Multivariate Pattern Analysis in Python

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# mvpa2.misc.neighborhood

Neighborhood objects

Functions

`array`(object[, dtype, copy, order, subok, ndmin]) | Create an array.
`borrowdoc`(cls[, methodname]) | Return a decorator to borrow docstring from another `cls`.`methodname` It should not be used for __init__ methods of classes derived from ClassWithCollections since __doc__’s of those are handled by the AttributeCollector anyways.
`borrowkwargs`(cls[, methodname, exclude]) | Return a decorator which would borrow docstring for `**kwargs` :Parameters: methodname : None or str Name of the method from which to borrow.
`cartesian_distance`(a, b) | Return Cartesian distance between a and b
`idhash_`(val) | Craft unique id+hash for an object
`is_sequence_type` | isSequenceType(a) – Return True if a has a sequence type, False otherwise.
`scatter_neighborhoods`(neighbor_gen, coords) | Scatter neighborhoods over a coordinate list.

Classes

`CachedQueryEngine`(queryengine) | Provides caching facility for query engines.
`HollowSphere`(radius, inner_radius, **kwargs) | N-Dimensional hypersphere with a hollow internal sphere See parent class `Sphere` for more information.
`IndexQueryEngine`([sorted]) | Provides efficient query engine for discrete spaces.
`QueryEngine`(**kwargs) | Basic class defining interface for querying neighborhood in a dataset Derived classes provide specific implementations possibly with trade-offs between generality and performance.
`QueryEngineInterface` | Very basic class for `QueryEngine`s defining the interface It should not be used directly, but is used to check either we are working with QueryEngine instances ..
`Sphere`(radius[, element_sizes, distance_func]) | N-Dimensional hypersphere.

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