hTensor 0.7.0.1 → 0.8.0

raw patch · 6 files changed

+24/−15 lines, 6 filesdep ~hmatrixPVP ok

version bump matches the API change (PVP)

Dependency ranges changed: hmatrix

API changes (from Hackage documentation)

Files

• hTensor.cabal +7/−3
• lib/Numeric/LinearAlgebra/Array.hs +1/−1
• lib/Numeric/LinearAlgebra/Array/Decomposition.hs +1/−1
• lib/Numeric/LinearAlgebra/Array/Internal.hs +1/−1
• lib/Numeric/LinearAlgebra/Array/Solve.hs +10/−7
• lib/Numeric/LinearAlgebra/Array/Util.hs +4/−2

@@ -1,5 +1,5 @@ Name:               hTensor-Version:            0.7.0.1+Version:            0.8.0 License:            GPL License-file:       LICENSE Author:             Alberto Ruiz@@ -26,7 +26,7 @@  A tutorial can be found in the website of the project.  Category:           Math-tested-with:        GHC ==6.12.1+tested-with:        GHC ==7.4  cabal-version:      >=1.6 build-type:         Simple@@ -42,7 +42,7 @@     else       build-depends:    base < 3 -    Build-Depends:      hmatrix >= 0.10, containers, random+    Build-Depends:      hmatrix >= 0.13, containers, random      hs-source-dirs:     lib     Exposed-modules:    Numeric.LinearAlgebra.Array.Util@@ -62,4 +62,8 @@     ghc-options:        -Wall                         -fno-warn-missing-signatures                         -fno-warn-orphans++source-repository head+    type:     git+    location: https://github.com/AlbertoRuiz/hTensor 

@@ -42,7 +42,7 @@ (.*) :: (Coord a, Compat i) => NArray i a -> NArray i a -> NArray i a (.*) = zipArray (*) -instance (Coord t, Compat i) => Eq (NArray i t) where+instance (Eq t, Coord t, Compat i) => Eq (NArray i t) where     t1 == t2 = sameStructure t1 t2 && coords t1 == coords (reorder (namesR t1) t2)  instance (Show (NArray i t), Coord t, Compat i) => Num (NArray i t) where

@@ -25,7 +25,7 @@ import Numeric.LinearAlgebra.Array.Internal(seqIdx,namesR,sizesR,renameRaw) import Numeric.LinearAlgebra.Array.Util import Numeric.LinearAlgebra.Array.Solve-import Numeric.LinearAlgebra hiding ((.*), scalar)+import Numeric.LinearAlgebra hiding (scalar) import Data.List import System.Random --import Control.Parallel.Strategies

@@ -76,7 +76,7 @@ debug m f x = trace (m ++ show (f x)) x  -- | Types that can be elements of the multidimensional arrays.-class (Num (Vector t), Field t, Normed Vector t) => Coord t+class (Num (Vector t), Field t, Normed Vector t, Show t) => Coord t instance Coord Double instance Coord (Complex Double) 

@@ -31,7 +31,7 @@ import Numeric.LinearAlgebra.Array.Util import Numeric.LinearAlgebra.Exterior import Numeric.LinearAlgebra.Array.Internal(mkNArray, selDims, debug, namesR)-import Numeric.LinearAlgebra hiding ((.*), scalar)+import Numeric.LinearAlgebra hiding (scalar) import Data.List import System.Random @@ -172,7 +172,7 @@  -- | Solution of a multilinear system a x y z ... = b based on alternating least squares. mlSolve-  :: (Compat i, Coord t, Num (NArray i t))+  :: (Compat i, Coord t, Num (NArray i t), Show (NArray i t))      => ALSParam i t     -- ^ optimization parameters      -> [NArray i t]  -- ^ coefficients (a), given as a list of factors.      -> [NArray i t]  -- ^ initial solution [x,y,z...]@@ -192,7 +192,7 @@  -- | Solution of the homogeneous multilinear system a x y z ... = 0 based on alternating least squares. mlSolveH-  :: (Compat i, Coord t, Num (NArray i t))+  :: (Compat i, Coord t, Num (NArray i t), Show (NArray i t))      => ALSParam  i t    -- ^ optimization parameters      -> [NArray i t]  -- ^ coefficients (a), given as a list of factors.      -> [NArray i t]  -- ^ initial solution [x,y,z...]@@ -232,7 +232,7 @@ {- | Given two arrays a (source) and  b (target), we try to compute linear transformations x,y,z,... for each dimension, such that product [a,x,y,z,...] == b. (We can use 'eqnorm' for 'post' processing, or 'id'.) -}-solveFactors :: (Coord t, Random t, Compat i, Num (NArray i t))+solveFactors :: (Coord t, Random t, Compat i, Num (NArray i t), Show (NArray i t))              => Int          -- ^ seed for random initialization              -> ALSParam i t     -- ^ optimization parameters              -> [NArray i t] -- ^ source (also factorized)@@ -245,7 +245,7 @@ initFactorsSeq rs a pairs b | ok = as                             | otherwise = error "solveFactors index pairs"   where-    (ia,ib) = unzip (map (\[x,y]->([x],[y])) (words pairs))+    (ia,ib) = unzip (map sep (words pairs))     ic = intersect (namesR a) (namesR b)     ok = sort (namesR b\\ic) == sort ib && sort (namesR a\\ic) == sort ia     db = selDims (dims b) ib@@ -264,7 +264,7 @@ -- [\"pi\",\"qj\", \"rk\", etc.], we try to compute linear transformations -- x!\"pi\", y!\"pi\", z!\"rk\", etc. such that product [a,x,y,z,...] == 0. solveFactorsH-  :: (Coord t, Random t, Compat i, Num (NArray i t))+  :: (Coord t, Random t, Compat i, Num (NArray i t), Show (NArray i t))      => Int -- ^ seed for random initialization      -> ALSParam  i t    -- ^ optimization parameters      -> [NArray i t] -- ^ coefficient array (a), (also factorized)@@ -274,7 +274,7 @@     mlSolveH params a (initFactorsHRandom seed (smartProduct a) pairs)  initFactorsHSeq rs a pairs = as where-    (ir,it) = unzip (map (\[x,y]->([x],[y])) (words pairs))+    (ir,it) = unzip (map sep (words pairs))     nr = map (flip size a) ir     nt = map (flip size a) it     ts = takes (zipWith (*) nr nt) rs@@ -282,6 +282,9 @@     f c i1 i2 d1 d2 = (mkNArray (map opos [d1,d2]) (fromList c)) `renameO` [i1,i2]  initFactorsHRandom seed a pairs = initFactorsHSeq (randomRs (-1,1) (mkStdGen seed)) a pairs++sep [a,b] = ([a],[b])+sep _ = error "impossible pattern in hTensor initFactors"  ---------------------------------- 

@@ -68,8 +68,10 @@ -- For instance, @t >\@> \"pi qj\"@ changes index \"p\" to \"i\" and \"q\" to \"j\". (!>) :: (Compat i, Coord t) => NArray i t -> [Char] -> NArray i t infixl 9 !>-t !> s = renameExplicit (map (\[a,b]->([a],[b])) (words s)) t-+t !> s = renameExplicit (map f (words s)) t+  where+    f [a,b] = ([a],[b])+    f _ = error "impossible pattern in hTensor (!>)"  -- | Rename indices in alphabetical order. Equal indices of compatible type are contracted out. renameO :: (Coord t, Compat i)