This content refers to the previous stable release of PyMVPA.
Please visit
www.pymvpa.org for the most
recent version of PyMVPA and its documentation.
mappers.array
Module: mappers.array
Inheritance diagram for mvpa.mappers.array:
Data mapper
-
class mvpa.mappers.array.DenseArrayMapper(mask=None, metric=None, distance_function=<function cartesianDistance at 0x66a4e60>, elementsize=None, shape=None, **kwargs)
Bases: mvpa.mappers.mask.MaskMapper
Mapper for equally spaced dense arrays.
See also
Please refer to the documentation of the base class for more information:
MaskMapper
Initialize DenseArrayMapper
Parameters: |
- mask (array) – an array in the original dataspace and its nonzero elements are
used to define the features included in the dataset. alternatively,
the shape argument can be used to define the array dimensions.
- metric (Metric) – Corresponding metric for the space. No attempt is made to
determine whether a certain metric is reasonable for this
mapper. If metric is None – DescreteMetric
is constructed that assumes an equal (1) spacing of all mask
elements with a distance_function given as a parameter listed
below.
- distance_function (functor) – Distance function to use as the parameter to
DescreteMetric if metric is not specified,
- elementsize (list or scalar) – Determines spacing within DescreteMetric. If it is given as a
scalar, corresponding value is assigned to all dimensions, which
are found within mask
- shape (tuple) – The shape of the array to be mapped. If shape is provided instead
of mask, a full mask (all True) of the desired shape is
constructed. If shape is specified in addition to mask, the
provided mask is extended to have the same number of dimensions.
|
Note : | parameters elementsize and distance_function are relevant
only if metric is None
|