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use const generics #12

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2 changes: 1 addition & 1 deletion Cargo.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,7 @@ optional = true
version = "~0.1"

[dependencies]
generic-array = "^0.14"
arrayvec = { version = "0.7.2", default-features = false }

[dev-dependencies]
arraydeque = "0.4.2"
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2 changes: 1 addition & 1 deletion src/lib.rs
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Expand Up @@ -13,7 +13,7 @@
#[cfg(all(not(feature = "std"), not(test)))]
extern crate core as std;

extern crate generic_array;
extern crate arrayvec;

#[cfg(feature = "std")]
pub mod heap;
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84 changes: 31 additions & 53 deletions src/stack.rs
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Expand Up @@ -5,9 +5,9 @@
//! An implementation of a stack-allocated, efficient O(n) median filter.

use std::fmt;
use std::ptr;
use std::iter::FromIterator;

use generic_array::{ArrayBuilder, ArrayLength, GenericArray};
use arrayvec::ArrayVec;

/// Implementation detail.
/// (Once we have value generics we will hopefully be able to un-leak it.)
Expand All @@ -33,12 +33,9 @@ where
/// has a worst-case complexity of `O(n^2)` (due to having to sort the sliding window)
/// the use of a combination of linked list and ring buffer allows for
/// a worst-case complexity of `O(n)`.
pub struct Filter<T, N>
where
N: ArrayLength<ListNode<T>>,
{
pub struct Filter<T, const N: usize> {
// Buffer of list nodes:
buffer: GenericArray<ListNode<T>, N>,
buffer: ArrayVec<ListNode<T>, N>,
// Cursor into circular buffer of data:
cursor: usize,
// Cursor to beginning of circular list:
Expand All @@ -47,10 +44,9 @@ where
median: usize,
}

impl<T, N> Clone for Filter<T, N>
impl<T, const N: usize> Clone for Filter<T, N>
where
T: Clone,
N: ArrayLength<ListNode<T>>,
{
fn clone(&self) -> Self {
Self {
Expand All @@ -62,10 +58,9 @@ where
}
}

impl<T, N> fmt::Debug for Filter<T, N>
impl<T, const N: usize> fmt::Debug for Filter<T, N>
where
T: fmt::Debug,
N: ArrayLength<ListNode<T>>,
{
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
f.debug_struct("Filter")
Expand All @@ -77,31 +72,17 @@ where
}
}

impl<T, N> Filter<T, N>
impl<T, const N: usize> Filter<T, N>
where
T: Clone + PartialOrd,
N: ArrayLength<ListNode<T>>,
{
/// Creates a new median filter with a given window size.
pub fn new() -> Self {
let buffer = unsafe {
let mut builder = ArrayBuilder::new();
{
let size = N::to_usize();
let (iter, index) = builder.iter_position();
for destination in iter {
// while let Some(destination) = iter.next() {
let node = ListNode {
value: None,
previous: (*index + size - 1) % size,
next: (*index + 1) % size,
};
ptr::write(destination, node);
*index += 1;
}
}
builder.into_inner()
};
let buffer = ArrayVec::from_iter((0..N).map(|index| ListNode {
value: None,
previous: (index + N - 1) % N,
next: (index + 1) % N,
}));
Filter {
buffer,
cursor: 0,
Expand Down Expand Up @@ -355,10 +336,9 @@ where
}
}

impl<T, N> Default for Filter<T, N>
impl<T, const N: usize> Default for Filter<T, N>
where
T: Clone + PartialOrd,
N: ArrayLength<ListNode<T>>,
{
fn default() -> Self {
Self::new()
Expand All @@ -369,10 +349,8 @@ where
mod tests {
use super::*;

use generic_array::typenum::*;

macro_rules! test_filter {
($size:ident, $input:expr, $output:expr) => {
($size:literal, $input:expr, $output:expr) => {
let filter: Filter<_, $size> = Filter::new();
let output: Vec<_> = $input
.iter()
Expand All @@ -387,117 +365,117 @@ mod tests {
let input = vec![10, 20, 30, 100, 30, 20, 10];
let output = vec![10, 10, 20, 20, 30, 30, 20];

test_filter!(U4, input, output);
test_filter!(4, input, output);
}

#[test]
fn single_peak_5() {
let input = vec![10, 20, 30, 100, 30, 20, 10];
let output = vec![10, 10, 20, 20, 30, 30, 30];
test_filter!(U5, input, output);
test_filter!(5, input, output);
}

#[test]
fn single_valley_4() {
let input = vec![90, 80, 70, 10, 70, 80, 90];
let output = vec![90, 80, 80, 70, 70, 70, 70];
test_filter!(U4, input, output);
test_filter!(4, input, output);
}

#[test]
fn single_valley_5() {
let input = vec![90, 80, 70, 10, 70, 80, 90];
let output = vec![90, 80, 80, 70, 70, 70, 70];
test_filter!(U5, input, output);
test_filter!(5, input, output);
}

#[test]
fn single_outlier_4() {
let input = vec![10, 10, 10, 100, 10, 10, 10];
let output = vec![10, 10, 10, 10, 10, 10, 10];
test_filter!(U4, input, output);
test_filter!(4, input, output);
}

#[test]
fn single_outlier_5() {
let input = vec![10, 10, 10, 100, 10, 10, 10];
let output = vec![10, 10, 10, 10, 10, 10, 10];
test_filter!(U5, input, output);
test_filter!(5, input, output);
}

#[test]
fn triple_outlier_4() {
let input = vec![10, 10, 100, 100, 100, 10, 10];
let output = vec![10, 10, 10, 10, 100, 100, 10];
test_filter!(U4, input, output);
test_filter!(4, input, output);
}

#[test]
fn triple_outlier_5() {
let input = vec![10, 10, 100, 100, 100, 10, 10];
let output = vec![10, 10, 10, 10, 100, 100, 100];
test_filter!(U5, input, output);
test_filter!(5, input, output);
}

#[test]
fn quintuple_outlier_4() {
let input = vec![10, 100, 100, 100, 100, 100, 10];
let output = vec![10, 10, 100, 100, 100, 100, 100];
test_filter!(U4, input, output);
test_filter!(4, input, output);
}

#[test]
fn quintuple_outlier_5() {
let input = vec![10, 100, 100, 100, 100, 100, 10];
let output = vec![10, 10, 100, 100, 100, 100, 100];
test_filter!(U5, input, output);
test_filter!(5, input, output);
}

#[test]
fn alternating_4() {
let input = vec![10, 20, 10, 20, 10, 20, 10];
let output = vec![10, 10, 10, 10, 10, 10, 10];
test_filter!(U4, input, output);
test_filter!(4, input, output);
}

#[test]
fn alternating_5() {
let input = vec![10, 20, 10, 20, 10, 20, 10];
let output = vec![10, 10, 10, 10, 10, 20, 10];
test_filter!(U5, input, output);
test_filter!(5, input, output);
}

#[test]
fn ascending_4() {
let input = vec![10, 20, 30, 40, 50, 60, 70];
let output = vec![10, 10, 20, 20, 30, 40, 50];
test_filter!(U4, input, output);
test_filter!(4, input, output);
}

#[test]
fn ascending_5() {
let input = vec![10, 20, 30, 40, 50, 60, 70];
let output = vec![10, 10, 20, 20, 30, 40, 50];
test_filter!(U5, input, output);
test_filter!(5, input, output);
}

#[test]
fn descending_4() {
let input = vec![70, 60, 50, 40, 30, 20, 10];
let output = vec![70, 60, 60, 50, 40, 30, 20];
test_filter!(U4, input, output);
test_filter!(4, input, output);
}

#[test]
fn descending_5() {
let input = vec![70, 60, 50, 40, 30, 20, 10];
let output = vec![70, 60, 60, 50, 50, 40, 30];
test_filter!(U5, input, output);
test_filter!(5, input, output);
}

#[test]
fn min_max_median() {
let mut filter: Filter<_, U5> = Filter::new();
let mut filter: Filter<_, 5> = Filter::new();
for input in [70, 50, 30, 10, 20, 40, 60] {
filter.consume(input);
}
Expand Down