generic-array 1.0

Cargo.toml

@@ -1,23 +1,26 @@
 [package]
-authors = ["Aaron Trent <[email protected]>"]
+authors = ["novacrazy <[email protected]>"]
 name = "numeric-array"
 description = "Wrapper around generic-array that adds efficient numeric trait implementations"
 repository = "https://github.com/novacrazy/numeric-array"
 documentation = "https://docs.rs/numeric-array"
-version = "0.5.2"
+version = "0.6.1"
 readme = "README.md"
 keywords = ["generic", "array", "numeric", "simd"]
-include = ["src/**/*", "Cargo.toml"]
-license = "MIT"
-categories = ["data-structures"]
+include = ["src/**/*", "LICENSE-*", "README.md"]
+license = "MIT OR Apache-2.0"
+categories = ["data-structures", "no-std"]
+edition = "2021"
 
 [dependencies]
-generic-array = "0.14.4"
-num-traits = "0.2"
-serde = { version = "1.0", optional = true, default_features = false }
+generic-array = { version = "1.1.0", default-features = false, features = ["internals"] }
+num-traits = { version = "0.2", default-features = false }
+serde = { version = "1.0", optional = true, default-features = false }
 
 [features]
-serde1 = ["serde", "generic-array/serde"]
+serde = ["dep:serde", "generic-array/serde"]
+std = ["num-traits/std"]
+default = ["std"]
 
 [dev-dependencies]
-serde_json = "1.0"
+serde_json = "1.0"

LICENSE-Apache

@@ -0,0 +1,202 @@
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LICENSE-MIT

@@ -0,0 +1,19 @@
+Copyright (c) 2022 Aaron Trent et al.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
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+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,7 +1,11 @@
 numeric-array
 =============
 
-`numeric-array` is a wrapper around [`generic-array`](https://github.com/fizyk20/generic-array) that adds efficient numeric trait implementations, often times making use of autovectorized SIMD instructions and compile-time evaluations (not const-eval, but LLVM optimizations).
+[![crates.io](https://img.shields.io/crates/v/numeric-array.svg)](https://crates.io/crates/numeric-array)
+[![Documentation](https://docs.rs/numeric-array/badge.svg)](https://docs.rs/numeric-array)
+[![MIT/Apache-2 licensed](https://img.shields.io/crates/l/numeric-array.svg)](./LICENSE-Apache)
+
+`numeric-array` is a wrapper around [`generic-array`](https://github.com/fizyk20/generic-array) that adds efficient numeric trait implementations, designed to encourage LLVM to autovectorize expressions into SIMD instructions and perform compile-time evaluation.
 
 All stable `core::ops` traits are implemented for `NumericArray` itself, plus the thin `NumericConstant` type, which is required to differentiate constant values from `NumericArray` itself.
 
@@ -10,14 +14,8 @@ Additionally, most of `num_traits` are implemented, including `Num` itself. So y
 Example:
 
 ```rust
-extern crate num_traits;
-#[macro_use]
-extern crate generic_array;
-#[macro_use]
-extern crate numeric_array;
-
 use num_traits::Float;
-use numeric_array::NumericArray;
+use numeric_array::{NumericArray, narr};
 
 fn main() {
     let a = narr![f32; 1, 2, 3, 4];
@@ -31,6 +29,6 @@ fn main() {
 }
 ```
 
-When used with `RUSTFLAGS = "-C opt-level=3 -C target-cpu=native"`, then Rust and LLVM are smart enough to autovectorize almost all operations into SIMD instructions, or even just evaluate them at compile time. The above example is actually evaluated at compile time, so if you were to view the assembly it would show the result only. Rust is pretty smart.
+When used with `RUSTFLAGS = "-C opt-level=3 -C target-cpu=native"`, then Rust and LLVM are smart enough to autovectorize almost all operations into SIMD instructions, or even just evaluate them at compile time. The above example is actually evaluated at compile time, so if you were to view the assembly it would show the result only.
 
-Therefore, this is ideal for situations where simple component-wise operations are required for arrays.
+This is ideal for situations where simple component-wise operations are required for arrays.

src/geometry.rs

@@ -1,6 +1,6 @@
 #![allow(missing_docs)]
 
-use core::ops::{Add, Mul};
+use core::ops::Mul;
 
 use num_traits::{Signed, Zero};
 
@@ -16,25 +16,21 @@ pub trait Geometric<T> {
     fn norm_squared(&self) -> T;
 }
 
-impl<T, N: ArrayLength<T>> Geometric<T> for NumericArray<T, N>
+impl<T, N: ArrayLength> Geometric<T> for NumericArray<T, N>
 where
-    T: Add<Output = T> + Mul<Output = T> + Zero + Copy,
+    T: Mul<Output = T> + Zero + Copy,
 {
     #[inline(always)]
     fn scalar_product(&self, other: &Self) -> T {
-        self.iter().zip(&other.0).fold(T::zero(), |sum, (l, r)| {
-            sum + (*l * *r)
-        })
+        self.iter().zip(&other.0).fold(T::zero(), |sum, (l, r)| sum + (*l * *r))
     }
 
     #[inline(always)]
     fn abs_scalar_product(&self, other: &Self) -> T
     where
         T: Signed,
     {
-        self.iter().zip(&other.0).fold(T::zero(), |sum, (l, r)| {
-            sum + (*l * *r).abs()
-        })
+        self.iter().zip(&other.0).fold(T::zero(), |sum, (l, r)| sum + (*l * *r).abs())
     }
 
     #[inline(always)]

src/impl_serde.rs

@@ -7,7 +7,7 @@ use generic_array::{ArrayLength, GenericArray};
 
 use super::{NumericArray, NumericConstant};
 
-impl<T: Serialize, N: ArrayLength<T>> Serialize for NumericArray<T, N> {
+impl<T: Serialize, N: ArrayLength> Serialize for NumericArray<T, N> {
     #[inline]
     fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
     where
@@ -17,7 +17,7 @@ impl<T: Serialize, N: ArrayLength<T>> Serialize for NumericArray<T, N> {
     }
 }
 
-impl<'de, T: Deserialize<'de>, N: ArrayLength<T>> Deserialize<'de> for NumericArray<T, N>
+impl<'de, T: Deserialize<'de>, N: ArrayLength> Deserialize<'de> for NumericArray<T, N>
 where
     T: Default,
 {