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...	...	@@ -235,9 +235,290 @@
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	+(% class="wikigeneratedid" %)
	327	+=== [[image:image-20220127165908-2.png||height="659" width="1149"]] ===
	328	+
	329	+=== Connecting the network nodes: neuronal populations, Poisson processes and spike detectors ===
	330	+
	331	+{{code language="python"}}
	332	+#############################------------------------------------------------------------------------
	333	+print("Connecting ")
	334	+#############################------------------------------------------------------------------------
	335	+
	336	+startconnect = time.time()
	337	+Connessioni=[]
	338	+Medie=[]
	339	+
	340	+#create and define the connections between the populations of neurons and the poisson generators
	341	+#and between the populations of neurons and the spike detectors with the parameters extracted from the.ini files
	342	+
	343	+for i in range(0,int(InfoBuild[0])):
	344	+ nest.Connect(NoisePop[i], NeuronPop[i], syn_spec={'synapse_model': 'static_synapse_hpc',
	345	+ 'delay': dt,
	346	+ 'weight': nest.math.redraw(nest.random.normal(mean=float(InfoConnectNoise[i+1][0]),
	347	+ std=(float(InfoConnectNoise[i+1][1])*float(InfoConnectNoise[i+1][0]))),
	348	+ min=0., max=float('Inf'))
	349	+ })
	350	+ nest.Connect(NeuronPop[i][:int(InfoBuild[i+1][0])], DetectorPop[i], syn_spec={"weight": 1.0, "delay": dt})
	351	+
	352	+#create and define the connections between the populations of neurons with the parameters extracted from the.ini files
	353	+
	354	+for i in range(0,len(InfoConnectPop[1:])):
	355	+
	356	+ conn=nest.Connect(NeuronPop[int(InfoConnectPop[i+1][1])], NeuronPop[int(InfoConnectPop[i+1][0])],
	357	+ {'rule': 'pairwise_bernoulli',
	358	+ 'p':float(InfoConnectPop[i+1][2]) },
	359	+ syn_spec={'synapse_model': 'static_synapse_hpc',
	360	+ 'delay':nest.math.redraw(nest.random.exponential(beta=float(1./(2.99573227355/(float(InfoConnectPop[i+1][4])-float(InfoConnectPop[i+1][3]))))),
	361	+ min= numpy.max([dt,float(1./float(InfoConnectPop[i+1][4]))]),
	362	+ max= float(1./(float(InfoConnectPop[i+1][3])-dt/2))),
	363	+
	364	+ 'weight':nest.random.normal(mean=float(InfoConnectPop[i+1][6]),
	365	+ std=math.fabs(float(InfoConnectPop[i+1][6])*float(InfoConnectPop[i+1][7])))})
	366	+
	367	+
	368	+endconnect = time.time()
	369	+{{/code}}
	370	+
	371	+=== ===
	372	+
	373	+=== ===
	374	+
	375	+=== Simulating: neuronal time evolution. ===
	376	+
	377	+=== ===
	378	+
	379	+{{code language="python"}}
	380	+ #############################------------------------------------------------------------------------
	381	+ print("Simulating")
	382	+ #############################------------------------------------------------------------------------
	383	+ ###################################################################################################################################################################
	384	+ if Salva:
	385	+ print("I m going to save the data")
	386	+ #x=str(iterazioni)
	387	+ f = open(FileName,"w")
	388	+ if len(InfoProtocol):
	389	+ print("I m going to split the simulation")
	390	+ tempo=0
	391	+ for contatore in range(0,len(InfoProtocol)):
	392	+ appoggio1=int((tempo+InfoProtocol[contatore][0])/1000.)
	393	+ appoggio2=int(tempo/1000.)
	394	+ appoggio3=tempo+InfoProtocol[contatore][0]
	395	+ if (appoggio1-appoggio2)>=1:
	396	+ T1=(1+appoggio2)*1000-tempo
	397	+ nest.Simulate(T1)
	398	+ #Save the Data!!!!
	399	+ ###########################################################
	400	+ Equilibri=[]
	401	+ for i in range(0,int(InfoBuild[0])):
	402	+ Equilibri.append([])
	403	+ a=nest.GetStatus(DetectorPop[i])[0]["events"]["times"]
	404	+ if len(a)>0:
	405	+ Trange=(1000*int(numpy.min(a)/1000.),1000*int(numpy.min(a)/1000.)+1000)
	406	+ hist,Tbin=numpy.histogram(a,200,(Trange[0],Trange[1]))
	407	+ Equilibri[i]=hist*1000./(5.*int(InfoBuild[i+1][0]))
	408	+ else:
	409	+ Trange=(1000*int(tempo/1000.),1000*int(tempo/1000.)+1000)
	410	+ hist=numpy.zeros(200)
	411	+ Tbin=numpy.linspace(Trange[0],Trange[1],num=201)
	412	+ Equilibri[i]=hist
	413	+ nest.SetStatus(DetectorPop[i],{'n_events':0})
	414	+ for j in range(0,len(hist)):
	415	+ f.write(str(Tbin[j])+" ")
	416	+ for i in range(0,int(InfoBuild[0])):
	417	+ f.write(str(Equilibri[i][j])+" ")
	418	+ f.write("\n ")
	419	+ ###########################################################
	420	+ tempo=tempo+T1
	421	+ for contatore2 in range(1,(appoggio1-appoggio2)):
	422	+ nest.Simulate(1000.)
	423	+ #Save the Data!!!!
	424	+ ###########################################################
	425	+ Equilibri=[]
	426	+ for i in range(0,int(InfoBuild[0])):
	427	+ Equilibri.append([])
	428	+ a=nest.GetStatus(DetectorPop[i])[0]["events"]["times"]
	429	+ if len(a)>0:
	430	+ Trange=(1000*int(numpy.min(a)/1000.),1000*int(numpy.min(a)/1000.)+1000)
	431	+ hist,Tbin=numpy.histogram(a,200,(Trange[0],Trange[1]))
	432	+ Equilibri[i]=hist*1000./(5.*int(InfoBuild[i+1][0]))
	433	+ else:
	434	+ Trange=(1000*int(tempo/1000.),1000*int(tempo/1000.)+1000)
	435	+ hist=numpy.zeros(200)
	436	+ Tbin=numpy.linspace(Trange[0],Trange[1],num=201)
	437	+ Equilibri[i]=hist
	438	+ nest.SetStatus(DetectorPop[i],{'n_events':0})
	439	+ for j in range(0,len(hist)):
	440	+ f.write(str(Tbin[j])+" ")
	441	+ for i in range(0,int(InfoBuild[0])):
	442	+ f.write(str(Equilibri[i][j])+" ")
	443	+ f.write("\n ")
	444	+ tempo=tempo+1000.
	445	+ T2=appoggio3-tempo
	446	+ nest.Simulate(T2);
	447	+ tempo=tempo+T2;
	448	+ else:
	449	+ nest.Simulate(InfoProtocol[contatore][0])
	450	+ temp=InfoProtocol[contatore][0]
	451	+ tempo=tempo+temp
	452	+ if InfoProtocol[contatore][2]==4:
	453	+ nest.SetStatus(NoisePop[InfoProtocol[contatore][1]],params={"rate": float(InfoBuild[1+InfoProtocol[contatore][1]][2]*InfoProtocol[contatore][3])})
	454	+ if InfoProtocol[contatore][2]==12:
	455	+ nest.SetStatus(NeuronPop[InfoProtocol[contatore][1]], params={"b": float(InfoProtocol[contatore][3])})
	456	+ else:
	457	+ nest.Simulate(simtime)
	458	+ tempo=simtime
	459	+ if (simtime-tempo)>0.:
	460	+ nest.Simulate(simtime-tempo)
	461	+
	462	+
	463	+ endsimulate = time.time()
	464	+ f.close()
	465	+ else:
	466	+ if len(InfoProtocol):
	467	+ tempo=0
	468	+ for contatore in range(0,len(InfoProtocol)):
	469	+ nest.Simulate(InfoProtocol[contatore][0])
	470	+ temp=InfoProtocol[contatore][0]
	471	+ tempo=tempo+temp
	472	+ if InfoProtocol[contatore][2]==4:
	473	+ nest.SetStatus(NoisePop[InfoProtocol[contatore][1]],params={"rate": float(InfoBuild[1+InfoProtocol[contatore][1]][2]*InfoProtocol[contatore][3])})
	474	+ #print "Population:", InfoProtocol[contatore][1] ,";Parameter:", InfoProtocol[contatore][2] ,"; Value: ",InfoProtocol[contatore][3]
	475	+ if InfoProtocol[contatore][2]==12:
	476	+ nest.SetStatus(NeuronPop[InfoProtocol[contatore][1]], params={"b": float(InfoProtocol[contatore][3])})
	477	+ #print "Population:", InfoProtocol[contatore][1] ,";Parameter:", InfoProtocol[contatore][2] ,"; Value: ",InfoProtocol[contatore][3]
	478	+
	479	+ else:
	480	+ nest.Simulate(simtime)
	481	+ tempo=simtime
	482	+ if (simtime-tempo)>0.:
	483	+ nest.Simulate(simtime-tempo)
	484	+ endsimulate = time.time()
	485	+
	486	+
	487	+ ###################################################################################################################################################################
	488	+
	489	+ #############################------------------------------------------------------------------------
	490	+ #print some information from the simulation
	491	+ #############################------------------------------------------------------------------------
	492	+
	493	+ num_synapses = nest.GetDefaults('static_synapse_hpc')["num_connections"]
	494	+ build_time = endbuild - startbuild
	495	+ connect_time = endconnect - startconnect
	496	+ sim_time = endsimulate - endconnect
	497	+
	498	+ N_neurons=0
	499	+ for i in range(0,int(InfoBuild[0])):
	500	+ N_neurons=N_neurons+int(InfoBuild[i+1][0])
	501	+
	502	+ print(" Network simulation (Python) neuron type:",InfoPerseo[0])
	503	+ print("Number of neurons : {0}".format(N_neurons))
	504	+ print("Number of synapses: {0}".format(num_synapses))
	505	+ print("Building time : %.2f s" % build_time)
	506	+ print("Connecting time : %.2f s" % connect_time)
	507	+ print("Simulation time : %.2f s" % sim_time)
	508	+
	509	+Fine=time.time()
	510	+print ("Total Simulation time : %.2f s" % (Fine-Inizio))
	511	+{{/code}}
	512	+
	513	+=== ===
	514	+
	515	+=== Results: ===
	516	+
	517	+the output of this simulationo is...
	518	+
	519	+
	520	+
	521	+
	522	+
	523	+
243	243	==== ====

image-20220127165822-1.png

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