-from __future__ import division
+from __future__ import absolute_import, division
+
+import __builtin__
+import math
+import random
+import time
def median(x, use_float=True):
# there exist better algorithms...
y = sorted(x)
+ if not y:
+ raise ValueError('empty sequence!')
left = (len(y) - 1)//2
right = len(y)//2
sum = y[left] + y[right]
else:
return sum//2
+def mean(x):
+ total = 0
+ count = 0
+ for y in x:
+ total += y
+ count += 1
+ return total/count
+
def shuffled(x):
x = list(x)
random.shuffle(x)
def shift_left(n, m):
# python: :(
- if m < 0:
- return n >> -m
- return n << m
+ if m >= 0:
+ return n << m
+ return n >> -m
def clip(x, (low, high)):
if x < low:
else:
return x
+add_to_range = lambda x, (low, high): (min(low, x), max(high, x))
+
def nth(i, n=0):
i = iter(i)
for _ in xrange(n):
i.next()
return i.next()
+
+def geometric(p):
+ if p <= 0 or p > 1:
+ raise ValueError('p must be in the interval (0.0, 1.0]')
+ if p == 1:
+ return 1
+ return int(math.log1p(-random.random()) / math.log1p(-p)) + 1
+
+def add_dicts_ext(add_func=lambda a, b: a+b, zero=0):
+ def add_dicts(*dicts):
+ res = {}
+ for d in dicts:
+ for k, v in d.iteritems():
+ res[k] = add_func(res.get(k, zero), v)
+ return dict((k, v) for k, v in res.iteritems() if v != zero)
+ return add_dicts
+add_dicts = add_dicts_ext()
+
+mult_dict = lambda c, x: dict((k, c*v) for k, v in x.iteritems())
+
+def format(x):
+ prefixes = 'kMGTPEZY'
+ count = 0
+ while x >= 100000 and count < len(prefixes) - 2:
+ x = x//1000
+ count += 1
+ s = '' if count == 0 else prefixes[count - 1]
+ return '%i' % (x,) + s
+
+def format_dt(dt):
+ for value, name in [(365.2425*60*60*24, 'years'), (60*60*24, 'days'), (60*60, 'hours'), (60, 'minutes'), (1, 'seconds')]:
+ if dt > value:
+ break
+ return '%.01f %s' % (dt/value, name)
+
+perfect_round = lambda x: int(x + random.random())
+
+def erf(x):
+ # save the sign of x
+ sign = 1
+ if x < 0:
+ sign = -1
+ x = abs(x)
+
+ # constants
+ a1 = 0.254829592
+ a2 = -0.284496736
+ a3 = 1.421413741
+ a4 = -1.453152027
+ a5 = 1.061405429
+ p = 0.3275911
+
+ # A&S formula 7.1.26
+ t = 1.0/(1.0 + p*x)
+ y = 1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*math.exp(-x*x)
+ return sign*y # erf(-x) = -erf(x)
+
+def find_root(y_over_dy, start, steps=10, bounds=(None, None)):
+ guess = start
+ for i in xrange(steps):
+ prev, guess = guess, guess - y_over_dy(guess)
+ if bounds[0] is not None and guess < bounds[0]: guess = bounds[0]
+ if bounds[1] is not None and guess > bounds[1]: guess = bounds[1]
+ if guess == prev:
+ break
+ return guess
+
+def ierf(z):
+ return find_root(lambda x: (erf(x) - z)/(2*math.e**(-x**2)/math.sqrt(math.pi)), 0)
+
+def binomial_conf_interval(x, n, conf=0.95):
+ assert 0 <= x <= n and 0 <= conf < 1
+ if n == 0:
+ left = random.random()*(1 - conf)
+ return left, left + conf
+ # approximate - Wilson score interval
+ z = math.sqrt(2)*ierf(conf)
+ p = x/n
+ topa = p + z**2/2/n
+ topb = z * math.sqrt(p*(1-p)/n + z**2/4/n**2)
+ bottom = 1 + z**2/n
+ return [clip(x, (0, 1)) for x in add_to_range(x/n, [(topa - topb)/bottom, (topa + topb)/bottom])]
+
+minmax = lambda x: (min(x), max(x))
+
+def format_binomial_conf(x, n, conf=0.95, f=lambda x: x):
+ if n == 0:
+ return '???'
+ left, right = minmax(map(f, binomial_conf_interval(x, n, conf)))
+ return '~%.1f%% (%.f-%.f%%)' % (100*f(x/n), math.floor(100*left), math.ceil(100*right))
+
+def reversed(x):
+ try:
+ return __builtin__.reversed(x)
+ except TypeError:
+ return reversed(list(x))
+
+class Object(object):
+ def __init__(self, **kwargs):
+ for k, v in kwargs.iteritems():
+ setattr(self, k, v)
+
+def add_tuples(res, *tuples):
+ for t in tuples:
+ if len(t) != len(res):
+ raise ValueError('tuples must all be the same length')
+ res = tuple(a + b for a, b in zip(res, t))
+ return res
+
+def flatten_linked_list(x):
+ while x is not None:
+ x, cur = x
+ yield cur
+
+def weighted_choice(choices):
+ choices = list((item, weight) for item, weight in choices)
+ target = random.randrange(sum(weight for item, weight in choices))
+ for item, weight in choices:
+ if weight > target:
+ return item
+ target -= weight
+ raise AssertionError()
+
+def natural_to_string(n, alphabet=None):
+ if n < 0:
+ raise TypeError('n must be a natural')
+ if alphabet is None:
+ s = ('%x' % (n,)).lstrip('0')
+ if len(s) % 2:
+ s = '0' + s
+ return s.decode('hex')
+ else:
+ assert len(set(alphabet)) == len(alphabet)
+ res = []
+ while n:
+ n, x = divmod(n, len(alphabet))
+ res.append(alphabet[x])
+ res.reverse()
+ return ''.join(res)
+
+def string_to_natural(s, alphabet=None):
+ if alphabet is None:
+ assert not s.startswith('\x00')
+ return int(s.encode('hex'), 16) if s else 0
+ else:
+ assert len(set(alphabet)) == len(alphabet)
+ assert not s.startswith(alphabet[0])
+ return sum(alphabet.index(char) * len(alphabet)**i for i, char in enumerate(reversed(s)))
+
+class RateMonitor(object):
+ def __init__(self, max_lookback_time):
+ self.max_lookback_time = max_lookback_time
+
+ self.datums = []
+ self.first_timestamp = None
+
+ def _prune(self):
+ start_time = time.time() - self.max_lookback_time
+ for i, (ts, datum) in enumerate(self.datums):
+ if ts > start_time:
+ self.datums[:] = self.datums[i:]
+ return
+
+ def get_datums_in_last(self, dt=None):
+ if dt is None:
+ dt = self.max_lookback_time
+ assert dt <= self.max_lookback_time
+ self._prune()
+ now = time.time()
+ return [datum for ts, datum in self.datums if ts > now - dt], min(dt, now - self.first_timestamp) if self.first_timestamp is not None else 0
+
+ def add_datum(self, datum):
+ self._prune()
+ t = time.time()
+ if self.first_timestamp is None:
+ self.first_timestamp = t
+ else:
+ self.datums.append((t, datum))