def __calculateValue(self, key):
# If value is forced, we don't have to calculate anything,
# just return forced value instead
force = self.__forced[key] if key in self.__forced else None
if force is not None:
return force
# Grab our values if they're there, otherwise we'll take default values
preIncrease = self.__preIncreases[
key] if key in self.__preIncreases else 0
multiplier = self.__multipliers[key] if key in self.__multipliers else 1
penalizedMultiplierGroups = self.__penalizedMultipliers[
key] if key in self.__penalizedMultipliers else {}
postIncrease = self.__postIncreases[
key] if key in self.__postIncreases else 0
# Grab initial value, priorities are:
# Results of ongoing calculation > preAssign > original > 0
try:
default = defaultValuesCache[key]
except KeyError:
from eos.db.gamedata.queries import getAttributeInfo
attrInfo = getAttributeInfo(key)
if attrInfo is None:
default = defaultValuesCache[key] = 0.0
else:
dv = attrInfo.defaultValue
default = defaultValuesCache[
key] = dv if dv is not None else 0.0
val = self.__intermediary[
key] if key in self.__intermediary else self.__preAssigns[
key] if key in self.__preAssigns else self.getOriginal(
key) if key in self.__original else default
# We'll do stuff in the following order:
# preIncrease > multiplier > stacking penalized multipliers > postIncrease
val += preIncrease
val *= multiplier
# Each group is penalized independently
# Things in different groups will not be stack penalized between each other
for penalizedMultipliers in penalizedMultiplierGroups.itervalues():
# A quick explanation of how this works:
# 1: Bonuses and penalties are calculated seperately, so we'll have to filter each of them
l1 = filter(lambda val: val > 1, penalizedMultipliers)
l2 = filter(lambda val: val < 1, penalizedMultipliers)
# 2: The most significant bonuses take the smallest penalty,
# This means we'll have to sort
abssort = lambda val: -abs(val - 1)
l1.sort(key=abssort)
l2.sort(key=abssort)
# 3: The first module doesn't get penalized at all
# Any module after the first takes penalties according to:
# 1 + (multiplier - 1) * math.exp(- math.pow(i, 2) / 7.1289)
for l in (l1, l2):
for i in xrange(len(l)):
bonus = l[i]
val *= 1 + (bonus - 1) * exp(-i**2 / 7.1289)
val += postIncrease
return val
def _importGetMutationData(lines):
data = {}
consumedIndices = set()
for i in range(len(lines)):
line = lines[i]
m = re.match('^\[(?P<ref>\d+)\]', line)
if m:
ref = int(m.group('ref'))
# Attempt to apply mutation is useless w/o mutaplasmid, so skip it
# altogether if we have no info on it
try:
mutaName = lines[i + 1]
except IndexError:
continue
else:
consumedIndices.add(i)
consumedIndices.add(i + 1)
# Get custom attribute values
mutaAttrs = {}
try:
mutaAttrsLine = lines[i + 2]
except IndexError:
pass
else:
consumedIndices.add(i + 2)
pairs = [p.strip() for p in mutaAttrsLine.split(',')]
for pair in pairs:
try:
attrName, value = pair.split(' ')
except ValueError:
continue
try:
value = float(value)
except (ValueError, TypeError):
continue
attrInfo = getAttributeInfo(attrName.strip())
if attrInfo is None:
continue
mutaAttrs[attrInfo.ID] = value
mutaItem = _fetchItem(mutaName)
if mutaItem is None:
continue
data[ref] = (mutaItem, mutaAttrs)
# If we got here, we have seen at least correct reference line and
# mutaplasmid name line
i += 2
# Bonus points for seeing correct attrs line. Worst case we
# will have to scan it once again
if mutaAttrs:
i += 1
# Cleanup the lines from mutaplasmid info
for i in sorted(consumedIndices, reverse=True):
del lines[i]
return data
def renderMutant(mutant, firstPrefix='', prefix=''):
exportLines = []
mutatedAttrs = {}
for attrID, mutator in mutant.mutators.items():
attrName = getAttributeInfo(attrID).name
mutatedAttrs[attrName] = mutator.value
exportLines.append('{}{}'.format(firstPrefix, mutant.baseItem.name))
exportLines.append('{}{}'.format(prefix, mutant.mutaplasmid.item.name))
customAttrsLine = ', '.join('{} {}'.format(a, floatUnerr(mutatedAttrs[a]))
for a in sorted(mutatedAttrs))
exportLines.append('{}{}'.format(prefix, customAttrsLine))
return '\n'.join(exportLines)
def getAttrDefault(key, fallback=None):
try:
default = defaultValuesCache[key]
except KeyError:
attrInfo = getAttributeInfo(key)
if attrInfo is None:
default = defaultValuesCache[key] = None
else:
default = defaultValuesCache[key] = attrInfo.defaultValue
if default is None:
default = fallback
return default
def __calculateValue(self, key):
# If value is forced, we don't have to calculate anything,
# just return forced value instead
force = self.__forced[key] if key in self.__forced else None
if force is not None:
return force
# Grab our values if they're there, otherwise we'll take default values
preIncrease = self.__preIncreases[key] if key in self.__preIncreases else 0
multiplier = self.__multipliers[key] if key in self.__multipliers else 1
penalizedMultiplierGroups = self.__penalizedMultipliers[key] if key in self.__penalizedMultipliers else {}
postIncrease = self.__postIncreases[key] if key in self.__postIncreases else 0
# Grab initial value, priorities are:
# Results of ongoing calculation > preAssign > original > 0
try:
default = defaultValuesCache[key]
except KeyError:
from eos.db.gamedata.queries import getAttributeInfo
attrInfo = getAttributeInfo(key)
if attrInfo is None:
default = defaultValuesCache[key] = 0.0
else:
dv = attrInfo.defaultValue
default = defaultValuesCache[key] = dv if dv is not None else 0.0
val = self.__intermediary[key] if key in self.__intermediary else self.__preAssigns[key] if key in self.__preAssigns else self.getOriginal(key) if key in self.__original else default
# We'll do stuff in the following order:
# preIncrease > multiplier > stacking penalized multipliers > postIncrease
val += preIncrease
val *= multiplier
# Each group is penalized independently
# Things in different groups will not be stack penalized between each other
for penalizedMultipliers in penalizedMultiplierGroups.itervalues():
# A quick explanation of how this works:
# 1: Bonuses and penalties are calculated seperately, so we'll have to filter each of them
l1 = filter(lambda val: val > 1, penalizedMultipliers)
l2 = filter(lambda val: val < 1, penalizedMultipliers)
# 2: The most significant bonuses take the smallest penalty,
# This means we'll have to sort
abssort = lambda val: -abs(val - 1)
l1.sort(key=abssort)
l2.sort(key=abssort)
# 3: The first module doesn't get penalized at all
# Any module after the first takes penalties according to:
# 1 + (multiplier - 1) * math.exp(- math.pow(i, 2) / 7.1289)
for l in (l1, l2):
for i in xrange(len(l)):
bonus = l[i]
val *= 1 + (bonus - 1) * exp(- i ** 2 / 7.1289)
val += postIncrease
return val
def renderMutant(mutant, firstPrefix='', prefix=''):
exportLines = []
mutatedAttrs = {}
for attrID, mutator in mutant.mutators.items():
attrName = getAttributeInfo(attrID).name
mutatedAttrs[attrName] = mutator.value
exportLines.append('{}{}'.format(firstPrefix, mutant.baseItem.name))
exportLines.append('{}{}'.format(prefix, mutant.mutaplasmid.item.name))
# Round to 7th significant number to avoid exporting float errors
customAttrsLine = ', '.join(
'{} {}'.format(a, roundToPrec(mutatedAttrs[a], 7))
for a in sorted(mutatedAttrs))
exportLines.append('{}{}'.format(prefix, customAttrsLine))
return '\n'.join(exportLines)
def renderMutant(mutant, firstPrefix='', prefix=''):
exportLines = []
mutatedAttrs = {}
for attrID, mutator in mutant.mutators.items():
attrName = getAttributeInfo(attrID).name
mutatedAttrs[attrName] = mutator.value
exportLines.append('{}{}'.format(firstPrefix, mutant.baseItem.name))
exportLines.append('{}{}'.format(prefix, mutant.mutaplasmid.item.name))
# Round to 7th significant number to avoid exporting float errors
customAttrsLine = ', '.join(
'{} {}'.format(a, roundToPrec(mutatedAttrs[a], 7))
for a in sorted(mutatedAttrs))
exportLines.append('{}{}'.format(prefix, customAttrsLine))
return '\n'.join(exportLines)
def OnImport(self, event):
dlg = wx.FileDialog(self, "Import pyfa override file",
wildcard="pyfa override file (*.csv)|*.csv",
style=wx.FD_OPEN | wx.FD_FILE_MUST_EXIST)
if dlg.ShowModal() == wx.ID_OK:
path = dlg.GetPath()
with open(path, 'rb') as csvfile:
spamreader = csv.reader(csvfile)
for row in spamreader:
itemID, attrID, value = row
item = getItem(int(itemID))
attr = getAttributeInfo(int(attrID))
item.setOverride(attr, float(value))
self.itemView.updateItems(True)
def getResistance(fit, effect):
# Resistances are applicable only to projected effects
if isinstance(effect.type, (tuple, list)):
effectType = effect.type
else:
effectType = (effect.type, )
if 'projected' not in effectType:
return 1
remoteResistID = getResistanceAttrID(modifyingItem=fit.getModifier(),
effect=effect)
attrInfo = getAttributeInfo(remoteResistID)
# Get the attribute of the resist
resist = fit.ship.itemModifiedAttributes[
attrInfo.attributeName] or None
return resist or 1.0
def getResistance(fit, effect):
remoteResistID = effect.resistanceID
# If it doesn't exist on the effect, check the modifying modules attributes. If it's there, set it on the
# effect for this session so that we don't have to look here again (won't always work when it's None, but
# will catch most)
if not remoteResistID:
mod = fit.getModifier()
effect.resistanceID = int(mod.getModifiedItemAttr("remoteResistanceID")) or None
remoteResistID = effect.resistanceID
attrInfo = getAttributeInfo(remoteResistID)
# Get the attribute of the resist
resist = fit.ship.itemModifiedAttributes[attrInfo.attributeName] or None
return resist or 1.0
def getResistance(fit, effect):
remoteResistID = effect.resistanceID
# If it doesn't exist on the effect, check the modifying modules attributes. If it's there, set it on the
# effect for this session so that we don't have to look here again (won't always work when it's None, but
# will catch most)
if not remoteResistID:
mod = fit.getModifier()
effect.resistanceID = int(mod.getModifiedItemAttr("remoteResistanceID")) or None
remoteResistID = effect.resistanceID
attrInfo = getAttributeInfo(remoteResistID)
# Get the attribute of the resist
resist = fit.ship.itemModifiedAttributes[attrInfo.attributeName] or None
return resist or 1.0
def OnImport(self, event):
with wx.FileDialog(
self, "Import pyfa override file",
wildcard="pyfa override file (*.csv)|*.csv",
style=wx.FD_OPEN | wx.FD_FILE_MUST_EXIST
) as dlg:
if dlg.ShowModal() == wx.ID_OK:
path = dlg.GetPath()
with open(path, 'r') as csvfile:
spamreader = csv.reader(csvfile)
for row in spamreader:
if len(row) == 0: # csvwriter seems to added blank lines to the end sometimes
continue
itemID, attrID, value = row
item = getItem(int(itemID))
attr = getAttributeInfo(int(attrID))
item.setOverride(attr, float(value))
self.itemView.updateItems(True)
def parseMutant(lines):
# Fetch base item type
try:
baseItemName = lines[0]
except IndexError:
return None
baseItem = fetchItem(baseItemName.strip())
if baseItem is None:
return None, None, {}
# Fetch mutaplasmid item type and actual item
try:
mutaplasmidName = lines[1]
except IndexError:
return baseItem, None, {}
mutaplasmidItem = fetchItem(mutaplasmidName.strip())
if mutaplasmidItem is None:
return baseItem, None, {}
mutaplasmidItem = getDynamicItem(mutaplasmidItem.ID)
# Process mutated attribute values
try:
mutationsLine = lines[2]
except IndexError:
return baseItem, mutaplasmidItem, {}
mutations = {}
pairs = [p.strip() for p in mutationsLine.split(',')]
for pair in pairs:
try:
attrName, value = pair.split(' ')
except ValueError:
continue
try:
value = float(value)
except (ValueError, TypeError):
continue
attrInfo = getAttributeInfo(attrName.strip())
if attrInfo is None:
continue
mutations[attrInfo.ID] = value
return baseItem, mutaplasmidItem, mutations
def parseMutant(lines):
# Fetch base item type
try:
baseItemName = lines[0]
except IndexError:
return None
baseItem = fetchItem(baseItemName.strip())
if baseItem is None:
return None, None, {}
# Fetch mutaplasmid item type and actual item
try:
mutaplasmidName = lines[1]
except IndexError:
return baseItem, None, {}
mutaplasmidItem = fetchItem(mutaplasmidName.strip())
if mutaplasmidItem is None:
return baseItem, None, {}
mutaplasmidItem = getDynamicItem(mutaplasmidItem.ID)
# Process mutated attribute values
try:
mutationsLine = lines[2]
except IndexError:
return baseItem, mutaplasmidItem, {}
mutations = {}
pairs = [p.strip() for p in mutationsLine.split(',')]
for pair in pairs:
try:
attrName, value = pair.split(' ')
except ValueError:
continue
try:
value = float(value)
except (ValueError, TypeError):
continue
attrInfo = getAttributeInfo(attrName.strip())
if attrInfo is None:
continue
mutations[attrInfo.ID] = value
return baseItem, mutaplasmidItem, mutations
def __calculateValue(self, key):
# It's possible that various attributes are capped by other attributes,
# it's defined by reference maxAttributeID
try:
cappingKey = cappingAttrKeyCache[key]
except KeyError:
attrInfo = getAttributeInfo(key)
if attrInfo is None:
cappingId = cappingAttrKeyCache[key] = None
else:
# see GH issue #620
cappingId = cappingAttrKeyCache[key] = attrInfo.maxAttributeID
if cappingId is None:
cappingKey = None
else:
cappingAttrInfo = getAttributeInfo(cappingId)
cappingKey = None if cappingAttrInfo is None else cappingAttrInfo.name
if cappingKey:
cappingValue = self.original.get(cappingKey, self.__calculateValue(cappingKey))
cappingValue = cappingValue.value if hasattr(cappingValue, "value") else cappingValue
else:
cappingValue = None
# If value is forced, we don't have to calculate anything,
# just return forced value instead
force = self.__forced[key] if key in self.__forced else None
if force is not None:
if cappingValue is not None:
force = min(force, cappingValue)
return force
# Grab our values if they're there, otherwise we'll take default values
preIncrease = self.__preIncreases.get(key, 0)
multiplier = self.__multipliers.get(key, 1)
penalizedMultiplierGroups = self.__penalizedMultipliers.get(key, {})
postIncrease = self.__postIncreases.get(key, 0)
# Grab initial value, priorities are:
# Results of ongoing calculation > preAssign > original > 0
try:
default = defaultValuesCache[key]
except KeyError:
attrInfo = getAttributeInfo(key)
if attrInfo is None:
default = defaultValuesCache[key] = 0.0
else:
dv = attrInfo.defaultValue
default = defaultValuesCache[key] = dv if dv is not None else 0.0
val = self.__intermediary.get(key,
self.__preAssigns.get(key,
self.getOriginal(key, default)
)
)
# We'll do stuff in the following order:
# preIncrease > multiplier > stacking penalized multipliers > postIncrease
val += preIncrease
val *= multiplier
# Each group is penalized independently
# Things in different groups will not be stack penalized between each other
for penalizedMultipliers in penalizedMultiplierGroups.values():
# A quick explanation of how this works:
# 1: Bonuses and penalties are calculated seperately, so we'll have to filter each of them
l1 = [_val for _val in penalizedMultipliers if _val > 1]
l2 = [_val for _val in penalizedMultipliers if _val < 1]
# 2: The most significant bonuses take the smallest penalty,
# This means we'll have to sort
abssort = lambda _val: -abs(_val - 1)
l1.sort(key=abssort)
l2.sort(key=abssort)
# 3: The first module doesn't get penalized at all
# Any module after the first takes penalties according to:
# 1 + (multiplier - 1) * math.exp(- math.pow(i, 2) / 7.1289)
for l in (l1, l2):
for i in range(len(l)):
bonus = l[i]
val *= 1 + (bonus - 1) * exp(- i ** 2 / 7.1289)
val += postIncrease
# Cap value if we have cap defined
if cappingValue is not None:
val = min(val, cappingValue)
return val
def __calculateValue(self, key):
# It's possible that various attributes are capped by other attributes,
# it's defined by reference maxAttributeID
try:
cappingKey = cappingAttrKeyCache[key]
except KeyError:
attrInfo = getAttributeInfo(key)
if attrInfo is None:
cappingId = cappingAttrKeyCache[key] = None
else:
# see GH issue #620
cappingId = cappingAttrKeyCache[key] = attrInfo.maxAttributeID
if cappingId is None:
cappingKey = None
else:
cappingAttrInfo = getAttributeInfo(cappingId)
cappingKey = None if cappingAttrInfo is None else cappingAttrInfo.name
if cappingKey:
cappingValue = self.original.get(cappingKey,
self.__calculateValue(cappingKey))
cappingValue = cappingValue.value if hasattr(
cappingValue, "value") else cappingValue
else:
cappingValue = None
# If value is forced, we don't have to calculate anything,
# just return forced value instead
force = self.__forced[key] if key in self.__forced else None
if force is not None:
if cappingValue is not None:
force = min(force, cappingValue)
return force
# Grab our values if they're there, otherwise we'll take default values
preIncrease = self.__preIncreases.get(key, 0)
multiplier = self.__multipliers.get(key, 1)
penalizedMultiplierGroups = self.__penalizedMultipliers.get(key, {})
postIncrease = self.__postIncreases.get(key, 0)
# Grab initial value, priorities are:
# Results of ongoing calculation > preAssign > original > 0
try:
default = defaultValuesCache[key]
except KeyError:
attrInfo = getAttributeInfo(key)
if attrInfo is None:
default = defaultValuesCache[key] = 0.0
else:
dv = attrInfo.defaultValue
default = defaultValuesCache[
key] = dv if dv is not None else 0.0
val = self.__intermediary.get(
key, self.__preAssigns.get(key, self.getOriginal(key, default)))
# We'll do stuff in the following order:
# preIncrease > multiplier > stacking penalized multipliers > postIncrease
val += preIncrease
val *= multiplier
# Each group is penalized independently
# Things in different groups will not be stack penalized between each other
for penalizedMultipliers in penalizedMultiplierGroups.values():
# A quick explanation of how this works:
# 1: Bonuses and penalties are calculated seperately, so we'll have to filter each of them
l1 = [_val for _val in penalizedMultipliers if _val > 1]
l2 = [_val for _val in penalizedMultipliers if _val < 1]
# 2: The most significant bonuses take the smallest penalty,
# This means we'll have to sort
abssort = lambda _val: -abs(_val - 1)
l1.sort(key=abssort)
l2.sort(key=abssort)
# 3: The first module doesn't get penalized at all
# Any module after the first takes penalties according to:
# 1 + (multiplier - 1) * math.exp(- math.pow(i, 2) / 7.1289)
for l in (l1, l2):
for i in range(len(l)):
bonus = l[i]
val *= 1 + (bonus - 1) * exp(-i**2 / 7.1289)
val += postIncrease
# Cap value if we have cap defined
if cappingValue is not None:
val = min(val, cappingValue)
return val
def exportEft(fit, options):
# EFT formatted export is split in several sections, each section is
# separated from another using 2 blank lines. Sections might have several
# sub-sections, which are separated by 1 blank line
sections = []
header = '[{}, {}]'.format(fit.ship.item.name, fit.name)
# Section 1: modules, rigs, subsystems, services
modsBySlotType = {}
sFit = svcFit.getInstance()
for module in fit.modules:
modsBySlotType.setdefault(module.slot, []).append(module)
modSection = []
mutants = {} # Format: {reference number: module}
mutantReference = 1
for slotType in SLOT_ORDER:
rackLines = []
modules = modsBySlotType.get(slotType, ())
for module in modules:
if module.item:
mutated = bool(module.mutators)
# if module was mutated, use base item name for export
if mutated:
modName = module.baseItem.name
else:
modName = module.item.name
if mutated and options & Options.MUTATIONS.value:
mutants[mutantReference] = module
mutationSuffix = ' [{}]'.format(mutantReference)
mutantReference += 1
else:
mutationSuffix = ''
modOfflineSuffix = ' {}'.format(OFFLINE_SUFFIX) if module.state == State.OFFLINE else ''
if module.charge and sFit.serviceFittingOptions['exportCharges']:
rackLines.append('{}, {}{}{}'.format(
modName, module.charge.name, modOfflineSuffix, mutationSuffix))
else:
rackLines.append('{}{}{}'.format(modName, modOfflineSuffix, mutationSuffix))
else:
rackLines.append('[Empty {} slot]'.format(
Slot.getName(slotType).capitalize() if slotType is not None else ''))
if rackLines:
modSection.append('\n'.join(rackLines))
if modSection:
sections.append('\n\n'.join(modSection))
# Section 2: drones, fighters
minionSection = []
droneLines = []
for drone in sorted(fit.drones, key=lambda d: d.item.name):
droneLines.append('{} x{}'.format(drone.item.name, drone.amount))
if droneLines:
minionSection.append('\n'.join(droneLines))
fighterLines = []
for fighter in sorted(fit.fighters, key=lambda f: f.item.name):
fighterLines.append('{} x{}'.format(fighter.item.name, fighter.amountActive))
if fighterLines:
minionSection.append('\n'.join(fighterLines))
if minionSection:
sections.append('\n\n'.join(minionSection))
# Section 3: implants, boosters
if options & Options.IMPLANTS.value:
charSection = []
implantLines = []
for implant in fit.implants:
implantLines.append(implant.item.name)
if implantLines:
charSection.append('\n'.join(implantLines))
boosterLines = []
for booster in fit.boosters:
boosterLines.append(booster.item.name)
if boosterLines:
charSection.append('\n'.join(boosterLines))
if charSection:
sections.append('\n\n'.join(charSection))
# Section 4: cargo
cargoLines = []
for cargo in sorted(
fit.cargo,
key=lambda c: (c.item.group.category.name, c.item.group.name, c.item.name)
):
cargoLines.append('{} x{}'.format(cargo.item.name, cargo.amount))
if cargoLines:
sections.append('\n'.join(cargoLines))
# Section 5: mutated modules' details
mutationLines = []
if mutants and options & Options.MUTATIONS.value:
for mutantReference in sorted(mutants):
mutant = mutants[mutantReference]
mutatedAttrs = {}
for attrID, mutator in mutant.mutators.items():
attrName = getAttributeInfo(attrID).name
mutatedAttrs[attrName] = mutator.value
mutationLines.append('[{}] {}'.format(mutantReference, mutant.baseItem.name))
mutationLines.append(' {}'.format(mutant.mutaplasmid.item.name))
# Round to 7th significant number to avoid exporting float errors
customAttrsLine = ', '.join(
'{} {}'.format(a, roundToPrec(mutatedAttrs[a], 7))
for a in sorted(mutatedAttrs))
mutationLines.append(' {}'.format(customAttrsLine))
if mutationLines:
sections.append('\n'.join(mutationLines))
return '{}\n\n{}'.format(header, '\n\n\n'.join(sections))
def __calculateValue(self,
key,
extraMultipliers=None,
preIncAdj=None,
multAdj=None,
postIncAdj=None,
ignorePenMult=None):
# It's possible that various attributes are capped by other attributes,
# it's defined by reference maxAttributeID
try:
cappingKey = cappingAttrKeyCache[key]
except KeyError:
attrInfo = getAttributeInfo(key)
if attrInfo is None:
cappingId = cappingAttrKeyCache[key] = None
else:
cappingId = attrInfo.maxAttributeID
if cappingId is None:
cappingKey = None
else:
cappingAttrInfo = getAttributeInfo(cappingId)
cappingKey = None if cappingAttrInfo is None else cappingAttrInfo.name
cappingAttrKeyCache[key] = cappingKey
if cappingKey:
cappingValue = self.original.get(cappingKey,
self.__calculateValue(cappingKey))
cappingValue = cappingValue.value if hasattr(
cappingValue, "value") else cappingValue
else:
cappingValue = None
# If value is forced, we don't have to calculate anything,
# just return forced value instead
force = self.__forced[key] if key in self.__forced else None
if force is not None:
if cappingValue is not None:
force = min(force, cappingValue)
if key in ("cpu", "power", "cpuOutput", "powerOutput"):
force = round(force, 2)
return force
# Grab our values if they're there, otherwise we'll take default values
preIncrease = self.__preIncreases.get(key, 0)
multiplier = self.__multipliers.get(key, 1)
penalizedMultiplierGroups = self.__penalizedMultipliers.get(key, {})
# Add extra multipliers to the group, not modifying initial data source
if extraMultipliers is not None:
penalizedMultiplierGroups = copy(penalizedMultiplierGroups)
for stackGroup, operationsData in extraMultipliers.items():
multipliers = []
for mult, resAttrID in operationsData:
if not resAttrID:
multipliers.append(mult)
continue
resAttrInfo = getAttributeInfo(resAttrID)
if not resAttrInfo:
multipliers.append(mult)
continue
resMult = self.fit.ship.itemModifiedAttributes[
resAttrInfo.attributeName]
if resMult is None or resMult == 1:
multipliers.append(mult)
continue
mult = (mult - 1) * resMult + 1
multipliers.append(mult)
penalizedMultiplierGroups[
stackGroup] = penalizedMultiplierGroups.get(
stackGroup, []) + multipliers
postIncrease = self.__postIncreases.get(key, 0)
# Grab initial value, priorities are:
# Results of ongoing calculation > preAssign > original > 0
default = getAttrDefault(key, fallback=0.0)
val = self.__intermediary.get(
key, self.__preAssigns.get(key, self.getOriginal(key, default)))
# We'll do stuff in the following order:
# preIncrease > multiplier > stacking penalized multipliers > postIncrease
val += preIncrease
if preIncAdj is not None:
val += preIncAdj
val *= multiplier
if multAdj is not None:
val *= multAdj
# Each group is penalized independently
# Things in different groups will not be stack penalized between each other
for penaltyGroup, penalizedMultipliers in penalizedMultiplierGroups.items(
):
if ignorePenMult is not None and penaltyGroup in ignorePenMult:
# Avoid modifying source and remove multipliers we were asked to remove for this calc
penalizedMultipliers = penalizedMultipliers[:]
for ignoreMult in ignorePenMult[penaltyGroup]:
try:
penalizedMultipliers.remove(ignoreMult)
except ValueError:
pass
# A quick explanation of how this works:
# 1: Bonuses and penalties are calculated seperately, so we'll have to filter each of them
l1 = [_val for _val in penalizedMultipliers if _val > 1]
l2 = [_val for _val in penalizedMultipliers if _val < 1]
# 2: The most significant bonuses take the smallest penalty,
# This means we'll have to sort
abssort = lambda _val: -abs(_val - 1)
l1.sort(key=abssort)
l2.sort(key=abssort)
# 3: The first module doesn't get penalized at all
# Any module after the first takes penalties according to:
# 1 + (multiplier - 1) * math.exp(- math.pow(i, 2) / 7.1289)
for l in (l1, l2):
for i in range(len(l)):
bonus = l[i]
val *= 1 + (bonus - 1) * exp(-i**2 / 7.1289)
val += postIncrease
if postIncAdj is not None:
val += postIncAdj
# Cap value if we have cap defined
if cappingValue is not None:
val = min(val, cappingValue)
if key in ("cpu", "power", "cpuOutput", "powerOutput"):
val = round(val, 2)
return val