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"
