Package | Description |
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inverters | |
mesd | |
numerics | |
optimizers |
Modifier and Type | Method and Description |
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static ThreeTensorFitter |
ThreeTensorFitter.getIndexedThreeTensorFitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s,
ModelIndex index)
Returns a ThreeTensorFitter with type specified by the index and
initialized with the passed parameters.
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static TwoTensorFitter |
TwoTensorFitter.getIndexedTwoTensorFitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s,
ModelIndex index)
Returns a TwoTensorFitter with type specified by the index and
initialized with the passed parameters.
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void |
DiffDataFitter.newDepVals(double[] depVals)
Initialises a new fitting procedure with the same independent variables
(b-vectors), but a new set of measurements (dependent variables).
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void |
BallStickFitter.newDepVals(double[] depVals)
Initializes the fitting procedure with a new set of measurements (dependent variables).
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void |
BallStickFitter.setInitParams(double[] aInit)
Sets the initial values of the parameters.
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Constructor and Description |
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BallStickFitter(DW_Scheme ip) |
DiffTensorFitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The number of unweighted acquisitions that are made (nob0s) is required to
estimate the noise levels of each data item.
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DiffTensorUnConFitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals, the
gradient directions) and associated dependent values (depVals, the data).
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ThreeTensorAxiSymFitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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ThreeTensorAxiSymFixMP_Fitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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ThreeTensorCholFitter(double[][] indepVals,
double[] depVals,
double[] diffusionTimes,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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ThreeTensorCholFixMP_Fitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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ThreeTensorFitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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ThreeTensorOneAxiSymFitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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ThreeTensorOneAxiSymFixMP_Fitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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ThreeTensorTwoAxiSymFitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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ThreeTensorTwoAxiSymFixMP_Fitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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TwoTensorAxiSymFitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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TwoTensorAxiSymFixMP_Fitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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TwoTensorCholFitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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TwoTensorCholFixMP_Fitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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TwoTensorFitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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TwoTensorOneAxiSymFitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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TwoTensorOneAxiSymFixMP_Fitter(double[][] indepVals,
double[] depVals,
double[] bValues,
int nob0s)
The constructor requires a list of independent values (indepVals) and
associated dependent values (depVals) - these are the data.
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Modifier and Type | Method and Description |
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void |
MESD_Fitter.newDepVals(double[] depVals)
Initialises a new fitting procedure with the same independent variables
(sampled directions), but a new set of measurements (dependent
variables).
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Constructor and Description |
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MESD_Fitter(double[][] indepVals,
int nob0s,
double[] params,
int numLambdas)
Constructor.
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Modifier and Type | Method and Description |
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void |
TwoFibreWatsonFitter.fitEstimatedParams(double initAlpha,
int attempts)
Make estimates of the initial parameters and attempt a minimisation with each.
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void |
TwoFibreFixedPropWatsonFitter.fitEstimatedParams(Vector3D mu1,
Vector3D mu2,
double innerCone1,
double outerCone1,
double innerCone2,
double outerCone2,
double initK1,
double initK2,
int attemptsOnCone)
Make estimates of the initial parameters and attempt a minimisation with each.
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void |
TwoFibreFixedPropWatsonFitter.fitEstimatedParams(Vector3D mu1,
Vector3D mu2,
int attemptsOnCone)
Two cones are defined for each mean axis, centered on the mean axis.
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void |
TwoFibreWatsonFitter.setInitParams(double[] aInit)
Sets the initial values of the parameters.
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void |
TwoFibreFixedPropWatsonFitter.setInitParams(double[] aInit)
Sets the initial values of the parameters.
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void |
TwoFibreBipolarWatsonFitter.setInitParams(double[] aInit)
Sets the initial values of the parameters.
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void |
TwoFibreFixedPropWatsonFitter.setInitParams(Vector3D mu1,
Vector3D mu2,
double k1,
double k2)
Set an initial estimate of the parameters.
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void |
TwoFibreBipolarWatsonFitter.setInitParams(Vector3D mu1,
Vector3D mu2,
double k1,
double k2)
Set an initial estimate of the parameters.
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Modifier and Type | Class and Description |
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class |
MarquardtMinimiserNonConvergenceException
Purpose:
Exception class used in Marquardt Minimiser.
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Modifier and Type | Method and Description |
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void |
MarquardtMinimiser.minimise()
Runs the minimization.
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void |
LM_Minimizer.minimise() |
void |
MarquardtMinimiser.setInitParams(double[] aInit)
Sets the initial values of the parameters.
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void |
LM_Minimizer.setMeasurements(double[] newMeas)
Initializes the fitting procedure with a new set of
measurements (dependent variables).
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Constructor and Description |
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LM_GaussianMinimizer(DW_Scheme scheme,
ParametricModel pm,
Codec cod)
Constructor needs all the following:
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LM_OffGaussMinimizer(DW_Scheme scheme,
ParametricModel pm,
Codec cod,
double sigma)
Constructor needs all the following:
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LM_RicianMinimizer(DW_Scheme scheme,
ParametricModel pm,
Codec cod,
double sigma)
Constructor needs all the following:
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