chore: BhattacharyyaDist

Author: Qazalbash

src/distance.rs

@@ -5,10 +5,10 @@ pub use crate::generic::metric::{
 };
 pub use crate::generic::pre_metric::{GenKLDivergence, KLDivergence};
 pub use crate::generic::semi_metric::{
-    BrayCurtis, ChiSqDist, JSDivergence, MeanAbsDeviation, MeanSqDeviation, SqEuclidean,
+    BhattacharyyaDist, BrayCurtis, ChiSqDist, JSDivergence, MeanAbsDeviation, MeanSqDeviation,
+    SqEuclidean,
 };
 
-
 /// Implement this trait for a distance metric. The trait provides a method to evaluate the distance
 /// between two arrays along a specified axis.
 pub trait Distance<T>
@@ -159,3 +159,15 @@ impl<T: 'static + num_traits::Float + num_traits::FromPrimitive> Distance<T> for
         (x - y).pow2().mean_axis(axis).unwrap().sqrt()
     }
 }
+
+#[doc(hidden)]
+impl<T: 'static + num_traits::Float + num_traits::FromPrimitive + ndarray::ScalarOperand>
+    Distance<T> for BhattacharyyaDist
+{
+    unsafe fn distance(&self, x: &ArrayD<T>, y: &ArrayD<T>, axis: Axis) -> ArrayD<T> {
+        let ln_sqrt_sum_x_y = (x * y).sqrt().sum_axis(axis).ln();
+        let sqrt_sum_x = x.sum_axis(axis).ln() * T::from(0.5).unwrap();
+        let sqrt_sum_y = y.sum_axis(axis).ln() * T::from(0.5).unwrap();
+        sqrt_sum_x + sqrt_sum_y - ln_sqrt_sum_x_y
+    }
+}

src/generic.rs

@@ -19,23 +19,23 @@ macro_rules! impl_metric {
     };
 }
 
-
 pub mod pre_metric {
     impl_metric! {
-        KLDivergence,
         GenKLDivergence,
+        KLDivergence,
         NormRMSDeviation,
     }
 }
 pub mod semi_metric {
     impl_metric! {
-        SqEuclidean,
+        BhattacharyyaDist,
         BrayCurtis,
         ChiSqDist,
         JSDivergence,
-        SpanNormDist,
         MeanAbsDeviation,
         MeanSqDeviation,
+        SpanNormDist,
+        SqEuclidean,
     }
 }
 pub mod metric {

src/lib.rs

@@ -34,6 +34,9 @@ pub use generic::pre_metric::GenKLDivergence;
 /// `KLDivergence(x, y) = sum(x .* ln(x ./ y))`
 #[doc(inline)]
 pub use generic::pre_metric::KLDivergence;
+/// `BhattacharyyaDist(x, y) = -ln(sum(sqrt(x .* y)))+0.5*ln(sum(x))+0.5*ln(sum(y))`
+#[doc(inline)]
+pub use generic::semi_metric::BhattacharyyaDist;
 /// `BrayCurtis(x, y) = sum(|x - y|) / sum(|x + y|)`
 #[doc(inline)]
 pub use generic::semi_metric::BrayCurtis;

tests/common/mod.rs

@@ -73,7 +73,6 @@ macro_rules! test_triangular_inequality {
     };
 }
 
-
 #[macro_export]
 macro_rules! test_only_on_negative_values {
     ($shape:expr, $axis:expr, $metric:expr, $name:ident) => {
@@ -89,7 +88,6 @@ macro_rules! test_only_on_negative_values {
     };
 }
 
-
 #[macro_export]
 macro_rules! test_on_negative_and_positive_values {
     ($shape:expr, $axis:expr, $metric:expr, $name:ident) => {

tests/tests.rs

@@ -1,8 +1,8 @@
 mod common;
 use faasle::{
-    BrayCurtis, Chebyshev, ChiSqDist, Cityblock, Distance, Euclidean, GenKLDivergence, Hamming,
-    JSDivergence, KLDivergence, MeanAbsDeviation, MeanSqDeviation, Minkowski, RMSDeviation,
-    SqEuclidean, TotalVariation,
+    BhattacharyyaDist, BrayCurtis, Chebyshev, ChiSqDist, Cityblock, Distance, Euclidean,
+    GenKLDivergence, Hamming, JSDivergence, KLDivergence, MeanAbsDeviation, MeanSqDeviation,
+    Minkowski, RMSDeviation, SqEuclidean, TotalVariation,
 };
 use ndarray::{Array, Axis};
 use ndarray_rand::rand_distr::Uniform;
@@ -88,4 +88,5 @@ enumerate_tests! {
     semi_metric: (js_divergence, JSDivergence::new()),
     semi_metric: (mean_sq_deviation, MeanSqDeviation::new()),
     semi_metric: (sq_euclidean, SqEuclidean::new()),
+    semi_metric: (bhattacharyya_dist, BhattacharyyaDist::new()),
 }