rlike¶
Overview¶
The package proposes R features for a pure Python context, that is without an embedded R running.
Containers¶
The module contains data collection-type data structures.
OrdDict
and TaggedList
are structures
with which contained items/elements can be tagged.
The module can be imported as follows:
>>> import rpy2.rlike.container as rlc
OrdDict¶
The OrdDict
proposes an implementation of what is
sometimes referred to in Python as an ordered dictionnary, with a
particularity: a key None
means that, although an item has a rank
and can be retrieved from that rank, it has no “name”.
In the hope of simplifying its usage, the API for an ordered dictionnary in PEP 372 was implemented. An example of usage is:
>>> x = (('a', 123), ('b', 456), ('c', 789))
>>> nl = rlc.OrdDict(x)
>>> nl['a']
123
>>> nl.index('a')
0
Not all elements have to be named, and specifying a key value equal to None indicates a value for which no name is associated.
>>> nl[None] = 'no name'
The Python docstring for the class is:
- class rpy2.rlike.container.OrdDict(c: Iterable[Tuple[Optional[str], Any]] = [])[source]¶
Implements the Ordered Dict API defined in PEP 372. When odict becomes part of collections, this class should inherit from it rather than from dict.
This class differs a little from the Ordered Dict proposed in PEP 372 by the fact that: not all elements have to be named. None as a key value means an absence of name for the element.
TaggedList¶
A TaggedList
is a Python list
in which each item has
an associated tag.
This is similar to named vectors in R.
>>> tl = rlc.TaggedList([1,2,3])
>>> tl
[1, 2, 3]
>>> tl.tags()
(None, None, None)
>>> tl.settag(0, 'a')
>>> tl.tags()
('a', None, None)
>>> tl = rlc.TaggedList([1,2,3], tags=('a', 'b', 'c'))
>>> tl
[1, 2, 3]
>>> tl.tags()
('a', 'b', 'c')
>>> tl.settag(2, 'a')
>>> tl.tags()
('a', 'b', 'a')
>>> it = tl.iterontag('a')
>>> [x for x in it]
[1, 3]
>>> [(t, sum([i for i in tl.iterontag(t)])) for t in set(tl.itertags())]
[('a', 4), ('b', 2)]
The Python docstring for the class is:
- class rpy2.rlike.container.TaggedList(seq, tags=None)[source]¶
A list for which each item has a ‘tag’.
- Parameters
l – list
tag – optional sequence of tags
- extend(iterable)[source]¶
Extend the list with an iterable object.
- Parameters
iterable – iterable object
Tools for working with sequences¶
Tools for working with objects implementing the sequence protocol can be found here.
- rpy2.rlike.functional.tapply(seq, tag, fun)[source]¶
Apply the function fun to the items in seq, grouped by the tags defined in tag.
- Parameters
seq – sequence
tag – any sequence of tags
fun – function
- Return type
>>> import rpy2.rlike.functional as rlf
>>> rlf.tapply((1,2,3), ('a', 'b', 'a'), sum)
[('a', 4), ('b', 2)]
TaggedList
objects can be used with their tags
(although more flexibility can be achieved using their
method iterontags()
):
>>> import rpy2.rlike.container as rlc
>>> tl = rlc.TaggedList([1, 2, 3], tags = ('a', 'b', 'a'))
>>> rlf.tapply(tl, tl.tags(), sum)
[('a', 4), ('b', 2)]
Indexing¶
Much of the R-style indexing can be achieved with Python’s list comprehension:
>>> l = ('a', 'b', 'c')
>>> l_i = (0, 2)
>>> [l[i] for i in l_i]
['a', 'c']
In R, negative indexes mean that values should be excluded. Again, list comprehension can be used (although this is not the most efficient way):
>>> l = ('a', 'b', 'c')
>>> l_i = (-1, -2)
>>> [x for i, x in enumerate(l) if -i not in l_i]
['a']
- rpy2.rlike.indexing.order(seq, cmp=default_cmp, reverse=False)[source]¶
Give the order in which to take the items in the sequence seq and have them sorted. The optional function cmp should return +1, -1, or 0.
- Parameters
seq – sequence
cmp – function
reverse – boolean
- Return type
list of integers
>>> import rpy2.rlike.indexing as rli
>>> x = ('a', 'c', 'b')
>>> o = rli.order(x)
>>> o
[0, 2, 1]
>>> [x[i] for i in o]
['a', 'b', 'c']