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Merge pull request #3591 from asn-d6/peerdas_refactor_recovery_polynomial
peerDAS: Initial refactor of recover_polynomial()
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2faa44b6b6
@ -42,6 +42,9 @@
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- [`verify_cell_proof`](#verify_cell_proof)
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- [`verify_cell_proof_batch`](#verify_cell_proof_batch)
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- [Reconstruction](#reconstruction)
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- [`construct_vanishing_polynomial`](#construct_vanishing_polynomial)
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- [`recover_shifted_data`](#recover_shifted_data)
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- [`recover_original_data`](#recover_original_data)
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- [`recover_polynomial`](#recover_polynomial)
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<!-- END doctoc generated TOC please keep comment here to allow auto update -->
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@ -76,9 +79,10 @@ Cells are the smallest unit of blob data that can come with their own KZG proofs
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| Name | Value | Description |
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| - | - | - |
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| `FIELD_ELEMENTS_PER_EXT_BLOB` | `2 * FIELD_ELEMENTS_PER_BLOB` | Number of field elements in a Reed-Solomon extended blob |
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| `FIELD_ELEMENTS_PER_CELL` | `uint64(64)` | Number of field elements in a cell |
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| `BYTES_PER_CELL` | `FIELD_ELEMENTS_PER_CELL * BYTES_PER_FIELD_ELEMENT` | The number of bytes in a cell |
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| `CELLS_PER_BLOB` | `((2 * FIELD_ELEMENTS_PER_BLOB) // FIELD_ELEMENTS_PER_CELL)` | The number of cells in a blob |
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| `CELLS_PER_BLOB` | `FIELD_ELEMENTS_PER_EXT_BLOB // FIELD_ELEMENTS_PER_CELL` | The number of cells in a blob |
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| `RANDOM_CHALLENGE_KZG_CELL_BATCH_DOMAIN` | `b'RCKZGCBATCH__V1_'` |
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## Helper functions
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@ -352,7 +356,7 @@ def coset_for_cell(cell_id: CellID) -> Cell:
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"""
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assert cell_id < CELLS_PER_BLOB
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roots_of_unity_brp = bit_reversal_permutation(
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compute_roots_of_unity(2 * FIELD_ELEMENTS_PER_BLOB)
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compute_roots_of_unity(FIELD_ELEMENTS_PER_EXT_BLOB)
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)
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return Cell(roots_of_unity_brp[FIELD_ELEMENTS_PER_CELL * cell_id:FIELD_ELEMENTS_PER_CELL * (cell_id + 1)])
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```
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@ -402,7 +406,7 @@ def compute_cells(blob: Blob) -> Vector[Cell, CELLS_PER_BLOB]:
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polynomial_coeff = polynomial_eval_to_coeff(polynomial)
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extended_data = fft_field(polynomial_coeff + [0] * FIELD_ELEMENTS_PER_BLOB,
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compute_roots_of_unity(2 * FIELD_ELEMENTS_PER_BLOB))
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compute_roots_of_unity(FIELD_ELEMENTS_PER_EXT_BLOB))
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extended_data_rbo = bit_reversal_permutation(extended_data)
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return [extended_data_rbo[i * FIELD_ELEMENTS_PER_CELL:(i + 1) * FIELD_ELEMENTS_PER_CELL]
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for i in range(CELLS_PER_BLOB)]
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@ -471,73 +475,99 @@ def verify_cell_proof_batch(row_commitments_bytes: Sequence[Bytes48],
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## Reconstruction
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### `recover_polynomial`
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### `construct_vanishing_polynomial`
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```python
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def recover_polynomial(cell_ids: Sequence[CellID],
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cells_bytes: Sequence[Vector[Bytes32, FIELD_ELEMENTS_PER_CELL]]) -> Polynomial:
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def construct_vanishing_polynomial(missing_cell_ids: Sequence[CellID]) -> Tuple[
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Sequence[BLSFieldElement],
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Sequence[BLSFieldElement]]:
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"""
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Recovers a polynomial from 2 * FIELD_ELEMENTS_PER_CELL evaluations, half of which can be missing.
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This algorithm uses FFTs to recover cells faster than using Lagrange implementation. However,
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a faster version thanks to Qi Zhou can be found here:
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https://github.com/ethereum/research/blob/51b530a53bd4147d123ab3e390a9d08605c2cdb8/polynomial_reconstruction/polynomial_reconstruction_danksharding.py
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Public method.
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Given the cells that are missing from the data, compute the polynomial that vanishes at every point that
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corresponds to a missing field element.
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"""
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assert len(cell_ids) == len(cells_bytes)
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cells = [bytes_to_cell(cell_bytes) for cell_bytes in cells_bytes]
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assert len(cells) >= CELLS_PER_BLOB // 2
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missing_cell_ids = [cell_id for cell_id in range(CELLS_PER_BLOB) if cell_id not in cell_ids]
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# Get the small domain
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roots_of_unity_reduced = compute_roots_of_unity(CELLS_PER_BLOB)
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# Compute polynomial that vanishes at all the missing cells (over the small domain)
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short_zero_poly = vanishing_polynomialcoeff([
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roots_of_unity_reduced[reverse_bits(cell_id, CELLS_PER_BLOB)]
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for cell_id in missing_cell_ids
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roots_of_unity_reduced[reverse_bits(missing_cell_id, CELLS_PER_BLOB)]
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for missing_cell_id in missing_cell_ids
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])
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full_zero_poly = []
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for i in short_zero_poly:
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full_zero_poly.append(i)
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full_zero_poly.extend([0] * (FIELD_ELEMENTS_PER_CELL - 1))
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full_zero_poly = full_zero_poly + [0] * (2 * FIELD_ELEMENTS_PER_BLOB - len(full_zero_poly))
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# Extend vanishing polynomial to full domain using the closed form of the vanishing polynomial over a coset
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zero_poly_coeff = [0] * FIELD_ELEMENTS_PER_EXT_BLOB
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for i, coeff in enumerate(short_zero_poly):
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zero_poly_coeff[i * FIELD_ELEMENTS_PER_CELL] = coeff
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zero_poly_eval = fft_field(full_zero_poly,
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compute_roots_of_unity(2 * FIELD_ELEMENTS_PER_BLOB))
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# Compute evaluations of the extended vanishing polynomial
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zero_poly_eval = fft_field(zero_poly_coeff,
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compute_roots_of_unity(FIELD_ELEMENTS_PER_EXT_BLOB))
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zero_poly_eval_brp = bit_reversal_permutation(zero_poly_eval)
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for cell_id in missing_cell_ids:
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start = cell_id * FIELD_ELEMENTS_PER_CELL
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end = (cell_id + 1) * FIELD_ELEMENTS_PER_CELL
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assert zero_poly_eval_brp[start:end] == [0] * FIELD_ELEMENTS_PER_CELL
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for cell_id in cell_ids:
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start = cell_id * FIELD_ELEMENTS_PER_CELL
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end = (cell_id + 1) * FIELD_ELEMENTS_PER_CELL
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assert all(a != 0 for a in zero_poly_eval_brp[start:end])
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extended_evaluation_rbo = [0] * (FIELD_ELEMENTS_PER_BLOB * 2)
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# Sanity check
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for cell_id in range(CELLS_PER_BLOB):
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start = cell_id * FIELD_ELEMENTS_PER_CELL
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end = (cell_id + 1) * FIELD_ELEMENTS_PER_CELL
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if cell_id in missing_cell_ids:
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assert all(a == 0 for a in zero_poly_eval_brp[start:end])
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else: # cell_id in cell_ids
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assert all(a != 0 for a in zero_poly_eval_brp[start:end])
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return zero_poly_coeff, zero_poly_eval, zero_poly_eval_brp
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```
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### `recover_shifted_data`
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```python
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def recover_shifted_data(cell_ids: Sequence[CellID],
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cells: Sequence[Cell],
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zero_poly_eval: Sequence[BLSFieldElement],
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zero_poly_coeff: Sequence[BLSFieldElement],
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roots_of_unity_extended: Sequence[BLSFieldElement]) -> Tuple[
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Sequence[BLSFieldElement],
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Sequence[BLSFieldElement],
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BLSFieldElement]:
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"""
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Given Z(x), return polynomial Q_1(x)=(E*Z)(k*x) and Q_2(x)=Z(k*x) and k^{-1}.
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"""
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shift_factor = BLSFieldElement(PRIMITIVE_ROOT_OF_UNITY)
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shift_inv = div(BLSFieldElement(1), shift_factor)
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extended_evaluation_rbo = [0] * FIELD_ELEMENTS_PER_EXT_BLOB
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for cell_id, cell in zip(cell_ids, cells):
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start = cell_id * FIELD_ELEMENTS_PER_CELL
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end = (cell_id + 1) * FIELD_ELEMENTS_PER_CELL
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extended_evaluation_rbo[start:end] = cell
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extended_evaluation = bit_reversal_permutation(extended_evaluation_rbo)
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# Compute (E*Z)(x)
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extended_evaluation_times_zero = [BLSFieldElement(int(a) * int(b) % BLS_MODULUS)
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for a, b in zip(zero_poly_eval, extended_evaluation)]
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roots_of_unity_extended = compute_roots_of_unity(2 * FIELD_ELEMENTS_PER_BLOB)
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extended_evaluations_fft = fft_field(extended_evaluation_times_zero, roots_of_unity_extended, inv=True)
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shift_factor = BLSFieldElement(PRIMITIVE_ROOT_OF_UNITY)
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shift_inv = div(BLSFieldElement(1), shift_factor)
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# Compute (E*Z)(k*x)
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shifted_extended_evaluation = shift_polynomialcoeff(extended_evaluations_fft, shift_factor)
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shifted_zero_poly = shift_polynomialcoeff(full_zero_poly, shift_factor)
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# Compute Z(k*x)
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shifted_zero_poly = shift_polynomialcoeff(zero_poly_coeff, shift_factor)
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eval_shifted_extended_evaluation = fft_field(shifted_extended_evaluation, roots_of_unity_extended)
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eval_shifted_zero_poly = fft_field(shifted_zero_poly, roots_of_unity_extended)
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return eval_shifted_extended_evaluation, eval_shifted_zero_poly, shift_inv
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```
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### `recover_original_data`
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```python
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def recover_original_data(eval_shifted_extended_evaluation: Sequence[BLSFieldElement],
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eval_shifted_zero_poly: Sequence[BLSFieldElement],
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shift_inv: BLSFieldElement,
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roots_of_unity_extended: Sequence[BLSFieldElement]) -> Sequence[BLSFieldElement]:
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"""
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Given Q_1, Q_2 and k^{-1}, compute P(x).
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"""
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# Compute Q_3 = Q_1(x)/Q_2(x) = P(k*x)
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eval_shifted_reconstructed_poly = [
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div(a, b)
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for a, b in zip(eval_shifted_extended_evaluation, eval_shifted_zero_poly)
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@ -545,10 +575,59 @@ def recover_polynomial(cell_ids: Sequence[CellID],
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shifted_reconstructed_poly = fft_field(eval_shifted_reconstructed_poly, roots_of_unity_extended, inv=True)
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# Unshift P(k*x) by k^{-1} to get P(x)
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reconstructed_poly = shift_polynomialcoeff(shifted_reconstructed_poly, shift_inv)
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reconstructed_data = bit_reversal_permutation(fft_field(reconstructed_poly, roots_of_unity_extended))
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return reconstructed_data
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```
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### `recover_polynomial`
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```python
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def recover_polynomial(cell_ids: Sequence[CellID],
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cells_bytes: Sequence[Vector[Bytes32, FIELD_ELEMENTS_PER_CELL]]) -> Polynomial:
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"""
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Recover original polynomial from FIELD_ELEMENTS_PER_EXT_BLOB evaluations, half of which can be missing. This
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algorithm uses FFTs to recover cells faster than using Lagrange implementation, as can be seen here:
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https://ethresear.ch/t/reed-solomon-erasure-code-recovery-in-n-log-2-n-time-with-ffts/3039
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A faster version thanks to Qi Zhou can be found here:
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https://github.com/ethereum/research/blob/51b530a53bd4147d123ab3e390a9d08605c2cdb8/polynomial_reconstruction/polynomial_reconstruction_danksharding.py
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Public method.
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"""
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assert len(cell_ids) == len(cells_bytes)
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# Check we have enough cells to be able to perform the reconstruction
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assert CELLS_PER_BLOB / 2 <= len(cell_ids) <= CELLS_PER_BLOB
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# Check for duplicates
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assert len(cell_ids) == len(set(cell_ids))
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# Get the extended domain
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roots_of_unity_extended = compute_roots_of_unity(FIELD_ELEMENTS_PER_EXT_BLOB)
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# Convert from bytes to cells
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cells = [bytes_to_cell(cell_bytes) for cell_bytes in cells_bytes]
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missing_cell_ids = [cell_id for cell_id in range(CELLS_PER_BLOB) if cell_id not in cell_ids]
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zero_poly_coeff, zero_poly_eval, zero_poly_eval_brp = construct_vanishing_polynomial(missing_cell_ids)
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eval_shifted_extended_evaluation, eval_shifted_zero_poly, shift_inv = recover_shifted_data(
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cell_ids,
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cells,
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zero_poly_eval,
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zero_poly_coeff,
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roots_of_unity_extended,
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)
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reconstructed_data = recover_original_data(
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eval_shifted_extended_evaluation,
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eval_shifted_zero_poly,
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shift_inv,
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roots_of_unity_extended,
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)
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for cell_id, cell in zip(cell_ids, cells):
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start = cell_id * FIELD_ELEMENTS_PER_CELL
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end = (cell_id + 1) * FIELD_ELEMENTS_PER_CELL
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