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Last modified by galluzziandrea on 2022/06/20 12:33
From version 7.1
edited by galluzziandrea
on 2021/12/09 14:49
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To version 20.1
edited by galluzziandrea
on 2022/01/27 17:12
Change comment: There is no comment for this version

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... ... @@ -235,9 +235,296 @@
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 +=== [[image:image-20220127165908-2.png||height="659" width="1149"]] ===
327 +
328 +=== Connecting the network nodes: neuronal populations, Poisson processes and spike detectors ===
329 +
330 +{{code language="python"}}
331 +#############################------------------------------------------------------------------------
332 +print("Connecting ")
333 +#############################------------------------------------------------------------------------
334 +
335 +startconnect = time.time()
336 +Connessioni=[]
337 +Medie=[]
338 +
339 +#create and define the connections between the populations of neurons and the poisson generators
340 +#and between the populations of neurons and the spike detectors with the parameters extracted from the.ini files
341 +
342 +for i in range(0,int(InfoBuild[0])):
343 + nest.Connect(NoisePop[i], NeuronPop[i], syn_spec={'synapse_model': 'static_synapse_hpc',
344 + 'delay': dt,
345 + 'weight': nest.math.redraw(nest.random.normal(mean=float(InfoConnectNoise[i+1][0]),
346 + std=(float(InfoConnectNoise[i+1][1])*float(InfoConnectNoise[i+1][0]))),
347 + min=0., max=float('Inf'))
348 + })
349 + nest.Connect(NeuronPop[i][:int(InfoBuild[i+1][0])], DetectorPop[i], syn_spec={"weight": 1.0, "delay": dt})
350 +
351 +#create and define the connections between the populations of neurons with the parameters extracted from the.ini files
352 +
353 +for i in range(0,len(InfoConnectPop[1:])):
354 +
355 + conn=nest.Connect(NeuronPop[int(InfoConnectPop[i+1][1])], NeuronPop[int(InfoConnectPop[i+1][0])],
356 + {'rule': 'pairwise_bernoulli',
357 + 'p':float(InfoConnectPop[i+1][2]) },
358 + syn_spec={'synapse_model': 'static_synapse_hpc',
359 + 'delay':nest.math.redraw(nest.random.exponential(beta=float(1./(2.99573227355/(float(InfoConnectPop[i+1][4])-float(InfoConnectPop[i+1][3]))))),
360 + min= numpy.max([dt,float(1./float(InfoConnectPop[i+1][4]))]),
361 + max= float(1./(float(InfoConnectPop[i+1][3])-dt/2))),
362 +
363 + 'weight':nest.random.normal(mean=float(InfoConnectPop[i+1][6]),
364 + std=math.fabs(float(InfoConnectPop[i+1][6])*float(InfoConnectPop[i+1][7])))})
365 +
366 +
367 +endconnect = time.time()
368 +{{/code}}
369 +
370 +=== ===
371 +
372 +=== ===
373 +
374 +=== [[image:image-20220127170722-1.png]] ===
375 +
376 +=== Simulating: neuronal time evolution. ===
377 +
378 +=== ===
379 +
380 +{{code language="python"}}
381 + #############################------------------------------------------------------------------------
382 + print("Simulating")
383 + #############################------------------------------------------------------------------------
384 + ###################################################################################################################################################################
385 + if Salva:
386 + print("I m going to save the data")
387 + #x=str(iterazioni)
388 + f = open(FileName,"w")
389 + if len(InfoProtocol):
390 + print("I m going to split the simulation")
391 + tempo=0
392 + for contatore in range(0,len(InfoProtocol)):
393 + appoggio1=int((tempo+InfoProtocol[contatore][0])/1000.)
394 + appoggio2=int(tempo/1000.)
395 + appoggio3=tempo+InfoProtocol[contatore][0]
396 + if (appoggio1-appoggio2)>=1:
397 + T1=(1+appoggio2)*1000-tempo
398 + nest.Simulate(T1)
399 + #Save the Data!!!!
400 + ###########################################################
401 + Equilibri=[]
402 + for i in range(0,int(InfoBuild[0])):
403 + Equilibri.append([])
404 + a=nest.GetStatus(DetectorPop[i])[0]["events"]["times"]
405 + if len(a)>0:
406 + Trange=(1000*int(numpy.min(a)/1000.),1000*int(numpy.min(a)/1000.)+1000)
407 + hist,Tbin=numpy.histogram(a,200,(Trange[0],Trange[1]))
408 + Equilibri[i]=hist*1000./(5.*int(InfoBuild[i+1][0]))
409 + else:
410 + Trange=(1000*int(tempo/1000.),1000*int(tempo/1000.)+1000)
411 + hist=numpy.zeros(200)
412 + Tbin=numpy.linspace(Trange[0],Trange[1],num=201)
413 + Equilibri[i]=hist
414 + nest.SetStatus(DetectorPop[i],{'n_events':0})
415 + for j in range(0,len(hist)):
416 + f.write(str(Tbin[j])+" ")
417 + for i in range(0,int(InfoBuild[0])):
418 + f.write(str(Equilibri[i][j])+" ")
419 + f.write("\n ")
420 + ###########################################################
421 + tempo=tempo+T1
422 + for contatore2 in range(1,(appoggio1-appoggio2)):
423 + nest.Simulate(1000.)
424 + #Save the Data!!!!
425 + ###########################################################
426 + Equilibri=[]
427 + for i in range(0,int(InfoBuild[0])):
428 + Equilibri.append([])
429 + a=nest.GetStatus(DetectorPop[i])[0]["events"]["times"]
430 + if len(a)>0:
431 + Trange=(1000*int(numpy.min(a)/1000.),1000*int(numpy.min(a)/1000.)+1000)
432 + hist,Tbin=numpy.histogram(a,200,(Trange[0],Trange[1]))
433 + Equilibri[i]=hist*1000./(5.*int(InfoBuild[i+1][0]))
434 + else:
435 + Trange=(1000*int(tempo/1000.),1000*int(tempo/1000.)+1000)
436 + hist=numpy.zeros(200)
437 + Tbin=numpy.linspace(Trange[0],Trange[1],num=201)
438 + Equilibri[i]=hist
439 + nest.SetStatus(DetectorPop[i],{'n_events':0})
440 + for j in range(0,len(hist)):
441 + f.write(str(Tbin[j])+" ")
442 + for i in range(0,int(InfoBuild[0])):
443 + f.write(str(Equilibri[i][j])+" ")
444 + f.write("\n ")
445 + tempo=tempo+1000.
446 + T2=appoggio3-tempo
447 + nest.Simulate(T2);
448 + tempo=tempo+T2;
449 + else:
450 + nest.Simulate(InfoProtocol[contatore][0])
451 + temp=InfoProtocol[contatore][0]
452 + tempo=tempo+temp
453 + if InfoProtocol[contatore][2]==4:
454 + nest.SetStatus(NoisePop[InfoProtocol[contatore][1]],params={"rate": float(InfoBuild[1+InfoProtocol[contatore][1]][2]*InfoProtocol[contatore][3])})
455 + if InfoProtocol[contatore][2]==12:
456 + nest.SetStatus(NeuronPop[InfoProtocol[contatore][1]], params={"b": float(InfoProtocol[contatore][3])})
457 + else:
458 + nest.Simulate(simtime)
459 + tempo=simtime
460 + if (simtime-tempo)>0.:
461 + nest.Simulate(simtime-tempo)
462 +
463 +
464 + endsimulate = time.time()
465 + f.close()
466 + else:
467 + if len(InfoProtocol):
468 + tempo=0
469 + for contatore in range(0,len(InfoProtocol)):
470 + nest.Simulate(InfoProtocol[contatore][0])
471 + temp=InfoProtocol[contatore][0]
472 + tempo=tempo+temp
473 + if InfoProtocol[contatore][2]==4:
474 + nest.SetStatus(NoisePop[InfoProtocol[contatore][1]],params={"rate": float(InfoBuild[1+InfoProtocol[contatore][1]][2]*InfoProtocol[contatore][3])})
475 + #print "Population:", InfoProtocol[contatore][1] ,";Parameter:", InfoProtocol[contatore][2] ,"; Value: ",InfoProtocol[contatore][3]
476 + if InfoProtocol[contatore][2]==12:
477 + nest.SetStatus(NeuronPop[InfoProtocol[contatore][1]], params={"b": float(InfoProtocol[contatore][3])})
478 + #print "Population:", InfoProtocol[contatore][1] ,";Parameter:", InfoProtocol[contatore][2] ,"; Value: ",InfoProtocol[contatore][3]
479 +
480 + else:
481 + nest.Simulate(simtime)
482 + tempo=simtime
483 + if (simtime-tempo)>0.:
484 + nest.Simulate(simtime-tempo)
485 + endsimulate = time.time()
486 +
487 +
488 + ###################################################################################################################################################################
489 +
490 + #############################------------------------------------------------------------------------
491 + #print some information from the simulation
492 + #############################------------------------------------------------------------------------
493 +
494 + num_synapses = nest.GetDefaults('static_synapse_hpc')["num_connections"]
495 + build_time = endbuild - startbuild
496 + connect_time = endconnect - startconnect
497 + sim_time = endsimulate - endconnect
498 +
499 + N_neurons=0
500 + for i in range(0,int(InfoBuild[0])):
501 + N_neurons=N_neurons+int(InfoBuild[i+1][0])
502 +
503 + print(" Network simulation (Python) neuron type:",InfoPerseo[0])
504 + print("Number of neurons : {0}".format(N_neurons))
505 + print("Number of synapses: {0}".format(num_synapses))
506 + print("Building time : %.2f s" % build_time)
507 + print("Connecting time : %.2f s" % connect_time)
508 + print("Simulation time : %.2f s" % sim_time)
509 +
510 +Fine=time.time()
511 +print ("Total Simulation time : %.2f s" % (Fine-Inizio))
512 +{{/code}}
513 +
514 +=== ===
515 +
516 +=== ===
517 +
518 +(% class="wikigeneratedid" %)
519 +=== [[image:image-20220127171242-1.png]] ===
520 +
521 +=== Results: ===
522 +
523 +the output of this simulationo is...
524 +
525 +
526 +
527 +
528 +
529 +
243 243  ==== ====
image-20220127165822-1.png
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