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...	...	@@ -235,9 +235,287 @@
235	235	# [.....],[],...]
236	236	{{/code}}
237	237
	238	+=== Defining general and nest.kernel parameters ===
238	238
	240	+{{code language="python"}}
	241	+#############################------------------------------------------------------------------------
	242	+#Clean the Network
	243	+#############################------------------------------------------------------------------------
	244	+nest.ResetKernel()
239	239
	246	+#############################------------------------------------------------------------------------
	247	+#insert the introductory parameters of the simulation
	248	+#############################------------------------------------------------------------------------
240	240
241		-=== Results ===
242	242
	251	+dt = 0.1 # the resolution in ms
	252	+StartMisure=0. # start time of measurements
	253	+simtime = int(float(InfoPerseo[3])) # Simulation time in ms (200 s)
	254	+if simtime<=StartMisure: # If the simulation time is less than StartMisure, it is increased by StartMisure
	255	+ simtime=simtime+StartMisure
	256	+start=0.0 # start time of poissonian processes
	257	+origin=0.0 # temporal origin
	258	+
	259	+#############################------------------------------------------------------------------------
	260	+# Kernel parameters
	261	+#############################------------------------------------------------------------------------
	262	+LNT=multiprocessing.cpu_count();
	263	+nest.SetKernelStatus({"local_num_threads": LNT})
	264	+nest.SetKernelStatus({"resolution": dt, "print_time": True,
	265	+ "overwrite_files": True})
	266	+
	267	+#############################------------------------------------------------------------------------
	268	+#"randomize" the seeds of the random generators
	269	+#############################------------------------------------------------------------------------
	270	+
	271	+#msd = int(math.fabs(time.process_time()*1000))
	272	+#N_vp = nest.GetKernelStatus(['total_num_virtual_procs'])[0]
	273	+#pyrngs = [numpy.random.RandomState(s) for s in range(msd, msd+N_vp)]
	274	+#nest.SetKernelStatus({"grng_seed" : msd+N_vp})
	275	+#nest.SetKernelStatus({"rng_seeds" : list(range(msd+N_vp+1, msd+2*N_vp+1))})
	276	+{{/code}}
	277	+
	278	+=== Building the network: neuronal populations , Poisson processes and spike detectors ===
	279	+
	280	+{{code language="python"}}
	281	+#############################------------------------------------------------------------------------
	282	+print("Building network")
	283	+#############################------------------------------------------------------------------------
	284	+
	285	+startbuild = time.time() #initialize the calculation of the time used to simulate
	286	+
	287	+NeuronPop=[]
	288	+NoisePop=[]
	289	+DetectorPop=[]
	290	+
	291	+#define and initialize the populations of neurons with the parameters extracted from the.ini files
	292	+for i in range(1,int(InfoBuild[0])+1):
	293	+ if int(InfoBuild[i][7])==0:
	294	+ app=float(InfoBuild[i][5])
	295	+ else:
	296	+ app=0.
	297	+ app2= nest.Create("aeif_psc_exp", int(InfoBuild[i][0]),params={"C_m": 1.0,
	298	+ "g_L": 1.0/float(InfoBuild[i][3]),
	299	+ "t_ref": float(InfoBuild[i][6]),
	300	+ "E_L": 0.0,
	301	+ "V_reset": float(InfoBuild[i][5]),
	302	+ "V_m": app,
	303	+ "V_th": float(InfoBuild[i][4]),
	304	+ "Delta_T": 0.,
	305	+ "tau_syn_ex": 1.0,
	306	+ "tau_syn_in": 1.0,
	307	+ "a": 0.0,
	308	+ "b": float(InfoBuild[i][10]),
	309	+ "tau_w": float(InfoBuild[i][9]),
	310	+ "V_peak":float(InfoBuild[i][4])+10.0})
	311	+ NeuronPop.append(app2)
	312	+
	313	+#define and initialize the poisson generators and the spike detectors with the parameters extracted from the.ini files
	314	+
	315	+for i in range(1,int(InfoBuild[0])+1):
	316	+ app3= nest.Create("poisson_generator",params={"rate": float(InfoBuild[i][1]*InfoBuild[i][2]),
	317	+ 'origin':0.,
	318	+ 'start':start})
	319	+ NoisePop.append(app3)
	320	+ app4 = nest.Create("spike_recorder",params={ "start":StartMisure})
	321	+ DetectorPop.append(app4)
	322	+
	323	+endbuild = time.time()
	324	+{{/code}}
	325	+
	326	+=== Connecting the network nodes: neuronal populations, Poisson processes and spike detectors ===
	327	+
	328	+{{code language="python"}}
	329	+#############################------------------------------------------------------------------------
	330	+print("Connecting ")
	331	+#############################------------------------------------------------------------------------
	332	+
	333	+startconnect = time.time()
	334	+Connessioni=[]
	335	+Medie=[]
	336	+
	337	+#create and define the connections between the populations of neurons and the poisson generators
	338	+#and between the populations of neurons and the spike detectors with the parameters extracted from the.ini files
	339	+
	340	+for i in range(0,int(InfoBuild[0])):
	341	+ nest.Connect(NoisePop[i], NeuronPop[i], syn_spec={'synapse_model': 'static_synapse_hpc',
	342	+ 'delay': dt,
	343	+ 'weight': nest.math.redraw(nest.random.normal(mean=float(InfoConnectNoise[i+1][0]),
	344	+ std=(float(InfoConnectNoise[i+1][1])*float(InfoConnectNoise[i+1][0]))),
	345	+ min=0., max=float('Inf'))
	346	+ })
	347	+ nest.Connect(NeuronPop[i][:int(InfoBuild[i+1][0])], DetectorPop[i], syn_spec={"weight": 1.0, "delay": dt})
	348	+
	349	+#create and define the connections between the populations of neurons with the parameters extracted from the.ini files
	350	+
	351	+for i in range(0,len(InfoConnectPop[1:])):
	352	+
	353	+ conn=nest.Connect(NeuronPop[int(InfoConnectPop[i+1][1])], NeuronPop[int(InfoConnectPop[i+1][0])],
	354	+ {'rule': 'pairwise_bernoulli',
	355	+ 'p':float(InfoConnectPop[i+1][2]) },
	356	+ syn_spec={'synapse_model': 'static_synapse_hpc',
	357	+ 'delay':nest.math.redraw(nest.random.exponential(beta=float(1./(2.99573227355/(float(InfoConnectPop[i+1][4])-float(InfoConnectPop[i+1][3]))))),
	358	+ min= numpy.max([dt,float(1./float(InfoConnectPop[i+1][4]))]),
	359	+ max= float(1./(float(InfoConnectPop[i+1][3])-dt/2))),
	360	+
	361	+ 'weight':nest.random.normal(mean=float(InfoConnectPop[i+1][6]),
	362	+ std=math.fabs(float(InfoConnectPop[i+1][6])*float(InfoConnectPop[i+1][7])))})
	363	+
	364	+
	365	+endconnect = time.time()
	366	+{{/code}}
	367	+
	368	+=== ===
	369	+
	370	+=== ===
	371	+
	372	+=== Simulating: neuronal time evolution. ===
	373	+
	374	+=== ===
	375	+
	376	+{{code language="python"}}
	377	+ #############################------------------------------------------------------------------------
	378	+ print("Simulating")
	379	+ #############################------------------------------------------------------------------------
	380	+ ###################################################################################################################################################################
	381	+ if Salva:
	382	+ print("I m going to save the data")
	383	+ #x=str(iterazioni)
	384	+ f = open(FileName,"w")
	385	+ if len(InfoProtocol):
	386	+ print("I m going to split the simulation")
	387	+ tempo=0
	388	+ for contatore in range(0,len(InfoProtocol)):
	389	+ appoggio1=int((tempo+InfoProtocol[contatore][0])/1000.)
	390	+ appoggio2=int(tempo/1000.)
	391	+ appoggio3=tempo+InfoProtocol[contatore][0]
	392	+ if (appoggio1-appoggio2)>=1:
	393	+ T1=(1+appoggio2)*1000-tempo
	394	+ nest.Simulate(T1)
	395	+ #Save the Data!!!!
	396	+ ###########################################################
	397	+ Equilibri=[]
	398	+ for i in range(0,int(InfoBuild[0])):
	399	+ Equilibri.append([])
	400	+ a=nest.GetStatus(DetectorPop[i])[0]["events"]["times"]
	401	+ if len(a)>0:
	402	+ Trange=(1000*int(numpy.min(a)/1000.),1000*int(numpy.min(a)/1000.)+1000)
	403	+ hist,Tbin=numpy.histogram(a,200,(Trange[0],Trange[1]))
	404	+ Equilibri[i]=hist*1000./(5.*int(InfoBuild[i+1][0]))
	405	+ else:
	406	+ Trange=(1000*int(tempo/1000.),1000*int(tempo/1000.)+1000)
	407	+ hist=numpy.zeros(200)
	408	+ Tbin=numpy.linspace(Trange[0],Trange[1],num=201)
	409	+ Equilibri[i]=hist
	410	+ nest.SetStatus(DetectorPop[i],{'n_events':0})
	411	+ for j in range(0,len(hist)):
	412	+ f.write(str(Tbin[j])+" ")
	413	+ for i in range(0,int(InfoBuild[0])):
	414	+ f.write(str(Equilibri[i][j])+" ")
	415	+ f.write("\n ")
	416	+ ###########################################################
	417	+ tempo=tempo+T1
	418	+ for contatore2 in range(1,(appoggio1-appoggio2)):
	419	+ nest.Simulate(1000.)
	420	+ #Save the Data!!!!
	421	+ ###########################################################
	422	+ Equilibri=[]
	423	+ for i in range(0,int(InfoBuild[0])):
	424	+ Equilibri.append([])
	425	+ a=nest.GetStatus(DetectorPop[i])[0]["events"]["times"]
	426	+ if len(a)>0:
	427	+ Trange=(1000*int(numpy.min(a)/1000.),1000*int(numpy.min(a)/1000.)+1000)
	428	+ hist,Tbin=numpy.histogram(a,200,(Trange[0],Trange[1]))
	429	+ Equilibri[i]=hist*1000./(5.*int(InfoBuild[i+1][0]))
	430	+ else:
	431	+ Trange=(1000*int(tempo/1000.),1000*int(tempo/1000.)+1000)
	432	+ hist=numpy.zeros(200)
	433	+ Tbin=numpy.linspace(Trange[0],Trange[1],num=201)
	434	+ Equilibri[i]=hist
	435	+ nest.SetStatus(DetectorPop[i],{'n_events':0})
	436	+ for j in range(0,len(hist)):
	437	+ f.write(str(Tbin[j])+" ")
	438	+ for i in range(0,int(InfoBuild[0])):
	439	+ f.write(str(Equilibri[i][j])+" ")
	440	+ f.write("\n ")
	441	+ tempo=tempo+1000.
	442	+ T2=appoggio3-tempo
	443	+ nest.Simulate(T2);
	444	+ tempo=tempo+T2;
	445	+ else:
	446	+ nest.Simulate(InfoProtocol[contatore][0])
	447	+ temp=InfoProtocol[contatore][0]
	448	+ tempo=tempo+temp
	449	+ if InfoProtocol[contatore][2]==4:
	450	+ nest.SetStatus(NoisePop[InfoProtocol[contatore][1]],params={"rate": float(InfoBuild[1+InfoProtocol[contatore][1]][2]*InfoProtocol[contatore][3])})
	451	+ if InfoProtocol[contatore][2]==12:
	452	+ nest.SetStatus(NeuronPop[InfoProtocol[contatore][1]], params={"b": float(InfoProtocol[contatore][3])})
	453	+ else:
	454	+ nest.Simulate(simtime)
	455	+ tempo=simtime
	456	+ if (simtime-tempo)>0.:
	457	+ nest.Simulate(simtime-tempo)
	458	+
	459	+
	460	+ endsimulate = time.time()
	461	+ f.close()
	462	+ else:
	463	+ if len(InfoProtocol):
	464	+ tempo=0
	465	+ for contatore in range(0,len(InfoProtocol)):
	466	+ nest.Simulate(InfoProtocol[contatore][0])
	467	+ temp=InfoProtocol[contatore][0]
	468	+ tempo=tempo+temp
	469	+ if InfoProtocol[contatore][2]==4:
	470	+ nest.SetStatus(NoisePop[InfoProtocol[contatore][1]],params={"rate": float(InfoBuild[1+InfoProtocol[contatore][1]][2]*InfoProtocol[contatore][3])})
	471	+ #print "Population:", InfoProtocol[contatore][1] ,";Parameter:", InfoProtocol[contatore][2] ,"; Value: ",InfoProtocol[contatore][3]
	472	+ if InfoProtocol[contatore][2]==12:
	473	+ nest.SetStatus(NeuronPop[InfoProtocol[contatore][1]], params={"b": float(InfoProtocol[contatore][3])})
	474	+ #print "Population:", InfoProtocol[contatore][1] ,";Parameter:", InfoProtocol[contatore][2] ,"; Value: ",InfoProtocol[contatore][3]
	475	+
	476	+ else:
	477	+ nest.Simulate(simtime)
	478	+ tempo=simtime
	479	+ if (simtime-tempo)>0.:
	480	+ nest.Simulate(simtime-tempo)
	481	+ endsimulate = time.time()
	482	+
	483	+
	484	+ ###################################################################################################################################################################
	485	+
	486	+ #############################------------------------------------------------------------------------
	487	+ #print some information from the simulation
	488	+ #############################------------------------------------------------------------------------
	489	+
	490	+ num_synapses = nest.GetDefaults('static_synapse_hpc')["num_connections"]
	491	+ build_time = endbuild - startbuild
	492	+ connect_time = endconnect - startconnect
	493	+ sim_time = endsimulate - endconnect
	494	+
	495	+ N_neurons=0
	496	+ for i in range(0,int(InfoBuild[0])):
	497	+ N_neurons=N_neurons+int(InfoBuild[i+1][0])
	498	+
	499	+ print(" Network simulation (Python) neuron type:",InfoPerseo[0])
	500	+ print("Number of neurons : {0}".format(N_neurons))
	501	+ print("Number of synapses: {0}".format(num_synapses))
	502	+ print("Building time : %.2f s" % build_time)
	503	+ print("Connecting time : %.2f s" % connect_time)
	504	+ print("Simulation time : %.2f s" % sim_time)
	505	+
	506	+Fine=time.time()
	507	+print ("Total Simulation time : %.2f s" % (Fine-Inizio))
	508	+{{/code}}
	509	+
	510	+=== ===
	511	+
	512	+=== Results: ===
	513	+
	514	+the output of this simulationo is...
	515	+
	516	+
	517	+
	518	+
	519	+
	520	+
243	243	==== ====