3.0.8

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "medians"
-version = "3.0.7"
+version = "3.0.8"
 authors = ["Libor Spacek"]
 edition = "2021"
 description = "Median, Statistical Measures, Mathematics, Statistics"

README.md

@@ -5,7 +5,7 @@
 Fast algorithm for finding medians of one dimensional data, implemented in 100% safe Rust.
 
 ```rust
-use medians::{medianu8,Medians,Medianf64,Median};
+use medians::{*,algos::*};
 ```
 
 ## Introduction
@@ -111,6 +111,8 @@ pub trait Median<'a, T> {
 
 ## Release Notes
 
+**Version 3.0.8** - Added `implementation.rs` module and reorganized the source.
+
 **Version 3.0.7** - Added `medf_weighted`, applying `&[f64]` weights.
 
 **Version 3.0.6** - Moved `part`, `ref_vec` and `deref_vec` into crate `Indxvec`, to allow their wider use.
@@ -126,19 +128,3 @@ pub trait Median<'a, T> {
 **Version 3.0.1** - Renamed `correlation` to `med_correlation` to avoid name clashes elsewhere.
 
 **Version 3.0.0** - Numerous improvements to speed and generality and renaming.
-
-**Version 2.3.1** - Further speed optimisation of `partf64`.
-
-**Version 2.3.0** - Some minor changes to `algosf64.rs`. Improvements to this manual.
-
-**Version 2.2.6** - Improved `README.md`. No changes to the code.
-
-**Version 2.2.5** - Upped dependency on `indxvec` to version 1.8.
-
-**Version 2.2.3** - Slight further improvement to efficiency of `part`.
-
-**Version 2.2.2** - Corrected some comment and readme typos. No change in functionality.
-
-**Version 2.2.1** - Some code pruning and streamlining. No change in functionality.
-
-**Version 2.2.0** - Major new version with much improved speed and generality and some breaking changes (renaming).

src/algos.rs

@@ -1,6 +1,7 @@
 use core::cmp::{Ordering, Ordering::*};
 use std::ops::Range;
 use indxvec::Mutops;
+use crate::{Me,merror};
 
 /// Scan a slice of f64s for NANs
 pub fn nans(v: &[f64]) -> bool {
@@ -111,7 +112,7 @@ pub fn qbalance<T>(s: &[T], centre: &f64, q: impl Fn(&T) -> f64) -> i64 {
 }
 
 /// Odd median of `&[u8]`
-pub fn oddmedianu8(s: &[u8]) -> f64 {
+fn oddmedianu8(s: &[u8]) -> f64 {
     let need = s.len() / 2; // median target position
     let mut histogram = [0_usize; 256];
     let mut cummulator = 0_usize;
@@ -133,7 +134,7 @@ pub fn oddmedianu8(s: &[u8]) -> f64 {
 }
 
 /// Even median of `&[u8]`
-pub fn evenmedianu8(s: &[u8]) -> f64 {
+fn evenmedianu8(s: &[u8]) -> f64 {
     let need = s.len() / 2; // first median target position
     let mut histogram = [0_usize; 256];
     let mut cummulator = 0_usize;
@@ -163,9 +164,24 @@ pub fn evenmedianu8(s: &[u8]) -> f64 {
     res
 }
 
+/// Median of primitive type u8 by fast radix search
+pub fn medianu8(s:&[u8]) -> Result<f64, Me> {
+    let n = s.len();
+    match n {
+        0 => return merror("size", "median: zero length data")?,
+        1 => return Ok(s[0] as f64),
+        2 => return Ok((s[0] as f64 + s[1] as f64) / 2.0),
+        _ => (),
+    };
+    if (n & 1) == 1 {
+        Ok(oddmedianu8(s))
+    } else {
+        Ok(evenmedianu8(s))
+    }
+}
 
 /// Median of odd sized generic data with Odering comparisons by custom closure
-pub fn oddmedian_by<'a, T>(s: &mut [&'a T], c: &mut impl FnMut(&T, &T) -> Ordering) -> &'a T {
+pub(super) fn oddmedian_by<'a, T>(s: &mut [&'a T], c: &mut impl FnMut(&T, &T) -> Ordering) -> &'a T {
     let mut rng = 0..s.len();
     let need = s.len() / 2; // median target position in fully partitioned set
     loop {
@@ -214,7 +230,7 @@ pub fn oddmedian_by<'a, T>(s: &mut [&'a T], c: &mut impl FnMut(&T, &T) -> Orderi
 }
 
 /// Median of even sized generic data with Odering comparisons by custom closure
-pub fn evenmedian_by<'a, T>(
+pub(super) fn evenmedian_by<'a, T>(
     s: &mut [&'a T],
     c: &mut impl FnMut(&T, &T) -> Ordering,
 ) -> (&'a T, &'a T) {