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tests: update block_weight for 2021 scaling

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the test was still performed with consensus rules from before
that change
This commit is contained in:
moneromooo-monero 2022-08-08 06:03:10 +00:00
parent b6a029f222
commit e0b3507c88
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2 changed files with 14 additions and 8 deletions
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6
tests/block_weight/block_weight.cpp
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@ -141,7 +141,7 @@ static uint32_t lcg()
static void test(test_t t, uint64_t blocks)
{
PREFIX(10);
PREFIX(HF_VERSION_2021_SCALING);
for (uint64_t h = 0; h < LONG_TERM_BLOCK_WEIGHT_WINDOW; ++h)
{
@ -180,8 +180,8 @@ static void test(test_t t, uint64_t blocks)
}
uint64_t ltw = bc->get_next_long_term_block_weight(w);
cryptonote::block b;
b.major_version = 10;
b.minor_version = 10;
b.major_version = HF_VERSION_2021_SCALING;
b.minor_version = HF_VERSION_2021_SCALING;
bc->get_db().add_block(std::make_pair(std::move(b), ""), w, ltw, bc->get_db().height(), bc->get_db().height(), {});
if (!bc->update_next_cumulative_weight_limit())

16
tests/block_weight/block_weight.py
View File

@ -18,14 +18,20 @@ ltembw = MEDIAN_THRESHOLD
weights = [MEDIAN_THRESHOLD]*MEDIAN_WINDOW_SMALL # weights of recent blocks (B), with index -1 most recent
lt_weights = [MEDIAN_THRESHOLD]*MEDIAN_WINDOW_BIG # long-term weights
# see contrib/epee/include/misc_language.h, get_mid
def get_mid(a, b):
return (a//2) + (b//2) + ((a - 2*(a//2)) + (b - 2*(b//2)))//2;
# Compute the median of a list
def get_median(vec):
#temp = vec
if len(vec) == 1:
return vec[0]
temp = sorted(vec)
n = len(temp) // 2
if len(temp) % 2 == 1:
return temp[len(temp)//2]
return temp[n]
else:
return int((temp[len(temp)//2]+temp[len(temp)//2-1])//2)
return get_mid(temp[n-1], temp[n])
def LCG():
global lcg_seed
@ -46,7 +52,7 @@ def run(t, blocks):
# determine the effective weight
stmedian = get_median(weights[-MEDIAN_WINDOW_SMALL:])
embw = min(max(MEDIAN_THRESHOLD,stmedian),int(MULTIPLIER_BIG*ltembw))
embw = min(max(ltembw,stmedian),int(MULTIPLIER_BIG*ltembw))
# drop the lowest values
weights = weights[1:]
@ -64,7 +70,7 @@ def run(t, blocks):
else:
sys.exit(1)
weights.append(max_weight)
lt_weights.append(min(max_weight,int(ltembw + int(ltembw * 2 / 5))))
lt_weights.append(min(max(max_weight, ltembw * 10 // 17),int(ltembw + int(ltembw * 7 / 10))))
#print "H %u, r %u, BW %u, EMBW %u, LTBW %u, LTEMBW %u, ltmedian %u" % (block, r, max_weight, embw, lt_weights[-1], ltembw, ltmedian)
print("H %u, BW %u, EMBW %u, LTBW %u" % (block, max_weight, embw, lt_weights[-1]))