rlst 0.10.0

A Rust native linear algebra library.
Documentation 
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//! MulAdd operation on two arrays.
//!
//! This module provides the `MulAdd` trait, which allows for efficient multiplication and addition
//! of two arrays with a scalar.

use num::traits::MulAdd;

use crate::{
    ContainerType, ContainerTypeSelector, SelectContainerType,
    dense::array::Array,
    traits::{
        accessors::{UnsafeRandom1DAccessByValue, UnsafeRandomAccessByValue},
        base_operations::{BaseItem, Shape},
    },
};

/// Struct that represents the `mul_add` operation on two arrays.
pub struct MulAddImpl<ArrayImpl1, ArrayImpl2, Item, const NDIM: usize> {
    // The first array
    arr1: Array<ArrayImpl1, NDIM>,
    arr2: Array<ArrayImpl2, NDIM>,
    scalar: Item,
}

impl<ArrayImpl1, ArrayImpl2, Item, const NDIM: usize>
    MulAddImpl<ArrayImpl1, ArrayImpl2, Item, NDIM>
{
    /// Create a new `MulAdd` instance.
    pub fn new(arr1: Array<ArrayImpl1, NDIM>, arr2: Array<ArrayImpl2, NDIM>, scalar: Item) -> Self
    where
        ArrayImpl1: BaseItem<Item = Item> + Shape<NDIM>,
        ArrayImpl2: BaseItem<Item = Item> + Shape<NDIM>,
        Item: MulAdd<Output = Item> + Copy,
    {
        // Ensure that both arrays have the same shape
        assert_eq!(
            arr1.shape(),
            arr2.shape(),
            "Arrays must have the same shape"
        );

        Self { arr1, arr2, scalar }
    }
}

impl<ArrayImpl1, ArrayImpl2, Item, const NDIM: usize> ContainerType
    for MulAddImpl<ArrayImpl1, ArrayImpl2, Item, NDIM>
where
    ArrayImpl1: ContainerType,
    ArrayImpl2: ContainerType,
    SelectContainerType: ContainerTypeSelector<ArrayImpl1::Type, ArrayImpl2::Type>,
{
    type Type = <ArrayImpl1 as ContainerType>::Type;
}

impl<ArrayImpl1, ArrayImpl2, Item, const NDIM: usize> BaseItem
    for MulAddImpl<ArrayImpl1, ArrayImpl2, Item, NDIM>
where
    ArrayImpl1: BaseItem<Item = Item>,
    ArrayImpl2: BaseItem<Item = Item>,
    Item: Copy + Default,
{
    type Item = Item;
}

impl<ArrayImpl1, ArrayImpl2, Item, const NDIM: usize> Shape<NDIM>
    for MulAddImpl<ArrayImpl1, ArrayImpl2, Item, NDIM>
where
    ArrayImpl1: Shape<NDIM>,
{
    fn shape(&self) -> [usize; NDIM] {
        self.arr1.shape()
    }
}

impl<ArrayImpl1, ArrayImpl2, Item, const NDIM: usize> UnsafeRandomAccessByValue<NDIM>
    for MulAddImpl<ArrayImpl1, ArrayImpl2, Item, NDIM>
where
    ArrayImpl1: UnsafeRandomAccessByValue<NDIM, Item = Item>,
    ArrayImpl2: UnsafeRandomAccessByValue<NDIM, Item = Item>,
    Item: num::traits::MulAdd<Output = Item> + Copy + Default,
{
    #[inline(always)]
    unsafe fn get_value_unchecked(&self, multi_index: [usize; NDIM]) -> Self::Item {
        unsafe {
            self.arr1
                .get_value_unchecked(multi_index)
                .mul_add(self.scalar, self.arr2.get_value_unchecked(multi_index))
        }
    }
}

impl<ArrayImpl1, ArrayImpl2, Item, const NDIM: usize> UnsafeRandom1DAccessByValue
    for MulAddImpl<ArrayImpl1, ArrayImpl2, Item, NDIM>
where
    ArrayImpl1: UnsafeRandom1DAccessByValue<Item = Item>,
    ArrayImpl2: UnsafeRandom1DAccessByValue<Item = Item>,
    Item: num::traits::MulAdd<Output = Item> + Copy + Default,
{
    #[inline(always)]
    unsafe fn get_value_1d_unchecked(&self, index: usize) -> Self::Item {
        unsafe {
            self.arr1
                .imp()
                .get_value_1d_unchecked(index)
                .mul_add(self.scalar, self.arr2.imp().get_value_1d_unchecked(index))
        }
    }
}