nipype.interfaces.nipy.model module

EstimateContrast

Link to code

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.

dof : any 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

Link to code

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)

mask : a 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_matrix : a boolean

Normalize (zscore) the regressors before fitting. (Nipype default value: False)

plot_design_matrix : a boolean

(Nipype default value: False)

save_residuals : a 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