research/elasticity/analyzer.py

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lines = open('data.csv').read().split('\n')
data = [(int(x[:x.find(',')]), float(x[x.find(',')+1:])) for x in lines if x]
REPORT_THRESHOLD = 0.23
def get_error(scale, elasticity, growth):
err = 0
bs_fac, fee_fac = 1 / (1 + elasticity), elasticity / (1 + elasticity)
for i, (block_size, avg_fee) in enumerate(data):
expected = scale * (1 + growth) ** i
actual = block_size ** bs_fac * avg_fee ** fee_fac
# if i >= len(data) - 6:
# err += ((expected / actual - 1) ** 2) * 2
err += (expected / actual - 1) ** 2
return err
best = (0, 0, 0, 9999999999999999999999999.0)
for scale in [1 * 1.05 ** x for x in range(300)]:
for elasticity in [x*0.025 for x in range(120)]:
for growth in [x*0.001 for x in range(120)]:
err = get_error(scale, elasticity, growth)
if err <= REPORT_THRESHOLD:
print('%d %.3f %.3f: %.3f' % (scale, elasticity, growth, err))
if err < best[-1]:
best = scale, elasticity, growth, err
print('Best params: %d %.3f %.3f (err %.3f)' % best)
scale, elasticity, growth, err = best
bs_fac, fee_fac = 1 / (1 + elasticity), elasticity / (1 + elasticity)
for i, (block_size, avg_fee) in enumerate(data):
expected = scale * (1 + growth) ** i
actual = block_size ** bs_fac * avg_fee ** fee_fac
print(i, actual, expected)