mvpa2.base.collections.UniformLengthCollection

class mvpa2.base.collections.UniformLengthCollection(items=None, length=None)

Container for attributes with the same length.

Methods

clear(() -> None.  Remove all items from D.)
copy(*args, **kwargs)	Create a copy of a collection.
fromkeys(...)	v defaults to None.
get((k[,d]) -> D[k] if k in D, ...)
has_key((k) -> True if D has a key k, else False)
items(() -> list of D’s (key, value) pairs, ...)
iteritems(() -> an iterator over the (key, ...)
iterkeys(() -> an iterator over the keys of D)
itervalues(...)
keys(() -> list of D’s keys)
match(d[, strict])	Given a dictionary describing selection, return mask for matching items
pop((k[,d]) -> v, ...)	If key is not found, d is returned if given, otherwise KeyError is raised
popitem(() -> (k, v), ...)	2-tuple; but raise KeyError if D is empty.
set_length_check(value)	Parameters:
setdefault((k[,d]) -> D.get(k,d), ...)
update(source[, copyvalues, memo])	Parameters:
values(() -> list of D’s values)
viewitems(...)
viewkeys(...)
viewvalues(...)

Parameters:

length : int

When adding items to the collection, they are checked if the have this length.

Methods

clear(() -> None.  Remove all items from D.)
copy(*args, **kwargs)	Create a copy of a collection.
fromkeys(...)	v defaults to None.
get((k[,d]) -> D[k] if k in D, ...)
has_key((k) -> True if D has a key k, else False)
items(() -> list of D’s (key, value) pairs, ...)
iteritems(() -> an iterator over the (key, ...)
iterkeys(() -> an iterator over the keys of D)
itervalues(...)
keys(() -> list of D’s keys)
match(d[, strict])	Given a dictionary describing selection, return mask for matching items
pop((k[,d]) -> v, ...)	If key is not found, d is returned if given, otherwise KeyError is raised
popitem(() -> (k, v), ...)	2-tuple; but raise KeyError if D is empty.
set_length_check(value)	Parameters:
setdefault((k[,d]) -> D.get(k,d), ...)
update(source[, copyvalues, memo])	Parameters:
values(() -> list of D’s values)
viewitems(...)
viewkeys(...)
viewvalues(...)

attr_length

Uniform length of all attributes in a collection

copy(*args, **kwargs)

Create a copy of a collection.

By default this is going to return a deep copy of the collection, hence no data would be shared between the original dataset and its copy.

Parameters:

deep : boolean, optional

If False, a shallow copy of the collection is return instead. The copy contains only views of the values.

a : list or None

List of attributes to include in the copy of the dataset. If None all attributes are considered. If an empty list is given, all attributes are stripped from the copy.

memo : dict

Developers only: This argument is only useful if copy() is called inside the __deepcopy__() method and refers to the dict-argument memo in the Python documentation.

match(d, strict=True)

Given a dictionary describing selection, return mask for matching items

Given a dictionary with keys known to the collection, search for item attributes which would satisfy the selection. E.g.

>>> col = UniformLengthCollection({'roi': ['a', 'b', 'c', 'a']})
>>> print col.match({'roi': ['a']})
[ True False False  True]
>>> print col.match({'roi': ['c', 'a']})
[ True False  True  True]

Multiple keys could be specified with desired matching values. Intersection of matchings is returned across different keys:

>>> col = UniformLengthCollection({'roi': ['a', 'b', 'c', 'a'],
...                                'vox': [[1,0], [0,1], [1,0], [0, 1]]})
>>> print col.match({'roi': ['c', 'a'], 'vox': [[0,1]]})
[False False False  True]

Parameters:

d: dict :

Dict describing the selection. Keys must be known to the collection

strict: bool, optional :

If True, absent matching to any specified selection key/value pair would result in ValueError exception. If False, it would allow to not have matches, but if only a single value for a key is given or none of the values match – you will end up with empty selection.

set_length_check(value)

Parameters:

value : int

When adding new items to the collection, they are checked if the have this length.