davidrusu dcdb419648
Cryptarchia/drop orphan proofs (#121)
* cryptarchia: introduce Hash class

* cryptarchia: Coin renamed to Note

* cryptarchia: simplify mock leader proof

* cryptarchia: remove orphan proofs from block headers

* cryptarchia: maintain a single commitment set in ledger state

* cryptarchia: drop note evolution

* cryptarchia: drop MOCK_LEADER_VRF

* cryptarchia fix nonce contribution derivation

* cryptarchia: mk_chain only returns list now

* fixup

* cryptarchia: shorten test cases using mk_chain
2025-03-21 20:49:04 +04:00

44 lines
1.5 KiB
Python

from unittest import TestCase
import numpy as np
from .cryptarchia import Leader, EpochState, LedgerState, Note, phi, Slot
from .test_common import mk_config
class TestLeader(TestCase):
def test_slot_leader_statistics(self):
epoch = EpochState(
stake_distribution_snapshot=LedgerState(block=None),
nonce_snapshot=LedgerState(block=None, nonce=b"1010101010"),
inferred_total_active_stake=1000,
)
note = Note(sk=0, value=10)
f = 0.05
l = Leader(
config=mk_config([note]).replace(active_slot_coeff=f),
note=note,
)
# We'll use the Margin of Error equation to decide how many samples we need.
# https://en.wikipedia.org/wiki/Margin_of_error
margin_of_error = 1e-4
p = phi(f=f, alpha=10 / epoch.total_active_stake())
std = np.sqrt(p * (1 - p))
Z = 3 # we want 3 std from the mean to be within the margin of error
N = int((Z * std / margin_of_error) ** 2)
# After N slots, the measured leader rate should be within the
# interval `p +- margin_of_error` with high probabiltiy
leader_rate = (
sum(
l.try_prove_slot_leader(epoch, Slot(slot), bytes(32)) is not None
for slot in range(N)
)
/ N
)
assert (
abs(leader_rate - p) < margin_of_error
), f"{leader_rate} != {p}, err={abs(leader_rate - p)} > {margin_of_error}"