pyhrf.ui.vb_jde_analyser_asl_fast.JDEVEMAnalyser(hrfDuration=25.0, dt=0.5, fast=True, constrained=False, nbClasses=2, PLOT=False, nItMax=1, nItMin=1, scale=False, beta=1.0, simulation=None, fmri_data=None, computeContrast=True, estimateH=True, estimateG=True, use_hyperprior=False, estimateSigmaH=True, estimateSigmaG=True, positivity=False, sigmaH=0.0001, sigmaG=0.0001, sigmaMu=0.0001, physio=True, gammaH=1000, gammaG=1000, zero_constrained=False, estimateLabels=True, estimateMixtParam=True, contrasts=None, InitVar=0.5, InitMean=2.0, estimateA=True, estimateC=True, estimateBeta=True, estimateNoise=True, estimateLA=True, phy_params={'E0': 0.34, 'TE': 0.018, 'V0': 1, 'alpha_w': 0.33, 'buxton': False, 'e': 1.43, 'eps': 0.54, 'eps_max': 10.0, 'linear': False, 'model': 'RBM', 'model_name': 'Khalidov11', 'obata': False, 'r0': 100, 'tau_f': 2.46, 'tau_m': 0.98, 'tau_s': 1.54, 'vt0': 80.6}, prior='omega', n_session=1)¶Bases: pyhrf.ui.jde.JDEAnalyser
analyse_roi(roiData)¶finalizeEstimation(true_labels, labels, nvox, true_brf, estimated_brf, true_prf, estimated_prf, true_brls, brls, true_prls, prls, true_drift, PL, L, true_noise, noise)¶parametersComments = {'InitMean': 'Initiale value of active gaussian means', 'InitVar': 'Initiale value of active and inactive gaussian variances', 'PLOT': 'plotting flag for convergence curves', 'beta': 'initial value of spatial Potts regularization parameter', 'constrained': 'adding constrains: positivity and norm = 1 ', 'dt': 'time resolution of the estimated HRF in seconds', 'estimateBeta': 'estimate or not the Potts spatial regularization parameter', 'estimateG': 'estimate or not the PRF', 'estimateH': 'estimate or not the HRF', 'estimateLA': 'Explicit drift and perfusion baseline estimation', 'estimateLabels': 'estimate or not the Labels', 'estimateMixtParam': 'estimate or not the mixture parameters', 'estimateSigmaG': 'estimate or not the PRF variance', 'estimateSigmaH': 'estimate or not the HRF variance', 'fast': 'running fast VEM with C extensions', 'hrfDuration': 'duration of the HRF in seconds', 'nItMax': 'maximum iteration number', 'nItMin': 'minimum iteration number', 'nbClasses': 'number of classes for the response levels', 'scale': 'flag for the scaling factor applied to the data fidelity term during m_h step.\nIf scale=False then do nothing, else divide the data fidelity term by the number of voxels', 'sigmaG': 'Initial PRF variance', 'sigmaH': 'Initial HRF variance', 'simulation': 'indicates whether the run corresponds to a simulation example or not', 'zero_constrained': 'putting first and last point of the HRF to zero '}¶parametersToShow = ['dt', 'hrfDuration', 'nItMax', 'nItMin', 'estimateSigmaH', 'estimateSigmaG', 'estimateH', 'estimateG', 'estimateBeta', 'estimateLabels', 'estimateLA', 'estimateMixtParam', 'InitVar', 'InitMean', 'scale', 'nbClasses', 'fast', 'PLOT', 'sigmaH', 'sigmaG']¶pyhrf.ui.vb_jde_analyser_asl_fast.change_dim(labels)¶Change labels dimension from (ncond, nclass, nvox) to (nclass, ncond, nvox)
pyhrf.ui.vb_jde_analyser_asl_fast.run_analysis(**params)¶