1use ark_ff::PrimeField;
  2pub use ark_relations::r1cs::Matrix as R1CSMatrix;
  3use ark_std::cfg_iter;
  4use rayon::iter::{IndexedParallelIterator, IntoParallelRefIterator, ParallelIterator};
  5
  6use crate::Error;
  7
  8#[derive(Clone, Debug, Eq, PartialEq)]
  9pub struct SparseMatrix<F: PrimeField> {
 10    pub n_rows: usize,
 11    pub n_cols: usize,
 12    /// coeffs = R1CSMatrix = Vec<Vec<(F, usize)>>, which contains each row and the F is the value
 13    /// of the coefficient and the usize indicates the column position
 14    pub coeffs: R1CSMatrix<F>,
 15}
 16
 17impl<F: PrimeField> SparseMatrix<F> {
 18    pub fn to_dense(&self) -> Vec<Vec<F>> {
 19        let mut r: Vec<Vec<F>> = vec![vec![F::zero(); self.n_cols]; self.n_rows];
 20        for (row_i, row) in self.coeffs.iter().enumerate() {
 21            for &(value, col_i) in row.iter() {
 22                r[row_i][col_i] = value;
 23            }
 24        }
 25        r
 26    }
 27}
 28
 29pub fn dense_matrix_to_sparse<F: PrimeField>(m: Vec<Vec<F>>) -> SparseMatrix<F> {
 30    let mut r = SparseMatrix::<F> {
 31        n_rows: m.len(),
 32        n_cols: m[0].len(),
 33        coeffs: Vec::new(),
 34    };
 35    for m_row in m.iter() {
 36        let mut row: Vec<(F, usize)> = Vec::new();
 37        for (col_i, value) in m_row.iter().enumerate() {
 38            if !value.is_zero() {
 39                row.push((*value, col_i));
 40            }
 41        }
 42        r.coeffs.push(row);
 43    }
 44    r
 45}
 46
 47pub fn vec_add<F: PrimeField>(a: &[F], b: &[F]) -> Result<Vec<F>, Error> {
 48    if a.len() != b.len() {
 49        return Err(Error::NotSameLength(a.len(), b.len()));
 50    }
 51    Ok(a.iter().zip(b.iter()).map(|(x, y)| *x + y).collect())
 52}
 53
 54pub fn vec_sub<F: PrimeField>(a: &[F], b: &[F]) -> Result<Vec<F>, Error> {
 55    if a.len() != b.len() {
 56        return Err(Error::NotSameLength(a.len(), b.len()));
 57    }
 58    Ok(a.iter().zip(b.iter()).map(|(x, y)| *x - y).collect())
 59}
 60
 61pub fn vec_scalar_mul<F: PrimeField>(vec: &[F], c: &F) -> Vec<F> {
 62    vec.iter().map(|a| *a * c).collect()
 63}
 64
 65pub fn is_zero_vec<F: PrimeField>(vec: &[F]) -> bool {
 66    vec.iter().all(|a| a.is_zero())
 67}
 68
 69pub fn mat_vec_mul<F: PrimeField>(M: &Vec<Vec<F>>, z: &[F]) -> Result<Vec<F>, Error> {
 70    if M.is_empty() {
 71        return Err(Error::Empty);
 72    }
 73    if M[0].len() != z.len() {
 74        return Err(Error::NotSameLength(M[0].len(), z.len()));
 75    }
 76
 77    let mut r: Vec<F> = vec![F::zero(); M.len()];
 78    for (i, M_i) in M.iter().enumerate() {
 79        for (j, M_ij) in M_i.iter().enumerate() {
 80            r[i] += *M_ij * z[j];
 81        }
 82    }
 83    Ok(r)
 84}
 85
 86pub fn mat_vec_mul_sparse<F: PrimeField>(matrix: &SparseMatrix<F>, vector: &[F]) -> Vec<F> {
 87    let mut res = vec![F::zero(); matrix.n_rows];
 88    for (row_i, row) in matrix.coeffs.iter().enumerate() {
 89        for &(value, col_i) in row.iter() {
 90            res[row_i] += value * vector[col_i];
 91        }
 92    }
 93    res
 94}
 95
 96pub fn hadamard<F: PrimeField>(a: &[F], b: &[F]) -> Result<Vec<F>, Error> {
 97    if a.len() != b.len() {
 98        return Err(Error::NotSameLength(a.len(), b.len()));
 99    }
100    Ok(cfg_iter!(a).zip(b).map(|(a, b)| *a * b).collect())
101}
102
103#[cfg(test)]
104pub mod tests {
105    use super::*;
106    use ark_pallas::Fr;
107
108    pub fn to_F_matrix<F: PrimeField>(M: Vec<Vec<usize>>) -> SparseMatrix<F> {
109        dense_matrix_to_sparse(to_F_dense_matrix(M))
110    }
111    pub fn to_F_dense_matrix<F: PrimeField>(M: Vec<Vec<usize>>) -> Vec<Vec<F>> {
112        M.iter()
113            .map(|m| m.iter().map(|r| F::from(*r as u64)).collect())
114            .collect()
115    }
116    pub fn to_F_vec<F: PrimeField>(z: Vec<usize>) -> Vec<F> {
117        z.iter().map(|c| F::from(*c as u64)).collect()
118    }
119
120    #[test]
121    fn test_dense_sparse_conversions() {
122        let A = to_F_dense_matrix::<Fr>(vec![
123            vec![0, 1, 0, 0, 0, 0],
124            vec![0, 0, 0, 1, 0, 0],
125            vec![0, 1, 0, 0, 1, 0],
126            vec![5, 0, 0, 0, 0, 1],
127        ]);
128        let A_sparse = dense_matrix_to_sparse(A.clone());
129        assert_eq!(A_sparse.to_dense(), A);
130    }
131
132    // test mat_vec_mul & mat_vec_mul_sparse
133    #[test]
134    fn test_mat_vec_mul() {
135        let A = to_F_matrix::<Fr>(vec![
136            vec![0, 1, 0, 0, 0, 0],
137            vec![0, 0, 0, 1, 0, 0],
138            vec![0, 1, 0, 0, 1, 0],
139            vec![5, 0, 0, 0, 0, 1],
140        ])
141        .to_dense();
142        let z = to_F_vec(vec![1, 3, 35, 9, 27, 30]);
143        assert_eq!(mat_vec_mul(&A, &z).unwrap(), to_F_vec(vec![3, 9, 30, 35]));
144        assert_eq!(
145            mat_vec_mul_sparse(&dense_matrix_to_sparse(A), &z),
146            to_F_vec(vec![3, 9, 30, 35])
147        );
148
149        let A = to_F_matrix::<Fr>(vec![vec![2, 3, 4, 5], vec![4, 8, 12, 14], vec![9, 8, 7, 6]]);
150        let v = to_F_vec(vec![19, 55, 50, 3]);
151
152        assert_eq!(
153            mat_vec_mul(&A.to_dense(), &v).unwrap(),
154            to_F_vec(vec![418, 1158, 979])
155        );
156        assert_eq!(mat_vec_mul_sparse(&A, &v), to_F_vec(vec![418, 1158, 979]));
157    }
158
159    #[test]
160    fn test_hadamard_product() {
161        let a = to_F_vec::<Fr>(vec![1, 2, 3, 4, 5, 6]);
162        let b = to_F_vec(vec![7, 8, 9, 10, 11, 12]);
163        assert_eq!(
164            hadamard(&a, &b).unwrap(),
165            to_F_vec(vec![7, 16, 27, 40, 55, 72])
166        );
167    }
168
169    #[test]
170    fn test_vec_add() {
171        let a: Vec<Fr> = to_F_vec::<Fr>(vec![1, 2, 3, 4, 5, 6]);
172        let b: Vec<Fr> = to_F_vec(vec![7, 8, 9, 10, 11, 12]);
173        assert_eq!(
174            vec_add(&a, &b).unwrap(),
175            to_F_vec(vec![8, 10, 12, 14, 16, 18])
176        );
177    }
178}