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