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```
``````//! Benchmark metrics.
use std::collections::BTreeMap;

#[derive(Clone, PartialEq, Debug, Copy)]
pub struct Metric {
value: f64,
noise: f64,
}

impl Metric {
pub fn new(value: f64, noise: f64) -> Metric {
Metric { value, noise }
}
}

#[derive(Clone, PartialEq)]
pub struct MetricMap(BTreeMap<String, Metric>);

impl MetricMap {
pub fn new() -> MetricMap {
MetricMap(BTreeMap::new())
}

/// Insert a named `value` (+/- `noise`) metric into the map. The value
/// must be non-negative. The `noise` indicates the uncertainty of the
/// metric, which doubles as the "noise range" of acceptable
/// pairwise-regressions on this named value, when comparing from one
/// metric to the next using `compare_to_old`.
///
/// If `noise` is positive, then it means this metric is of a value
/// you want to see grow smaller, so a change larger than `noise` in the
/// positive direction represents a regression.
///
/// If `noise` is negative, then it means this metric is of a value
/// you want to see grow larger, so a change larger than `noise` in the
/// negative direction represents a regression.
pub fn insert_metric(&mut self, name: &str, value: f64, noise: f64) {
let m = Metric { value, noise };
self.0.insert(name.to_owned(), m);
}

pub fn fmt_metrics(&self) -> String {
let v = self
.0
.iter()
.map(|(k, v)| format!("{}: {} (+/- {})", *k, v.value, v.noise))
.collect::<Vec<_>>();
v.join(", ")
}
}
``````