def runSim(pars,prefix): psth_exc_all=[] psth_inh_all=[] se_exc_all =[] freq_exc_all =[] se_inh_all= [] freq_inh_all= [] for num in np.arange(0,numTrials): pars["seed"] = [seeds[num]] net1 = simd.Simulation(prefix,new_pars=pars) net1.sim() ad2 = adata.analyze_data(prefix,net1.pars,net1.seed) ad2.pars.pops_exc = net1.pars.pops_exc ad2.pars.pops_inh = net1.pars.pops_inh ad2.pars.T_sim = net1.pars.T_sim print "len(ad2.pars.pops_exc)",len(ad2.pars.pops_exc) print "len(ad2.pars.pops_inh)",len(ad2.pars.pops_inh) print net1.events['spikes'] psth_exc,xx_exc = ad2.comp_psth1(nmax=len(ad2.pars.pops_exc),pop_id=ad2.pars.pops_exc,color='r',binsize=5.) psth_inh,xx_inh = ad2.comp_psth1(nmax=len(ad2.pars.pops_inh),pop_id=ad2.pars.pops_inh,color='r',binsize=5.) se_exc,power_exc,freq_exc,freq2_exc = ad2.spec_entropy(pop_id = ad2.pars.pops_exc,nmax=len(ad2.pars.pops_exc),freq_range=[10.,35.]) se_inh,power_inh,freq_inh,freq2_inh = ad2.spec_entropy(pop_id = ad2.pars.pops_inh,nmax=len(ad2.pars.pops_inh),freq_range=[10.,35.]) psth_exc_all.append(psth_exc) psth_inh_all.append(psth_inh) se_exc_all.append(se_exc) se_inh_all.append(se_inh) freq_exc_all.append(freq2_exc*100) freq_inh_all.append(freq2_inh*100) print "se_exc_all",se_exc_all print "se_inh_all",se_inh_all data=dict() data["psth_stn"] = [psth_exc_all,xx_exc] data["psth_gpe"] = [psth_inh_all,xx_inh] data["gids_stn"] = ad2.pars.pops_exc data["gids_gpe"] = ad2.pars.pops_inh data["freqSpec_stn"] = [se_exc_all,freq_exc_all] data["freqSpec_gpe"] = [se_inh_all,freq_inh_all] print "data",data pickle.dump(data,open("output/"+prefix+".pickle","w"),protocol=2)
def get_sim_3d(match_pars): print path1 res = adata.analyze_data(prefix1,data_path=path1) return res
def get_sim_3d(match_pars, seed): res = adata.analyze_data(prefix1, data_path=path1, netPars=pars, seed=seed) return res