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|
package core
import (
"container/heap"
"log"
"sort"
)
const (
MaxCapital = 100000000000.0 // 100B
MaxTradesToConsider = 200 // Keep bound so we don't evaluate forever, python doesn't effectively bound it
)
type Action struct {
ActionType string `json:"action_type"` // "buy" or "sell"
Item string `json:"item"`
TypeID int `json:"type_id"`
Quantity int `json:"quantity"`
Price float64 `json:"price"`
}
type RouteStep struct {
ID int `json:"id"`
LocationID int `json:"location_id"`
Location string `json:"location"`
LocationType string `json:"location_type"`
SystemID int `json:"system_id,omitempty"`
SystemName string `json:"system_name,omitempty"`
StationName string `json:"station_name,omitempty"`
Security float64 `json:"security,omitempty"`
RegionID int `json:"region_id,omitempty"`
Actions []Action `json:"actions"`
}
type RouteInfo struct {
ProfitRate float64 `json:"profit_rate"`
Risk float64 `json:"risk"`
Capital float64 `json:"capital"`
TransportTime float64 `json:"transport_time"`
GrossProfit float64 `json:"gross_profit"`
NetProfit float64 `json:"net_profit"`
}
type RoutePlan struct {
Route []RouteStep
Info *RouteInfo
OptimizedTrades []Trade
Path []int
RawOffsets []int
}
type Ship struct {
TaxRate float64 `json:"tax_rate"`
ProfitThreshold float64 `json:"profit_threshold"`
MaxCapital float64 `json:"max_capital"`
SnipeThreshold float64 `json:"snipe_profit_threshold"`
Location int `json:"location"`
Cargo float64 `json:"cargo"`
MaxWarpSpeed float64 `json:"max_warp_speed"`
MaxSubwarpSpeed float64 `json:"max_subwarp_speed"`
GankersAreas map[string]float64 `json:"gankers_areas"`
PlayerCost float64 `json:"player_cost"`
RiskCost float64 `json:"risk_cost"`
ShipCost float64 `json:"ship_cost"`
}
type tradeDensityHeap struct {
trades []Trade
}
func (h tradeDensityHeap) Len() int { return len(h.trades) }
func (h tradeDensityHeap) Less(i, j int) bool {
// Reverse sorted by profit density
di := h.trades[i].GrossProfit / h.trades[i].Cargo
dj := h.trades[j].GrossProfit / h.trades[j].Cargo
return di > dj
}
func (h tradeDensityHeap) Swap(i, j int) { h.trades[i], h.trades[j] = h.trades[j], h.trades[i] }
func (h *tradeDensityHeap) Push(x any) { h.trades = append(h.trades, x.(Trade)) }
func (h *tradeDensityHeap) Pop() any {
old := h.trades
n := len(old)
x := old[n-1]
h.trades = old[0 : n-1]
return x
}
func tradeCapitalEfficiency(t Trade) float64 {
invested := t.FromPrice * float64(t.Quantity)
if invested > 0 {
return t.GrossProfit / invested
}
return 0.0
}
func minInt(vars ...int) int {
m := vars[0]
for _, v := range vars[1:] {
if v < m {
m = v
}
}
return m
}
func maxFloat(vars ...float64) float64 {
m := vars[0]
for _, v := range vars[1:] {
if v > m {
m = v
}
}
return m
}
func buildRankedTriplets(trades []Trade, shipLoc int) [][3]int {
// Sort by capital efficiency descending
sorted := make([]Trade, len(trades))
copy(sorted, trades)
sort.Slice(sorted, func(i, j int) bool {
return tradeCapitalEfficiency(sorted[i]) > tradeCapitalEfficiency(sorted[j])
})
var ranked [][3]int
seen := make(map[[3]int]bool)
for _, t := range sorted {
trip := [3]int{shipLoc, t.FromStation, t.ToStation}
if !seen[trip] {
seen[trip] = true
ranked = append(ranked, trip)
}
}
return ranked
}
func buildStationPairIndex(trades []Trade) map[[2]int][]Trade {
index := make(map[[2]int][]Trade)
for _, t := range trades {
pair := [2]int{t.FromStation, t.ToStation}
index[pair] = append(index[pair], t)
}
for k := range index {
sort.Slice(index[k], func(i, j int) bool {
di := index[k][i].GrossProfit / index[k][i].Cargo
dj := index[k][j].GrossProfit / index[k][j].Cargo
return di > dj
})
}
return index
}
func selectTrades(routeStations [3]int, tradesByPair map[[2]int][]Trade, ship Ship) []Trade {
var candidatePairs [][2]int
for i, fromStation := range routeStations {
for _, toStation := range routeStations[i+1:] {
pair := [2]int{fromStation, toStation}
// ensure unique pairs
exists := false
for _, cp := range candidatePairs {
if cp == pair {
exists = true
break
}
}
if !exists {
candidatePairs = append(candidatePairs, pair)
}
}
}
// merge candidates into max heap based on profit density
h := &tradeDensityHeap{}
heap.Init(h)
for _, pair := range candidatePairs {
if ts, ok := tradesByPair[pair]; ok {
for _, t := range ts {
heap.Push(h, t)
}
}
}
usedOrders := make(map[int]int)
var optimized []Trade
var cargo, capital float64
for h.Len() > 0 {
t := heap.Pop(h).(Trade)
fromRemaining, ok := usedOrders[t.FromOrderID]
if !ok {
fromRemaining = t.Quantity
}
toRemaining, ok := usedOrders[t.ToOrderID]
if !ok {
toRemaining = t.Quantity
}
maxQtyCargo := int((ship.Cargo - cargo) / (t.Cargo / float64(t.Quantity))) // rough item volume
itemVol := t.Cargo / float64(t.Quantity)
if itemVol == 0 {
itemVol = 0.01 // avoid divide by zero just in case
maxQtyCargo = t.Quantity
} else {
maxQtyCargo = int((ship.Cargo - cargo) / itemVol)
}
maxQtyCapital := int((MaxCapital - capital) / t.FromPrice)
maxQty := minInt(t.Quantity, fromRemaining, toRemaining, maxQtyCargo, maxQtyCapital)
if maxQty <= 0 {
continue
}
cargo += itemVol * float64(maxQty)
capital += t.FromPrice * float64(maxQty)
usedOrders[t.FromOrderID] = fromRemaining - maxQty
usedOrders[t.ToOrderID] = toRemaining - maxQty
updated := t
updated.Quantity = maxQty
updated.Cargo = itemVol * float64(maxQty)
if t.Quantity > 0 {
updated.GrossProfit = t.GrossProfit * (float64(maxQty) / float64(t.Quantity))
} else {
updated.GrossProfit = 0
}
optimized = append(optimized, updated)
if cargo >= ship.Cargo || capital >= MaxCapital {
break
}
}
return optimized
}
func calculatePeakCapital(locationIDs []int, trades []Trade, shipCost float64) float64 {
if len(trades) == 0 {
return shipCost
}
remainingLocs := make(map[int]bool)
for _, l := range locationIDs {
remainingLocs[l] = true
}
committed := shipCost
for _, t := range trades {
if !remainingLocs[t.FromStation] {
committed += t.FromPrice * float64(t.Quantity)
}
}
peak := committed
for _, loc := range locationIDs {
// sell
for _, t := range trades {
if t.ToStation == loc {
committed -= t.FromPrice * float64(t.Quantity)
}
}
committed = maxFloat(shipCost, committed)
// buy
for _, t := range trades {
if t.FromStation == loc {
committed += t.FromPrice * float64(t.Quantity)
}
}
peak = maxFloat(peak, committed)
}
return peak
}
func buildRouteInfo(locationIDs []int, trades []Trade, ship Ship, time, risk float64) *RouteInfo {
if len(trades) == 0 {
return nil
}
capital := calculatePeakCapital(locationIDs, trades, ship.ShipCost)
var gross float64
for _, t := range trades {
gross += t.GrossProfit
}
net := gross - risk*capital
rate := 0.0
if time > 0 {
rate = net / time
}
return &RouteInfo{
ProfitRate: rate,
Risk: risk,
Capital: capital,
TransportTime: time,
GrossProfit: gross,
NetProfit: net,
}
}
func RouteOptimizer(trades []Trade, graph *Graph, ship Ship, legMetrics map[[2]int]*LegMetrics) *RoutePlan {
if len(trades) == 0 {
return &RoutePlan{Route: []RouteStep{}, OptimizedTrades: []Trade{}, Path: []int{}, RawOffsets: []int{}}
}
rankedTriplets := buildRankedTriplets(trades, ship.Location)
tradesByPair := buildStationPairIndex(trades)
if legMetrics == nil {
legMetrics = BuildTradeLegMetrics(graph, ship.Location, trades)
}
var bestRate float64
var bestInfo *RouteInfo
var bestStations []int
var bestTrades []Trade
limit := MaxTradesToConsider
if len(rankedTriplets) < limit {
limit = len(rankedTriplets)
}
for _, trip := range rankedTriplets[:limit] {
optimized := selectTrades(trip, tradesByPair, ship)
if len(optimized) == 0 {
continue
}
sLeg, sOk := legMetrics[[2]int{trip[0], trip[1]}]
dLeg, dOk := legMetrics[[2]int{trip[1], trip[2]}]
if !sOk || !dOk || sLeg == nil || dLeg == nil {
continue
}
risk := sLeg.Risk + dLeg.Risk
time := sLeg.Time + dLeg.Time
locs := []int{trip[0], trip[1], trip[2]}
info := buildRouteInfo(locs, optimized, ship, time, risk)
if info == nil {
continue
}
if info.ProfitRate > bestRate {
bestRate = info.ProfitRate
bestInfo = info
bestStations = locs
bestTrades = optimized
log.Printf("New best profit rate: %.2f/hr", bestRate*3600)
}
}
if bestStations == nil || bestTrades == nil {
return &RoutePlan{Route: []RouteStep{}, OptimizedTrades: []Trade{}, Path: []int{}, RawOffsets: []int{}}
}
// Reconstruct path
sRes := graph.ShortestPath(bestStations[0], bestStations[1])
dRes := graph.ShortestPath(bestStations[1], bestStations[2])
var path []int
if len(sRes) > 0 {
path = append(path, sRes[:len(sRes)-1]...)
path = append(path, dRes...)
} else {
// fallback
path = append(path, dRes...)
}
// Formatted route (this needs more detailed graph metadata merging, we'll build a simplified version)
formatted, offsets := graph.FormattedRouteWithOffsets(path)
// Set Actions
actionsRoute := setActions(formatted, bestTrades)
return &RoutePlan{
Route: actionsRoute,
Info: bestInfo,
OptimizedTrades: bestTrades,
Path: path,
RawOffsets: offsets,
}
}
func setActions(route []RouteStep, trades []Trade) []RouteStep {
bought := make(map[int]bool)
for _, t := range trades {
for i := range route {
if t.FromStation == route[i].LocationID {
route[i].Actions = append(route[i].Actions, Action{
ActionType: "buy",
Item: t.ItemName,
TypeID: t.TypeID,
Quantity: t.Quantity,
Price: t.FromPrice,
})
bought[t.TypeID] = true
}
if t.ToStation == route[i].LocationID && bought[t.TypeID] {
route[i].Actions = append(route[i].Actions, Action{
ActionType: "sell",
Item: t.ItemName,
TypeID: t.TypeID,
Quantity: t.Quantity,
Price: t.ToPrice,
})
}
}
}
// Sort actions
for i := range route {
sort.Slice(route[i].Actions, func(a, b int) bool {
al := route[i].Actions[a]
bl := route[i].Actions[b]
if al.ActionType != bl.ActionType {
return al.ActionType == "sell" // sell comes before buy (0 vs 1 in python logic)
}
if al.Item != bl.Item {
return al.Item < bl.Item
}
return al.Price < bl.Price
})
}
return route
}
|