Merge pull request #47 from mgeisler/ndarray-optional

Make the dependency on the ndarray crate optional
mgeisler · Aug 23, 2020 · 06ef9ee · 06ef9ee
2 parents dc846a2 + 4cf68fd
commit 06ef9ee
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Showing 8 changed files with 104 additions and 64 deletions.
diff --git a/Cargo.toml b/Cargo.toml
@@ -16,7 +16,7 @@ appveyor = { repository = "mgeisler/smawk" }
 codecov = { repository = "mgeisler/smawk" }
 
 [dependencies]
-ndarray = "0.13"
+ndarray = { version = "0.13", optional = true }
 num-traits = "0.2"
 rand = "0.7"
 

diff --git a/benches/comparison.rs b/benches/comparison.rs
@@ -1,3 +1,4 @@
+#![cfg(feature = "ndarray")]
 #![feature(test)]
 
 extern crate test;

diff --git a/src/brute_force.rs b/src/brute_force.rs
@@ -1,4 +1,10 @@
 //! Brute-force algorithm for finding column minima.
+//!
+//! The functions here are mostly meant to be used for testing
+//! correctness of the SMAWK implementation.
+//!
+//! **Note: this module is only available if you enable the `ndarray`
+//! Cargo feature.**
 
 use ndarray::{Array2, ArrayView1};
 

diff --git a/src/lib.rs b/src/lib.rs
@@ -90,8 +90,11 @@
 
 #![doc(html_root_url = "https://docs.rs/smawk/0.2.0")]
 
+#[cfg(feature = "ndarray")]
 pub mod brute_force;
+#[cfg(feature = "ndarray")]
 pub mod monge;
+#[cfg(feature = "ndarray")]
 pub mod recursive;
 
 /// Minimal matrix trait for two-dimensional arrays.
@@ -101,6 +104,9 @@ pub mod recursive;
 /// elements. Modeled after
 /// [`ndarray::Array2`](https://docs.rs/ndarray/latest/ndarray/type.Array2.html)
 /// from the [ndarray crate ](https://crates.io/crates/ndarray).
+///
+/// Enable the `ndarray` Cargo feature if you want to use it with
+/// `ndarray::Array2`.
 pub trait Matrix<T: Copy> {
     /// Return the number of rows.
     fn nrows(&self) -> usize;
@@ -129,6 +135,10 @@ impl<T: Copy> Matrix<T> for Vec<Vec<T>> {
 }
 
 /// Adapting `ndarray::Array2` to the `Matrix` trait.
+///
+/// **Note: this implementation is only available if you enable the
+/// `ndarray` Cargo feature.**
+#[cfg(feature = "ndarray")]
 impl<T: Copy> Matrix<T> for ndarray::Array2<T> {
     #[inline]
     fn nrows(&self) -> usize {
@@ -376,120 +386,127 @@ pub fn online_column_minima<T: Copy + Ord, M: Fn(&[(usize, T)], usize, usize) ->
 #[cfg(test)]
 mod tests {
     use super::*;
-    use ndarray::arr2;
 
     #[test]
     fn smawk_1x1() {
-        let matrix = arr2(&[[2]]);
-        let minima = vec![0];
-        assert_eq!(smawk_row_minima(&matrix), minima);
-        assert_eq!(smawk_column_minima(&matrix.reversed_axes()), minima);
+        let matrix = vec![vec![2]];
+        assert_eq!(smawk_row_minima(&matrix), vec![0]);
+        assert_eq!(smawk_column_minima(&matrix), vec![0]);
     }
 
     #[test]
     fn smawk_2x1() {
-        let matrix = arr2(&[[3], [2]]);
-        let minima = vec![0, 0];
-        assert_eq!(smawk_row_minima(&matrix), minima);
-        assert_eq!(smawk_column_minima(&matrix.reversed_axes()), minima);
+        let matrix = vec![
+            vec![3], //
+            vec![2],
+        ];
+        assert_eq!(smawk_row_minima(&matrix), vec![0, 0]);
+        assert_eq!(smawk_column_minima(&matrix), vec![1]);
     }
 
     #[test]
     fn smawk_1x2() {
-        let matrix = arr2(&[[2, 1]]);
-        let minima = vec![1];
-        assert_eq!(smawk_row_minima(&matrix), minima);
-        assert_eq!(smawk_column_minima(&matrix.reversed_axes()), minima);
+        let matrix = vec![vec![2, 1]];
+        assert_eq!(smawk_row_minima(&matrix), vec![1]);
+        assert_eq!(smawk_column_minima(&matrix), vec![0, 0]);
     }
 
     #[test]
     fn smawk_2x2() {
-        let matrix = arr2(&[[3, 2], [2, 1]]);
-        let minima = vec![1, 1];
-        assert_eq!(smawk_row_minima(&matrix), minima);
-        assert_eq!(smawk_column_minima(&matrix.reversed_axes()), minima);
+        let matrix = vec![
+            vec![3, 2], //
+            vec![2, 1],
+        ];
+        assert_eq!(smawk_row_minima(&matrix), vec![1, 1]);
+        assert_eq!(smawk_column_minima(&matrix), vec![1, 1]);
     }
 
     #[test]
     fn smawk_3x3() {
-        let matrix = arr2(&[[3, 4, 4], [3, 4, 4], [2, 3, 3]]);
-        let minima = vec![0, 0, 0];
-        assert_eq!(smawk_row_minima(&matrix), minima);
-        assert_eq!(smawk_column_minima(&matrix.reversed_axes()), minima);
+        let matrix = vec![
+            vec![3, 4, 4], //
+            vec![3, 4, 4],
+            vec![2, 3, 3],
+        ];
+        assert_eq!(smawk_row_minima(&matrix), vec![0, 0, 0]);
+        assert_eq!(smawk_column_minima(&matrix), vec![2, 2, 2]);
     }
 
     #[test]
     fn smawk_4x4() {
-        let matrix = arr2(&[[4, 5, 5, 5], [2, 3, 3, 3], [2, 3, 3, 3], [2, 2, 2, 2]]);
-        let minima = vec![0, 0, 0, 0];
-        assert_eq!(smawk_row_minima(&matrix), minima);
-        assert_eq!(smawk_column_minima(&matrix.reversed_axes()), minima);
+        let matrix = vec![
+            vec![4, 5, 5, 5], //
+            vec![2, 3, 3, 3],
+            vec![2, 3, 3, 3],
+            vec![2, 2, 2, 2],
+        ];
+        assert_eq!(smawk_row_minima(&matrix), vec![0, 0, 0, 0]);
+        assert_eq!(smawk_column_minima(&matrix), vec![1, 3, 3, 3]);
     }
 
     #[test]
     fn smawk_5x5() {
-        let matrix = arr2(&[
-            [3, 2, 4, 5, 6],
-            [2, 1, 3, 3, 4],
-            [2, 1, 3, 3, 4],
-            [3, 2, 4, 3, 4],
-            [4, 3, 2, 1, 1],
-        ]);
-        let minima = vec![1, 1, 1, 1, 3];
-        assert_eq!(smawk_row_minima(&matrix), minima);
-        assert_eq!(smawk_column_minima(&matrix.reversed_axes()), minima);
+        let matrix = vec![
+            vec![3, 2, 4, 5, 6],
+            vec![2, 1, 3, 3, 4],
+            vec![2, 1, 3, 3, 4],
+            vec![3, 2, 4, 3, 4],
+            vec![4, 3, 2, 1, 1],
+        ];
+        assert_eq!(smawk_row_minima(&matrix), vec![1, 1, 1, 1, 3]);
+        assert_eq!(smawk_column_minima(&matrix), vec![1, 1, 4, 4, 4]);
     }
 
     #[test]
     fn online_1x1() {
-        let matrix = arr2(&[[0]]);
+        let matrix = vec![vec![0]];
         let minima = vec![(0, 0)];
-        assert_eq!(
-            online_column_minima(0, 1, |_, i, j| matrix[[i, j]],),
-            minima
-        );
+        assert_eq!(online_column_minima(0, 1, |_, i, j| matrix[i][j]), minima);
     }
 
     #[test]
     fn online_2x2() {
-        let matrix = arr2(&[[0, 2], [0, 0]]);
+        let matrix = vec![
+            vec![0, 2], //
+            vec![0, 0],
+        ];
         let minima = vec![(0, 0), (0, 2)];
-        assert_eq!(
-            online_column_minima(0, 2, |_, i, j| matrix[[i, j]],),
-            minima
-        );
+        assert_eq!(online_column_minima(0, 2, |_, i, j| matrix[i][j]), minima);
     }
 
     #[test]
     fn online_3x3() {
-        let matrix = arr2(&[[0, 4, 4], [0, 0, 4], [0, 0, 0]]);
+        let matrix = vec![
+            vec![0, 4, 4], //
+            vec![0, 0, 4],
+            vec![0, 0, 0],
+        ];
         let minima = vec![(0, 0), (0, 4), (0, 4)];
-        assert_eq!(
-            online_column_minima(0, 3, |_, i, j| matrix[[i, j]],),
-            minima
-        );
+        assert_eq!(online_column_minima(0, 3, |_, i, j| matrix[i][j]), minima);
     }
 
     #[test]
     fn online_4x4() {
-        let matrix = arr2(&[[0, 5, 5, 5], [0, 0, 3, 3], [0, 0, 0, 3], [0, 0, 0, 0]]);
+        let matrix = vec![
+            vec![0, 5, 5, 5], //
+            vec![0, 0, 3, 3],
+            vec![0, 0, 0, 3],
+            vec![0, 0, 0, 0],
+        ];
         let minima = vec![(0, 0), (0, 5), (1, 3), (1, 3)];
-        assert_eq!(
-            online_column_minima(0, 4, |_, i, j| matrix[[i, j]],),
-            minima
-        );
+        assert_eq!(online_column_minima(0, 4, |_, i, j| matrix[i][j]), minima);
     }
 
     #[test]
     fn online_5x5() {
-        let matrix = arr2(&[
-            [0, 2, 4, 6, 7],
-            [0, 0, 3, 4, 5],
-            [0, 0, 0, 3, 4],
-            [0, 0, 0, 0, 4],
-            [0, 0, 0, 0, 0],
-        ]);
+        let matrix = vec![
+            vec![0, 2, 4, 6, 7],
+            vec![0, 0, 3, 4, 5],
+            vec![0, 0, 0, 3, 4],
+            vec![0, 0, 0, 0, 4],
+            vec![0, 0, 0, 0, 0],
+        ];
         let minima = vec![(0, 0), (0, 2), (1, 3), (2, 3), (2, 4)];
-        assert_eq!(online_column_minima(0, 5, |_, i, j| matrix[[i, j]]), minima);
+        assert_eq!(online_column_minima(0, 5, |_, i, j| matrix[i][j]), minima);
     }
 }
diff --git a/src/monge.rs b/src/monge.rs
@@ -1,4 +1,10 @@
 //! Functions for generating and checking Monge arrays.
+//!
+//! The functions here are mostly meant to be used for testing
+//! correctness of the SMAWK implementation.
+//!
+//! **Note: this module is only available if you enable the `ndarray`
+//! Cargo feature.**
 
 use ndarray::{s, Array2};
 use num_traits::{PrimInt, WrappingAdd};

diff --git a/src/recursive.rs b/src/recursive.rs
@@ -1,4 +1,10 @@
 //! Recursive algorithm for finding column minima.
+//!
+//! The functions here are mostly meant to be used for testing
+//! correctness of the SMAWK implementation.
+//!
+//! **Note: this module is only available if you enable the `ndarray`
+//! Cargo feature.**
 
 use ndarray::{s, Array2, ArrayView2, Axis};
 

diff --git a/tests/agreement.rs b/tests/agreement.rs
@@ -1,3 +1,5 @@
+#![cfg(feature = "ndarray")]
+
 use ndarray::{s, Array2};
 use rand::SeedableRng;
 use rand_chacha::ChaCha20Rng;

diff --git a/tests/complexity.rs b/tests/complexity.rs
@@ -1,3 +1,5 @@
+#![cfg(feature = "ndarray")]
+
 use ndarray::{Array1, Array2};
 use rand::SeedableRng;
 use rand_chacha::ChaCha20Rng;