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1/* Planeteer: Give trade route advice for Planets: The Exploration of Space
2 * Copyright (C) 2011 Scott Worley <sworley@chkno.net>
3 *
4 * This program is free software: you can redistribute it and/or modify
5 * it under the terms of the GNU Affero General Public License as
6 * published by the Free Software Foundation, either version 3 of the
7 * License, or (at your option) any later version.
8 *
9 * This program is distributed in the hope that it will be useful,
10 * but WITHOUT ANY WARRANTY; without even the implied warranty of
11 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
12 * GNU Affero General Public License for more details.
13 *
14 * You should have received a copy of the GNU Affero General Public License
15 * along with this program. If not, see <http://www.gnu.org/licenses/>.
16 */
17
18package main
19
20import "flag"
c45c1bca 21import "fmt"
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22import "json"
23import "os"
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24import "strings"
25
26var start = flag.String("start", "",
27 "The planet to start at")
d07f3caa 28
c45c1bca 29var end = flag.String("end", "",
e9ff66cf 30 "A comma-separated list of acceptable ending planets.")
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31
32var planet_data_file = flag.String("planet_data_file", "planet-data",
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33 "The file to read planet data from")
34
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35var fuel = flag.Int("fuel", 16, "Reactor units")
36
37var hold = flag.Int("hold", 300, "Size of your cargo hold")
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38
39var start_edens = flag.Int("start_edens", 0,
40 "How many Eden Warp Units are you starting with?")
41
42var end_edens = flag.Int("end_edens", 0,
43 "How many Eden Warp Units would you like to keep (not use)?")
44
45var cloak = flag.Bool("cloak", false,
46 "Make sure to end with a Device of Cloaking")
47
e9ff66cf 48var drones = flag.Int("drones", 0, "Buy this many Fighter Drones")
c45c1bca 49
e9ff66cf 50var batteries = flag.Int("batteries", 0, "Buy this many Shield Batterys")
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51
52var visit_string = flag.String("visit", "",
53 "A comma-separated list of planets to make sure to visit")
54
55func visit() []string {
56 return strings.Split(*visit_string, ",")
57}
58
9b3b3d9a 59type Commodity struct {
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60 BasePrice int
61 CanSell bool
62 Limit int
63}
12bc2cd7 64type Planet struct {
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65 BeaconOn bool
66 /* Use relative prices rather than absolute prices because you
67 can get relative prices without traveling to each planet. */
0e94bdac 68 RelativePrices map[string]int
12bc2cd7 69}
d07f3caa 70type planet_data struct {
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71 Commodities map[string]Commodity
72 Planets map[string]Planet
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73 p2i, c2i map[string]int // Generated; not read from file
74 i2p, i2c []string // Generated; not read from file
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75}
76
77func ReadData() (data planet_data) {
c45c1bca 78 f, err := os.Open(*planet_data_file)
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79 if err != nil {
80 panic(err)
81 }
82 defer f.Close()
83 err = json.NewDecoder(f).Decode(&data)
84 if err != nil {
85 panic(err)
86 }
87 return
88}
89
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90/* This program operates by filling in a state table representing the best
91 * possible trips you could make; the ones that makes you the most money.
92 * This is feasible because we don't look at all the possible trips.
93 * We define a list of things that are germane to this game and then only
94 * consider the best outcome in each possible game state.
95 *
96 * Each cell in the table represents a state in the game. In each cell,
97 * we track two things: 1. the most money you could possibly have while in
98 * that state and 2. one possible way to get into that state with that
99 * amount of money.
100 *
101 * A basic analysis can be done with a two-dimensional table: location and
102 * fuel. planeteer-1.0 used this two-dimensional table. This version
103 * adds features mostly by adding dimensions to this table.
104 *
105 * Note that the sizes of each dimension are data driven. Many dimensions
106 * collapse to one possible value (ie, disappear) if the corresponding
107 * feature is not enabled.
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108 *
109 * The order of the dimensions in the list of constants below determines
110 * their layout in RAM. The cargo-based 'dimensions' are not completely
111 * independent -- some combinations are illegal and not used. They are
112 * handled as three dimensions rather than one for simplicity. Placing
113 * these dimensions first causes the unused cells in the table to be
114 * grouped together in large blocks. This keeps them from polluting
115 * cache lines, and if they are large enough, prevent the memory manager
116 * from allocating pages for these areas at all.
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117 */
118
119// The official list of dimensions:
120const (
e9ff66cf 121 // Name Num Size Description
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122 Edens = iota // 1 3 # of Eden warp units (0 - 2 typically)
123 Cloaks // 2 2 # of Devices of Cloaking (0 or 1)
124 UnusedCargo // 3 4 # of unused cargo spaces (0 - 3 typically)
125 Fuel // 4 17 Reactor power left (0 - 16)
126 Location // 5 26 Location (which planet)
127 Hold // 6 15 Cargo bay contents (a *Commodity or nil)
128 NeedFighters // 7 2 Errand: Buy fighter drones (needed or not)
129 NeedShields // 8 2 Errand: Buy shield batteries (needed or not)
130 Visit // 9 2**N Visit: Stop by these N planets in the route
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131
132 NumDimensions
133)
134
135func bint(b bool) int {
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136 if b {
137 return 1
138 }
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139 return 0
140}
141
142func DimensionSizes(data planet_data) []int {
143 eden_capacity := data.Commodities["Eden Warp Units"].Limit
144 cloak_capacity := bint(*cloak)
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145 dims := make([]int, NumDimensions)
146 dims[Edens] = eden_capacity + 1
147 dims[Cloaks] = cloak_capacity + 1
148 dims[UnusedCargo] = eden_capacity + cloak_capacity + 1
149 dims[Fuel] = *fuel + 1
150 dims[Location] = len(data.Planets)
151 dims[Hold] = len(data.Commodities)
152 dims[NeedFighters] = bint(*drones > 0) + 1
153 dims[NeedShields] = bint(*batteries > 0) + 1
154 dims[Visit] = 1 << uint(len(visit()))
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155
156 // Remind myself to add a line above when adding new dimensions
157 for i, dim := range dims {
158 if dim < 1 {
159 panic(i)
160 }
161 }
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162 return dims
163}
164
165func StateTableSize(dims []int) int {
166 sum := 0
167 for _, size := range dims {
168 sum += size
169 }
170 return sum
171}
172
173type State struct {
174 funds, from int
175}
176
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177func EncodeIndex(dims, addr []int) int {
178 index := addr[0]
179 for i := 1; i < len(dims); i++ {
0e94bdac 180 index = index*dims[i] + addr[i]
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181 }
182 return index
183}
184
185func DecodeIndex(dims []int, index int) []int {
186 addr := make([]int, len(dims))
187 for i := len(dims) - 1; i > 0; i-- {
188 addr[i] = index % dims[i]
189 index /= dims[i]
190 }
191 addr[0] = index
192 return addr
193}
194
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195func FillStateCell(data planet_data, dims []int, table []State, addr []int) {
196}
197
198func FillStateTable2(data planet_data, dims []int, table []State,
199fuel_remaining, edens_remaining int, planet string, barrier chan<- bool) {
200 /* The dimension nesting order up to this point is important.
201 * Beyond this point, it's not important.
202 *
203 * It is very important when iterating through the Hold dimension
204 * to visit the null commodity (empty hold) first. Visiting the
205 * null commodity represents selling. Visiting it first gets the
206 * action order correct: arrive, sell, buy, leave. Visiting the
207 * null commodity after another commodity would evaluate the action
208 * sequence: arrive, buy, sell, leave. This is a useless action
209 * sequence. Because we visit the null commodity first, we do not
210 * consider these action sequences.
211 */
212 eden_capacity := data.Commodities["Eden Warp Units"].Limit
213 addr := make([]int, len(dims))
214 addr[Edens] = edens_remaining
215 addr[Fuel] = fuel_remaining
216 addr[Location] = data.p2i[planet]
217 for addr[Hold] = 0; addr[Hold] < dims[Hold]; addr[Hold]++ {
218 for addr[Cloaks] = 0; addr[Cloaks] < dims[Cloaks]; addr[Cloaks]++ {
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219 for addr[UnusedCargo] = 0; addr[UnusedCargo] < dims[UnusedCargo]; addr[UnusedCargo]++ {
220 if addr[Edens]+addr[Cloaks]+addr[UnusedCargo] <=
221 eden_capacity+1 {
222 for addr[NeedFighters] = 0; addr[NeedFighters] < dims[NeedFighters]; addr[NeedFighters]++ {
223 for addr[NeedShields] = 0; addr[NeedShields] < dims[NeedShields]; addr[NeedShields]++ {
224 for addr[Visit] = 0; addr[Visit] < dims[Visit]; addr[Visit]++ {
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225 FillStateCell(data, dims, table, addr)
226 }
227 }
228 }
229 }
230 }
231 }
232 }
233 barrier <- true
234}
235
236/* Filling the state table is a set of nested for loops NumDimensions deep.
237 * We split this into two procedures: 1 and 2. #1 is the outer, slowest-
238 * changing indexes. #1 fires off many calls to #2 that run in parallel.
239 * The order of the nesting of the dimensions, the order of iteration within
240 * each dimension, and where the 1 / 2 split is placed are carefully chosen
241 * to make this arrangement safe.
242 *
243 * Outermost two layers: Go from high-energy states (lots of fuel, edens) to
244 * low-energy state. These must be processed sequentially and in this order
245 * because you travel through high-energy states to get to the low-energy
246 * states.
247 *
248 * Third layer: Planet. This is a good layer to parallelize on. There's
249 * high enough cardinality that we don't have to mess with parallelizing
250 * multiple layers for good utilization (on 2011 machines). Each thread
251 * works on one planet's states and need not synchronize with peer threads.
252 */
253func FillStateTable1(data planet_data, dims []int) []State {
254 table := make([]State, StateTableSize(dims))
255 barrier := make(chan bool, len(data.Planets))
256 eden_capacity := data.Commodities["Eden Warp Units"].Limit
257 work_units := (float64(*fuel) + 1) * (float64(eden_capacity) + 1)
258 work_done := 0.0
259 for fuel_remaining := *fuel; fuel_remaining >= 0; fuel_remaining-- {
a1f10151 260 for edens_remaining := eden_capacity; edens_remaining >= 0; edens_remaining-- {
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261 for planet := range data.Planets {
262 go FillStateTable2(data, dims, table, fuel_remaining,
263 edens_remaining, planet, barrier)
264 }
265 for _ = range data.Planets {
266 <-barrier
267 }
268 work_done++
a1f10151 269 fmt.Printf("\r%3.0f%%", 100*work_done/work_units)
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270 }
271 }
272 return table
273}
274
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275/* What is the value of hauling 'commodity' from 'from' to 'to'?
276 * Take into account the available funds and the available cargo space. */
277func TradeValue(data planet_data,
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278from, to Planet,
279commodity string,
280initial_funds, max_quantity int) int {
5f1a50e1 281 if !data.Commodities[commodity].CanSell {
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282 return 0
283 }
5f1a50e1 284 from_relative_price, from_available := from.RelativePrices[commodity]
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285 if !from_available {
286 return 0
287 }
5f1a50e1 288 to_relative_price, to_available := to.RelativePrices[commodity]
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289 if !to_available {
290 return 0
291 }
292
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293 base_price := data.Commodities[commodity].BasePrice
294 from_absolute_price := from_relative_price * base_price
295 to_absolute_price := to_relative_price * base_price
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296 buy_price := from_absolute_price
297 sell_price := int(float64(to_absolute_price) * 0.9)
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298 var can_afford int = initial_funds / buy_price
299 quantity := can_afford
300 if quantity > max_quantity {
301 quantity = max_quantity
302 }
303 return (sell_price - buy_price) * max_quantity
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304}
305
5f1a50e1 306func FindBestTrades(data planet_data) [][]string {
c45c1bca 307 // TODO: We can't cache this because this can change based on available funds.
5f1a50e1 308 best := make([][]string, len(data.Planets))
c45c1bca 309 for from := range data.Planets {
e7e4bc13 310 best[data.p2i[from]] = make([]string, len(data.Planets))
c45c1bca 311 for to := range data.Planets {
5a1593ab 312 best_gain := 0
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313 price_list := data.Planets[from].RelativePrices
314 if len(data.Planets[to].RelativePrices) < len(data.Planets[from].RelativePrices) {
315 price_list = data.Planets[to].RelativePrices
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316 }
317 for commodity := range price_list {
318 gain := TradeValue(data,
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319 data.Planets[from],
320 data.Planets[to],
321 commodity,
322 10000000,
323 1)
5a1593ab 324 if gain > best_gain {
e7e4bc13 325 best[data.p2i[from]][data.p2i[to]] = commodity
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326 gain = best_gain
327 }
328 }
329 }
330 }
331 return best
332}
333
c45c1bca 334// (Example of a use case for generics in Go)
e7e4bc13 335func IndexPlanets(m *map[string]Planet, start_at int) (map[string]int, []string) {
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336 e2i := make(map[string]int, len(*m)+start_at)
337 i2e := make([]string, len(*m)+start_at)
e7e4bc13 338 i := start_at
c45c1bca 339 for e := range *m {
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340 e2i[e] = i
341 i2e[i] = e
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342 i++
343 }
e7e4bc13 344 return e2i, i2e
c45c1bca 345}
e7e4bc13 346func IndexCommodities(m *map[string]Commodity, start_at int) (map[string]int, []string) {
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347 e2i := make(map[string]int, len(*m)+start_at)
348 i2e := make([]string, len(*m)+start_at)
e7e4bc13 349 i := start_at
c45c1bca 350 for e := range *m {
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351 e2i[e] = i
352 i2e[i] = e
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353 i++
354 }
e7e4bc13 355 return e2i, i2e
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356}
357
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358func main() {
359 flag.Parse()
360 data := ReadData()
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361 data.p2i, data.i2p = IndexPlanets(&data.Planets, 0)
362 data.c2i, data.i2c = IndexCommodities(&data.Commodities, 1)
c45c1bca 363 dims := DimensionSizes(data)
e7e4bc13 364 table := FillStateTable1(data, dims)
0e94bdac 365 table[0] = State{1, 1}
5a1593ab 366 best_trades := FindBestTrades(data)
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367
368 for from := range data.Planets {
369 for to := range data.Planets {
5a1593ab 370 best_trade := "(nothing)"
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371 if best_trades[data.p2i[from]][data.p2i[to]] != "" {
372 best_trade = best_trades[data.p2i[from]][data.p2i[to]]
5a1593ab 373 }
c45c1bca 374 fmt.Printf("%s to %s: %s\n", from, to, best_trade)
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375 }
376 }
d07f3caa 377}