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// Copyright 2016 Matthew D. Michelotti // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. //! This crate contains floating point types that panic if they are set //! to an illegal value, such as NaN. //! //! The name "Noisy Float" comes from //! the terms "quiet NaN" and "signaling NaN"; "signaling" was too long //! to put in a struct/crate name, so "noisy" is used instead, being the opposite //! of "quiet." //! //! The standard types defined in `noisy_float::types` follow the principle //! demonstrated by Rust's handling of integer overflow: //! a bad arithmetic operation is considered an error, //! but it is too costly to check everywhere in optimized builds. //! For each floating point number that is created, a `debug_assert!` invocation is used //! to check if it is valid or not. //! This way, there are guarantees when developing code that floating point //! numbers have valid values, //! but during a release run there is *no overhead* for using these floating //! point types compared to using `f32` or `f64` directly. //! //! This crate makes use of the floating point and number traits in the //! popular `num_traits` crate. //! //! #Examples //! An example using the `R64` type, which corresponds to *finite* `f64` values. //! //! ``` //! use noisy_float::prelude::*; //! //! fn geometric_mean(a: R64, b: R64) -> R64 { //! (a * b).sqrt() //used just like regular floating point numbers //! } //! //! fn mean(a: R64, b: R64) -> R64 { //! (a + b) * 0.5 //the RHS of ops can be the underlying float type //! } //! //! println!("geometric_mean(10.0, 20.0) = {}", geometric_mean(r64(10.0), r64(20.0))); //! //prints 14.142... //! assert!(mean(r64(10.0), r64(20.0)) == 15.0); //! ``` //! //! An example using the `N32` type, which corresponds to *non-NaN* `f32` values. //! The float types in this crate are able to implement `Eq` and `Ord` properly, //! since NaN is not allowed. //! //! ``` //! use noisy_float::prelude::*; //! //! let values = vec![n32(3.0), n32(-1.5), n32(71.3), N32::infinity()]; //! assert!(values.iter().cloned().min() == Some(n32(-1.5))); //! assert!(values.iter().cloned().max() == Some(N32::infinity())); //! ``` extern crate num_traits; mod float_impl; pub mod checkers; pub mod types; /// Prelude for the `noisy_float` crate. /// /// This includes all of the types defined in the `noisy_float::types` module, /// as well as a re-export of the `Float` trait from the `num_traits` crate. /// It is important to have this re-export here, because it allows the user /// to access common floating point methods like `abs()`, `sqrt()`, etc. pub mod prelude { pub use types::*; #[doc(no_inline)] pub use num_traits::Float; } use std::marker::PhantomData; use std::fmt; use num_traits::Float; /// Trait for checking whether a floating point number is *valid*. /// /// The implementation defines its own criteria for what constitutes a *valid* value. pub trait FloatChecker<F> { /// Returns `true` if (and only if) the given floating point number is *valid* /// according to this checker's criteria. /// /// The only hard requirement is that NaN *must* be considered *invalid* /// for all implementations of `FloatChecker`. fn check(value: F) -> bool; /// A function that may panic if the floating point number is *invalid*. /// /// Should either call `assert!(check(value), ...)` or `debug_assert!(check(value), ...)`. fn assert(value: F); } /// A floating point number with a restricted set of legal values. /// /// Typical users will not need to access this struct directly, but /// can instead use the type aliases found in the module `noisy_float::types`. /// However, this struct together with a `FloatChecker` implementation can be used /// to define custom behavior. /// /// The underlying float type is `F`, usually `f32` or `f64`. /// Valid values for the float are determined by the float checker `C`. /// If an invalid value would ever be returned from a method on this type, /// the method will panic instead, using either `assert!` or `debug_assert!` /// as defined by the float checker. /// The exception to this rule is for methods that return an `Option` containing /// a `NoisyFloat`, in which case the result would be `None` if the value is invalid. pub struct NoisyFloat<F: Float, C: FloatChecker<F>> { value: F, checker: PhantomData<C> } impl<F: Float, C: FloatChecker<F>> NoisyFloat<F, C> { /// Constructs a `NoisyFloat` with the given value. /// /// Uses the `FloatChecker` to assert that the value is valid. #[inline] pub fn new(value: F) -> Self { C::assert(value); Self::unchecked_new(value) } #[inline] fn unchecked_new(value: F) -> Self { NoisyFloat { value: value, checker: PhantomData } } /// Tries to construct a `NoisyFloat` with the given value. /// /// Returns `None` if the value is invalid. #[inline] pub fn try_new(value: F) -> Option<Self> { if C::check(value) { Some(NoisyFloat { value: value, checker: PhantomData }) } else { None } } /// Constructs a `NoisyFloat` with the given `f32` value. /// /// May panic not only by the `FloatChecker` but also /// by unwrapping the result of a `NumCast` invocation for type `F`, /// although the later should not occur in normal situations. #[inline] pub fn from_f32(value: f32) -> Self { Self::new(F::from(value).unwrap()) } /// Constructs a `NoisyFloat` with the given `f64` value. /// /// May panic not only by the `FloatChecker` but also /// by unwrapping the result of a `NumCast` invocation for type `F`, /// although the later should not occur in normal situations. #[inline] pub fn from_f64(value: f64) -> Self { Self::new(F::from(value).unwrap()) } /// Returns the underlying float value. #[inline] pub fn raw(self) -> F { self.value } } impl<F: Float + Default, C: FloatChecker<F>> Default for NoisyFloat<F, C> { #[inline] fn default() -> Self { Self::new(F::default()) } } impl<F: Float + fmt::Debug, C: FloatChecker<F>> fmt::Debug for NoisyFloat<F, C> { #[inline] fn fmt(&self, f: &mut fmt::Formatter) -> Result<(), fmt::Error> { fmt::Debug::fmt(&self.value, f) } } impl<F: Float + fmt::Display, C: FloatChecker<F>> fmt::Display for NoisyFloat<F, C> { #[inline] fn fmt(&self, f: &mut fmt::Formatter) -> Result<(), fmt::Error> { fmt::Display::fmt(&self.value, f) } } impl<F: Float + fmt::LowerExp, C: FloatChecker<F>> fmt::LowerExp for NoisyFloat<F, C> { #[inline] fn fmt(&self, f: &mut fmt::Formatter) -> Result<(), fmt::Error> { fmt::LowerExp::fmt(&self.value, f) } } impl<F: Float + fmt::UpperExp, C: FloatChecker<F>> fmt::UpperExp for NoisyFloat<F, C> { #[inline] fn fmt(&self, f: &mut fmt::Formatter) -> Result<(), fmt::Error> { fmt::UpperExp::fmt(&self.value, f) } } #[cfg(test)] mod tests { use prelude::*; use std::f32; use std::f64::{self, consts}; #[test] fn smoke_test() { assert!(n64(1.0) + 2.0 == 3.0); assert!(n64(3.0) != n64(2.9)); assert!(r64(1.0) < 2.0); let mut value = n64(18.0); value %= n64(5.0); assert!(-value == n64(-3.0)); assert!(r64(1.0).exp() == consts::E); assert!((N64::try_new(1.0).unwrap() / N64::infinity()) == 0.0); assert!(N64::from_f32(f32::INFINITY) == N64::from_f64(f64::INFINITY)); assert!(R64::try_new(f64::NEG_INFINITY) == None); assert!(N64::try_new(f64::NAN) == None); assert!(R64::try_new(f64::NAN) == None); } #[test] #[should_panic] fn n64_nan() { n64(0.0) / n64(0.0); } #[test] #[should_panic] fn r64_nan() { r64(0.0) / r64(0.0); } #[test] #[should_panic] fn r64_infinity() { r64(1.0) / r64(0.0); } }