//
// A rust binding for the GSL library by Guillaume Gomez (guillaume1.gomez@gmail.com)
//

#![allow(clippy::upper_case_acronyms)]

use crate::enums;
use crate::Value;
use ffi::FFI;

ffi_wrapper!(IntegrationFixedType, *const sys::gsl_integration_fixed_type);

impl IntegrationFixedType {
    #[doc(alias = "gsl_integration_fixed_legendre")]
    pub fn legendre() -> IntegrationFixedType {
        ffi_wrap!(gsl_integration_fixed_legendre)
    }
    #[doc(alias = "gsl_integration_fixed_chebyshev")]
    pub fn chebyshev() -> IntegrationFixedType {
        ffi_wrap!(gsl_integration_fixed_chebyshev)
    }
    #[doc(alias = "gsl_integration_fixed_chebyshev2")]
    pub fn chebyshev2() -> IntegrationFixedType {
        ffi_wrap!(gsl_integration_fixed_chebyshev2)
    }
    #[doc(alias = "gsl_integration_fixed_gegenbauer")]
    pub fn gegenbauer() -> IntegrationFixedType {
        ffi_wrap!(gsl_integration_fixed_gegenbauer)
    }
    #[doc(alias = "gsl_integration_fixed_jacobi")]
    pub fn jacobi() -> IntegrationFixedType {
        ffi_wrap!(gsl_integration_fixed_jacobi)
    }
    #[doc(alias = "gsl_integration_fixed_laguerre")]
    pub fn laguerre() -> IntegrationFixedType {
        ffi_wrap!(gsl_integration_fixed_laguerre)
    }
    #[doc(alias = "gsl_integration_fixed_hermite")]
    pub fn hermite() -> IntegrationFixedType {
        ffi_wrap!(gsl_integration_fixed_hermite)
    }
    #[doc(alias = "gsl_integration_fixed_exponential")]
    pub fn exponential() -> IntegrationFixedType {
        ffi_wrap!(gsl_integration_fixed_exponential)
    }
    #[doc(alias = "gsl_integration_fixed_rational")]
    pub fn rational() -> IntegrationFixedType {
        ffi_wrap!(gsl_integration_fixed_rational)
    }
}

ffi_wrapper!(
    IntegrationFixedWorkspace,
    *mut sys::gsl_integration_fixed_workspace,
    gsl_integration_fixed_free
);

impl IntegrationFixedWorkspace {
    #[doc(alias = "gsl_integration_fixed_alloc")]
    pub fn new(
        type_: IntegrationFixedType,
        n: usize,
        a: f64,
        b: f64,
        alpha: f64,
        beta: f64,
    ) -> Option<IntegrationFixedWorkspace> {
        let tmp = unsafe {
            sys::gsl_integration_fixed_alloc(type_.unwrap_shared(), n, a, b, alpha, beta)
        };

        if tmp.is_null() {
            None
        } else {
            Some(Self::wrap(tmp))
        }
    }

    #[doc(alias = "gsl_integration_fixed_n")]
    pub fn n(&self) -> usize {
        unsafe { sys::gsl_integration_fixed_n(self.unwrap_shared()) }
    }

    #[doc(alias = "gsl_integration_fixed_nodes")]
    pub fn nodes(&self) -> Option<&[f64]> {
        let tmp = unsafe { sys::gsl_integration_fixed_nodes(self.unwrap_shared()) };
        if tmp.is_null() {
            return None;
        }
        unsafe { Some(::std::slice::from_raw_parts(tmp, self.n())) }
    }

    #[doc(alias = "gsl_integration_fixed_weights")]
    pub fn weights(&self) -> Option<&[f64]> {
        let tmp = unsafe { sys::gsl_integration_fixed_weights(self.unwrap_shared()) };
        if tmp.is_null() {
            return None;
        }
        unsafe { Some(::std::slice::from_raw_parts(tmp, self.n())) }
    }

    #[doc(alias = "gsl_integration_fixed")]
    pub fn fixed<F: Fn(f64) -> f64>(&self, f: F) -> (::Value, f64) {
        let mut result = 0.;
        let function = wrap_callback!(f, F);

        let ret =
            unsafe { sys::gsl_integration_fixed(&function, &mut result, self.unwrap_shared()) };
        (::Value::from(ret), result)
    }
}

ffi_wrapper!(IntegrationWorkspace, *mut sys::gsl_integration_workspace, gsl_integration_workspace_free,
"The QAG algorithm is a simple adaptive integration procedure. The integration region is divided
into subintervals, and on each iteration the subinterval with the largest estimated error is
bisected. This reduces the overall error rapidly, as the subintervals become concentrated
around local difficulties in the integrand. These subintervals are managed by a
gsl_integration_workspace struct, which handles the memory for the subinterval ranges, results
and error estimates.");

impl IntegrationWorkspace {
    /// This function allocates a workspace sufficient to hold n double precision intervals, their
    /// integration results and error estimates. One workspace may be used multiple times as all
    /// necessary reinitialization is performed automatically by the integration routines.
    #[doc(alias = "gsl_integration_workspace_alloc")]
    pub fn new(n: usize) -> Option<IntegrationWorkspace> {
        let tmp = unsafe { sys::gsl_integration_workspace_alloc(n) };

        if tmp.is_null() {
            None
        } else {
            Some(Self::wrap(tmp))
        }
    }

    pub fn limit(&self) -> usize {
        unsafe { (*self.unwrap_shared()).limit }
    }
    pub fn size(&self) -> usize {
        unsafe { (*self.unwrap_shared()).size }
    }
    pub fn nrmax(&self) -> usize {
        unsafe { (*self.unwrap_shared()).nrmax }
    }
    pub fn i(&self) -> usize {
        unsafe { (*self.unwrap_shared()).i }
    }
    pub fn maximum_level(&self) -> usize {
        unsafe { (*self.unwrap_shared()).maximum_level }
    }

    /// This function applies an integration rule adaptively until an estimate of the integral of f
    /// over (a,b) is achieved within the desired absolute and relative error limits, epsabs and
    /// epsrel. The function returns the final approximation, result, and an estimate of the
    /// absolute error, abserr. The integration rule is determined by the value of key, which should
    /// be chosen from the following symbolic names,
    ///
    /// GSL_INTEG_GAUSS15  (key = 1)
    ///
    /// GSL_INTEG_GAUSS21  (key = 2)
    ///
    /// GSL_INTEG_GAUSS31  (key = 3)
    ///
    /// GSL_INTEG_GAUSS41  (key = 4)
    ///
    /// GSL_INTEG_GAUSS51  (key = 5)
    ///
    /// GSL_INTEG_GAUSS61  (key = 6)
    ///
    /// corresponding to the 15f64, 21f64, 31f64, 41f64, 51 and 61 point Gauss-Kronrod rules. The
    /// higher-order rules give better accuracy for smooth functions, while lower-order rules save
    /// time when the function contains local difficulties, such as discontinuities.
    ///
    /// On each iteration the adaptive integration strategy bisects the interval with the largest
    /// error estimate. The subintervals and their results are stored in the memory provided by
    /// workspace. The maximum number of subintervals is given by limit, which may not exceed the
    /// allocated size of the workspace.
    ///
    /// Returns `(result, abs_err)`.
    #[doc(alias = "gsl_integration_qag")]
    pub fn qag<F: Fn(f64) -> f64>(
        &mut self,
        f: F,
        a: f64,
        b: f64,
        epsabs: f64,
        epsrel: f64,
        limit: usize,
        key: enums::GaussKronrodRule,
    ) -> (::Value, f64, f64) {
        let mut result = 0.;
        let mut abs_err = 0.;
        let function = wrap_callback!(f, F);

        let ret = unsafe {
            sys::gsl_integration_qag(
                &function,
                a,
                b,
                epsabs,
                epsrel,
                limit,
                key.into(),
                self.unwrap_unique(),
                &mut result,
                &mut abs_err,
            )
        };
        (::Value::from(ret), result, abs_err)
    }

    /// This function applies the Gauss-Kronrod 21-point integration rule adaptively until an
    /// estimate of the integral of f over (a,b) is achieved within the desired absolute and
    /// relative error limits, epsabs and epsrel. The results are extrapolated using the
    /// epsilon-algorithm, which accelerates the convergence of the integral in the presence of
    /// discontinuities and integrable singularities. The function returns the final approximation
    /// from the extrapolation, result, and an estimate of the absolute error, abserr. The
    /// subintervals and their results are stored in the memory provided by workspace. The maximum
    /// number of subintervals is given by limit, which may not exceed the allocated size of the
    /// workspace.
    ///
    /// Returns `(result, abs_err)`.
    #[doc(alias = "gsl_integration_qags")]
    pub fn qags<F: Fn(f64) -> f64>(
        &mut self,
        f: F,
        a: f64,
        b: f64,
        epsabs: f64,
        epsrel: f64,
        limit: usize,
    ) -> (::Value, f64, f64) {
        let mut result = 0.;
        let mut abs_err = 0.;
        let function = wrap_callback!(f, F);

        let ret = unsafe {
            sys::gsl_integration_qags(
                &function,
                a,
                b,
                epsabs,
                epsrel,
                limit,
                self.unwrap_unique(),
                &mut result,
                &mut abs_err,
            )
        };
        (::Value::from(ret), result, abs_err)
    }

    /// This function applies the adaptive integration algorithm QAGS taking account of the
    /// user-supplied locations of singular points. The array pts of length npts should contain the
    /// endpoints of the integration ranges defined by the integration region and locations of the
    /// singularities.
    ///
    /// For example, to integrate over the region (a,b) with break-points at x_1, x_2, x_3
    /// (where a < x_1 < x_2 < x_3 < b) the following pts array should be used
    ///
    /// ```text
    /// pts[0] = a
    /// pts[1] = x_1
    /// pts[2] = x_2
    /// pts[3] = x_3
    /// pts[4] = b
    /// with npts = 5.
    /// ```
    ///
    /// If you know the locations of the singular points in the integration region then this routine
    /// will be faster than QAGS.
    ///
    /// Returns `(result, abs_err)`.
    #[doc(alias = "gsl_integration_qagp")]
    pub fn qagp<F: Fn(f64) -> f64>(
        &mut self,
        f: F,
        pts: &mut [f64],
        epsabs: f64,
        epsrel: f64,
        limit: usize,
    ) -> (::Value, f64, f64) {
        let mut result = 0.;
        let mut abs_err = 0.;
        let function = wrap_callback!(f, F);

        let ret = unsafe {
            sys::gsl_integration_qagp(
                &function,
                pts.as_mut_ptr(),
                pts.len() as _,
                epsabs,
                epsrel,
                limit,
                self.unwrap_unique(),
                &mut result,
                &mut abs_err,
            )
        };
        (::Value::from(ret), result, abs_err)
    }

    /// This function computes the integral of the function f over the infinite interval
    /// `(-\infty,+\infty)`. The integral is mapped onto the semi-open interval `(0,1]` using the
    /// transformation:
    ///
    /// ```text
    /// x = (1-t)/t,
    ///
    /// \int_{-\infty}^{+\infty} dx f(x) =
    ///      \int_0^1 dt (f((1-t)/t) + f((-1+t)/t))/t^2.
    /// ```
    ///
    /// It is then integrated using the QAGS algorithm. The normal 21-point Gauss-Kronrod rule of
    /// QAGS is replaced by a 15-point rule, because the transformation can generate an integrable
    /// singularity at the origin. In this case a lower-order rule is more efficient.
    ///
    /// Returns `(result, abs_err)`.
    #[doc(alias = "gsl_integration_qagi")]
    pub fn qagi<F: Fn(f64) -> f64>(
        &mut self,
        f: F,
        epsabs: f64,
        epsrel: f64,
        limit: usize,
    ) -> (::Value, f64, f64) {
        let mut result = 0.;
        let mut abs_err = 0.;
        let mut function = wrap_callback!(f, F);

        let ret = unsafe {
            sys::gsl_integration_qagi(
                &mut function,
                epsabs,
                epsrel,
                limit,
                self.unwrap_unique(),
                &mut result,
                &mut abs_err,
            )
        };
        (::Value::from(ret), result, abs_err)
    }

    /// This function computes the integral of the function f over the semi-infinite interval
    /// `(a,+\infty)`. The integral is mapped onto the semi-open interval `(0,1]` using the
    /// transformation:
    ///
    /// ```text
    /// x = a + (1-t)/t,
    ///
    /// \int_{a}^{+\infty} dx f(x) =
    ///      \int_0^1 dt f(a + (1-t)/t)/t^2
    /// ```
    ///
    /// and then integrated using the QAGS algorithm.
    ///
    /// Returns `(result, abs_err)`.
    #[doc(alias = "gsl_integration_qagiu")]
    pub fn qagiu<F: Fn(f64) -> f64>(
        &mut self,
        f: F,
        a: f64,
        epsabs: f64,
        epsrel: f64,
        limit: usize,
    ) -> (::Value, f64, f64) {
        let mut result = 0.;
        let mut abs_err = 0.;
        let mut function = wrap_callback!(f, F);

        let ret = unsafe {
            sys::gsl_integration_qagiu(
                &mut function,
                a,
                epsabs,
                epsrel,
                limit,
                self.unwrap_unique(),
                &mut result,
                &mut abs_err,
            )
        };
        (::Value::from(ret), result, abs_err)
    }

    /// This function computes the integral of the function f over the semi-infinite interval
    /// `(-\infty,b)`. The integral is mapped onto the semi-open interval `(0,1]` using the
    /// transformation:
    ///
    /// ```text
    ///  x = b - (1-t)/t,
    ///
    /// \int_{-\infty}^{b} dx f(x) =
    ///      \int_0^1 dt f(b - (1-t)/t)/t^2
    /// ```
    ///
    /// and then integrated using the QAGS algorithm.
    ///
    /// Returns `(result, abs_err)`.
    #[doc(alias = "gsl_integration_qagil")]
    pub fn qagil<F: Fn(f64) -> f64>(
        &mut self,
        f: F,
        b: f64,
        epsabs: f64,
        epsrel: f64,
        limit: usize,
    ) -> (::Value, f64, f64) {
        let mut result = 0.;
        let mut abs_err = 0.;
        let mut function = wrap_callback!(f, F);

        let ret = unsafe {
            sys::gsl_integration_qagil(
                &mut function,
                b,
                epsabs,
                epsrel,
                limit,
                self.unwrap_unique(),
                &mut result,
                &mut abs_err,
            )
        };
        (::Value::from(ret), result, abs_err)
    }

    /// This function computes the Cauchy principal value of the integral of f over `(a,b)`, with a
    /// singularity at c,
    ///
    /// ```text
    /// I = \int_a^b dx f(x) / (x - c)
    /// ```
    ///
    /// The adaptive bisection algorithm of QAG is used, with modifications to ensure that
    /// subdivisions do not occur at the singular point x = c.
    ///
    /// When a subinterval contains the point x = c or is close to it then a special 25-point
    /// modified Clenshaw-Curtis rule is used to control the singularity. Further away from the
    /// singularity the algorithm uses an ordinary 15-point Gauss-Kronrod integration rule.
    ///
    /// Returns `(result, abs_err)`.
    #[doc(alias = "gsl_integration_qawc")]
    pub fn qawc<F: Fn(f64) -> f64>(
        &mut self,
        f: F,
        a: f64,
        b: f64,
        c: f64,
        epsabs: f64,
        epsrel: f64,
        limit: usize,
    ) -> (::Value, f64, f64) {
        let mut result = 0.;
        let mut abs_err = 0.;
        let mut function = wrap_callback!(f, F);

        let ret = unsafe {
            sys::gsl_integration_qawc(
                &mut function,
                a,
                b,
                c,
                epsabs,
                epsrel,
                limit,
                self.unwrap_unique(),
                &mut result,
                &mut abs_err,
            )
        };
        (::Value::from(ret), result, abs_err)
    }
}

ffi_wrapper!(
    IntegrationQawsTable,
    *mut sys::gsl_integration_qaws_table,
    gsl_integration_qaws_table_free,
    "The QAWS algorithm is designed for integrands with algebraic-logarithmic singularities at the
end-points of an integration region. In order to work efficiently the algorithm requires a
precomputed table of Chebyshev moments."
);

impl IntegrationQawsTable {
    /// This function allocates space for a gsl_integration_qaws_table struct describing a singular
    /// weight function W(x) with the parameters `alpha`, `beta`, `mu` and `nu`,
    ///
    /// ```text
    /// W(x) = (x-a)^alpha (b-x)^beta log^mu (x-a) log^nu (b-x)
    /// ```
    ///
    /// where `alpha > -1f64`, `beta > -1f64`, and `mu = 0, 1`, `nu = 0, 1`. The weight function can
    /// take four different forms depending on the values of `mu` and `nu`,
    ///
    /// ```text
    /// W(x) = (x-a)^alpha (b-x)^beta                   (mu = 0, nu = 0)
    /// W(x) = (x-a)^alpha (b-x)^beta log(x-a)          (mu = 1, nu = 0)
    /// W(x) = (x-a)^alpha (b-x)^beta log(b-x)          (mu = 0, nu = 1)
    /// W(x) = (x-a)^alpha (b-x)^beta log(x-a) log(b-x) (mu = 1, nu = 1)
    /// ```
    ///
    /// The singular points (a,b) do not have to be specified until the integral is computed, where
    /// they are the endpoints of the integration range.
    ///
    /// The function returns a pointer to the newly allocated table gsl_integration_qaws_table if no
    /// errors were detected, and 0 in the case of error.
    #[doc(alias = "gsl_integration_qaws_table_alloc")]
    pub fn new(alpha: f64, beta: f64, mu: i32, nu: i32) -> Option<IntegrationQawsTable> {
        let tmp = unsafe { sys::gsl_integration_qaws_table_alloc(alpha, beta, mu, nu) };

        if tmp.is_null() {
            None
        } else {
            Some(Self::wrap(tmp))
        }
    }

    /// This function modifies the parameters (\alpha, \beta, \mu, \nu)
    #[doc(alias = "gsl_integration_qaws_table_set")]
    pub fn set(&mut self, alpha: f64, beta: f64, mu: i32, nu: i32) -> ::Value {
        ::Value::from(unsafe {
            sys::gsl_integration_qaws_table_set(self.unwrap_unique(), alpha, beta, mu, nu)
        })
    }

    /// This function computes the integral of the function f(x) over the interval (a,b) with the
    /// singular weight function `(x-a)^\alpha (b-x)^\beta \log^\mu (x-a) \log^\nu (b-x)`. The
    /// parameters of the weight function (\alpha, \beta, \mu, \nu) are taken from the table self.
    /// The integral is,
    ///
    /// ```text
    /// I = \int_a^b dx f(x) (x-a)^alpha (b-x)^beta log^mu (x-a) log^nu (b-x).
    /// ```
    ///
    /// The adaptive bisection algorithm of QAG is used. When a subinterval contains one of the
    /// endpoints then a special 25-point modified Clenshaw-Curtis rule is used to control the
    /// singularities. For subintervals which do not include the endpoints an ordinary 15-point
    /// Gauss-Kronrod integration rule is used.
    ///
    /// Returns `(result, abs_err)`
    #[doc(alias = "gsl_integration_qaws")]
    pub fn qaws<F: Fn(f64) -> f64>(
        &mut self,
        f: F,
        a: f64,
        b: f64,
        epsabs: f64,
        epsrel: f64,
        limit: usize,
        workspace: &mut IntegrationWorkspace,
    ) -> (::Value, f64, f64) {
        let mut result = 0.;
        let mut abs_err = 0.;
        let mut function = wrap_callback!(f, F);

        let ret = unsafe {
            sys::gsl_integration_qaws(
                &mut function,
                a,
                b,
                self.unwrap_unique(),
                epsabs,
                epsrel,
                limit,
                workspace.unwrap_unique(),
                &mut result,
                &mut abs_err,
            )
        };
        (::Value::from(ret), result, abs_err)
    }
}

ffi_wrapper!(
    IntegrationQawoTable,
    *mut sys::gsl_integration_qawo_table,
    gsl_integration_qawo_table_free,
    "The QAWO algorithm is designed for integrands with an oscillatory factor, `sin(omega x)` or
`cos(omega x)`. In order to work efficiently the algorithm requires a table of Chebyshev moments
which must be pre-computed with calls to the functions below."
);

impl IntegrationQawoTable {
    /// This function allocates space for a gsl_integration_qawo_table struct and its associated
    /// workspace describing a sine or cosine weight function W(x) with the parameters (\omega, L),
    ///
    /// ```text
    /// W(x) = sin(omega x)
    /// W(x) = cos(omega x)
    /// ```
    ///
    /// The parameter L must be the length of the interval over which the function will be
    /// integrated L = b - a. The choice of sine or cosine is made with the parameter sine which
    /// should be chosen from one of the two following symbolic values:
    ///
    /// ```text
    /// ::Cosine
    /// ::IntegrationQawo::Sine
    /// ```
    ///
    /// The gsl_integration_qawo_table is a table of the trigonometric coefficients required in the
    /// integration process. The parameter n determines the number of levels of coefficients that
    /// are computed. Each level corresponds to one bisection of the interval L, so that n levels
    /// are sufficient for subintervals down to the length L/2^n. The integration routine
    /// gsl_integration_qawo returns the error ::Table if the number of levels is insufficient for
    /// the requested accuracy.
    #[doc(alias = "gsl_integration_qawo_table_alloc")]
    pub fn new(
        omega: f64,
        l: f64,
        sine: ::IntegrationQawo,
        n: usize,
    ) -> Option<IntegrationQawoTable> {
        let tmp = unsafe { sys::gsl_integration_qawo_table_alloc(omega, l, sine.into(), n) };

        if tmp.is_null() {
            None
        } else {
            Some(Self::wrap(tmp))
        }
    }

    /// This function changes the parameters omega, L and sine of the existing self workspace.
    #[doc(alias = "gsl_integration_qawo_table_set")]
    pub fn set(&mut self, omega: f64, l: f64, sine: ::IntegrationQawo) -> ::Value {
        ::Value::from(unsafe {
            sys::gsl_integration_qawo_table_set(self.unwrap_unique(), omega, l, sine.into())
        })
    }

    /// This function allows the length parameter l of the self workspace to be changed.
    #[doc(alias = "gsl_integration_qawo_table_set_length")]
    pub fn set_length(&mut self, l: f64) -> ::Value {
        ::Value::from(unsafe {
            sys::gsl_integration_qawo_table_set_length(self.unwrap_unique(), l)
        })
    }

    /// This function uses an adaptive algorithm to compute the integral of f over (a,b) with the
    /// weight function \sin(\omega x) or \cos(\omega x) defined by the table `wf`,
    ///
    /// I = \int_a^b dx f(x) sin(omega x)
    /// I = \int_a^b dx f(x) cos(omega x)
    ///
    /// The results are extrapolated using the epsilon-algorithm to accelerate the convergence of
    /// the integral. The function returns the final approximation from the extrapolation, result,
    /// and an estimate of the absolute error, abserr. The subintervals and their results are
    /// stored in the memory provided by workspace. The maximum number of subintervals is given by
    /// limit, which may not exceed the allocated size of the workspace.
    ///
    /// Those subintervals with “large” widths d where d\omega > 4 are computed using a 25-point
    /// Clenshaw-Curtis integration rule, which handles the oscillatory behavior. Subintervals with
    /// a "small" widths where d\omega < 4 are computed using a 15-point Gauss-Kronrod integration.
    ///
    /// Returns `(result, abserr)`.
    #[doc(alias = "gsl_integration_qawo")]
    pub fn qawo<F: Fn(f64) -> f64>(
        &mut self,
        f: F,
        a: f64,
        epsabs: f64,
        epsrel: f64,
        limit: usize,
        workspace: &mut IntegrationWorkspace,
    ) -> (::Value, f64, f64) {
        let mut function = wrap_callback!(f, F);
        let mut result = 0.;
        let mut abserr = 0.;

        let ret = unsafe {
            sys::gsl_integration_qawo(
                &mut function,
                a,
                epsabs,
                epsrel,
                limit,
                workspace.unwrap_unique(),
                self.unwrap_unique(),
                &mut result,
                &mut abserr,
            )
        };
        (::Value::from(ret), result, abserr)
    }
}

ffi_wrapper!(CquadWorkspace, *mut sys::gsl_integration_cquad_workspace, gsl_integration_cquad_workspace_free,
"CQUAD is a new doubly-adaptive general-purpose quadrature routine which can handle most types of
singularities, non-numerical function values such as Inf or NaN, as well as some divergent
integrals. It generally requires more function evaluations than the integration routines in
QUADPACK, yet fails less often for difficult integrands.

The underlying algorithm uses a doubly-adaptive scheme in which Clenshaw-Curtis quadrature rules
of increasing degree are used to compute the integral in each interval. The L_2-norm of the
difference between the underlying interpolatory polynomials of two successive rules is used as
an error estimate. The interval is subdivided if the difference between two successive rules is
too large or a rule of maximum degree has been reached.");

impl CquadWorkspace {
    /// This function allocates a workspace sufficient to hold the data for n intervals. The number
    /// n is not the maximum number of intervals that will be evaluated. If the workspace is full,
    /// intervals with smaller error estimates will be discarded. A minimum of 3 intervals
    /// is required and for most functions, a workspace of size 100 is sufficient.
    #[doc(alias = "gsl_integration_cquad_workspace_alloc")]
    pub fn new(n: usize) -> Option<CquadWorkspace> {
        let tmp = unsafe { sys::gsl_integration_cquad_workspace_alloc(n) };

        if tmp.is_null() {
            None
        } else {
            Some(Self::wrap(tmp))
        }
    }

    /// This function computes the integral of f over (a,b) within the desired absolute and relative
    /// error limits, epsabs and epsrel using the CQUAD algorithm. The function returns the final
    /// approximation, result, an estimate of the absolute error, abserr, and the number of function
    /// evaluations required, nevals.
    ///
    /// The CQUAD algorithm divides the integration region into subintervals, and in each iteration,
    /// the subinterval with the largest estimated error is processed. The algorithm uses
    /// Clenshaw-Curits quadrature rules of degree 4, 8, 16 and 32 over 5, 9, 17 and 33 nodes
    /// respectively. Each interval is initialized with the lowest-degree rule. When an interval is
    /// processed, the next-higher degree rule is evaluated and an error estimate is computed based
    /// on the L_2-norm of the difference between the underlying interpolating polynomials of both
    /// rules. If the highest-degree rule has already been used, or the interpolatory polynomials
    /// differ significantly, the interval is bisected.
    ///
    /// The subintervals and their results are stored in the memory provided by workspace. If the
    /// error estimate or the number of function evaluations is not needed, the pointers abserr and
    /// nevals can be set to NULL (not in rgsl).
    ///
    /// Returns `(result, abs_err, n_evals)`.
    #[doc(alias = "gsl_integration_cquad")]
    pub fn cquad<F: Fn(f64) -> f64>(
        &mut self,
        f: F,
        a: f64,
        b: f64,
        epsabs: f64,
        epsrel: f64,
    ) -> (::Value, f64, f64, usize) {
        let function = wrap_callback!(f, F);
        let mut result = 0.;
        let mut abs_err = 0.;
        let mut n_evals = 0;

        let ret = unsafe {
            sys::gsl_integration_cquad(
                &function,
                a,
                b,
                epsabs,
                epsrel,
                self.unwrap_unique(),
                &mut result,
                &mut abs_err,
                &mut n_evals,
            )
        };
        (::Value::from(ret), result, abs_err, n_evals)
    }
}

ffi_wrapper!(GLFixedTable, *mut sys::gsl_integration_glfixed_table, gsl_integration_glfixed_table_free,
"The fixed-order Gauss-Legendre integration routines are provided for fast integration of smooth
functions with known polynomial order. The n-point Gauss-Legendre rule is exact for polynomials
of order 2*n-1 or less. For example, these rules are useful when integrating basis functions to
form mass matrices for the Galerkin method. Unlike other numerical integration routines within
the library, these routines do not accept absolute or relative error bounds.");

impl GLFixedTable {
    /// This function determines the Gauss-Legendre abscissae and weights necessary for an n-point
    /// fixed order integration scheme. If possible, high precision precomputed coefficients are
    /// used. If precomputed weights are not available, lower precision coefficients are computed
    /// on the fly.
    #[doc(alias = "gsl_integration_glfixed_table_alloc")]
    pub fn new(n: usize) -> Option<GLFixedTable> {
        let tmp = unsafe { sys::gsl_integration_glfixed_table_alloc(n) };

        if tmp.is_null() {
            None
        } else {
            Some(Self::wrap(tmp))
        }
    }

    /// For i in [0, …, t->n - 1], this function obtains the i-th Gauss-Legendre point xi and weight
    /// wi on the interval [a,b]. The points and weights are ordered by increasing point value. A
    /// function f may be integrated on [a,b] by summing wi * f(xi) over i.
    ///
    /// Returns `(Value, xi, wi)`.
    #[doc(alias = "gsl_integration_glfixed_point")]
    pub fn point(&self, a: f64, b: f64, i: usize) -> (::Value, f64, f64) {
        let mut xi = 0.;
        let mut wi = 0.;
        let ret = unsafe {
            sys::gsl_integration_glfixed_point(a, b, i, &mut xi, &mut wi, self.unwrap_shared())
        };
        (::Value::from(ret), xi, wi)
    }

    /// This function applies the Gauss-Legendre integration rule contained in table self and
    /// returns the result.
    #[doc(alias = "gsl_integration_glfixed")]
    pub fn glfixed<F: Fn(f64) -> f64>(&self, f: F, a: f64, b: f64) -> f64 {
        let function = wrap_callback!(f, F);
        unsafe { sys::gsl_integration_glfixed(&function, a, b, self.unwrap_shared()) }
    }

    #[doc(alias = "gsl_integration_glfixed_point")]
    pub fn glfixed_point(&self, a: f64, b: f64, xi: &mut [f64], wi: &mut [f64]) -> Value {
        assert!(xi.len() == wi.len());

        Value::from(unsafe {
            sys::gsl_integration_glfixed_point(
                a,
                b,
                xi.len() as _,
                xi.as_mut_ptr(),
                wi.as_mut_ptr(),
                self.unwrap_shared(),
            )
        })
    }
}