Note
This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.
nilearn.glm.compute_contrast#
- nilearn.glm.compute_contrast(labels, regression_result, con_val, contrast_type=None)[source]#
Compute the specified contrast given an estimated glm
- Parameters
- labelsarray of shape (n_voxels,)
A map of values on voxels used to identify the corresponding model
- regression_resultdict
With keys corresponding to the different labels values are RegressionResults instances corresponding to the voxels.
- con_valnumpy.ndarray of shape (p) or (q, p)
Where q = number of contrast vectors and p = number of regressors.
- contrast_type{None, ‘t’, ‘F’}, optional
Type of the contrast. If None, then defaults to ‘t’ for 1D con_val and ‘F’ for 2D con_val
- Returns
- conContrast instance,
Yields the statistics of the contrast (effects, variance, p-values).
Notes
This function is experimental. It may change in any future release of Nilearn.
Examples using nilearn.glm.compute_contrast#
Surface-based dataset first and second level analysis of a dataset