X-Git-Url: https://wannabe.guru.org/gitweb/?a=blobdiff_plain;f=math_utils.py;h=ed9c2f450f0fb0a9b121069a19d4a0b1fe7acfba;hb=562a15c6397610cf93646d9530005eb4a0d6e6f8;hp=3953ae585d249123c17e82f4a829ad68cf442c0b;hpb=31c81f6539969a5eba864d3305f9fb7bf716a367;p=python_utils.git diff --git a/math_utils.py b/math_utils.py index 3953ae5..ed9c2f4 100644 --- a/math_utils.py +++ b/math_utils.py @@ -1,52 +1,138 @@ #!/usr/bin/env python3 +# © Copyright 2021-2022, Scott Gasch + +"""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 + self.maximum = None + self.minimum = None + + def add_number(self, number: float): + """Adds a number to the population. Runtime complexity of this + operation is :math:`O(2 log_2 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() - - def rebalance(self): + self.aggregate += number + self._rebalance() + if not self.maximum or number > self.maximum: + self.maximum = number + if not self.minimum or number < self.minimum: + self.minimum = number + + 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]: + """Returns the mode (most common member in the population) + in O(n) time.""" + + 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) + return math.sqrt(variance) / count + + def _create_sorted_copy_if_needed(self, count: int): + if not self.sorted_copy or count != len(self.sorted_copy): + self.sorted_copy = [] + for x in self.lowers: + self.sorted_copy.append(-x) + for x in self.highers: + self.sorted_copy.append(x) + self.sorted_copy = sorted(self.sorted_copy) + + 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. Not thread-safe; + does caching across multiple calls without an invocation to + add_number for perf reasons. + """ + if n == 50: + return self.get_median() + count = len(self.lowers) + len(self.highers) + self._create_sorted_copy_if_needed(count) + assert self.sorted_copy + index = round(count * (n / 100.0)) + index = max(0, index) + index = min(count - 1, index) + return self.sorted_copy[index] + def gcd_floats(a: float, b: float) -> float: + """Returns the greatest common divisor of a and b.""" if a < b: return gcd_floats(b, a) @@ -57,6 +143,7 @@ def gcd_floats(a: float, b: float) -> float: def gcd_float_sequence(lst: List[float]) -> float: + """Returns the greatest common divisor of a list of floats.""" if len(lst) <= 0: raise ValueError("Need at least one number") elif len(lst) == 1: @@ -69,15 +156,14 @@ def gcd_float_sequence(lst: List[float]) -> float: def truncate_float(n: float, decimals: int = 2): - """ - Truncate a float to a particular number of decimals. + """Truncate a float to a particular number of decimals. >>> truncate_float(3.1415927, 3) 3.141 """ - assert decimals > 0 and decimals < 10 - multiplier = 10 ** decimals + assert 0 < decimals < 10 + multiplier = 10**decimals return int(n * multiplier) / multiplier @@ -91,7 +177,6 @@ def percentage_to_multiplier(percent: float) -> float: 1.45 >>> percentage_to_multiplier(-25) 0.75 - """ multiplier = percent / 100 multiplier += 1.0 @@ -107,7 +192,6 @@ def multiplier_to_percent(multiplier: float) -> float: 0.0 >>> multiplier_to_percent(1.99) 99.0 - """ percent = multiplier if percent > 0.0: @@ -130,7 +214,6 @@ def is_prime(n: int) -> bool: False >>> is_prime(51602981) True - """ if not isinstance(n, int): raise TypeError("argument passed to is_prime is not of 'int' type")