pub fn dot_dense<T>(&self, rhs: T) -> N
    where T: DenseVector<N>,
          N: Num + Copy + Sum,
    {
        assert_eq!(self.dim(), rhs.dim());
        self.iter().map(|(idx, val)| *val * *rhs.index(idx.index())).sum()
    }
/// Sparse-dense vector dot product. The right-hand-side can be any type
/// that can be interpreted as a dense vector (hence std vectors and
/// slices, and ndarray's dense vectors work).
///
/// Since the `dot` method can work with the same performance on
/// dot vectors, the main interest of this method is to enforce at
/// compile time that the rhs is dense.
///
/// # Panics
///
/// If the dimension of the vectors do not match.
Sparse-dense vector dot product. The right-hand-side can be any type
that can be interpreted as a dense vector (hence std vectors and
slices, and ndarray's dense vectors work).

Since the `dot` method can work with the same performance on
dot vectors, the main interest of this method is to enforce at
compile time that the rhs is dense.
Sparse - dense vector dot product . The right - hand - side can be any type that can be interpreted as a dense vector ( hence std vectors and slices and ndarray ' s dense vectors work ) . Since the ` dot ` method can work with the same performance on dot vectors the main interest of this method is to enforce at compile time that the rhs is dense .
pub fn dot_dense<T>(&self, rhs: T) -> N
    where T: DenseVector<N>,
          N: Num + Copy + Sum,
    {
        assert_eq!(self.dim(), rhs.dim());
        self.iter().map(|(idx, val)| *val * *rhs.index(idx.index())).sum()
    }
pub fn dot_dense < T > ( & self , rhs : T ) -> N where T : DenseVector < N > , N : Num + Copy + Sum , { assert_eq ! ( self dim ( ) rhs dim ( ) ) ; self . iter ( ) . map ( | ( idx , val ) | * val * * rhs . index ( idx . index ( ) ) ) . sum ( ) }
Sparse-dense vector dot product.
Sparse - dense vector dot product .
&self
rhs
T
&self
rhs
T
panics
If the dimension of the vectors do not match.
If the dimension of the vectors do not match .