from_arrayd/
from_arrayd.rs

1//! Convert an `ndarray::ArrayD<f64>` into a `matten::Tensor`, including a
2//! non-standard-layout (transposed) input.
3//!
4//! Run:
5//! cargo run -p matten-ndarray --example from_arrayd
6
7use matten_ndarray::from_arrayd;
8use ndarray::{ArrayD, IxDyn};
9
10fn main() {
11    let arr = ArrayD::from_shape_vec(IxDyn(&[2, 3]), vec![1., 2., 3., 4., 5., 6.]).unwrap();
12
13    let t = from_arrayd(arr.clone()).expect("contiguous converts");
14    println!(
15        "from contiguous: shape {:?} data {:?}",
16        t.shape(),
17        t.as_slice()
18    );
19
20    // Transposed input is non-standard layout; conversion preserves logical order.
21    let tt = from_arrayd(arr.t().to_owned()).expect("transposed converts");
22    println!(
23        "from transposed: shape {:?} data {:?}",
24        tt.shape(),
25        tt.as_slice()
26    );
27    assert_eq!(tt.shape(), &[3, 2]);
28    assert_eq!(tt.as_slice(), &[1.0, 4.0, 2.0, 5.0, 3.0, 6.0]);
29    println!("ok");
30}
from_arrayd/from_arrayd.rs

from_arrayd/
from_arrayd.rs
