Merge pull request #6 from sile/remove-ordered-float

Remove `ordered-float` dependency and replace it with `total_cmp` method for float comparisons

Author: sile

Cargo.toml

@@ -11,7 +11,6 @@ categories = ["science"]
 license = "MIT"
 
 [dependencies]
-ordered-float = "2"
 rand = "0.8"
 rand_distr = "0.4"
 statrs = "0.15"

src/density_estimation/parzen.rs

@@ -1,6 +1,5 @@
 use crate::density_estimation::{BuildDensityEstimator, DensityEstimator};
 use crate::Range;
-use ordered_float::OrderedFloat;
 use rand::distributions::Distribution;
 use rand::seq::SliceRandom;
 use rand::Rng;
@@ -62,7 +61,7 @@ impl BuildDensityEstimator for ParzenEstimatorBuilder {
                 stddev: f64::NAN,
             })
             .collect::<Vec<_>>();
-        xs.sort_by_key(|x| OrderedFloat(x.mean));
+        xs.sort_by(|x, y| x.mean.total_cmp(&y.mean));
 
         self.setup_stddev(&mut xs, range);
 
@@ -126,7 +125,7 @@ impl DensityEstimator for ParzenEstimator {
 fn logsumexp(xs: &[f64]) -> f64 {
     let max_x = xs
         .iter()
-        .max_by_key(|&&x| OrderedFloat(x))
+        .max_by(|x, y| x.total_cmp(y))
         .expect("unreachable");
     xs.iter().map(|&x| (x - max_x).exp()).sum::<f64>().ln() + max_x
 }

src/lib.rs

@@ -45,7 +45,6 @@ use crate::density_estimation::{BuildDensityEstimator, DefaultEstimatorBuilder,
 #[cfg(doc)]
 use crate::density_estimation::{HistogramEstimator, ParzenEstimator};
 use crate::range::{Range, RangeError};
-use ordered_float::OrderedFloat;
 use rand::distributions::Distribution;
 use rand::Rng;
 use std::num::NonZeroUsize;
@@ -171,7 +170,7 @@ impl<T: BuildDensityEstimator> TpeOptimizer<T> {
     /// to reduce bias due to too few samples.
     pub fn ask<R: Rng + ?Sized>(&mut self, rng: &mut R) -> Result<f64, T::Error> {
         if !self.is_sorted {
-            self.trials.sort_by_key(|t| OrderedFloat(t.value));
+            self.trials.sort_by(|x, y| x.value.total_cmp(&y.value));
             self.is_sorted = true;
         }
 
@@ -196,7 +195,7 @@ impl<T: BuildDensityEstimator> TpeOptimizer<T> {
                 let ei = superior_log_likelihood - inferior_log_likelihood;
                 (ei, candidate)
             })
-            .max_by_key(|(ei, _)| OrderedFloat(*ei))
+            .max_by(|(ei0, _), (ei1, _)| ei0.total_cmp(ei1))
             .map(|(_, param)| param)
             .expect("unreachable");
         Ok(param)