package main
import "flag"
+import "fmt"
import "json"
import "os"
-import "fmt"
+import "strings"
+
+var start = flag.String("start", "",
+ "The planet to start at")
-var datafile = flag.String("planet_data_file", "planet-data",
+var flight_plan_string = flag.String("flight_plan", "",
+ "Your hidey-holes for the day, comma-separated.")
+
+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 {
+ if *visit_string == "" {
+ return []string{}
+ }
+ return strings.Split(*visit_string, ",")
+}
+
+func flight_plan() []string {
+ if *flight_plan_string == "" {
+ return []string{}
+ }
+ return strings.Split(*flight_plan_string, ",")
+}
+
type Commodity struct {
- Name string
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 []Commodity
- Planets []struct {
- Name string
- BeaconOn bool
- /* Use relative prices rather than absolute prices because you
- can get relative prices without traveling to each planet. */
- RelativePrices map [string] int
- }
+ 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(*datafile)
+ f, err := os.Open(*planet_data_file)
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.
+ *
+ * If the table gets too big to fit in RAM:
+ * * Combine the Edens, Cloaks, and UnusedCargo dimensions. Of the
+ * 24 combinations, only 15 are legal: a 38% savings.
+ * * Reduce the size of the Fuel dimension to 3. We only ever look
+ * backwards 2 units, so just rotate the logical values through
+ * the same 3 physical addresses. This is good for an 82% savings.
+ * * Reduce the size of the Edens dimension from 3 to 2, for the
+ * same reasons as Fuel above. 33% savings.
+ * * Buy more ram. (Just sayin'. It's cheaper than you think.)
+ *
+ */
+
+// 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 {
+ product := 1
+ for _, size := range dims {
+ product *= size
+ }
+ return product
+}
+
+type State struct {
+ value, from int
+}
+
+func EncodeIndex(dims, addr []int) int {
+ index := addr[0]
+ if addr[0] > dims[0] {
+ panic(0)
+ }
+ for i := 1; i < len(dims); i++ {
+ if addr[i] > dims[i] {
+ panic(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 InitializeStateTable(data planet_data, dims []int, table []State) {
+}
+
+/* Fill in the cell at address addr by looking at all the possible ways
+ * to reach this cell and selecting the best one.
+ *
+ * The other obvious implementation choice is to do this the other way
+ * around -- for each cell, conditionally overwrite all the other cells
+ * that are reachable *from* the considered cell. We choose gathering
+ * reads over scattering writes to avoid having to take a bunch of locks.
+ *
+ * The order that we check things here matters only for value ties. We
+ * keep the first best path. So when action order doesn't matter, the
+ * check that is performed first here will appear in the output first.
+ */
+func FillStateTableCell(data planet_data, dims []int, table []State, addr []int) {
+ my_index := EncodeIndex(dims, addr)
+ other := make([]int, NumDimensions)
+ copy(other, addr)
+
+ /* Travel here via a 2-fuel unit jump */
+ if addr[Fuel] + 2 < dims[Fuel] {
+ other[Fuel] = addr[Fuel] + 2
+ for p := 0; p < dims[Location]; p++ {
+ other[Location] = p
+ if table[EncodeIndex(dims, other)].value > table[my_index].value {
+ table[my_index].value = table[EncodeIndex(dims, other)].value
+ table[my_index].from = EncodeIndex(dims, other)
+ }
+ }
+ other[Location] = addr[Location]
+ other[Fuel] = addr[Fuel]
+ }
+
+ /* Travel here via a hidey hole */
+ if addr[Fuel] + 1 < dims[Fuel] {
+ hole_index := (dims[Fuel] - 1) - (addr[Fuel] + 1)
+ if hole_index < len(flight_plan()) {
+ other[Fuel] = addr[Fuel] + 1
+ other[Location] = data.p2i[flight_plan()[hole_index]]
+ if table[EncodeIndex(dims, other)].value > table[my_index].value {
+ table[my_index].value = table[EncodeIndex(dims, other)].value
+ table[my_index].from = EncodeIndex(dims, other)
+ }
+ other[Fuel] = addr[Fuel]
+ }
+ }
+
+ /* Travel here via Eden Warp Unit */
+ /* Silly: Dump Eden warp units */
+ /* Buy Eden warp units */
+ /* Buy a Device of Cloaking */
+ /* Silly: Dump a Device of Cloaking */
+ /* Buy Fighter Drones */
+ /* Buy Shield Batteries */
+ if addr[Hold] == 0 {
+ /* Sell or dump things */
+ // for commodity := range data.Commodities { }
+ } else {
+ /* Buy this thing */
+ }
+ /* Visit this planet */
+}
+
+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]++ {
+ FillStateTableCell(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, table []State) {
+ 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)
+ }
+ }
+ print("\n")
+}
+
+/* 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()
- fmt.Printf("%v", data)
+ data.p2i, data.i2p = IndexPlanets(&data.Planets, 0)
+ data.c2i, data.i2c = IndexCommodities(&data.Commodities, 1)
+ dims := DimensionSizes(data)
+ table := make([]State, StateTableSize(dims))
+ InitializeStateTable(data, dims, table)
+ FillStateTable1(data, dims, table)
+ print("Going to print state table...")
+ fmt.Printf("%v", table)
+ 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)
+ }
+ }
}
projects / planeteer / blobdiff