ad_trait 0.3.1

Easy to use, efficient, and highly flexible automatic differentiation in Rust
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

# Integration with ndarray

`ad_trait` also supports the `ndarray` crate, which is commonly used for data science and machine learning.

## Example: AD Array

```rust
use ndarray::Array2;
use ad_trait::adfn;

let a = Array2::<adfn<1>>::zeros((10, 10));
```

## Scalar Operations

The `AD` trait includes `mul_by_ndarray_matrix_ref`, allowing you to perform scalar-array multiplication efficiently across different AD modes.

## Generic Algorithms

Similar to `nalgebra`, you can write generic algorithms using `ndarray` that work with any `AD` type. This is particularly useful for implementing complex mathematical models that require gradients for optimization.