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Last modified by galluzziandrea on 2022/06/20 12:33
From version 22.1
edited by galluzziandrea
on 2022/01/27 17:20
Change comment: There is no comment for this version
To version 6.1
edited by galluzziandrea
on 2021/12/09 14:47
Change comment: There is no comment for this version

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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 +{{code language="python" width="90%" title="
40 +120%"}}
40 40  class ImportIniLIFCA():
41 41   #initialize the information to look for in perseo.ini
42 42   inf=["NeuronType", #still fixed value
... ... @@ -235,296 +235,9 @@
235 235  # [.....],[],...]
236 236  {{/code}}
237 237  
238 -=== Defining general and nest.kernel parameters ===
239 239  
240 -{{code language="python"}}
241 -#############################------------------------------------------------------------------------
242 -#Clean the Network
243 -#############################------------------------------------------------------------------------
244 -nest.ResetKernel()
245 245  
246 -#############################------------------------------------------------------------------------
247 -#insert the introductory parameters of the simulation
248 -#############################------------------------------------------------------------------------
249 249  
242 +=== Results ===
250 250  
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 -=== [[image:image-20220127171242-1.png]] ===
519 -
520 -=== Results: ===
521 -
522 -the output of this simulationo is...
523 -
524 -[[attach:CorticalField_t=80_DeepSpontPlanar.mp4||target="_blank"]]
525 -
526 -
527 -
528 -
529 -
530 530  ==== ====
CorticalField_t=80_DeepSpontPlanar.mp4
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