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, write_to_matrix_market_file, write_to_matrix_market_str, }; use nalgebra_sparse::proptest::coo_no_duplicates; use nalgebra_sparse::CooMatrix; use proptest::prelude::*; type C64 = Complex; type C32 = Complex; #[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 = 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::(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 = 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::(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::(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::(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::>(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::(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::(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::(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::(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::(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::(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 = write_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 = write_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 = write_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 = write_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 = write_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 mut tempdir = std::env::temp_dir(); tempdir.push("temp.mtx"); write_to_matrix_market_file(&coo,&tempdir).unwrap(); let generated_matrix = load_coo_from_matrix_market_file(tempdir).unwrap(); assert_matrix_eq!(generated_matrix, coo); } }