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 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.

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

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 unless 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 response 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