pyhrf.jde.asl_physio_joint module¶
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class
pyhrf.jde.asl_physio_joint.ASLPhysioSampler(nb_iterations=3000, obs_hist_pace=-1.0, glob_obs_hist_pace=-1, smpl_hist_pace=-1.0, burnin=0.3, callback=<pyhrf.jde.samplerbase.GSDefaultCallbackHandler object>, bold_response_levels=<pyhrf.jde.asl_physio_joint.BOLDResponseLevelSampler object>, perf_response_levels=<pyhrf.jde.asl_physio_joint.PerfResponseLevelSampler object>, labels=<pyhrf.jde.asl_physio_joint.LabelSampler object>, noise_var=<pyhrf.jde.asl_physio_joint.NoiseVarianceSampler object>, brf=<pyhrf.jde.asl_physio_joint.PhysioBOLDResponseSampler object>, prf=<pyhrf.jde.asl_physio_joint.PhysioPerfResponseSampler object>, prfbrf_var=<pyhrf.jde.asl_physio_joint.PhysioJointResponseVarianceSampler object>, bold_mixt_params=<pyhrf.jde.asl_physio_joint.BOLDMixtureSampler object>, perf_mixt_params=<pyhrf.jde.asl_physio_joint.PerfMixtureSampler object>, drift=<pyhrf.jde.asl_physio_joint.DriftCoeffSampler object>, drift_var=<pyhrf.jde.asl_physio_joint.DriftVarianceSampler object>, perf_baseline=<pyhrf.jde.asl_physio_joint.PerfBaselineSampler object>, perf_baseline_var=<pyhrf.jde.asl_physio_joint.PerfBaselineVarianceSampler object>, check_final_value=None)¶ Bases:
pyhrf.xmlio.Initable,pyhrf.jde.samplerbase.GibbsSampler-
computeFit()¶
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default_nb_its= 3000¶
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finalizeSampling()¶
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getGlobalOutputs()¶
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inputClass¶ alias of
WN_BiG_ASLSamplerInput
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parametersToShow= ['nb_its', 'response_levels', 'hrf', 'hrf_var']¶
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class
pyhrf.jde.asl_physio_joint.BOLDMixtureSampler(val_ini=None, do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.asl_physio_joint.MixtureParamsSampler,pyhrf.xmlio.Initable-
get_true_values_from_simulation_cdefs(cdefs)¶
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class
pyhrf.jde.asl_physio_joint.BOLDResponseLevelSampler(val_ini=None, do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.asl_physio_joint.ResponseLevelSampler,pyhrf.xmlio.Initable-
computeVarYTildeOpt(update_perf=False)¶ if update_perf is True then also update sumcXg and prl.ytilde update_perf should only be used at init of variable values.
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getOutputs()¶
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samplingWarmUp(v)¶
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class
pyhrf.jde.asl_physio_joint.DriftCoeffSampler(val_ini=None, do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.samplerbase.GibbsSamplerVariable,pyhrf.xmlio.Initable-
checkAndSetInitValue(variables)¶
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compute_y_tilde()¶
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getOutputs()¶
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linkToData(dataInput)¶
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sampleNextInternal(variables)¶
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samplingWarmUp(v)¶
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updateNorm()¶
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class
pyhrf.jde.asl_physio_joint.DriftVarianceSampler(val_ini=array([ 1.]), do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.samplerbase.GibbsSamplerVariable,pyhrf.xmlio.Initable-
checkAndSetInitValue(variables)¶
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linkToData(dataInput)¶
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sampleNextInternal(variables)¶
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class
pyhrf.jde.asl_physio_joint.LabelSampler(val_ini=None, do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.samplerbase.GibbsSamplerVariable,pyhrf.xmlio.Initable-
CLASSES= array([0, 1])¶
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CLASS_NAMES= ['inactiv', 'activ']¶
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L_CA= 1¶
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L_CI= 0¶
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checkAndSetInitValue(variables)¶
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compute_ext_field()¶
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countLabels()¶
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linkToData(dataInput)¶
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sampleNextInternal(v)¶
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samplingWarmUp(v)¶
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class
pyhrf.jde.asl_physio_joint.MixtureParamsSampler(name, response_level_name, val_ini=None, do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.samplerbase.GibbsSamplerVariable-
I_MEAN_CA= 0¶
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I_VAR_CA= 1¶
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I_VAR_CI= 2¶
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L_CA= 1¶
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L_CI= 0¶
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NB_PARAMS= 3¶
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PARAMS_NAMES= ['Mean_Activ', 'Var_Activ', 'Var_Inactiv']¶
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checkAndSetInitValue(variables)¶
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computeWithJeffreyPriors(j, cardCIj, cardCAj)¶
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get_current_means()¶
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get_current_vars()¶
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get_true_values_from_simulation_dict()¶
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linkToData(dataInput)¶
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sampleNextInternal(variables)¶
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class
pyhrf.jde.asl_physio_joint.NoiseVarianceSampler(val_ini=None, do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.samplerbase.GibbsSamplerVariable,pyhrf.xmlio.Initable-
checkAndSetInitValue(variables)¶
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compute_y_tilde()¶
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linkToData(dataInput)¶
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sampleNextInternal(variables)¶
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class
pyhrf.jde.asl_physio_joint.PerfBaselineSampler(val_ini=None, do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.samplerbase.GibbsSamplerVariable,pyhrf.xmlio.Initable-
checkAndSetInitValue(variables)¶
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compute_residuals()¶
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compute_wa(a=None)¶
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linkToData(dataInput)¶
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sampleNextInternal(v)¶
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class
pyhrf.jde.asl_physio_joint.PerfBaselineVarianceSampler(val_ini=None, do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.samplerbase.GibbsSamplerVariable,pyhrf.xmlio.Initable-
checkAndSetInitValue(variables)¶
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linkToData(dataInput)¶
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sampleNextInternal(v)¶
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class
pyhrf.jde.asl_physio_joint.PerfMixtureSampler(val_ini=None, do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.asl_physio_joint.MixtureParamsSampler,pyhrf.xmlio.Initable-
checkAndSetInitValue(variables)¶
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get_true_values_from_simulation_cdefs(cdefs)¶
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class
pyhrf.jde.asl_physio_joint.PerfResponseLevelSampler(val_ini=None, do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.asl_physio_joint.ResponseLevelSampler,pyhrf.xmlio.Initable-
checkAndSetInitValue(variables)¶
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computeVarYTildeOpt()¶
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class
pyhrf.jde.asl_physio_joint.PhysioBOLDResponseSampler(smooth_order=2, zero_constraint=True, duration=25.0, normalise=1.0, val_ini=None, do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.asl_physio_joint.ResponseSampler,pyhrf.xmlio.Initable-
computeYTilde()¶ y - sum cWXg - Pl - wa
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get_mat_X()¶
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get_mat_XtX()¶
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get_stackX()¶
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sampleNextInternal(variables)¶ Sample BRF
changes to mean: changes to var:
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samplingWarmUp(v)¶
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class
pyhrf.jde.asl_physio_joint.PhysioJointResponseVarianceSampler(val_ini=array([ 0.001]), do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.samplerbase.GibbsSamplerVariable,pyhrf.xmlio.Initable-
checkAndSetInitValue(v)¶
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linkToData(dataInput)¶
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sampleNextInternal(v)¶ Sample joint variance of BRF and PRF
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class
pyhrf.jde.asl_physio_joint.PhysioPerfResponseSampler(smooth_order=2, zero_constraint=True, duration=25.0, normalise=1.0, val_ini=None, do_sampling=True, use_true_value=False, diff_res=True)¶ Bases:
pyhrf.jde.asl_physio_joint.ResponseSampler,pyhrf.xmlio.Initable-
computeYTilde()¶ y - sum aXh - Pl - wa
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get_mat_X()¶
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get_mat_XtX()¶
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get_stackX()¶
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sampleNextInternal(variables)¶ Sample PRF with physio prior
changes to mean: add a factor of Omega h Sigma_g^-1 v_g^-1
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samplingWarmUp(variables)¶
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class
pyhrf.jde.asl_physio_joint.ResponseLevelSampler(name, response_name, mixture_name, val_ini=None, do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.samplerbase.GibbsSamplerVariable-
checkAndSetInitValue(variables)¶
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computeRR()¶
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computeVarYTildeOpt()¶
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linkToData(dataInput)¶
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sampleNextInternal(variables)¶
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samplingWarmUp(variables)¶
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class
pyhrf.jde.asl_physio_joint.ResponseSampler(name, response_level_name, variance_name, smooth_order=2, zero_constraint=True, duration=25.0, normalise=1.0, val_ini=None, do_sampling=True, use_true_value=False)¶ Bases:
pyhrf.jde.samplerbase.GibbsSamplerVariableGeneric parent class to perfusion response & BOLD response samplers
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calcXResp(resp, stackX=None)¶
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checkAndSetInitValue(variables)¶
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computeYTilde()¶
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getOutputs()¶
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get_mat_X()¶
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get_mat_XtX()¶
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get_rlrl()¶
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get_stackX()¶
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get_ybar()¶
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linkToData(dataInput)¶
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sampleNextInternal(variables)¶
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setFinalValue()¶
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updateNorm()¶
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updateXResp()¶
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class
pyhrf.jde.asl_physio_joint.WN_BiG_ASLSamplerInput(data, dt, typeLFD, paramLFD, hrfZc, hrfDuration)¶ Bases:
pyhrf.jde.models.WN_BiG_Drift_BOLDSamplerInput-
cleanPrecalculations()¶
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makePrecalculations()¶
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pyhrf.jde.asl_physio_joint.b()¶
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pyhrf.jde.asl_physio_joint.compute_StS_StY(rls, v_b, mx, mxtx, ybar, rlrl, yaj, ajak_vb)¶ yaj and ajak_vb are only used to store intermediate quantities, they’re not inputs.
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pyhrf.jde.asl_physio_joint.compute_bRpR(brl, prl, nbConditions, nbVoxels)¶