Allow sum_axis and mean_axis for empty arrays

Author: jturner314

src/numeric/impl_numeric.rs

@@ -61,14 +61,13 @@ impl<A, S, D> ArrayBase<S, D>
     /// );
     /// ```
     ///
-    /// **Panics** if `axis` is out of bounds or if the length of the axis is
-    /// zero.
+    /// **Panics** if `axis` is out of bounds.
     pub fn sum_axis(&self, axis: Axis) -> Array<A, D::Smaller>
         where A: Clone + Zero + Add<Output=A>,
               D: RemoveAxis,
     {
         let n = self.len_of(axis);
-        let mut res = self.subview(axis, 0).to_owned();
+        let mut res = Array::zeros(self.raw_dim().remove_axis(axis));
         let stride = self.strides()[axis.index()];
         if self.ndim() == 2 && stride == 1 {
             // contiguous along the axis we are summing
@@ -77,7 +76,7 @@ impl<A, S, D> ArrayBase<S, D>
                 *elt = self.subview(Axis(1 - ax), i).scalar_sum();
             }
         } else {
-            for i in 1..n {
+            for i in 0..n {
                 let view = self.subview(axis, i);
                 res = res + &view;
             }
@@ -88,7 +87,7 @@ impl<A, S, D> ArrayBase<S, D>
     /// Return mean along `axis`.
     ///
     /// **Panics** if `axis` is out of bounds or if the length of the axis is
-    /// zero.
+    /// zero and division by zero panics for type `A`.
     ///
     /// ```
     /// use ndarray::{aview1, arr2, Axis};
@@ -106,8 +105,8 @@ impl<A, S, D> ArrayBase<S, D>
     {
         let n = self.len_of(axis);
         let sum = self.sum_axis(axis);
-        let mut cnt = A::one();
-        for _ in 1..n {
+        let mut cnt = A::zero();
+        for _ in 0..n {
             cnt = cnt + A::one();
         }
         sum / &aview0(&cnt)

tests/array.rs

@@ -697,6 +697,22 @@ fn sum_mean()
     assert_eq!(a.scalar_sum(), 10.);
 }
 
+#[test]
+fn sum_mean_empty() {
+    assert_eq!(Array3::<f32>::ones((2, 0, 3)).scalar_sum(), 0.);
+    assert_eq!(Array1::<f32>::ones(0).sum_axis(Axis(0)), arr0(0.));
+    assert_eq!(
+        Array3::<f32>::ones((2, 0, 3)).sum_axis(Axis(1)),
+        Array::zeros((2, 3)),
+    );
+    let a = Array1::<f32>::ones(0).mean_axis(Axis(0));
+    assert_eq!(a.shape(), &[]);
+    assert!(a[()].is_nan());
+    let a = Array3::<f32>::ones((2, 0, 3)).mean_axis(Axis(1));
+    assert_eq!(a.shape(), &[2, 3]);
+    a.mapv(|x| assert!(x.is_nan()));
+}
+
 #[test]
 fn var_axis() {
     let a = array![