MiniAgda-0.2016.12.19: src/SparseMatrix.hs
{- | Sparse matrices. Original: Agda.Termination.SparseMatrix
We assume the matrices to be very sparse, so we just implement them as
sorted association lists.
-}
module SparseMatrix
( -- * Basic data types
Matrix(M)
, matrixInvariant
, Size(..)
, sizeInvariant
, MIx (..)
, mIxInvariant
-- * Generating and creating matrices
, fromLists
, fromIndexList
, toLists
-- , matrix
-- , matrixUsingRowGen
-- * Combining and querying matrices
, size
, square
, isEmpty
, isSingleton
, SparseMatrix.all, SparseMatrix.any
, add, intersectWith, SparseMatrix.zip
, mul
, transpose
, diagonal
-- * Modifying matrices
, addRow
, addColumn
-- * Tests
) where
import Data.Array
import qualified Data.List as List
import Data.Monoid
-- import Test.QuickCheck
import Semiring (HasZero(..), SemiRing, Semiring)
import qualified Semiring as Semiring
------------------------------------------------------------------------
-- Basic data types
-- | This matrix type is used for tests.
type TM = Matrix Integer Integer
-- | Size of a matrix.
data Size i = Size { rows :: i, cols :: i }
deriving (Eq, Ord, Show)
sizeInvariant :: (Ord i, Num i) => Size i -> Bool
sizeInvariant sz = rows sz >= 0 && cols sz >= 0
{-
instance (Arbitrary i, Integral i) => Arbitrary (Size i) where
arbitrary = do
r <- natural
c <- natural
return $ Size { rows = fromInteger r, cols = fromInteger c }
instance CoArbitrary i => CoArbitrary (Size i) where
coarbitrary (Size rs cs) = coarbitrary rs . coarbitrary cs
prop_Arbitrary_Size :: Size Integer -> Bool
prop_Arbitrary_Size = sizeInvariant
-}
-- | Converts a size to a set of bounds suitable for use with
-- the matrices in this module.
toBounds :: Num i => Size i -> (MIx i, MIx i)
toBounds sz = (MIx { row = 1, col = 1 }, MIx { row = rows sz, col = cols sz })
-- | Type of matrix indices (row, column).
data MIx i = MIx { row, col :: i }
deriving (Eq, Show, Ix, Ord)
{-
instance (Arbitrary i, Integral i) => Arbitrary (MIx i) where
arbitrary = do
r <- positive
c <- positive
return $ MIx { row = r, col = c }
instance CoArbitrary i => CoArbitrary (MIx i) where
coarbitrary (MIx r c) = coarbitrary r . coarbitrary c
-}
-- | No nonpositive indices are allowed.
mIxInvariant :: (Ord i, Num i) => MIx i -> Bool
mIxInvariant i = row i >= 1 && col i >= 1
prop_Arbitrary_MIx :: MIx Integer -> Bool
prop_Arbitrary_MIx = mIxInvariant
-- | Type of matrices, parameterised on the type of values.
data Matrix i b = M { size :: Size i, unM :: [(MIx i, b)] }
deriving (Ord)
instance (Ord i, Eq a, HasZero a) => Eq (Matrix i a) where
m1 == m2 = size m1 == size m2 &&
SparseMatrix.all (uncurry (==)) (SparseMatrix.zip m1 m2)
instance Functor (Matrix i) where
fmap f (M sz m) = M sz (map (\ (i,a) -> (i, f a)) m)
matrixInvariant :: (Num i, Ix i) => Matrix i b -> Bool
matrixInvariant m = List.all (\ (MIx i j, b) -> 1 <= i && i <= rows sz
&& 1 <= j && j <= cols sz) (unM m)
&& strictlySorted (MIx 0 0) (unM m)
&& sizeInvariant sz
where sz = size m
-- matrix indices are lexicographically sorted with no duplicates
-- Ord MIx should be the lexicographic one already (Haskell report)
strictlySorted :: (Ord i) => i -> [(i, b)] -> Bool
strictlySorted i [] = True
strictlySorted i ((i', b) : l) = i < i' && strictlySorted i' l
{-
strictlySorted (MIx i j) [] = True
strictlySorted (MIx i j) ((MIx i' j', b) : l) =
(i < i' || i == i' && j < j' ) && strictlySorted (MIx i' j') b
-}
instance (Ord i, Integral i, Enum i, Show i, Show b, HasZero b) => Show (Matrix i b) where
showsPrec _ m =
showString "SparseMatrix.fromLists " . shows (size m) .
showString " " . shows (toLists m)
{-
instance (Integral i, HasZero b, Pretty b) =>
Pretty (Matrix i b) where
pretty = vcat . map (hsep . map pretty) . toLists
instance (Arbitrary i, Num i, Integral i, Arbitrary b, HasZero b)
=> Arbitrary (Matrix i b) where
arbitrary = matrix =<< arbitrary
instance (Ord i, Integral i, Enum i, CoArbitrary b, HasZero b) => CoArbitrary (Matrix i b) where
coarbitrary m = coarbitrary (toLists m)
prop_Arbitrary_Matrix :: TM -> Bool
prop_Arbitrary_Matrix = matrixInvariant
-}
------------------------------------------------------------------------
-- Generating and creating matrices
-- | Generates a matrix of the given size, using the given generator
-- to generate the rows.
{-
matrixUsingRowGen :: (Arbitrary i, Integral i, Arbitrary b, HasZero b)
=> Size i
-> (i -> Gen [b])
-- ^ The generator is parameterised on the size of the row.
-> Gen (Matrix i b)
matrixUsingRowGen sz rowGen = do
rows <- vectorOf (fromIntegral $ rows sz) (rowGen $ cols sz)
return $ fromLists sz rows
-}
-- | Generates a matrix of the given size.
{-
matrix :: (Arbitrary i, Integral i, Arbitrary b, HasZero b)
=> Size i -> Gen (Matrix i b)
matrix sz = matrixUsingRowGen sz (\n -> vectorOf (fromIntegral n) arbitrary)
prop_matrix sz = forAll (matrix sz :: Gen TM) $ \m ->
-- matrixInvariant m &&
size m == sz
-}
-- | Constructs a matrix from a list of (index, value)-pairs.
-- compareElt = (\ (i,_) (j,_) -> compare i j)
-- normalize = filter (\ (i,b) -> b /= zeroElement)
fromIndexList :: (Ord i, HasZero b) => Size i -> [(MIx i, b)] -> Matrix i b
fromIndexList sz = M sz . List.sortBy (\ (i,_) (j,_) -> compare i j) . filter (\ (i,b) -> b /= zeroElement)
prop_fromIndexList :: TM -> Bool
prop_fromIndexList m = matrixInvariant m' && m' == m
where vs = unM m
m' = fromIndexList (size m) vs
-- | @'fromLists' sz rs@ constructs a matrix from a list of lists of
-- values (a list of rows).
--
-- Precondition: @'length' rs '==' 'rows' sz '&&' 'all' (('==' 'cols' sz) . 'length') rs@.
fromLists :: (Ord i, Num i, Enum i, HasZero b) => Size i -> [[b]] -> Matrix i b
fromLists sz bs = fromIndexList sz $
List.zip ([ MIx i j | i <- [1..rows sz] , j <- [1..cols sz]]) (concat bs)
-- | Converts a sparse matrix to a sparse list of rows
toSparseRows :: (Num i, Enum i, Eq i) => Matrix i b -> [(i,[(i,b)])]
toSparseRows m = aux 1 [] (unM m)
where aux i' [] [] = []
aux i' row [] = [(i', reverse row)]
aux i' row ((MIx i j, b) : m)
| i' == i = aux i' ((j,b):row) m
| otherwise = (i', reverse row) : aux i [(j,b)] m
-- sparse vectors cannot have two entries in one column
blowUpSparseVec :: (Eq i, Ord i, Num i, Enum i, Show i) => b -> i -> [(i,b)] -> [b]
blowUpSparseVec zero n l = aux 1 l
where aux i [] | i > n = []
| otherwise = zero : aux (i+1) []
aux i ((j,b):l) | i <= n && j == i = b : aux (succ i) l
aux i ((j,b):l) | i <= n && j >= i = zero : aux (succ i) ((j,b):l)
aux i l = error $ "blowUpSparseVec (n = " ++ show n ++ ") aux i=" ++ show i ++ " j=" ++ show (fst (head l)) ++ " length l = " ++ show (length l)
-- __IMPOSSIBLE__
-- | Converts a matrix to a list of row lists.
toLists :: (Ord i, Integral i, Enum i, HasZero b, Show i) => Matrix i b -> [[b]]
toLists m = blowUpSparseVec emptyRow (rows sz) $
map (\ (i,r) -> (i, blowUpSparseVec zeroElement (cols sz) r)) $ toSparseRows m
-- [ [ maybe zeroElement id $ lookup (MIx { row = r, col = c }) (unM m)
-- | c <- [1 .. cols sz] ] | r <- [1 .. rows sz] ]
where sz = size m
emptyRow = take (fromIntegral (cols sz)) $ repeat zeroElement
prop_fromLists_toLists :: TM -> Bool
prop_fromLists_toLists m = fromLists (size m) (toLists m) == m
------------------------------------------------------------------------
-- Combining and querying matrices
-- | The size of a matrix.
{-
size :: Ix i => Matrix i b -> Size i
size m = Size { rows = row b, cols = col b }
where (_, b) = bounds $ unM m
-}
prop_size :: TM -> Bool
prop_size m = sizeInvariant (size m)
prop_size_fromIndexList :: Size Int -> Bool
prop_size_fromIndexList sz =
size (fromIndexList sz ([] :: [(MIx Int, Integer)])) == sz
-- | 'True' iff the matrix is square.
square :: Ix i => Matrix i b -> Bool
square m = rows (size m) == cols (size m)
-- | Returns 'True' iff the matrix is empty.
isEmpty :: (Num i, Ix i) => Matrix i b -> Bool
isEmpty m = rows sz <= 0 || cols sz <= 0
where sz = size m
-- | Returns 'Just b' iff it is a 1x1 matrix with just one entry 'b'.
isSingleton :: (Num i, Ix i, HasZero b) => Matrix i b -> Maybe b
isSingleton m = if (rows sz == 1 || cols sz == 1) then
case unM m of
[(_,b)] -> Just b
[] -> Just zeroElement
else Nothing
where sz = size m
-- | Transposition
transposeSize (Size { rows = n, cols = m }) = Size { rows = m, cols = n }
transpose m = M { size = transposeSize (size m)
, unM = List.sortBy (\ (i,a) (j,b) -> compare i j) $
map (\(MIx i j, b) -> (MIx j i, b)) $ unM m }
all :: (a -> Bool) -> Matrix i a -> Bool
all p m = List.all (\ (i,a) -> p a) (unM m)
any :: (a -> Bool) -> Matrix i a -> Bool
any p m = List.any (\ (i,a) -> p a) (unM m)
-- | @'zip' m1 m2@ zips @m1@ and @m2@.
--
-- Precondition: @'size' m1 == 'size' m2@.
zip :: (Ord i, HasZero a) => Matrix i a -> Matrix i a -> Matrix i (a,a)
zip m1 m2 = M (size m1) $ zips (unM m1) (unM m2) where
zips [] m = map (\ (i,b) -> (i,(zeroElement,b))) m
zips l [] = map (\ (i,a) -> (i,(a,zeroElement))) l
zips l@((i,a):l') m@((j,b):m')
| i < j = (i,(a,zeroElement)) : zips l' m
| i > j = (j,(zeroElement,b)) : zips l m'
| otherwise = (i,(a,b)) : zips l' m'
-- | @'add' (+) m1 m2@ adds @m1@ and @m2@. Uses @(+)@ to add values.
--
-- Precondition: @'size' m1 == 'size' m2@.
add :: (Ord i) => (a -> a -> a) -> Matrix i a -> Matrix i a -> Matrix i a
add plus m1 m2 = M (size m1) $ mergeAssocWith plus (unM m1) (unM m2)
-- | assoc list union
mergeAssocWith :: (Ord i) => (a -> a -> a) -> [(i,a)] -> [(i,a)] -> [(i,a)]
mergeAssocWith f [] m = m
mergeAssocWith f l [] = l
mergeAssocWith f l@((i,a):l') m@((j,b):m')
| i < j = (i,a) : mergeAssocWith f l' m
| i > j = (j,b) : mergeAssocWith f l m'
| otherwise = (i, f a b) : mergeAssocWith f l' m'
-- | @'intersectWith' f m1 m2@ build the pointwise conjunction @m1@ and @m2@.
-- Uses @f@ to combine non-zero values.
--
-- Precondition: @'size' m1 == 'size' m2@.
intersectWith :: (Ord i) => (a -> a -> a) -> Matrix i a -> Matrix i a -> Matrix i a
intersectWith f m1 m2 = M (size m1) $ interAssocWith f (unM m1) (unM m2)
-- | assoc list intersection
interAssocWith :: (Ord i) => (a -> a -> a) -> [(i,a)] -> [(i,a)] -> [(i,a)]
interAssocWith f [] m = []
interAssocWith f l [] = []
interAssocWith f l@((i,a):l') m@((j,b):m')
| i < j = interAssocWith f l' m
| i > j = interAssocWith f l m'
| otherwise = (i, f a b) : interAssocWith f l' m'
{-
prop_add sz =
forAll (three (matrix sz :: Gen TM)) $ \(m1, m2, m3) ->
let m' = add (+) m1 m2 in
associative (add (+)) m1 m2 m3 &&
commutative (add (+)) m1 m2 &&
matrixInvariant m' &&
size m' == size m1
-}
-- | @'mul' semiring m1 m2@ multiplies @m1@ and @m2@. Uses the
-- operations of the semiring @semiring@ to perform the
-- multiplication.
--
-- Precondition: @'cols' ('size' m1) == rows ('size' m2)@.
{- mul A B works as follows:
* turn A into a list of sparse rows and the transposed B as well
* form the crossproduct using the inner vector product to compute els
* the inner vector product is summing up
after intersecting with the muliplication op of the semiring
-}
mul :: (Enum i, Num i, Ix i, Eq a)
=> Semiring a -> Matrix i a -> Matrix i a -> Matrix i a
mul semiring m1 m2 = M (Size { rows = rows (size m1), cols = cols (size m2) }) $
filter (\ (i,b) -> b /= Semiring.zero semiring) $
[ (MIx i j, foldl (Semiring.add semiring) (Semiring.zero semiring) $
map snd $ interAssocWith (Semiring.mul semiring) v w)
| (i,v) <- toSparseRows m1
, (j,w) <- toSparseRows $ transpose m2 ]
{-
prop_mul sz =
sized $ \n -> resize (n `div` 2) $
forAll (two natural) $ \(c2, c3) ->
forAll (matrix sz :: Gen TM) $ \m1 ->
forAll (matrix (Size { rows = cols sz, cols = c2 })) $ \m2 ->
forAll (matrix (Size { rows = c2, cols = c3 })) $ \m3 ->
let m' = mult m1 m2 in
associative mult m1 m2 m3 &&
matrixInvariant m' &&
size m' == Size { rows = rows sz, cols = c2 }
where mult = mul Semiring.integerSemiring
-}
-- | @'diagonal' m@ extracts the diagonal of @m@.
--
-- Precondition: @'square' m@.
diagonal :: (Enum i, Num i, Ix i, Show i, HasZero b) => Matrix i b -> [b]
diagonal m = blowUpSparseVec zeroElement (rows sz) $
map (\ ((MIx i j),b) -> (i,b)) $ filter (\ ((MIx i j),b) -> i==j) (unM m)
where sz = size m
{-
diagonal :: (Enum i, Num i, Ix i, HasZero b) => Matrix i b -> Array i b
diagonal m = listArray (1, rows sz) $ blowUpSparseVec zeroElement (rows sz) $
map (\ ((MIx i j),b) -> (i,b)) $ filter (\ ((MIx i j),b) -> i==j) (unM m)
where sz = size m
-}
{-
prop_diagonal =
forAll natural $ \n ->
forAll (matrix (Size n n) :: Gen TM) $ \m ->
bounds (diagonal m) == (1, n)
-}
------------------------------------------------------------------------
-- Modifying matrices
-- | @'addColumn' x m@ adds a new column to @m@, after the columns
-- already existing in the matrix. All elements in the new column get
-- set to @x@.
addColumn :: (Num i, HasZero b) => b -> Matrix i b -> Matrix i b
addColumn x m | x == zeroElement = m { size = (size m) { cols = cols (size m) + 1 }}
-- | otherwise = __IMPOSSIBLE__
{-
prop_addColumn :: TM -> Bool
prop_addColumn m =
matrixInvariant m'
&&
map init (toLists m') == toLists m
where
m' = addColumn zeroElement m
-}
-- | @'addRow' x m@ adds a new row to @m@, after the rows already
-- existing in the matrix. All elements in the new row get set to @x@.
addRow :: (Num i, HasZero b) => b -> Matrix i b -> Matrix i b
addRow x m | x == zeroElement = m { size = (size m) { rows = rows (size m) + 1 }}
-- | otherwise = __IMPOSSIBLE__
prop_addRow :: TM -> Bool
prop_addRow m =
matrixInvariant m'
&&
init (toLists m') == toLists m
where
m' = addRow zeroElement m
------------------------------------------------------------------------
-- Zipping (assumes non-empty matrices)
{- use mergeAssocList or interAssocList instead
zipWith :: (a -> b -> c) ->
Matrix Integer a -> Matrix Integer b -> Matrix Integer c
zipWith f m1 m2
= fromLists (Size { rows = toInteger $ length ll,
cols = toInteger $ length (head ll) }) ll
where ll = List.zipWith (List.zipWith f) (toLists m1) (toLists m2)
-}