hmatrix

I am having a hard time optimizing a program that is relying on ad s conjugateGradientDescent function for most of it's work. Basically my code is a translation of an old papers code that is written in Matlab and C. I have not measured it, but that code is running at several iterations per second. Mine is in the order of minutes per iteration ... The code is available in this repositories: https://github.com/fhaust/aer https://github.com/fhaust/aer-utils The code in question can be run by following these commands: $ cd aer-utils $ cabal sandbox init $ cabal sandbox add-source ../aer $ cabal

Is there a standard Haskell equivalent to NumPy's argsort function? I'm using HMatrix and, so, would like a function compatible with Vector R which is an alias for Data.Vector.Storable.Vector Double . The argSort function below is the implementation I'm currently using: {-# LANGUAGE NoImplicitPrelude #-} module Main where import qualified Data.List as L import qualified Data.Vector as V import qualified Data.Vector.Storable as VS import Prelude (($), Double, IO, Int, compare, print, snd) a :: VS.Vector Double a = VS.fromList [40.0, 20.0, 10.0, 11.0] argSort :: VS.Vector Double -> V.Vector Int

Sooooo ... as it turns out going from fake matrices to hmatrix datatypes turns out to be nontrivial :) Preamble for reference: {-# LANGUAGE RankNTypes #-} {-# LANGUAGE ParallelListComp #-} {-# LANGUAGE ScopedTypeVariables #-} {-# LANGUAGE TypeFamilies #-} {-# LANGUAGE FlexibleContexts #-} import Numeric.LinearAlgebra.HMatrix import Numeric.AD reconstruct :: (Container Vector a, Num (Vector a)) => [a] -> [Matrix a] -> Matrix a reconstruct as φs = sum [ a `scale` φ | a <- as | φ <- φs ] preserveInfo :: (Container Vector a, Num (Vector a)) => Matrix a -> [a] -> [Matrix a] -> a preserveInfo img as