pyhrf.jde.wsampler.
WSampler
(do_sampling=True, use_true_value=False, val_ini=None, pr_sigmoid_slope=1.0, pr_sigmoid_thresh=0.0)¶Bases: pyhrf.xmlio.Initable
, pyhrf.jde.samplerbase.GibbsSamplerVariable
CLASSES
= array([0, 1])¶CLASS_NAMES
= ['inactiv', 'activ']¶L_CA
= 1¶L_CI
= 0¶checkAndSetInitValue
(variables)¶computeProbW1
(Qgj, gTQgj, rb, moyqj, t1, t2, mCAj, vCIj, vCAj, j, cardClassCAj)¶ProbW1 is the probability that condition is relevant It is a vecteur on length nbcond
computeVarXhtQ
(h, matXQ)¶computemoyq
(cardClassCA, nbVoxels)¶Compute mean of labels in ROI
finalizeSampling
()¶getOutputs
()¶initObservables
()¶linkToData
(dataInput)¶sampleNextInternal
(variables)¶Define the behaviour of the variable at each sampling step when its sampling is not activated. Must be overriden in child classes.
saveCurrentValue
(it)¶saveObservables
(it)¶threshold_W
(meanW, thresh)¶updateObsersables
()¶pyhrf.jde.wsampler.
W_Drift_Sampler
(do_sampling=True, use_true_value=False, val_ini=None, pr_sigmoid_slope=1.0, pr_sigmoid_thresh=0.0)¶Bases: pyhrf.xmlio.Initable
, pyhrf.jde.samplerbase.GibbsSamplerVariable
CLASSES
= array([0, 1])¶CLASS_NAMES
= ['inactiv', 'activ']¶L_CA
= 1¶L_CI
= 0¶checkAndSetInitValue
(variables)¶computeProbW1
(gj, gTgj, rb, t1, t2, mCAj, vCIj, vCAj, j, cardClassCAj)¶ProbW1 is the probability that condition is relevant It is a vecteur on length nbcond
computemoyq
(cardClassCA, nbVoxels)¶Compute mean of labels in ROI
finalizeSampling
()¶getOutputs
()¶initObservables
()¶linkToData
(dataInput)¶sampleNextInternal
(variables)¶Define the behaviour of the variable at each sampling step when its sampling is not activated. Must be overriden in child classes.
saveCurrentValue
(it)¶saveObservables
(it)¶threshold_W
(meanW, thresh)¶updateObsersables
()¶