def modelOutputSlow(self,params): filename,namesList = self.filename,self.namesList endTime,nSteps = self.endTime,self.nSteps # use BNG to integrate the model writeBNGL.writeBNGLsimulate(filename,namesList,params,endTime,nSteps) os.system(BNGpath+"Perl2/BNG2.pl "+filename+"_simulate.bngl > " \ +filename+"_simulate_messages.txt") # read in output of model output = self._readModelOutput(filename+"_simulate.cdat") self.recentOutput = output return output
def modelOutputSlow(self, params): filename, namesList = self.filename, self.namesList endTime, nSteps = self.endTime, self.nSteps # use BNG to integrate the model writeBNGL.writeBNGLsimulate(filename, namesList, params, endTime, nSteps) os.system(BNGpath+"Perl2/BNG2.pl "+filename+"_simulate.bngl > " \ +filename+"_simulate_messages.txt") # read in output of model output = self._readModelOutput(filename + "_simulate.cdat") self.recentOutput = output return output
def _createNetwork(self,verbose): """ Creates BioNetGen network 'filename.net'. Returns list of names of network parameters. """ filename,n,rulesList = self.filename,self.n,self.rulesList if self.verbose: mult = 2 if self.MichaelisMenten: mult = 4 start,startWall = cpuTime(),wallTime() print "" print "Creating network with "+str(n)+" activation sites" print " and "+str(len(rulesList))+" additional rules (" \ +str(mult*(n+len(rulesList)))+" parameters)." namesList = writeBNGL.writeBNGLnetwork(n,rulesList,filename, \ MichaelisMenten=self.MichaelisMenten) self._runBNGLfile(filename) if self.verbose: print "Network creation took "+bothTimeStr(start,startWall) return namesList
def _createNetwork(self, verbose): """ Creates BioNetGen network 'filename.net'. Returns list of names of network parameters. """ filename, n, rulesList = self.filename, self.n, self.rulesList if self.verbose: mult = 2 if self.MichaelisMenten: mult = 4 start, startWall = cpuTime(), wallTime() print "" print "Creating network with " + str(n) + " activation sites" print " and "+str(len(rulesList))+" additional rules (" \ +str(mult*(n+len(rulesList)))+" parameters)." namesList = writeBNGL.writeBNGLnetwork(n,rulesList,filename, \ MichaelisMenten=self.MichaelisMenten) self._runBNGLfile(filename) if self.verbose: print "Network creation took " + bothTimeStr(start, startWall) return namesList
def modelOutput(self,params): """ Returns model output as array: output[0] = time series for species 1, output[1] = time series for species 2, ... """ netFile,namesList = self.filename,self.namesList endTime,nSteps = self.endTime,self.nSteps # use BNG to integrate the model writeBNGL.writeModifiedNet(netFile,namesList,params,"_modified") writeBNGL.writeBNGLsimulate(netFile+"_modified",endTime,nSteps) self._runBNGLfile(netFile+"_modified_simulate") # or use (slow) #writeBNGL.writeBNGLsimulateSlow(filename,namesList,params,endTime,nSteps) #os.system(BNGpath+"Perl2/BNG2.pl "+filename+"_simulate.bngl > " \ # +filename+"_simulate_messages.txt") # read in output of model output = self._readModelOutput(netFile+"_modified_simulate.cdat") self.recentOutput = output return output
def modelOutput(self, params): """ Returns model output as array: output[0] = time series for species 1, output[1] = time series for species 2, ... """ netFile, namesList = self.filename, self.namesList endTime, nSteps = self.endTime, self.nSteps # use BNG to integrate the model writeBNGL.writeModifiedNet(netFile, namesList, params, "_modified") writeBNGL.writeBNGLsimulate(netFile + "_modified", endTime, nSteps) self._runBNGLfile(netFile + "_modified_simulate") # or use (slow) #writeBNGL.writeBNGLsimulateSlow(filename,namesList,params,endTime,nSteps) #os.system(BNGpath+"Perl2/BNG2.pl "+filename+"_simulate.bngl > " \ # +filename+"_simulate_messages.txt") # read in output of model output = self._readModelOutput(netFile + "_modified_simulate.cdat") self.recentOutput = output return output
def writeSBML(self,params): writeBNGL.writeBNGL_SBML(self.filename,self.namesList,params) self._runBNGLfile(self.filename[:-4]+"sbml") return self.filename[:-4]+"sbml.xml"
def writeSBML(self, params): writeBNGL.writeBNGL_SBML(self.filename, self.namesList, params) self._runBNGLfile(self.filename[:-4] + "sbml") return self.filename[:-4] + "sbml.xml"