nipype.interfaces.nipy.model module¶
EstimateContrast¶
Bases: NipyBaseInterface
Estimate contrast of a fitted model.
axis : any value beta : a pathlike object or string representing an existing file
Beta coefficients of the fitted model.
constants : any value contrasts : a list of items which are a tuple of the form: (a unicode string, ‘T’, a list of items which are a unicode string, a list of items which are a float) or a tuple of the form: (a unicode string, ‘T’, a list of items which are a unicode string, a list of items which are a float, a list of items which are a float) or a tuple of the form: (a unicode string, ‘F’, a list of items which are a tuple of the form: (a unicode string, ‘T’, a list of items which are a unicode string, a list of items which are a float) or a tuple of the form: (a unicode string, ‘T’, a list of items which are a unicode 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.
- dofany value
Degrees of freedom.
nvbeta : any value reg_names : a list of items which are any value s2 : a pathlike object or string representing an existing file
Squared variance of the residuals.
mask : a pathlike object or string representing an existing file
p_maps : a list of items which are a pathlike object or string representing an existing file stat_maps : a list of items which are a pathlike object or string representing an existing file z_maps : a list of items which are a pathlike object or string representing an existing file
FitGLM¶
Bases: NipyBaseInterface
Fit GLM model based on the specified design. Supports only single or concatenated runs.
TR : a float 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).
- drift_model‘Cosine’ or ‘Polynomial’ or ‘Blank’
String that specifies the desired drift model, to be chosen among ‘Polynomial’, ‘Cosine’, ‘Blank’. (Nipype default value:
Cosine
)- hrf_model‘Canonical’ or ‘Canonical With Derivative’ or ‘FIR’
That specifies the hemodynamic reponse function it can be ‘Canonical’, ‘Canonical With Derivative’ or ‘FIR’. (Nipype default value:
Canonical
)- maska pathlike object or string representing an existing file
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. (Nipype default value:
kalman
)- model‘ar1’ or ‘spherical’
Autoregressive mode is available only for the kalman method. (Nipype default value:
ar1
)- normalize_design_matrixa boolean
Normalize (zscore) the regressors before fitting. (Nipype default value:
False
)- plot_design_matrixa boolean
(Nipype default value:
False
)- save_residualsa boolean
(Nipype default value:
False
)a : a pathlike object or string representing an existing file axis : any value beta : a pathlike object or string representing an existing file constants : any value dof : any value nvbeta : any value reg_names : a list of items which are any value residuals : a pathlike object or string representing a file s2 : a pathlike object or string representing an existing file