maxmouchet

def penalty(β):
    """
    L: log-likelihood
    n: number of data points
    k: number of parameters
    """
    return lambda L, n, k: β(n)*k - 2*L

AIC = penalty(lambda n: 2)
BIC = penalty(lambda n: np.log(n))

maxmouchet

#!/usr/bin/python3
import mmap
from collections import defaultdict
from sys import argv

# cb: control byte
# cs: control byte size
# dt: data type
# ps: payload size (or pointer size if ptr)
# pv: pointer value

maxmouchet

#!/usr/bin/python3
from ipaddress import ip_address
import mmap
from sys import argv
import sys

DATA_SECTION_SEP = b"\x00" * 16
META_SECTION_SEP = b"\xab\xcd\xefMaxMind.com"

if __name__ == "__main__":