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Last modified by galluzziandrea on 2022/06/20 12:33
From version 28.1
edited by mattia
on 2022/01/28 13:39
Change comment: There is no comment for this version
To version 7.1
edited by galluzziandrea
on 2021/12/09 14:49
Change comment: There is no comment for this version

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1 -XWiki.mattia
1 +XWiki.galluzziandrea
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235 235  # [.....],[],...]
236 236  {{/code}}
237 237  
238 -=== [[image:image-20220127173048-1.png||height="508" width="948"]] ===
239 239  
240 -=== Defining general and nest.kernel parameters ===
241 241  
242 -{{code language="python"}}
243 -#############################------------------------------------------------------------------------
244 -#Clean the Network
245 -#############################------------------------------------------------------------------------
246 -nest.ResetKernel()
247 247  
248 -#############################------------------------------------------------------------------------
249 -#insert the introductory parameters of the simulation
250 -#############################------------------------------------------------------------------------
241 +=== Results ===
251 251  
252 -
253 -dt = 0.1 # the resolution in ms
254 -StartMisure=0. # start time of measurements
255 -simtime = int(float(InfoPerseo[3])) # Simulation time in ms (200 s)
256 -if simtime<=StartMisure: # If the simulation time is less than StartMisure, it is increased by StartMisure
257 - simtime=simtime+StartMisure
258 -start=0.0 # start time of poissonian processes
259 -origin=0.0 # temporal origin
260 -
261 -#############################------------------------------------------------------------------------
262 -# Kernel parameters
263 -#############################------------------------------------------------------------------------
264 -LNT=multiprocessing.cpu_count();
265 -nest.SetKernelStatus({"local_num_threads": LNT})
266 -nest.SetKernelStatus({"resolution": dt, "print_time": True,
267 - "overwrite_files": True})
268 -
269 -#############################------------------------------------------------------------------------
270 -#"randomize" the seeds of the random generators
271 -#############################------------------------------------------------------------------------
272 -
273 -#msd = int(math.fabs(time.process_time()*1000))
274 -#N_vp = nest.GetKernelStatus(['total_num_virtual_procs'])[0]
275 -#pyrngs = [numpy.random.RandomState(s) for s in range(msd, msd+N_vp)]
276 -#nest.SetKernelStatus({"grng_seed" : msd+N_vp})
277 -#nest.SetKernelStatus({"rng_seeds" : list(range(msd+N_vp+1, msd+2*N_vp+1))})
278 -{{/code}}
279 -
280 -=== Building the network: neuronal populations , Poisson processes and spike detectors ===
281 -
282 -{{code language="python"}}
283 -#############################------------------------------------------------------------------------
284 -print("Building network")
285 -#############################------------------------------------------------------------------------
286 -
287 -startbuild = time.time() #initialize the calculation of the time used to simulate
288 -
289 -NeuronPop=[]
290 -NoisePop=[]
291 -DetectorPop=[]
292 -
293 -#define and initialize the populations of neurons with the parameters extracted from the.ini files
294 -for i in range(1,int(InfoBuild[0])+1):
295 - if int(InfoBuild[i][7])==0:
296 - app=float(InfoBuild[i][5])
297 - else:
298 - app=0.
299 - app2= nest.Create("aeif_psc_exp", int(InfoBuild[i][0]),params={"C_m": 1.0,
300 - "g_L": 1.0/float(InfoBuild[i][3]),
301 - "t_ref": float(InfoBuild[i][6]),
302 - "E_L": 0.0,
303 - "V_reset": float(InfoBuild[i][5]),
304 - "V_m": app,
305 - "V_th": float(InfoBuild[i][4]),
306 - "Delta_T": 0.,
307 - "tau_syn_ex": 1.0,
308 - "tau_syn_in": 1.0,
309 - "a": 0.0,
310 - "b": float(InfoBuild[i][10]),
311 - "tau_w": float(InfoBuild[i][9]),
312 - "V_peak":float(InfoBuild[i][4])+10.0})
313 - NeuronPop.append(app2)
314 -
315 -#define and initialize the poisson generators and the spike detectors with the parameters extracted from the.ini files
316 -
317 -for i in range(1,int(InfoBuild[0])+1):
318 - app3= nest.Create("poisson_generator",params={"rate": float(InfoBuild[i][1]*InfoBuild[i][2]),
319 - 'origin':0.,
320 - 'start':start})
321 - NoisePop.append(app3)
322 - app4 = nest.Create("spike_recorder",params={ "start":StartMisure})
323 - DetectorPop.append(app4)
324 -
325 -endbuild = time.time()
326 -{{/code}}
327 -
328 -=== [[image:image-20220127165908-2.png||height="659" width="1149"]] ===
329 -
330 -=== Connecting the network nodes: neuronal populations, Poisson processes and spike detectors ===
331 -
332 -{{code language="python"}}
333 -#############################------------------------------------------------------------------------
334 -print("Connecting ")
335 -#############################------------------------------------------------------------------------
336 -
337 -startconnect = time.time()
338 -Connessioni=[]
339 -Medie=[]
340 -
341 -#create and define the connections between the populations of neurons and the poisson generators
342 -#and between the populations of neurons and the spike detectors with the parameters extracted from the.ini files
343 -
344 -for i in range(0,int(InfoBuild[0])):
345 - nest.Connect(NoisePop[i], NeuronPop[i], syn_spec={'synapse_model': 'static_synapse_hpc',
346 - 'delay': dt,
347 - 'weight': nest.math.redraw(nest.random.normal(mean=float(InfoConnectNoise[i+1][0]),
348 - std=(float(InfoConnectNoise[i+1][1])*float(InfoConnectNoise[i+1][0]))),
349 - min=0., max=float('Inf'))
350 - })
351 - nest.Connect(NeuronPop[i][:int(InfoBuild[i+1][0])], DetectorPop[i], syn_spec={"weight": 1.0, "delay": dt})
352 -
353 -#create and define the connections between the populations of neurons with the parameters extracted from the.ini files
354 -
355 -for i in range(0,len(InfoConnectPop[1:])):
356 -
357 - conn=nest.Connect(NeuronPop[int(InfoConnectPop[i+1][1])], NeuronPop[int(InfoConnectPop[i+1][0])],
358 - {'rule': 'pairwise_bernoulli',
359 - 'p':float(InfoConnectPop[i+1][2]) },
360 - syn_spec={'synapse_model': 'static_synapse_hpc',
361 - 'delay':nest.math.redraw(nest.random.exponential(beta=float(1./(2.99573227355/(float(InfoConnectPop[i+1][4])-float(InfoConnectPop[i+1][3]))))),
362 - min= numpy.max([dt,float(1./float(InfoConnectPop[i+1][4]))]),
363 - max= float(1./(float(InfoConnectPop[i+1][3])-dt/2))),
364 -
365 - 'weight':nest.random.normal(mean=float(InfoConnectPop[i+1][6]),
366 - std=math.fabs(float(InfoConnectPop[i+1][6])*float(InfoConnectPop[i+1][7])))})
367 -
368 -
369 -endconnect = time.time()
370 -{{/code}}
371 -
372 -=== ===
373 -
374 -=== ===
375 -
376 -=== [[image:image-20220127170722-1.png]] ===
377 -
378 -=== Simulating: neuronal time evolution. ===
379 -
380 -=== ===
381 -
382 -{{code language="python"}}
383 - #############################------------------------------------------------------------------------
384 - print("Simulating")
385 - #############################------------------------------------------------------------------------
386 - ###################################################################################################################################################################
387 - if Salva:
388 - print("I m going to save the data")
389 - #x=str(iterazioni)
390 - f = open(FileName,"w")
391 - if len(InfoProtocol):
392 - print("I m going to split the simulation")
393 - tempo=0
394 - for contatore in range(0,len(InfoProtocol)):
395 - appoggio1=int((tempo+InfoProtocol[contatore][0])/1000.)
396 - appoggio2=int(tempo/1000.)
397 - appoggio3=tempo+InfoProtocol[contatore][0]
398 - if (appoggio1-appoggio2)>=1:
399 - T1=(1+appoggio2)*1000-tempo
400 - nest.Simulate(T1)
401 - #Save the Data!!!!
402 - ###########################################################
403 - Equilibri=[]
404 - for i in range(0,int(InfoBuild[0])):
405 - Equilibri.append([])
406 - a=nest.GetStatus(DetectorPop[i])[0]["events"]["times"]
407 - if len(a)>0:
408 - Trange=(1000*int(numpy.min(a)/1000.),1000*int(numpy.min(a)/1000.)+1000)
409 - hist,Tbin=numpy.histogram(a,200,(Trange[0],Trange[1]))
410 - Equilibri[i]=hist*1000./(5.*int(InfoBuild[i+1][0]))
411 - else:
412 - Trange=(1000*int(tempo/1000.),1000*int(tempo/1000.)+1000)
413 - hist=numpy.zeros(200)
414 - Tbin=numpy.linspace(Trange[0],Trange[1],num=201)
415 - Equilibri[i]=hist
416 - nest.SetStatus(DetectorPop[i],{'n_events':0})
417 - for j in range(0,len(hist)):
418 - f.write(str(Tbin[j])+" ")
419 - for i in range(0,int(InfoBuild[0])):
420 - f.write(str(Equilibri[i][j])+" ")
421 - f.write("\n ")
422 - ###########################################################
423 - tempo=tempo+T1
424 - for contatore2 in range(1,(appoggio1-appoggio2)):
425 - nest.Simulate(1000.)
426 - #Save the Data!!!!
427 - ###########################################################
428 - Equilibri=[]
429 - for i in range(0,int(InfoBuild[0])):
430 - Equilibri.append([])
431 - a=nest.GetStatus(DetectorPop[i])[0]["events"]["times"]
432 - if len(a)>0:
433 - Trange=(1000*int(numpy.min(a)/1000.),1000*int(numpy.min(a)/1000.)+1000)
434 - hist,Tbin=numpy.histogram(a,200,(Trange[0],Trange[1]))
435 - Equilibri[i]=hist*1000./(5.*int(InfoBuild[i+1][0]))
436 - else:
437 - Trange=(1000*int(tempo/1000.),1000*int(tempo/1000.)+1000)
438 - hist=numpy.zeros(200)
439 - Tbin=numpy.linspace(Trange[0],Trange[1],num=201)
440 - Equilibri[i]=hist
441 - nest.SetStatus(DetectorPop[i],{'n_events':0})
442 - for j in range(0,len(hist)):
443 - f.write(str(Tbin[j])+" ")
444 - for i in range(0,int(InfoBuild[0])):
445 - f.write(str(Equilibri[i][j])+" ")
446 - f.write("\n ")
447 - tempo=tempo+1000.
448 - T2=appoggio3-tempo
449 - nest.Simulate(T2);
450 - tempo=tempo+T2;
451 - else:
452 - nest.Simulate(InfoProtocol[contatore][0])
453 - temp=InfoProtocol[contatore][0]
454 - tempo=tempo+temp
455 - if InfoProtocol[contatore][2]==4:
456 - nest.SetStatus(NoisePop[InfoProtocol[contatore][1]],params={"rate": float(InfoBuild[1+InfoProtocol[contatore][1]][2]*InfoProtocol[contatore][3])})
457 - if InfoProtocol[contatore][2]==12:
458 - nest.SetStatus(NeuronPop[InfoProtocol[contatore][1]], params={"b": float(InfoProtocol[contatore][3])})
459 - else:
460 - nest.Simulate(simtime)
461 - tempo=simtime
462 - if (simtime-tempo)>0.:
463 - nest.Simulate(simtime-tempo)
464 -
465 -
466 - endsimulate = time.time()
467 - f.close()
468 - else:
469 - if len(InfoProtocol):
470 - tempo=0
471 - for contatore in range(0,len(InfoProtocol)):
472 - nest.Simulate(InfoProtocol[contatore][0])
473 - temp=InfoProtocol[contatore][0]
474 - tempo=tempo+temp
475 - if InfoProtocol[contatore][2]==4:
476 - nest.SetStatus(NoisePop[InfoProtocol[contatore][1]],params={"rate": float(InfoBuild[1+InfoProtocol[contatore][1]][2]*InfoProtocol[contatore][3])})
477 - #print "Population:", InfoProtocol[contatore][1] ,";Parameter:", InfoProtocol[contatore][2] ,"; Value: ",InfoProtocol[contatore][3]
478 - if InfoProtocol[contatore][2]==12:
479 - nest.SetStatus(NeuronPop[InfoProtocol[contatore][1]], params={"b": float(InfoProtocol[contatore][3])})
480 - #print "Population:", InfoProtocol[contatore][1] ,";Parameter:", InfoProtocol[contatore][2] ,"; Value: ",InfoProtocol[contatore][3]
481 -
482 - else:
483 - nest.Simulate(simtime)
484 - tempo=simtime
485 - if (simtime-tempo)>0.:
486 - nest.Simulate(simtime-tempo)
487 - endsimulate = time.time()
488 -
489 -
490 - ###################################################################################################################################################################
491 -
492 - #############################------------------------------------------------------------------------
493 - #print some information from the simulation
494 - #############################------------------------------------------------------------------------
495 -
496 - num_synapses = nest.GetDefaults('static_synapse_hpc')["num_connections"]
497 - build_time = endbuild - startbuild
498 - connect_time = endconnect - startconnect
499 - sim_time = endsimulate - endconnect
500 -
501 - N_neurons=0
502 - for i in range(0,int(InfoBuild[0])):
503 - N_neurons=N_neurons+int(InfoBuild[i+1][0])
504 -
505 - print(" Network simulation (Python) neuron type:",InfoPerseo[0])
506 - print("Number of neurons : {0}".format(N_neurons))
507 - print("Number of synapses: {0}".format(num_synapses))
508 - print("Building time : %.2f s" % build_time)
509 - print("Connecting time : %.2f s" % connect_time)
510 - print("Simulation time : %.2f s" % sim_time)
511 -
512 -Fine=time.time()
513 -print ("Total Simulation time : %.2f s" % (Fine-Inizio))
514 -{{/code}}
515 -
516 -=== ===
517 -
518 -=== ===
519 -
520 -=== [[image:image-20220127171242-1.png]] ===
521 -
522 -=== Results: ===
523 -
524 -[[the output of this simulation is...>>https://drive.ebrains.eu/smart-link/215f8213-17e3-468b-b573-e6eaf49d315e/]]
525 -
526 -
527 -
528 -
529 -
530 -
531 531  ==== ====
CorticalField_t=80_DeepSpontPlanar.mp4
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