To provide the most recent news and documentation www.pymvpa.org reflects the
development 2.0 series (renamed 0.6 series) of PyMVPA. If you are interested in the
documentation of the previous stable 0.4 series of PyMVPA, please
class mvpa2.datasets.base.HollowSamples(shape=None, sid=None, fid=None, dtype=<type 'float'>)¶
Samples container that doesn’t store samples.
The purpose of this class is to provide an object that can be used as
samples in a Dataset, without having actual samples. Instead of storing
multiple samples it only maintains a IDs for samples and features it
pretends to contain.
Using this class in a dataset in conjuction will actual attributes, will
yield a lightweight dataset that is compatible with the majority of all
mappers and can be used to ‘simulate’ processing by mappers. The class
offers acces to the sample and feature IDs via its sid and fid
shape : 2-tuple or None
Shape of the pretend-sample array (nsamples x nfeatures). Can be
left out if both sid and fid are provided.
sid : 1d-array or None
Vector of sample IDs. Can be left out if shape is provided.
fid : 1d-array or None
Vector of feature IDs. Can be left out if shape is provided.