-- Hoogle documentation, generated by Haddock
-- See Hoogle, http://www.haskell.org/hoogle/
-- | n-dimensional arrays
--
-- n-dimensional arrays founded on numhask.
@package numhask-array
@version 0.7.0
-- | Functions for manipulating shape. The module tends to supply
-- equivalent functionality at type-level and value-level with functions
-- of the same name (except for capitalization).
module NumHask.Array.Shape
-- | The Shape type holds a [Nat] at type level and the equivalent [Int] at
-- value level. Using [Int] as the index for an array nicely represents
-- the practical interests and constraints downstream of this high-level
-- API: densely-packed numbers (reals or integrals), indexed and layered.
newtype Shape (s :: [Nat])
Shape :: [Int] -> Shape
[shapeVal] :: Shape -> [Int]
class HasShape s
toShape :: HasShape s => Shape s
type family (a :: [k]) ++ (b :: [k]) :: [k]
type family (a :: [k]) !! (b :: Nat) :: k
type family Take (n :: Nat) (a :: [k]) :: [k]
type family Drop (n :: Nat) (a :: [k]) :: [k]
type Reverse (a :: [k]) = ReverseGo a '[]
type family ReverseGo (a :: [k]) (b :: [k]) :: [k]
type family Filter (r :: [Nat]) (xs :: [Nat]) (i :: Nat)
-- | Number of dimensions
rank :: [a] -> Int
type family Rank (s :: [a]) :: Nat
-- | The shape of a list of element indexes
ranks :: [[a]] -> [Int]
type family Ranks (s :: [[a]]) :: [Nat]
-- | Number of elements
size :: [Int] -> Int
type family Size (s :: [Nat]) :: Nat
-- | dimension i is the i'th dimension of a Shape
dimension :: [Int] -> Int -> Int
type family Dimension (s :: [Nat]) (i :: Nat) :: Nat
-- | convert from n-dim shape index to a flat index
--
--
-- >>> flatten [2,3,4] [1,1,1]
-- 17
--
--
--
-- >>> flatten [] [1,1,1]
-- 0
--
flatten :: [Int] -> [Int] -> Int
-- | convert from a flat index to a shape index
--
--
-- >>> shapen [2,3,4] 17
-- [1,1,1]
--
shapen :: [Int] -> Int -> [Int]
-- | minimum value in a list
minimum :: [Int] -> Int
type family Minimum (s :: [Nat]) :: Nat
-- | checkIndex i n checks if i is a valid index of a list of
-- length n
checkIndex :: Int -> Int -> Bool
type family CheckIndex (i :: Nat) (n :: Nat) :: Bool
-- | checkIndexes is n check if is are valid indexes of a
-- list of length n
checkIndexes :: [Int] -> Int -> Bool
type family CheckIndexes (i :: [Nat]) (n :: Nat) :: Bool
-- | addIndex s i d adds a new dimension to shape s at
-- position i
--
--
-- >>> addIndex [2,4] 1 3
-- [2,3,4]
--
addIndex :: [Int] -> Int -> Int -> [Int]
type AddIndex s i d = Take i s ++ (d : Drop i s)
-- | drop the i'th dimension from a shape
--
--
-- >>> dropIndex [2, 3, 4] 1
-- [2,4]
--
dropIndex :: [Int] -> Int -> [Int]
type DropIndex s i = Take i s ++ Drop (i + 1) s
-- | convert a list of position that references a final shape to one that
-- references positions relative to an accumulator. Deletions are from
-- the left and additions are from the right.
--
-- deletions
--
--
-- >>> posRelative [0,1]
-- [0,0]
--
--
-- additions
--
--
-- >>> reverse (posRelative (reverse [1,0]))
-- [0,0]
--
posRelative :: [Int] -> [Int]
type family PosRelative (s :: [Nat])
type family PosRelativeGo (r :: [Nat]) (s :: [Nat])
-- | insert a list of dimensions according to position and dimension lists.
-- Note that the list of positions references the final shape and not the
-- initial shape.
--
--
-- >>> addIndexes [4] [1,0] [3,2]
-- [2,3,4]
--
addIndexes :: () => [Int] -> [Int] -> [Int] -> [Int]
type family AddIndexes (as :: [Nat]) (xs :: [Nat]) (ys :: [Nat])
type family AddIndexesGo (as :: [Nat]) (xs :: [Nat]) (ys :: [Nat])
-- | drop dimensions of a shape according to a list of positions (where
-- position refers to the initial shape)
--
--
-- >>> dropIndexes [2, 3, 4] [1, 0]
-- [4]
--
dropIndexes :: [Int] -> [Int] -> [Int]
type family DropIndexes (s :: [Nat]) (i :: [Nat])
-- | take list of dimensions according to position lists.
--
--
-- >>> takeIndexes [2,3,4] [2,0]
-- [4,2]
--
takeIndexes :: [Int] -> [Int] -> [Int]
type family TakeIndexes (s :: [Nat]) (i :: [Nat])
-- | turn a list of included positions for a given rank into a list of
-- excluded positions
--
--
-- >>> exclude 3 [1,2]
-- [0]
--
exclude :: Int -> [Int] -> [Int]
type family Exclude (r :: Nat) (i :: [Nat])
-- | concatenate
--
--
-- >>> concatenate' 1 [2,3,4] [2,3,4]
-- [2,6,4]
--
concatenate' :: Int -> [Int] -> [Int] -> [Int]
type Concatenate i s0 s1 = Take i s0 ++ (Dimension s0 i + Dimension s1 i : Drop (i + 1) s0)
type CheckConcatenate i s0 s1 s = (CheckIndex i (Rank s0) && DropIndex s0 i == DropIndex s1 i && Rank s0 == Rank s1) ~ 'True
type Insert d s = Take d s ++ (Dimension s d + 1 : Drop (d + 1) s)
type CheckInsert d i s = (CheckIndex d (Rank s) && CheckIndex i (Dimension s d)) ~ 'True
-- | reorder' s i reorders the dimensions of shape s
-- according to a list of positions i
--
--
-- >>> reorder' [2,3,4] [2,0,1]
-- [4,2,3]
--
reorder' :: [Int] -> [Int] -> [Int]
type family Reorder (s :: [Nat]) (ds :: [Nat]) :: [Nat]
type family CheckReorder (ds :: [Nat]) (s :: [Nat])
-- | remove 1's from a list
squeeze' :: (Eq a, Num a) => [a] -> [a]
type family Squeeze (a :: [Nat])
-- | incAt d s increments the index at d of shape s by
-- one.
incAt :: Int -> [Int] -> [Int]
-- | decAt d s decrements the index at d of shape s by
-- one.
decAt :: Int -> [Int] -> [Int]
-- | Reflect a list of Nats
class KnownNats (ns :: [Nat])
natVals :: KnownNats ns => Proxy ns -> [Int]
-- | Reflect a list of list of Nats
class KnownNatss (ns :: [[Nat]])
natValss :: KnownNatss ns => Proxy ns -> [[Int]]
instance GHC.Show.Show (NumHask.Array.Shape.Shape s)
instance NumHask.Array.Shape.KnownNatss '[]
instance (NumHask.Array.Shape.KnownNats n, NumHask.Array.Shape.KnownNatss ns) => NumHask.Array.Shape.KnownNatss (n : ns)
instance NumHask.Array.Shape.KnownNats '[]
instance (GHC.TypeNats.KnownNat n, NumHask.Array.Shape.KnownNats ns) => NumHask.Array.Shape.KnownNats (n : ns)
instance NumHask.Array.Shape.HasShape '[]
instance (GHC.TypeNats.KnownNat n, NumHask.Array.Shape.HasShape s) => NumHask.Array.Shape.HasShape (n : s)
-- | Arrays with a dynamic shape.
module NumHask.Array.Dynamic
-- | a multidimensional array with a value-level shape
--
--
-- >>> let a = fromFlatList [2,3,4] [1..24] :: Array Int
--
-- >>> a
-- [[[1, 2, 3, 4],
-- [5, 6, 7, 8],
-- [9, 10, 11, 12]],
-- [[13, 14, 15, 16],
-- [17, 18, 19, 20],
-- [21, 22, 23, 24]]]
--
data Array a
Array :: [Int] -> Vector a -> Array a
[shape] :: Array a -> [Int]
[unArray] :: Array a -> Vector a
-- | convert from a list
--
--
-- >>> fromFlatList [2,3,4] [1..24] == a
-- True
--
fromFlatList :: [Int] -> [a] -> Array a
-- | extract an element at index i
--
--
-- >>> index a [1,2,3]
-- 24
--
index :: () => Array a -> [Int] -> a
-- | tabulate an array with a generating function
--
--
-- >>> tabulate [2,3,4] ((1+) . flatten [2,3,4]) == a
-- True
--
tabulate :: () => [Int] -> ([Int] -> a) -> Array a
-- | Reshape an array (with the same number of elements).
--
--
-- >>> reshape [4,3,2] a
-- [[[1, 2],
-- [3, 4],
-- [5, 6]],
-- [[7, 8],
-- [9, 10],
-- [11, 12]],
-- [[13, 14],
-- [15, 16],
-- [17, 18]],
-- [[19, 20],
-- [21, 22],
-- [23, 24]]]
--
reshape :: [Int] -> Array a -> Array a
-- | Reverse indices eg transposes the element Aijk to Akji.
--
--
-- >>> index (transpose a) [1,0,0] == index a [0,0,1]
-- True
--
transpose :: Array a -> Array a
-- | Extract the diagonal of an array.
--
--
-- >>> diag (ident [3,2])
-- [1, 1]
--
diag :: Array a -> Array a
-- | The identity array.
--
--
-- >>> ident [3,2]
-- [[1, 0],
-- [0, 1],
-- [0, 0]]
--
ident :: Num a => [Int] -> Array a
-- | Create an array composed of a single value.
--
--
-- >>> singleton [3,2] one
-- [[1, 1],
-- [1, 1],
-- [1, 1]]
--
singleton :: [Int] -> a -> Array a
-- | Select an array along dimensions.
--
--
-- >>> let s = selects [0,1] [1,1] a
--
-- >>> s
-- [17, 18, 19, 20]
--
selects :: [Int] -> [Int] -> Array a -> Array a
-- | Select an index except along specified dimensions
--
--
-- >>> let s = selectsExcept [2] [1,1] a
--
-- >>> s
-- [17, 18, 19, 20]
--
selectsExcept :: [Int] -> [Int] -> Array a -> Array a
-- | Fold along specified dimensions.
--
--
-- >>> folds sum [1] a
-- [68, 100, 132]
--
folds :: (Array a -> b) -> [Int] -> Array a -> Array b
-- | Extracts dimensions to an outer layer.
--
--
-- >>> let e = extracts [1,2] a
--
-- >>> shape <$> extracts [0] a
-- [[3,4], [3,4]]
--
extracts :: [Int] -> Array a -> Array (Array a)
-- | Join inner and outer dimension layers.
--
--
-- >>> let e = extracts [1,0] a
--
-- >>> let j = joins [1,0] e
--
-- >>> a == j
-- True
--
joins :: [Int] -> Array (Array a) -> Array a
-- | Maps a function along specified dimensions.
--
--
-- >>> shape $ maps (transpose) [1] a
-- [4,3,2]
--
maps :: (Array a -> Array b) -> [Int] -> Array a -> Array b
-- | Concatenate along a dimension.
--
--
-- >>> shape $ concatenate 1 a a
-- [2,6,4]
--
concatenate :: Int -> Array a -> Array a -> Array a
-- | Insert along a dimension at a position.
--
--
-- >>> insert 2 0 a (fromFlatList [2,3] [100..105])
-- [[[100, 1, 2, 3, 4],
-- [101, 5, 6, 7, 8],
-- [102, 9, 10, 11, 12]],
-- [[103, 13, 14, 15, 16],
-- [104, 17, 18, 19, 20],
-- [105, 21, 22, 23, 24]]]
--
insert :: Int -> Int -> Array a -> Array a -> Array a
-- | Insert along a dimension at the end.
--
--
-- >>> append 2 a (fromFlatList [2,3] [100..105])
-- [[[1, 2, 3, 4, 100],
-- [5, 6, 7, 8, 101],
-- [9, 10, 11, 12, 102]],
-- [[13, 14, 15, 16, 103],
-- [17, 18, 19, 20, 104],
-- [21, 22, 23, 24, 105]]]
--
append :: Int -> Array a -> Array a -> Array a
-- | change the order of dimensions
--
--
-- >>> let r = reorder [2,0,1] a
--
-- >>> r
-- [[[1, 5, 9],
-- [13, 17, 21]],
-- [[2, 6, 10],
-- [14, 18, 22]],
-- [[3, 7, 11],
-- [15, 19, 23]],
-- [[4, 8, 12],
-- [16, 20, 24]]]
--
reorder :: [Int] -> Array a -> Array a
-- | Product two arrays using the supplied binary function.
--
-- For context, if the function is multiply, and the arrays are tensors,
-- then this can be interpreted as a tensor product.
--
-- https://en.wikipedia.org/wiki/Tensor_product
--
-- The concept of a tensor product is a dense crossroad, and a complete
-- treatment is elsewhere. To quote: ... the tensor product can be
-- extended to other categories of mathematical objects in addition to
-- vector spaces, such as to matrices, tensors, algebras, topological
-- vector spaces, and modules. In each such case the tensor product is
-- characterized by a similar universal property: it is the freest
-- bilinear operation. The general concept of a "tensor product" is
-- captured by monoidal categories; that is, the class of all things that
-- have a tensor product is a monoidal category.
--
--
-- >>> expand (*) v v
-- [[1, 2, 3],
-- [2, 4, 6],
-- [3, 6, 9]]
--
expand :: (a -> b -> c) -> Array a -> Array b -> Array c
-- | Contract an array by applying the supplied (folding) function on
-- diagonal elements of the dimensions.
--
-- This generalises a tensor contraction by allowing the number of
-- contracting diagonals to be other than 2, and allowing a binary
-- operator other than multiplication.
--
--
-- >>> let b = fromFlatList [2,3] [1..6] :: Array Int
--
-- >>> contract sum [1,2] (expand (*) b (transpose b))
-- [[14, 32],
-- [32, 77]]
--
contract :: (Array a -> b) -> [Int] -> Array a -> Array b
-- | A generalisation of a dot operation, which is a multiplicative
-- expansion of two arrays and sum contraction along the middle two
-- dimensions.
--
-- matrix multiplication
--
--
-- >>> let b = fromFlatList [2,3] [1..6] :: Array Int
--
-- >>> dot sum (*) b (transpose b)
-- [[14, 32],
-- [32, 77]]
--
--
-- inner product
--
--
-- >>> let v = fromFlatList [3] [1..3] :: Array Int
--
-- >>> dot sum (*) v v
-- 14
--
--
-- matrix-vector multiplication Note that an `Array Int` with shape [3]
-- is neither a row vector nor column vector. dot is not turning
-- the vector into a matrix and then using matrix multiplication.
--
--
-- >>> dot sum (*) v b
-- [9, 12, 15]
--
--
--
-- >>> dot sum (*) b v
-- [14, 32]
--
dot :: (Array c -> d) -> (a -> b -> c) -> Array a -> Array b -> Array d
-- | Array multiplication.
--
-- matrix multiplication
--
--
-- >>> let b = fromFlatList [2,3] [1..6] :: Array Int
--
-- >>> mult b (transpose b)
-- [[14, 32],
-- [32, 77]]
--
--
-- inner product
--
--
-- >>> let v = fromFlatList [3] [1..3] :: Array Int
--
-- >>> mult v v
-- 14
--
--
-- matrix-vector multiplication
--
--
-- >>> mult v b
-- [9, 12, 15]
--
--
--
-- >>> mult b v
-- [14, 32]
--
mult :: (Additive a, Multiplicative a) => Array a -> Array a -> Array a
-- | Select elements along positions in every dimension.
--
--
-- >>> let s = slice [[0,1],[0,2],[1,2]] a
--
-- >>> s
-- [[[2, 3],
-- [10, 11]],
-- [[14, 15],
-- [22, 23]]]
--
slice :: [[Int]] -> Array a -> Array a
-- | Remove single dimensions.
--
--
-- >>> let a' = fromFlatList [2,1,3,4,1] [1..24] :: Array Int
--
-- >>> shape $ squeeze a'
-- [2,3,4]
--
squeeze :: Array a -> Array a
-- | Unwrapping scalars is probably a performance bottleneck.
--
--
-- >>> let s = fromFlatList [] [3] :: Array Int
--
-- >>> fromScalar s
-- 3
--
fromScalar :: Array a -> a
-- | Convert a number to a scalar.
--
--
-- >>> :t toScalar 2
-- toScalar 2 :: Num a => Array a
--
toScalar :: a -> Array a
-- | extract specialised to a matrix
--
--
-- >>> col 1 m
-- [1, 5, 9]
--
col :: Int -> Array a -> Array a
-- | Extract specialised to a matrix.
--
--
-- >>> row 1 m
-- [4, 5, 6, 7]
--
row :: Int -> Array a -> Array a
-- | matrix multiplication
--
-- This is dot sum (*) specialised to matrices
--
--
-- >>> let a = fromFlatList [2,2] [1, 2, 3, 4] :: Array Int
--
-- >>> let b = fromFlatList [2,2] [5, 6, 7, 8] :: Array Int
--
-- >>> a
-- [[1, 2],
-- [3, 4]]
--
--
--
-- >>> b
-- [[5, 6],
-- [7, 8]]
--
--
--
-- >>> mmult a b
-- [[19, 22],
-- [43, 50]]
--
mmult :: Ring a => Array a -> Array a -> Array a
instance GHC.Generics.Generic (NumHask.Array.Dynamic.Array a)
instance Control.DeepSeq.NFData a => Control.DeepSeq.NFData (NumHask.Array.Dynamic.Array a)
instance GHC.Classes.Ord a => GHC.Classes.Ord (NumHask.Array.Dynamic.Array a)
instance GHC.Classes.Eq a => GHC.Classes.Eq (NumHask.Array.Dynamic.Array a)
instance GHC.Base.Functor NumHask.Array.Dynamic.Array
instance Data.Foldable.Foldable NumHask.Array.Dynamic.Array
instance Data.Traversable.Traversable NumHask.Array.Dynamic.Array
instance GHC.Show.Show a => GHC.Show.Show (NumHask.Array.Dynamic.Array a)
-- | Arrays with a fixed shape.
module NumHask.Array.Fixed
-- | a multidimensional array with a type-level shape
--
--
-- >>> let a = [1..24] :: Array '[2,3,4] Int
--
-- >>> a
-- [[[1, 2, 3, 4],
-- [5, 6, 7, 8],
-- [9, 10, 11, 12]],
-- [[13, 14, 15, 16],
-- [17, 18, 19, 20],
-- [21, 22, 23, 24]]]
--
--
--
-- >>> [1,2,3] :: Array '[2,2] Int
-- [[*** Exception: NumHaskException {errorMessage = "shape mismatch"}
--
newtype Array s a
Array :: Vector a -> Array s a
[unArray] :: Array s a -> Vector a
-- | Use a dynamic array in a fixed context.
--
--
-- >>> with (D.fromFlatList [2,3,4] [1..24]) (selects (Proxy :: Proxy '[0,1]) [1,1] :: Array '[2,3,4] Int -> Array '[4] Int)
-- [17, 18, 19, 20]
--
with :: forall a r s. HasShape s => Array a -> (Array s a -> r) -> r
-- | Get shape of an Array as a value.
--
--
-- >>> shape a
-- [2,3,4]
--
shape :: forall a s. HasShape s => Array s a -> [Int]
-- | convert to a dynamic array with shape at the value level.
toDynamic :: HasShape s => Array s a -> Array a
-- | Reshape an array (with the same number of elements).
--
--
-- >>> reshape a :: Array '[4,3,2] Int
-- [[[1, 2],
-- [3, 4],
-- [5, 6]],
-- [[7, 8],
-- [9, 10],
-- [11, 12]],
-- [[13, 14],
-- [15, 16],
-- [17, 18]],
-- [[19, 20],
-- [21, 22],
-- [23, 24]]]
--
reshape :: forall a s s'. (Size s ~ Size s', HasShape s, HasShape s') => Array s a -> Array s' a
-- | Reverse indices eg transposes the element Aijk to Akji.
--
--
-- >>> index (transpose a) [1,0,0] == index a [0,0,1]
-- True
--
transpose :: forall a s. (HasShape s, HasShape (Reverse s)) => Array s a -> Array (Reverse s) a
-- | Extract the diagonal of an array.
--
--
-- >>> diag (ident :: Array '[3,2] Int)
-- [1, 1]
--
diag :: forall a s. (HasShape s, HasShape '[Minimum s]) => Array s a -> Array '[Minimum s] a
-- | The identity array.
--
--
-- >>> ident :: Array '[3,2] Int
-- [[1, 0],
-- [0, 1],
-- [0, 0]]
--
ident :: forall a s. (HasShape s, Additive a, Multiplicative a) => Array s a
-- | Create an array composed of a single value.
--
--
-- >>> singleton one :: Array '[3,2] Int
-- [[1, 1],
-- [1, 1],
-- [1, 1]]
--
singleton :: HasShape s => a -> Array s a
-- | Select an array along dimensions.
--
--
-- >>> let s = selects (Proxy :: Proxy '[0,1]) [1,1] a
--
-- >>> :t s
-- s :: Array '[4] Int
--
--
--
-- >>> s
-- [17, 18, 19, 20]
--
selects :: forall ds s s' a. (HasShape s, HasShape ds, HasShape s', s' ~ DropIndexes s ds) => Proxy ds -> [Int] -> Array s a -> Array s' a
-- | Select an index except along specified dimensions.
--
--
-- >>> let s = selectsExcept (Proxy :: Proxy '[2]) [1,1] a
--
-- >>> :t s
-- s :: Array '[4] Int
--
--
--
-- >>> s
-- [17, 18, 19, 20]
--
selectsExcept :: forall ds s s' a. (HasShape s, HasShape ds, HasShape s', s' ~ TakeIndexes s ds) => Proxy ds -> [Int] -> Array s a -> Array s' a
-- | Fold along specified dimensions.
--
--
-- >>> folds sum (Proxy :: Proxy '[1]) a
-- [68, 100, 132]
--
folds :: forall ds st si so a b. (HasShape st, HasShape ds, HasShape si, HasShape so, si ~ DropIndexes st ds, so ~ TakeIndexes st ds) => (Array si a -> b) -> Proxy ds -> Array st a -> Array so b
-- | Extracts dimensions to an outer layer.
--
--
-- >>> let e = extracts (Proxy :: Proxy '[1,2]) a
--
-- >>> :t e
-- e :: Array '[3, 4] (Array '[2] Int)
--
extracts :: forall ds st si so a. (HasShape st, HasShape ds, HasShape si, HasShape so, si ~ DropIndexes st ds, so ~ TakeIndexes st ds) => Proxy ds -> Array st a -> Array so (Array si a)
-- | Join inner and outer dimension layers.
--
--
-- >>> let e = extracts (Proxy :: Proxy '[1,0]) a
--
--
--
-- >>> :t e
-- e :: Array '[3, 2] (Array '[4] Int)
--
--
--
-- >>> let j = joins (Proxy :: Proxy '[1,0]) e
--
--
--
-- >>> :t j
-- j :: Array '[2, 3, 4] Int
--
--
--
-- >>> a == j
-- True
--
joins :: forall ds si st so a. (HasShape st, HasShape ds, st ~ AddIndexes si ds so, HasShape si, HasShape so) => Proxy ds -> Array so (Array si a) -> Array st a
-- | Maps a function along specified dimensions.
--
--
-- >>> :t maps (transpose) (Proxy :: Proxy '[1]) a
-- maps (transpose) (Proxy :: Proxy '[1]) a :: Array '[4, 3, 2] Int
--
maps :: forall ds st st' si si' so a b. (HasShape st, HasShape st', HasShape ds, HasShape si, HasShape si', HasShape so, si ~ DropIndexes st ds, so ~ TakeIndexes st ds, st' ~ AddIndexes si' ds so, st ~ AddIndexes si ds so) => (Array si a -> Array si' b) -> Proxy ds -> Array st a -> Array st' b
-- | Concatenate along a dimension.
--
--
-- >>> :t concatenate (Proxy :: Proxy 1) a a
-- concatenate (Proxy :: Proxy 1) a a :: Array '[2, 6, 4] Int
--
concatenate :: forall a s0 s1 d s. (CheckConcatenate d s0 s1 s, Concatenate d s0 s1 ~ s, HasShape s0, HasShape s1, HasShape s, KnownNat d) => Proxy d -> Array s0 a -> Array s1 a -> Array s a
-- | Insert along a dimension at a position.
--
--
-- >>> insert (Proxy :: Proxy 2) (Proxy :: Proxy 0) a ([100..105])
-- [[[100, 1, 2, 3, 4],
-- [101, 5, 6, 7, 8],
-- [102, 9, 10, 11, 12]],
-- [[103, 13, 14, 15, 16],
-- [104, 17, 18, 19, 20],
-- [105, 21, 22, 23, 24]]]
--
insert :: forall a s s' d i. (DropIndex s d ~ s', CheckInsert d i s, KnownNat i, KnownNat d, HasShape s, HasShape s', HasShape (Insert d s)) => Proxy d -> Proxy i -> Array s a -> Array s' a -> Array (Insert d s) a
-- | Insert along a dimension at the end.
--
--
-- >>> :t append (Proxy :: Proxy 0) a
-- append (Proxy :: Proxy 0) a
-- :: Array '[3, 4] Int -> Array '[3, 3, 4] Int
--
append :: forall a d s s'. (DropIndex s d ~ s', CheckInsert d (Dimension s d - 1) s, KnownNat (Dimension s d - 1), KnownNat d, HasShape s, HasShape s', HasShape (Insert d s)) => Proxy d -> Array s a -> Array s' a -> Array (Insert d s) a
-- | Change the order of dimensions.
--
--
-- >>> let r = reorder (Proxy :: Proxy '[2,0,1]) a
--
-- >>> :t r
-- r :: Array '[4, 2, 3] Int
--
reorder :: forall a ds s. (HasShape ds, HasShape s, HasShape (Reorder s ds), CheckReorder ds s) => Proxy ds -> Array s a -> Array (Reorder s ds) a
-- | Product two arrays using the supplied binary function.
--
-- For context, if the function is multiply, and the arrays are tensors,
-- then this can be interpreted as a tensor product.
--
-- https://en.wikipedia.org/wiki/Tensor_product
--
-- The concept of a tensor product is a dense crossroad, and a complete
-- treatment is elsewhere. To quote:
--
-- ... the tensor product can be extended to other categories of
-- mathematical objects in addition to vector spaces, such as to
-- matrices, tensors, algebras, topological vector spaces, and modules.
-- In each such case the tensor product is characterized by a similar
-- universal property: it is the freest bilinear operation. The general
-- concept of a "tensor product" is captured by monoidal categories; that
-- is, the class of all things that have a tensor product is a monoidal
-- category.
--
--
-- >>> expand (*) v v
-- [[1, 2, 3],
-- [2, 4, 6],
-- [3, 6, 9]]
--
expand :: forall s s' a b c. (HasShape s, HasShape s', HasShape ((++) s s')) => (a -> b -> c) -> Array s a -> Array s' b -> Array ((++) s s') c
-- | Contract an array by applying the supplied (folding) function on
-- diagonal elements of the dimensions.
--
-- This generalises a tensor contraction by allowing the number of
-- contracting diagonals to be other than 2, and allowing a binary
-- operator other than multiplication.
--
--
-- >>> let b = [1..6] :: Array '[2,3] Int
--
-- >>> contract sum (Proxy :: Proxy '[1,2]) (expand (*) b (transpose b))
-- [[14, 32],
-- [32, 77]]
--
contract :: forall a b s ss s' ds. (KnownNat (Minimum (TakeIndexes s ds)), HasShape (TakeIndexes s ds), HasShape s, HasShape ds, HasShape ss, HasShape s', s' ~ DropIndexes s ds, ss ~ '[Minimum (TakeIndexes s ds)]) => (Array ss a -> b) -> Proxy ds -> Array s a -> Array s' b
-- | A generalisation of a dot operation, which is a multiplicative
-- expansion of two arrays and sum contraction along the middle two
-- dimensions.
--
-- matrix multiplication
--
--
-- >>> let b = [1..6] :: Array '[2,3] Int
--
-- >>> dot sum (*) b (transpose b)
-- [[14, 32],
-- [32, 77]]
--
--
-- inner product
--
--
-- >>> let v = [1..3] :: Array '[3] Int
--
-- >>> :t dot sum (*) v v
-- dot sum (*) v v :: Array '[] Int
--
--
--
-- >>> dot sum (*) v v
-- 14
--
--
-- matrix-vector multiplication (Note how the vector doesn't need to be
-- converted to a row or column vector)
--
--
-- >>> dot sum (*) v b
-- [9, 12, 15]
--
--
--
-- >>> dot sum (*) b v
-- [14, 32]
--
--
-- dot allows operation on mis-shaped matrices:
--
--
-- >>> let m23 = [1..6] :: Array '[2,3] Int
--
-- >>> let m12 = [1,2] :: Array '[1,2] Int
--
-- >>> shape $ dot sum (*) m23 m12
-- [2,2]
--
--
-- the algorithm ignores excess positions within the contracting
-- dimension(s):
--
-- m23 shape: 2 3
--
-- m12 shape: 1 2
--
-- res shape: 2 2
--
-- FIXME: work out whether this is a feature or a bug...
--
-- find instances of a vector in a matrix
--
--
-- >>> let cs = fromList ("abacbaab" :: [Char]) :: Array '[4,2] Char
--
-- >>> let v = fromList ("ab" :: [Char]) :: Vector 2 Char
--
-- >>> dot (all id) (==) cs v
-- [True, False, False, True]
--
dot :: forall a b c d sa sb s' ss se. (HasShape sa, HasShape sb, HasShape (sa ++ sb), se ~ TakeIndexes (sa ++ sb) '[Rank sa - 1, Rank sa], HasShape se, KnownNat (Minimum se), KnownNat (Rank sa - 1), KnownNat (Rank sa), ss ~ '[Minimum se], HasShape ss, s' ~ DropIndexes (sa ++ sb) '[Rank sa - 1, Rank sa], HasShape s') => (Array ss c -> d) -> (a -> b -> c) -> Array sa a -> Array sb b -> Array s' d
-- | Array multiplication.
--
-- matrix multiplication
--
--
-- >>> let b = [1..6] :: Array '[2,3] Int
--
-- >>> mult b (transpose b)
-- [[14, 32],
-- [32, 77]]
--
--
-- inner product
--
--
-- >>> let v = [1..3] :: Array '[3] Int
--
-- >>> :t mult v v
-- mult v v :: Array '[] Int
--
--
--
-- >>> mult v v
-- 14
--
--
-- matrix-vector multiplication
--
--
-- >>> mult v b
-- [9, 12, 15]
--
--
--
-- >>> mult b v
-- [14, 32]
--
mult :: forall a sa sb s' ss se. (Additive a, Multiplicative a, HasShape sa, HasShape sb, HasShape (sa ++ sb), se ~ TakeIndexes (sa ++ sb) '[Rank sa - 1, Rank sa], HasShape se, KnownNat (Minimum se), KnownNat (Rank sa - 1), KnownNat (Rank sa), ss ~ '[Minimum se], HasShape ss, s' ~ DropIndexes (sa ++ sb) '[Rank sa - 1, Rank sa], HasShape s') => Array sa a -> Array sb a -> Array s' a
-- | Select elements along positions in every dimension.
--
--
-- >>> let s = slice (Proxy :: Proxy '[[0,1],[0,2],[1,2]]) a
--
-- >>> :t s
-- s :: Array '[2, 2, 2] Int
--
--
--
-- >>> s
-- [[[2, 3],
-- [10, 11]],
-- [[14, 15],
-- [22, 23]]]
--
--
--
-- >>> let s = squeeze $ slice (Proxy :: Proxy '[ '[0], '[0], '[0]]) a
--
-- >>> :t s
-- s :: Array '[] Int
--
--
--
-- >>> s
-- 1
--
slice :: forall (pss :: [[Nat]]) s s' a. (HasShape s, HasShape s', KnownNatss pss, KnownNat (Rank pss), s' ~ Ranks pss) => Proxy pss -> Array s a -> Array s' a
-- | Remove single dimensions.
--
--
-- >>> let a = [1..24] :: Array '[2,1,3,4,1] Int
--
-- >>> a
-- [[[[[1],
-- [2],
-- [3],
-- [4]],
-- [[5],
-- [6],
-- [7],
-- [8]],
-- [[9],
-- [10],
-- [11],
-- [12]]]],
-- [[[[13],
-- [14],
-- [15],
-- [16]],
-- [[17],
-- [18],
-- [19],
-- [20]],
-- [[21],
-- [22],
-- [23],
-- [24]]]]]
--
-- >>> squeeze a
-- [[[1, 2, 3, 4],
-- [5, 6, 7, 8],
-- [9, 10, 11, 12]],
-- [[13, 14, 15, 16],
-- [17, 18, 19, 20],
-- [21, 22, 23, 24]]]
--
--
--
-- >>> squeeze ([1] :: Array '[1,1] Double)
-- 1.0
--
squeeze :: forall s t a. t ~ Squeeze s => Array s a -> Array t a
-- | Wiki Scalar
--
-- An Array '[] a despite being a Scalar is never-the-less a one-element
-- vector under the hood. Unification of representation is unexplored.
type Scalar a = Array ('[] :: [Nat]) a
-- | Unwrapping scalars is probably a performance bottleneck.
--
--
-- >>> let s = [3] :: Array ('[] :: [Nat]) Int
--
-- >>> fromScalar s
-- 3
--
fromScalar :: HasShape ('[] :: [Nat]) => Array ('[] :: [Nat]) a -> a
-- | Convert a number to a scalar.
--
--
-- >>> :t toScalar 2
-- toScalar 2 :: Num a => Array '[] a
--
toScalar :: HasShape ('[] :: [Nat]) => a -> Array ('[] :: [Nat]) a
-- | Wiki Vector
type Vector s a = Array '[s] a
-- | Wiki Matrix
type Matrix m n a = Array '[m, n] a
-- | Extract specialised to a matrix.
--
--
-- >>> col 1 m
-- [1, 5, 9]
--
col :: forall m n a. (KnownNat m, KnownNat n, HasShape '[m, n]) => Int -> Matrix m n a -> Vector n a
-- | Extract specialised to a matrix.
--
--
-- >>> row 1 m
-- [4, 5, 6, 7]
--
row :: forall m n a. (KnownNat m, KnownNat n, HasShape '[m, n]) => Int -> Matrix m n a -> Vector n a
-- | Column extraction checked at type level.
--
--
-- >>> safeCol (Proxy :: Proxy 1) m
-- [1, 5, 9]
--
--
--
-- >>> safeCol (Proxy :: Proxy 4) m
-- ...
-- ... index outside range
-- ...
--
safeCol :: forall m n a j. ( 'True ~ CheckIndex j n, KnownNat j, KnownNat m, KnownNat n, HasShape '[m, n]) => Proxy j -> Matrix m n a -> Vector n a
-- | Row extraction checked at type level.
--
--
-- >>> safeRow (Proxy :: Proxy 1) m
-- [4, 5, 6, 7]
--
--
--
-- >>> safeRow (Proxy :: Proxy 3) m
-- ...
-- ... index outside range
-- ...
--
safeRow :: forall m n a j. ( 'True ~ CheckIndex j m, KnownNat j, KnownNat m, KnownNat n, HasShape '[m, n]) => Proxy j -> Matrix m n a -> Vector n a
-- | Matrix multiplication.
--
-- This is dot sum (*) specialised to matrices
--
--
-- >>> let a = [1, 2, 3, 4] :: Array '[2, 2] Int
--
-- >>> let b = [5, 6, 7, 8] :: Array '[2, 2] Int
--
-- >>> a
-- [[1, 2],
-- [3, 4]]
--
--
--
-- >>> b
-- [[5, 6],
-- [7, 8]]
--
--
--
-- >>> mmult a b
-- [[19, 22],
-- [43, 50]]
--
mmult :: forall m n k a. (KnownNat k, KnownNat m, KnownNat n, HasShape [m, n], Ring a) => Array [m, k] a -> Array [k, n] a -> Array [m, n] a
instance forall k (s :: k). Data.Traversable.Traversable (NumHask.Array.Fixed.Array s)
instance forall k (s :: k) a. GHC.Generics.Generic (NumHask.Array.Fixed.Array s a)
instance forall k (s :: k). Data.Foldable.Foldable (NumHask.Array.Fixed.Array s)
instance forall k (s :: k). GHC.Base.Functor (NumHask.Array.Fixed.Array s)
instance forall k (s :: k) a. Control.DeepSeq.NFData a => Control.DeepSeq.NFData (NumHask.Array.Fixed.Array s a)
instance forall k (s :: k) a. GHC.Classes.Ord a => GHC.Classes.Ord (NumHask.Array.Fixed.Array s a)
instance forall k (s :: k) a. GHC.Classes.Eq a => GHC.Classes.Eq (NumHask.Array.Fixed.Array s a)
instance (NumHask.Algebra.Abstract.Multiplicative.Multiplicative a, NumHask.Algebra.Abstract.Ring.Distributive a, NumHask.Algebra.Abstract.Additive.Subtractive a, GHC.TypeNats.KnownNat m, NumHask.Array.Shape.HasShape '[m, m]) => NumHask.Algebra.Abstract.Multiplicative.Multiplicative (NumHask.Array.Fixed.Matrix m m a)
instance (NumHask.Array.Shape.HasShape s, GHC.Show.Show a) => GHC.Show.Show (NumHask.Array.Fixed.Array s a)
instance NumHask.Array.Shape.HasShape s => Data.Distributive.Distributive (NumHask.Array.Fixed.Array s)
instance NumHask.Array.Shape.HasShape s => Data.Functor.Rep.Representable (NumHask.Array.Fixed.Array s)
instance (NumHask.Algebra.Abstract.Additive.Additive a, NumHask.Array.Shape.HasShape s) => NumHask.Algebra.Abstract.Additive.Additive (NumHask.Array.Fixed.Array s a)
instance (NumHask.Algebra.Abstract.Additive.Subtractive a, NumHask.Array.Shape.HasShape s) => NumHask.Algebra.Abstract.Additive.Subtractive (NumHask.Array.Fixed.Array s a)
instance (NumHask.Array.Shape.HasShape s, NumHask.Algebra.Abstract.Multiplicative.Multiplicative a) => NumHask.Algebra.Abstract.Action.MultiplicativeAction (NumHask.Array.Fixed.Array s a)
instance (NumHask.Array.Shape.HasShape s, NumHask.Algebra.Abstract.Lattice.JoinSemiLattice a) => NumHask.Algebra.Abstract.Lattice.JoinSemiLattice (NumHask.Array.Fixed.Array s a)
instance (NumHask.Array.Shape.HasShape s, NumHask.Algebra.Abstract.Lattice.MeetSemiLattice a) => NumHask.Algebra.Abstract.Lattice.MeetSemiLattice (NumHask.Array.Fixed.Array s a)
instance (NumHask.Array.Shape.HasShape s, NumHask.Algebra.Abstract.Additive.Subtractive a, NumHask.Analysis.Metric.Epsilon a) => NumHask.Analysis.Metric.Epsilon (NumHask.Array.Fixed.Array s a)
instance NumHask.Array.Shape.HasShape s => GHC.Exts.IsList (NumHask.Array.Fixed.Array s a)
-- | Arrays with a fixed shape, with a HMatrix representation.
module NumHask.Array.HMatrix
-- | a multidimensional array with a type-level shape
--
--
-- >>> let a = [1..24] :: Array '[2,3,4] Int
--
-- >>> a
-- [[[1, 2, 3, 4],
-- [5, 6, 7, 8],
-- [9, 10, 11, 12]],
-- [[13, 14, 15, 16],
-- [17, 18, 19, 20],
-- [21, 22, 23, 24]]]
--
--
--
-- >>> [1,2,3] :: Array '[2,2] Int
-- [[*** Exception: NumHaskException {errorMessage = "shape mismatch"}
--
newtype Array s a
Array :: Matrix a -> Array s a
[unArray] :: Array s a -> Matrix a
-- | with no fmap, we supply the representable API
index :: forall s a. (HasShape s, Element a, Container Vector a) => Array s a -> [Int] -> a
-- | tabulate an array with a generating function
--
--
-- >>> tabulate [2,3,4] ((1+) . flatten [2,3,4]) == a
-- True
--
tabulate :: forall s a. (HasShape s, Element a) => ([Int] -> a) -> Array s a
-- | Get shape of an Array as a value.
--
--
-- >>> shape a
-- [2,3,4]
--
shape :: forall a s. HasShape s => Array s a -> [Int]
-- | Convert to a dynamic array.
toDynamic :: (HasShape s, Element a) => Array s a -> Array a
-- | Convert to a fixed array.
toFixed :: (HasShape s, Element a) => Array s a -> Array s a
-- | Convert from a fixed array.
fromFixed :: (HasShape s, Element a) => Array s a -> Array s a
-- | Reshape an array (with the same number of elements).
--
--
-- >>> reshape a :: Array '[4,3,2] Int
-- [[[1, 2],
-- [3, 4],
-- [5, 6]],
-- [[7, 8],
-- [9, 10],
-- [11, 12]],
-- [[13, 14],
-- [15, 16],
-- [17, 18]],
-- [[19, 20],
-- [21, 22],
-- [23, 24]]]
--
reshape :: forall a s s'. (Size s ~ Size s', HasShape s, HasShape s', Container Vector a) => Array s a -> Array s' a
-- | Reverse indices eg transposes the element Aijk to Akji.
--
--
-- >>> index (transpose a) [1,0,0] == index a [0,0,1]
-- True
--
transpose :: forall a s. (Element a, Container Vector a, HasShape s, HasShape (Reverse s)) => Array s a -> Array (Reverse s) a
-- | Extract the diagonal of an array.
--
--
-- >>> diag (ident :: Array '[3,2] Int)
-- [1, 1]
--
diag :: forall a s. (HasShape s, HasShape '[Minimum s], Element a, Container Vector a) => Array s a -> Array '[Minimum s] a
-- | The identity array.
--
--
-- >>> ident :: Array '[3,2] Int
-- [[1, 0],
-- [0, 1],
-- [0, 0]]
--
ident :: forall a s. (Element a, Container Vector a, HasShape s, Additive a, Multiplicative a) => Array s a
-- | Create an array composed of a single value.
--
--
-- >>> singleton one :: Array '[3,2] Int
-- [[1, 1],
-- [1, 1],
-- [1, 1]]
--
singleton :: (Element a, Container Vector a, HasShape s) => a -> Array s a
-- | Select an array along dimensions.
--
--
-- >>> let s = selects (Proxy :: Proxy '[0,1]) [1,1] a
--
-- >>> :t s
-- s :: Array '[4] Int
--
--
--
-- >>> s
-- [17, 18, 19, 20]
--
selects :: forall ds s s' a. (HasShape s, HasShape ds, HasShape s', s' ~ DropIndexes s ds, Element a, Container Vector a) => Proxy ds -> [Int] -> Array s a -> Array s' a
-- | Select an index except along specified dimensions.
--
--
-- >>> let s = selectsExcept (Proxy :: Proxy '[2]) [1,1] a
--
-- >>> :t s
-- s :: Array '[4] Int
--
--
--
-- >>> s
-- [17, 18, 19, 20]
--
selectsExcept :: forall ds s s' a. (HasShape s, HasShape ds, HasShape s', s' ~ TakeIndexes s ds, Element a, Container Vector a) => Proxy ds -> [Int] -> Array s a -> Array s' a
-- | Fold along specified dimensions.
--
--
-- >>> folds sum (Proxy :: Proxy '[1]) a
-- [68, 100, 132]
--
folds :: forall ds st si so a b. (HasShape st, HasShape ds, HasShape si, HasShape so, si ~ DropIndexes st ds, so ~ TakeIndexes st ds, Element a, Container Vector a, Element b, Container Vector b) => (Array si a -> b) -> Proxy ds -> Array st a -> Array so b
-- | Concatenate along a dimension.
--
--
-- >>> :t concatenate (Proxy :: Proxy 1) a a
-- concatenate (Proxy :: Proxy 1) a a :: Array '[2, 6, 4] Int
--
concatenate :: forall a s0 s1 d s. (CheckConcatenate d s0 s1 s, Concatenate d s0 s1 ~ s, HasShape s0, HasShape s1, HasShape s, KnownNat d, Element a, Container Vector a) => Proxy d -> Array s0 a -> Array s1 a -> Array s a
-- | Insert along a dimension at a position.
--
--
-- >>> insert (Proxy :: Proxy 2) (Proxy :: Proxy 0) a ([100..105])
-- [[[100, 1, 2, 3, 4],
-- [101, 5, 6, 7, 8],
-- [102, 9, 10, 11, 12]],
-- [[103, 13, 14, 15, 16],
-- [104, 17, 18, 19, 20],
-- [105, 21, 22, 23, 24]]]
--
insert :: forall a s s' d i. (DropIndex s d ~ s', CheckInsert d i s, KnownNat i, KnownNat d, HasShape s, HasShape s', HasShape (Insert d s), Element a, Container Vector a) => Proxy d -> Proxy i -> Array s a -> Array s' a -> Array (Insert d s) a
-- | Insert along a dimension at the end.
--
--
-- >>> :t append (Proxy :: Proxy 0) a
-- append (Proxy :: Proxy 0) a
-- :: Array '[3, 4] Int -> Array '[3, 3, 4] Int
--
append :: forall a d s s'. (DropIndex s d ~ s', CheckInsert d (Dimension s d - 1) s, KnownNat (Dimension s d - 1), KnownNat d, HasShape s, HasShape s', HasShape (Insert d s), Element a, Container Vector a) => Proxy d -> Array s a -> Array s' a -> Array (Insert d s) a
-- | Change the order of dimensions.
--
--
-- >>> let r = reorder (Proxy :: Proxy '[2,0,1]) a
--
-- >>> :t r
-- r :: Array '[4, 2, 3] Int
--
reorder :: forall a ds s. (HasShape ds, HasShape s, HasShape (Reorder s ds), CheckReorder ds s, Element a, Container Vector a) => Proxy ds -> Array s a -> Array (Reorder s ds) a
-- | Product two arrays using the supplied binary function.
--
-- For context, if the function is multiply, and the arrays are tensors,
-- then this can be interpreted as a tensor product.
--
-- https://en.wikipedia.org/wiki/Tensor_product
--
-- The concept of a tensor product is a dense crossroad, and a complete
-- treatment is elsewhere. To quote:
--
-- ... the tensor product can be extended to other categories of
-- mathematical objects in addition to vector spaces, such as to
-- matrices, tensors, algebras, topological vector spaces, and modules.
-- In each such case the tensor product is characterized by a similar
-- universal property: it is the freest bilinear operation. The general
-- concept of a "tensor product" is captured by monoidal categories; that
-- is, the class of all things that have a tensor product is a monoidal
-- category.
--
--
-- >>> expand (*) v v
-- [[1, 2, 3],
-- [2, 4, 6],
-- [3, 6, 9]]
--
expand :: forall s s' a b c. (HasShape s, HasShape s', HasShape ((++) s s'), Element a, Container Vector a, Element b, Container Vector b, Element c) => (a -> b -> c) -> Array s a -> Array s' b -> Array ((++) s s') c
-- | Select elements along positions in every dimension.
--
--
-- >>> let s = slice (Proxy :: Proxy '[[0,1],[0,2],[1,2]]) a
--
-- >>> :t s
-- s :: Array '[2, 2, 2] Int
--
--
--
-- >>> s
-- [[[2, 3],
-- [10, 11]],
-- [[14, 15],
-- [22, 23]]]
--
--
--
-- >>> let s = squeeze $ slice (Proxy :: Proxy '[ '[0], '[0], '[0]]) a
--
-- >>> :t s
-- s :: Array '[] Int
--
--
--
-- >>> s
-- 1
--
slice :: forall (pss :: [[Nat]]) s s' a. (HasShape s, HasShape s', KnownNatss pss, KnownNat (Rank pss), s' ~ Ranks pss, Element a, Container Vector a) => Proxy pss -> Array s a -> Array s' a
-- | Remove single dimensions.
--
--
-- >>> let a = [1..24] :: Array '[2,1,3,4,1] Int
--
-- >>> a
-- [[[[[1],
-- [2],
-- [3],
-- [4]],
-- [[5],
-- [6],
-- [7],
-- [8]],
-- [[9],
-- [10],
-- [11],
-- [12]]]],
-- [[[[13],
-- [14],
-- [15],
-- [16]],
-- [[17],
-- [18],
-- [19],
-- [20]],
-- [[21],
-- [22],
-- [23],
-- [24]]]]]
--
-- >>> squeeze a
-- [[[1, 2, 3, 4],
-- [5, 6, 7, 8],
-- [9, 10, 11, 12]],
-- [[13, 14, 15, 16],
-- [17, 18, 19, 20],
-- [21, 22, 23, 24]]]
--
--
--
-- >>> squeeze ([1] :: Array '[1,1] Double)
-- 1.0
--
squeeze :: forall s t a. t ~ Squeeze s => Array s a -> Array t a
-- | Wiki Scalar
--
-- An Array '[] a despite being a Scalar is never-the-less a one-element
-- vector under the hood. Unification of representation is unexplored.
type Scalar a = Array ('[] :: [Nat]) a
-- | Unwrapping scalars is probably a performance bottleneck.
--
--
-- >>> let s = [3] :: Array ('[] :: [Nat]) Int
--
-- >>> fromScalar s
-- 3
--
fromScalar :: (Element a, Container Vector a, HasShape ('[] :: [Nat])) => Array ('[] :: [Nat]) a -> a
-- | Convert a number to a scalar.
--
--
-- >>> :t toScalar 2
-- toScalar 2 :: Num a => Array '[] a
--
toScalar :: (Element a, Container Vector a, HasShape ('[] :: [Nat])) => a -> Array ('[] :: [Nat]) a
-- | Wiki Vector
type Vector s a = Array '[s] a
-- | Wiki Matrix
type Matrix m n a = Array '[m, n] a
-- | Extract specialised to a matrix.
--
--
-- >>> col 1 m
-- [1, 5, 9]
--
col :: forall m n a. (Element a, Container Vector a, KnownNat m, KnownNat n, HasShape '[m, n]) => Int -> Matrix m n a -> Vector n a
-- | Extract specialised to a matrix.
--
--
-- >>> row 1 m
-- [4, 5, 6, 7]
--
row :: forall m n a. (Element a, Container Vector a, KnownNat m, KnownNat n, HasShape '[m, n]) => Int -> Matrix m n a -> Vector n a
-- | Column extraction checked at type level.
--
--
-- >>> safeCol (Proxy :: Proxy 1) m
-- [1, 5, 9]
--
--
--
-- >>> safeCol (Proxy :: Proxy 4) m
-- ...
-- ... index outside range
-- ...
--
safeCol :: forall m n a j. (Element a, Container Vector a, 'True ~ CheckIndex j n, KnownNat j, KnownNat m, KnownNat n, HasShape '[m, n]) => Proxy j -> Matrix m n a -> Vector n a
-- | Row extraction checked at type level.
--
--
-- >>> safeRow (Proxy :: Proxy 1) m
-- [4, 5, 6, 7]
--
--
--
-- >>> safeRow (Proxy :: Proxy 3) m
-- ...
-- ... index outside range
-- ...
--
safeRow :: forall m n a j. (Element a, Container Vector a, 'True ~ CheckIndex j m, KnownNat j, KnownNat m, KnownNat n, HasShape '[m, n]) => Proxy j -> Matrix m n a -> Vector n a
-- | Matrix multiplication.
--
-- This is dot sum (*) specialised to matrices
--
--
-- >>> let a = [1, 2, 3, 4] :: Array '[2, 2] Int
--
-- >>> let b = [5, 6, 7, 8] :: Array '[2, 2] Int
--
-- >>> a
-- [[1, 2],
-- [3, 4]]
--
--
--
-- >>> b
-- [[5, 6],
-- [7, 8]]
--
--
--
-- >>> mmult a b
-- [[19, 22],
-- [43, 50]]
--
mmult :: forall m n k a. (KnownNat k, KnownNat m, KnownNat n, HasShape [m, n], Ring a, Numeric a) => Array [m, k] a -> Array [k, n] a -> Array [m, n] a
instance forall k (s :: k) a. GHC.Generics.Generic (NumHask.Array.HMatrix.Array s a)
instance forall k (s :: k) a. (Foreign.Storable.Storable a, Control.DeepSeq.NFData a) => Control.DeepSeq.NFData (NumHask.Array.HMatrix.Array s a)
instance forall k (s :: k) a. (GHC.Show.Show a, Internal.Matrix.Element a) => GHC.Show.Show (NumHask.Array.HMatrix.Array s a)
instance (NumHask.Algebra.Abstract.Multiplicative.Multiplicative a, NumHask.Algebra.Abstract.Ring.Distributive a, NumHask.Algebra.Abstract.Additive.Subtractive a, Internal.Numeric.Numeric a, GHC.TypeNats.KnownNat m, NumHask.Array.Shape.HasShape '[m, m], Internal.Matrix.Element a, Internal.Numeric.Container Data.Vector.Storable.Vector a) => NumHask.Algebra.Abstract.Multiplicative.Multiplicative (NumHask.Array.HMatrix.Matrix m m a)
instance (NumHask.Algebra.Abstract.Additive.Additive a, NumHask.Array.Shape.HasShape s, Internal.Numeric.Container Data.Vector.Storable.Vector a, GHC.Num.Num a) => NumHask.Algebra.Abstract.Additive.Additive (NumHask.Array.HMatrix.Array s a)
instance (NumHask.Algebra.Abstract.Multiplicative.Multiplicative a, NumHask.Array.Shape.HasShape s, Internal.Numeric.Container Data.Vector.Storable.Vector a, GHC.Num.Num (Data.Vector.Storable.Vector a), GHC.Num.Num a) => NumHask.Algebra.Abstract.Multiplicative.Multiplicative (NumHask.Array.HMatrix.Array s a)
instance (NumHask.Array.Shape.HasShape s, NumHask.Algebra.Abstract.Multiplicative.Multiplicative a, Internal.Numeric.Container Data.Vector.Storable.Vector a, GHC.Num.Num a) => NumHask.Algebra.Abstract.Action.MultiplicativeAction (NumHask.Array.HMatrix.Array s a)
instance (NumHask.Array.Shape.HasShape s, Internal.Matrix.Element a) => GHC.Exts.IsList (NumHask.Array.HMatrix.Array s a)
-- | Numbers that can be indexed into with an Int list.
module NumHask.Array