/* Planeteer: Give trade route advice for Planets: The Exploration of Space * Copyright (C) 2011 Scott Worley * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU Affero General Public License as * published by the Free Software Foundation, either version 3 of the * License, or (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU Affero General Public License for more details. * * You should have received a copy of the GNU Affero General Public License * along with this program. If not, see . */ package main import "flag" import "fmt" import "json" import "os" import "strings" var start = flag.String("start", "", "The planet to start at") var end = flag.String("end", "", "A comma-separated list of acceptable ending planets.") var planet_data_file = flag.String("planet_data_file", "planet-data", "The file to read planet data from") var fuel = flag.Int("fuel", 16, "Reactor units") var hold = flag.Int("hold", 300, "Size of your cargo hold") var start_edens = flag.Int("start_edens", 0, "How many Eden Warp Units are you starting with?") var end_edens = flag.Int("end_edens", 0, "How many Eden Warp Units would you like to keep (not use)?") var cloak = flag.Bool("cloak", false, "Make sure to end with a Device of Cloaking") var drones = flag.Int("drones", 0, "Buy this many Fighter Drones") var batteries = flag.Int("batteries", 0, "Buy this many Shield Batterys") var visit_string = flag.String("visit", "", "A comma-separated list of planets to make sure to visit") func visit() []string { return strings.Split(*visit_string, ",") } type Commodity struct { BasePrice int CanSell bool Limit int } type Planet struct { BeaconOn bool /* Use relative prices rather than absolute prices because you can get relative prices without traveling to each planet. */ RelativePrices map[string]int } type planet_data struct { Commodities map[string]Commodity Planets map[string]Planet p2i, c2i map[string]int // Generated; not read from file i2p, i2c []string // Generated; not read from file } func ReadData() (data planet_data) { f, err := os.Open(*planet_data_file) if err != nil { panic(err) } defer f.Close() err = json.NewDecoder(f).Decode(&data) if err != nil { panic(err) } return } /* This program operates by filling in a state table representing the best * possible trips you could make; the ones that makes you the most money. * This is feasible because we don't look at all the possible trips. * We define a list of things that are germane to this game and then only * consider the best outcome in each possible game state. * * Each cell in the table represents a state in the game. In each cell, * we track two things: 1. the most money you could possibly have while in * that state and 2. one possible way to get into that state with that * amount of money. * * A basic analysis can be done with a two-dimensional table: location and * fuel. planeteer-1.0 used this two-dimensional table. This version * adds features mostly by adding dimensions to this table. * * Note that the sizes of each dimension are data driven. Many dimensions * collapse to one possible value (ie, disappear) if the corresponding * feature is not enabled. * * The order of the dimensions in the list of constants below determines * their layout in RAM. The cargo-based 'dimensions' are not completely * independent -- some combinations are illegal and not used. They are * handled as three dimensions rather than one for simplicity. Placing * these dimensions first causes the unused cells in the table to be * grouped together in large blocks. This keeps them from polluting * cache lines, and if they are large enough, prevent the memory manager * from allocating pages for these areas at all. */ // The official list of dimensions: const ( // Name Num Size Description Edens = iota // 1 3 # of Eden warp units (0 - 2 typically) Cloaks // 2 2 # of Devices of Cloaking (0 or 1) UnusedCargo // 3 4 # of unused cargo spaces (0 - 3 typically) Fuel // 4 17 Reactor power left (0 - 16) Location // 5 26 Location (which planet) Hold // 6 15 Cargo bay contents (a *Commodity or nil) NeedFighters // 7 2 Errand: Buy fighter drones (needed or not) NeedShields // 8 2 Errand: Buy shield batteries (needed or not) Visit // 9 2**N Visit: Stop by these N planets in the route NumDimensions ) func bint(b bool) int { if b { return 1 } return 0 } func DimensionSizes(data planet_data) []int { eden_capacity := data.Commodities["Eden Warp Units"].Limit cloak_capacity := bint(*cloak) dims := make([]int, NumDimensions) dims[Edens] = eden_capacity + 1 dims[Cloaks] = cloak_capacity + 1 dims[UnusedCargo] = eden_capacity + cloak_capacity + 1 dims[Fuel] = *fuel + 1 dims[Location] = len(data.Planets) dims[Hold] = len(data.Commodities) dims[NeedFighters] = bint(*drones > 0) + 1 dims[NeedShields] = bint(*batteries > 0) + 1 dims[Visit] = 1 << uint(len(visit())) // Remind myself to add a line above when adding new dimensions for i, dim := range dims { if dim < 1 { panic(i) } } return dims } func StateTableSize(dims []int) int { sum := 0 for _, size := range dims { sum += size } return sum } type State struct { funds, from int } func EncodeIndex(dims, addr []int) int { index := addr[0] for i := 1; i < len(dims); i++ { index = index*dims[i] + addr[i] } return index } func DecodeIndex(dims []int, index int) []int { addr := make([]int, len(dims)) for i := len(dims) - 1; i > 0; i-- { addr[i] = index % dims[i] index /= dims[i] } addr[0] = index return addr } func FillStateCell(data planet_data, dims []int, table []State, addr []int) { } func FillStateTable2(data planet_data, dims []int, table []State, fuel_remaining, edens_remaining int, planet string, barrier chan<- bool) { /* The dimension nesting order up to this point is important. * Beyond this point, it's not important. * * It is very important when iterating through the Hold dimension * to visit the null commodity (empty hold) first. Visiting the * null commodity represents selling. Visiting it first gets the * action order correct: arrive, sell, buy, leave. Visiting the * null commodity after another commodity would evaluate the action * sequence: arrive, buy, sell, leave. This is a useless action * sequence. Because we visit the null commodity first, we do not * consider these action sequences. */ eden_capacity := data.Commodities["Eden Warp Units"].Limit addr := make([]int, len(dims)) addr[Edens] = edens_remaining addr[Fuel] = fuel_remaining addr[Location] = data.p2i[planet] for addr[Hold] = 0; addr[Hold] < dims[Hold]; addr[Hold]++ { for addr[Cloaks] = 0; addr[Cloaks] < dims[Cloaks]; addr[Cloaks]++ { for addr[UnusedCargo] = 0; addr[UnusedCargo] < dims[UnusedCargo]; addr[UnusedCargo]++ { if addr[Edens]+addr[Cloaks]+addr[UnusedCargo] <= eden_capacity+1 { for addr[NeedFighters] = 0; addr[NeedFighters] < dims[NeedFighters]; addr[NeedFighters]++ { for addr[NeedShields] = 0; addr[NeedShields] < dims[NeedShields]; addr[NeedShields]++ { for addr[Visit] = 0; addr[Visit] < dims[Visit]; addr[Visit]++ { FillStateCell(data, dims, table, addr) } } } } } } } barrier <- true } /* Filling the state table is a set of nested for loops NumDimensions deep. * We split this into two procedures: 1 and 2. #1 is the outer, slowest- * changing indexes. #1 fires off many calls to #2 that run in parallel. * The order of the nesting of the dimensions, the order of iteration within * each dimension, and where the 1 / 2 split is placed are carefully chosen * to make this arrangement safe. * * Outermost two layers: Go from high-energy states (lots of fuel, edens) to * low-energy state. These must be processed sequentially and in this order * because you travel through high-energy states to get to the low-energy * states. * * Third layer: Planet. This is a good layer to parallelize on. There's * high enough cardinality that we don't have to mess with parallelizing * multiple layers for good utilization (on 2011 machines). Each thread * works on one planet's states and need not synchronize with peer threads. */ func FillStateTable1(data planet_data, dims []int) []State { table := make([]State, StateTableSize(dims)) barrier := make(chan bool, len(data.Planets)) eden_capacity := data.Commodities["Eden Warp Units"].Limit work_units := (float64(*fuel) + 1) * (float64(eden_capacity) + 1) work_done := 0.0 for fuel_remaining := *fuel; fuel_remaining >= 0; fuel_remaining-- { for edens_remaining := eden_capacity; edens_remaining >= 0; edens_remaining-- { for planet := range data.Planets { go FillStateTable2(data, dims, table, fuel_remaining, edens_remaining, planet, barrier) } for _ = range data.Planets { <-barrier } work_done++ fmt.Printf("\r%3.0f%%", 100*work_done/work_units) } } return table } /* What is the value of hauling 'commodity' from 'from' to 'to'? * Take into account the available funds and the available cargo space. */ func TradeValue(data planet_data, from, to Planet, commodity string, initial_funds, max_quantity int) int { if !data.Commodities[commodity].CanSell { return 0 } from_relative_price, from_available := from.RelativePrices[commodity] if !from_available { return 0 } to_relative_price, to_available := to.RelativePrices[commodity] if !to_available { return 0 } base_price := data.Commodities[commodity].BasePrice from_absolute_price := from_relative_price * base_price to_absolute_price := to_relative_price * base_price buy_price := from_absolute_price sell_price := int(float64(to_absolute_price) * 0.9) var can_afford int = initial_funds / buy_price quantity := can_afford if quantity > max_quantity { quantity = max_quantity } return (sell_price - buy_price) * max_quantity } func FindBestTrades(data planet_data) [][]string { // TODO: We can't cache this because this can change based on available funds. best := make([][]string, len(data.Planets)) for from := range data.Planets { best[data.p2i[from]] = make([]string, len(data.Planets)) for to := range data.Planets { best_gain := 0 price_list := data.Planets[from].RelativePrices if len(data.Planets[to].RelativePrices) < len(data.Planets[from].RelativePrices) { price_list = data.Planets[to].RelativePrices } for commodity := range price_list { gain := TradeValue(data, data.Planets[from], data.Planets[to], commodity, 10000000, 1) if gain > best_gain { best[data.p2i[from]][data.p2i[to]] = commodity gain = best_gain } } } } return best } // (Example of a use case for generics in Go) func IndexPlanets(m *map[string]Planet, start_at int) (map[string]int, []string) { e2i := make(map[string]int, len(*m)+start_at) i2e := make([]string, len(*m)+start_at) i := start_at for e := range *m { e2i[e] = i i2e[i] = e i++ } return e2i, i2e } func IndexCommodities(m *map[string]Commodity, start_at int) (map[string]int, []string) { e2i := make(map[string]int, len(*m)+start_at) i2e := make([]string, len(*m)+start_at) i := start_at for e := range *m { e2i[e] = i i2e[i] = e i++ } return e2i, i2e } func main() { flag.Parse() data := ReadData() data.p2i, data.i2p = IndexPlanets(&data.Planets, 0) data.c2i, data.i2c = IndexCommodities(&data.Commodities, 1) dims := DimensionSizes(data) table := FillStateTable1(data, dims) table[0] = State{1, 1} best_trades := FindBestTrades(data) for from := range data.Planets { for to := range data.Planets { best_trade := "(nothing)" if best_trades[data.p2i[from]][data.p2i[to]] != "" { best_trade = best_trades[data.p2i[from]][data.p2i[to]] } fmt.Printf("%s to %s: %s\n", from, to, best_trade) } } }