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SatisfactoryLP.py
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SatisfactoryLP.py
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#!/usr/bin/env python
# coding: utf-8
import scipy.optimize
import json
import numpy as np
import re
import sys
import math
import argparse
from collections import defaultdict
from pprint import pprint
def float_list(s):
return [float(x) for x in s.split(",")] if s else []
parser = argparse.ArgumentParser()
parser.add_argument("--transport-power-cost", type=float, default=50.0,
help="added power cost for transport per conveyor/pipeline of mined resource")
parser.add_argument("--drone-battery-cost", type=float, default=0.5,
help="added battery cost for drone transport per conveyor/pipeline of mined resource")
parser.add_argument("--machine-penalty", type=float, default=2000.0,
help="objective penalty per machine built")
parser.add_argument("--conveyor-penalty", type=float, default=0.0,
help="objective penalty per conveyor belt needed")
parser.add_argument("--pipeline-penalty", type=float, default=0.0,
help="objective penalty per pipeline needed")
parser.add_argument("--power-shard-penalty-ratio", type=float, default=0.6,
help="objective penalty per power shard used, specified as ratio of machine penalty")
parser.add_argument("--extra-miner-clocks", type=float_list, default=[],
help="extra clock choices for miners, specified as decimals")
parser.add_argument("--extra-manufacturer-clocks", type=float_list, default=[0.25, 0.5, 0.75],
help="extra clock choices for manufacturers, specified as decimals")
parser.add_argument("--allow-waste", action="store_true",
help="allow accumulation of nuclear waste and other unsinkable items")
parser.add_argument("--show-unused", action="store_true",
help="show unused LP columns (coeff 0) in the optimization result")
parser.add_argument("--xlsx-report", type=str, default="Report.xlsx",
help="path to xlsx report output")
parser.add_argument("--xlsx-sheet-suffix", type=str, default="",
help="suffix to add to xlsx sheet names")
args = parser.parse_args()
### Constants ###
# Common
STACK_SIZES = {
"SS_HUGE": 500,
"SS_BIG": 200,
"SS_MEDIUM": 100,
"SS_SMALL": 50,
"SS_ONE": 1,
"SS_FLUID": 50000,
}
MACHINE_POWER_SHARD_LIMIT = 3
EPSILON = 1e-9
# Logistics
CONVEYOR_BELT_CLASS = "Build_ConveyorBeltMk5_C"
PIPELINE_CLASS = "Build_PipelineMK2_C"
# Resource extraction
MINER_CLASS = "Build_MinerMk3_C"
OIL_EXTRACTOR_CLASS = "Build_OilPump_C"
WATER_EXTRACTOR_CLASS = "Build_WaterPump_C"
RESOURCE_WELL_EXTRACTOR_CLASS = "Build_FrackingExtractor_C"
RESOURCE_WELL_PRESSURIZER_CLASS = "Build_FrackingSmasher_C"
# Sink
SINK_CLASS = "Build_ResourceSink_C"
# Water
WATER_CLASS = "Desc_Water_C"
# Nuclear power
NUCLEAR_WASTE_MAPPINGS = {
"Desc_NuclearFuelRod_C": "Desc_NuclearWaste_C",
"Desc_PlutoniumFuelRod_C": "Desc_PlutoniumWaste_C",
}
# Geothermal power
GEOTHERMAL_GENERATOR_CLASS = "Build_GeneratorGeoThermal_C"
GEYSER_CLASS = "Desc_Geyser_C"
# Resource map
PURITY_MULTIPLIERS = {
"impure": 0.5,
"normal": 1.0,
"pure": 2.0,
}
POWER_SLUG_SHARDS = {
"greenSlugs": 1,
"yellowSlugs": 2,
"purpleSlugs": 5,
}
RESOURCE_MAPPINGS = {
"Desc_LiquidOilWell_C": "Desc_LiquidOil_C",
"Desc_SAM_C": None, # exclude
}
# Miscellaneous
BIOMASS_GENERATOR_CLASS = "Build_GeneratorBiomass_C"
BATTERY_CLASS = "Desc_Battery_C"
ADDITIONAL_ITEMS = {
"Desc_PlutoniumWaste_C": {
"class": "Desc_PlutoniumWaste_C",
"display_name": "Plutonium Waste",
"form": "RF_SOLID",
"points": 0,
"stack_size": STACK_SIZES["SS_HUGE"],
"energy": 0.0,
},
}
ADDITIONAL_DISPLAY_NAMES = {
GEYSER_CLASS: "Geyser",
}
docs_path = r"Docs.json"
map_info_path = r"MapInfo.json"
with open(docs_path, "r", encoding="utf-16") as f:
docs_raw = json.load(f)
class_entries = {}
class_types = {}
for fg_entry in docs_raw:
class_type = re.sub(r"Class'/Script/FactoryGame.(\w+)'", r"\1", fg_entry["NativeClass"])
class_type_list = []
for class_entry in fg_entry["Classes"]:
class_name = class_entry["ClassName"]
if class_name in class_entries:
print(f"WARNING: ignoring duplicate class {class_name}")
else:
class_entries[class_name] = class_entry
class_type_list.append(class_entry)
class_types[class_type] = class_type_list
### Parsing helpers ###
def parse_paren_list(s):
if not s:
return None
assert(s.startswith("(") and s.endswith(")"))
s = s[1:-1]
if not s:
return []
else:
return s.split(",")
def find_class_name(s):
m = re.search(r"\.\w+", s)
if m is None:
raise ValueError(f"could not find class name in: {s}")
return m[0][1:]
def parse_class_list(s):
l = parse_paren_list(s)
if l is None:
return l
return [find_class_name(x) for x in l]
def find_item_amounts(s):
for m in re.finditer(r"\(ItemClass=([^,]+),Amount=(\d+)\)", s):
yield (find_class_name(m[1]), int(m[2]))
### Misc constants ###
CONVEYOR_BELT_LIMIT = 0.5 * float(class_entries[CONVEYOR_BELT_CLASS]["mSpeed"])
PIPELINE_LIMIT = 60000.0 * float(class_entries[PIPELINE_CLASS]["mFlowLimit"])
SINK_POWER_CONSUMPTION = float(class_entries[SINK_CLASS]["mPowerConsumption"])
print(f"CONVEYOR_BELT_LIMIT: {CONVEYOR_BELT_LIMIT}")
print(f"PIPELINE_LIMIT: {PIPELINE_LIMIT}")
print(f"SINK_POWER_CONSUMPTION: {SINK_POWER_CONSUMPTION}")
### Miners ###
def parse_miner(entry):
if entry["ClassName"] == RESOURCE_WELL_PRESSURIZER_CLASS:
extractor = class_entries[RESOURCE_WELL_EXTRACTOR_CLASS]
else:
extractor = entry
return {
"class": entry["ClassName"],
"display_name": entry["mDisplayName"],
"power_consumption": float(entry["mPowerConsumption"]),
"power_consumption_exponent": float(entry["mPowerConsumptionExponent"]),
"min_clock": float(entry["mMinPotential"]),
"max_clock_base": float(entry["mMaxPotential"]),
"max_clock_per_power_shard": float(entry["mMaxPotentialIncreasePerCrystal"]),
"rate": 60.0 / float(extractor["mExtractCycleTime"]) * float(extractor["mItemsPerCycle"]),
"only_allow_certain_resources": (extractor["mOnlyAllowCertainResources"] == "True"),
"allowed_resource_forms": parse_paren_list(extractor["mAllowedResourceForms"]),
"allowed_resources": parse_class_list(extractor["mAllowedResources"]),
}
miners = {}
for name in (MINER_CLASS, OIL_EXTRACTOR_CLASS, WATER_EXTRACTOR_CLASS, RESOURCE_WELL_PRESSURIZER_CLASS):
miners[name] = parse_miner(class_entries[name])
# pprint(miners)
### Manufacturers ###
def parse_manufacturer(entry):
return {
"class": entry["ClassName"],
"display_name": entry["mDisplayName"],
"power_consumption": float(entry["mPowerConsumption"]),
"power_consumption_exponent": float(entry["mPowerConsumptionExponent"]),
"min_clock": float(entry["mMinPotential"]),
"max_clock_base": float(entry["mMaxPotential"]),
"max_clock_per_power_shard": float(entry["mMaxPotentialIncreasePerCrystal"]),
}
manufacturers = {}
for entry in class_types["FGBuildableManufacturer"]:
manufacturer = parse_manufacturer(entry)
manufacturer["is_variable_power"] = False
manufacturers[entry["ClassName"]] = manufacturer
for entry in class_types["FGBuildableManufacturerVariablePower"]:
manufacturer = parse_manufacturer(entry)
manufacturer["is_variable_power"] = True
manufacturers[entry["ClassName"]] = manufacturer
# pprint(manufacturers)
### Recipes ###
def parse_recipe(entry):
recipe_manufacturer = None
for manufacturer in parse_class_list(entry["mProducedIn"]) or []:
if manufacturer in manufacturers:
recipe_manufacturer = manufacturer
break
# we are only considering automatable recipes
if recipe_manufacturer is None:
return None
rate = 60.0 / float(entry["mManufactoringDuration"])
def item_rates(key):
return [(item, rate * amount) for (item, amount) in find_item_amounts(entry[key])]
vpc_constant = float(entry["mVariablePowerConsumptionConstant"])
vpc_factor = float(entry["mVariablePowerConsumptionFactor"])
return {
"class": entry["ClassName"],
"display_name": entry["mDisplayName"],
"manufacturer": recipe_manufacturer,
"inputs": item_rates("mIngredients"),
"outputs": item_rates("mProduct"),
"variable_power_consumption": vpc_constant + 0.5 * vpc_factor,
}
recipes = {}
for entry in class_types["FGRecipe"]:
recipe = parse_recipe(entry)
if recipe is not None:
recipes[entry["ClassName"]] = recipe
# pprint(recipes)
### Items ###
def parse_item(entry):
points = int(entry["mResourceSinkPoints"])
return {
"display_name": entry["mDisplayName"],
"form": entry["mForm"],
"points": int(entry["mResourceSinkPoints"]),
"stack_size": STACK_SIZES[entry["mStackSize"]],
"energy": float(entry["mEnergyValue"]),
}
items = {}
# any items not contained in Docs.json
items.update(ADDITIONAL_ITEMS)
for class_type in [
"FGItemDescriptor",
"FGItemDescriptorBiomass",
"FGItemDescriptorNuclearFuel",
"FGResourceDescriptor",
"FGEquipmentDescriptor",
"FGConsumableDescriptor",
]:
for entry in class_types[class_type]:
item = parse_item(entry)
if class_type == "FGItemDescriptorNuclearFuel":
item["nuclear_waste"] = NUCLEAR_WASTE_MAPPINGS[entry["ClassName"]]
item["nuclear_waste_amount"] = float(entry["mAmountOfWaste"])
items[entry["ClassName"]] = item
# pprint(items)
### Generators ###
generators = {}
def parse_generator(entry):
power_production = float(entry["mPowerProduction"])
return {
"display_name": entry["mDisplayName"],
"fuel_classes": parse_class_list(entry["mDefaultFuelClasses"]),
"power_production": power_production,
"power_production_exponent": float(entry["mPowerProductionExponent"]),
"requires_supplemental": (entry["mRequiresSupplementalResource"] == "True"),
"supplemental_to_power_ratio": float(entry["mSupplementalToPowerRatio"]),
}
def parse_geothermal_generator(entry):
# unclear why mVariablePowerProductionConstant=0 in the json;
# it's set to 100.0f in the header, which we will hardcode here
return {
"display_name": entry["mDisplayName"],
"power_production": 100.0 + 0.5 * float(entry["mVariablePowerProductionFactor"]),
}
# coal and fuel generators
for entry in class_types["FGBuildableGeneratorFuel"]:
# exclude biomass generator
if entry["ClassName"] == BIOMASS_GENERATOR_CLASS:
continue
generators[entry["ClassName"]] = parse_generator(entry)
# nuclear power plant
for entry in class_types["FGBuildableGeneratorNuclear"]:
generators[entry["ClassName"]] = parse_generator(entry)
# geothermal generator (special case)
geothermal_generator = parse_geothermal_generator(class_entries[GEOTHERMAL_GENERATOR_CLASS])
# pprint(generators)
### Resources ###
with open(map_info_path, "r") as f:
map_info_raw = json.load(f)
map_info = {}
for tab in map_info_raw["options"]:
if "tabId" in tab:
map_info[tab["tabId"]] = tab["options"]
TOTAL_POWER_SHARDS = 0
for slug_type in map_info["power_slugs"][0]["options"]:
TOTAL_POWER_SHARDS += POWER_SLUG_SHARDS[slug_type["layerId"]] * len(slug_type["markers"])
print(f"TOTAL_POWER_SHARDS: {TOTAL_POWER_SHARDS}")
resources = {}
geysers = {}
def parse_and_add_node_type(node_type):
if "type" not in node_type:
return
item = node_type["type"]
if item in RESOURCE_MAPPINGS:
item = RESOURCE_MAPPINGS[item]
if item is None:
return
output = geysers if item == GEYSER_CLASS else resources
for node_purity in node_type["options"]:
purity = node_purity["purity"]
nodes = node_purity["markers"]
if not nodes:
continue
sample_node = nodes[0]
if "core" in sample_node:
# resource well satellite nodes, map them to cores
for node in nodes:
subtype = find_class_name(node["core"])
resource_id = f"{item}|{subtype}"
if resource_id not in output:
output[resource_id] = {
"resource_id": resource_id,
"item": item,
"subtype": subtype,
"multiplier": 0.0,
"count": 1,
"is_limited": True,
"is_resource_well": True,
"num_satellites": 0,
}
output[resource_id]["multiplier"] += PURITY_MULTIPLIERS[purity]
output[resource_id]["num_satellites"] += 1
else:
# normal nodes, add directly
subtype = purity
resource_id = f"{item}|{subtype}"
assert(resource_id not in output)
output[resource_id] = {
"resource_id": resource_id,
"item": item,
"subtype": subtype,
"multiplier": PURITY_MULTIPLIERS[purity],
"count": len(nodes),
"is_limited": True,
"is_resource_well": False,
}
for node_type in map_info["resource_nodes"]:
parse_and_add_node_type(node_type)
for node_type in map_info["resource_wells"]:
parse_and_add_node_type(node_type)
resources[WATER_CLASS] = {
"resource_id": f"{WATER_CLASS}:extractor",
"item": WATER_CLASS,
"subtype": "extractor",
"multiplier": 1,
"is_limited": False,
"is_resource_well": False,
}
# pprint(resources)
# pprint(geysers)
### LP setup ###
class LPColumn(dict):
def __init__(self, *args, display_info=None, **kwargs):
super().__init__(*args, **kwargs)
self.display_info = display_info
lp_columns = {}
lp_equalities = {}
lp_lower_bounds = {}
def get_power_consumption(machine, clock=1.0, recipe=None):
power_consumption = machine["power_consumption"]
if recipe is not None and machine.get("is_variable_power", False):
power_consumption += recipe["variable_power_consumption"]
return power_consumption * (clock ** machine["power_consumption_exponent"])
def get_miner_for_resource(resource):
item_class = resource["item"]
item = items[item_class]
candidates = []
for miner_class, miner in miners.items():
if ((resource["is_resource_well"]) == (miner_class == RESOURCE_WELL_PRESSURIZER_CLASS)
and item["form"] in miner["allowed_resource_forms"]
and (not miner["only_allow_certain_resources"] or item_class in miner["allowed_resources"])):
candidates.append(miner_class)
if not candidates:
raise RuntimeError(f"could not find miner for resource {item_class}")
elif len(candidates) > 1:
raise RuntimeError(f"more than one miner for resource {item_class}: {candidates}")
return candidates[0]
def get_form_conveyance_limit(form):
if form == "RF_SOLID":
return CONVEYOR_BELT_LIMIT
elif form == "RF_LIQUID" or form == "RF_GAS":
return PIPELINE_LIMIT
else:
assert(False)
def get_max_overclock(machine):
return machine["max_clock_base"] + MACHINE_POWER_SHARD_LIMIT * machine["max_clock_per_power_shard"]
def get_conveyance_limit_clock(item, rate):
conveyance_limit = get_form_conveyance_limit(item["form"])
return math.floor(1000000 * conveyance_limit / rate) / 1000000
def get_max_miner_clock(miner, resource, rate):
max_overclock = get_max_overclock(miner)
if resource["is_resource_well"]:
return max_overclock
item_class = resource["item"]
item = items[item_class]
return min(max_overclock, get_conveyance_limit_clock(item, rate))
def get_max_manufacturer_clock(manufacturer, recipe):
max_clock = get_max_overclock(manufacturer)
for (item_class, rate) in recipe["inputs"]:
max_clock = min(max_clock, get_conveyance_limit_clock(items[item_class], rate))
for (item_class, rate) in recipe["outputs"]:
max_clock = min(max_clock, get_conveyance_limit_clock(items[item_class], rate))
return max_clock
def get_power_shards_needed(machine, clock):
return max(0, math.ceil((clock - machine["max_clock_base"]) / machine["max_clock_per_power_shard"]))
def get_item_display_name(item_class):
if item_class in items:
return items[item_class]["display_name"]
else:
return ADDITIONAL_DISPLAY_NAMES[item_class]
def add_lp_column(column, type_, name, display_name=None, machine_name=None, subtype=None, clock=None):
tokens = [type_, name]
if subtype is not None:
tokens.append(subtype)
if clock is not None:
clock_percent = 100.0 * clock
tokens.append(f"{clock_percent}")
column_id = "|".join(tokens)
display_info = {
"type": type_,
"display_name": display_name or name,
"machine_name": machine_name,
"subtype": subtype,
"clock": clock,
}
lp_columns[column_id] = LPColumn(column, display_info=display_info)
for resource_id, resource in resources.items():
item_class = resource["item"]
item = items[item_class]
miner_class = get_miner_for_resource(resource)
miner = miners[miner_class]
rate = miner["rate"] * resource["multiplier"]
min_clock = miner["min_clock"]
max_clock_base = miner["max_clock_base"]
max_clock = get_max_miner_clock(miner, resource, rate)
resource_var = f"resource|{resource_id}"
item_var = f"item|{item_class}"
clock_choices = {max_clock_base, max_clock}
for clock in args.extra_miner_clocks:
clock = min(max_clock, max(min_clock, clock))
clock_choices.add(clock)
for clock in sorted(clock_choices):
column = {
item_var: clock * rate,
"power_consumption": get_power_consumption(miner, clock=clock),
"machines": 1 + (resource["num_satellites"] if resource["is_resource_well"] else 0),
}
if resource["is_limited"]:
column[resource_var] = -1
power_shards = get_power_shards_needed(miner, clock)
if power_shards > 0:
column["power_shard_usage"] = power_shards
add_lp_column(
column,
type_="miner",
name=resource_id,
display_name=item["display_name"],
machine_name=miner["display_name"],
subtype=resource["subtype"],
clock=clock,
)
if resource["is_limited"]:
lp_lower_bounds[resource_var] = -resource["count"]
lp_equalities[item_var] = 0.0
for recipe_class, recipe in recipes.items():
manufacturer_class = recipe["manufacturer"]
manufacturer = manufacturers[manufacturer_class]
min_clock = manufacturer["min_clock"]
max_clock_base = manufacturer["max_clock_base"]
max_clock = get_max_manufacturer_clock(manufacturer, recipe)
# let's not allow manufacturer OC by default, but it can be specified via option
clock_choices = {min_clock, max_clock_base}
for clock in args.extra_manufacturer_clocks:
clock = min(max_clock, max(min_clock, clock))
clock_choices.add(clock)
for clock in sorted(clock_choices):
column = {
"power_consumption": get_power_consumption(manufacturer, clock=clock, recipe=recipe),
"machines": 1,
}
for (item_class, rate) in recipe["inputs"]:
item_var = f"item|{item_class}"
column[item_var] = column.get(item_var, 0.0) - clock * rate
lp_equalities[item_var] = 0.0
for (item_class, rate) in recipe["outputs"]:
item_var = f"item|{item_class}"
column[item_var] = column.get(item_var, 0.0) + clock * rate
lp_equalities[item_var] = 0.0
power_shards = get_power_shards_needed(manufacturer, clock)
if power_shards > 0:
column["power_shard_usage"] = power_shards
add_lp_column(
column,
type_="manufacturer",
name=recipe_class,
display_name=recipe["display_name"],
machine_name=manufacturer["display_name"],
clock=clock,
)
for item_class, item in items.items():
points = item["points"]
item_var = f"item|{item_class}"
if not (item["form"] == "RF_SOLID" and points > 0):
if args.allow_waste:
add_lp_column(
{item_var: -1},
type_="waste",
name=item_class,
display_name=item["display_name"],
)
continue
column = {
item_var: -1,
"points": points,
"power_consumption": SINK_POWER_CONSUMPTION / CONVEYOR_BELT_LIMIT,
"machines": 1 / CONVEYOR_BELT_LIMIT,
}
add_lp_column(
column,
type_="sink",
name=item_class,
display_name=item["display_name"],
)
lp_equalities[item_var] = 0.0
for generator_class, generator in generators.items():
power_production = generator["power_production"]
for fuel_class in generator["fuel_classes"]:
fuel = items[fuel_class]
fuel_rate = 60.0 * power_production / fuel["energy"]
fuel_var = f"item|{fuel_class}"
column = {
fuel_var: -fuel_rate,
"power_production": power_production,
"machines": 1,
}
if generator["requires_supplemental"]:
supplemental_class = WATER_CLASS
supplemental_var = f"item|{supplemental_class}"
supplemental_rate = 60.0 * power_production * generator["supplemental_to_power_ratio"]
column[supplemental_var] = -supplemental_rate
lp_equalities[supplemental_var] = 0.0
if fuel_class in NUCLEAR_WASTE_MAPPINGS:
waste_class = NUCLEAR_WASTE_MAPPINGS[fuel_class]
waste_var = f"item|{waste_class}"
column[waste_var] = fuel_rate * fuel["nuclear_waste_amount"]
lp_equalities[waste_var] = 0.0
add_lp_column(
column,
type_="generator",
name=fuel_class,
display_name=fuel["display_name"],
machine_name=generator["display_name"],
clock=1,
)
for resource_id, resource in geysers.items():
resource_var = f"resource|{resource_id}"
column = {
resource_var: -1,
"power_production": geothermal_generator["power_production"] * resource["multiplier"],
"machines": 1,
}
add_lp_column(
column,
type_="generator",
name=resource_id,
display_name=get_item_display_name(GEYSER_CLASS),
machine_name=geothermal_generator["display_name"],
subtype=resource["subtype"],
)
lp_lower_bounds[resource_var] = -resource["count"]
for column_id, column in lp_columns.items():
to_add = defaultdict(float)
for variable, coeff in column.items():
if abs(coeff) < EPSILON:
print(f"WARNING: zero or near-zero coeff: column_id={column_id} variable={variable} coeff={coeff}")
if variable.startswith("item|") and coeff > 0:
item_class = variable[5:]
if item_class not in items:
print(f"WARNING: item not found in items dict: {item_class}")
continue
item = items[item_class]
form = item["form"]
conveyance_limit = get_form_conveyance_limit(form)
conveyance = coeff / conveyance_limit
if column_id.startswith("miner|"):
to_add["transport_power_cost"] += args.transport_power_cost * conveyance
to_add["drone_battery_cost"] += args.drone_battery_cost * conveyance
if form == "RF_SOLID":
to_add["conveyors"] += conveyance
else:
to_add["pipelines"] += conveyance
for variable, coeff in to_add.items():
if coeff != 0.0:
column[variable] = column.get(variable, 0.0) + coeff
for objective in ["points", "machines", "conveyors", "pipelines"]:
column = {
objective: -1,
}
add_lp_column(
column,
type_="objective",
name=objective,
)
lp_equalities[objective] = 0.0
for extra_cost, cost_variable, cost_coeff in [
("transport_power_cost", "power_consumption", 1.0),
("drone_battery_cost", f"item|{BATTERY_CLASS}", -1.0),
]:
column = {
extra_cost: -1,
cost_variable: cost_coeff,
}
add_lp_column(
column,
type_="extra_cost",
name=extra_cost,
)
lp_equalities[extra_cost] = 0.0
column = {
"power_consumption": -1,
"power_production": -1,
}
add_lp_column(
column,
type_="power",
name="usage",
)
lp_equalities["power_consumption"] = 0.0
lp_lower_bounds["power_production"] = 0.0
column = {
"power_shard_usage": -1,
"power_shards": -1,
}
add_lp_column(
column,
type_="objective",
name="power_shards",
)
lp_equalities["power_shard_usage"] = 0.0
lp_lower_bounds["power_shards"] = -TOTAL_POWER_SHARDS
# pprint(lp_columns)
# pprint(lp_equalities)
# pprint(lp_lower_bounds)
def get_all_variables():
variables = set()
for column_id, column in lp_columns.items():
for variable, coeff in column.items():
variables.add(variable)
for variable in variables:
if variable not in lp_equalities and variable not in lp_lower_bounds:
print(f"WARNING: no constraint for variable: {variable}")
for variable in lp_equalities.keys():
if variable not in variables:
print(f"WARNING: equality constraint with unknown variable: {variable}")
for variable in lp_lower_bounds.keys():
if variable not in variables:
print(f"WARNING: lower bound constraint with unknown variable: {variable}")
return variables
variables = get_all_variables()
# pprint(variables)
### Pruning ###
reachable_items = set()
while True:
any_added = False
for column_id, column in lp_columns.items():
eligible = True
to_add = set()
for variable, coeff in column.items():
if variable.startswith("item|") and variable not in reachable_items:
if coeff > 0:
to_add.add(variable)
elif coeff < 0:
eligible = False
break
if eligible and to_add:
any_added = True
reachable_items |= to_add
if not any_added:
break
unreachable_items = set(v for v in variables if v.startswith("item|")) - reachable_items
print("pruning unreachable items:")
pprint(unreachable_items)
columns_to_prune = list()
for column_id, column in lp_columns.items():
for variable, coeff in column.items():
if variable in unreachable_items and coeff < 0:
columns_to_prune.append(column_id)
break
for column_id in columns_to_prune:
# pprint(lp_columns[column_id])
del lp_columns[column_id]
for item_var in unreachable_items:
if item_var in lp_equalities:
del lp_equalities[item_var]
variables = get_all_variables()
# pprint(variables)
# pprint(lp_columns)
# pprint(lp_equalities)
# pprint(lp_lower_bounds)
### LP run ###
def to_index_map(seq):
return {value: index for index, value in enumerate(seq)}
def from_index_map(d):
result = [None] * len(d)
for value, index in d.items():
result[index] = value
return result
# order is for report display, but we might as well sort it here
column_type_order = to_index_map(["objective", "power", "extra_cost", "sink", "waste", "manufacturer", "miner", "generator"])
column_subtype_order = to_index_map(["impure", "normal", "pure"])
objective_order = to_index_map(["points", "machines", "conveyors", "pipelines", "power_shards"])
extra_cost_order = to_index_map(["transport_power_cost", "drone_battery_cost"])
def column_order_key(arg):
column_id, column = arg
info = column.display_info
type_ = info["type"]
if type_ in column_type_order:
type_key = (0, column_type_order[type_])
else:
type_key = (1, type_)
name = info["display_name"]
if type_ == "objective":
name_key = objective_order[name]
elif type_ == "extra_cost":
name_key = extra_cost_order[name]
else:
name_key = name
subtype = info["subtype"]
if subtype in column_subtype_order:
subtype_key = (0, column_subtype_order[subtype])
else:
subtype_key = (1, subtype)
return (type_key, name_key, subtype_key, info["clock"], column_id)
sorted_columns = sorted(lp_columns.items(), key=column_order_key)
indices_eq = to_index_map(sorted(lp_equalities.keys()))
indices_lb = to_index_map(sorted(lp_lower_bounds.keys()))
# pprint(indices_eq)
# pprint(indices_lb)
lp_c = np.zeros(len(lp_columns), dtype=np.double)
lp_A_eq = np.zeros((len(lp_equalities), len(lp_columns)), dtype=np.double)
lp_b_eq = np.zeros(len(lp_equalities), dtype=np.double)
lp_A_lb = np.zeros((len(lp_lower_bounds), len(lp_columns)), dtype=np.double)
lp_b_lb = np.zeros(len(lp_lower_bounds), dtype=np.double)
objective_weights = {f"objective|{obj}": weight for (obj, weight) in {
"points": 1,
"machines": -args.machine_penalty,
"conveyors": -args.conveyor_penalty,
"pipelines": -args.pipeline_penalty,
"power_shards": -args.power_shard_penalty_ratio * args.machine_penalty,
}.items()}
for column_index, (column_id, column) in enumerate(sorted_columns):
if column_id in objective_weights:
lp_c[column_index] = objective_weights[column_id]
for variable, coeff in column.items():
if variable in lp_equalities:
lp_A_eq[indices_eq[variable], column_index] = coeff
else:
lp_A_lb[indices_lb[variable], column_index] = coeff
for variable, rhs in lp_equalities.items():
lp_b_eq[indices_eq[variable]] = rhs
for variable, rhs in lp_lower_bounds.items():
lp_b_lb[indices_lb[variable]] = rhs
print("running LP")
lp_result = scipy.optimize.linprog(-lp_c, A_ub=-lp_A_lb, b_ub=-lp_b_lb, A_eq=lp_A_eq, b_eq=lp_b_eq, method="highs")
if lp_result.status != 0:
print("ERROR: LP did not terminate successfully")
pprint(lp_result)
sys.exit(1)
pprint(lp_result)
### Display formatting ###
def format_subtype(subtype):
if subtype is None or subtype == "extractor":
return None
return re.sub(r"^BP_FrackingCore_?", "#", subtype).capitalize()
def get_column_desc(column):
info = column.display_info
tokens = [info["machine_name"] or info["type"], info["display_name"]]
subtype = format_subtype(info["subtype"])
if subtype is not None:
tokens.append(subtype)
if info["clock"] is not None:
clock_percent = 100.0 * info["clock"]
tokens.append(f"{clock_percent}%")
return "|".join(tokens)
column_results = [
(column_id, column, lp_result.x[column_index])
for column_index, (column_id, column) in enumerate(sorted_columns)
]
if not args.show_unused:
column_results = list(filter(lambda x: abs(x[2]) > EPSILON, column_results))
variable_breakdowns = {variable: {"production": [], "consumption": []} for variable in variables}
for column_id, column, column_coeff in column_results:
column_desc = get_column_desc(column)
print(f"{column_desc} = {column_coeff}")
for variable, coeff in column.items():
rate = column_coeff * coeff
source = {
"desc": column_desc,
"count": column_coeff,