I'm working on a project using central differences meaning I need to work with the previous, current and next value on each iteration. Using nalgebra this would be simple, just call .windows(3) and map the values like so:
y.windows(3).map(|window_vals| window_vals[0] - 2.0 * window_vals[1] + window_vals[2])
However, unfortunately I need to use this central difference method as part of an impl block for ode_solver's (for those of you familiar with the crate this is the system method) unfortunately the trait requirements for this library mean I need to use nalgebra matrix's instead, which don't appear to have a similar method. Please let me know what the best option is for replicating the above code snippet with when working with nalgebra matricies rather than ndarray arrays
You can use as_slice or as_mut_slice to get a slice view of your Matrix, then use the standard windows method on that slice:
y.as_slice().windows(3).map(|window_vals| window_vals[0] - 2.0 * window_vals[1] + window_vals[2])