@@ -44,7 +44,8 @@ impl<A: Scalar> MGS<A> {
4444 ///
4545 /// Panic
4646 /// -------
47- /// - if the size of the input array mismaches to the dimension
47+ /// - if the size of the input array mismatches to the dimension
48+ ///
4849 pub fn orthogonalize < S > ( & self , a : & mut ArrayBase < S , Ix1 > ) -> Array1 < A >
4950 where
5051 A : Lapack ,
@@ -67,7 +68,7 @@ impl<A: Scalar> MGS<A> {
6768 ///
6869 /// Panic
6970 /// -------
70- /// - if the size of the input array mismaches to the dimension
71+ /// - if the size of the input array mismatches to the dimension
7172 ///
7273 /// ```rust
7374 /// # use ndarray::*;
@@ -79,7 +80,7 @@ impl<A: Scalar> MGS<A> {
7980 /// let coef = mgs.append(array![1.0, 1.0, 0.0], 1e-9).unwrap();
8081 /// close_l2(&coef, &array![1.0, 1.0], 1e-9);
8182 ///
82- /// assert!(mgs.append(array![1.0, 2.0, 0.0], 1e-9).is_err()); // Fail if the vector is linearly dependend
83+ /// assert!(mgs.append(array![1.0, 2.0, 0.0], 1e-9).is_err()); // Fail if the vector is linearly dependent
8384 ///
8485 /// if let Err(coef) = mgs.append(array![1.0, 2.0, 0.0], 1e-9) {
8586 /// close_l2(&coef, &array![2.0, 1.0, 0.0], 1e-9); // You can get coefficients of dependent vector
@@ -117,15 +118,14 @@ pub enum Strategy {
117118 /// Skip dependent vector
118119 Skip ,
119120
120- /// Orghotonalize dependent vector without adding to Q,
121- /// thus R must be non-regular like following:
121+ /// Orthogonalize dependent vector without adding to Q,
122+ /// i.e. R must be non-square like following:
122123 ///
123124 /// ```text
124125 /// x x x x x
125126 /// 0 x x x x
126127 /// 0 0 0 x x
127128 /// 0 0 0 0 x
128- /// 0 0 0 0 0 // 0-filled to be square matrix
129129 /// ```
130130 Full ,
131131}
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