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Last modified by galluzziandrea on 2022/06/20 12:33
From version 4.2
edited by galluzziandrea
on 2021/12/09 14:39
on 2021/12/09 14:39
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To version 16.1
edited by galluzziandrea
on 2022/01/27 17:03
on 2022/01/27 17:03
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... ... @@ -1,8 +1,8 @@ 1 -== Introduction (path and modules) == 1 +== Introduction (path and modules): == 2 2 3 3 First of all we check the path and import the necessary modules . 4 4 5 -=== Check where I am and place myself in the right folder 5 +=== Check where I am and place myself in the right folder: === 6 6 7 7 {{code language="python"}} 8 8 # Import the os module ... ... @@ -18,7 +18,7 @@ 18 18 print("Current working directory: {0}".format(os.getcwd())) 19 19 {{/code}} 20 20 21 -=== import the modules necessary for the simulation ===21 +=== Import the modules necessary for the simulation: === 22 22 23 23 {{code language="python"}} 24 24 import nest ... ... @@ -34,6 +34,502 @@ 34 34 35 35 === === 36 36 37 -=== =Results ====37 +=== Define necessary classes to import the Initialization Files: === 38 38 39 +{{code language="python" title=" "}} 40 +class ImportIniLIFCA(): 41 + #initialize the information to look for in perseo.ini 42 + inf=["NeuronType", #still fixed value 43 + "DelayDistribType", #still fixed value 44 + "SynapticExtractionType", #still fixed value 45 + "Life"] 46 + 47 + def __init__(self,files): 48 + self.files=files 49 + 50 + def FilesControllo(self): 51 + import sys 52 + for i in range(0,len(self.files)): 53 + if self.FileControllo(self.files[i]): 54 + sys.exit(0) 55 + 56 + def FileControllo(self,file1): 57 + try: 58 + f1=open(file1,"r") 59 + f1.close() 60 + return 0 61 + except ValueError: 62 + print("ValueError") 63 + return 1 64 + except IOError as err: 65 + print("OS error: {0}".format(err)) 66 + return 1 67 + except: 68 + print("Unexpected error:", sys.exc_info()[0]) 69 + return 1 70 + 71 + def Estrai_inf(self,stampa=0): 72 + 73 + InfoPerseo=self.EstraiInfoPerseo() #extract info from perseo.ini 74 + AppoggioTempM=self.EstraiInfoModuli() #extract info from modules.ini 75 + AppoggioTempC=self.EstraiInfoConnectivity() #extract info from connectivity.ini 76 + AppoggioTempP=self.EstraiProtocol() #extract info from protocol.ini 77 + 78 + def getKey(item): 79 + return item[0] 80 + InfoProtocol=AppoggioTempP 81 + # I convert the extracted information into a suitable format from tuple to list 82 + 83 + InfoBuildT=[AppoggioTempM[0]] 84 + for i in range(0,AppoggioTempM[0]): 85 + app1=[int(AppoggioTempM[2][i][0])] 86 + app=(app1+list(AppoggioTempM[2][i][3:9])+list(AppoggioTempM[2][i][12])+list(AppoggioTempM[2][i][9:12])) 87 + InfoBuildT.append(app) 88 + del app 89 + 90 + InfoBuild=[float(InfoBuildT[0])] 91 + for i in range(0,int(InfoBuildT[0])): 92 + app=[] 93 + for j in range(0,11): 94 + app.append(float(InfoBuildT[i+1][j])) 95 + InfoBuild=InfoBuild+[app] 96 + del app 97 + 98 + InfoConnectPop=[AppoggioTempM[0]] 99 + for i in range(0,len(AppoggioTempC[1][:])): 100 + app=list(AppoggioTempC[1][i]) 101 + InfoConnectPop.append(app) 102 + del app 103 + 104 + InfoConnectNoise=[AppoggioTempM[0]] 105 + for i in range(0,AppoggioTempM[0]): 106 + app=list(AppoggioTempM[2][i][1:3]) 107 + InfoConnectNoise.append(app) 108 + 109 + 110 + if stampa==1: #Print on screen of saved data 111 + for i,j in enumerate(InfoPerseo): 112 + print(self.inf[i],"=",j) 113 + print("\n") 114 + print("the network consists of ", AppoggioTempM[0], " neuronal population" ) 115 + print(AppoggioTempM[1]) 116 + for i in range(0,AppoggioTempM[0]): 117 + print(AppoggioTempM[2][i]) 118 + print("\n") 119 + print(AppoggioTempC[0]) 120 + for i in range(0,AppoggioTempM[0]**2): 121 + print(AppoggioTempC[1][i]) 122 + print("\n") 123 + for i in InfoProtocol: 124 + print("SET_PARAM"+str(i)) 125 + 126 + 127 + return InfoPerseo,InfoBuild,InfoConnectPop,InfoConnectNoise,InfoProtocol 128 + 129 + def EstraiProtocol(self): 130 + import string 131 + f1=open(self.files[3],"r") 132 + ProtocolList= [] 133 + for x in f1.readlines(): 134 + y=x.split() 135 + if len(y): 136 + if x[0]!="#" and y[0]=="SET_PARAM": 137 + try: 138 + ProtocolList.append([float(y[1]),int(y[2]),float(y[3]),float(y[4])]) 139 + except ValueError: 140 + pass 141 + f1.close() 142 + return ProtocolList 143 + 144 + def EstraiInfoPerseo(self): 145 + import string 146 + f1=open(self.files[0],"r") 147 + InfList= [] 148 + for x in f1.readlines(): 149 + y=x.split() 150 + if len(y): 151 + if x[0]!="#": 152 + for findinf in self.inf: 153 + try: 154 + temp=y.index(findinf) 155 + InfList.append(y[temp+2]) 156 + except ValueError: 157 + pass 158 + f1.close() 159 + return InfList 160 + 161 + def EstraiInfoModuli(self): 162 + import string 163 + f1=open(self.files[2],"r") 164 + NumPop=0 165 + for i,x in enumerate(f1.readlines()): 166 + y=x.split() 167 + if len(y): 168 + if x[0]!="#": 169 + NumPop=NumPop+1 170 + if i==2: 171 + ParamList=[] 172 + for j in range(1,14): 173 + ParamList.append(y[j]) 174 + f1.close() 175 + PopsParamList=[] 176 + f1=open(self.files[2],"r") 177 + x=f1.readlines() 178 + for j in range(0,NumPop): 179 + appo=x[4+j]; 180 + PopsParamList.append(appo.split()) 181 + f1.close() 182 + return NumPop,ParamList,PopsParamList 183 + 184 + def EstraiInfoConnectivity(self): 185 + import string 186 + f1=open(self.files[1],"r") 187 + PopConParamList=[] 188 + for i,x in enumerate(f1.readlines()): 189 + y=x.split() 190 + if len(y): 191 + if x[0]!="#": 192 + PopConParamList.append(y) 193 + if i==1: 194 + ParamList=[] 195 + for j in range(1,9): 196 + ParamList.append(y[j]) 197 + f1.close() 198 + return ParamList,PopConParamList 199 +{{/code}} 200 + 201 +=== Import the initialization files: === 202 + 203 +in this section we... 204 + 205 +{{code language="python"}} 206 +Salva=1 207 +file1="perseo35.ini" 208 +file2="c_cortsurf_Pot1.43PotStr148v3.ini" 209 +file3="m_cortsurf_Pot1.43.ini" 210 +file4="ProtocolExploration36.ini" 211 +files=[file1,file2,file3,file4] 212 +#define the name of the Output file 213 +FileName="dati/Rates_Nest_Run_Milano_Test36_13x13_"+str(nest.Rank())+"_Pot1.43PotStr148v3Long3.dat" 214 +#check the existence of the files being read 215 +ImpFil=ImportIniLIFCA(files); 216 +ImpFil.FilesControllo() 217 + 218 +#extract the information of interest from the files.ini and transfer them to the files: 219 +#InfoPerseo,InfoBuild,InfoConnectPop,InfoConnectNoise 220 + 221 +stampa=0; #stampa=1 print output simulation data on screen stampa=0 dont 222 +InfoPerseo,InfoBuild,InfoConnectPop,InfoConnectNoise,InfoProtocol=ImpFil.Estrai_inf(stampa) 223 + 224 +# InfoPerseo=["NeuronType","DelayDistribType","SynapticExtractionType","Life" ] 225 +# InfoBuild=[numero di popolazioni, 226 +# [N,C_ext,\nu_ext,\tau,\tetha,H,\tau_arp,NeuronInitType,\alpha_c,\tau_c,g_c], 227 +# [.....],[],...] 228 +# InfoConnectPop=[numero di popolazioni, 229 +# [post,pre,c,Dmin,Dmax,syn typ,J,DJ], 230 +# [.....],[],...] 231 +# InfoConnectNoise=[numero di popolazioni, 232 +# [J_ext,DJ_ext], 233 +# [.....],[],...] 234 +# InfoProtocol=[[time,population,param_num,value], 235 +# [.....],[],...] 236 +{{/code}} 237 + 238 +=== Defining general and nest.kernel parameters === 239 + 240 +{{code language="python"}} 241 +#############################------------------------------------------------------------------------ 242 +#Clean the Network 243 +#############################------------------------------------------------------------------------ 244 +nest.ResetKernel() 245 + 246 +#############################------------------------------------------------------------------------ 247 +#insert the introductory parameters of the simulation 248 +#############################------------------------------------------------------------------------ 249 + 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 +(% class="wikigeneratedid" %) 375 +=== [[image:image-20220127170104-1.png||height="630" width="1430"]] === 376 + 377 +(% class="wikigeneratedid" %) 378 +=== === 379 + 380 +(% class="wikigeneratedid" %) 381 +=== === 382 + 383 +=== Simulating: neuronal time evolution. === 384 + 385 +=== === 386 + 387 +{{code language="python"}} 388 + #############################------------------------------------------------------------------------ 389 + print("Simulating") 390 + #############################------------------------------------------------------------------------ 391 + ################################################################################################################################################################### 392 + if Salva: 393 + print("I m going to save the data") 394 + #x=str(iterazioni) 395 + f = open(FileName,"w") 396 + if len(InfoProtocol): 397 + print("I m going to split the simulation") 398 + tempo=0 399 + for contatore in range(0,len(InfoProtocol)): 400 + appoggio1=int((tempo+InfoProtocol[contatore][0])/1000.) 401 + appoggio2=int(tempo/1000.) 402 + appoggio3=tempo+InfoProtocol[contatore][0] 403 + if (appoggio1-appoggio2)>=1: 404 + T1=(1+appoggio2)*1000-tempo 405 + nest.Simulate(T1) 406 + #Save the Data!!!! 407 + ########################################################### 408 + Equilibri=[] 409 + for i in range(0,int(InfoBuild[0])): 410 + Equilibri.append([]) 411 + a=nest.GetStatus(DetectorPop[i])[0]["events"]["times"] 412 + if len(a)>0: 413 + Trange=(1000*int(numpy.min(a)/1000.),1000*int(numpy.min(a)/1000.)+1000) 414 + hist,Tbin=numpy.histogram(a,200,(Trange[0],Trange[1])) 415 + Equilibri[i]=hist*1000./(5.*int(InfoBuild[i+1][0])) 416 + else: 417 + Trange=(1000*int(tempo/1000.),1000*int(tempo/1000.)+1000) 418 + hist=numpy.zeros(200) 419 + Tbin=numpy.linspace(Trange[0],Trange[1],num=201) 420 + Equilibri[i]=hist 421 + nest.SetStatus(DetectorPop[i],{'n_events':0}) 422 + for j in range(0,len(hist)): 423 + f.write(str(Tbin[j])+" ") 424 + for i in range(0,int(InfoBuild[0])): 425 + f.write(str(Equilibri[i][j])+" ") 426 + f.write("\n ") 427 + ########################################################### 428 + tempo=tempo+T1 429 + for contatore2 in range(1,(appoggio1-appoggio2)): 430 + nest.Simulate(1000.) 431 + #Save the Data!!!! 432 + ########################################################### 433 + Equilibri=[] 434 + for i in range(0,int(InfoBuild[0])): 435 + Equilibri.append([]) 436 + a=nest.GetStatus(DetectorPop[i])[0]["events"]["times"] 437 + if len(a)>0: 438 + Trange=(1000*int(numpy.min(a)/1000.),1000*int(numpy.min(a)/1000.)+1000) 439 + hist,Tbin=numpy.histogram(a,200,(Trange[0],Trange[1])) 440 + Equilibri[i]=hist*1000./(5.*int(InfoBuild[i+1][0])) 441 + else: 442 + Trange=(1000*int(tempo/1000.),1000*int(tempo/1000.)+1000) 443 + hist=numpy.zeros(200) 444 + Tbin=numpy.linspace(Trange[0],Trange[1],num=201) 445 + Equilibri[i]=hist 446 + nest.SetStatus(DetectorPop[i],{'n_events':0}) 447 + for j in range(0,len(hist)): 448 + f.write(str(Tbin[j])+" ") 449 + for i in range(0,int(InfoBuild[0])): 450 + f.write(str(Equilibri[i][j])+" ") 451 + f.write("\n ") 452 + tempo=tempo+1000. 453 + T2=appoggio3-tempo 454 + nest.Simulate(T2); 455 + tempo=tempo+T2; 456 + else: 457 + nest.Simulate(InfoProtocol[contatore][0]) 458 + temp=InfoProtocol[contatore][0] 459 + tempo=tempo+temp 460 + if InfoProtocol[contatore][2]==4: 461 + nest.SetStatus(NoisePop[InfoProtocol[contatore][1]],params={"rate": float(InfoBuild[1+InfoProtocol[contatore][1]][2]*InfoProtocol[contatore][3])}) 462 + if InfoProtocol[contatore][2]==12: 463 + nest.SetStatus(NeuronPop[InfoProtocol[contatore][1]], params={"b": float(InfoProtocol[contatore][3])}) 464 + else: 465 + nest.Simulate(simtime) 466 + tempo=simtime 467 + if (simtime-tempo)>0.: 468 + nest.Simulate(simtime-tempo) 469 + 470 + 471 + endsimulate = time.time() 472 + f.close() 473 + else: 474 + if len(InfoProtocol): 475 + tempo=0 476 + for contatore in range(0,len(InfoProtocol)): 477 + nest.Simulate(InfoProtocol[contatore][0]) 478 + temp=InfoProtocol[contatore][0] 479 + tempo=tempo+temp 480 + if InfoProtocol[contatore][2]==4: 481 + nest.SetStatus(NoisePop[InfoProtocol[contatore][1]],params={"rate": float(InfoBuild[1+InfoProtocol[contatore][1]][2]*InfoProtocol[contatore][3])}) 482 + #print "Population:", InfoProtocol[contatore][1] ,";Parameter:", InfoProtocol[contatore][2] ,"; Value: ",InfoProtocol[contatore][3] 483 + if InfoProtocol[contatore][2]==12: 484 + nest.SetStatus(NeuronPop[InfoProtocol[contatore][1]], params={"b": float(InfoProtocol[contatore][3])}) 485 + #print "Population:", InfoProtocol[contatore][1] ,";Parameter:", InfoProtocol[contatore][2] ,"; Value: ",InfoProtocol[contatore][3] 486 + 487 + else: 488 + nest.Simulate(simtime) 489 + tempo=simtime 490 + if (simtime-tempo)>0.: 491 + nest.Simulate(simtime-tempo) 492 + endsimulate = time.time() 493 + 494 + 495 + ################################################################################################################################################################### 496 + 497 + #############################------------------------------------------------------------------------ 498 + #print some information from the simulation 499 + #############################------------------------------------------------------------------------ 500 + 501 + num_synapses = nest.GetDefaults('static_synapse_hpc')["num_connections"] 502 + build_time = endbuild - startbuild 503 + connect_time = endconnect - startconnect 504 + sim_time = endsimulate - endconnect 505 + 506 + N_neurons=0 507 + for i in range(0,int(InfoBuild[0])): 508 + N_neurons=N_neurons+int(InfoBuild[i+1][0]) 509 + 510 + print(" Network simulation (Python) neuron type:",InfoPerseo[0]) 511 + print("Number of neurons : {0}".format(N_neurons)) 512 + print("Number of synapses: {0}".format(num_synapses)) 513 + print("Building time : %.2f s" % build_time) 514 + print("Connecting time : %.2f s" % connect_time) 515 + print("Simulation time : %.2f s" % sim_time) 516 + 517 +Fine=time.time() 518 +print ("Total Simulation time : %.2f s" % (Fine-Inizio)) 519 +{{/code}} 520 + 521 +=== === 522 + 523 +(% class="wikigeneratedid" %) 524 +=== [[image:image-20220127170155-2.png||height="682" width="1439"]] === 525 + 526 +=== Results: === 527 + 528 +the output of this simulationo is... 529 + 530 + 531 + 532 + 533 + 534 + 39 39 ==== ====
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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: