X-Git-Url: https://wannabe.guru.org/gitweb/?a=blobdiff_plain;f=math_utils.py;h=156862a9c1b55eeec5515efef82f8f951d59b416;hb=89f305d67e913ea1512e2618a0375359ec925ada;hp=37fcec5f6c557cdf1a66d39b671fd8d9438ba29c;hpb=e8fbbb7306430478dec55d2c963eed116d8330cc;p=python_utils.git diff --git a/math_utils.py b/math_utils.py index 37fcec5..156862a 100644 --- a/math_utils.py +++ b/math_utils.py @@ -2,51 +2,121 @@ """Mathematical helpers.""" +import collections import functools import math from heapq import heappop, heappush -from typing import List +from typing import Dict, List, Optional, Tuple +import dict_utils -class RunningMedian(object): - """A running median computer. - >>> median = RunningMedian() - >>> median.add_number(1) - >>> median.add_number(10) - >>> median.add_number(3) - >>> median.get_median() +class NumericPopulation(object): + """A numeric population with some statistics such as median, mean, pN, + stdev, etc... + + >>> pop = NumericPopulation() + >>> pop.add_number(1) + >>> pop.add_number(10) + >>> pop.add_number(3) + >>> pop.get_median() 3 - >>> median.add_number(7) - >>> median.add_number(5) - >>> median.get_median() + >>> pop.add_number(7) + >>> pop.add_number(5) + >>> pop.get_median() 5 + >>> pop.get_mean() + 5.2 + >>> round(pop.get_stdev(), 2) + 1.75 + >>> pop.get_percentile(20) + 3 + >>> pop.get_percentile(60) + 7 + """ def __init__(self): self.lowers, self.highers = [], [] + self.aggregate = 0.0 + self.sorted_copy: Optional[List[float]] = None + + def add_number(self, number: float): + """O(2 log2 n)""" - def add_number(self, number): if not self.highers or number > self.highers[0]: heappush(self.highers, number) else: heappush(self.lowers, -number) # for lowers we need a max heap - self.rebalance() + self.aggregate += number + self._rebalance() - def rebalance(self): + def _rebalance(self): if len(self.lowers) - len(self.highers) > 1: heappush(self.highers, -heappop(self.lowers)) elif len(self.highers) - len(self.lowers) > 1: heappush(self.lowers, -heappop(self.highers)) - def get_median(self): + def get_median(self) -> float: + """Returns the approximate median (p50) so far in O(1) time.""" + if len(self.lowers) == len(self.highers): - return (-self.lowers[0] + self.highers[0]) / 2 + return -self.lowers[0] elif len(self.lowers) > len(self.highers): return -self.lowers[0] else: return self.highers[0] + def get_mean(self) -> float: + """Returns the mean (arithmetic mean) so far in O(1) time.""" + + count = len(self.lowers) + len(self.highers) + return self.aggregate / count + + def get_mode(self) -> Tuple[float, int]: + count: Dict[float, int] = collections.defaultdict(int) + for n in self.lowers: + count[-n] += 1 + for n in self.highers: + count[n] += 1 + return dict_utils.item_with_max_value(count) + + def get_stdev(self) -> float: + """Returns the stdev so far in O(n) time.""" + + mean = self.get_mean() + variance = 0.0 + for n in self.lowers: + n = -n + variance += (n - mean) ** 2 + for n in self.highers: + variance += (n - mean) ** 2 + count = len(self.lowers) + len(self.highers) - 1 + return math.sqrt(variance) / count + + def get_percentile(self, n: float) -> float: + """Returns the number at approximately pn% (i.e. the nth percentile) + of the distribution in O(n log n) time (expensive, requires a + complete sort). Not thread safe. Caching does across + multiple calls without an invocation to add_number. + + """ + if n == 50: + return self.get_median() + count = len(self.lowers) + len(self.highers) + if self.sorted_copy is not None: + if count == len(self.sorted_copy): + index = round(count * (n / 100.0)) + assert 0 <= index < count + return self.sorted_copy[index] + self.sorted_copy = [-x for x in self.lowers] + for x in self.highers: + self.sorted_copy.append(x) + self.sorted_copy = sorted(self.sorted_copy) + index = round(count * (n / 100.0)) + assert 0 <= index < count + return self.sorted_copy[index] + def gcd_floats(a: float, b: float) -> float: if a < b: