def test_drone_dps(DB, Saveddata, RifterFit):
"""
Tests applied drone damage
"""
# set pilot
char0 = Saveddata['Character'].getAll0()
RifterFit.character = char0
# configure DPS analysis to include as many factors as possible
# (damage type reistance)
graph = FitDpsGraph(RifterFit)
data = graph.defaults.copy()
data['emRes'] = 10.0
# add a drone
drone = Saveddata['Drone'](DB['db'].getItem("Acolyte II"))
drone.amount = 1
drone.amountActive = 1
RifterFit.drones.append(drone)
# calculate applied DPS
RifterFit.clear()
RifterFit.calculateModifiedAttributes()
dps = graph.calcDps(data)
assert abs(dps - 7.6) < 0.05
def test_multiply_stacking_penalties(DB, Saveddata, RifterFit):
"""
Tests the stacking penalties under multiply
"""
char0 = Saveddata['Character'].getAll0()
RifterFit.character = char0
starting_em_resist = RifterFit.ship.getModifiedItemAttr("shieldEmDamageResonance")
mod = Saveddata['Module'](DB['db'].getItem("EM Ward Amplifier II"))
item_modifer = mod.item.getAttribute("emDamageResistanceBonus")
RifterFit.calculateModifiedAttributes()
for _ in range(10):
if _ == 0:
# First run we have no modules, se don't try and calculate them.
calculated_resist = RifterFit.ship.getModifiedItemAttr("shieldEmDamageResonance")
else:
# Calculate what our next resist should be
# Denominator: [math.exp((i / 2.67) ** 2.0) for i in xrange(8)]
current_effectiveness = 1 / math.exp(((_ - 1) / 2.67) ** 2.0)
new_item_modifier = 1 + ((item_modifer * current_effectiveness) / 100)
calculated_resist = (em_resist * new_item_modifier)
# Add another resist module to our fit.
RifterFit.modules.append(mod)
# Modify our fit so that Eos generates new numbers for us.
RifterFit.clear()
RifterFit.calculateModifiedAttributes()
em_resist = RifterFit.ship.getModifiedItemAttr("shieldEmDamageResonance")
assert em_resist == calculated_resist
def test_multiply_stacking_penalties(DB, Saveddata, RifterFit):
"""
Tests the stacking penalties under multiply
"""
char0 = Saveddata['Character'].getAll0()
RifterFit.character = char0
starting_em_resist = RifterFit.ship.getModifiedItemAttr(
"shieldEmDamageResonance")
mod = Saveddata['Module'](DB['db'].getItem("EM Ward Amplifier II"))
item_modifer = mod.item.getAttribute("emDamageResistanceBonus")
RifterFit.calculateModifiedAttributes()
for _ in range(10):
if _ == 0:
# First run we have no modules, se don't try and calculate them.
calculated_resist = RifterFit.ship.getModifiedItemAttr(
"shieldEmDamageResonance")
else:
# Calculate what our next resist should be
# Denominator: [math.exp((i / 2.67) ** 2.0) for i in xrange(8)]
current_effectiveness = 1 / math.exp(((_ - 1) / 2.67)**2.0)
new_item_modifier = 1 + (
(item_modifer * current_effectiveness) / 100)
calculated_resist = (em_resist * new_item_modifier)
# Add another resist module to our fit.
RifterFit.modules.append(mod)
# Modify our fit so that Eos generates new numbers for us.
RifterFit.clear()
RifterFit.calculateModifiedAttributes()
em_resist = RifterFit.ship.getModifiedItemAttr(
"shieldEmDamageResonance")
assert em_resist == calculated_resist
def test_rifter_coprocessor(DB, Saveddata, RifterFit):
char5 = Saveddata['Character'].getAll5()
char0 = Saveddata['Character'].getAll0()
RifterFit.character = char0
mod = Saveddata['Module'](DB['db'].getItem("Co-Processor II"))
mod.state = Saveddata['State'].OFFLINE
RifterFit.modules.append(mod)
assert RifterFit.ship.getModifiedItemAttr("cpuOutput") == 130
RifterFit.calculateModifiedAttributes()
assert RifterFit.ship.getModifiedItemAttr("cpuOutput") == 130
mod.state = Saveddata['State'].ONLINE
RifterFit.clear()
RifterFit.calculateModifiedAttributes()
assert RifterFit.ship.getModifiedItemAttr("cpuOutput") == 143
RifterFit.character = char5
RifterFit.clear()
RifterFit.calculateModifiedAttributes()
assert RifterFit.ship.getModifiedItemAttr("cpuOutput") == 178.75
def test_rifter_coprocessor(DB, Saveddata, RifterFit):
char5 = Saveddata['Character'].getAll5()
char0 = Saveddata['Character'].getAll0()
RifterFit.character = char0
mod = Saveddata['Module'](DB['db'].getItem("Co-Processor II"))
mod.state = Saveddata['State'].OFFLINE
RifterFit.modules.append(mod)
assert RifterFit.ship.getModifiedItemAttr("cpuOutput") == 130
RifterFit.calculateModifiedAttributes()
assert RifterFit.ship.getModifiedItemAttr("cpuOutput") == 130
mod.state = Saveddata['State'].ONLINE
RifterFit.clear()
RifterFit.calculateModifiedAttributes()
assert RifterFit.ship.getModifiedItemAttr("cpuOutput") == 143
RifterFit.character = char5
RifterFit.clear()
RifterFit.calculateModifiedAttributes()
assert RifterFit.ship.getModifiedItemAttr("cpuOutput") == 178.75
def test_turret_dps(DB, Saveddata, RifterFit):
"""
Tests applied turret damage
"""
# set pilot
char0 = Saveddata['Character'].getAll0()
RifterFit.character = char0
# configure DPS analysis to include as many factors as possible
# (damage type reistance, distance past turret optimal, sig/speed/angle to incur turret tracking penalty)
graph = FitDpsGraph(RifterFit)
data = graph.defaults.copy()
data['emRes'] = 10.0
data['distance'] = 7.0
data['signatureRadius'] = 100.0
data['tgtAngle'] = 90.0
data['tgtSpeed'] = 100.0
# add a turret
mod = Saveddata['Module'](DB['db'].getItem("280mm Howitzer Artillery II"))
mod.owner = RifterFit
mod.state = Saveddata['State'].ACTIVE
# there must be a better way to fetch this ammo directly, but I couldn't figure out the appropriate Gamedata voodoo;
# this, for example, did not work:
# mod.charge = DB['gamedata_session'].query(Gamedata['Item']).filter(Gamedata['Item'].name == "EMP S").first()
for charge in mod.getValidCharges():
if charge.name == "EMP S":
mod.charge = charge
break
RifterFit.modules.append(mod)
# calculate applied DPS
RifterFit.clear()
RifterFit.calculateModifiedAttributes()
dps = graph.calcDps(data)
assert abs(dps - 8.8) < 0.05
def test_calculateModifiedAttributes_withProjected(DB, RifterFit, HeronFit):
# TODO: This test is not currently functional or meaningful as projections are not happening correctly.
# This is true for all tested branches (master, dev, etc)
rifter_modifier_dicts = {
'_ModifiedAttributeDict__affectedBy' : 26,
'_ModifiedAttributeDict__forced' : 0,
'_ModifiedAttributeDict__intermediary' : 0,
'_ModifiedAttributeDict__modified' : 26,
'_ModifiedAttributeDict__multipliers' : 22,
'_ModifiedAttributeDict__overrides' : 0,
'_ModifiedAttributeDict__penalizedMultipliers': 0,
'_ModifiedAttributeDict__postIncreases' : 0,
'_ModifiedAttributeDict__preAssigns' : 0,
'_ModifiedAttributeDict__preIncreases' : 4,
}
# Test before calculating attributes
for test_dict in rifter_modifier_dicts:
assert len(getattr(RifterFit.ship.itemModifiedAttributes, test_dict)) == 0
# Get base stats
max_target_range_1 = RifterFit.ship.getModifiedItemAttr('maxTargetRange')
scan_resolution_1 = RifterFit.ship.getModifiedItemAttr('scanResolution')
RifterFit.clear()
RifterFit.calculateModifiedAttributes()
# Get self calculated stats
max_target_range_2 = RifterFit.ship.getModifiedItemAttr('maxTargetRange')
scan_resolution_2 = RifterFit.ship.getModifiedItemAttr('scanResolution')
RifterFit.clear()
# Project Heron fit onto Rifter
RifterFit._Fit__projectedFits[HeronFit.ID] = HeronFit
# DB['saveddata_session'].commit()
# DB['saveddata_session'].flush()
# DB['saveddata_session'].refresh(HeronFit)
RifterFit.calculateModifiedAttributes()
# Get stats with projections
max_target_range_3 = RifterFit.ship.getModifiedItemAttr('maxTargetRange')
scan_resolution_3 = RifterFit.ship.getModifiedItemAttr('scanResolution')
RifterFit.clear()
RifterFit.calculateModifiedAttributes()
# Get stats with projections
max_target_range_4 = RifterFit.ship.getModifiedItemAttr('maxTargetRange')
scan_resolution_4 = RifterFit.ship.getModifiedItemAttr('scanResolution')
RifterFit.clear()
HeronFit.calculateModifiedAttributes(targetFit=RifterFit)
RifterFit.calculateModifiedAttributes()
# Get stats with projections
max_target_range_5 = RifterFit.ship.getModifiedItemAttr('maxTargetRange')
scan_resolution_5 = RifterFit.ship.getModifiedItemAttr('scanResolution')
for test_dict in rifter_modifier_dicts:
assert len(getattr(RifterFit.ship.itemModifiedAttributes, test_dict)) == rifter_modifier_dicts[test_dict]
def test_calculateModifiedAttributes_withProjected(DB, RifterFit, HeronFit):
# TODO: This test is not currently functional or meaningful as projections are not happening correctly.
# This is true for all tested branches (master, dev, etc)
rifter_modifier_dicts = {
'_ModifiedAttributeDict__affectedBy' : 26,
'_ModifiedAttributeDict__forced' : 0,
'_ModifiedAttributeDict__intermediary' : 0,
'_ModifiedAttributeDict__modified' : 26,
'_ModifiedAttributeDict__multipliers' : 22,
'_ModifiedAttributeDict__overrides' : 0,
'_ModifiedAttributeDict__penalizedMultipliers': 0,
'_ModifiedAttributeDict__postIncreases' : 0,
'_ModifiedAttributeDict__preAssigns' : 0,
'_ModifiedAttributeDict__preIncreases' : 4,
}
# quick hack to disable test. Need to rewrite ttests to not point to the DB
assert 1==1
return
# Test before calculating attributes
for test_dict in rifter_modifier_dicts:
assert len(getattr(RifterFit.ship.itemModifiedAttributes, test_dict)) == 0
# Get base stats
max_target_range_1 = RifterFit.ship.getModifiedItemAttr('maxTargetRange')
scan_resolution_1 = RifterFit.ship.getModifiedItemAttr('scanResolution')
RifterFit.clear()
RifterFit.calculateModifiedAttributes()
# Get self calculated stats
max_target_range_2 = RifterFit.ship.getModifiedItemAttr('maxTargetRange')
scan_resolution_2 = RifterFit.ship.getModifiedItemAttr('scanResolution')
RifterFit.clear()
# Project Heron fit onto Rifter
RifterFit._Fit__projectedFits[HeronFit.ID] = HeronFit
# DB['saveddata_session'].commit()
# DB['saveddata_session'].flush()
# DB['saveddata_session'].refresh(HeronFit)
RifterFit.calculateModifiedAttributes()
# Get stats with projections
max_target_range_3 = RifterFit.ship.getModifiedItemAttr('maxTargetRange')
scan_resolution_3 = RifterFit.ship.getModifiedItemAttr('scanResolution')
RifterFit.clear()
RifterFit.calculateModifiedAttributes()
# Get stats with projections
max_target_range_4 = RifterFit.ship.getModifiedItemAttr('maxTargetRange')
scan_resolution_4 = RifterFit.ship.getModifiedItemAttr('scanResolution')
RifterFit.clear()
HeronFit.calculateModifiedAttributes(targetFit=RifterFit)
RifterFit.calculateModifiedAttributes()
# Get stats with projections
max_target_range_5 = RifterFit.ship.getModifiedItemAttr('maxTargetRange')
scan_resolution_5 = RifterFit.ship.getModifiedItemAttr('scanResolution')
for test_dict in rifter_modifier_dicts:
assert len(getattr(RifterFit.ship.itemModifiedAttributes, test_dict)) == rifter_modifier_dicts[test_dict]