Randomize the test_recover_polynomial()

specs/_features/peerdas/polynomial-commitments-sampling.md

@@ -486,7 +486,7 @@ def recover_polynomial(cell_ids: Sequence[CellID], cells: Sequence[Cell]) -> Pol
         extended_evaluation_rbo[start:end] = cell
     extended_evaluation = bit_reversal_permutation(extended_evaluation_rbo)
 
-    extended_evaluation_times_zero = [BLSFieldElement(a * b % BLS_MODULUS)
+    extended_evaluation_times_zero = [BLSFieldElement(int(a) * int(b) % BLS_MODULUS)
                                       for a, b in zip(zero_poly_eval, extended_evaluation)]
 
     extended_evaluations_fft = fft_field(extended_evaluation_times_zero, ROOTS_OF_UNITY_EXTENDED, inv=True)

tests/core/pyspec/eth2spec/test/peerdas/unittests/polynomial_commitments/test_polynomial_commitments.py

@@ -1,3 +1,4 @@
+import random
 from eth2spec.test.context import (
     spec_test,
     single_phase,
@@ -17,6 +18,7 @@ def test_fft(spec):
     result = spec.fft_field(vals, roots_of_unity)
     assert len(result) == len(vals)
     # TODO: add more assertions?
+    # One possible test would be to use polynomial_eval_to_coeff()
 
 
 @with_peerdas_and_later
@@ -53,11 +55,37 @@ def test_verify_cell_proof_batch(spec):
 @spec_test
 @single_phase
 def test_recover_polynomial(spec):
-    blob = get_sample_blob(spec)
+    rng = random.Random(5566)
-    original_polynomial = spec.blob_to_polynomial(blob)
-    cells = spec.compute_cells(blob)
-    cell_ids = list(range(spec.CELLS_PER_BLOB // 2))
-    known_cells = [cells[cell_id] for cell_id in cell_ids]
-    result = spec.recover_polynomial(cell_ids, known_cells)
 
-    assert original_polynomial == result[0:len(result) // 2]
+    # Number of samples we will be recovering from
+    N_SAMPLES = spec.CELLS_PER_BLOB // 2
+
+    # Get the data we will be working with
+    blob = get_sample_blob(spec)
+    # Get the data in evaluation form
+    original_polynomial = spec.blob_to_polynomial(blob)
+
+    # Extend data with Reed-Solomon and split the extended data in cells
+    cells = spec.compute_cells(blob)
+
+    # Compute the cells we will be recovering from
+    cell_ids = []
+    known_cells = []
+    # First figure out just the indices of the cells
+    for i in range(N_SAMPLES):
+        j = rng.randint(0, spec.CELLS_PER_BLOB)
+        while j in cell_ids:
+            j = rng.randint(0, spec.CELLS_PER_BLOB)
+        cell_ids.append(j)
+    # Now the cells themselves
+    known_cells = [cells[cell_id] for cell_id in cell_ids]
+
+    # Recover the data
+    recovered_data = spec.recover_polynomial(cell_ids, known_cells)
+
+    # Check that the original data match the non-extended portion of the recovered data
+    assert original_polynomial == recovered_data[:len(recovered_data) // 2]
+
+    # Now flatten the cells and check that they match the entirety of the recovered data
+    flattened_cells = [x for xs in cells for x in xs]
+    assert flattened_cells == recovered_data