Views and operations with mixed scalar types

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難度
5/5
預估耗時
一週以上
新手友好度
25/100
Issue 類型
功能
描述清晰度
需要釐清
活躍度
停滯
技術堆疊
rust
領域
data

研究方向

Start by reviewing the proposed RawData trait, ArrayBase storage pointer, and Index implementation changes in the issue. Assess whether they can support views exposing a different scalar type and mixed-type operations without breaking existing ndarray behavior. Done would be a maintainer-backed design decision with clear API and implementation boundaries.

由索引模型根據 Issue 內容生成。

描述

postponed

I'm curious about the feasibility of extending ndarray to support mixed-precision and mixed-domain algorithms. I was thinking of syntax something like this, enabling a view to offer up f64 values despite the backing storage being f32 (for example).

    let a: Array1<f64> = array![1., 2., 3.];
    let b: Array1<f32> = array![4., 5., 6.];
    let c = a + b.view_as::<f64>();

I'm a Rust novice and ran into some trouble (attempting to use associated_type_defaults to avoid more disruptive changes)

 pub unsafe trait RawData: Sized {
     /// The array element type.
    type Elem: From<Self::ElemMem>;
    type ElemMem;

where ArrayBase would have

    ptr: std::ptr::NonNull<S::ElemMem>,

and the Index implementation becomes

     fn index(&self, index: I) -> &S::Elem {
         debug_bounds_check!(self, index);
         unsafe {
            &S::Elem::from(*self.ptr.as_ptr().offset(
                 index
                     .index_checked(&self.dim, &self.strides)
                    .unwrap_or_else(|| array_out_of_bounds())
            ))
         }
     }

I'm curious whether

  1. this sort of feature to support mixed precision is of interest to include in ndarray, and
  2. this implementation strategy seems like a reasonable way to go about it.
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