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Last modified by galluzziandrea on 2022/06/20 12:33
From version 14.1
edited by galluzziandrea
on 2022/01/27 17:01
on 2022/01/27 17:01
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Uploaded new attachment "image-20220127170104-1.png", version {1}
To version 8.1
edited by galluzziandrea
on 2021/12/09 14:58
on 2021/12/09 14:58
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... ... @@ -323,202 +323,6 @@ 323 323 endbuild = time.time() 324 324 {{/code}} 325 325 326 -(% class="wikigeneratedid" %) 327 -=== [[image:image-20220127165908-2.png||height="659" width="1149"]] === 326 +=== Results === 328 328 329 -=== Connecting the network nodes: neuronal populations, Poisson processes and spike detectors === 330 - 331 -{{code language="python"}} 332 -#############################------------------------------------------------------------------------ 333 -print("Connecting ") 334 -#############################------------------------------------------------------------------------ 335 - 336 -startconnect = time.time() 337 -Connessioni=[] 338 -Medie=[] 339 - 340 -#create and define the connections between the populations of neurons and the poisson generators 341 -#and between the populations of neurons and the spike detectors with the parameters extracted from the.ini files 342 - 343 -for i in range(0,int(InfoBuild[0])): 344 - nest.Connect(NoisePop[i], NeuronPop[i], syn_spec={'synapse_model': 'static_synapse_hpc', 345 - 'delay': dt, 346 - 'weight': nest.math.redraw(nest.random.normal(mean=float(InfoConnectNoise[i+1][0]), 347 - std=(float(InfoConnectNoise[i+1][1])*float(InfoConnectNoise[i+1][0]))), 348 - min=0., max=float('Inf')) 349 - }) 350 - nest.Connect(NeuronPop[i][:int(InfoBuild[i+1][0])], DetectorPop[i], syn_spec={"weight": 1.0, "delay": dt}) 351 - 352 -#create and define the connections between the populations of neurons with the parameters extracted from the.ini files 353 - 354 -for i in range(0,len(InfoConnectPop[1:])): 355 - 356 - conn=nest.Connect(NeuronPop[int(InfoConnectPop[i+1][1])], NeuronPop[int(InfoConnectPop[i+1][0])], 357 - {'rule': 'pairwise_bernoulli', 358 - 'p':float(InfoConnectPop[i+1][2]) }, 359 - syn_spec={'synapse_model': 'static_synapse_hpc', 360 - 'delay':nest.math.redraw(nest.random.exponential(beta=float(1./(2.99573227355/(float(InfoConnectPop[i+1][4])-float(InfoConnectPop[i+1][3]))))), 361 - min= numpy.max([dt,float(1./float(InfoConnectPop[i+1][4]))]), 362 - max= float(1./(float(InfoConnectPop[i+1][3])-dt/2))), 363 - 364 - 'weight':nest.random.normal(mean=float(InfoConnectPop[i+1][6]), 365 - std=math.fabs(float(InfoConnectPop[i+1][6])*float(InfoConnectPop[i+1][7])))}) 366 - 367 - 368 -endconnect = time.time() 369 -{{/code}} 370 - 371 -=== === 372 - 373 -=== === 374 - 375 -=== Simulating: neuronal time evolution. === 376 - 377 -=== === 378 - 379 -{{code language="python"}} 380 - #############################------------------------------------------------------------------------ 381 - print("Simulating") 382 - #############################------------------------------------------------------------------------ 383 - ################################################################################################################################################################### 384 - if Salva: 385 - print("I m going to save the data") 386 - #x=str(iterazioni) 387 - f = open(FileName,"w") 388 - if len(InfoProtocol): 389 - print("I m going to split the simulation") 390 - tempo=0 391 - for contatore in range(0,len(InfoProtocol)): 392 - appoggio1=int((tempo+InfoProtocol[contatore][0])/1000.) 393 - appoggio2=int(tempo/1000.) 394 - appoggio3=tempo+InfoProtocol[contatore][0] 395 - if (appoggio1-appoggio2)>=1: 396 - T1=(1+appoggio2)*1000-tempo 397 - nest.Simulate(T1) 398 - #Save the Data!!!! 399 - ########################################################### 400 - Equilibri=[] 401 - for i in range(0,int(InfoBuild[0])): 402 - Equilibri.append([]) 403 - a=nest.GetStatus(DetectorPop[i])[0]["events"]["times"] 404 - if len(a)>0: 405 - Trange=(1000*int(numpy.min(a)/1000.),1000*int(numpy.min(a)/1000.)+1000) 406 - hist,Tbin=numpy.histogram(a,200,(Trange[0],Trange[1])) 407 - Equilibri[i]=hist*1000./(5.*int(InfoBuild[i+1][0])) 408 - else: 409 - Trange=(1000*int(tempo/1000.),1000*int(tempo/1000.)+1000) 410 - hist=numpy.zeros(200) 411 - Tbin=numpy.linspace(Trange[0],Trange[1],num=201) 412 - Equilibri[i]=hist 413 - nest.SetStatus(DetectorPop[i],{'n_events':0}) 414 - for j in range(0,len(hist)): 415 - f.write(str(Tbin[j])+" ") 416 - for i in range(0,int(InfoBuild[0])): 417 - f.write(str(Equilibri[i][j])+" ") 418 - f.write("\n ") 419 - ########################################################### 420 - tempo=tempo+T1 421 - for contatore2 in range(1,(appoggio1-appoggio2)): 422 - nest.Simulate(1000.) 423 - #Save the Data!!!! 424 - ########################################################### 425 - Equilibri=[] 426 - for i in range(0,int(InfoBuild[0])): 427 - Equilibri.append([]) 428 - a=nest.GetStatus(DetectorPop[i])[0]["events"]["times"] 429 - if len(a)>0: 430 - Trange=(1000*int(numpy.min(a)/1000.),1000*int(numpy.min(a)/1000.)+1000) 431 - hist,Tbin=numpy.histogram(a,200,(Trange[0],Trange[1])) 432 - Equilibri[i]=hist*1000./(5.*int(InfoBuild[i+1][0])) 433 - else: 434 - Trange=(1000*int(tempo/1000.),1000*int(tempo/1000.)+1000) 435 - hist=numpy.zeros(200) 436 - Tbin=numpy.linspace(Trange[0],Trange[1],num=201) 437 - Equilibri[i]=hist 438 - nest.SetStatus(DetectorPop[i],{'n_events':0}) 439 - for j in range(0,len(hist)): 440 - f.write(str(Tbin[j])+" ") 441 - for i in range(0,int(InfoBuild[0])): 442 - f.write(str(Equilibri[i][j])+" ") 443 - f.write("\n ") 444 - tempo=tempo+1000. 445 - T2=appoggio3-tempo 446 - nest.Simulate(T2); 447 - tempo=tempo+T2; 448 - else: 449 - nest.Simulate(InfoProtocol[contatore][0]) 450 - temp=InfoProtocol[contatore][0] 451 - tempo=tempo+temp 452 - if InfoProtocol[contatore][2]==4: 453 - nest.SetStatus(NoisePop[InfoProtocol[contatore][1]],params={"rate": float(InfoBuild[1+InfoProtocol[contatore][1]][2]*InfoProtocol[contatore][3])}) 454 - if InfoProtocol[contatore][2]==12: 455 - nest.SetStatus(NeuronPop[InfoProtocol[contatore][1]], params={"b": float(InfoProtocol[contatore][3])}) 456 - else: 457 - nest.Simulate(simtime) 458 - tempo=simtime 459 - if (simtime-tempo)>0.: 460 - nest.Simulate(simtime-tempo) 461 - 462 - 463 - endsimulate = time.time() 464 - f.close() 465 - else: 466 - if len(InfoProtocol): 467 - tempo=0 468 - for contatore in range(0,len(InfoProtocol)): 469 - nest.Simulate(InfoProtocol[contatore][0]) 470 - temp=InfoProtocol[contatore][0] 471 - tempo=tempo+temp 472 - if InfoProtocol[contatore][2]==4: 473 - nest.SetStatus(NoisePop[InfoProtocol[contatore][1]],params={"rate": float(InfoBuild[1+InfoProtocol[contatore][1]][2]*InfoProtocol[contatore][3])}) 474 - #print "Population:", InfoProtocol[contatore][1] ,";Parameter:", InfoProtocol[contatore][2] ,"; Value: ",InfoProtocol[contatore][3] 475 - if InfoProtocol[contatore][2]==12: 476 - nest.SetStatus(NeuronPop[InfoProtocol[contatore][1]], params={"b": float(InfoProtocol[contatore][3])}) 477 - #print "Population:", InfoProtocol[contatore][1] ,";Parameter:", InfoProtocol[contatore][2] ,"; Value: ",InfoProtocol[contatore][3] 478 - 479 - else: 480 - nest.Simulate(simtime) 481 - tempo=simtime 482 - if (simtime-tempo)>0.: 483 - nest.Simulate(simtime-tempo) 484 - endsimulate = time.time() 485 - 486 - 487 - ################################################################################################################################################################### 488 - 489 - #############################------------------------------------------------------------------------ 490 - #print some information from the simulation 491 - #############################------------------------------------------------------------------------ 492 - 493 - num_synapses = nest.GetDefaults('static_synapse_hpc')["num_connections"] 494 - build_time = endbuild - startbuild 495 - connect_time = endconnect - startconnect 496 - sim_time = endsimulate - endconnect 497 - 498 - N_neurons=0 499 - for i in range(0,int(InfoBuild[0])): 500 - N_neurons=N_neurons+int(InfoBuild[i+1][0]) 501 - 502 - print(" Network simulation (Python) neuron type:",InfoPerseo[0]) 503 - print("Number of neurons : {0}".format(N_neurons)) 504 - print("Number of synapses: {0}".format(num_synapses)) 505 - print("Building time : %.2f s" % build_time) 506 - print("Connecting time : %.2f s" % connect_time) 507 - print("Simulation time : %.2f s" % sim_time) 508 - 509 -Fine=time.time() 510 -print ("Total Simulation time : %.2f s" % (Fine-Inizio)) 511 -{{/code}} 512 - 513 -=== === 514 - 515 -=== Results: === 516 - 517 -the output of this simulationo is... 518 - 519 - 520 - 521 - 522 - 523 - 524 524 ==== ====
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- Introduction (path and modules):
- Check where I am and place myself in the right folder:
- Import the modules necessary for the simulation:
- Define necessary classes to import the Initialization Files:
- Import the initialization files:
- Defining general and nest.kernel parameters
- Building the network: neuronal populations , Poisson processes and spike detectors
- Connecting the network nodes: neuronal populations, Poisson processes and spike detectors
- Simulating: neuronal time evolution.
- Results: