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ghc-statistics-linreg
ghc-statistics-linreg.spec
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File ghc-statistics-linreg.spec of Package ghc-statistics-linreg
# # spec file for package ghc-statistics-linreg # # Copyright (c) 2020 SUSE LLC # # All modifications and additions to the file contributed by third parties # remain the property of their copyright owners, unless otherwise agreed # upon. The license for this file, and modifications and additions to the # file, is the same license as for the pristine package itself (unless the # license for the pristine package is not an Open Source License, in which # case the license is the MIT License). An "Open Source License" is a # license that conforms to the Open Source Definition (Version 1.9) # published by the Open Source Initiative. # Please submit bugfixes or comments via https://bugs.opensuse.org/ # %global pkg_name statistics-linreg Name: ghc-%{pkg_name} Version: 0.3 Release: 0 Summary: Linear regression between two samples, based on the 'statistics' package License: MIT URL: https://hackage.haskell.org/package/%{pkg_name} Source0: https://hackage.haskell.org/package/%{pkg_name}-%{version}/%{pkg_name}-%{version}.tar.gz BuildRequires: ghc-Cabal-devel BuildRequires: ghc-MonadRandom-devel BuildRequires: ghc-random-devel BuildRequires: ghc-random-shuffle-devel BuildRequires: ghc-rpm-macros BuildRequires: ghc-safe-devel BuildRequires: ghc-statistics-devel BuildRequires: ghc-vector-devel ExcludeArch: %{ix86} %description Provides functions to perform a linear regression between 2 samples, see the documentation of the linearRegression functions. This library is based on the 'statistics' package. * 0.3: you can now use all functions on any instance of the Vector class (not just unboxed vectors). * 0.2.4: added distribution estimations for standard regression parameters. * 0.2.3: added robust-fit support. * 0.2.2: added the Total-Least-Squares version and made some refactoring to eliminate code duplication * 0.2.1: added the r-squared version and improved the performances. Code sample: > import qualified Data.Vector.Unboxed as U > > test :: Int -> IO () > test k = do > let n = 10000000 > let a = k*n + 1 > let b = (k+1)*n > let xs = U.fromList [a..b] > let ys = U.map (x -> x*100 + 2000) xs > -- thus 100 and 2000 are the alpha and beta we want > putStrLn "linearRegression:" > print $ linearRegression xs ys The r-squared and Total-Least-Squares versions work the same way. %package devel Summary: Haskell %{pkg_name} library development files Requires: %{name} = %{version}-%{release} Requires: ghc-compiler = %{ghc_version} Requires(post): ghc-compiler = %{ghc_version} Requires(postun): ghc-compiler = %{ghc_version} %description devel This package provides the Haskell %{pkg_name} library development files. %prep %autosetup -n %{pkg_name}-%{version} %build %ghc_lib_build %install %ghc_lib_install %post devel %ghc_pkg_recache %postun devel %ghc_pkg_recache %files -f %{name}.files %license LICENSE %files devel -f %{name}-devel.files %changelog
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