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If your creep needs to find... | |
(can be accessed as creep.pos, or any other RoomPosition) | |
creep.pos.findClosestByRange(type, options) -- returns one object, type is FIND_xx, for example: target = creep.pos.findClosestByRange(FIND_MY_SPAWNS); | |
creep.pos.findClosestByPath(type, options) -- as above, but more CPU costly (searches by real path, not distance) | |
creep.pos.findInRange(type, range, options) -- array, type is FIND_xx. Searches in square. All 8 adjacent tiles to creep are in range 1 | |
creep.pos.lookFor(type) -- array of objects that are at same position as creep. Type is LOOK_xx, for example LOOK_CONSTRUCTION_SITES | |
(can be accessed as creep.room, or any other Room) | |
creep.room.find(type, options) -- array, type is FIND_xx, for example FIND_DROPPED_RESOURCES. Options can have filter - as a function or object, like |
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module.getItemNames = function (item_ids, cb) { | |
dbItems.find({ 'id': { $in: item_ids } }).toArray(function (err, docs) { | |
if (err) { | |
log.error("getContracts_items: Error for dbItems.find", { err }); | |
cb(err); | |
return; | |
} | |
var fullquery = docs.map(d => d.id); |
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let UTILS_ROOM = {}; | |
UTILS_ROOM.getSpawns = function (room) { | |
//return getCached(room.name, "spawn", () => | |
return room.find(FIND_MY_STRUCTURES, { | |
filter: { structureType: STRUCTURE_SPAWN } | |
}) | |
//); | |
}; | |
let UTILS = {}; |
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//let UTILS = require('./utils'); | |
//let UTILS_ROOM = require('./utils.room'); | |
let UTILS_ROOM = {}; | |
UTILS_ROOM.getSpawns = function (room) { | |
//return getCached(room.name, "spawn", () => | |
return room.find(FIND_MY_STRUCTURES, { | |
filter: { structureType: STRUCTURE_SPAWN } |
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// cacheEnum | |
CACHE.E_ROOM = 1; | |
CACHE.coreInit = function () { | |
if (!global.my_caches) { | |
CACHE[CACHE.E_ROOM] = Memory.rooms; | |
global.my_caches = true; | |
} |
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function renderMatrix(roomName, costMatrix, color = '#ff0000') { | |
var vis = Game.rooms[roomName].visual; | |
const array = costMatrix._bits; | |
var max = _.max(array); | |
for (var x = 0; x < 50; ++x) { | |
for (var y = 0; y < 50; ++y) { | |
var value = array[x * 50 + y]; |
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const PLAIN_COST = 3; | |
const SWAMP_COST = 6; | |
const WALL_COST = 30 * PLAIN_COST; | |
const EXISTING_PATH_COST = PLAIN_COST - 2; | |
function getDestinations(room) { | |
let destinations = room.find(FIND_SOURCES); | |
destinations.push({ pos: room.getPositionAt(1, 25) }); | |
return destinations; | |
} |
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////////////////////////////////////////////////////////////////////////////////////////////////////////////// | |
// Funkcja: Update() | |
// Działanie: update.. | |
////////////////////////////////////////////////////////////////////////////////////////////////////////////// | |
void Bohater :: Update() | |
{ | |
brain->Update(); | |
cycles++; | |
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Procedure naucz(var _siec :Tsiec;var _uczacy :Tuczacy); | |
{uczenie sieci metoda wstecznej propagacji bledow, liczba warstw: min 3} | |
var | |
_out :Tout; _in :Tin; _delta :Tdelta; _blad :Tblad; | |
_i,_i2,_i3 :integer; waga_tmp :real; | |
begin | |
for _i2:=1 to _siec.liczba_n[1] do _out[1,_i2]:=_uczacy.we[_i2]; {warstwa we} | |
for _i:=1 to _siec.liczba_w-1 do _out[_i,_siec.liczba_n[_i]]:=1; {bias} | |
{mnozenie wejsc przez wagi dla kazdego neuronu} | |
for _i:=2 to _siec.liczba_w do |
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function planner_loop (roomName, opts = {}) { | |
let _this = {}; | |
_this.visual = new RoomVisual(roomName); | |
_this.anchor = getAnchor(roomName); | |
_this.terrain = new Room.Terrain(roomName); | |
if (!_this.anchor) return; | |
let s = 1; |
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