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use crate::{build_mle, errors::HyperPlonkErrors};
use ark_ff::PrimeField;
use ark_poly::DenseMultilinearExtension;
use ark_std::log2;
use std::rc::Rc;
/// A row of witnesses of width `#wires`
#[derive(Debug, Clone)]
pub struct WitnessRow<F: PrimeField>(pub(crate) Vec<F>);
/// A column of witnesses of length `#constraints`
#[derive(Debug, Clone, Default)]
pub struct WitnessColumn<F: PrimeField>(pub(crate) Vec<F>);
impl<F: PrimeField> WitnessColumn<F> {
/// the number of variables of the multilinear polynomial that presents a
/// column.
pub fn get_nv(&self) -> usize {
log2(self.0.len()) as usize
}
/// Append a new element to the witness column
pub fn append(&mut self, new_element: F) {
self.0.push(new_element)
}
/// Build witness columns from rows
pub fn from_witness_rows(
witness_rows: &[WitnessRow<F>],
) -> Result<Vec<Self>, HyperPlonkErrors> {
if witness_rows.is_empty() {
return Err(HyperPlonkErrors::InvalidParameters(
"empty witness rows".to_string(),
));
}
let mut res = Vec::with_capacity(witness_rows.len());
let num_columns = witness_rows[0].0.len();
for i in 0..num_columns {
let mut cur_column = Vec::new();
for row in witness_rows.iter() {
cur_column.push(row.0[i])
}
res.push(Self(cur_column))
}
Ok(res)
}
pub fn coeff_ref(&self) -> &[F] {
self.0.as_ref()
}
}
impl<F: PrimeField> From<&WitnessColumn<F>> for DenseMultilinearExtension<F> {
fn from(witness: &WitnessColumn<F>) -> Self {
let nv = witness.get_nv();
Self::from_evaluations_slice(nv, witness.0.as_ref())
}
}
impl<F: PrimeField> WitnessRow<F> {
/// Build MLE from matrix of witnesses.
///
/// Given a matrix := [row1, row2, ...] where
/// row1:= (a1, a2, ...)
/// row2:= (b1, b2, ...)
/// row3:= (c1, c2, ...)
///
/// output mle(a1,b1,c1, ...), mle(a2,b2,c2, ...), ...
pub fn build_mles(
matrix: &[Self],
) -> Result<Vec<Rc<DenseMultilinearExtension<F>>>, HyperPlonkErrors> {
build_mle!(matrix)
}
}