Use MaybeUninitSubst and Zip to avoid uninitialized(), rename BroadCa…

…stOutput to Output, remove zip_mut_from_pair()

src/data_traits.rs

@@ -9,14 +9,12 @@
 //! The data (inner representation) traits for ndarray
 
 use rawpointer::PointerExt;
-use std::mem::{self, size_of};
+use std::mem::{self, size_of, MaybeUninit};
 use std::ptr::NonNull;
 use alloc::sync::Arc;
 use alloc::vec::Vec;
 
-use crate::{
-    ArrayBase, CowRepr, Dimension, OwnedArcRepr, OwnedRepr, RawViewRepr, ViewRepr,
-};
+use crate::{ArrayBase, CowRepr, Dimension, OwnedArcRepr, OwnedRepr, RawViewRepr, ViewRepr};
 
 /// Array representation trait.
 ///
@@ -401,6 +399,7 @@ unsafe impl<'a, A> DataMut for ViewRepr<&'a mut A> {}
 ///
 /// ***Internal trait, see `Data`.***
 pub unsafe trait DataOwned: Data {
+
     #[doc(hidden)]
     fn new(elements: Vec<Self::Elem>) -> Self;
 
@@ -424,6 +423,7 @@ unsafe impl<A> DataOwned for OwnedRepr<A> {
     fn new(elements: Vec<A>) -> Self {
         OwnedRepr::from(elements)
     }
+
     fn into_shared(self) -> OwnedArcRepr<A> {
         OwnedArcRepr(Arc::new(self))
     }
@@ -605,3 +605,22 @@ impl<'a, A: 'a, B: 'a> RawDataSubst<B> for ViewRepr<&'a mut A> {
         ViewRepr::new()
     }
 }
+
+/// Array representation trait.
+///
+/// The MaybeUninitSubst trait maps the MaybeUninit type of element, while
+/// mapping the MaybeUninit type back to origin element type.
+///
+/// For example, `MaybeUninitSubst` can map the type `OwnedRepr<A>` to `OwnedRepr<MaybeUninit<A>>`,
+/// and use `Output as RawDataSubst` to map `OwnedRepr<MaybeUninit<A>>` back to `OwnedRepr<A>`.
+pub trait MaybeUninitSubst<A>: DataOwned<Elem = A> {
+    type Output: DataOwned<Elem = MaybeUninit<A>> + RawDataSubst<A, Output=Self, Elem = MaybeUninit<A>>;
+}
+
+impl<A> MaybeUninitSubst<A> for OwnedRepr<A> {
+    type Output = OwnedRepr<MaybeUninit<A>>;
+}
+
+impl<A> MaybeUninitSubst<A> for OwnedArcRepr<A> {
+    type Output = OwnedArcRepr<MaybeUninit<A>>;
+}

src/dimension/broadcast.rs

@@ -43,43 +43,43 @@ where
 
 pub trait BroadcastShape<Other: Dimension> {
     /// The resulting dimension type after broadcasting.
-    type BroadcastOutput: Dimension;
+    type Output: Dimension;
 
     /// Determines the shape after broadcasting the dimensions together.
     ///
     /// If the dimensions are not compatible, returns `Err`.
     ///
     /// Uses the [NumPy broadcasting rules]
     /// (https://docs.scipy.org/doc/numpy/user/basics.broadcasting.html#general-broadcasting-rules).
-    fn broadcast_shape(&self, other: &Other) -> Result<Self::BroadcastOutput, ShapeError>;
+    fn broadcast_shape(&self, other: &Other) -> Result<Self::Output, ShapeError>;
 }
 
 /// Dimensions of the same type remain unchanged when co_broadcast.
 /// So you can directly use D as the resulting type.
 /// (Instead of <D as BroadcastShape<D>>::BroadcastOutput)
 impl<D: Dimension> BroadcastShape<D> for D {
-    type BroadcastOutput = D;
+    type Output = D;
 
-    fn broadcast_shape(&self, other: &D) -> Result<Self::BroadcastOutput, ShapeError> {
-        broadcast_shape::<D, D, Self::BroadcastOutput>(self, other)
+    fn broadcast_shape(&self, other: &D) -> Result<Self::Output, ShapeError> {
+        broadcast_shape::<D, D, Self::Output>(self, other)
     }
 }
 
 macro_rules! impl_broadcast_distinct_fixed {
     ($smaller:ty, $larger:ty) => {
         impl BroadcastShape<$larger> for $smaller {
-            type BroadcastOutput = $larger;
+            type Output = $larger;
 
-            fn broadcast_shape(&self, other: &$larger) -> Result<Self::BroadcastOutput, ShapeError> {
-                broadcast_shape::<Self, $larger, Self::BroadcastOutput>(self, other)
+            fn broadcast_shape(&self, other: &$larger) -> Result<Self::Output, ShapeError> {
+                broadcast_shape::<Self, $larger, Self::Output>(self, other)
             }
         }
 
         impl BroadcastShape<$smaller> for $larger {
-            type BroadcastOutput = $larger;
+            type Output = $larger;
 
-            fn broadcast_shape(&self, other: &$smaller) -> Result<Self::BroadcastOutput, ShapeError> {
-                broadcast_shape::<Self, $smaller, Self::BroadcastOutput>(self, other)
+            fn broadcast_shape(&self, other: &$smaller) -> Result<Self::Output, ShapeError> {
+                broadcast_shape::<Self, $smaller, Self::Output>(self, other)
             }
         }
     };

src/dimension/dimension_trait.rs

@@ -46,11 +46,11 @@ pub trait Dimension:
     + MulAssign
     + for<'x> MulAssign<&'x Self>
     + MulAssign<usize>
-    + BroadcastShape<Ix0, BroadcastOutput=Self>
-    + BroadcastShape<Self, BroadcastOutput=Self>
-    + BroadcastShape<IxDyn, BroadcastOutput=IxDyn>
-    + BroadcastShape<<Self as Dimension>::Smaller, BroadcastOutput=Self>
-    + BroadcastShape<<Self as Dimension>::Larger, BroadcastOutput=<Self as Dimension>::Larger>
+    + BroadcastShape<Ix0, Output=Self>
+    + BroadcastShape<Self, Output=Self>
+    + BroadcastShape<IxDyn, Output=IxDyn>
+    + BroadcastShape<<Self as Dimension>::Smaller, Output=Self>
+    + BroadcastShape<<Self as Dimension>::Larger, Output=<Self as Dimension>::Larger>
 {
     /// For fixed-size dimension representations (e.g. `Ix2`), this should be
     /// `Some(ndim)`, and for variable-size dimension representations (e.g.

src/impl_methods.rs

@@ -1968,46 +1968,6 @@ where
         self.zip_mut_with_by_rows(rhs, f);
     }
 
-    /// Traverse two arrays in unspecified order, in lock step,
-    /// calling the closure `f` on each element pair, and put
-    /// the result into the corresponding element of self.
-    pub fn zip_mut_from_pair<B, C, S1, S2, F>(&mut self, lhs: &ArrayBase<S1, D>, rhs: &ArrayBase<S2, D>, f: F, )
-    where
-        S: DataMut,
-        S1: Data<Elem = B>,
-        S2: Data<Elem = C>,
-        F: Fn(&B, &C) -> A,
-    {
-        debug_assert_eq!(self.shape(), lhs.shape());
-        debug_assert_eq!(self.shape(), rhs.shape());
-
-        if self.dim.strides_equivalent(&self.strides, &lhs.strides)
-            && self.dim.strides_equivalent(&self.strides, &rhs.strides)
-        {
-            if let Some(self_s) = self.as_slice_memory_order_mut() {
-                if let Some(lhs_s) = lhs.as_slice_memory_order() {
-                    if let Some(rhs_s) = rhs.as_slice_memory_order() {
-                        for (s, (l, r)) in
-                        self_s.iter_mut().zip(lhs_s.iter().zip(rhs_s)) {
-                            *s = f(&l, &r);
-                        }
-                        return;
-                    }
-                }
-            }
-        }
-
-        // Otherwise, fall back to the outer iter
-        let n = self.ndim();
-        let dim = self.raw_dim();
-        Zip::from(LanesMut::new(self.view_mut(), Axis(n - 1)))
-            .and(Lanes::new(lhs.broadcast_assume(dim.clone()), Axis(n - 1)))
-            .and(Lanes::new(rhs.broadcast_assume(dim), Axis(n - 1)))
-            .for_each(move |s_row, l_row, r_row| {
-                Zip::from(s_row).and(l_row).and(r_row).for_each(|s, a, b| *s = f(a, b))
-            });
-    }
-
     // zip two arrays where they have different layout or strides
     #[inline(always)]
     fn zip_mut_with_by_rows<B, S2, E, F>(&mut self, rhs: &ArrayBase<S2, E>, mut f: F)

src/impl_ops.rs

@@ -7,6 +7,8 @@
 // except according to those terms.
 
 use crate::dimension::BroadcastShape;
+use crate::data_traits::MaybeUninitSubst;
+use crate::Zip;
 use num_complex::Complex;
 
 /// Elements that can be used as direct operands in arithmetic with arrays.
@@ -64,14 +66,15 @@ macro_rules! impl_binary_op(
 /// **Panics** if broadcasting isn’t possible.
 impl<A, B, S, S2, D, E> $trt<ArrayBase<S2, E>> for ArrayBase<S, D>
 where
-    A: Copy + $trt<B, Output=A>,
+    A: Clone + $trt<B, Output=A>,
     B: Clone,
-    S: DataOwned<Elem=A> + DataMut,
+    S: DataOwned<Elem=A> + DataMut + MaybeUninitSubst<A>,
+    <S as MaybeUninitSubst<A>>::Output: DataMut,
     S2: Data<Elem=B>,
     D: Dimension + BroadcastShape<E>,
     E: Dimension,
 {
-    type Output = ArrayBase<S, <D as BroadcastShape<E>>::BroadcastOutput>;
+    type Output = ArrayBase<S, <D as BroadcastShape<E>>::Output>;
     fn $mth(self, rhs: ArrayBase<S2, E>) -> Self::Output
     {
         self.$mth(&rhs)
@@ -80,7 +83,7 @@ where
 
 /// Perform elementwise
 #[doc=$doc]
-/// between reference `self` and `rhs`,
+/// between `self` and reference `rhs`,
 /// and return the result.
 ///
 /// `rhs` must be an `Array` or `ArcArray`.
@@ -89,44 +92,49 @@ where
 /// cloning the data if needed.
 ///
 /// **Panics** if broadcasting isn’t possible.
-impl<'a, A, B, S, S2, D, E> $trt<ArrayBase<S2, E>> for &'a ArrayBase<S, D>
+impl<'a, A, B, S, S2, D, E> $trt<&'a ArrayBase<S2, E>> for ArrayBase<S, D>
 where
-    A: Clone + $trt<B, Output=B>,
-    B: Copy,
-    S: Data<Elem=A>,
-    S2: DataOwned<Elem=B> + DataMut,
-    D: Dimension,
-    E: Dimension + BroadcastShape<D>,
+    A: Clone + $trt<B, Output=A>,
+    B: Clone,
+    S: DataOwned<Elem=A> + DataMut + MaybeUninitSubst<A>,
+    <S as MaybeUninitSubst<A>>::Output: DataMut,
+    S2: Data<Elem=B>,
+    D: Dimension + BroadcastShape<E>,
+    E: Dimension,
 {
-    type Output = ArrayBase<S2, <E as BroadcastShape<D>>::BroadcastOutput>;
-    fn $mth(self, rhs: ArrayBase<S2, E>) -> Self::Output
+    type Output = ArrayBase<S, <D as BroadcastShape<E>>::Output>;
+    fn $mth(self, rhs: &ArrayBase<S2, E>) -> Self::Output
     {
-        let shape = rhs.dim.broadcast_shape(&self.dim).unwrap();
-        if shape.slice() == rhs.dim.slice() {
-            let mut out = rhs.into_dimensionality::<<E as BroadcastShape<D>>::BroadcastOutput>().unwrap();
-            out.zip_mut_with(self, |x, y| {
-                *x = y.clone() $operator x.clone();
+        let shape = self.dim.broadcast_shape(&rhs.dim).unwrap();
+        if shape.slice() == self.dim.slice() {
+            let mut out = self.into_dimensionality::<<D as BroadcastShape<E>>::Output>().unwrap();
+            out.zip_mut_with(rhs, |x, y| {
+                *x = x.clone() $operator y.clone();
             });
             out
         } else {
-            // SAFETY: Overwrite all the elements in the array after
-            // it is created via `zip_mut_from_pair`.
-            let mut out = unsafe {
-                Self::Output::uninitialized(shape.clone().into_pattern())
-            };
             let lhs = self.broadcast(shape.clone()).unwrap();
-            let rhs = rhs.broadcast(shape).unwrap();
-            out.zip_mut_from_pair(&lhs, &rhs, |x, y| {
-                x.clone() $operator y.clone()
-            });
-            out
+            let rhs = rhs.broadcast(shape.clone()).unwrap();
+            // SAFETY: Overwrite all the elements in the array after
+            // it is created via `raw_view_mut`.
+            unsafe {
+                let mut out =ArrayBase::<<S as MaybeUninitSubst<A>>::Output, <D as BroadcastShape<E>>::Output>::maybe_uninit(shape.into_pattern());
+                let output_view = out.raw_view_mut().cast::<A>();
+                Zip::from(&lhs).and(&rhs)
+                    .and(output_view)
+                    .collect_with_partial(|x, y| {
+                        x.clone() $operator y.clone()
+                    })
+                    .release_ownership();
+                out.assume_init()
+            }
         }
     }
 }
 
 /// Perform elementwise
 #[doc=$doc]
-/// between `self` and reference `rhs`,
+/// between reference `self` and `rhs`,
 /// and return the result.
 ///
 /// `rhs` must be an `Array` or `ArcArray`.
@@ -135,37 +143,43 @@ where
 /// cloning the data if needed.
 ///
 /// **Panics** if broadcasting isn’t possible.
-impl<'a, A, B, S, S2, D, E> $trt<&'a ArrayBase<S2, E>> for ArrayBase<S, D>
+impl<'a, A, B, S, S2, D, E> $trt<ArrayBase<S2, E>> for &'a ArrayBase<S, D>
 where
-    A: Copy + $trt<B, Output=A>,
+    A: Clone + $trt<B, Output=B>,
     B: Clone,
-    S: DataOwned<Elem=A> + DataMut,
-    S2: Data<Elem=B>,
-    D: Dimension + BroadcastShape<E>,
-    E: Dimension,
+    S: Data<Elem=A>,
+    S2: DataOwned<Elem=B> + DataMut + MaybeUninitSubst<B>,
+    <S2 as MaybeUninitSubst<B>>::Output: DataMut,
+    D: Dimension,
+    E: Dimension + BroadcastShape<D>,
 {
-    type Output = ArrayBase<S, <D as BroadcastShape<E>>::BroadcastOutput>;
-    fn $mth(self, rhs: &ArrayBase<S2, E>) -> Self::Output
+    type Output = ArrayBase<S2, <E as BroadcastShape<D>>::Output>;
+    fn $mth(self, rhs: ArrayBase<S2, E>) -> Self::Output
+    where
     {
-        let shape = self.dim.broadcast_shape(&rhs.dim).unwrap();
-        if shape.slice() == self.dim.slice() {
-            let mut out = self.into_dimensionality::<<D as BroadcastShape<E>>::BroadcastOutput>().unwrap();
-            out.zip_mut_with(rhs, |x, y| {
-                *x = x.clone() $operator y.clone();
+        let shape = rhs.dim.broadcast_shape(&self.dim).unwrap();
+        if shape.slice() == rhs.dim.slice() {
+            let mut out = rhs.into_dimensionality::<<E as BroadcastShape<D>>::Output>().unwrap();
+            out.zip_mut_with(self, |x, y| {
+                *x = y.clone() $operator x.clone();
             });
             out
         } else {
-            // SAFETY: Overwrite all the elements in the array after
-            // it is created via `zip_mut_from_pair`.
-            let mut out = unsafe {
-                Self::Output::uninitialized(shape.clone().into_pattern())
-            };
             let lhs = self.broadcast(shape.clone()).unwrap();
-            let rhs = rhs.broadcast(shape).unwrap();
-            out.zip_mut_from_pair(&lhs, &rhs, |x, y| {
-                x.clone() $operator y.clone()
-            });
-            out
+            let rhs = rhs.broadcast(shape.clone()).unwrap();
+            // SAFETY: Overwrite all the elements in the array after
+            // it is created via `raw_view_mut`.
+            unsafe {
+                let mut out =ArrayBase::<<S2 as MaybeUninitSubst<B>>::Output, <E as BroadcastShape<D>>::Output>::maybe_uninit(shape.into_pattern());
+                let output_view = out.raw_view_mut().cast::<B>();
+                Zip::from(&lhs).and(&rhs)
+                    .and(output_view)
+                    .collect_with_partial(|x, y| {
+                        x.clone() $operator y.clone()
+                    })
+                    .release_ownership();
+                out.assume_init()
+            }
         }
     }
 }
@@ -188,19 +202,12 @@ where
     D: Dimension + BroadcastShape<E>,
     E: Dimension,
 {
-    type Output = Array<A, <D as BroadcastShape<E>>::BroadcastOutput>;
+    type Output = Array<A, <D as BroadcastShape<E>>::Output>;
     fn $mth(self, rhs: &'a ArrayBase<S2, E>) -> Self::Output {
         let shape = self.dim.broadcast_shape(&rhs.dim).unwrap();
-        // SAFETY: Overwrite all the elements in the array after
-        // it is created via `zip_mut_from_pair`.
-        let mut out = unsafe {
-            Self::Output::uninitialized(shape.clone().into_pattern())
-        };
         let lhs = self.broadcast(shape.clone()).unwrap();
         let rhs = rhs.broadcast(shape).unwrap();
-        out.zip_mut_from_pair(&lhs, &rhs, |x, y| {
-                x.clone() $operator y.clone()
-        });
+        let out = Zip::from(&lhs).and(&rhs).map_collect(|x, y| x.clone() $operator y.clone());
         out
     }
 }

src/lib.rs

@@ -179,7 +179,7 @@ pub use crate::aliases::*;
 
 pub use crate::data_traits::{
     Data, DataMut, DataOwned, DataShared, RawData, RawDataClone, RawDataMut,
-    RawDataSubst,
+    RawDataSubst, MaybeUninitSubst,
 };
 
 mod free_functions;

tests/array.rs

@@ -1563,7 +1563,7 @@ fn test_broadcast_shape() {
     fn test_co<D1, D2>(
         d1: &D1,
         d2: &D2,
-        r: Result<<D1 as BroadcastShape<D2>>::BroadcastOutput, ShapeError>,
+        r: Result<<D1 as BroadcastShape<D2>>::Output, ShapeError>,
     ) where
         D1: Dimension + BroadcastShape<D2>,
         D2: Dimension,