Awesome
This library is abandonned by the original author. A fork is maintained at https://github.com/Lisp-Stat/array-operations.
NOTE 2019-05-16
@bendudson and others have continued maintaining a fork of this library at https://github.com/bendudson/array-operations.
!!! important This is an alpha release. All the code works and unit tests are expected to run perfectly, but the operations are not optimized and the API change.
Introduction
array-operations
is a Common Lisp library that facilitates working
with Common Lisp arrays using syntax and semantics that work well with
the rest of the language.
The library previously available under this name is deprecated, but you can find it here.
A quick tour of the library
Shorthand for frequently used Common Lisp array functions
The library defines the following short function names that are synomyms for Common Lisp operations:
array-operations | Common Lisp |
---|---|
size | array-total-size |
rank | array-rank |
dim | array-dimension |
dims | array-dimensions |
nrow | number of rows in matrix |
ncol | number of columns in matrix |
The array-operations
package has the nickname ao
, so you can use,
for example, (ao:size my-array)
without use
'ing the package.
Displaced arrays for fun and profit
displaced array n. an array which has no storage of its own, but which is instead indirected to the storage of another array, called its target, at a specified offset, in such a way that any attempt to access the displaced array implicitly references the target array. (CLHS Glossary)
Displaced arrays are one of the niftiest features of Common Lisp. When an array is displaced to another array, it shares structure with (part of) that array. The two arrays do not need to have the same dimensions, in fact, the dimensions do not be related at all as long as the displaced array fits inside the original one. The row-major index of the former in the latter is called the offset of the displacement.
Displaced arrays are usually constructed using make-array
, but this
library also provides displace
for that purpose:
(defparameter *a* #2A((1 2 3) (4 5 6)))
(ao:displace *a* 2 1) ; => #(2 3)
flatten
displaces to a row-major array:
(ao:flatten *a*) ; => #(1 2 3 4 5 6)
The real fun starts with split
, which splits off subarrays nested
within a given axis:
(ao:split *a* 1) ; => #(#(1 2 3) #(4 5 6))
(defparameter *b* #3A(((0 1) (2 3))
((4 5) (6 7))))
(ao:split *b* 0) ; => #3A(((0 1) (2 3)) ((4 5) (6 7)))
(ao:split *b* 1) ; => #(#2A((0 1) (2 3)) #2A((4 5) (6 7)))
(ao:split *b* 2) ; => #2A((#(0 1) #(2 3)) (#(4 5) #(6 7)))
(ao:split *b* 3) ; => #3A(((0 1) (2 3)) ((4 5) (6 7)))
Note how splitting at 0
and the rank of the array returns the array
itself.
Now consider sub
, which returns a specific array, composed of the
elements that would start with given subscripts:
(ao:sub *b* 0) ; => #2A((0 1) (2 3))
(ao:sub *b* 0 1) ; => #(2 3)
(ao:sub *b* 0 1 0) ; => 2
There is also a (setf sub)
function.
partition
returns a consecutive chunk of an array separated along its
first subscript:
(ao:partition #2A((0 1)
(2 3)
(4 5)
(6 7)
(8 9))
1 3) ; => #2A((2 3) (4 5))
and also has a (setf partition)
pair.
combine
is the opposite of split
:
(ao:combine #(#(0 1) #(2 3))) ; => #2A((0 1) (2 3))
subvec
returns a displaced subvector:
(ao:subvec #(0 1 2 3 4) 2 4) ; => #(2 3)
There is also a (setf subvec)
function, which is like (setf subseq)
except for demanding matching lengths.
Finally, reshape
can be used to displace arrays into a different
shape:
(ao:reshape *a* '(3 2)) ; => #2A((1 2) (3 4) (5 6))
You can use t
for one of the dimensions, to be filled in
automatically:
(ao:reshape *b* '(1 t)) ; => #2A((0 1 2 3 4 5 6 7))
reshape-col
and reshape-row
reshape your array into a column or row
matrix, respectively.
Dimension specifications
Functions in the library accept the following in place of dimensions:
- a list of dimensions (as for
make-array
), - a positive integer, which is used as a single-element list,
- another array, the dimensions of which are used.
The last one allows you to specify dimensions with other arrays. For
example, to reshape an array a1
to look like a2
, you can use
(ao:reshape a1 a2)
instead of the longer form
(ao:reshape a1 (ao:dims a2))
Array creation and transformations
When the resulting element type cannot be inferred, functions that
create and transform arrays are provided in pairs: one of these will
allow you to specify the array-element-type of the result, while the
other assumes it is t
. The former ends with a *
, and the
element-type
is always its first argument. I give examples for the
versions without *
, use the other when you are optimizing your code
and you are sure you can constrain to a given element-type.
Element traversal order of these functions is unspecified. The reason for this is that the library may use parallel code in the future, so it is unsafe to rely on a particular element traversal order.
generate
(and generate*
) allow you to generate arrays using
functions.
(ao:generate (lambda () (random 10)) 3) ; => #(6 9 5)
(ao:generate #'identity '(2 3) :position) ; => #2A((0 1 2) (3 4 5))
(ao:generate #'identity '(2 2) :subscripts)
;; => #2A(((0 0) (0 1)) ((1 0) (1 1)))
(ao:generate #'cons '(2 2) :position-and-subscripts)
;; => #2A(((0 0 0) (1 0 1)) ((2 1 0) (3 1 1)))
Depending on the last argument, the function will be called with the (row-major) position, the subscripts, both, or no argument.
permute
can permutate subscripts (you can also invert, complement, and
complete permutations, look at the docstring and the unit tests).
Transposing is a special case of permute:
(ao:permute '(0 1) *a*) ; => #2A((1 2 3) (4 5 6))
each
applies a function to its (array) arguments elementwise:
(ao:each #'+ #(0 1 2) #(2 3 5)) ; => #(2 4 7)
The semantics of margin
are more difficult to explain, so perhaps an
example will be more useful. Suppose that you want to calculate column
sums in a matrix. You could permute
(transpose) the matrix, split
its subarrays at rank one (so you get a vector for each row), and apply
the function that calculates the sum. margin
automates that for you:
(ao:margin (lambda (column)
(reduce #'+ column))
#2A((0 1)
(2 3)
(5 7)) 0) ; => #(7 11)
But the function is much more general than this: the arguments inner
and outer
allow arbitrary permutations before splitting.
Finally, recycle
allows you to recycle arrays along inner and outer
dimensions:
(ao:recycle #(2 3) :inner 2 :outer 4)
; => #3A(((2 2) (3 3)) ((2 2) (3 3)) ((2 2) (3 3)) ((2 2) (3 3)))
Scalars as 0-dimensional arrays
Library functions treat non-array objects as if they were equivalent to
0-dimensional arrays: for example, (ao:split array (rank array))
returns an array that effectively equivalent (eq
) to array. Another
example is recycle
:
(ao:recycle 4 :inner '(2 2)) ; => #2A((4 4) (4 4))
Stacking
You can also stack compatible arrays along any axis:
(defparameter *a1* #(0 1 2))
(defparameter *a2* #(3 5 7))
(ao:stack 0 *a1* *a2*) ; => #(0 1 2 3 5 7)
(ao:stack 1
(ao:reshape-col *a1*)
(ao:reshape-col *a2*)) ; => #2A((0 3) (1 5) (2 7))
Shared structure
Rules for that aren't finalized yet, see the source. Suggestions are welcome.
To-do list
benchmark and optimize walk-subscripts and walk-subscripts-list
- instead of allocating a new list each time, could map into a preallocated one