modalities.fmri.spm.model¶
Class¶
SecondStage
¶
-
class
nipy.modalities.fmri.spm.model.
SecondStage
(fmri_image, formula, sigma, outputs=[], volume_start_times=None)¶ Bases:
object
- Parameters
- fmri_imageFmriImageList
object returning 4D array from
np.asarray
, having attributevolume_start_times
(if volume_start_times is None), and such thatobject[0]
returns something with attributesshape
- formula
nipy.algorithms.statistics.formula.Formula
- sigma :
- outputs :
- volume_start_times :
-
__init__
(fmri_image, formula, sigma, outputs=[], volume_start_times=None)¶ Initialize self. See help(type(self)) for accurate signature.
-
execute
()¶
Functions¶
-
nipy.modalities.fmri.spm.model.
Fmask
(Fimg, dfnum, dfdenom, pvalue=0.0001)¶ Create mask for use in estimating pooled covariance based on an F contrast.
-
nipy.modalities.fmri.spm.model.
estimate_pooled_covariance
(resid, ARtarget=[0.3], mask=None)¶ Use SPM’s REML implementation to estimate a pooled covariance matrix.
Thresholds an F statistic at a marginal pvalue to estimate covariance matrix.