mvpa2.datasets.baseΒΆ
PyMVPA’s common Dataset container.
Functions
| idhash_(val) | Craft unique id+hash for an object |
| mask_mapper([mask, shape, space]) | Factory method to create a chain of Flatten+StaticFeatureSelection Mappers :Parameters: mask : None or array an array in the original dataspace and its nonzero elements are used to define the features included in the dataset. |
Classes
| AttrDataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |
| ChainMapper(nodes, **kwargs) | Class that amends ChainNode with a mapper-like interface. |
| Dataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |
| DatasetAttribute([value, name, doc, length]) | Dataset attribute .. |
| DatasetAttributesCollection([items]) | Container for attributes of datasets (i.e. |
| FeatureAttribute([value, name, doc, length]) | Per feature attribute in a dataset .. |
| FeatureAttributesCollection([items, length]) | Container for attributes of features .. |
| FlattenMapper([shape, maxdims]) | Reshaping mapper that flattens multidimensional arrays into 1D vectors. |
| HollowSamples([shape, sid, fid, dtype]) | Samples container that doesn’t store samples. |
| SampleAttribute([value, name, doc, length]) | Per sample attribute in a dataset .. |
| SampleAttributesCollection([items, length]) | Container for attributes of samples (i.e. |
| StaticFeatureSelection(slicearg[, dshape, ...]) | Feature selection by static slicing argument. |
