use matrixcompare::assert_matrix_eq;
use nalgebra::dmatrix;
use nalgebra::Complex;
use nalgebra_sparse::io::load_coo_from_matrix_market_str;
use nalgebra_sparse::CooMatrix;

#[test]
#[rustfmt::skip]
fn test_matrixmarket_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 = dmatrix![
        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_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 = dmatrix![
         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_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 = dmatrix![
        Complex::<f64>{re:1.0,im:0.0}, Complex::<f64>{re:0.0,im:0.0}, Complex::<f64>{re:0.0,im:0.0}, Complex::<f64>{re:0.0,im:0.0},Complex::<f64>{re:0.0,im:0.0};
        Complex::<f64>{re:0.0,im:0.0}, Complex::<f64>{re:10.5,im:0.0}, Complex::<f64>{re:0.0,im:0.0}, Complex::<f64>{re:250.5,im:-22.22},Complex::<f64>{re:0.0,im:0.0};
        Complex::<f64>{re:0.0,im:0.0}, Complex::<f64>{re:0.0,im:0.0}, Complex::<f64>{re:0.015,im:0.0}, Complex::<f64>{re:0.0,im:0.0},Complex::<f64>{re:0.0,im:0.0};
        Complex::<f64>{re:0.0,im:0.0}, Complex::<f64>{re:250.5,im:22.22}, Complex::<f64>{re:0.0,im:0.0}, Complex::<f64>{re:-280.0,im:0.0},Complex::<f64>{re:0.0,im:-33.32};
        Complex::<f64>{re:0.0,im:0.0}, Complex::<f64>{re:0.0,im:0.0}, Complex::<f64>{re:0.0,im:0.0}, Complex::<f64>{re:0.0,im:33.32},Complex::<f64>{re:12.0,im:0.0};
    ];
    assert_matrix_eq!(sparse_mat, expected);
}

#[test]
#[rustfmt::skip]
fn test_matrixmarket_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 = dmatrix![
      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_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.disassemble();
    let values = vec![1; val.len()];
    let sparse_mat = CooMatrix::try_from_triplets(nrows, ncols, row_idx, col_idx, values).unwrap();
    let expected = dmatrix![
        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_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 = dmatrix![
        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_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 = dmatrix![
        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_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::<Complex<f64>>(file_str).unwrap();
    let expected = dmatrix![
        Complex::<f64>{re:1.0,im:0.0}, Complex::<f64>{re:2.0,im:-2.0} ,Complex::<f64>{re:3.0,im:-3.0} ,Complex::<f64>{re:4.0,im:-4.0};
        Complex::<f64>{re:2.0,im:2.0}, Complex::<f64>{re:5.0,im:0.0} ,Complex::<f64>{re:6.0,im:-6.0} ,Complex::<f64>{re:7.0,im:-7.0};
        Complex::<f64>{re:3.0,im:3.0}, Complex::<f64>{re:6.0,im:6.0} ,Complex::<f64>{re:8.0,im:0.0} ,Complex::<f64>{re:9.0,im:-9.0};
        Complex::<f64>{re:4.0,im:4.0}, Complex::<f64>{re:7.0,im:7.0} ,Complex::<f64>{re:9.0,im:9.0} ,Complex::<f64>{re:10.0,im:0.0};
    ];
    assert_matrix_eq!(sparse_mat, expected);
}

#[test]
#[rustfmt::skip]
fn test_matrixmarket_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 = dmatrix![
        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_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::<Complex<f32>>(file_str).unwrap();
    let expected = dmatrix![
        Complex::<f32>{re:1.0,im:0.0},Complex::<f32>{re:1.0,im:0.0};
        Complex::<f32>{re:1.0,im:0.0},Complex::<f32>{re:1.0,im:0.0};
    ];
    assert_matrix_eq!(sparse_mat, expected);
}