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executable file 101 lines (88 sloc) 2.428 kB
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import json
import math
import itertools
BIG_VALUE = 2 ** 60
SMALL_VALUE = - (2 ** 60)
def hostport(hoststring, default_port=8091):
""" finds the host and port given a host:port string """
try:
host, port = hoststring.split(':')
port = int(port)
except ValueError:
host = hoststring
port = default_port
return (host, port)
def time_label(s):
# -(2**64) -> '-inf'
# 2**64 -> 'inf'
# 0 -> '0'
# 4 -> '4us'
# 838384 -> '838ms'
# 8283852 -> '8s'
if s > BIG_VALUE:
return 'inf'
elif s < SMALL_VALUE:
return '-inf'
elif s == 0:
return '0'
product = 1
sizes = (('us', 1), ('ms', 1000), ('s', 1000), ('m', 60))
sizeMap = []
for l,sz in sizes:
product = sz * product
sizeMap.insert(0, (l, product))
lbl, factor = itertools.dropwhile(lambda x: x[1] > s, sizeMap).next()
return "%d %s" % (s / factor, lbl)
def size_label(s):
if type(s) in (int, long, float, complex) :
if s == 0:
return "0"
sizes=['', 'KB', 'MB', 'GB', 'TB', 'PB', 'EB']
e = math.floor(math.log(abs(s), 1024))
suffix = sizes[int(e)]
return "%d %s" % (s/(1024 ** math.floor(e)), suffix)
else:
return s
def linreg(X, Y):
"""
Summary
Linear regression of y = ax + b
Usage
real, real, real = linreg(list, list)
Returns coefficients to the regression line "y=ax+b" from x[] and y[], and R^2 Value
"""
if len(X) != len(Y): raise ValueError, 'unequal length'
N = len(X)
Sx = Sy = Sxx = Syy = Sxy = 0.0
for x, y in map(None, X, Y):
Sx = Sx + x
Sy = Sy + y
Sxx = Sxx + x*x
Syy = Syy + y*y
Sxy = Sxy + x*y
det = Sxx * N - Sx * Sx
if det == 0:
return 0, 0
else:
a, b = (Sxy * N - Sy * Sx)/det, (Sxx * Sy - Sx * Sxy)/det
return a, b
def two_pass_variance(data):
n = 0
sum1 = 0
sum2 = 0
for x in data:
n = n + 1
sum1 = sum1 + x
mean = sum1/n
for x in data:
sum2 = sum2 + (x - mean)*(x - mean)
if n <= 1:
return 0
variance = sum2/(n - 1)
return variance
def pretty_float(number, precision=2):
return '%.*f' % (precision, number)
def pretty_print(obj):
return json.dumps(obj, indent=4, sort_keys=True)
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