Portability | uses ffi |
---|---|
Stability | provisional |
Maintainer | Alberto Ruiz (aruiz at um dot es) |
Numeric.GSL.Root
Description
Multidimensional root finding.
http://www.gnu.org/software/gsl/manual/html_node/Multidimensional-Root_002dFinding.html
The example in the GSL manual:
import Numeric.GSL import Numeric.LinearAlgebra(format) import Text.Printf(printf) rosenbrock a b [x,y] = [ a*(1-x), b*(y-x^2) ] disp = putStrLn . format " " (printf "%.3f") main = do let (sol,path) = root Hybrids 1E-7 30 (rosenbrock 1 10) [-10,-5] print sol disp path > main [1.0,1.0] 0.000 -10.000 -5.000 11.000 -1050.000 1.000 -3.976 24.827 4.976 90.203 2.000 -3.976 24.827 4.976 90.203 3.000 -3.976 24.827 4.976 90.203 4.000 -1.274 -5.680 2.274 -73.018 5.000 -1.274 -5.680 2.274 -73.018 6.000 0.249 0.298 0.751 2.359 7.000 0.249 0.298 0.751 2.359 8.000 1.000 0.878 -0.000 -1.218 9.000 1.000 0.989 -0.000 -0.108 10.000 1.000 1.000 0.000 0.000
Documentation
Arguments
:: RootMethod | |
-> Double | maximum residual |
-> Int | maximum number of iterations allowed |
-> ([Double] -> [Double]) | function to minimize |
-> [Double] | starting point |
-> ([Double], Matrix Double) | solution vector and optimization path |
Nonlinear multidimensional root finding using algorithms that do not require any derivative information to be supplied by the user. Any derivatives needed are approximated by finite differences.
data RootMethod Source
Instances
Arguments
:: RootMethodJ | |
-> Double | maximum residual |
-> Int | maximum number of iterations allowed |
-> ([Double] -> [Double]) | function to minimize |
-> ([Double] -> [[Double]]) | Jacobian |
-> [Double] | starting point |
-> ([Double], Matrix Double) | solution vector and optimization path |
Nonlinear multidimensional root finding using both the function and its derivatives.
data RootMethodJ Source
Instances