openethereum/util/stats/src/lib.rs

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// Copyright 2015-2017 Parity Technologies (UK) Ltd.
// This file is part of Parity.
// Parity is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
// Parity is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with Parity. If not, see <http://www.gnu.org/licenses/>.
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//! Statistical functions and helpers.
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use std::iter::FromIterator;
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use std::ops::{Add, Sub, Deref, Div};
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#[macro_use]
extern crate log;
/// Sorted corpus of data.
#[derive(Debug, Clone, PartialEq)]
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pub struct Corpus<T>(Vec<T>);
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impl<T: Ord> From<Vec<T>> for Corpus<T> {
fn from(mut data: Vec<T>) -> Self {
data.sort();
Corpus(data)
}
}
impl<T: Ord> FromIterator<T> for Corpus<T> {
fn from_iter<I: IntoIterator<Item=T>>(iterable: I) -> Self {
iterable.into_iter().collect::<Vec<_>>().into()
}
}
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impl<T> Deref for Corpus<T> {
type Target = [T];
fn deref(&self) -> &[T] { &self.0[..] }
}
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impl<T: Ord> Corpus<T> {
/// Get given percentile (approximated).
pub fn percentile(&self, val: usize) -> Option<&T> {
let len = self.0.len();
let x = val * len / 100;
let x = ::std::cmp::min(x, len);
if x == 0 {
return None;
}
self.0.get(x - 1)
}
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/// Get the median element, if it exists.
pub fn median(&self) -> Option<&T> {
self.0.get(self.0.len() / 2)
}
/// Whether the corpus is empty.
pub fn is_empty(&self) -> bool {
self.0.is_empty()
}
/// Number of elements in the corpus.
pub fn len(&self) -> usize {
self.0.len()
}
}
impl<T: Ord + Copy + ::std::fmt::Display> Corpus<T>
where T: Add<Output=T> + Sub<Output=T> + Div<Output=T> + From<usize>
{
/// Create a histogram of this corpus if it at least spans the buckets. Bounds are left closed.
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/// Excludes outliers.
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pub fn histogram(&self, bucket_number: usize) -> Option<Histogram<T>> {
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// TODO: get outliers properly.
let upto = self.len() - self.len() / 40;
Histogram::create(&self.0[..upto], bucket_number)
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}
}
/// Discretised histogram.
#[derive(Debug, PartialEq)]
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pub struct Histogram<T> {
/// Bounds of each bucket.
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pub bucket_bounds: Vec<T>,
/// Count within each bucket.
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pub counts: Vec<usize>,
}
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impl<T: Ord + Copy + ::std::fmt::Display> Histogram<T>
where T: Add<Output=T> + Sub<Output=T> + Div<Output=T> + From<usize>
{
// Histogram of a sorted corpus if it at least spans the buckets. Bounds are left closed.
fn create(corpus: &[T], bucket_number: usize) -> Option<Histogram<T>> {
if corpus.len() < 1 { return None; }
let corpus_end = corpus.last().expect("there is at least 1 element; qed").clone();
let corpus_start = corpus.first().expect("there is at least 1 element; qed").clone();
trace!(target: "stats", "Computing histogram from {} to {} with {} buckets.", corpus_start, corpus_end, bucket_number);
// Bucket needs to be at least 1 wide.
let bucket_size = {
// Round up to get the entire corpus included.
let raw_bucket_size = (corpus_end - corpus_start + bucket_number.into()) / bucket_number.into();
if raw_bucket_size == 0.into() { 1.into() } else { raw_bucket_size }
};
let mut bucket_end = corpus_start + bucket_size;
let mut bucket_bounds = vec![corpus_start; bucket_number + 1];
let mut counts = vec![0; bucket_number];
let mut corpus_i = 0;
// Go through the corpus adding to buckets.
for bucket in 0..bucket_number {
while corpus.get(corpus_i).map_or(false, |v| v < &bucket_end) {
// Initialized to size bucket_number above; iterates up to bucket_number; qed
counts[bucket] += 1;
corpus_i += 1;
}
// Initialized to size bucket_number + 1 above; iterates up to bucket_number; subscript is in range; qed
bucket_bounds[bucket + 1] = bucket_end;
bucket_end = bucket_end + bucket_size;
}
Some(Histogram { bucket_bounds: bucket_bounds, counts: counts })
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn check_corpus() {
let corpus = Corpus::from(vec![1, 2, 3, 4, 5, 6, 7, 8, 9, 10]);
assert_eq!(corpus.percentile(0), None);
assert_eq!(corpus.percentile(1), None);
assert_eq!(corpus.percentile(101), Some(&10));
assert_eq!(corpus.percentile(100), Some(&10));
assert_eq!(corpus.percentile(50), Some(&5));
assert_eq!(corpus.percentile(60), Some(&6));
assert_eq!(corpus.median(), Some(&6));
}
#[test]
fn check_histogram() {
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let hist = Histogram::create(&[643,689,1408,2000,2296,2512,4250,4320,4842,4958,5804,6065,6098,6354,7002,7145,7845,8589,8593,8895], 5).unwrap();
let correct_bounds: Vec<usize> = vec![643, 2294, 3945, 5596, 7247, 8898];
assert_eq!(Histogram { bucket_bounds: correct_bounds, counts: vec![4,2,4,6,4] }, hist);
}
#[test]
fn smaller_data_range_than_bucket_range() {
assert_eq!(
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Histogram::create(&[1, 2, 2], 3),
Some(Histogram { bucket_bounds: vec![1, 2, 3, 4], counts: vec![1, 2, 0] })
);
}
#[test]
fn data_range_is_not_multiple_of_bucket_range() {
assert_eq!(
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Histogram::create(&[1, 2, 5], 2),
Some(Histogram { bucket_bounds: vec![1, 4, 7], counts: vec![2, 1] })
);
}
#[test]
fn data_range_is_multiple_of_bucket_range() {
assert_eq!(
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Histogram::create(&[1, 2, 6], 2),
Some(Histogram { bucket_bounds: vec![1, 4, 7], counts: vec![2, 1] })
);
}
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#[test]
fn none_when_too_few_data() {
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assert!(Histogram::<usize>::create(&[], 1).is_none());
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}
}