Add support for average ailment stacks on capped ailments

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Is your feature request related to a problem?

Ingame due to the probabilistic nature of inflicting ailments (<100% chance) your number of stacks inflicted can change between any given number e.g. 0-1 stacks for an ignite build with low chance. But as stacks are truncated at one almost always average stacks are less than one. Factoring this will give chance to inflict ailments a better indication in dps for low values.

Stacks vs Chance

Describe the solution you'd like

Proper calculation of these average stacks that is at least reasonably accurate like the simulation is. Getting a direct formula might be possible if you consider the maximum stack counts separately but it is a hard probability problem to solve.

Describe alternatives you've considered

No response

Additional context

Script to generate graph beforehand

import random

max = 1000000
chance = 0.5
intervalTime = 1/33
attackTime = 0.75
duration = 4
cap = 2

f = open("out.txt", "w")

for j in range(0, 100):
    stacks = [ ]
    chance = j / 100
    lastAttackTime = 0
    time = 0
    average = 0
    print(chance)
    for i in range(0, max):
        if lastAttackTime <= time:
            lastAttackTime = time + attackTime
            if random.random() < chance: 
                stacks.append(time)

        for v in stacks:
            if v + duration < time:
                stacks.remove(v)

        averageStack = min(cap, len(stacks))

        average += averageStack

        time += intervalTime
    average /= max

    f.write("{:.6f}".format(average))
    f.write("\n")

f.close()

Sheet with data https://docs.google.com/spreadsheets/d/15rNcc18PqFRU2f9NCbd-T0WU2-d0_iGT1Tb99I9ca4c/edit?usp=sharing

Non viene indicato alcun file di implementazione, test o punto di ingresso. Inizia individuando nel codice di Path of Building il calcolo degli stack di ailment con limite e confrontalo con la simulazione fornita; il lavoro è completato quando vengono calcolati gli stack medi per gli ailment con limite e producono risultati ragionevolmente accurati con diverse probabilità di inflizione.