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Last modified by galluzziandrea on 2022/06/20 12:33
From version 8.1
edited by galluzziandrea
on 2021/12/09 14:58
Change comment: There is no comment for this version
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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... ... @@ -323,6 +323,208 @@
323 323  endbuild = time.time()
324 324  {{/code}}
325 325  
326 -=== Results ===
326 +=== [[image:image-20220127165908-2.png||height="659" width="1149"]] ===
327 327  
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 +
328 328  ==== ====
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