mvpa2.mappers.fx

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

Functions

absolute_features()	Returns a mapper that converts features into absolute values.
argsort(seq[, reverse])	Return indices to get sequence sorted
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.
merge2first(attrs)	Compress a sequence by discard all but the first element
subtract_mean_feature([attrfx])	Subtract mean of features across samples.
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.
BinomialProportionCI(**kwargs)	Compute binomial proportion confidence intervals
FxMapper(axis, fx[, fxargs, uattrs, attrfx, ...])	Apply a custom transformation to (groups of) samples or features.
MeanRemoval([in_place])	Subtract sample mean from features.