Multivariate Pattern Analysis in Python

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# mvpa2.measures.adhocsearchlightbase

An efficient implementation of searchlight for GNB.

Functions

`borrowkwargs`(cls[, methodname, exclude]) | Return a decorator which would borrow docstring for `**kwargs` :Parameters: methodname : None or str Name of the method from which to borrow.
`inds_to_coo`(inds[, shape]) | Dispatcher for conversion to coo
`lastdim_columnsums_fancy_indexing`(a, inds, out) |
`lastdim_columnsums_spmatrix`(a, inds, out) |
`mean_mismatch_error`(predicted, target) | Computes the percentage of mismatches between some target and some predicted values.
`r_helper`(*args) |

Classes

`BaseSearchlight`(queryengine[, roi_ids, nproc]) | Base class for searchlights.
`Dataset`(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes.
`IndexQueryEngine`([sorted]) | Provides efficient query engine for discrete spaces.
`SimpleStatBaseSearchlight`(generator, qe[, ...]) | Base class for clf searchlights based on basic univar.
`Sphere`(radius[, element_sizes, distance_func]) | N-Dimensional hypersphere.
`Splitter`(attr[, attr_values, count, ...]) | Generator node for dataset splitting.

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