Better support for circular bed.
This commit is contained in:
tamasmeszaros
parent
3c32a7c3db
commit
e1edb05bbb
@ -50,492 +50,12 @@ void arrangeRectangles() {
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using namespace libnest2d;
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const int SCALE = 1000000;
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// const int SCALE = 1;
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std::vector<Rectangle> rects = {
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{80*SCALE, 80*SCALE},
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{60*SCALE, 90*SCALE},
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{70*SCALE, 30*SCALE},
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{80*SCALE, 60*SCALE},
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{60*SCALE, 60*SCALE},
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{60*SCALE, 40*SCALE},
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{40*SCALE, 40*SCALE},
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{10*SCALE, 10*SCALE},
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{10*SCALE, 10*SCALE},
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{10*SCALE, 10*SCALE},
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{10*SCALE, 10*SCALE},
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{10*SCALE, 10*SCALE},
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{5*SCALE, 5*SCALE},
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{5*SCALE, 5*SCALE},
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{5*SCALE, 5*SCALE},
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{5*SCALE, 5*SCALE},
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{5*SCALE, 5*SCALE},
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{5*SCALE, 5*SCALE},
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{5*SCALE, 5*SCALE},
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{20*SCALE, 20*SCALE}
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};
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// std::vector<Rectangle> rects = {
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// {20*SCALE, 10*SCALE},
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// {20*SCALE, 10*SCALE},
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// {20*SCALE, 20*SCALE},
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// };
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// std::vector<Item> input {
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// {{0, 0}, {0, 20*SCALE}, {10*SCALE, 0}, {0, 0}}
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// };
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std::vector<Item> crasher =
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{
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{
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{-5000000, 8954050},
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{5000000, 8954050},
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{5000000, -45949},
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{4972609, -568549},
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{3500000, -8954050},
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{-3500000, -8954050},
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{-4972609, -568549},
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{-5000000, -45949},
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{-5000000, 8954050},
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},
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{
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{-5000000, 8954050},
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{5000000, 8954050},
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{5000000, -45949},
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{4972609, -568549},
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{3500000, -8954050},
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{-3500000, -8954050},
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{-4972609, -568549},
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{-5000000, -45949},
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{-5000000, 8954050},
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},
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{
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{-5000000, 8954050},
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{5000000, 8954050},
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{5000000, -45949},
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{4972609, -568549},
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{3500000, -8954050},
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{-3500000, -8954050},
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{-4972609, -568549},
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{-5000000, -45949},
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{-5000000, 8954050},
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},
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{
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{-5000000, 8954050},
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{5000000, 8954050},
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{5000000, -45949},
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{4972609, -568549},
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{3500000, -8954050},
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{-3500000, -8954050},
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{-4972609, -568549},
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{-5000000, -45949},
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{-5000000, 8954050},
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},
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{
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{-5000000, 8954050},
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{5000000, 8954050},
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{5000000, -45949},
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{4972609, -568549},
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{3500000, -8954050},
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{-3500000, -8954050},
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{-4972609, -568549},
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{-5000000, -45949},
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{-5000000, 8954050},
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},
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{
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{-5000000, 8954050},
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{5000000, 8954050},
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{5000000, -45949},
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{4972609, -568549},
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{3500000, -8954050},
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{-3500000, -8954050},
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{-4972609, -568549},
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{-5000000, -45949},
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{-5000000, 8954050},
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},
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{
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{-9945219, -3065619},
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{-9781479, -2031780},
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{-9510560, -1020730},
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{-9135450, -43529},
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{-2099999, 14110899},
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{2099999, 14110899},
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{9135450, -43529},
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{9510560, -1020730},
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{9781479, -2031780},
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{9945219, -3065619},
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{10000000, -4110899},
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{9945219, -5156179},
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{9781479, -6190020},
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{9510560, -7201069},
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{9135450, -8178270},
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{8660249, -9110899},
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{8090169, -9988750},
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{7431449, -10802200},
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{6691309, -11542300},
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{5877850, -12201100},
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{5000000, -12771100},
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{4067369, -13246399},
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{3090169, -13621500},
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{2079119, -13892399},
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{1045279, -14056099},
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{0, -14110899},
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{-1045279, -14056099},
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{-2079119, -13892399},
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{-3090169, -13621500},
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{-4067369, -13246399},
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{-5000000, -12771100},
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{-5877850, -12201100},
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{-6691309, -11542300},
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{-7431449, -10802200},
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{-8090169, -9988750},
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{-8660249, -9110899},
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{-9135450, -8178270},
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{-9510560, -7201069},
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{-9781479, -6190020},
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{-9945219, -5156179},
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{-10000000, -4110899},
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{-9945219, -3065619},
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},
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{
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{-9945219, -3065619},
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{-9781479, -2031780},
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{-9510560, -1020730},
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{-9135450, -43529},
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{-2099999, 14110899},
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{2099999, 14110899},
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{9135450, -43529},
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{9510560, -1020730},
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{9781479, -2031780},
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{9945219, -3065619},
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{10000000, -4110899},
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{9945219, -5156179},
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{9781479, -6190020},
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{9510560, -7201069},
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{9135450, -8178270},
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{8660249, -9110899},
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{8090169, -9988750},
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{7431449, -10802200},
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{6691309, -11542300},
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{5877850, -12201100},
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{5000000, -12771100},
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{4067369, -13246399},
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{3090169, -13621500},
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{2079119, -13892399},
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{1045279, -14056099},
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{0, -14110899},
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{-1045279, -14056099},
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{-2079119, -13892399},
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{-3090169, -13621500},
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{-4067369, -13246399},
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{-5000000, -12771100},
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{-5877850, -12201100},
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{-6691309, -11542300},
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{-7431449, -10802200},
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{-8090169, -9988750},
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{-8660249, -9110899},
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{-9135450, -8178270},
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{-9510560, -7201069},
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{-9781479, -6190020},
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{-9945219, -5156179},
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{-10000000, -4110899},
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{-9945219, -3065619},
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},
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{
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{-9945219, -3065619},
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{-9781479, -2031780},
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{-9510560, -1020730},
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{-9135450, -43529},
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{-2099999, 14110899},
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{2099999, 14110899},
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{9135450, -43529},
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{9510560, -1020730},
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{9781479, -2031780},
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{9945219, -3065619},
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{10000000, -4110899},
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{9945219, -5156179},
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{9781479, -6190020},
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{9510560, -7201069},
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{9135450, -8178270},
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{8660249, -9110899},
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{8090169, -9988750},
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{7431449, -10802200},
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{6691309, -11542300},
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{5877850, -12201100},
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{5000000, -12771100},
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{4067369, -13246399},
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{3090169, -13621500},
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{2079119, -13892399},
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{1045279, -14056099},
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{0, -14110899},
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{-1045279, -14056099},
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{-2079119, -13892399},
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{-3090169, -13621500},
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{-4067369, -13246399},
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{-5000000, -12771100},
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{-5877850, -12201100},
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{-6691309, -11542300},
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{-7431449, -10802200},
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{-8090169, -9988750},
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{-8660249, -9110899},
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{-9135450, -8178270},
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{-9510560, -7201069},
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{-9781479, -6190020},
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{-9945219, -5156179},
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{-10000000, -4110899},
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{-9945219, -3065619},
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},
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{
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{-9945219, -3065619},
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{-9781479, -2031780},
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{-9510560, -1020730},
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{-9135450, -43529},
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{-2099999, 14110899},
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{2099999, 14110899},
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{9135450, -43529},
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{9510560, -1020730},
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{9781479, -2031780},
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{9945219, -3065619},
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{10000000, -4110899},
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{9945219, -5156179},
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{9781479, -6190020},
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{9510560, -7201069},
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{9135450, -8178270},
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{8660249, -9110899},
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{8090169, -9988750},
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{7431449, -10802200},
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{6691309, -11542300},
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{5877850, -12201100},
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{5000000, -12771100},
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{4067369, -13246399},
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{3090169, -13621500},
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{2079119, -13892399},
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{1045279, -14056099},
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{0, -14110899},
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{-1045279, -14056099},
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{-2079119, -13892399},
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{-3090169, -13621500},
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{-4067369, -13246399},
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{-5000000, -12771100},
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{-5877850, -12201100},
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{-6691309, -11542300},
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{-7431449, -10802200},
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{-8090169, -9988750},
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{-8660249, -9110899},
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{-9135450, -8178270},
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{-9510560, -7201069},
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{-9781479, -6190020},
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{-9945219, -5156179},
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{-10000000, -4110899},
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{-9945219, -3065619},
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},
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{
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{-9945219, -3065619},
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{-9781479, -2031780},
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{-9510560, -1020730},
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{-9135450, -43529},
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{-2099999, 14110899},
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{2099999, 14110899},
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{9135450, -43529},
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{9510560, -1020730},
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{9781479, -2031780},
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{9945219, -3065619},
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{10000000, -4110899},
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{9945219, -5156179},
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{9781479, -6190020},
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{9510560, -7201069},
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{9135450, -8178270},
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||||
{8660249, -9110899},
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{8090169, -9988750},
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||||
{7431449, -10802200},
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||||
{6691309, -11542300},
|
||||
{5877850, -12201100},
|
||||
{5000000, -12771100},
|
||||
{4067369, -13246399},
|
||||
{3090169, -13621500},
|
||||
{2079119, -13892399},
|
||||
{1045279, -14056099},
|
||||
{0, -14110899},
|
||||
{-1045279, -14056099},
|
||||
{-2079119, -13892399},
|
||||
{-3090169, -13621500},
|
||||
{-4067369, -13246399},
|
||||
{-5000000, -12771100},
|
||||
{-5877850, -12201100},
|
||||
{-6691309, -11542300},
|
||||
{-7431449, -10802200},
|
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{-8090169, -9988750},
|
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{-8660249, -9110899},
|
||||
{-9135450, -8178270},
|
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{-9510560, -7201069},
|
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{-9781479, -6190020},
|
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{-9945219, -5156179},
|
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{-10000000, -4110899},
|
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{-9945219, -3065619},
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},
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{
|
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{-9945219, -3065619},
|
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{-9781479, -2031780},
|
||||
{-9510560, -1020730},
|
||||
{-9135450, -43529},
|
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{-2099999, 14110899},
|
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{2099999, 14110899},
|
||||
{9135450, -43529},
|
||||
{9510560, -1020730},
|
||||
{9781479, -2031780},
|
||||
{9945219, -3065619},
|
||||
{10000000, -4110899},
|
||||
{9945219, -5156179},
|
||||
{9781479, -6190020},
|
||||
{9510560, -7201069},
|
||||
{9135450, -8178270},
|
||||
{8660249, -9110899},
|
||||
{8090169, -9988750},
|
||||
{7431449, -10802200},
|
||||
{6691309, -11542300},
|
||||
{5877850, -12201100},
|
||||
{5000000, -12771100},
|
||||
{4067369, -13246399},
|
||||
{3090169, -13621500},
|
||||
{2079119, -13892399},
|
||||
{1045279, -14056099},
|
||||
{0, -14110899},
|
||||
{-1045279, -14056099},
|
||||
{-2079119, -13892399},
|
||||
{-3090169, -13621500},
|
||||
{-4067369, -13246399},
|
||||
{-5000000, -12771100},
|
||||
{-5877850, -12201100},
|
||||
{-6691309, -11542300},
|
||||
{-7431449, -10802200},
|
||||
{-8090169, -9988750},
|
||||
{-8660249, -9110899},
|
||||
{-9135450, -8178270},
|
||||
{-9510560, -7201069},
|
||||
{-9781479, -6190020},
|
||||
{-9945219, -5156179},
|
||||
{-10000000, -4110899},
|
||||
{-9945219, -3065619},
|
||||
},
|
||||
{
|
||||
{-9945219, -3065619},
|
||||
{-9781479, -2031780},
|
||||
{-9510560, -1020730},
|
||||
{-9135450, -43529},
|
||||
{-2099999, 14110899},
|
||||
{2099999, 14110899},
|
||||
{9135450, -43529},
|
||||
{9510560, -1020730},
|
||||
{9781479, -2031780},
|
||||
{9945219, -3065619},
|
||||
{10000000, -4110899},
|
||||
{9945219, -5156179},
|
||||
{9781479, -6190020},
|
||||
{9510560, -7201069},
|
||||
{9135450, -8178270},
|
||||
{8660249, -9110899},
|
||||
{8090169, -9988750},
|
||||
{7431449, -10802200},
|
||||
{6691309, -11542300},
|
||||
{5877850, -12201100},
|
||||
{5000000, -12771100},
|
||||
{4067369, -13246399},
|
||||
{3090169, -13621500},
|
||||
{2079119, -13892399},
|
||||
{1045279, -14056099},
|
||||
{0, -14110899},
|
||||
{-1045279, -14056099},
|
||||
{-2079119, -13892399},
|
||||
{-3090169, -13621500},
|
||||
{-4067369, -13246399},
|
||||
{-5000000, -12771100},
|
||||
{-5877850, -12201100},
|
||||
{-6691309, -11542300},
|
||||
{-7431449, -10802200},
|
||||
{-8090169, -9988750},
|
||||
{-8660249, -9110899},
|
||||
{-9135450, -8178270},
|
||||
{-9510560, -7201069},
|
||||
{-9781479, -6190020},
|
||||
{-9945219, -5156179},
|
||||
{-10000000, -4110899},
|
||||
{-9945219, -3065619},
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},
|
||||
{
|
||||
{-9945219, -3065619},
|
||||
{-9781479, -2031780},
|
||||
{-9510560, -1020730},
|
||||
{-9135450, -43529},
|
||||
{-2099999, 14110899},
|
||||
{2099999, 14110899},
|
||||
{9135450, -43529},
|
||||
{9510560, -1020730},
|
||||
{9781479, -2031780},
|
||||
{9945219, -3065619},
|
||||
{10000000, -4110899},
|
||||
{9945219, -5156179},
|
||||
{9781479, -6190020},
|
||||
{9510560, -7201069},
|
||||
{9135450, -8178270},
|
||||
{8660249, -9110899},
|
||||
{8090169, -9988750},
|
||||
{7431449, -10802200},
|
||||
{6691309, -11542300},
|
||||
{5877850, -12201100},
|
||||
{5000000, -12771100},
|
||||
{4067369, -13246399},
|
||||
{3090169, -13621500},
|
||||
{2079119, -13892399},
|
||||
{1045279, -14056099},
|
||||
{0, -14110899},
|
||||
{-1045279, -14056099},
|
||||
{-2079119, -13892399},
|
||||
{-3090169, -13621500},
|
||||
{-4067369, -13246399},
|
||||
{-5000000, -12771100},
|
||||
{-5877850, -12201100},
|
||||
{-6691309, -11542300},
|
||||
{-7431449, -10802200},
|
||||
{-8090169, -9988750},
|
||||
{-8660249, -9110899},
|
||||
{-9135450, -8178270},
|
||||
{-9510560, -7201069},
|
||||
{-9781479, -6190020},
|
||||
{-9945219, -5156179},
|
||||
{-10000000, -4110899},
|
||||
{-9945219, -3065619},
|
||||
},
|
||||
{
|
||||
{-18000000, -1000000},
|
||||
{-15000000, 22000000},
|
||||
{-11000000, 26000000},
|
||||
{11000000, 26000000},
|
||||
{15000000, 22000000},
|
||||
{18000000, -1000000},
|
||||
{18000000, -26000000},
|
||||
{-18000000, -26000000},
|
||||
{-18000000, -1000000},
|
||||
},
|
||||
{60*SCALE, 200*SCALE},
|
||||
{60*SCALE, 200*SCALE}
|
||||
};
|
||||
|
||||
std::vector<Item> proba = {
|
||||
{
|
||||
Rectangle(100, 2)
|
||||
},
|
||||
{
|
||||
Rectangle(100, 2)
|
||||
},
|
||||
{
|
||||
Rectangle(100, 2)
|
||||
},
|
||||
{
|
||||
Rectangle(10, 10)
|
||||
},
|
||||
};
|
||||
|
||||
proba[0].rotate(Pi/3);
|
||||
proba[1].rotate(Pi-Pi/3);
|
||||
|
||||
// std::vector<Item> input(25, Rectangle(70*SCALE, 10*SCALE));
|
||||
std::vector<Item> input;
|
||||
input.insert(input.end(), prusaParts().begin(), prusaParts().end());
|
||||
// input.insert(input.end(), prusaExParts().begin(), prusaExParts().end());
|
||||
@ -544,7 +64,7 @@ void arrangeRectangles() {
|
||||
// input.insert(input.end(), proba.begin(), proba.end());
|
||||
// input.insert(input.end(), crasher.begin(), crasher.end());
|
||||
|
||||
Box bin(250*SCALE, 210*SCALE);
|
||||
// Box bin(250*SCALE, 210*SCALE);
|
||||
// PolygonImpl bin = {
|
||||
// {
|
||||
// {25*SCALE, 0},
|
||||
@ -560,9 +80,11 @@ void arrangeRectangles() {
|
||||
// {}
|
||||
// };
|
||||
|
||||
_Circle<PointImpl> bin({0, 0}, 125*SCALE);
|
||||
|
||||
auto min_obj_distance = static_cast<Coord>(0*SCALE);
|
||||
|
||||
using Placer = strategies::_NofitPolyPlacer<PolygonImpl, Box>;
|
||||
using Placer = strategies::_NofitPolyPlacer<PolygonImpl, decltype(bin)>;
|
||||
using Packer = Arranger<Placer, FirstFitSelection>;
|
||||
|
||||
Packer arrange(bin, min_obj_distance);
|
||||
@ -571,9 +93,9 @@ void arrangeRectangles() {
|
||||
pconf.alignment = Placer::Config::Alignment::CENTER;
|
||||
pconf.starting_point = Placer::Config::Alignment::CENTER;
|
||||
pconf.rotations = {0.0/*, Pi/2.0, Pi, 3*Pi/2*/};
|
||||
pconf.accuracy = 0.5f;
|
||||
pconf.accuracy = 1.0f;
|
||||
|
||||
// auto bincenter = ShapeLike::boundingBox(bin).center();
|
||||
// auto bincenter = ShapeLike::boundingBox<PolygonImpl>(bin).center();
|
||||
// pconf.object_function = [&bin, bincenter](
|
||||
// Placer::Pile pile, const Item& item,
|
||||
// double /*area*/, double norm, double penality) {
|
||||
@ -660,10 +182,7 @@ void arrangeRectangles() {
|
||||
// score = pl::distance(ibb.center(), bigbb.center()) / norm;
|
||||
// }
|
||||
|
||||
// // If it does not fit into the print bed we will beat it
|
||||
// // with a large penality. If we would not do this, there would be only
|
||||
// // one big pile that doesn't care whether it fits onto the print bed.
|
||||
// if(!NfpPlacer::wouldFit(fullbb, bin)) score = 2*penality - score;
|
||||
// if(!Placer::wouldFit(fullbb, bin)) score += norm;
|
||||
|
||||
// return score;
|
||||
// };
|
||||
|
||||
@ -109,7 +109,7 @@ public:
|
||||
inline void radius(double r) { radius_ = r; }
|
||||
|
||||
inline double area() const BP2D_NOEXCEPT {
|
||||
return 2.0*Pi*radius_;
|
||||
return 2.0*Pi*radius_*radius_;
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
@ -1,16 +1,19 @@
|
||||
#ifndef NOFITPOLY_HPP
|
||||
#define NOFITPOLY_HPP
|
||||
|
||||
#include <cassert>
|
||||
#include <random>
|
||||
|
||||
#ifndef NDEBUG
|
||||
#include <iostream>
|
||||
#endif
|
||||
#include "placer_boilerplate.hpp"
|
||||
#include "../geometry_traits_nfp.hpp"
|
||||
#include "libnest2d/optimizer.hpp"
|
||||
#include <cassert>
|
||||
|
||||
#include "tools/svgtools.hpp"
|
||||
|
||||
|
||||
namespace libnest2d { namespace strategies {
|
||||
|
||||
template<class RawShape>
|
||||
@ -161,12 +164,11 @@ template<class RawShape> class EdgeCache {
|
||||
}
|
||||
|
||||
size_t stride(const size_t N) const {
|
||||
using std::ceil;
|
||||
using std::round;
|
||||
using std::pow;
|
||||
|
||||
return static_cast<Coord>(
|
||||
std::round(N/std::pow(N, std::pow(accuracy_, 1.0/3.0)))
|
||||
round(N/pow(N, pow(accuracy_, 1.0/3.0)))
|
||||
);
|
||||
}
|
||||
|
||||
@ -177,6 +179,7 @@ template<class RawShape> class EdgeCache {
|
||||
const auto S = stride(N);
|
||||
|
||||
contour_.corners.reserve(N / S + 1);
|
||||
contour_.corners.emplace_back(0.0);
|
||||
auto N_1 = N-1;
|
||||
contour_.corners.emplace_back(0.0);
|
||||
for(size_t i = 0; i < N_1; i += S) {
|
||||
@ -190,8 +193,8 @@ template<class RawShape> class EdgeCache {
|
||||
if(!hc.corners.empty()) return;
|
||||
|
||||
const auto N = hc.distances.size();
|
||||
const auto S = stride(N);
|
||||
auto N_1 = N-1;
|
||||
const auto S = stride(N);
|
||||
hc.corners.reserve(N / S + 1);
|
||||
hc.corners.emplace_back(0.0);
|
||||
for(size_t i = 0; i < N_1; i += S) {
|
||||
@ -339,7 +342,7 @@ Nfp::Shapes<RawShape> nfp( const Container& polygons,
|
||||
|
||||
Nfp::Shapes<RawShape> nfps;
|
||||
|
||||
//int pi = 0;
|
||||
// int pi = 0;
|
||||
for(Item& sh : polygons) {
|
||||
auto subnfp_r = Nfp::noFitPolygon<NfpLevel::CONVEX_ONLY>(
|
||||
sh.transformedShape(), trsh.transformedShape());
|
||||
@ -441,6 +444,63 @@ Nfp::Shapes<RawShape> nfp( const Container& polygons,
|
||||
// return nfps;
|
||||
}
|
||||
|
||||
template<class RawShape>
|
||||
_Circle<TPoint<RawShape>> minimizeCircle(const RawShape& sh) {
|
||||
using sl = ShapeLike; using pl = PointLike;
|
||||
using Point = TPoint<RawShape>;
|
||||
using Coord = TCoord<Point>;
|
||||
|
||||
auto bb = sl::boundingBox(sh);
|
||||
auto capprx = bb.center();
|
||||
auto rapprx = pl::distance(bb.minCorner(), bb.maxCorner());
|
||||
|
||||
auto& ctr = sl::getContour(sh);
|
||||
|
||||
opt::StopCriteria stopcr;
|
||||
stopcr.max_iterations = 100;
|
||||
stopcr.relative_score_difference = 1e-3;
|
||||
opt::TOptimizer<opt::Method::L_SUBPLEX> solver(stopcr);
|
||||
|
||||
std::vector<double> dists(ctr.size(), 0);
|
||||
|
||||
auto result = solver.optimize_min(
|
||||
[capprx, rapprx, &ctr, &dists](double xf, double yf) {
|
||||
auto xt = Coord( std::round(getX(capprx) + rapprx*xf) );
|
||||
auto yt = Coord( std::round(getY(capprx) + rapprx*yf) );
|
||||
|
||||
Point centr(xt, yt);
|
||||
|
||||
unsigned i = 0;
|
||||
for(auto v : ctr) {
|
||||
dists[i++] = pl::distance(v, centr);
|
||||
}
|
||||
|
||||
auto mit = std::max_element(dists.begin(), dists.end());
|
||||
|
||||
assert(mit != dists.end());
|
||||
|
||||
return *mit;
|
||||
},
|
||||
opt::initvals(0.0, 0.0),
|
||||
opt::bound(-1.0, 1.0), opt::bound(-1.0, 1.0)
|
||||
);
|
||||
|
||||
double oxf = std::get<0>(result.optimum);
|
||||
double oyf = std::get<1>(result.optimum);
|
||||
auto xt = Coord( std::round(getX(capprx) + rapprx*oxf) );
|
||||
auto yt = Coord( std::round(getY(capprx) + rapprx*oyf) );
|
||||
|
||||
Point cc(xt, yt);
|
||||
auto r = result.score;
|
||||
|
||||
return {cc, r};
|
||||
}
|
||||
|
||||
template<class RawShape>
|
||||
_Circle<TPoint<RawShape>> boundingCircle(const RawShape& sh) {
|
||||
return minimizeCircle(sh);
|
||||
}
|
||||
|
||||
template<class RawShape, class TBin = _Box<TPoint<RawShape>>>
|
||||
class _NofitPolyPlacer: public PlacerBoilerplate<_NofitPolyPlacer<RawShape, TBin>,
|
||||
RawShape, TBin, NfpPConfig<RawShape>> {
|
||||
@ -512,11 +572,7 @@ public:
|
||||
bool static inline wouldFit(const RawShape& chull,
|
||||
const _Circle<Vertex>& bin)
|
||||
{
|
||||
auto bb = sl::boundingBox(chull);
|
||||
auto d = bin.center() - bb.center();
|
||||
auto chullcpy = chull;
|
||||
sl::translate(chullcpy, d);
|
||||
return sl::isInside<RawShape>(chullcpy, bin);
|
||||
return boundingCircle(chull).radius() < bin.radius();
|
||||
}
|
||||
|
||||
PackResult trypack(Item& item) {
|
||||
@ -574,8 +630,9 @@ public:
|
||||
|
||||
auto getNfpPoint = [&ecache](const Optimum& opt)
|
||||
{
|
||||
return opt.hidx < 0? ecache[opt.nfpidx].coords(opt.relpos) :
|
||||
auto ret = opt.hidx < 0? ecache[opt.nfpidx].coords(opt.relpos) :
|
||||
ecache[opt.nfpidx].coords(opt.hidx, opt.relpos);
|
||||
return ret;
|
||||
};
|
||||
|
||||
Nfp::Shapes<RawShape> pile;
|
||||
@ -595,7 +652,7 @@ public:
|
||||
[this, &merged_pile](
|
||||
Nfp::Shapes<RawShape>& /*pile*/,
|
||||
const Item& item,
|
||||
double occupied_area,
|
||||
double occupied_area,
|
||||
double norm,
|
||||
double /*penality*/)
|
||||
{
|
||||
@ -751,14 +808,37 @@ public:
|
||||
}
|
||||
|
||||
inline void clearItems() {
|
||||
finalAlign(bin_);
|
||||
Base::clearItems();
|
||||
}
|
||||
|
||||
private:
|
||||
|
||||
inline void finalAlign(const RawShape& pbin) {
|
||||
auto bbin = sl::boundingBox(pbin);
|
||||
finalAlign(bbin);
|
||||
}
|
||||
|
||||
inline void finalAlign(_Circle<TPoint<RawShape>> cbin) {
|
||||
if(items_.empty()) return;
|
||||
|
||||
Nfp::Shapes<RawShape> m;
|
||||
m.reserve(items_.size());
|
||||
for(Item& item : items_) m.emplace_back(item.transformedShape());
|
||||
|
||||
auto c = boundingCircle(sl::convexHull(m));
|
||||
|
||||
auto d = cbin.center() - c.center();
|
||||
for(Item& item : items_) item.translate(d);
|
||||
}
|
||||
|
||||
inline void finalAlign(Box bbin) {
|
||||
Nfp::Shapes<RawShape> m;
|
||||
m.reserve(items_.size());
|
||||
for(Item& item : items_) m.emplace_back(item.transformedShape());
|
||||
auto&& bb = sl::boundingBox<RawShape>(m);
|
||||
|
||||
Vertex ci, cb;
|
||||
auto bbin = sl::boundingBox<RawShape>(bin_);
|
||||
|
||||
switch(config_.alignment) {
|
||||
case Config::Alignment::CENTER: {
|
||||
@ -790,12 +870,8 @@ public:
|
||||
|
||||
auto d = cb - ci;
|
||||
for(Item& item : items_) item.translate(d);
|
||||
|
||||
Base::clearItems();
|
||||
}
|
||||
|
||||
private:
|
||||
|
||||
void setInitialPosition(Item& item) {
|
||||
Box&& bb = item.boundingBox();
|
||||
Vertex ci, cb;
|
||||
|
||||
@ -99,6 +99,43 @@ TEST(BasicFunctionality, creationAndDestruction)
|
||||
|
||||
}
|
||||
|
||||
TEST(GeometryAlgorithms, boundingCircle) {
|
||||
using namespace libnest2d;
|
||||
using strategies::boundingCircle;
|
||||
|
||||
PolygonImpl p = {{{0, 10}, {10, 0}, {0, -10}, {0, 10}}, {}};
|
||||
_Circle<PointImpl> c = boundingCircle<PolygonImpl>(p);
|
||||
|
||||
ASSERT_EQ(c.center().X, 0);
|
||||
ASSERT_EQ(c.center().Y, 0);
|
||||
ASSERT_DOUBLE_EQ(c.radius(), 10);
|
||||
|
||||
ShapeLike::translate(p, PointImpl{10, 10});
|
||||
c = boundingCircle<PolygonImpl>(p);
|
||||
|
||||
ASSERT_EQ(c.center().X, 10);
|
||||
ASSERT_EQ(c.center().Y, 10);
|
||||
ASSERT_DOUBLE_EQ(c.radius(), 10);
|
||||
|
||||
auto parts = prusaParts();
|
||||
|
||||
int i = 0;
|
||||
for(auto& part : parts) {
|
||||
c = boundingCircle(part.transformedShape());
|
||||
if(std::isnan(c.radius())) std::cout << "fail: radius is nan" << std::endl;
|
||||
|
||||
else for(auto v : ShapeLike::getContour(part.transformedShape()) ) {
|
||||
auto d = PointLike::distance(v, c.center());
|
||||
if(d > c.radius() ) {
|
||||
auto e = std::abs( 1.0 - d/c.radius());
|
||||
ASSERT_LE(e, 1e-3);
|
||||
}
|
||||
}
|
||||
i++;
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
TEST(GeometryAlgorithms, Distance) {
|
||||
using namespace libnest2d;
|
||||
|
||||
|
||||
@ -102,9 +102,9 @@ using SpatIndex = bgi::rtree< SpatElement, bgi::rstar<16, 4> >;
|
||||
|
||||
std::tuple<double /*score*/, Box /*farthest point from bin center*/>
|
||||
objfunc(const PointImpl& bincenter,
|
||||
double /*bin_area*/,
|
||||
double bin_area,
|
||||
ShapeLike::Shapes<PolygonImpl>& pile, // The currently arranged pile
|
||||
double /*pile_area*/,
|
||||
double pile_area,
|
||||
const Item &item,
|
||||
double norm, // A norming factor for physical dimensions
|
||||
std::vector<double>& areacache, // pile item areas will be cached
|
||||
@ -115,12 +115,16 @@ objfunc(const PointImpl& bincenter,
|
||||
using pl = PointLike;
|
||||
using sl = ShapeLike;
|
||||
|
||||
static const double BIG_ITEM_TRESHOLD = 0.2;
|
||||
static const double BIG_ITEM_TRESHOLD = 0.04;
|
||||
static const double ROUNDNESS_RATIO = 0.5;
|
||||
static const double DENSITY_RATIO = 1.0 - ROUNDNESS_RATIO;
|
||||
|
||||
// We will treat big items (compared to the print bed) differently
|
||||
auto normarea = [norm](double area) { return std::sqrt(area)/norm; };
|
||||
|
||||
auto isBig = [&areacache, bin_area](double a) {
|
||||
bool t = areacache.empty() ? true : a > 0.5*areacache.front();
|
||||
return a/bin_area > BIG_ITEM_TRESHOLD || t;
|
||||
};
|
||||
|
||||
// If a new bin has been created:
|
||||
if(pile.size() < areacache.size()) {
|
||||
@ -133,7 +137,7 @@ objfunc(const PointImpl& bincenter,
|
||||
for(auto& p : pile) {
|
||||
if(idx == areacache.size()) {
|
||||
areacache.emplace_back(sl::area(p));
|
||||
if(normarea(areacache[idx]) > BIG_ITEM_TRESHOLD)
|
||||
if(isBig(areacache[idx]))
|
||||
spatindex.insert({sl::boundingBox(p), idx});
|
||||
}
|
||||
|
||||
@ -157,14 +161,10 @@ objfunc(const PointImpl& bincenter,
|
||||
boost::geometry::convert(boostbb, bigbb);
|
||||
}
|
||||
|
||||
// The size indicator of the candidate item. This is not the area,
|
||||
// but almost...
|
||||
double item_normarea = normarea(item.area());
|
||||
|
||||
// Will hold the resulting score
|
||||
double score = 0;
|
||||
|
||||
if(item_normarea > BIG_ITEM_TRESHOLD) {
|
||||
if(isBig(item.area())) {
|
||||
// This branch is for the bigger items..
|
||||
// Here we will use the closest point of the item bounding box to
|
||||
// the already arranged pile. So not the bb center nor the a choosen
|
||||
@ -223,10 +223,9 @@ objfunc(const PointImpl& bincenter,
|
||||
// The final mix of the score is the balance between the distance
|
||||
// from the full pile center, the pack density and the
|
||||
// alignment with the neigbours
|
||||
auto C = 0.33;
|
||||
score = C * dist + C * density + C * alignment_score;
|
||||
score = 0.4 * dist + 0.4 * density + 0.2 * alignment_score;
|
||||
|
||||
} else if( item_normarea < BIG_ITEM_TRESHOLD && spatindex.empty()) {
|
||||
} else if( !isBig(item.area()) && spatindex.empty()) {
|
||||
// If there are no big items, only small, we should consider the
|
||||
// density here as well to not get silly results
|
||||
auto bindist = pl::distance(ibb.center(), bincenter) / norm;
|
||||
@ -349,17 +348,26 @@ public:
|
||||
auto result = objfunc(bin.center(), bin_area_, pile,
|
||||
pile_area, item, norm, areacache_, rtree_);
|
||||
double score = std::get<0>(result);
|
||||
|
||||
// Circle fitting detection is very rough at the moment but
|
||||
// we still need something that tells how badly the arrangement
|
||||
// misses the print bed.
|
||||
auto& fullbb = std::get<1>(result);
|
||||
auto bbr = 0.5*PointLike::distance(fullbb.minCorner(),
|
||||
fullbb.maxCorner());
|
||||
auto diff = bbr - bin.radius();
|
||||
|
||||
if(diff > 0) score += std::pow(diff, 2) / norm;
|
||||
auto d = PointLike::distance(fullbb.minCorner(),
|
||||
fullbb.maxCorner());
|
||||
auto diff = d - 2*bin.radius();
|
||||
|
||||
if(diff > 0) {
|
||||
if( item.area() > 0.01*bin_area_ && item.vertexCount() < 20) {
|
||||
pile.emplace_back(item.transformedShape());
|
||||
auto chull = ShapeLike::convexHull(pile);
|
||||
pile.pop_back();
|
||||
|
||||
auto C = strategies::boundingCircle(chull);
|
||||
auto rdiff = C.radius() - bin.radius();
|
||||
|
||||
if(rdiff > 0) {
|
||||
score += std::pow(rdiff, 3) / norm;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return score;
|
||||
};
|
||||
@ -695,6 +703,8 @@ bool arrange(Model &model, coordf_t min_obj_distance,
|
||||
}
|
||||
};
|
||||
|
||||
if(result.empty()) return false;
|
||||
|
||||
if(first_bin_only) {
|
||||
applyResult(result.front(), 0, shapemap);
|
||||
} else {
|
||||
|
||||
Loading…
Reference in New Issue
Block a user