kurtbrose

'''
Implementation of piece-wise parabolic quantile estimation, algorithm defined in
http://www.cs.wustl.edu/~jain/papers/ftp/psqr.pdf
'''
from math import copysign

DEFAULT_LEVELS = (0.1, 1, 2, 5, 10, 25, 50, 75, 80, 85, 90, 95, 98, 99, 99.5, 99.8, 99.9, 99.99)


class Measure(object):

kurtbrose

'''
Efficient online statistics gathering.  Create a Stats object to track
as many statistics as desired.


Implementation of piece-wise parabolic quantile estimation, algorithm defined in
http://www.cs.wustl.edu/~jain/papers/ftp/psqr.pdf
'''
from math import copysign

kurtbrose

class Sample(object):
    '''
    This class implements Reservoir Sampling to keep a random sample of an infinite stream.
    See http://gregable.com/2007/10/reservoir-sampling.html for one description.
    '''
    def __init__(self, sample_size=2**14, type='f'):
        self.sample = array.array(type)
        self.sample_size = sample_size
        self.num_vals = 0

kurtbrose

import parsley

GRAMMAR = '''
digit = :x ?(x in '0123456789') -> x
digit1_9 = :x ?(x in '123456789') -> x
digits = (digit1_9:first <digit*>:rest -> first + rest) | '0'
integer = ('-' | -> ''):sign digits:ds  -> int(sign + ds)

alpha_ = :x ?(x.isalpha() or x == '_') -> x
alphanum_ = :x ?(x.isalnum() or x == '_') -> x

kurtbrose

'''
Computation of higher order statistics based on
http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Higher-order_statistics

Intended for use in long-running applications.
'''


class Stats(object):
    def __init__(self):

kurtbrose

'''
JKS file format decoder.
Use in conjunction with PyOpenSSL to translate to PEM, or load private key and certs
directly into openssl structs and wrap sockets.

See http://grepcode.com/file/repository.grepcode.com/java/root/jdk/openjdk/6-b14/sun/security/provider/JavaKeyStore.java#JavaKeyStore.engineLoad%28java.io.InputStream%2Cchar%5B%5D%29

'''
import struct
import hashlib

kurtbrose

import heapq
import collections
import time
import random

import greenlet
#import faststat


class Simulation(object):

kurtbrose

import sys
import code
from gevent import fileobject

_green_stdin = fileobject.FileObject(sys.stdin)
_green_stdout = fileobject.FileObject(sys.stdout)

def _green_raw_input(prompt):
    _green_stdout.write(prompt)
    return _green_stdin.readline()[:-1]

kurtbrose

import threading
import functools
import gc
import types


class ObjBrowserThread(threading.Thread):
    def __init__(self):
        threading.Thread.__init__(self)
        self.daemon = True

kurtbrose

'''
Two main jobs:
1- calculate the desired position
2- accelerate towards that position

Several acceleration profiles:
"spring" acceleration -- acceleration proportional to displacement from ideal
"rocket" acceleration -- max acceleration to mid point, followed by max de-celleration