use core::iter::Iterator;
use rand::SeedableRng;
use rand_distr::Distribution;
use average::{Histogram, Merge, define_histogram, assert_almost_eq};
define_histogram!(hist10, 10);
define_histogram!(hist100, 100);
use crate::hist10::Histogram as Histogram10;
#[test]
fn with_const_width() {
let mut h = Histogram10::with_const_width(-30., 70.);
for i in -30..70 {
h.add(f64::from(i)).unwrap();
}
assert_eq!(h.bins(), &[10, 10, 10, 10, 10, 10, 10, 10, 10, 10]);
}
#[test]
fn from_ranges() {
let mut h = Histogram10::from_ranges(
[0., 0.1, 0.2, 0.3, 0.4, 0.5, 0.7, 0.8, 0.9, 1.0, 2.0].iter().cloned()).unwrap();
for &i in &[0.05, 0.7, 1.0, 1.5] {
h.add(i).unwrap();
}
assert_eq!(h.bins(), &[1, 0, 0, 0, 0, 0, 1, 0, 0, 2]);
}
#[test]
fn iter() {
let mut h = Histogram10::from_ranges(
[0., 0.1, 0.2, 0.3, 0.4, 0.5, 0.7, 0.8, 0.9, 1.0, 2.0].iter().cloned()).unwrap();
for &i in &[0.05, 0.7, 1.0, 1.5] {
h.add(i).unwrap();
}
let iterated: Vec<((f64, f64), u64)> = h.iter().collect();
assert_eq!(&iterated, &[
((0., 0.1), 1), ((0.1, 0.2), 0), ((0.2, 0.3), 0), ((0.3, 0.4), 0),
((0.4, 0.5), 0), ((0.5, 0.7), 0), ((0.7, 0.8), 1), ((0.8, 0.9), 0),
((0.9, 1.0), 0), ((1.0, 2.0), 2)
]);
}
#[test]
fn normalized_bins() {
let inf = std::f64::INFINITY;
let mut h = Histogram10::from_ranges(
[-inf, 0.1, 0.2, 0.3, 0.4, 0.4, 0.7, 0.8, 0.9, 1.0, inf].iter().cloned()).unwrap();
for &i in &[0.05, 0.1, 0.7, 1.0, 1.5] {
h.add(i).unwrap();
}
let normalized: Vec<f64> = h.normalized_bins().collect();
let expected = [0., 10., 0., 0., 0., 0., 10., 0., 0., 0.];
for (a, b) in normalized.iter().zip(expected.iter()) {
assert_almost_eq!(a, b, 1e-14);
}
}
#[test]
fn widths() {
let inf = std::f64::INFINITY;
let h = Histogram10::from_ranges(
[-inf, 0.1, 0.2, 0.3, 0.4, 0.4, 0.7, 0.8, 0.9, 1.0, inf].iter().cloned()).unwrap();
let widths: Vec<f64> = h.widths().collect();
let expected = [inf, 0.1, 0.1, 0.1, 0., 0.3, 0.1, 0.1, 0.1, inf];
for (a, b) in widths.iter().zip(expected.iter()) {
assert_almost_eq!(a, b, 1e-14);
}
}
#[test]
fn centers() {
let inf = std::f64::INFINITY;
let h = Histogram10::from_ranges(
[-inf, 0.1, 0.2, 0.3, 0.4, 0.4, 0.7, 0.8, 0.9, 1.0, inf].iter().cloned()).unwrap();
let centers: Vec<f64> = h.centers().collect();
let expected = [-inf, 0.15, 0.25, 0.35, 0.4, 0.55, 0.75, 0.85, 0.95, inf];
for (a, b) in centers.iter().zip(expected.iter()) {
assert_almost_eq!(a, b, 1e-14);
}
}
#[test]
fn from_ranges_infinity() {
let inf = std::f64::INFINITY;
let mut h = Histogram10::from_ranges(
[-inf, -0.4, -0.3, -0.2, -0.1, 0.0, 0.1, 0.2, 0.3, 0.4, inf].iter().cloned()).unwrap();
for &i in &[-100., -0.45, 0., 0.25, 0.4, 100.] {
h.add(i).unwrap();
}
assert_eq!(h.bins(), &[2, 0, 0, 0, 0, 1, 0, 1, 0, 2]);
}
#[test]
fn from_ranges_invalid() {
assert!(Histogram10::from_ranges([].iter().cloned()).is_err());
let valid = vec![0., 0.1, 0.2, 0.3, 0.4, 0.5, 0.7, 0.8, 0.9, 1.0, 2.0];
assert!(Histogram10::from_ranges(valid.iter().cloned()).is_ok());
let mut invalid_nan = valid.clone();
invalid_nan[3] = std::f64::NAN;
assert!(Histogram10::from_ranges(invalid_nan.iter().cloned()).is_err());
let mut invalid_order = valid.clone();
invalid_order[10] = 0.9;
assert!(Histogram10::from_ranges(invalid_order.iter().cloned()).is_err());
let mut valid_empty_ranges = valid.clone();
valid_empty_ranges[1] = 0.;
valid_empty_ranges[10] = 1.;
}
#[test]
fn from_ranges_empty() {
let mut h = Histogram10::from_ranges(
[0., 0., 0.2, 0.3, 0.4, 0.5, 0.5, 0.8, 0.9, 2.0, 2.0].iter().cloned()).unwrap();
for &i in &[0.05, 0.7, 1.0, 1.5] {
h.add(i).unwrap();
}
assert_eq!(h.bins(), &[0, 1, 0, 0, 0, 0, 1, 0, 2, 0]);
}
#[test]
fn out_of_range() {
let mut h = Histogram10::with_const_width(0., 100.);
assert_eq!(h.add(-0.1), Err(()));
assert_eq!(h.add(0.0), Ok(()));
assert_eq!(h.add(1.0), Ok(()));
assert_eq!(h.add(100.0), Err(()));
assert_eq!(h.add(100.1), Err(()));
}
#[test]
fn reset() {
let mut h = Histogram10::with_const_width(0., 100.);
for i in 0..100 {
h.add(f64::from(i)).unwrap();
}
assert_eq!(h.bins(), &[10, 10, 10, 10, 10, 10, 10, 10, 10, 10]);
h.reset();
assert_eq!(h.bins(), &[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]);
}
#[test]
fn range_minmax() {
let h = Histogram10::with_const_width(0., 100.);
assert_eq!(h.range_min(), 0.);
assert_eq!(h.range_max(), 100.);
}
#[test]
fn add() {
let mut h1 = Histogram10::with_const_width(0., 100.);
let mut h2 = h1.clone();
let mut expected = h1.clone();
for i in 0..50 {
h1.add(f64::from(i)).unwrap();
expected.add(f64::from(i)).unwrap();
}
for i in 50..100 {
h2.add(f64::from(i)).unwrap();
expected.add(f64::from(i)).unwrap();
}
h1 += &h2;
assert_eq!(h1.bins(), expected.bins());
}
#[test]
fn mul() {
let mut h = Histogram10::with_const_width(0., 100.);
let mut expected = h.clone();
for i in 0..100 {
h.add(f64::from(i)).unwrap();
expected.add(f64::from(i)).unwrap();
expected.add(f64::from(i)).unwrap();
}
h *= 2;
assert_eq!(h.bins(), expected.bins());
}
#[test]
fn variance() {
let mut h = Histogram10::with_const_width(-3., 3.);
let normal = rand_distr::Normal::new(0., 1.).unwrap();
let mut rng = rand_xoshiro::Xoshiro256StarStar::from_entropy();
for _ in 0..1000000 {
let _ = h.add(normal.sample(&mut rng));
}
println!("{:?}", h);
let sum: u64 = h.bins().iter().sum();
let sum = sum as f64;
for (i, v) in h.variances().enumerate() {
assert_almost_eq!(v, h.variance(i), 1e-14);
let poissonian_variance = h.bins()[i] as f64;
assert_almost_eq!(v.sqrt() / sum, poissonian_variance.sqrt() / sum, 1e-4);
}
}
#[test]
fn merge() {
let mut h = Histogram10::from_ranges(
[0., 0.1, 0.2, 0.3, 0.4, 0.5, 0.7, 0.8, 0.9, 1.0, 2.0].iter().cloned()).unwrap();
let mut h1 = h.clone();
let mut h2 = h.clone();
for &i in &[0.05, 0.7, 1.0, 1.5] {
h.add(i).unwrap();
h1.add(i).unwrap();
}
for &i in &[0., 0.3, 0.5, 0.5, 0.9] {
h.add(i).unwrap();
h2.add(i).unwrap();
}
println!("{:?}", h.bins());
println!("{:?}", h1.bins());
println!("{:?}", h2.bins());
println!();
h1.merge(&h2);
println!("{:?}", h1.bins());
assert_eq!(h.bins(), h1.bins());
}
#[cfg(feature = "serde1")]
#[test]
fn simple_serde() {
let mut a = Histogram10::from_ranges(
[0., 0.1, 0.2, 0.3, 0.4, 0.5, 0.7, 0.8, 0.9, 1.0, 2.0].iter().cloned()).unwrap();
for &i in &[0.05, 0.7, 1.0, 1.5] {
a.add(i).unwrap();
}
let b = serde_json::to_string(&a).unwrap();
assert_eq!(&b, "{\"range\":[0.0,0.1,0.2,0.3,0.4,0.5,0.7,0.8,0.9,1.0,2.0],\"bin\":[1,0,0,0,0,0,1,0,0,2]}");
let c: Histogram10 = serde_json::from_str(&b).unwrap();
assert_eq!(c.bins(), &[1, 0, 0, 0, 0, 0, 1, 0, 0, 2]);
}