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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
Change comment: There is no comment for this version
To version 27.1
edited by galluzziandrea
on 2022/01/27 17:31
Change comment: There is no comment for this version

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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 +34,499 @@
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 +(% class="wikigeneratedid" %)
239 +=== [[image:image-20220127173048-1.png||height="508" width="948"]] ===
240 +
241 +=== Defining general and nest.kernel parameters ===
242 +
243 +{{code language="python"}}
244 +#############################------------------------------------------------------------------------
245 +#Clean the Network
246 +#############################------------------------------------------------------------------------
247 +nest.ResetKernel()
248 +
249 +#############################------------------------------------------------------------------------
250 +#insert the introductory parameters of the simulation
251 +#############################------------------------------------------------------------------------
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 +
39 39  ==== ====
CorticalField_t=80_DeepSpontPlanar.mp4
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