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Last modified by galluzziandrea on 2022/06/20 12:33
From version 27.1
edited by galluzziandrea
on 2022/01/27 17:31
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To version 5.1
edited by galluzziandrea
on 2021/12/09 14:46
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... ... @@ -36,7 +36,8 @@
36 36  
37 37  === Define necessary classes to import the Initialization Files: ===
38 38  
39 -{{code language="python" title=" "}}
39 +
40 +{{code language="python"}}
40 40  class ImportIniLIFCA():
41 41   #initialize the information to look for in perseo.ini
42 42   inf=["NeuronType", #still fixed value
... ... @@ -235,298 +235,9 @@
235 235  # [.....],[],...]
236 236  {{/code}}
237 237  
238 -(% class="wikigeneratedid" %)
239 -=== [[image:image-20220127173048-1.png||height="508" width="948"]] ===
240 240  
241 -=== Defining general and nest.kernel parameters ===
242 242  
243 -{{code language="python"}}
244 -#############################------------------------------------------------------------------------
245 -#Clean the Network
246 -#############################------------------------------------------------------------------------
247 -nest.ResetKernel()
248 248  
249 -#############################------------------------------------------------------------------------
250 -#insert the introductory parameters of the simulation
251 -#############################------------------------------------------------------------------------
242 +=== Results ===
252 252  
253 -
254 -dt = 0.1 # the resolution in ms
255 -StartMisure=0. # start time of measurements
256 -simtime = int(float(InfoPerseo[3])) # Simulation time in ms (200 s)
257 -if simtime<=StartMisure: # If the simulation time is less than StartMisure, it is increased by StartMisure
258 - simtime=simtime+StartMisure
259 -start=0.0 # start time of poissonian processes
260 -origin=0.0 # temporal origin
261 -
262 -#############################------------------------------------------------------------------------
263 -# Kernel parameters
264 -#############################------------------------------------------------------------------------
265 -LNT=multiprocessing.cpu_count();
266 -nest.SetKernelStatus({"local_num_threads": LNT})
267 -nest.SetKernelStatus({"resolution": dt, "print_time": True,
268 - "overwrite_files": True})
269 -
270 -#############################------------------------------------------------------------------------
271 -#"randomize" the seeds of the random generators
272 -#############################------------------------------------------------------------------------
273 -
274 -#msd = int(math.fabs(time.process_time()*1000))
275 -#N_vp = nest.GetKernelStatus(['total_num_virtual_procs'])[0]
276 -#pyrngs = [numpy.random.RandomState(s) for s in range(msd, msd+N_vp)]
277 -#nest.SetKernelStatus({"grng_seed" : msd+N_vp})
278 -#nest.SetKernelStatus({"rng_seeds" : list(range(msd+N_vp+1, msd+2*N_vp+1))})
279 -{{/code}}
280 -
281 -=== Building the network: neuronal populations , Poisson processes and spike detectors ===
282 -
283 -{{code language="python"}}
284 -#############################------------------------------------------------------------------------
285 -print("Building network")
286 -#############################------------------------------------------------------------------------
287 -
288 -startbuild = time.time() #initialize the calculation of the time used to simulate
289 -
290 -NeuronPop=[]
291 -NoisePop=[]
292 -DetectorPop=[]
293 -
294 -#define and initialize the populations of neurons with the parameters extracted from the.ini files
295 -for i in range(1,int(InfoBuild[0])+1):
296 - if int(InfoBuild[i][7])==0:
297 - app=float(InfoBuild[i][5])
298 - else:
299 - app=0.
300 - app2= nest.Create("aeif_psc_exp", int(InfoBuild[i][0]),params={"C_m": 1.0,
301 - "g_L": 1.0/float(InfoBuild[i][3]),
302 - "t_ref": float(InfoBuild[i][6]),
303 - "E_L": 0.0,
304 - "V_reset": float(InfoBuild[i][5]),
305 - "V_m": app,
306 - "V_th": float(InfoBuild[i][4]),
307 - "Delta_T": 0.,
308 - "tau_syn_ex": 1.0,
309 - "tau_syn_in": 1.0,
310 - "a": 0.0,
311 - "b": float(InfoBuild[i][10]),
312 - "tau_w": float(InfoBuild[i][9]),
313 - "V_peak":float(InfoBuild[i][4])+10.0})
314 - NeuronPop.append(app2)
315 -
316 -#define and initialize the poisson generators and the spike detectors with the parameters extracted from the.ini files
317 -
318 -for i in range(1,int(InfoBuild[0])+1):
319 - app3= nest.Create("poisson_generator",params={"rate": float(InfoBuild[i][1]*InfoBuild[i][2]),
320 - 'origin':0.,
321 - 'start':start})
322 - NoisePop.append(app3)
323 - app4 = nest.Create("spike_recorder",params={ "start":StartMisure})
324 - DetectorPop.append(app4)
325 -
326 -endbuild = time.time()
327 -{{/code}}
328 -
329 -=== [[image:image-20220127165908-2.png||height="659" width="1149"]] ===
330 -
331 -=== Connecting the network nodes: neuronal populations, Poisson processes and spike detectors ===
332 -
333 -{{code language="python"}}
334 -#############################------------------------------------------------------------------------
335 -print("Connecting ")
336 -#############################------------------------------------------------------------------------
337 -
338 -startconnect = time.time()
339 -Connessioni=[]
340 -Medie=[]
341 -
342 -#create and define the connections between the populations of neurons and the poisson generators
343 -#and between the populations of neurons and the spike detectors with the parameters extracted from the.ini files
344 -
345 -for i in range(0,int(InfoBuild[0])):
346 - nest.Connect(NoisePop[i], NeuronPop[i], syn_spec={'synapse_model': 'static_synapse_hpc',
347 - 'delay': dt,
348 - 'weight': nest.math.redraw(nest.random.normal(mean=float(InfoConnectNoise[i+1][0]),
349 - std=(float(InfoConnectNoise[i+1][1])*float(InfoConnectNoise[i+1][0]))),
350 - min=0., max=float('Inf'))
351 - })
352 - nest.Connect(NeuronPop[i][:int(InfoBuild[i+1][0])], DetectorPop[i], syn_spec={"weight": 1.0, "delay": dt})
353 -
354 -#create and define the connections between the populations of neurons with the parameters extracted from the.ini files
355 -
356 -for i in range(0,len(InfoConnectPop[1:])):
357 -
358 - conn=nest.Connect(NeuronPop[int(InfoConnectPop[i+1][1])], NeuronPop[int(InfoConnectPop[i+1][0])],
359 - {'rule': 'pairwise_bernoulli',
360 - 'p':float(InfoConnectPop[i+1][2]) },
361 - syn_spec={'synapse_model': 'static_synapse_hpc',
362 - 'delay':nest.math.redraw(nest.random.exponential(beta=float(1./(2.99573227355/(float(InfoConnectPop[i+1][4])-float(InfoConnectPop[i+1][3]))))),
363 - min= numpy.max([dt,float(1./float(InfoConnectPop[i+1][4]))]),
364 - max= float(1./(float(InfoConnectPop[i+1][3])-dt/2))),
365 -
366 - 'weight':nest.random.normal(mean=float(InfoConnectPop[i+1][6]),
367 - std=math.fabs(float(InfoConnectPop[i+1][6])*float(InfoConnectPop[i+1][7])))})
368 -
369 -
370 -endconnect = time.time()
371 -{{/code}}
372 -
373 -=== ===
374 -
375 -=== ===
376 -
377 -=== [[image:image-20220127170722-1.png]] ===
378 -
379 -=== Simulating: neuronal time evolution. ===
380 -
381 -=== ===
382 -
383 -{{code language="python"}}
384 - #############################------------------------------------------------------------------------
385 - print("Simulating")
386 - #############################------------------------------------------------------------------------
387 - ###################################################################################################################################################################
388 - if Salva:
389 - print("I m going to save the data")
390 - #x=str(iterazioni)
391 - f = open(FileName,"w")
392 - if len(InfoProtocol):
393 - print("I m going to split the simulation")
394 - tempo=0
395 - for contatore in range(0,len(InfoProtocol)):
396 - appoggio1=int((tempo+InfoProtocol[contatore][0])/1000.)
397 - appoggio2=int(tempo/1000.)
398 - appoggio3=tempo+InfoProtocol[contatore][0]
399 - if (appoggio1-appoggio2)>=1:
400 - T1=(1+appoggio2)*1000-tempo
401 - nest.Simulate(T1)
402 - #Save the Data!!!!
403 - ###########################################################
404 - Equilibri=[]
405 - for i in range(0,int(InfoBuild[0])):
406 - Equilibri.append([])
407 - a=nest.GetStatus(DetectorPop[i])[0]["events"]["times"]
408 - if len(a)>0:
409 - Trange=(1000*int(numpy.min(a)/1000.),1000*int(numpy.min(a)/1000.)+1000)
410 - hist,Tbin=numpy.histogram(a,200,(Trange[0],Trange[1]))
411 - Equilibri[i]=hist*1000./(5.*int(InfoBuild[i+1][0]))
412 - else:
413 - Trange=(1000*int(tempo/1000.),1000*int(tempo/1000.)+1000)
414 - hist=numpy.zeros(200)
415 - Tbin=numpy.linspace(Trange[0],Trange[1],num=201)
416 - Equilibri[i]=hist
417 - nest.SetStatus(DetectorPop[i],{'n_events':0})
418 - for j in range(0,len(hist)):
419 - f.write(str(Tbin[j])+" ")
420 - for i in range(0,int(InfoBuild[0])):
421 - f.write(str(Equilibri[i][j])+" ")
422 - f.write("\n ")
423 - ###########################################################
424 - tempo=tempo+T1
425 - for contatore2 in range(1,(appoggio1-appoggio2)):
426 - nest.Simulate(1000.)
427 - #Save the Data!!!!
428 - ###########################################################
429 - Equilibri=[]
430 - for i in range(0,int(InfoBuild[0])):
431 - Equilibri.append([])
432 - a=nest.GetStatus(DetectorPop[i])[0]["events"]["times"]
433 - if len(a)>0:
434 - Trange=(1000*int(numpy.min(a)/1000.),1000*int(numpy.min(a)/1000.)+1000)
435 - hist,Tbin=numpy.histogram(a,200,(Trange[0],Trange[1]))
436 - Equilibri[i]=hist*1000./(5.*int(InfoBuild[i+1][0]))
437 - else:
438 - Trange=(1000*int(tempo/1000.),1000*int(tempo/1000.)+1000)
439 - hist=numpy.zeros(200)
440 - Tbin=numpy.linspace(Trange[0],Trange[1],num=201)
441 - Equilibri[i]=hist
442 - nest.SetStatus(DetectorPop[i],{'n_events':0})
443 - for j in range(0,len(hist)):
444 - f.write(str(Tbin[j])+" ")
445 - for i in range(0,int(InfoBuild[0])):
446 - f.write(str(Equilibri[i][j])+" ")
447 - f.write("\n ")
448 - tempo=tempo+1000.
449 - T2=appoggio3-tempo
450 - nest.Simulate(T2);
451 - tempo=tempo+T2;
452 - else:
453 - nest.Simulate(InfoProtocol[contatore][0])
454 - temp=InfoProtocol[contatore][0]
455 - tempo=tempo+temp
456 - if InfoProtocol[contatore][2]==4:
457 - nest.SetStatus(NoisePop[InfoProtocol[contatore][1]],params={"rate": float(InfoBuild[1+InfoProtocol[contatore][1]][2]*InfoProtocol[contatore][3])})
458 - if InfoProtocol[contatore][2]==12:
459 - nest.SetStatus(NeuronPop[InfoProtocol[contatore][1]], params={"b": float(InfoProtocol[contatore][3])})
460 - else:
461 - nest.Simulate(simtime)
462 - tempo=simtime
463 - if (simtime-tempo)>0.:
464 - nest.Simulate(simtime-tempo)
465 -
466 -
467 - endsimulate = time.time()
468 - f.close()
469 - else:
470 - if len(InfoProtocol):
471 - tempo=0
472 - for contatore in range(0,len(InfoProtocol)):
473 - nest.Simulate(InfoProtocol[contatore][0])
474 - temp=InfoProtocol[contatore][0]
475 - tempo=tempo+temp
476 - if InfoProtocol[contatore][2]==4:
477 - nest.SetStatus(NoisePop[InfoProtocol[contatore][1]],params={"rate": float(InfoBuild[1+InfoProtocol[contatore][1]][2]*InfoProtocol[contatore][3])})
478 - #print "Population:", InfoProtocol[contatore][1] ,";Parameter:", InfoProtocol[contatore][2] ,"; Value: ",InfoProtocol[contatore][3]
479 - if InfoProtocol[contatore][2]==12:
480 - nest.SetStatus(NeuronPop[InfoProtocol[contatore][1]], params={"b": float(InfoProtocol[contatore][3])})
481 - #print "Population:", InfoProtocol[contatore][1] ,";Parameter:", InfoProtocol[contatore][2] ,"; Value: ",InfoProtocol[contatore][3]
482 -
483 - else:
484 - nest.Simulate(simtime)
485 - tempo=simtime
486 - if (simtime-tempo)>0.:
487 - nest.Simulate(simtime-tempo)
488 - endsimulate = time.time()
489 -
490 -
491 - ###################################################################################################################################################################
492 -
493 - #############################------------------------------------------------------------------------
494 - #print some information from the simulation
495 - #############################------------------------------------------------------------------------
496 -
497 - num_synapses = nest.GetDefaults('static_synapse_hpc')["num_connections"]
498 - build_time = endbuild - startbuild
499 - connect_time = endconnect - startconnect
500 - sim_time = endsimulate - endconnect
501 -
502 - N_neurons=0
503 - for i in range(0,int(InfoBuild[0])):
504 - N_neurons=N_neurons+int(InfoBuild[i+1][0])
505 -
506 - print(" Network simulation (Python) neuron type:",InfoPerseo[0])
507 - print("Number of neurons : {0}".format(N_neurons))
508 - print("Number of synapses: {0}".format(num_synapses))
509 - print("Building time : %.2f s" % build_time)
510 - print("Connecting time : %.2f s" % connect_time)
511 - print("Simulation time : %.2f s" % sim_time)
512 -
513 -Fine=time.time()
514 -print ("Total Simulation time : %.2f s" % (Fine-Inizio))
515 -{{/code}}
516 -
517 -=== ===
518 -
519 -=== ===
520 -
521 -=== [[image:image-20220127171242-1.png]] ===
522 -
523 -=== Results: ===
524 -
525 -[[the output of this simulationo is...>>https://drive.ebrains.eu/smart-link/215f8213-17e3-468b-b573-e6eaf49d315e/]]
526 -
527 -
528 -
529 -
530 -
531 -
532 532  ==== ====
CorticalField_t=80_DeepSpontPlanar.mp4
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