Ndarray views of numpy arrays

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难度
5/5
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一周以上
新手友好度
25/100
Issue 类型
功能
描述清晰度
需要澄清
活跃度
停滞
技术栈
numpy, r, rust
领域
backend-api-design, data

调研方向

Start by reviewing the scirust commit linked in the issue and the current ndarray APIs for constructing views from external data. Define what dtype, dimensions, strides, and safety checks are required for NumPy arrays and R matrices, then identify tests that demonstrate accepted and rejected inputs.

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描述

help wanted

I write numerical code in Rust, but use Python and sometimes R to drive them (e.g., plot graphs comparing performance for different algorithms). This involves exporting an extern function that accepts pointers to (parts of) numpy arrays or R matrices, then treating these as Rusty datastructures (I implemented a basic version of for scirust in [1]).

As a user it would be great to have a function to which I pass a pointer to the raw Numpy array object (without doing any conversions in Python), and get back a view I can use safely. This involves looking at the Numpy array for the dtype, dimension, strides etc. Since ndarray encodes some of these in the type, a generic function that merely tests that the NP array passed conforms to its expectations (or panics with highly informative debug information) seems best.

Same applies to R, with different particulars of course.

Or is there a way to do this already?

[1] https://github.com/daniel-vainsencher/scirust/commit/48c9109abae32db06217576f03c22a18ad39e5d6 which doesn't compile on current nightly rust, sadly.

主要语言
Rust
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