created API from MGS #8

src/lib.rs

@@ -33,5 +33,7 @@ println!("eigenvectors:{}", eig.eigenvectors);
 
 pub mod algorithms;
 pub mod matrix_operations;
+pub mod modified_gram_schmidt;
 pub mod utils;
 pub use algorithms::{davidson, SpectrumTarget};
+pub use modified_gram_schmidt::{MGS};

src/modified_gram_schmidt.rs

@@ -0,0 +1,47 @@
+/*!
+
+# Modified Gram-Schmidt (MGS)
+
+The Gram-Schmidt method is a method for orthonormalising a set of vectors. see:
+[Gram-Schmidt process](https://en.wikipedia.org/wiki/Gram%E2%80%93Schmidt_process)
+The MGS method improves the orthogonality loss due to the finite numerical precision
+on computers.
+ */
+
+extern crate nalgebra as na;
+use na::DMatrix;
+
+pub struct MGS {
+    pub basis: DMatrix<f64>,
+}
+
+impl MGS {
+    /// The new static method takes a single argument:
+    /// * `vectors` to diagonalize as columns of the matrix
+    pub fn new(vectors: DMatrix<f64>) -> Result<Self, &'static str> {
+        let mut result = Err("Something when wrong!");
+        result
+    }
+}
+
+#[cfg(test)]
+mod test {
+    extern crate nalgebra as na;
+    use approx::relative_eq;
+    use na::DMatrix;
+
+    #[test]
+    fn test_gram_schmidt() {
+        let dim = 10;
+        let vectors = DMatrix::<f64>::new_random(dim, dim);
+        let mgs_result = super::MGS::new(vectors);
+        let basis: DMatrix<f64> = match mgs_result {
+            Ok(ortho) => ortho.basis,
+            Err(message) => panic!(message),
+        };
+
+        let result = basis.transpose() * &basis;
+        let diag = result.sum();
+        assert!(relative_eq!(diag, dim as f64, epsilon = 1e-8));
+    }
+}