Wiki source code of Code description
Version 26.1 by galluzziandrea on 2022/01/27 17:30
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| author | version | line-number | content |
|---|---|---|---|
| 1 | == Introduction (path and modules): == | ||
| 2 | |||
| 3 | First of all we check the path and import the necessary modules . | ||
| 4 | |||
| 5 | === Check where I am and place myself in the right folder: === | ||
| 6 | |||
| 7 | {{code language="python"}} | ||
| 8 | # Import the os module | ||
| 9 | import os | ||
| 10 | |||
| 11 | #Print the current working directory | ||
| 12 | print("Current working directory: {0}".format(os.getcwd())) | ||
| 13 | |||
| 14 | # Change the current working directory | ||
| 15 | os.chdir('/mnt/user/shared/Slow waves in fading anesthesia/Nest3Python3') | ||
| 16 | |||
| 17 | # Print the current working directory | ||
| 18 | print("Current working directory: {0}".format(os.getcwd())) | ||
| 19 | {{/code}} | ||
| 20 | |||
| 21 | === Import the modules necessary for the simulation: === | ||
| 22 | |||
| 23 | {{code language="python"}} | ||
| 24 | import nest | ||
| 25 | import time | ||
| 26 | from numpy import exp | ||
| 27 | import numpy | ||
| 28 | import math | ||
| 29 | import random | ||
| 30 | import multiprocessing | ||
| 31 | Inizio=time.time() | ||
| 32 | print('tempo di Inizio:',Inizio) | ||
| 33 | {{/code}} | ||
| 34 | |||
| 35 | === === | ||
| 36 | |||
| 37 | === Define necessary classes to import the Initialization Files: === | ||
| 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 | === [[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...>>https://drive.ebrains.eu/smart-link/215f8213-17e3-468b-b573-e6eaf49d315e/]] | ||
| 523 | |||
| 524 | |||
| 525 | |||
| 526 | |||
| 527 | |||
| 528 | |||
| 529 | ==== ==== |
- 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: