示例#1
0
        public void launchWorkers(NestItem[] parts)
        {
            background.ResponseAction = ResponseProcessor;
            if (ga == null)
            {
                List <NFP> adam = new List <NFP>();
                var        id   = 0;
                for (int i = 0; i < parts.Count(); i++)
                {
                    if (!parts[i].IsSheet)
                    {
                        for (int j = 0; j < parts[i].Quanity; j++)
                        {
                            var poly = cloneTree(parts[i].Polygon); // deep copy
                            poly.id     = id;                       // id is the unique id of all parts that will be nested, including cloned duplicates
                            poly.source = i;                        // source is the id of each unique part from the main part list

                            adam.Add(poly);
                            id++;
                        }
                    }
                }

                adam = adam.OrderByDescending(z => Math.Abs(GeometryUtil.polygonArea(z))).ToList();

                /*List<NFP> shuffle = new List<NFP>();
                 * Random r = new Random(DateTime.Now.Millisecond);
                 * while (adam.Any())
                 * {
                 *  var rr = r.Next(adam.Count);
                 *  shuffle.Add(adam[rr]);
                 *  adam.RemoveAt(rr);
                 * }
                 * adam = shuffle;*/

                /*#region special case
                 * var temp = adam[1];
                 * adam.RemoveAt(1);
                 * adam.Insert(9, temp);
                 *
                 #endregion*/
                ga = new GeneticAlgorithm(adam.ToArray(), Config);
            }
            individual = null;

            // check if current generation is finished
            var finished = true;

            for (int i = 0; i < ga.population.Count; i++)
            {
                if (ga.population[i].fitness == null)
                {
                    finished = false;
                    break;
                }
            }
            if (finished)
            {
                //console.log('new generation!');
                // all individuals have been evaluated, start next generation
                ga.generation();
            }

            var running = ga.population.Where((p) =>
            {
                return(p.processing != null);
            }).Count();

            List <NFP>         sheets        = new List <NFP>();
            List <int>         sheetids      = new List <int>();
            List <int>         sheetsources  = new List <int>();
            List <List <NFP> > sheetchildren = new List <List <NFP> >();
            var sid = 0;

            for (int i = 0; i < parts.Count(); i++)
            {
                if (parts[i].IsSheet)
                {
                    var poly = parts[i].Polygon;
                    for (int j = 0; j < parts[i].Quanity; j++)
                    {
                        var cln = cloneTree(poly);
                        cln.id     = sid;         // id is the unique id of all parts that will be nested, including cloned duplicates
                        cln.source = poly.source; // source is the id of each unique part from the main part list

                        sheets.Add(cln);
                        sheetids.Add(sid);
                        sheetsources.Add(i);
                        sheetchildren.Add(poly.children);
                        sid++;
                    }
                }
            }
            for (int i = 0; i < ga.population.Count; i++)
            {
                //if(running < config.threads && !GA.population[i].processing && !GA.population[i].fitness){
                // only one background window now...
                if (running < 1 && ga.population[i].processing == null && ga.population[i].fitness == null)
                {
                    ga.population[i].processing = true;

                    // hash values on arrays don't make it across ipc, store them in an array and reassemble on the other side....
                    List <int>         ids      = new List <int>();
                    List <int>         sources  = new List <int>();
                    List <List <NFP> > children = new List <List <NFP> >();

                    for (int j = 0; j < ga.population[i].placements.Count; j++)
                    {
                        var id     = ga.population[i].placements[j].id;
                        var source = ga.population[i].placements[j].source;
                        var child  = ga.population[i].placements[j].children;
                        //ids[j] = id;
                        ids.Add(id);
                        //sources[j] = source;
                        sources.Add(source.Value);
                        //children[j] = child;
                        children.Add(child);
                    }

                    DataInfo data = new DataInfo()
                    {
                        index         = i,
                        sheets        = sheets,
                        sheetids      = sheetids.ToArray(),
                        sheetsources  = sheetsources.ToArray(),
                        sheetchildren = sheetchildren,
                        individual    = ga.population[i],
                        config        = Config,
                        ids           = ids.ToArray(),
                        sources       = sources.ToArray(),
                        children      = children
                    };

                    background.BackgroundStart(data);
                    //ipcRenderer.send('background-start', { index: i, sheets: sheets, sheetids: sheetids, sheetsources: sheetsources, sheetchildren: sheetchildren, individual: GA.population[i], config: config, ids: ids, sources: sources, children: children});
                    running++;
                }
            }
        }