hyperplonk/arithmetic/src/multilinear_polynomial.rs
arithmetic/src/multilinear_polynomial.rsRaw
1use crate::{util::get_batched_nv, ArithErrors};
2use ark_ff::{Field, PrimeField};
3use ark_poly::MultilinearExtension;
4use ark_std::{end_timer, rand::RngCore, start_timer};
5#[cfg(feature = "parallel")]
6use rayon::prelude::{IndexedParallelIterator, IntoParallelRefMutIterator, ParallelIterator};
7use std::rc::Rc;
8
9pub use ark_poly::DenseMultilinearExtension;
10
11/// Sample a random list of multilinear polynomials.
12/// Returns
13/// - the list of polynomials,
14/// - its sum of polynomial evaluations over the boolean hypercube.
15pub fn random_mle_list<F: PrimeField, R: RngCore>(
16 nv: usize,
17 degree: usize,
18 rng: &mut R,
19) -> (Vec<Rc<DenseMultilinearExtension<F>>>, F) {
20 let start = start_timer!(|| "sample random mle list");
21 let mut multiplicands = Vec::with_capacity(degree);
22 for _ in 0..degree {
23 multiplicands.push(Vec::with_capacity(1 << nv))
24 }
25 let mut sum = F::zero();
26
27 for _ in 0..(1 << nv) {
28 let mut product = F::one();
29
30 for e in multiplicands.iter_mut() {
31 let val = F::rand(rng);
32 e.push(val);
33 product *= val;
34 }
35 sum += product;
36 }
37
38 let list = multiplicands
39 .into_iter()
40 .map(|x| Rc::new(DenseMultilinearExtension::from_evaluations_vec(nv, x)))
41 .collect();
42
43 end_timer!(start);
44 (list, sum)
45}
46
47// Build a randomize list of mle-s whose sum is zero.
48pub fn random_zero_mle_list<F: PrimeField, R: RngCore>(
49 nv: usize,
50 degree: usize,
51 rng: &mut R,
52) -> Vec<Rc<DenseMultilinearExtension<F>>> {
53 let start = start_timer!(|| "sample random zero mle list");
54
55 let mut multiplicands = Vec::with_capacity(degree);
56 for _ in 0..degree {
57 multiplicands.push(Vec::with_capacity(1 << nv))
58 }
59 for _ in 0..(1 << nv) {
60 multiplicands[0].push(F::zero());
61 for e in multiplicands.iter_mut().skip(1) {
62 e.push(F::rand(rng));
63 }
64 }
65
66 let list = multiplicands
67 .into_iter()
68 .map(|x| Rc::new(DenseMultilinearExtension::from_evaluations_vec(nv, x)))
69 .collect();
70
71 end_timer!(start);
72 list
73}
74
75/// An MLE that represent an identity permutation: `f(index) \mapto index`
76pub fn identity_permutation_mle<F: PrimeField>(
77 num_vars: usize,
78) -> Rc<DenseMultilinearExtension<F>> {
79 let s_id_vec = (0..1u64 << num_vars).map(F::from).collect();
80 Rc::new(DenseMultilinearExtension::from_evaluations_vec(
81 num_vars, s_id_vec,
82 ))
83}
84
85/// An MLE that represent a random permutation
86pub fn random_permutation_mle<F: PrimeField, R: RngCore>(
87 num_vars: usize,
88 rng: &mut R,
89) -> Rc<DenseMultilinearExtension<F>> {
90 let len = 1u64 << num_vars;
91 let mut s_id_vec: Vec<F> = (0..len).map(F::from).collect();
92 let mut s_perm_vec = vec![];
93 for _ in 0..len {
94 let index = rng.next_u64() as usize % s_id_vec.len();
95 s_perm_vec.push(s_id_vec.remove(index));
96 }
97 Rc::new(DenseMultilinearExtension::from_evaluations_vec(
98 num_vars, s_perm_vec,
99 ))
100}
101
102pub fn evaluate_opt<F: Field>(poly: &DenseMultilinearExtension<F>, point: &[F]) -> F {
103 assert_eq!(poly.num_vars, point.len());
104 fix_variables(poly, point).evaluations[0]
105}
106
107pub fn fix_variables<F: Field>(
108 poly: &DenseMultilinearExtension<F>,
109 partial_point: &[F],
110) -> DenseMultilinearExtension<F> {
111 assert!(
112 partial_point.len() <= poly.num_vars,
113 "invalid size of partial point"
114 );
115 let nv = poly.num_vars;
116 let mut poly = poly.evaluations.to_vec();
117 let dim = partial_point.len();
118 // evaluate single variable of partial point from left to right
119 for (i, point) in partial_point.iter().enumerate().take(dim) {
120 poly = fix_one_variable_helper(&poly, nv - i, point);
121 }
122
123 DenseMultilinearExtension::<F>::from_evaluations_slice(nv - dim, &poly[..(1 << (nv - dim))])
124}
125
126fn fix_one_variable_helper<F: Field>(data: &[F], nv: usize, point: &F) -> Vec<F> {
127 let mut res = vec![F::zero(); 1 << (nv - 1)];
128
129 // evaluate single variable of partial point from left to right
130 #[cfg(not(feature = "parallel"))]
131 for i in 0..(1 << (nv - 1)) {
132 res[i] = data[i] + (data[(i << 1) + 1] - data[i << 1]) * point;
133 }
134
135 #[cfg(feature = "parallel")]
136 if nv >= 13 {
137 // on my computer we parallelization doesn't help till nv >= 13
138 res.par_iter_mut().enumerate().for_each(|(i, x)| {
139 *x = data[i << 1] + (data[(i << 1) + 1] - data[i << 1]) * point;
140 });
141 } else {
142 for i in 0..(1 << (nv - 1)) {
143 res[i] = data[i << 1] + (data[(i << 1) + 1] - data[i << 1]) * point;
144 }
145 }
146
147 res
148}
149
150pub fn evaluate_no_par<F: Field>(poly: &DenseMultilinearExtension<F>, point: &[F]) -> F {
151 assert_eq!(poly.num_vars, point.len());
152 fix_variables_no_par(poly, point).evaluations[0]
153}
154
155fn fix_variables_no_par<F: Field>(
156 poly: &DenseMultilinearExtension<F>,
157 partial_point: &[F],
158) -> DenseMultilinearExtension<F> {
159 assert!(
160 partial_point.len() <= poly.num_vars,
161 "invalid size of partial point"
162 );
163 let nv = poly.num_vars;
164 let mut poly = poly.evaluations.to_vec();
165 let dim = partial_point.len();
166 // evaluate single variable of partial point from left to right
167 for i in 1..dim + 1 {
168 let r = partial_point[i - 1];
169 for b in 0..(1 << (nv - i)) {
170 poly[b] = poly[b << 1] + (poly[(b << 1) + 1] - poly[b << 1]) * r;
171 }
172 }
173 DenseMultilinearExtension::from_evaluations_slice(nv - dim, &poly[..(1 << (nv - dim))])
174}
175
176/// merge a set of polynomials. Returns an error if the
177/// polynomials do not share a same number of nvs.
178pub fn merge_polynomials<F: PrimeField>(
179 polynomials: &[Rc<DenseMultilinearExtension<F>>],
180) -> Result<Rc<DenseMultilinearExtension<F>>, ArithErrors> {
181 let nv = polynomials[0].num_vars();
182 for poly in polynomials.iter() {
183 if nv != poly.num_vars() {
184 return Err(ArithErrors::InvalidParameters(
185 "num_vars do not match for polynomials".to_string(),
186 ));
187 }
188 }
189
190 let merged_nv = get_batched_nv(nv, polynomials.len());
191 let mut scalars = vec![];
192 for poly in polynomials.iter() {
193 scalars.extend_from_slice(poly.to_evaluations().as_slice());
194 }
195 scalars.extend_from_slice(vec![F::zero(); (1 << merged_nv) - scalars.len()].as_ref());
196 Ok(Rc::new(DenseMultilinearExtension::from_evaluations_vec(
197 merged_nv, scalars,
198 )))
199}
200
201pub fn fix_last_variables_no_par<F: PrimeField>(
202 poly: &DenseMultilinearExtension<F>,
203 partial_point: &[F],
204) -> DenseMultilinearExtension<F> {
205 let mut res = fix_last_variable_no_par(poly, partial_point.last().unwrap());
206 for p in partial_point.iter().rev().skip(1) {
207 res = fix_last_variable_no_par(&res, p);
208 }
209 res
210}
211
212fn fix_last_variable_no_par<F: PrimeField>(
213 poly: &DenseMultilinearExtension<F>,
214 partial_point: &F,
215) -> DenseMultilinearExtension<F> {
216 let nv = poly.num_vars();
217 let half_len = 1 << (nv - 1);
218 let mut res = vec![F::zero(); half_len];
219 for (i, e) in res.iter_mut().enumerate().take(half_len) {
220 *e = poly.evaluations[i]
221 + *partial_point * (poly.evaluations[i + half_len] - poly.evaluations[i]);
222 }
223 DenseMultilinearExtension::from_evaluations_vec(nv - 1, res)
224}
225pub fn fix_last_variables<F: PrimeField>(
226 poly: &DenseMultilinearExtension<F>,
227 partial_point: &[F],
228) -> DenseMultilinearExtension<F> {
229 assert!(
230 partial_point.len() <= poly.num_vars,
231 "invalid size of partial point"
232 );
233 let nv = poly.num_vars;
234 let mut poly = poly.evaluations.to_vec();
235 let dim = partial_point.len();
236 // evaluate single variable of partial point from left to right
237 for (i, point) in partial_point.iter().rev().enumerate().take(dim) {
238 poly = fix_last_variable_helper(&poly, nv - i, point);
239 }
240
241 DenseMultilinearExtension::<F>::from_evaluations_slice(nv - dim, &poly[..(1 << (nv - dim))])
242}
243
244fn fix_last_variable_helper<F: Field>(data: &[F], nv: usize, point: &F) -> Vec<F> {
245 let half_len = 1 << (nv - 1);
246 let mut res = vec![F::zero(); half_len];
247
248 // evaluate single variable of partial point from left to right
249 #[cfg(not(feature = "parallel"))]
250 for b in 0..half_len {
251 res[b] = data[b] + (data[b + half_len] - data[b]) * point;
252 }
253
254 #[cfg(feature = "parallel")]
255 if nv >= 13 {
256 // on my computer we parallelization doesn't help till nv >= 13
257 res.par_iter_mut().enumerate().for_each(|(i, x)| {
258 *x = data[i] + (data[i + half_len] - data[i]) * point;
259 });
260 } else {
261 for b in 0..(1 << (nv - 1)) {
262 res[b] = data[b] + (data[b + half_len] - data[b]) * point;
263 }
264 }
265
266 res
267}