arrayfire 3.5.0

ArrayFire is a high performance software library for parallel computing with an easy-to-use API. Its array based function set makes parallel programming simple. ArrayFire's multiple backends (CUDA, OpenCL and native CPU) make it platform independent and highly portable. A few lines of code in ArrayFire can replace dozens of lines of parallel computing code, saving you valuable time and lowering development costs. This crate provides Rust bindings for ArrayFire library.
Documentation 
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extern crate libc;

use array::Array;
use defines::AfError;
use defines::MatProp;
use error::HANDLE_ERROR;
use self::libc::{c_uint, c_int};
use util::{AfArray, MutAfArray, to_u32};

#[allow(dead_code)]
extern {
    fn af_matmul(out: MutAfArray, lhs: AfArray, rhs: AfArray,
                 optlhs: c_uint, optrhs: c_uint) -> c_int;

    fn af_dot(out: MutAfArray, lhs: AfArray, rhs: AfArray,
              optlhs: c_uint, optrhs: c_uint) -> c_int;

    fn af_transpose(out: MutAfArray, arr: AfArray, conjugate: c_int) -> c_int;
    fn af_transpose_inplace(arr: AfArray, conjugate: c_int) -> c_int;
}

/// Matrix multiple of two Arrays
///
/// # Parameters
///
/// - `lhs` is the Array on left hand side
/// - `rhs` is the Array on right hand side
/// - `optlhs` - Transpose left hand side before the function is performed, uses one of the values of [MatProp](./enum.MatProp.html)
/// - `optrhs` - Transpose right hand side before the function is performed, uses one of the values of [MatProp](./enum.MatProp.html)
///
/// # Return Values
///
/// The result Array of matrix multiplication
#[allow(unused_mut)]
pub fn matmul(lhs: &Array, rhs: &Array,
              optlhs: MatProp, optrhs: MatProp) -> Array {
    unsafe {
        let mut temp: i64 = 0;
        let err_val = af_matmul(&mut temp as MutAfArray,
                                lhs.get() as AfArray, rhs.get() as AfArray,
                                to_u32(optlhs) as c_uint, to_u32(optrhs) as c_uint);
        HANDLE_ERROR(AfError::from(err_val));
        Array::from(temp)
    }
}

/// Calculate the dot product of vectors.
///
/// Scalar dot product between two vectors. Also referred to as the inner product. This function returns the scalar product of two equal sized vectors.
///
/// # Parameters
///
/// - `lhs` - Left hand side of dot operation
/// - `rhs` - Right hand side of dot operation
/// - `optlhs` - Options for lhs. Currently only NONE value from [MatProp](./enum.MatProp.html) is supported.
/// - `optrhs` - Options for rhs. Currently only NONE value from [MatProp](./enum.MatProp.html) is supported.
///
/// # Return Values
///
/// The result of dot product.
#[allow(unused_mut)]
pub fn dot(lhs: &Array, rhs: &Array,
           optlhs: MatProp, optrhs: MatProp) -> Array {
    unsafe {
        let mut temp: i64 = 0;
        let err_val = af_dot(&mut temp as MutAfArray,
                             lhs.get() as AfArray, rhs.get() as AfArray,
                             to_u32(optlhs) as c_uint, to_u32(optrhs) as c_uint);
        HANDLE_ERROR(AfError::from(err_val));
        Array::from(temp)
    }
}

/// Transpose of a matrix.
///
/// # Parameters
///
/// - `arr` is the input Array
/// - `conjugate` is a boolean that indicates if the transpose operation needs to be a conjugate
/// transpose
///
/// # Return Values
///
/// Transposed Array.
#[allow(unused_mut)]
pub fn transpose(arr: &Array, conjugate: bool) -> Array {
    unsafe {
        let mut temp: i64 = 0;
        let err_val = af_transpose(&mut temp as MutAfArray,
                                   arr.get() as AfArray, conjugate as c_int);
        HANDLE_ERROR(AfError::from(err_val));
        Array::from(temp)
    }
}

/// Inplace transpose of a matrix.
///
/// # Parameters
///
/// - `arr` is the input Array that has to be transposed
/// - `conjugate` is a boolean that indicates if the transpose operation needs to be a conjugate
/// transpose
#[allow(unused_mut)]
pub fn transpose_inplace(arr: &mut Array, conjugate: bool) {
    unsafe {
        let err_val = af_transpose_inplace(arr.get() as AfArray, conjugate as c_int);
        HANDLE_ERROR(AfError::from(err_val));
    }
}