pyhrf.jde.drift module

class pyhrf.jde.drift.DriftARSampler(do_sampling=True, use_true_value=False, val_ini=None)

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

Gibbs sampler of the parameters modelling the low frequency drift in the fMRI time course, in the case of AR noise

checkAndSetInitValue(variables)
computeVarYTilde(varNrls, varXh)
fillOutputs2(outputs, iROI=-1)
finalizeSampling()
initOutputs2(outputs, nbROI=-1)
linkToData(dataInput)
sampleNextAlt(variables)
sampleNextInternal(variables)
samplingWarmUp(variables)

#TODO : comment

updateNorm()
updateVarYmDrift()
class pyhrf.jde.drift.DriftSampler(do_sampling=True, use_true_value=False, val_ini=None)

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

Gibbs sampler of the parameters modelling the low frequency drift in the fMRI time course, in the case of white noise.

checkAndSetInitValue(variables)
getOutputs()
linkToData(dataInput)
sampleNextInternal(variables)
updateNorm()
class pyhrf.jde.drift.DriftSamplerWithRelVar(do_sampling=True, use_true_value=False, val_ini=None)

Bases: pyhrf.jde.drift.DriftSampler

Gibbs sampler of the parameters modelling the low frequency drift in the fMRI time course, in the case of white noise.

checkAndSetInitValue(variables)
getOutputs()
linkToData(dataInput)
sampleNextInternal(variables)
updateNorm()
class pyhrf.jde.drift.ETASampler(do_sampling=True, use_true_value=False, val_ini=array([ 1.]))

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

Gibbs sampler of the variance of the Inverse Gamma prior used to regularise the estimation of the low frequency drift embedded in the fMRI time course

checkAndSetInitValue(variables)
linkToData(dataInput)
sampleNextInternal(variables)
class pyhrf.jde.drift.ETASampler_MultiSess(do_sampling=True, use_true_value=False, val_ini=array([ 1.]))

Bases: pyhrf.jde.drift.ETASampler

linkToData(dataInput)
sampleNextInternal(variables)
pyhrf.jde.drift.sampleDrift(varInvSigma_drift, ptLambdaY, dim)