
graph=graph+str(model.getListOfReactions().get(i).getId())+"_Reverse -> "+str(reactant.getSpecies())+" [arrowhead=vee, label="+str(reactant.getStoichiometry())+"];\n"
#to get inverse reaction's products
for product in model.getListOfReactions().get(i).getListOfProducts():
graph=graph+str(product.getSpecies())+" -> "+str(model.getListOfReactions().get(i).getId())+"_Reverse [arrowhead=vee, label="+str(product.getStoichiometry())+"];\n"
graph=graph+"}"
try:
f.write(graph)
finally:
try:
f.close()
except IOError:
return 1
return 0
def createOnePetriNet(rr, path, file, pathResult, nTest, valueIncrease):
filefile = open("modifiers_discovered.txt", "a")
filefilelist = []
if BaseFunctions.createDirectory(pathResult) == 1:
return 1
#it clears the currently loaded model and all associated memory
rr.clearModel()
path = path + "\\"
try:
#to load the file with roadrunner
rr.load(path + file)
except:
print("An error occurs during file load")
return 1
#to get the model using libSBML
model = libsbml.SBMLReader().readSBMLFromString(rr.getSBML()).getModel()
nameFile = file[0:(len(file) - 4)]
try:
f = open(pathResult + "\\" + nameFile + ".gv", "w")
except IOError:
print("An error occurs during opening file")
return 1
#string that will contains petri net of model
graph = 'digraph "' + str(file) + '"{\n'
#to create a node for each specie
for i in range(model.getNumSpecies()):
graph = graph + str(model.getSpecies(i).getId()) + " [shape=circle];\n"
#to examine one reaction at a time
for i in range(model.getNumReactions()):
#to create a box (node) for each reaction
graph = graph + str(
model.getListOfReactions().get(i).getId()) + " [shape=box];\n"
#to get reaction's reactants
for reactant in model.getReaction(i).getListOfReactants():
graph = graph + str(reactant.getSpecies()) + " -> " + str(
model.getReaction(
i).getId()) + " [arrowhead=vee, label=" + str(
reactant.getStoichiometry()) + "];\n"
#to get reaction's products
for product in model.getListOfReactions().get(i).getListOfProducts():
graph = graph + str(model.getReaction(i).getId()) + " -> " + str(
product.getSpecies()) + " [arrowhead=vee, label=" + str(
product.getStoichiometry()) + "];\n"
#lista di tutti i modificatori
listModifiers = [
modifier.getSpecies()
for modifier in model.getReaction(i).getListOfModifiers()
]
#to get reaction's modifiers and establish if they are promoter or inhibitor
for j in range(model.getReaction(i).getNumModifiers()):
#se il modificatore è anche un reagente non lo considero
if model.getReaction(i).getModifier(j).getSpecies() in [
reactant.getSpecies()
for reactant in model.getReaction(i).getListOfReactants()
]:
continue
#se il modificatore compare più volte lo considero solo l'ultima volta
if model.getReaction(i).getModifier(
j).getSpecies() in listModifiers[j + 1:]:
continue
response = findRole(
rr, model,
model.getReaction(i).getModifier(j).getSpecies(), i, nTest,
valueIncrease)
#if it's a promoter
if response == 1:
graph = graph + str(
model.getReaction(i).
getModifier(j).getSpecies()) + " -> " + str(
model.getReaction(i).getId()) + " [arrowhead=dot];\n"
#if it's a inhibitor
elif response == 0:
graph = graph + str(
model.getReaction(i).
getModifier(j).getSpecies()) + " -> " + str(
model.getReaction(i).getId()) + " [arrowhead=tee];\n"
listReactants = [
reactant.getSpecies()
for reactant in model.getReaction(i).getListOfReactants()
]
listProducts = [
product.getSpecies()
for product in model.getReaction(i).getListOfProducts()
]
alreadySeen = []
#vedo se ci sono specie nè reagenti nè modificatori nella legge cinetica
for k in range(
model.getReaction(
i).getKineticLaw().getMath().getListOfNodes().getSize()):
#se il nodo è una specie
nameOfNode = model.getReaction(
i).getKineticLaw().getMath().getListOfNodes().get(k).getName()
if nameOfNode in [
specie.getId() for specie in model.getListOfSpecies()
]:
#se non è nè nella lista dei reagenti nè dei modificatore trattalo come un modificatore
if nameOfNode in alreadySeen or nameOfNode in listReactants or nameOfNode in listModifiers or \
(nameOfNode in listProducts and model.getReaction(i).getReversible()):
continue
alreadySeen.append(nameOfNode)
response = findRole(rr, model, nameOfNode, i, nTest,
valueIncrease)
#if it's a promoter
if response == 1:
graph = graph + str(
model.getReaction(i).getKineticLaw().getMath().
getListOfNodes().get(k).getName()) + " -> " + str(
model.getReaction(
i).getId()) + " [arrowhead=dot];\n"
#if it's a inhibitor
elif response == 0:
graph = graph + str(
model.getReaction(i).getKineticLaw().getMath().
getListOfNodes().get(k).getName()) + " -> " + str(
model.getReaction(
i).getId()) + " [arrowhead=tee];\n"
if file not in filefilelist:
filefilelist.append(file)
#if there is the inverse reaction
if model.getReaction(i).getReversible():
#to create a box (node) for the inverse reaction
graph = graph + str(
model.getReaction(i).getId()) + "_Reverse [shape=box];\n"
#to get inverse reaction's reactants
for reactant in model.getListOfReactions().get(
i).getListOfReactants():
graph = graph + str(model.getListOfReactions().get(i).getId(
)) + "_Reverse -> " + str(
reactant.getSpecies()) + " [arrowhead=vee, label=" + str(
reactant.getStoichiometry()) + "];\n"
#to get inverse reaction's products
for product in model.getListOfReactions().get(
i).getListOfProducts():
graph = graph + str(product.getSpecies()) + " -> " + str(
model.getListOfReactions().get(
i).getId()) + "_Reverse [arrowhead=vee, label=" + str(
product.getStoichiometry()) + "];\n"
graph = graph + "}"
try:
f.write(graph)
finally:
try:
f.close()
except IOError:
return 1
for elem in filefilelist:
filefile.write(elem + "\n")
filefile.close()
return 0