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add simple test, remove comment from old variance impl

This commit is contained in:
vasil 2023-04-24 23:22:32 +03:00
parent 032002dce9
commit fc56abe481
2 changed files with 8 additions and 16 deletions
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17
src/base/statistics.rs
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@ -335,25 +335,14 @@ impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
if self.is_empty() { if self.is_empty() {
T::zero() T::zero()
} else { } else {
// let val = self.iter().cloned().fold((T::zero(), T::zero()), |a, b| {
// (a.0 + b.clone() * b.clone(), a.1 + b)
// });
// let denom = T::one() / crate::convert::<_, T>(self.len() as f64);
// let vd = val.1 * denom.clone();
// val.0 * denom - vd.clone() * vd
// let mean: T = self.iter().map(|&entry| entry).sum::<T>();
//
// let x: Vec<T> = (0..1000).map(|_| T::zero()).collect();
// let s: T = x.iter().cloned().fold(T::zero(), |a, b| a + b);
// cannot use sum since `T` is not `Sum` by trait bounds // cannot use sum since `T` is not `Sum` by trait bounds
let total_sum = self.iter().cloned().fold(T::zero(), |a, b| a + b); let sum_of_elements = self.iter().cloned().fold(T::zero(), |a, b| a + b);
let n_elements = crate::convert::<_, T>(self.len() as f64); let n_elements = crate::convert::<_, T>(self.len() as f64);
let mean = total_sum / n_elements.clone(); let mean = sum_of_elements / n_elements.clone();
let variance = self.iter().cloned().fold(T::zero(), |acc, x| { let variance = self.iter().cloned().fold(T::zero(), |acc, x| {
acc + (x.clone() - mean.clone()) * (x.clone() - mean.clone()) acc + (x.clone() - mean.clone()) * (x.clone() - mean.clone())
}) / n_elements.clone(); }) / n_elements;
variance variance
} }

7
src/base/variance_test.rs
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@ -2,6 +2,9 @@
use crate::DVector; use crate::DVector;
#[test] #[test]
fn test_variance_new() { fn test_variance_new() {
let v = DVector::repeat(10_000, 100000000.0); let long_repeating_vector = DVector::repeat(10_000, 100000000.0);
assert_eq!(v.variance(), 0.0) assert_eq!(long_repeating_vector.variance(), 0.0);
let short_vec = DVector::from_vec(vec![1., 2., 3.]);
assert_eq!(short_vec.variance(), 2.0 / 3.0)
} }