Add test comparing to streaming-stats

benches/average.rs

@@ -6,6 +6,7 @@ extern crate stats;
 
 use bencher::Bencher;
 
+/// Create a random vector by sampling from a normal distribution.
 fn initialize_vec() -> Vec<f64> {
     use rand::distributions::{Normal, IndependentSample};
     use rand::{XorShiftRng, SeedableRng};

src/lib.rs

@@ -140,13 +140,15 @@ impl core::iter::FromIterator<f64> for Average {
 ///
 /// On panic, this macro will print the values of the expressions with their
 /// debug representations.
+#[macro_export]
 macro_rules! assert_almost_eq {
     ($a:expr, $b:expr, $prec:expr) => (
-        if ($a - $b).abs() > $prec {
+        let diff = ($a - $b).abs();
+        if diff > $prec {
             panic!(format!(
-                "assertion failed: `abs(left - right) < {:e}`, \
+                "assertion failed: `abs(left - right) = {:.1e} < {:e}`, \
                  (left: `{}`, right: `{}`)",
-                $prec, $a, $b));
+                diff, $prec, $a, $b));
         }
     );
 }

tests/average.rs

@@ -0,0 +1,35 @@
+#[macro_use] extern crate average;
+
+extern crate rand;
+extern crate stats;
+
+/// Create a random vector by sampling from a normal distribution.
+fn initialize_vec(size: usize) -> Vec<f64> {
+    use rand::distributions::{Normal, IndependentSample};
+    use rand::{XorShiftRng, SeedableRng};
+    let normal = Normal::new(2.0, 3.0);
+    let mut values = Vec::with_capacity(size);
+    let mut rng = XorShiftRng::from_seed([1, 2, 3, 4]);
+    for _ in 0..size {
+        values.push(normal.ind_sample(&mut rng));
+    }
+    values
+}
+
+#[test]
+fn average_vs_streaming_stats_small() {
+    let values = initialize_vec(100);
+    let a: average::Average = values.iter().map(|x| *x).collect();
+    let b: stats::OnlineStats = values.iter().map(|x| *x).collect();
+    assert_almost_eq!(a.mean(), b.mean(), 1e-16);
+    assert_almost_eq!(a.population_variance(), b.variance(), 1e-16);
+}
+
+#[test]
+fn average_vs_streaming_stats_large() {
+    let values = initialize_vec(1_000_000);
+    let a: average::Average = values.iter().map(|x| *x).collect();
+    let b: stats::OnlineStats = values.iter().map(|x| *x).collect();
+    assert_almost_eq!(a.mean(), b.mean(), 1e-16);
+    assert_almost_eq!(a.population_variance(), b.variance(), 1e-13);
+}