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# 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.

> 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 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