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++;
}
}
}