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//! A collection of (more or less) accurate floating point algorithms //! //! This crate implements several algorithms for floating point summation and dot product. The //! algorithms are realized as types that implement the `SumAccumulator` and `DotAccumulator` //! trait. //! //! # Basic usage //! //! Calculating a sum (or a dot product) begins by initializing an accumulator to zero: //! //! ``` //! use accurate::traits::*; // Most functionality is derived from traits in this module //! use accurate::sum::NaiveSum; // Chose a specific algorithm to perform summation / dot product //! //! let s = NaiveSum::<f32>::zero(); //! ``` //! //! The accumulator traits are generic over the type of the underlying floating point numbers and //! the `zero()` constructor is supported if the number type implements the Zero trait. //! Alternatively the accumulator traits imply that an accumulator can be constructed `from()` an //! arbitrary value of the number type. //! //! ``` //! # use accurate::traits::*; //! # use accurate::sum::NaiveSum; //! let s = NaiveSum::from(42.0f64); //! ``` //! //! The actual calculation is performed via the `Add<F, Output = Self>` trait that is also implied //! by the `SumAccumulator` trait, where `F` is the type of the floating point numbers. //! //! ``` //! # use accurate::traits::*; //! use accurate::sum::Sum2; //! //! let s = Sum2::zero() + 1.0f64 + 2.0 + 3.0; //! ``` //! //! For dot products, the `DotAccumulator` trait implies `Add<(F, F), Output = Self>` to allow //! accumulation of the products of pairs into the final result. //! //! ``` //! # use accurate::traits::*; //! use accurate::dot::NaiveDot; //! //! let d = NaiveDot::zero() + (1.0f64, 1.0f64) + (2.0, 2.0) + (3.0, 3.0); //! ``` //! //! Once all of the terms have been accumulated, the result can be evaluated using the `sum()` and //! `dot()` methods respectively. //! //! ``` //! # use accurate::traits::*; //! # use accurate::sum::Sum2; //! # use accurate::dot::NaiveDot; //! let s = Sum2::zero() + 1.0f64 + 2.0 + 3.0; //! assert_eq!(6.0, s.sum()); //! //! let d = NaiveDot::zero() + (1.0f64, 1.0f64) + (2.0, 2.0) + (3.0, 3.0); //! assert_eq!(14.0, d.dot()); //! ``` //! //! Both `sum()` and `dot()` take their argument by value, because the evaluation of the final //! result is in some cases a destructive operation on the internal state of the accumulator. //! However, the evaluation of partial results is supported by `clone()`ing the accumulator. //! //! ``` //! # use accurate::traits::*; //! # use accurate::sum::Sum2; //! let s = Sum2::zero() + 1.0f32 + 2.0; //! assert_eq!(3.0, s.clone().sum()); //! let s = s + 3.0; //! assert_eq!(6.0, s.sum()); //! ``` //! //! # Iterator consumption //! //! Accumulators can be used in `fold()` operations on iterators as one would expect. //! //! ``` //! # use accurate::traits::*; //! # use accurate::sum::Sum2; //! use accurate::dot::Dot2; //! //! let s = vec![1.0f32, 2.0, 3.0].into_iter().fold(Sum2::zero(), |acc, x| acc + x); //! assert_eq!(6.0, s.sum()); //! //! let d = vec![1.0f32, 2.0, 3.0].into_iter() //! .zip(vec![1.0, 2.0, 3.0].into_iter()) //! .fold(Dot2::zero(), |acc, xy| acc + xy); //! assert_eq!(14.0, d.dot()); //! ``` //! //! For convenience, the accumulator traits also define `absorb()` methods to absorb values from //! anything that implements `IntoIterator`. //! //! ``` //! # use accurate::traits::*; //! # use accurate::sum::Sum2; //! # use accurate::dot::Dot2; //! //! let s = Sum2::zero().absorb(vec![1.0f32, 2.0, 3.0]); //! assert_eq!(6.0, s.sum()); //! //! let d = Dot2::zero().absorb(vec![(1.0f32, 1.0), (2.0, 2.0), (3.0, 3.0)]); //! assert_eq!(14.0, d.dot()); //! ``` //! //! And for even more convenience, suitable iterators are extended by a `sum_with_accumulator()` //! (and `dot_with_accumulator()`) method that directly evaluates to the result in the floating //! point number type. //! //! ``` //! # use accurate::traits::*; //! # use accurate::sum::Sum2; //! # use accurate::dot::Dot2; //! //! let s = Sum2::zero().absorb(vec![1.0f32, 2.0, 3.0]); //! assert_eq!(6.0f64, vec![1.0, 2.0, 3.0].into_iter().sum_with_accumulator::<Sum2<_>>()); //! //! assert_eq!(14.0f64, vec![(1.0, 1.0), (2.0, 2.0), (3.0, 3.0)].into_iter() //! .dot_with_accumulator::<Dot2<_>>()); //! ``` //! #![cfg_attr(feature = "parallel", doc = " # Parallel computation If compiled with the `parallel` feature enabled (which is the default) the `rayon` parallel iterator facilities are used to perform large calculations in parallel. Parallel calculations are performed through the `parallel_sum_with_accumulator()` and `parallel_dot_with_accumulator()` extension methods on parallel iterators. ``` # extern crate accurate; extern crate rayon; use rayon::prelude::*; # use accurate::traits::*; # use accurate::sum::Sum2; # fn main() { let xs = vec![1.0f64; 100_000]; let s = xs.par_iter().map(|&x| x).parallel_sum_with_accumulator::<Sum2<_>>(); assert_eq!(100_000.0, s); # } ``` ")] #![deny(missing_docs)] #![warn(missing_copy_implementations)] #![warn(missing_debug_implementations)] #![warn(trivial_casts)] #![warn(trivial_numeric_casts)] // This has false positives on #[macro_use], // see https://github.com/rust-lang/rust/issues/30849 // #![warn(unused_extern_crates)] #![warn(unused_import_braces)] #![warn(unused_qualifications)] #![warn(unused_results)] #![deny(warnings)] #![cfg_attr(feature = "cargo-clippy", warn(cast_possible_truncation))] #![cfg_attr(feature = "cargo-clippy", warn(cast_possible_wrap))] #![cfg_attr(feature = "cargo-clippy", warn(cast_precision_loss))] #![cfg_attr(feature = "cargo-clippy", warn(cast_sign_loss))] #![cfg_attr(feature = "cargo-clippy", allow(doc_markdown))] #![cfg_attr(feature = "cargo-clippy", allow(many_single_char_names))] #![cfg_attr(feature = "cargo-clippy", warn(mut_mut))] #![cfg_attr(feature = "cargo-clippy", warn(mutex_integer))] #![cfg_attr(feature = "cargo-clippy", warn(non_ascii_literal))] #![cfg_attr(feature = "cargo-clippy", warn(option_unwrap_used))] #![cfg_attr(feature = "cargo-clippy", warn(print_stdout))] #![cfg_attr(feature = "cargo-clippy", warn(result_unwrap_used))] #![cfg_attr(feature = "cargo-clippy", warn(single_match_else))] #![cfg_attr(feature = "cargo-clippy", warn(string_add))] #![cfg_attr(feature = "cargo-clippy", warn(string_add_assign))] #![cfg_attr(feature = "cargo-clippy", warn(unicode_not_nfc))] #![cfg_attr(feature = "cargo-clippy", warn(wrong_pub_self_convention))] #![cfg_attr(feature = "cargo-clippy", allow(suspicious_op_assign_impl))] #[macro_use] extern crate cfg_if; extern crate ieee754; extern crate num; #[cfg(feature = "parallel")] extern crate rayon; pub mod dot; pub mod sum; pub mod util; /// Includes all traits of this crate pub mod traits { #[doc(inline)] pub use dot::traits::*; #[doc(inline)] pub use sum::traits::*; #[doc(inline)] pub use util::traits::*; }