use matrixcompare::assert_matrix_eq;
use nalgebra::matrix;
use nalgebra::Complex;
use nalgebra_sparse::io::{
load_coo_from_matrix_market_file, load_coo_from_matrix_market_str, save_to_matrix_market_file,
save_to_matrix_market_str,
};
use nalgebra_sparse::proptest::coo_no_duplicates;
use nalgebra_sparse::CooMatrix;
use proptest::prelude::*;
use tempfile::tempdir;
type C64 = Complex<f64>;
type C32 = Complex<f32>;
#[test]
#[rustfmt::skip]
fn test_matrixmarket_load_sparse_real_general_empty() {
// Test several valid zero-shapes of a sparse matrix
let shapes = vec![ (0, 0), (1, 0), (0, 1) ];
let strings: Vec<String> = shapes
.iter()
.map(|(m, n)| format!("%%MatrixMarket matrix coordinate real general\n {} {} 0", m, n))
.collect();
for (shape,string) in shapes.iter().zip(strings.iter()) {
let sparse_mat = load_coo_from_matrix_market_str::<f32>(string).unwrap();
assert_eq!(sparse_mat.nrows(), shape.0);
assert_eq!(sparse_mat.ncols(), shape.1);
assert_eq!(sparse_mat.nnz(), 0);
}
}
#[test]
#[rustfmt::skip]
fn test_matrixmarket_load_dense_real_general_empty() {
// Test several valid zero-shapes of a dense matrix
let shapes = vec![ (0, 0), (1, 0), (0, 1) ];
let strings: Vec<String> = shapes
.iter()
.map(|(m, n)| format!("%%MatrixMarket matrix array real general\n {} {}", m, n))
.collect();
for (shape,string) in shapes.iter().zip(strings.iter()) {
let sparse_mat = load_coo_from_matrix_market_str::<f32>(string).unwrap();
assert_eq!(sparse_mat.nrows(), shape.0);
assert_eq!(sparse_mat.ncols(), shape.1);
assert_eq!(sparse_mat.nnz(), 0);
}
}
#[test]
#[rustfmt::skip]
fn test_matrixmarket_load_sparse_real_general() {
let file_str = r#"
%%MatrixMarket matrix CoOrdinate real general
% This is also an example of free-format features.
%=================================================================================
%
% This ASCII file represents a sparse MxN matrix with L
% nonzeros in the following Matrix Market format:
%
% +----------------------------------------------+
% |%%MatrixMarket matrix coordinate real general | <--- header line
% |% | <--+
% |% comments | |-- 0 or more comment lines
% |% | <--+
% | M T L | <--- rows, columns, entries
% | I1 J1 A(I1, J1) | <--+
% | I2 J2 A(I2, J2) | |
% | I3 J3 A(I3, J3) | |-- L lines
% | . . . | |
% | IL JL A(IL, JL) | <--+
% +----------------------------------------------+
%
% Indices are 1-based, i.e. A(1,1) is the first element.
%
%=================================================================================
5 5 8
1 1 1
2 2 1.050e+01
3 3 1.500e-02
1 4 6.000e+00
4 2 2.505e+02
4 4 -2.800e+02
4 5 3.332e+01
5 5 1.200e+01
"#;
let sparse_mat = load_coo_from_matrix_market_str::<f32>(file_str).unwrap();
let expected = matrix![
1.0, 0.0, 0.0, 6.0, 0.0;
0.0, 10.5, 0.0, 0.0, 0.0;
0.0, 0.0, 0.015, 0.0, 0.0;
0.0, 250.5, 0.0, -280.0, 33.32;
0.0, 0.0, 0.0, 0.0, 12.0;
];
assert_matrix_eq!(sparse_mat, expected);
}
#[test]
#[rustfmt::skip]
fn test_matrixmarket_load_sparse_int_symmetric() {
let file_str = r#"
%%MatrixMarket matrix coordinate integer symmetric
%
5 5 9
1 1 11
2 2 22
3 2 23
3 3 33
4 2 24
4 4 44
5 1 -15
5 3 35
5 5 55
"#;
let sparse_mat = load_coo_from_matrix_market_str::<i128>(file_str).unwrap();
let expected = matrix![
11, 0, 0, 0, -15;
0, 22, 23, 24, 0;
0, 23, 33, 0, 35;
0, 24, 0, 44, 0;
-15, 0, 35, 0, 55;
];
assert_matrix_eq!(sparse_mat, expected);
}
#[test]
#[rustfmt::skip]
fn test_matrixmarket_load_sparse_complex_hermitian() {
let file_str = r#"
%%MatrixMarket matrix coordinate complex hermitian
%
5 5 7
1 1 1.0 0.0
2 2 10.5 0.0
4 2 250.5 22.22
3 3 0.015 0.0
4 4 -2.8e2 0.0
5 5 12.0 0.0
5 4 0.0 33.32
"#;
let sparse_mat = load_coo_from_matrix_market_str::<Complex<f64>>(file_str).unwrap();
let expected = matrix![
C64{re:1.0,im:0.0}, C64{re:0.0,im:0.0}, C64{re:0.0,im:0.0}, C64{re:0.0,im:0.0},C64{re:0.0,im:0.0};
C64{re:0.0,im:0.0}, C64{re:10.5,im:0.0}, C64{re:0.0,im:0.0}, C64{re:250.5,im:-22.22},C64{re:0.0,im:0.0};
C64{re:0.0,im:0.0}, C64{re:0.0,im:0.0}, C64{re:0.015,im:0.0}, C64{re:0.0,im:0.0},C64{re:0.0,im:0.0};
C64{re:0.0,im:0.0}, C64{re:250.5,im:22.22}, C64{re:0.0,im:0.0}, C64{re:-280.0,im:0.0},C64{re:0.0,im:-33.32};
C64{re:0.0,im:0.0}, C64{re:0.0,im:0.0}, C64{re:0.0,im:0.0}, C64{re:0.0,im:33.32},C64{re:12.0,im:0.0};
];
assert_matrix_eq!(sparse_mat, expected);
}
#[test]
#[rustfmt::skip]
fn test_matrixmarket_load_sparse_real_skew() {
let file_str = r#"
%%MatrixMarket matrix coordinate real skew-symmetric
%
5 5 4
3 2 -23.0
4 2 -24.0
5 1 -15.0
5 3 -35.0
"#;
let sparse_mat = load_coo_from_matrix_market_str::<f64>(file_str).unwrap();
let expected = matrix![
0.0, 0.0, 0.0, 0.0, 15.0;
0.0, 0.0, 23.0, 24.0, 0.0;
0.0, -23.0, 0.0, 0.0, 35.0;
0.0, -24.0, 0.0, 0.0, 0.0;
-15.0, 0.0, -35.0, 0.0, 0.0;
];
assert_matrix_eq!(sparse_mat, expected);
}
#[test]
#[rustfmt::skip]
fn test_matrixmarket_load_sparse_pattern_general() {
let file_str = r#"
%%MatrixMarket matrix coordinate pattern general
%
5 5 10
1 1
1 5
2 3
2 4
3 2
3 5
4 1
5 2
5 4
5 5
"#;
let pattern_matrix = load_coo_from_matrix_market_str::<()>(file_str).unwrap();
let nrows = pattern_matrix.nrows();
let ncols = pattern_matrix.ncols();
let (row_idx, col_idx, val) = pattern_matrix.clone().disassemble();
let values = vec![1; val.len()];
let sparse_mat = CooMatrix::try_from_triplets(nrows, ncols, row_idx, col_idx, values).unwrap();
let expected = matrix![
1, 0, 0, 0, 1;
0, 0, 1, 1, 0;
0, 1, 0, 0, 1;
1, 0, 0, 0, 0;
0, 1, 0, 1, 1;
];
assert_matrix_eq!(sparse_mat, expected);
}
#[test]
#[rustfmt::skip]
fn test_matrixmarket_load_dense_real_general() {
let file_str = r#"
%%MatrixMarket matrix array real general
%
4 3
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
11.0
12.0
"#;
let sparse_mat = load_coo_from_matrix_market_str::<f32>(file_str).unwrap();
let expected = matrix![
1.0, 5.0, 9.0;
2.0, 6.0, 10.0;
3.0, 7.0, 11.0;
4.0, 8.0, 12.0;
];
assert_matrix_eq!(sparse_mat, expected);
}
#[test]
#[rustfmt::skip]
fn test_matrixmarket_load_dense_real_symmetric() {
let file_str = r#"
%%MatrixMarket matrix array real symmetric
%
4 4
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
"#;
let sparse_mat = load_coo_from_matrix_market_str::<f32>(file_str).unwrap();
let expected = matrix![
1.0, 2.0, 3.0, 4.0;
2.0, 5.0, 6.0, 7.0;
3.0, 6.0, 8.0, 9.0;
4.0, 7.0, 9.0, 10.0;
];
assert_matrix_eq!(sparse_mat, expected);
}
#[test]
#[rustfmt::skip]
fn test_matrixmarket_load_dense_complex_hermitian() {
let file_str = r#"
%%MatrixMarket matrix array complex hermitian
%
4 4
1.0 0.0
2.0 2.0
3.0 3.0
4.0 4.0
5.0 0.0
6.0 6.0
7.0 7.0
8.0 0.0
9.0 9.0
10.0 0.0
"#;
let sparse_mat = load_coo_from_matrix_market_str::<C64>(file_str).unwrap();
let expected = matrix![
C64{re:1.0,im:0.0}, C64{re:2.0,im:-2.0} ,C64{re:3.0,im:-3.0} ,C64{re:4.0,im:-4.0};
C64{re:2.0,im:2.0}, C64{re:5.0,im:0.0} ,C64{re:6.0,im:-6.0} ,C64{re:7.0,im:-7.0};
C64{re:3.0,im:3.0}, C64{re:6.0,im:6.0} ,C64{re:8.0,im:0.0} ,C64{re:9.0,im:-9.0};
C64{re:4.0,im:4.0}, C64{re:7.0,im:7.0} ,C64{re:9.0,im:9.0} ,C64{re:10.0,im:0.0};
];
assert_matrix_eq!(sparse_mat, expected);
}
#[test]
#[rustfmt::skip]
fn test_matrixmarket_load_dense_int_skew() {
let file_str = r#"
%%MatrixMarket matrix array integer skew-symmetric
%
4 4
1
2
3
4
5
6
"#;
let sparse_mat = load_coo_from_matrix_market_str::<i32>(file_str).unwrap();
let expected = matrix![
0,-1,-2,-3;
1, 0,-4,-5;
2, 4, 0,-6;
3, 5, 6, 0;
];
assert_matrix_eq!(sparse_mat, expected);
}
#[test]
#[rustfmt::skip]
fn test_matrixmarket_load_dense_complex_general() {
let file_str = r#"
%%MatrixMarket matrix array complex general
%
2 2
1 0
1 0
1 0
1 0
"#;
let sparse_mat = load_coo_from_matrix_market_str::<C32>(file_str).unwrap();
let expected = matrix![
C32{re:1.0,im:0.0},C32{re:1.0,im:0.0};
C32{re:1.0,im:0.0},C32{re:1.0,im:0.0};
];
assert_matrix_eq!(sparse_mat, expected);
}
#[test]
#[rustfmt::skip]
fn test_matrixmarket_write_real(){
let dense_matrix = matrix![
1.0, 2.0, 3.0;
2.0, 0.0, 3.0;
];
let row_indices = vec![0,1,0,0,1];
let col_indices = vec![0,0,1,2,2];
let values = vec![1.0,2.0,2.0,3.0,3.0];
let coo_matrix = CooMatrix::try_from_triplets(2, 3, row_indices, col_indices, values).unwrap();
assert_matrix_eq!(dense_matrix,coo_matrix);
let expected = r#"%%matrixmarket matrix coordinate real general
% matrixmarket file generated by nalgebra-sparse.
2 3 5
1 1 1
2 1 2
1 2 2
1 3 3
2 3 3
"#;
let matrixmarket_str = save_to_matrix_market_str(&coo_matrix);
assert_eq!(matrixmarket_str,expected);
}
#[test]
fn test_matrixmarket_write_int() {
let dense_matrix = matrix![
1,2,3;
2,0,3;
];
let row_indices = vec![0, 1, 0, 0, 1];
let col_indices = vec![0, 0, 1, 2, 2];
let values = vec![1, 2, 2, 3, 3];
let coo_matrix = CooMatrix::try_from_triplets(2, 3, row_indices, col_indices, values).unwrap();
assert_matrix_eq!(dense_matrix, coo_matrix);
let expected = r#"%%matrixmarket matrix coordinate integer general
% matrixmarket file generated by nalgebra-sparse.
2 3 5
1 1 1
2 1 2
1 2 2
1 3 3
2 3 3
"#;
let matrixmarket_str = save_to_matrix_market_str(&coo_matrix);
assert_eq!(matrixmarket_str, expected);
}
#[test]
fn test_matrixmarket_write_pattern() {
let row_indices = vec![0, 1, 0, 0, 1];
let col_indices = vec![0, 0, 1, 2, 2];
let values = vec![(), (), (), (), ()];
let coo_matrix = CooMatrix::try_from_triplets(2, 3, row_indices, col_indices, values).unwrap();
let expected = r#"%%matrixmarket matrix coordinate pattern general
% matrixmarket file generated by nalgebra-sparse.
2 3 5
1 1
2 1
1 2
1 3
2 3
"#;
let matrixmarket_str = save_to_matrix_market_str(&coo_matrix);
assert_eq!(matrixmarket_str, expected);
}
#[test]
fn test_matrixmarket_write_complex() {
let row_indices = vec![0, 1, 0, 0, 1];
let col_indices = vec![0, 0, 1, 2, 2];
let values = vec![
C64 { re: 1.0, im: 2.0 },
C64 { re: 2.0, im: 3.0 },
C64 { re: 3.0, im: 4.0 },
C64 { re: 4.0, im: 5.0 },
C64 { re: 5.0, im: 6.0 },
];
let coo_matrix = CooMatrix::try_from_triplets(2, 3, row_indices, col_indices, values).unwrap();
let expected = r#"%%matrixmarket matrix coordinate complex general
% matrixmarket file generated by nalgebra-sparse.
2 3 5
1 1 1 2
2 1 2 3
1 2 3 4
1 3 4 5
2 3 5 6
"#;
let matrixmarket_str = save_to_matrix_market_str(&coo_matrix);
assert_eq!(matrixmarket_str, expected);
}
proptest! {
#[test]
fn coo_matrix_market_roundtrip_str(coo in coo_no_duplicates(-10 ..= 10, 0 ..= 10, 0..= 10, 100)) {
let generated_matrixmarket_string = save_to_matrix_market_str(&coo);
let generated_matrix = load_coo_from_matrix_market_str(&generated_matrixmarket_string).unwrap();
assert_matrix_eq!(generated_matrix, coo);
}
}
proptest! {
#[test]
fn coo_matrix_market_roundtrip_file(coo in coo_no_duplicates(-10 ..= 10, 0 ..= 10, 0..= 10, 100)) {
let temp_dir = tempdir().expect("Unable to create temporary directory");
let file_path = temp_dir.path().join("temp.mtx");
save_to_matrix_market_file(&coo,&file_path).unwrap();
let generated_matrix = load_coo_from_matrix_market_file(file_path).unwrap();
assert_matrix_eq!(generated_matrix, coo);
temp_dir.close().expect("Unable to delete temporary directory");
}
}