Implement kronecker product

Author: maxtremblay

src/matrix/kronecker.rs

@@ -0,0 +1,68 @@
+use super::SparseBinMat;
+use crate::SparseBinSlice;
+
+pub(super) fn kronecker_product(
+    left_matrix: &SparseBinMat,
+    right_matrix: &SparseBinMat,
+) -> SparseBinMat {
+    let rows = left_matrix
+        .rows()
+        .flat_map(|row| kron_row(row, right_matrix))
+        .collect();
+    let number_of_columns = left_matrix.number_of_columns * right_matrix.number_of_columns();
+    SparseBinMat::new(number_of_columns, rows)
+}
+
+fn kron_row<'a>(
+    left_row: SparseBinSlice<'a>,
+    right_matrix: &'a SparseBinMat,
+) -> impl Iterator<Item = Vec<usize>> + 'a {
+    right_matrix.rows().map(move |right_row| {
+        left_row
+            .non_trivial_positions()
+            .flat_map(|position| pad_row(position * right_row.len(), &right_row))
+            .collect()
+    })
+}
+
+fn pad_row<'a>(pad: usize, row: &'a SparseBinSlice<'a>) -> impl Iterator<Item = usize> + 'a {
+    row.non_trivial_positions()
+        .map(move |position| position + pad)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+
+    #[test]
+    fn left_kron_with_identity() {
+        let matrix = SparseBinMat::new(4, vec![vec![0, 2], vec![1, 3]]);
+        let product = matrix.kron_with(&SparseBinMat::identity(2));
+        let expected = SparseBinMat::new(8, vec![vec![0, 4], vec![1, 5], vec![2, 6], vec![3, 7]]);
+        assert_eq!(product, expected);
+    }
+
+    #[test]
+    fn right_kron_with_identity() {
+        let matrix = SparseBinMat::new(4, vec![vec![0, 2], vec![1, 3]]);
+        let product = SparseBinMat::identity(2).kron_with(&matrix);
+        let expected = SparseBinMat::new(8, vec![vec![0, 2], vec![1, 3], vec![4, 6], vec![5, 7]]);
+        assert_eq!(product, expected);
+    }
+
+    #[test]
+    fn kron_with_itself() {
+        let matrix = SparseBinMat::new(4, vec![vec![0, 2], vec![1, 3]]);
+        let product = matrix.kron_with(&matrix);
+        let expected = SparseBinMat::new(
+            16,
+            vec![
+                vec![0, 2, 8, 10],
+                vec![1, 3, 9, 11],
+                vec![4, 6, 12, 14],
+                vec![5, 7, 13, 15],
+            ],
+        );
+        assert_eq!(product, expected);
+    }
+}

src/matrix/mod.rs

@@ -17,6 +17,9 @@ use constructor_utils::initialize_from;
 mod gauss_jordan;
 use gauss_jordan::GaussJordan;
 
+mod kronecker;
+use kronecker::kronecker_product;
+
 mod non_trivial_elements;
 pub use self::non_trivial_elements::NonTrivialElements;
 
@@ -733,6 +736,24 @@ impl SparseBinMat {
         self.keep_only_columns(&to_keep)
     }
 
+    /// Returns the Kronecker product of two matrices.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # use sparse_bin_mat::SparseBinMat;
+    /// let left_matrix = SparseBinMat::new(2, vec![vec![1], vec![0]]);
+    /// let right_matrix = SparseBinMat::new(3, vec![vec![0, 1], vec![1, 2]]);
+    ///
+    /// let product = left_matrix.kron_with(&right_matrix);
+    /// let expected = SparseBinMat::new(6, vec![vec![3, 4], vec![4, 5], vec![0, 1], vec![1, 2]]);
+    ///
+    /// assert_eq!(product, expected);
+    /// ```
+    pub fn kron_with(&self, other: &Self) -> Self {
+        kronecker_product(self, other)
+    }
+
     /// Returns a json string for the matrix.
     pub fn as_json(&self) -> Result<String, serde_json::Error> {
         serde_json::to_string(self)