fn multiscalar_mul()

in src/backend/vector/scalar_mul/straus.rs [39:70]

• 26 lines of code
• 3 McCabe index (conditional complexity)

    fn multiscalar_mul<I, J>(scalars: I, points: J) -> EdwardsPoint
    where
        I: IntoIterator,
        I::Item: Borrow<Scalar>,
        J: IntoIterator,
        J::Item: Borrow<EdwardsPoint>,
    {
        // Construct a lookup table of [P,2P,3P,4P,5P,6P,7P,8P]
        // for each input point P
        let lookup_tables: Vec<_> = points
            .into_iter()
            .map(|point| LookupTable::<CachedPoint>::from(point.borrow()))
            .collect();

        let scalar_digits_vec: Vec<_> = scalars
            .into_iter()
            .map(|s| s.borrow().to_radix_16())
            .collect();
        // Pass ownership to a `Zeroizing` wrapper
        let scalar_digits = Zeroizing::new(scalar_digits_vec);

        let mut Q = ExtendedPoint::identity();
        for j in (0..64).rev() {
            Q = Q.mul_by_pow_2(4);
            let it = scalar_digits.iter().zip(lookup_tables.iter());
            for (s_i, lookup_table_i) in it {
                // Q = Q + s_{i,j} * P_i
                Q = &Q + &lookup_table_i.select(s_i[j]);
            }
        }
        Q.into()
    }