PathOfBuildingCommunity / PathOfBuildingCommunity/PathOfBuilding

EHP calculation for mitigated hits with life gain on block is incorrect

Offen
#9,446 2 Kommentare 0 Reaktionen 0 zugewiesene Personen Auf GitHub ansehen

Dieses Issue hat noch niemand übernommen.

bug: calculation
Vorherrschende Sprache
Lua
Sterne
5.4k
Forks
2.4k
Ø Merge
1 T. 12 Std.
Gemergte PRs (30 T.)
26

Beschreibung

Check version
  • I'm running the latest version of Path of Building and I've verified this by checking the changelog
Check for duplicates
  • I've checked for duplicate open and closed issues by using the search function of the issue tracker
Check for support
  • I've checked that the calculation is supposed to be supported. If it isn't please open a feature request instead (Red text is a feature request).
What platform are you running Path of Building on?

Windows

What is the value from the calculation in-game?

In pob, allocating certain life nodes causes EHP to decrease, despite increasing every ehp metric. I have narrowed this down to an interaction with how life gain on block is being calculated in the process.

If I remove life from my character, as expected the "hits before death" value lowers. However, at certain breakpoints, the "Mitigated hits" number increases. For reasons unknown to me. Despite every other value in the ehp calculation staying the same or decreasing.

What is the value from the calculation in Path of Building?

At 3323 life, 1609 es I see hits before death at 2.49, unmitigated% at 22% and mitigated hits at 11.96.
At 3102 life, 1609 es I see hits before death at 2.37, unmitigated% at 22% and mitigated hits at 12.65.

How to reproduce the issue

Load the pob pastebin below
Toggle discipline and training on/off - you should see odd ehp behaviour

In config toggle "Disable EHP gain when hit"
Again, Toggle discipline and training on/off - no odd ehp behaviour appears

This works with other life nodes, but NOT all. Certain life breakpoints seem to trigger the issue, while others do not.

PoB for PoE1 build code
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
Screenshots
Image Image

Beitragsleitfaden

Beitragsleitfaden öffnen

Erste Schritte

  1. Lies das ganze Issue und danach den Beitragsleitfaden des Projekts.
  2. Schreib ins Issue, dass du es übernimmst — das erspart doppelte Arbeit.
  3. Forke das Repository und arbeite in einem Branch.
  4. Öffne einen Pull Request, der die Issue-Nummer nennt.

Rechercherichtung

Lade den bereitgestellten PoE1-Build-Code und reproduziere die EHP-Änderungen beim Aktivieren und Deaktivieren von Discipline and Training; wiederhole dies mit aktiviertem „Disable EHP gain when hit“. Vergleiche die Treffer vor dem Tod, den ungeminderten Prozentsatz und die geminderten Treffer über die gemeldeten Lebenswerte hinweg; abgeschlossen ist die Aufgabe, wenn Änderungen des Lebens nicht mehr das falsche Verhalten bei geminderten Treffern und bei EHP verursachen.

Vom Indexierungsmodell aus dem Issue-Text verfasst.

Bewertung

Tech-Stack
lua
Bereich
backend
Issue-Typ
Bug
Schwierigkeit
4/5
Geschätzter Aufwand
3-5 Tage
Aktivitätsstatus
Veraltet
Klarheit
Größtenteils klar
Anfängerfreundlichkeit
35/100

Neue Issues direkt in Ihr Postfach

Eine kurze Übersicht über anfängerfreundliche GitHub-Issues.