mvpa2.mappers.fxΒΆ

Transform data by applying a function along samples or feature axis.

Inheritance diagram of mvpa2.mappers.fx

Functions

absolute_features() Returns a mapper that converts features into absolute values.
array_whereequal(a, x) Reliable comparison for numpy.ndarray numpy.ndarray (as of 1.5.0.dev) fails to compare tuples in array of dtype object, e.g.
borrowdoc(cls[, methodname]) Return a decorator to borrow docstring from another cls.`methodname`
max_of_abs(x) Max of absolute values along the 2nd axis
maxofabs_sample() Returns a mapper that finds max of absolute values of all samples.
mean_feature([attrfx]) Returns a mapper that computes the mean feature of a dataset.
mean_group_feature(attrs[, attrfx]) Returns a mapper that computes the mean features of unique feature groups.
mean_group_sample(attrs[, attrfx]) Returns a mapper that computes the mean samples of unique sample groups.
mean_sample([attrfx]) Returns a mapper that computes the mean sample of a dataset.
sum_of_abs(x) Sum of absolute values along the 2nd axis
sum_sample([attrfx]) Returns a mapper that computes the sum sample of a dataset.
sumofabs_sample() Returns a mapper that returns the sum of absolute values of all samples.

Classes

BinaryFxNode(fx, space, **kwargs) Extract a dataset attribute and call a function with it and the samples.
Dataset(samples[, sa, fa, a]) Generic storage class for datasets with multiple attributes.
FxMapper(axis, fx[, fxargs, uattrs, attrfx]) Apply a custom transformation to (groups of) samples or features.
Mapper(**kwargs) Basic mapper interface definition.
Node([space, postproc]) Common processing object.

NeuroDebian

NITRC-listed