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from dataclasses import dataclass
from collections import defaultdict
from typing import Dict
from base.attribute import Attribute
from base.constant import FRAME_PER_SECOND
from base.skill import Skill, DotDamage
from utils.parser import School
@dataclass
class Detail:
damage: int = 0
critical_damage: int = 0
expected_damage: float = 0.
critical_strike: float = 0.
gradients: Dict[str, float] = None
critical_count: int = 0
count: int = 0
def __post_init__(self):
self.gradients = defaultdict(float)
@property
def actual_critical_strike(self):
if self.count:
return self.critical_count / self.count
return 0
def filter_status(status, school: School, skill_id):
buffs = []
for buff_id, buff_level, buff_stack in status:
buff = school.buffs[buff_id]
if not buff.activate:
continue
buff.buff_level, buff.buff_stack = buff_level, buff_stack
if buff.gain_attributes or skill_id in buff.gain_skills:
buffs.append(buff)
return tuple(sorted(buffs, key=lambda x: x.buff_id))
def add_buffs(current_buffs, snapshot_buffs, attribute: Attribute, skill: Skill):
if not snapshot_buffs:
for buff in current_buffs:
buff.add_all(attribute, skill)
elif isinstance(skill, DotDamage):
for buff in snapshot_buffs:
buff.add_dot(attribute, skill, True)
for buff in current_buffs:
buff.add_dot(attribute, skill, False)
def sub_buffs(current_buffs, snapshot_buffs, attribute: Attribute, skill: Skill):
if not snapshot_buffs:
for buff in current_buffs:
buff.sub_all(attribute, skill)
elif isinstance(skill, DotDamage):
for buff in snapshot_buffs:
buff.sub_dot(attribute, skill, True)
for buff in current_buffs:
buff.sub_dot(attribute, skill, False)
def concat_buffs(current_buffs, snapshot_buffs):
buffs = ",".join(buff.display_name for buff in current_buffs)
if snapshot_buffs and current_buffs != snapshot_buffs:
buffs += f"({','.join(buff.display_name for buff in snapshot_buffs)})"
if not buffs:
buffs = "~"
return buffs
def analyze_details(record, duration: int, attribute: Attribute, school: School):
total = Detail()
details = {}
summary = {}
duration *= FRAME_PER_SECOND
for skill, status in record.items():
skill_id, skill_level, skill_stack = skill
skill: Skill = school.skills[skill_id]
if not skill.activate:
continue
skill.skill_level, skill.skill_stack = skill_level, skill_stack
skill_name = skill.skill_name
skill_detail = details[skill.display_name] = {}
if not (skill_summary := summary.get(skill_name)):
skill_summary = summary[skill_name] = Detail()
skill_total = skill_detail[""] = Detail()
for (current_status, snapshot_status), timeline in status.items():
if not (timeline := [t for t in timeline if t[0] < duration]):
continue
critical_timeline = [t for t in timeline if t[1]]
current_buffs = filter_status(current_status, school, skill_id)
snapshot_buffs = filter_status(snapshot_status, school, skill_id)
buffs = concat_buffs(current_buffs, snapshot_buffs)
if not (detail := skill_detail.get(buffs)):
add_buffs(current_buffs, snapshot_buffs, attribute, skill)
detail = skill_detail[buffs] = Detail(*skill(attribute))
detail.gradients = analyze_gradients(skill, attribute)
sub_buffs(current_buffs, snapshot_buffs, attribute, skill)
detail.critical_count += len(critical_timeline)
detail.count += len(timeline)
skill_total.critical_count += len(critical_timeline)
skill_total.count += len(timeline)
skill_total.damage += detail.damage * len(timeline)
skill_total.critical_damage += detail.critical_damage * len(timeline)
skill_total.expected_damage += detail.expected_damage * len(timeline)
skill_total.critical_strike += detail.critical_strike * len(timeline)
for attr, residual_damage in detail.gradients.items():
skill_total.gradients[attr] += residual_damage * len(timeline)
if skill_total.count:
total.expected_damage += skill_total.expected_damage
skill_summary.expected_damage += skill_total.expected_damage
skill_summary.critical_count += skill_total.critical_strike
skill_summary.count += skill_total.count
skill_total.damage /= skill_total.count
skill_total.critical_damage /= skill_total.count
skill_total.expected_damage /= skill_total.count
skill_total.critical_strike /= skill_total.count
for attr, residual_damage in skill_total.gradients.items():
total.gradients[attr] += residual_damage
skill_total.gradients[attr] /= skill_total.count
else:
details.pop(skill.display_name)
summary = {skill: detail for skill, detail in summary.items() if detail.count}
return total, summary, details
def analyze_gradients(skill, attribute):
results = {}
for attr, value in attribute.grad_attrs.items():
origin_value = getattr(attribute, attr)
setattr(attribute, attr, origin_value + value)
_, _, results[attr], _ = skill(attribute)
setattr(attribute, attr, origin_value)
return results
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