Multivariate Pattern Analysis in Python

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# mvpa2.measures.base.vstack

`mvpa2.measures.base.``vstack`(datasets)

  Stacks datasets vertically (appending samples).

  Feature attribute collections are merged incrementally, attribute with identical keys overwriting previous ones in the stacked dataset. All datasets must have an identical set of sample attributes (matching keys, not values), otherwise a ValueError will be raised. No dataset attributes from any source dataset will be transferred into the stacked dataset. If all input dataset have common dataset attributes that are also valid for the stacked dataset, they can be moved into the output dataset like this:

      ds_merged = vstack((ds1, ds2, ds3))
      ds_merged.a.update(ds1.a)

  Parameters:

  datasets : tuple

  > Sequence of datasets to be stacked.

  Returns: | AttrDataset (or respective subclass) :

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