pyhrf.jde.nrl.bigaussian.
BiGaussMixtureParamsSampler
(do_sampling=True, use_true_value=False, val_ini=None, hyper_prior_type='Jeffreys', activ_thresh=4.0, var_ci_pr_alpha=2.04, var_ci_pr_beta=0.5, var_ca_pr_alpha=2.01, var_ca_pr_beta=0.5, mean_ca_pr_mean=5.0, mean_ca_pr_var=20.0)¶Bases: pyhrf.xmlio.Initable
, pyhrf.jde.samplerbase.GibbsSamplerVariable
#TODO : comment
I_MEAN_CA
= 0¶I_VAR_CA
= 1¶I_VAR_CI
= 2¶L_CA
= 1¶L_CI
= 0¶NB_PARAMS
= 3¶PARAMS_NAMES
= ['Mean_Activ', 'Var_Activ', 'Var_Inactiv']¶checkAndSetInitValue
(variables)¶computeWithJeffreyPriors
(j, cardCIj, cardCAj)¶computeWithProperPriors
(j, cardCIj, cardCAj)¶finalizeSampling
()¶getCurrentMeans
()¶getCurrentVars
()¶getOutputs
()¶get_string_value
(v)¶linkToData
(dataInput)¶parametersComments
= {'activ_thresh': 'Threshold for the max activ mean above which the region is considered activating', 'hyper_prior_type': "Either 'proper' or 'Jeffreys'"}¶parametersToShow
= []¶sampleNextInternal
(variables)¶Define the behaviour of the variable at each sampling step when its sampling is not activated. Must be overriden in child classes.
updateObsersables
()¶pyhrf.jde.nrl.bigaussian.
BiGaussMixtureParamsSamplerWithRelVar
(do_sampling=True, use_true_value=False, val_ini=None, hyper_prior_type='Jeffreys', activ_thresh=4.0, var_ci_pr_alpha=2.04, var_ci_pr_beta=0.5, var_ca_pr_alpha=2.01, var_ca_pr_beta=0.5, mean_ca_pr_mean=5.0, mean_ca_pr_var=20.0)¶Bases: pyhrf.jde.nrl.bigaussian.BiGaussMixtureParamsSampler
computeWithProperPriorsWithRelVar
(nrlsj, j, cardCIj, cardCAj, wj)¶sampleNextInternal
(variables)¶Define the behaviour of the variable at each sampling step when its sampling is not activated. Must be overriden in child classes.
pyhrf.jde.nrl.bigaussian.
BiGaussMixtureParamsSamplerWithRelVar_OLD
(do_sampling=True, use_true_value=False, val_ini=None, hyper_prior_type='Jeffreys', activ_thresh=4.0, var_ci_pr_alpha=2.04, var_ci_pr_beta=0.5, var_ca_pr_alpha=2.01, var_ca_pr_beta=0.5, mean_ca_pr_mean=5.0, mean_ca_pr_var=20.0)¶Bases: pyhrf.jde.nrl.bigaussian.BiGaussMixtureParamsSampler
computeWithProperPriorsWithRelVar
(nrlsj, j, cardCIj, cardCAj, wj)¶sampleNextInternal
(variables)¶Define the behaviour of the variable at each sampling step when its sampling is not activated. Must be overriden in child classes.
pyhrf.jde.nrl.bigaussian.
MixtureWeightsSampler
(do_sampling=True, use_true_value=False, val_ini=None)¶Bases: pyhrf.xmlio.Initable
, pyhrf.jde.samplerbase.GibbsSamplerVariable
#TODO : comment
checkAndSetInitValue
(variables)¶getOutputs
()¶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.
pyhrf.jde.nrl.bigaussian.
NRLSampler
(do_sampling=True, val_ini=None, contrasts={}, do_label_sampling=True, use_true_nrls=False, use_true_labels=False, labels_ini=None, ppm_proba_threshold=0.05, ppm_value_threshold=0, ppm_value_multi_threshold=array([ 0., 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1., 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2., 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3., 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4. ]), mean_activation_threshold=4, rescale_results=False, wip_variance_computation=False)¶Bases: pyhrf.xmlio.Initable
, pyhrf.jde.samplerbase.GibbsSamplerVariable
Class handling the Gibbs sampling of Neural Response Levels with a prior bi-gaussian mixture model. It handles independent and spatial versions.
CLASSES
= array([0, 1])¶CLASS_NAMES
= ['inactiv', 'activ']¶FALSE_NEG
= 3¶FALSE_POS
= 2¶L_CA
= 1¶L_CI
= 0¶PPMcalculus
(apost_mean_activ, apost_var_activ, apost_mean_inactiv, apost_var_inactiv, labels_activ, labels_inactiv)¶Function to calculate the probability that the nrl in voxel j, condition m, is superior to a given hreshold_value
ThresholdPPM
(threshold_pval)¶calcFracLambdaTilde
(cond, c1, c2, variables)¶checkAndSetInitLabels
(variables)¶checkAndSetInitNRL
(variables)¶checkAndSetInitValue
(variables)¶cleanMemory
()¶cleanObservables
()¶computeAA
(nrls, destaa)¶computeComponentsApost
(variables, j, gTQg)¶computeContrasts
()¶computeVarXhtQ
(h, varXQ)¶computeVarYTildeOpt
(varXh)¶compute_summary_stats
()¶countLabels
(labels, voxIdx, cardClass)¶finalizeSampling
()¶getClassifRate
()¶getFinalLabels
(thres=None)¶getOutputs
()¶getRocData
(dthres=0.005)¶get_final_summary
()¶initObservables
()¶init_contrasts
()¶linkToData
(dataInput)¶markWrongLabels
(labels)¶parametersComments
= {'contrasts': 'Define contrasts as arithmetic expressions.\nCondition names used in expressions must be consistent with those specified in session data above'}¶parametersToShow
= ['contrasts']¶printState
(_)¶reportDetection
()¶sampleLabels
(cond, variables)¶sampleNextAlt
(variables)¶Define the behaviour of the variable at each sampling step when its sampling is not activated.
sampleNextInternal
(variables)¶Define the behaviour of the variable at each sampling step when its sampling is not activated. Must be overriden in child classes.
sampleNrlsParallel
(varXh, rb, h, varLambda, varCI, varCA, meanCA, gTQg, variables)¶sampleNrlsSerial
(rb, h, varCI, varCA, meanCA, gTQg, variables)¶samplingWarmUp
(variables)¶#TODO : comment
saveCurrentValue
(it)¶saveObservables
(it)¶updateObsersables
()¶pyhrf.jde.nrl.bigaussian.
NRLSamplerWithRelVar
(do_sampling=True, val_ini=None, contrasts={}, do_label_sampling=True, use_true_nrls=False, use_true_labels=False, labels_ini=None, ppm_proba_threshold=0.05, ppm_value_threshold=0, ppm_value_multi_threshold=array([ 0., 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1., 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2., 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3., 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4. ]), mean_activation_threshold=4, rescale_results=False, wip_variance_computation=False)¶Bases: pyhrf.jde.nrl.bigaussian.NRLSampler
calcFracLambdaTildeWithIRRelCond
(cond, c1, c2, variables, nbVox, moyqvoxj, t1, t2)¶calcFracLambdaTildeWithRelCond
(l, nbVox, moyqvoxj, t1, t2)¶computeComponentsApostWithRelVar
(variables, j, gTQg, w)¶computeSumWAxh
(wa, varXh)¶computeVarYTildeOptWithRelVar
(varXh, w)¶computeWA
(a, w, wa)¶computemoyqvox
(cardClass, nbVox)¶Compute mean of labels in ROI (without the label of voxel i)
createWAxh
(aXh, w)¶deltaWCorr0
(nbVox, moyqvoxj, t1, t2)¶deltaWCorr1
(nbVox, moyqvoxj, t1, t2)¶sampleLabelsWithRelVar
(cond, variables)¶sampleNextInternal
(variables)¶Define the behaviour of the variable at each sampling step when its sampling is not activated. Must be overriden in child classes.
sampleNrlsParallelWithRelVar
(varXh, rb, h, varLambda, varCI, varCA, meanCA, gTQg, variables, w)¶sampleNrlsSerialWithRelVar
(rb, h, gTQg, variables, w, t1, t2)¶samplingWarmUp
(variables)¶#TODO : comment
subtractYtildeWithRelVar
()¶pyhrf.jde.nrl.bigaussian.
NRL_Multi_Sess_Sampler
(parameters=None, xmlHandler=None, xmlLabel=None, xmlComment=None)¶Bases: pyhrf.jde.samplerbase.GibbsSamplerVariable
P_OUTPUT_NRL
= 'writeResponsesOutput'¶P_SAMPLE_FLAG
= 'sampleFlag'¶P_TrueNrlFilename
= 'TrueNrlFilename'¶P_USE_TRUE_NRLS
= 'useTrueNrls'¶P_VAL_INI
= 'initialValue'¶checkAndSetInitValue
(variables)¶cleanMemory
()¶computeAA
(nrls, destaa)¶computeComponentsApost
(variables, m, varXh, s)¶computeVarYTildeSessionOpt
(varXh, s)¶defaultParameters
= {'TrueNrlFilename': None, 'initialValue': None, 'sampleFlag': True, 'useTrueNrls': False, 'writeResponsesOutput': True}¶finalizeSampling
()¶getOutputs
()¶linkToData
(dataInput)¶parametersComments
= {'TrueNrlFilename': 'Define the filename of simulated NRLs.\nIt is taken into account when NRLs is not sampled.'}¶parametersToShow
= ['writeResponsesOutput']¶sampleNextAlt
(variables)¶sampleNextInternal
(variables)¶samplingWarmUp
(variables)¶#TODO : comment
saveCurrentValue
(it)¶pyhrf.jde.nrl.bigaussian.
Variance_GaussianNRL_Multi_Sess
(parameters=None, xmlHandler=None, xmlLabel=None, xmlComment=None)¶Bases: pyhrf.jde.samplerbase.GibbsSamplerVariable
P_SAMPLE_FLAG
= 'sampleFlag'¶P_USE_TRUE_VALUE
= 'useTrueValue'¶P_VAL_INI
= 'initialValue'¶checkAndSetInitValue
(variables)¶defaultParameters
= {'initialValue': array([ 1.]), 'sampleFlag': False, 'useTrueValue': False}¶linkToData
(dataInput)¶parametersToShow
= ['useTrueValue']¶sampleNextInternal
(variables)¶