FillStateTable()

[planeteer] / planeteer.go

/* Planeteer: Give trade route advice for Planets: The Exploration of Space
 * Copyright (C) 2011  Scott Worley <sworley@chkno.net>
 *
 * 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 <http://www.gnu.org/licenses/>.
 */

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)
                }
        }
}