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interfaces.nipy.model

EstimateContrast

Code: file:///tmp/buildd/nipype-0.5.3/nipype/interfaces/nipy/model.py#L234

Estimate contrast of a fitted model.

Inputs:

[Mandatory]
axis
beta: (an existing file name)
        beta coefficients of the fitted model
constants
contrasts: (a list of items which are a tuple of the form: (a string, 'T', a list of
         items which are a string, a list of items which are a float) or a tuple of the form: (a
         string, 'T', a list of items which are a string, a list of items which are a float, a
         list of items which are a float) or a tuple of the form: (a string, 'F', a list of
         items which are a tuple of the form: (a string, 'T', a list of items which are a
         string, a list of items which are a float) or a tuple of the form: (a string, 'T', a
         list of items which are a string, a list of items which are a float, a list of items
         which are a float)))
        List of contrasts with each contrast being a list of the form:
                    [('name', 'stat', [condition list], [weight list], [session list])]. if
                    session list is None or not provided, all sessions are used. For F
                    contrasts, the condition list should contain previously defined
                    T-contrasts.
dof
        degrees of freedom
nvbeta
reg_names: (a list of items which are any value)
s2: (an existing file name)
        squared variance of the residuals

[Optional]
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the interface fails to
        run
mask: (a file name)

Outputs:

p_maps: (an existing file name)
stat_maps: (an existing file name)
z_maps: (an existing file name)

FitGLM

Code: file:///tmp/buildd/nipype-0.5.3/nipype/interfaces/nipy/model.py#L60

Fit GLM model based on the specified design. Supports only single or concatenated runs.

Inputs:

[Mandatory]
TR: (a float)

[Optional]
drift_model: ('Cosine' or 'Polynomial' or 'Blank', nipype default value: Cosine)
        string that specifies the desired drift model, to be chosen among 'Polynomial',
        'Cosine', 'Blank'
hrf_model: ('Canonical' or 'Canonical With Derivative' or 'FIR', nipype default value:
         Canonical)
        that specifies the hemodynamic reponse function it can be 'Canonical', 'Canonical With
        Derivative' or 'FIR'
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the interface fails to
        run
mask: (a file name)
        restrict the fitting only to the region defined by this mask
method: ('kalman' or 'ols')
        method to fit the model, ols or kalma; kalman is more time consuming but it supports
        autoregressive model
model: ('ar1' or 'spherical', nipype default value: ar1)
        autoregressive mode is available only for the kalman method
normalize_design_matrix: (a boolean, nipype default value: False)
        normalize (zscore) the regressors before fitting
plot_design_matrix: (a boolean, nipype default value: False)
save_residuals: (a boolean, nipype default value: False)
session_info: (a list of from 1 to 1 items which are any value)
        Session specific information generated by ``modelgen.SpecifyModel``, FitGLM    does not
        support multiple runs uless they are concatenated (see SpecifyModel options)

Outputs:

a: (an existing file name)
axis
beta: (an existing file name)
constants
dof
nvbeta
reg_names: (a list of items which are any value)
residuals: (a file name)
s2: (an existing file name)