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Add public method markers

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Dankrad Feist 2023-12-04 01:26:07 +00:00
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specs/deneb/polynomial-commitments-sampling.md
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@ -386,6 +386,8 @@ def compute_samples_and_proofs(blob: Blob) -> Tuple[
Compute all the sample proofs for one blob. This is an inefficient O(n^2) algorithm, Compute all the sample proofs for one blob. This is an inefficient O(n^2) algorithm,
for performant implementation the FK20 algorithm that runs in O(n log n) should be for performant implementation the FK20 algorithm that runs in O(n log n) should be
used instead. used instead.
Public method.
""" """
polynomial = blob_to_polynomial(blob) polynomial = blob_to_polynomial(blob)
polynomial_coeff = polynomial_eval_to_coeff(polynomial) polynomial_coeff = polynomial_eval_to_coeff(polynomial)
@ -406,6 +408,11 @@ def compute_samples_and_proofs(blob: Blob) -> Tuple[
```python ```python
def compute_samples(blob: Blob) -> Vector[Vector[BLSFieldElement, FIELD_ELEMENTS_PER_SAMPLE], SAMPLES_PER_BLOB]: def compute_samples(blob: Blob) -> Vector[Vector[BLSFieldElement, FIELD_ELEMENTS_PER_SAMPLE], SAMPLES_PER_BLOB]:
"""
Compute the sample data for a blob (without computing the proofs).
Public method.
"""
polynomial = blob_to_polynomial(blob) polynomial = blob_to_polynomial(blob)
polynomial_coeff = polynomial_eval_to_coeff(polynomial) polynomial_coeff = polynomial_eval_to_coeff(polynomial)
@ -422,10 +429,12 @@ def compute_samples(blob: Blob) -> Vector[Vector[BLSFieldElement, FIELD_ELEMENTS
```python ```python
def verify_sample_proof(commitment: KZGCommitment, def verify_sample_proof(commitment: KZGCommitment,
sample_id: int, sample_id: int,
data: Vector[BLSFieldElement], data: Vector[BLSFieldElement, FIELD_ELEMENTS_PER_SAMPLE],
proof: KZGProof) -> bool: proof: KZGProof) -> bool:
""" """
Check a sample proof Check a sample proof
Publiiic method.
""" """
coset = coset_for_sample(sample_id) coset = coset_for_sample(sample_id)
@ -444,6 +453,8 @@ def verify_sample_proof_batch(row_commitments: Sequence[KZGCommitment],
Check multiple sample proofs. This function implements the naive algorithm of checking every sample Check multiple sample proofs. This function implements the naive algorithm of checking every sample
individually; an efficient algorithm can be found here: individually; an efficient algorithm can be found here:
https://ethresear.ch/t/a-universal-verification-equation-for-data-availability-sampling/13240 https://ethresear.ch/t/a-universal-verification-equation-for-data-availability-sampling/13240
Public method.
""" """
# Get commitments via row IDs # Get commitments via row IDs
@ -465,6 +476,8 @@ def recover_samples_impl(samples: Sequence[Tuple[int, Sequence[BLSFieldElement]]
This algorithm uses FFTs to recover samples faster than using Lagrange implementation. However, This algorithm uses FFTs to recover samples faster than using Lagrange implementation. However,
a faster version thanks to Qi Zhou can be found here: a faster version thanks to Qi Zhou can be found here:
https://github.com/ethereum/research/blob/51b530a53bd4147d123ab3e390a9d08605c2cdb8/polynomial_reconstruction/polynomial_reconstruction_danksharding.py https://github.com/ethereum/research/blob/51b530a53bd4147d123ab3e390a9d08605c2cdb8/polynomial_reconstruction/polynomial_reconstruction_danksharding.py
Public method.
""" """
assert len(samples) >= SAMPLES_PER_BLOB // 2 assert len(samples) >= SAMPLES_PER_BLOB // 2
sample_ids = [sample_id for sample_id, _ in samples] sample_ids = [sample_id for sample_id, _ in samples]