def __init__(self, hrfDuration=25., sigmaH=0.1, fast=True,
computeContrast=True, nbClasses=2, PLOT=False, nItMax=100,
nItMin=1, scale=False, beta=1.0, estimateSigmaH=True,
estimateHRF=True, TrueHrfFlag=False, HrfFilename='hrf.nii',
estimateDrifts=True, hyper_prior_sigma_H=1000, dt=.6,
estimateBeta=True, contrasts=None, simulation=False,
estimateLabels=True, LabelsFilename=None,
MFapprox=False, estimateMixtParam=True, constrained=False,
InitVar=0.5, InitMean=2.0, MiniVemFlag=False, NbItMiniVem=5,
zero_constraint=True, output_drifts=False, drifts_type="poly"):
XmlInitable.__init__(self)
JDEAnalyser.__init__(self, outputPrefix='jde_vem_')
# Important thing : all parameters must have default values
self.dt = dt
#self.driftType = driftType
self.hrfDuration = hrfDuration
self.nbClasses = nbClasses
self.nItMax = nItMax
self.estimateSigmaH = estimateSigmaH
self.scale = scale
self.estimateDrifts = estimateDrifts
self.PLOT = PLOT
self.fast = fast
self.simulation = simulation
self.beta = beta
self.sigmaH = sigmaH
self.estimateHRF = estimateHRF
self.TrueHrfFlag = TrueHrfFlag
self.HrfFilename = HrfFilename
self.nItMin = nItMin
self.estimateBeta = estimateBeta
self.estimateMixtParam = estimateMixtParam
self.estimateLabels = estimateLabels
self.LabelsFilename = LabelsFilename
self.MFapprox = MFapprox
self.InitVar = InitVar
self.InitMean = InitMean
self.MiniVemFlag = MiniVemFlag
self.NbItMiniVem = NbItMiniVem
if contrasts is None:
contrasts = OrderedDict()
self.contrasts = contrasts
self.computeContrast = computeContrast
self.hyper_prior_sigma_H = hyper_prior_sigma_H
self.constrained = constrained
self.zero_constraint = zero_constraint
self.output_drifts = output_drifts
self.drifts_type = drifts_type
logger.info("VEM analyzer:")
logger.info(" - estimate sigma H: %s", str(self.estimateSigmaH))
logger.info(" - init sigma H: %f", self.sigmaH)
logger.info(" - hyper_prior_sigma_H: %f", self.hyper_prior_sigma_H)
logger.info(" - estimate drift: %s", str(self.estimateDrifts))
def __init__(self,
hrfDuration=25.,
dt=.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=PHY_PARAMS_KHALIDOV11,
prior='no',
n_session=1):
XmlInitable.__init__(self)
JDEAnalyser.__init__(self, outputPrefix='jde_vem_asl_')
# Important thing : all parameters must have default values
self.hrfDuration = hrfDuration
self.dt = dt
self.fast = fast
self.constrained = constrained
self.nbClasses = nbClasses
self.PLOT = PLOT
self.nItMax = nItMax
self.nItMin = nItMin
self.scale = scale
self.beta = beta
self.simulation = simulation
self.fmri_data = fmri_data
self.estimateH = estimateH
self.estimateG = estimateG
self.estimateSigmaH = estimateSigmaH
self.estimateSigmaG = estimateSigmaG
self.sigmaH = sigmaH
self.sigmaG = sigmaG
self.sigmaMu = sigmaMu
self.gammaH = gammaH
self.gammaG = gammaG
self.estimateLabels = estimateLabels
self.estimateMixtParam = estimateMixtParam
self.InitVar = InitVar
self.InitMean = InitMean
self.estimateA = estimateA
self.estimateC = estimateC
self.estimateBeta = estimateBeta
self.estimateNoise = estimateNoise
self.estimateLA = estimateLA
self.use_hyperprior = use_hyperprior
self.positivity = positivity
self.physio = physio
self.prior = prior
if contrasts is None:
contrasts = OrderedDict()
self.contrasts = contrasts
self.computeContrast = computeContrast
self.phy_params = phy_params
self.n_session = n_session
self.zc = zero_constrained
logger.info("VEM analyzer:")
logger.info(" - estimate sigma H: %s", str(self.estimateSigmaH))
logger.info(" - init sigma H: %f", self.sigmaH)
logger.info(" - estimate drift and perfusion baseline: %s",
str(self.estimateLA))
def __init__(self, hrfDuration=25., dt=.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=PHY_PARAMS_KHALIDOV11, prior='no', n_session=1):
XmlInitable.__init__(self)
JDEAnalyser.__init__(self, outputPrefix='jde_vem_asl_')
# Important thing : all parameters must have default values
self.hrfDuration = hrfDuration
self.dt = dt
self.fast = fast
self.constrained = constrained
self.nbClasses = nbClasses
self.PLOT = PLOT
self.nItMax = nItMax
self.nItMin = nItMin
self.scale = scale
self.beta = beta
self.simulation = simulation
self.fmri_data = fmri_data
self.estimateH = estimateH
self.estimateG = estimateG
self.estimateSigmaH = estimateSigmaH
self.estimateSigmaG = estimateSigmaG
self.sigmaH = sigmaH
self.sigmaG = sigmaG
self.sigmaMu = sigmaMu
self.gammaH = gammaH
self.gammaG = gammaG
self.estimateLabels = estimateLabels
self.estimateMixtParam = estimateMixtParam
self.InitVar = InitVar
self.InitMean = InitMean
self.estimateA = estimateA
self.estimateC = estimateC
self.estimateBeta = estimateBeta
self.estimateNoise = estimateNoise
self.estimateLA = estimateLA
self.use_hyperprior = use_hyperprior
self.positivity = positivity
self.physio = physio
self.prior = prior
if contrasts is None:
contrasts = OrderedDict()
self.contrasts = contrasts
self.computeContrast = computeContrast
self.phy_params = phy_params
self.n_session = n_session
self.zc = zero_constrained
logger.info("VEM analyzer:")
logger.info(" - estimate sigma H: %s", str(self.estimateSigmaH))
logger.info(" - init sigma H: %f", self.sigmaH)
logger.info(" - estimate drift and perfusion baseline: %s",
str(self.estimateLA))
