Use into_matrix

Author: termoshtt

ndarray-linalg/src/svd.rs

@@ -2,12 +2,9 @@
 //!
 //! [Wikipedia article on SVD](https://en.wikipedia.org/wiki/Singular_value_decomposition)
 
+use crate::{convert::*, error::*, layout::*, types::*};
 use ndarray::*;
 
-use super::error::*;
-use super::layout::*;
-use super::types::*;
-
 /// singular-value decomposition of matrix reference
 pub trait SVD {
     type U;
@@ -98,27 +95,11 @@ where
         let l = self.layout()?;
         let svd_res = unsafe { A::svd(l, calc_u, calc_vt, self.as_allocated_mut()?)? };
         let (n, m) = l.size();
-        let n = n as usize;
-        let m = m as usize;
-
-        let u = svd_res.u.map(|u| {
-            assert_eq!(u.len(), n * n);
-            match l {
-                MatrixLayout::F { .. } => Array::from_shape_vec((n, n).f(), u),
-                MatrixLayout::C { .. } => Array::from_shape_vec((n, n), u),
-            }
-            .unwrap()
-        });
-
-        let vt = svd_res.vt.map(|vt| {
-            assert_eq!(vt.len(), m * m);
-            match l {
-                MatrixLayout::F { .. } => Array::from_shape_vec((m, m).f(), vt),
-                MatrixLayout::C { .. } => Array::from_shape_vec((m, m), vt),
-            }
-            .unwrap()
-        });
 
+        let u = svd_res.u.map(|u| into_matrix(l.resized(n, n), u).unwrap());
+        let vt = svd_res
+            .vt
+            .map(|vt| into_matrix(l.resized(m, m), vt).unwrap());
         let s = ArrayBase::from(svd_res.s);
         Ok((u, s, vt))
     }