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use ndarray::*;
use num_traits::Zero;
use super::types::*;
pub trait Norm {
type Output;
fn norm(&self) -> Self::Output {
self.norm_l2()
}
fn norm_l1(&self) -> Self::Output;
fn norm_l2(&self) -> Self::Output;
fn norm_max(&self) -> Self::Output;
}
impl<A, S, D> Norm for ArrayBase<S, D>
where
A: Scalar + Lapack,
S: Data<Elem = A>,
D: Dimension,
{
type Output = A::Real;
fn norm_l1(&self) -> Self::Output {
self.iter().map(|x| x.abs()).sum()
}
fn norm_l2(&self) -> Self::Output {
self.iter().map(|x| x.square()).sum::<A::Real>().sqrt()
}
fn norm_max(&self) -> Self::Output {
self.iter().fold(A::Real::zero(), |f, &val| {
let v = val.abs();
if f > v {
f
} else {
v
}
})
}
}
pub enum NormalizeAxis {
Row = 0,
Column = 1,
}
pub fn normalize<A, S>(
mut m: ArrayBase<S, Ix2>,
axis: NormalizeAxis,
) -> (ArrayBase<S, Ix2>, Vec<A::Real>)
where
A: Scalar + Lapack,
S: DataMut<Elem = A>,
{
let mut ms = Vec::new();
for mut v in m.axis_iter_mut(Axis(axis as usize)) {
let n = v.norm();
ms.push(n);
v.map_inplace(|x| *x /= A::from_real(n))
}
(m, ms)
}