pyhrf.jde.noise module

class pyhrf.jde.noise.NoiseARParamsSampler(do_sampling=True, use_true_value=False, val_ini=None)

Bases: pyhrf.xmlio.Initable, pyhrf.jde.samplerbase.GibbsSamplerVariable

MH_ARsampling_gauss_proposal(sig2, M)
MH_ARsampling_optim(A, reps, M)
P_SAMPLE_FLAG = 'sampleFlag'
P_USE_TRUE_VALUE = 'useTrueValue'
P_VAL_INI = 'initialValue'
checkAndSetInitValue(variables)
computeInvAutoCorrNoise(ARp)
defaultParameters = {'useTrueValue': False, 'initialValue': None, 'sampleFlag': True}
finalizeSampling()
linkToData(dataInput)
sampleNextInternal(variables)
class pyhrf.jde.noise.NoiseVarianceARSampler(do_sampling=True, use_true_value=False, val_ini=None)

Bases: pyhrf.jde.noise.NoiseVarianceSampler

checkAndSetInitValue(variables)
computeVarYTilde(varNrls, varXh, varMBYPl)
finalizeSampling()
sampleNextInternal(variables)
class pyhrf.jde.noise.NoiseVarianceSampler(do_sampling=True, use_true_value=False, val_ini=None)

Bases: pyhrf.xmlio.Initable, pyhrf.jde.samplerbase.GibbsSamplerVariable

#TODO : comment

checkAndSetInitValue(variables)
computeMXhQXh(h, varXQX)
compute_aaXhQXhi(aa, i)
finalizeSampling()
linkToData(dataInput)
sampleNextInternal(variables)
sampleNextInternal_bak(variables)
class pyhrf.jde.noise.NoiseVarianceSamplerWithRelVar(do_sampling=True, use_true_value=False, val_ini=None)

Bases: pyhrf.jde.noise.NoiseVarianceSampler

computeWW(w, destww)
compute_aawwXhQXhi(ww, aa, i)
finalizeSampling()
sampleNextInternal(variables)
class pyhrf.jde.noise.NoiseVariance_Drift_Sampler(do_sampling=True, use_true_value=False, val_ini=None)

Bases: pyhrf.xmlio.Initable, pyhrf.jde.samplerbase.GibbsSamplerVariable

checkAndSetInitValue(variables)
linkToData(dataInput)
sampleNextInternal(variables)
class pyhrf.jde.noise.NoiseVariancewithHabSampler(do_sampling=True, use_true_value=False, val_ini=None)

Bases: pyhrf.jde.noise.NoiseVarianceSampler

#TODO : Sampling procedure for noise variance parameters (white noise) #in case of habituation modeling wrt magnitude

finalizeSampling()
sampleNextInternal(variables)