Struct ndarray::Zip [−][src]
pub struct Zip<Parts, D> { /* fields omitted */ }
Expand description
Lock step function application across several arrays or other producers.
Zip allows matching several producers to each other elementwise and applying a function over all tuples of elements (one item from each input at a time).
In general, the zip uses a tuple of producers
(NdProducer
trait) that all have to be of the
same shape. The NdProducer implementation defines what its item type is
(for example if it’s a shared reference, mutable reference or an array
view etc).
If all the input arrays are of the same memory layout the zip performs much better and the compiler can usually vectorize the loop (if applicable).
The order elements are visited is not specified. The producers don’t have to have the same item type.
The Zip
has two methods for function application: apply
and
fold_while
. The zip object can be split, which allows parallelization.
A read-only zip object (no mutable producers) can be cloned.
See also the azip!()
macro which offers a convenient shorthand
to common ways to use Zip
.
use ndarray::Zip; use ndarray::Array2; type M = Array2<f64>; // Create four 2d arrays of the same size let mut a = M::zeros((64, 32)); let b = M::from_elem(a.dim(), 1.); let c = M::from_elem(a.dim(), 2.); let d = M::from_elem(a.dim(), 3.); // Example 1: Perform an elementwise arithmetic operation across // the four arrays a, b, c, d. Zip::from(&mut a) .and(&b) .and(&c) .and(&d) .apply(|w, &x, &y, &z| { *w += x + y * z; }); // Example 2: Create a new array `e` with one entry per row of `a`. // Use Zip to traverse the rows of `a` and assign to the corresponding // entry in `e` with the sum across each row. // This is possible because the producer for `e` and the row producer // for `a` have the same shape and dimensionality. // The rows producer yields one array view (`row`) per iteration. use ndarray::{Array1, Axis}; let mut e = Array1::zeros(a.rows()); Zip::from(&mut e) .and(a.genrows()) .apply(|e, row| { *e = row.scalar_sum(); }); // Check the result against the built in `.sum_axis()` along axis 1. assert_eq!(e, a.sum_axis(Axis(1)));
Implementations
Create a new Zip
from the input array or other producer p
.
The Zip will take the exact dimension of p
and all inputs
must have the same dimensions (or be broadcast to them).
pub fn indexed<IP>(p: IP) -> Self where
IP: IntoNdProducer<Dim = D, Output = P, Item = P::Item>,
[src]
pub fn indexed<IP>(p: IP) -> Self where
IP: IntoNdProducer<Dim = D, Output = P, Item = P::Item>,
[src]Create a new Zip
with an index producer and the producer p
.
The Zip will take the exact dimension of p
and all inputs
must have the same dimensions (or be broadcast to them).
Note: Indexed zip has overhead.
Apply a function to all elements of the input arrays, visiting elements in lock step.
Apply a fold function to all elements of the input arrays, visiting elements in lock step.
The fold continues while the return value is a
FoldWhile::Continue
.
Include the producer p
in the Zip.
Panics if p
’s shape doesn’t match the Zip’s exactly.
pub fn and_broadcast<'a, P, D2, Elem>(
self,
p: P
) -> Zip<(P1, ArrayView<'a, Elem, D>), D> where
P: IntoNdProducer<Dim = D2, Output = ArrayView<'a, Elem, D2>, Item = &'a Elem>,
D2: Dimension,
[src]
pub fn and_broadcast<'a, P, D2, Elem>(
self,
p: P
) -> Zip<(P1, ArrayView<'a, Elem, D>), D> where
P: IntoNdProducer<Dim = D2, Output = ArrayView<'a, Elem, D2>, Item = &'a Elem>,
D2: Dimension,
[src]Include the producer p
in the Zip, broadcasting if needed.
If their shapes disagree, rhs
is broadcast to the shape of self
.
Panics if broadcasting isn’t possible.
Apply a function to all elements of the input arrays, visiting elements in lock step.
Apply a fold function to all elements of the input arrays, visiting elements in lock step.
The fold continues while the return value is a
FoldWhile::Continue
.
Include the producer p
in the Zip.
Panics if p
’s shape doesn’t match the Zip’s exactly.
pub fn and_broadcast<'a, P, D2, Elem>(
self,
p: P
) -> Zip<(P1, P2, ArrayView<'a, Elem, D>), D> where
P: IntoNdProducer<Dim = D2, Output = ArrayView<'a, Elem, D2>, Item = &'a Elem>,
D2: Dimension,
[src]
pub fn and_broadcast<'a, P, D2, Elem>(
self,
p: P
) -> Zip<(P1, P2, ArrayView<'a, Elem, D>), D> where
P: IntoNdProducer<Dim = D2, Output = ArrayView<'a, Elem, D2>, Item = &'a Elem>,
D2: Dimension,
[src]Include the producer p
in the Zip, broadcasting if needed.
If their shapes disagree, rhs
is broadcast to the shape of self
.
Panics if broadcasting isn’t possible.
impl<D: Dimension, P1: NdProducer<Dim = D>, P2: NdProducer<Dim = D>, P3: NdProducer<Dim = D>> Zip<(P1, P2, P3), D>
[src]
impl<D: Dimension, P1: NdProducer<Dim = D>, P2: NdProducer<Dim = D>, P3: NdProducer<Dim = D>> Zip<(P1, P2, P3), D>
[src]Apply a function to all elements of the input arrays, visiting elements in lock step.
Apply a fold function to all elements of the input arrays, visiting elements in lock step.
The fold continues while the return value is a
FoldWhile::Continue
.
Include the producer p
in the Zip.
Panics if p
’s shape doesn’t match the Zip’s exactly.
pub fn and_broadcast<'a, P, D2, Elem>(
self,
p: P
) -> Zip<(P1, P2, P3, ArrayView<'a, Elem, D>), D> where
P: IntoNdProducer<Dim = D2, Output = ArrayView<'a, Elem, D2>, Item = &'a Elem>,
D2: Dimension,
[src]
pub fn and_broadcast<'a, P, D2, Elem>(
self,
p: P
) -> Zip<(P1, P2, P3, ArrayView<'a, Elem, D>), D> where
P: IntoNdProducer<Dim = D2, Output = ArrayView<'a, Elem, D2>, Item = &'a Elem>,
D2: Dimension,
[src]Include the producer p
in the Zip, broadcasting if needed.
If their shapes disagree, rhs
is broadcast to the shape of self
.
Panics if broadcasting isn’t possible.
impl<D: Dimension, P1: NdProducer<Dim = D>, P2: NdProducer<Dim = D>, P3: NdProducer<Dim = D>, P4: NdProducer<Dim = D>> Zip<(P1, P2, P3, P4), D>
[src]
impl<D: Dimension, P1: NdProducer<Dim = D>, P2: NdProducer<Dim = D>, P3: NdProducer<Dim = D>, P4: NdProducer<Dim = D>> Zip<(P1, P2, P3, P4), D>
[src]Apply a function to all elements of the input arrays, visiting elements in lock step.
Apply a fold function to all elements of the input arrays, visiting elements in lock step.
The fold continues while the return value is a
FoldWhile::Continue
.
Include the producer p
in the Zip.
Panics if p
’s shape doesn’t match the Zip’s exactly.
pub fn and_broadcast<'a, P, D2, Elem>(
self,
p: P
) -> Zip<(P1, P2, P3, P4, ArrayView<'a, Elem, D>), D> where
P: IntoNdProducer<Dim = D2, Output = ArrayView<'a, Elem, D2>, Item = &'a Elem>,
D2: Dimension,
[src]
pub fn and_broadcast<'a, P, D2, Elem>(
self,
p: P
) -> Zip<(P1, P2, P3, P4, ArrayView<'a, Elem, D>), D> where
P: IntoNdProducer<Dim = D2, Output = ArrayView<'a, Elem, D2>, Item = &'a Elem>,
D2: Dimension,
[src]Include the producer p
in the Zip, broadcasting if needed.
If their shapes disagree, rhs
is broadcast to the shape of self
.
Panics if broadcasting isn’t possible.
impl<D: Dimension, P1: NdProducer<Dim = D>, P2: NdProducer<Dim = D>, P3: NdProducer<Dim = D>, P4: NdProducer<Dim = D>, P5: NdProducer<Dim = D>> Zip<(P1, P2, P3, P4, P5), D>
[src]
impl<D: Dimension, P1: NdProducer<Dim = D>, P2: NdProducer<Dim = D>, P3: NdProducer<Dim = D>, P4: NdProducer<Dim = D>, P5: NdProducer<Dim = D>> Zip<(P1, P2, P3, P4, P5), D>
[src]Apply a function to all elements of the input arrays, visiting elements in lock step.
Apply a fold function to all elements of the input arrays, visiting elements in lock step.
The fold continues while the return value is a
FoldWhile::Continue
.
Include the producer p
in the Zip.
Panics if p
’s shape doesn’t match the Zip’s exactly.
pub fn and_broadcast<'a, P, D2, Elem>(
self,
p: P
) -> Zip<(P1, P2, P3, P4, P5, ArrayView<'a, Elem, D>), D> where
P: IntoNdProducer<Dim = D2, Output = ArrayView<'a, Elem, D2>, Item = &'a Elem>,
D2: Dimension,
[src]
pub fn and_broadcast<'a, P, D2, Elem>(
self,
p: P
) -> Zip<(P1, P2, P3, P4, P5, ArrayView<'a, Elem, D>), D> where
P: IntoNdProducer<Dim = D2, Output = ArrayView<'a, Elem, D2>, Item = &'a Elem>,
D2: Dimension,
[src]Include the producer p
in the Zip, broadcasting if needed.
If their shapes disagree, rhs
is broadcast to the shape of self
.
Panics if broadcasting isn’t possible.
impl<D: Dimension, P1: NdProducer<Dim = D>, P2: NdProducer<Dim = D>, P3: NdProducer<Dim = D>, P4: NdProducer<Dim = D>, P5: NdProducer<Dim = D>, P6: NdProducer<Dim = D>> Zip<(P1, P2, P3, P4, P5, P6), D>
[src]
impl<D: Dimension, P1: NdProducer<Dim = D>, P2: NdProducer<Dim = D>, P3: NdProducer<Dim = D>, P4: NdProducer<Dim = D>, P5: NdProducer<Dim = D>, P6: NdProducer<Dim = D>> Zip<(P1, P2, P3, P4, P5, P6), D>
[src]Apply a function to all elements of the input arrays, visiting elements in lock step.
Apply a fold function to all elements of the input arrays, visiting elements in lock step.
The fold continues while the return value is a
FoldWhile::Continue
.
Trait Implementations
Auto Trait Implementations
impl<Parts, D> RefUnwindSafe for Zip<Parts, D> where
D: RefUnwindSafe,
Parts: RefUnwindSafe,
impl<Parts, D> UnwindSafe for Zip<Parts, D> where
D: UnwindSafe,
Parts: UnwindSafe,
Blanket Implementations
Mutably borrows from an owned value. Read more