numeric-prelude-0.1.2: An experimental alternative hierarchy of numeric type classesSource codeContentsIndex
MathObj.Matrix
Portabilityrequires multi-parameter type classes
Stabilityprovisional
Maintainer[email protected]
Description

Routines and abstractions for Matrices and basic linear algebra over fields or rings.

We stick to simple Int indices. Although advanced indices would be nice e.g. for matrices with sub-matrices, this is not easily implemented since arrays do only support a lower and an upper bound but no additional parameters.

ToDo: - Matrix inverse, determinant

Synopsis
data T a
type Dimension = Int
format :: Show a => T a -> String
transpose :: T a -> T a
rows :: T a -> [[a]]
columns :: T a -> [[a]]
fromRows :: Dimension -> Dimension -> [[a]] -> T a
fromColumns :: Dimension -> Dimension -> [[a]] -> T a
fromList :: Dimension -> Dimension -> [a] -> T a
dimension :: T a -> (Dimension, Dimension)
numRows :: T a -> Dimension
numColumns :: T a -> Dimension
zipWith :: (a -> b -> c) -> T a -> T b -> T c
zero :: C a => Dimension -> Dimension -> T a
one :: C a => Dimension -> T a
diagonal :: C a => [a] -> T a
scale :: C a => a -> T a -> T a
random :: (RandomGen g, Random a) => Dimension -> Dimension -> g -> (T a, g)
randomR :: (RandomGen g, Random a) => Dimension -> Dimension -> (a, a) -> g -> (T a, g)
Documentation
data T a Source
A matrix is a twodimensional array, indexed by integers.
show/hide Instances
Functor T
C T
C a b => C a (T b)
Eq a => Eq (T a)
Ord a => Ord (T a)
Read a => Read (T a)
Show a => Show (T a)
C a => C (T a)
C a => C (T a)
type Dimension = IntSource
format :: Show a => T a -> StringSource
transpose :: T a -> T aSource
Transposition of matrices is just transposition in the sense of Data.List.
rows :: T a -> [[a]]Source
columns :: T a -> [[a]]Source
fromRows :: Dimension -> Dimension -> [[a]] -> T aSource
fromColumns :: Dimension -> Dimension -> [[a]] -> T aSource
fromList :: Dimension -> Dimension -> [a] -> T aSource
dimension :: T a -> (Dimension, Dimension)Source
numRows :: T a -> DimensionSource
numColumns :: T a -> DimensionSource
zipWith :: (a -> b -> c) -> T a -> T b -> T cSource
zero :: C a => Dimension -> Dimension -> T aSource
one :: C a => Dimension -> T aSource
diagonal :: C a => [a] -> T aSource
scale :: C a => a -> T a -> T aSource
random :: (RandomGen g, Random a) => Dimension -> Dimension -> g -> (T a, g)Source
randomR :: (RandomGen g, Random a) => Dimension -> Dimension -> (a, a) -> g -> (T a, g)Source
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