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Julia interface to the GNU Scientific Library (GSL)
Julia Python
Latest commit 8456534 May 23, 2016 @AndyGreenwell AndyGreenwell Support for multimin functionality
Add multimin_fminimizer_set, fix multimin_fdf_minimizer_iterate, change appropriate underscore files to non-underscore within __FILELIST.jl

README.md

GSL.jl

GSL GSL Build Status Coverage Status codecov.io

Julia interface to the GNU Scientific Library (GSL)

Jiahao Chen

Licensed under GPLv3

Tested with libgsl 1.16

How to install

In Julia:

Pkg.add("GSL")

How to use

This package aims to provide wrappers to all documented functions and structs in the GSL manual. For GSL functions, the gsl_ prefix is not necessary in the name. More information is available below.

Example:

    using GSL
    x = randn()
    sf_hyperg_U(-1.0, -1.0, x) - (1 + x)
    #Answer: 0.0

Translated examples from the GSL documentation are available in examples/.

Convenience methods provided

Roots of polynomials

    roots{T<:Real}(c::Vector{T}, realOnly::Bool) -> Vector{Complex128}

Finds the roots of the polynomial with real coefficients c [ 0 = \sum_{i=1}^{length(c)} c_i z^{i-1} ] The coefficients are returned in ascending order of the power If the degree of the polynomial is <= 3, then realOnly=true finds only the real roots.

Special functions

Hypergeometric functions

    hypergeom(a, b, x::Float64) -> Float64

Computes the appropriate hypergeometric pFq function, where p and q are the lengths of the input vectors a and b respectively. Singleton a and/or b may be specified as scalars, and length-0 a and/or b may be input as simply []. Supported values of (p, q) are (0, 0), (0, 1), (1, 1), (2, 0) and (2, 1). This only calls the floating-point versions of the GSL functions gsl_sf_hyperg_?F? (GSL manual, Section 7.24)

    hypergeom_e(a, b, x::Float64) -> (Float64, Float64)

An error-estimating version of hypergeom.

Test functions

    @sf_test(sf, args...)

Macro to help test equality of a function and its error-propagating variant. Requires Base.Test. Example:

    x = randn()
    @eval @sf_test sf_dawson $x

Current status

What is available

  • Functions: all except the ones described below. Functions have the gsl_ prefix stripped.
    • Most special functions: All except for the following categories:
      • Some array-valued functions sf_*_array
        • Available: sf_bessel_*_array, sf_gegenpoly_array.
        • Not available: all others. The wrappers do not currently work.
      • Not available: sf_*_e10_e that return the sf_result_e10 struct. (Currently returns bus error.)
  • All documented gsl_* structs - These do NOT have the gsl_ prefix stripped.
  • GSL_* constants: strip GSL_ and GSL_CONST_ prefixes
  • GSL_* macros: Most available but untested.

What is not available

  • GSL's BLAS and CBLAS wrappers blas_*, cblas_*. Use Julia's interface instead.
  • Data I/O functions, such as *_fprintf and *_fscanf. Work in progress. Wrappers to these functions exist but most likely won't work
  • Row and column views of matrices, matrix_row* and matrix_column* (Sec. 8.4.6)
  • GSL_* macros:
    • COMPLEX_AT, COMPLEX_FLOAT_AT, COMPLEX_LONG_DOUBLE_AT
    • SF_RESULT_SET and others in gsl_sf_result.h
    • SET_COMPLEX, SET_REAL, SET_IMAG, SET_COMPLEX_PACKED

Current tests

  • Special functions
    • Basic tests comparing equality of basic and error-propagating special functions
    • Some identity tests for hypergeometric functions
    • Available but untested:
      • sf_bessel_sequence_Jnu_e, sf_bessel_Jnu
      • sf_coulomb_CL_e, sf_coulomb_CL_e
      • sf_coupling_6j, sf_elljac_e
      • Mathieu Functions (Section 7.26). (Needs convenience function)
      • Trigonometric Functions for Complex Arguments (Section 7.31)
      • Conversion Functions (Section 7.31.4)
      • Restriction Functions (Section 7.31.5)
      • Trigonometric Functions With Error Estimates (Section 7.31.6)
  • All other functions are untested
  • All macros are untested

How you can help

The wrappers are automatically generated using util/makewrapper.py.

  1. Test function wrappers for correctness.
  2. Write convenience methods to further wrap the function calls with a Julia- friendly syntax.
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