cmp: switch min
and max
to TotalOrd
The `Float` trait provides correct `min` and `max` methods on floating point types, providing a consistent result regardless of the order the parameters are passed. These generic functions do not take the necessary performance hit to correctly support a partial order, so the true requirement should be given as a type bound. Closes #12712
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@ -353,8 +353,6 @@ fn pnorm(nums: &~[f64], p: uint) -> f64 {
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fn main() {
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let numbers = vec::from_fn(1000000, |_| rand::random::<f64>());
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println!("Inf-norm = {}", *numbers.iter().max().unwrap());
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let numbers_arc = Arc::new(numbers);
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for num in range(1u, 10) {
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@ -184,12 +184,12 @@ pub trait Equiv<T> {
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}
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#[inline]
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pub fn min<T:Ord>(v1: T, v2: T) -> T {
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pub fn min<T: TotalOrd>(v1: T, v2: T) -> T {
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if v1 < v2 { v1 } else { v2 }
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}
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#[inline]
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pub fn max<T:Ord>(v1: T, v2: T) -> T {
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pub fn max<T: TotalOrd>(v1: T, v2: T) -> T {
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if v1 > v2 { v1 } else { v2 }
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}
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@ -68,7 +68,7 @@ use cmp;
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use num::{Zero, One, CheckedAdd, CheckedSub, Saturating, ToPrimitive, Int};
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use option::{Option, Some, None};
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use ops::{Add, Mul, Sub};
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use cmp::{Eq, Ord};
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use cmp::{Eq, Ord, TotalOrd};
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use clone::Clone;
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use uint;
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use mem;
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@ -626,7 +626,7 @@ pub trait Iterator<A> {
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/// assert_eq!(*xs.iter().max_by(|x| x.abs()).unwrap(), -10);
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/// ```
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#[inline]
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fn max_by<B: Ord>(&mut self, f: |&A| -> B) -> Option<A> {
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fn max_by<B: TotalOrd>(&mut self, f: |&A| -> B) -> Option<A> {
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self.fold(None, |max: Option<(A, B)>, x| {
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let x_val = f(&x);
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match max {
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@ -650,7 +650,7 @@ pub trait Iterator<A> {
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/// assert_eq!(*xs.iter().min_by(|x| x.abs()).unwrap(), 0);
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/// ```
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#[inline]
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fn min_by<B: Ord>(&mut self, f: |&A| -> B) -> Option<A> {
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fn min_by<B: TotalOrd>(&mut self, f: |&A| -> B) -> Option<A> {
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self.fold(None, |min: Option<(A, B)>, x| {
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let x_val = f(&x);
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match min {
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@ -917,7 +917,7 @@ pub trait OrdIterator<A> {
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fn min_max(&mut self) -> MinMaxResult<A>;
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}
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impl<A: Ord, T: Iterator<A>> OrdIterator<A> for T {
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impl<A: TotalOrd, T: Iterator<A>> OrdIterator<A> for T {
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#[inline]
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fn max(&mut self) -> Option<A> {
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self.fold(None, |max, x| {
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@ -1069,7 +1069,7 @@ impl MetricMap {
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if delta.abs() <= noise {
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LikelyNoise
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} else {
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let pct = delta.abs() / cmp::max(vold.value, f64::EPSILON) * 100.0;
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let pct = delta.abs() / vold.value.max(f64::EPSILON) * 100.0;
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if vold.noise < 0.0 {
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// When 'noise' is negative, it means we want
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// to see deltas that go up over time, and can
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