if __name__ == "__main__":
mw = MicroWriter(write_key=WRITE_KEY)
LONG = '~' + str(mw.DELAYS[-1])
SHORT = '~' + str(mw.DELAYS[0])
# Give up if things are going badly ... do it nicely
for _ in range(5):
mw.cancel_worst_active(stop_loss=STOP_LOSS, num=1)
time.sleep(1)
for name in mw.get_streams():
if 'z2~' in name and (LONG in name or SHORT in name):
num = mw.num_predictions
z11 = '~'.join(['z1', name.split('~')[1], name.split('~')[3]])
z12 = '~'.join(['z1', name.split('~')[2], name.split('~')[3]])
lagged1 = mw.get_lagged_values(z11)
lagged2 = mw.get_lagged_values(z12)
if len(lagged1) > 10:
z_samples = list()
for z1, z2 in zip(lagged1, lagged2):
try:
p1 = mw.normcdf(z1)
p2 = mw.normcdf(z2)
z = mw.to_zcurve(prctls=[p1, p2])
z_samples.append(z)
except:
pass
samples = exponential_bootstrap(z_samples,
decay=0.001,
num=mw.num_predictions,
from microprediction import MicroWriter, new_key
import random
from pprint import pprint
from collections import Counter
# Crush the die.json contest and some others using the new discrete_pdf_lagged functionality
NAMES = ['die.json']
if __name__ == "__main__":
write_key = new_key(difficulty=8)
print(write_key)
mw = MicroWriter(write_key=write_key, base_url='https://devapi.microprediction.org')
for name in NAMES:
for delay in mw.DELAYS:
lagged_values = mw.get_lagged_values(name=name)
pdf = mw.get_discrete_pdf_lagged(name=name, delay=mw.DELAYS[1],
lagged_values=lagged_values) # "market measure"
empirical_pdf = Counter(lagged_values)
market_pdf = dict(zip(pdf['x'], pdf['y']))
weights = [empirical_pdf[x] / (0.01 + market_pdf[x]) for x in pdf['x']]
samples = random.choices(population=pdf['x'], weights=weights, k=mw.num_predictions)
res = mw.submit(name=name, delay=delay, values=samples, verbose=True)
pprint(res)
print('Punch ' + write_key + ' into dashboard at https://www.microprediction.org/dashboard.html')
