import math
from heapq import heappush
from pysad.core.base_statistic import UnivariateStatistic
import numpy as np
[docs]class MinMeter(UnivariateStatistic):
"""The statistic that keeps track of the minimum value.
Attrs:
min (float): The minimum value.
lst (list[float]): The list of values that are used to update the statistic. It is necessary for windowing operations.
"""
def __init__(self):
self.min = math.inf
self.lst = []
[docs] def update(self, num):
"""Updates the statistic with the value for a timestep.
Args:
num (float): The incoming value, for which the statistic is used.
Returns:
object: self.
"""
if num < self.min:
self.min = num
heappush(self.lst, num)
return self
[docs] def remove(self, num):
"""Updates the statistic by removing particular value. This method
Args:
num (float): The value to be removed.
Returns:
object: self.
"""
self.lst.remove(num)
if len(self.lst) > 0:
self.min = np.min(self.lst)
else:
self.min = math.inf
return self
[docs] def get(self):
""" Method to obtain the tracked statistic.
Returns:
float: The statistic.
"""
return self.min