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Commit 4b9e8b61 authored by tolgayurt's avatar tolgayurt
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mysite/.idea/workspace.xml
+ 160
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View file @ 4b9e8b61
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......@@ -16521,10 +16522,24 @@
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......@@ -16745,7 +16775,7 @@
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<item name="" type="442cc68d:ScopeViewTreeModel$RootNode" />
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......@@ -17084,9 +17114,10 @@
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\ No newline at end of file
mysite/plots/avl_tree.py
+ 0
− 3
View file @ 4b9e8b61
# AVl Quelle:https://www.programiz.com/dsa/avl-tree
# AVL tree implementation in Python
import sys
......
mysite/plots/dataset_creator.py
+ 27
− 25
View file @ 4b9e8b61
......@@ -4,15 +4,14 @@ from plots.packing_algo import ConvexPolygon, pack_polygons, truncate, Rectangul
from plots.polygon_creator import voronoi_polygons_wrapper, rectangle_cutter
# def build_aprox_factors():
def build_dataset_with_rectangle_cutter(rect_width: float, rect_height, repetition, cut_list=[], angle_steps=90, cut_min=1,
cut_max=1, cut_steps=1, intervals=[0, 0.01, 0.05, 1], weights=[0, 0, 0.5, 1],save_container=True):
cut_numbers=[]
def build_dataset_with_rectangle_cutter(rect_width: float, rect_height, repetition, cut_list=[], angle_steps=90,
cut_min=1,
cut_max=1, cut_steps=1, intervals=[0, 0.01, 0.05, 1], weights=[0, 0, 0.5, 1],
save_container=True, create_plots=True):
cut_numbers = []
data_dict_list = []
if cut_list:
cut_numbers= cut_list
cut_numbers = cut_list
else:
if cut_min > cut_max:
cut_max = cut_min
......@@ -23,13 +22,15 @@ def build_dataset_with_rectangle_cutter(rect_width: float, rect_height, repetiti
for n in range(0, repetition):
cutted_polygons = rectangle_cutter(rect_width, rect_height, cut_count, intervals=intervals, weights=weights)
cutted_polygons_lists.append(cutted_polygons)
dict_data = collect_rect_containers_data(rect_width, rect_height, cutted_polygons_lists, angle_steps,save_container)
dict_data = collect_rect_containers_data(rect_width, rect_height, cutted_polygons_lists, angle_steps,
save_container, create_plots=True)
data_dict_list.append(dict_data)
return data_dict_list
def build_dataset_with_voronoi(rect_width, rect_height, repetition, cut_list=[], cut_min=5, cut_max=5, cut_steps=1, angle_steps=90, save_container=True):
cut_numbers=[]
def build_dataset_with_voronoi(rect_width, rect_height, repetition, cut_list=[], cut_min=5, cut_max=5, cut_steps=1,
angle_steps=90, save_container=True, create_plots=True):
cut_numbers = []
data_dict_list = []
if cut_list:
cut_numbers = cut_list
......@@ -43,13 +44,14 @@ def build_dataset_with_voronoi(rect_width, rect_height, repetition, cut_list=[],
for n in range(0, repetition):
cutted_polygons = voronoi_polygons_wrapper(rect_width, rect_height, cut_count)
cutted_polygons_lists.append(cutted_polygons)
dict_data = collect_rect_containers_data(rect_width, rect_height, cutted_polygons_lists, angle_steps,save_container)
dict_data = collect_rect_containers_data(rect_width, rect_height, cutted_polygons_lists, angle_steps,
save_container, create_plots=True)
data_dict_list.append(dict_data)
return data_dict_list
def collect_rect_containers_data(rect_width: float, rect_height: float, cutted_polygons_lists: [[ConvexPolygon]],
angle_steps=90, save_container=True) -> {str, list}:
angle_steps=90, save_container=True, create_plots=True) -> {str, list}:
opt_area = rect_width * rect_height
opt_area_list = []
area_list = []
......@@ -61,7 +63,7 @@ def collect_rect_containers_data(rect_width: float, rect_height: float, cutted_p
polygon_count_list = []
end_container_list_plots = []
for polygons in cutted_polygons_lists:
cc = ConvexContainer(polygons, steps=angle_steps)
cc = ConvexContainer(polygons, steps=angle_steps, build_plots=create_plots)
end_container = cc.smallest_rectangular_container
end_container_angle_0 = cc.angle_0_rectangular_container
......@@ -69,13 +71,13 @@ def collect_rect_containers_data(rect_width: float, rect_height: float, cutted_p
c_not_opt_area = end_container.container_not_clipped_area
c_not_r_area = end_container_angle_0.container_area
c_not_r_not_opt_area = end_container_angle_0.container_not_clipped_area
area_list.append(truncate(c_area, 1))
area_div_list.append(truncate(c_area / opt_area, 1))
not_clipped_area_list.append(truncate(c_not_opt_area, 1))
not_clipped_area_div_list.append(truncate(c_not_opt_area / opt_area, 1))
area_list.append(c_area)
area_div_list.append(c_area / opt_area)
not_clipped_area_list.append(c_not_opt_area)
not_clipped_area_div_list.append(c_not_opt_area / opt_area)
angle_0_area_div_list.append(truncate(c_not_r_area / opt_area, 1))
angle_0_not_clipped_area_div_list.append(truncate(c_not_r_not_opt_area / opt_area, 1))
angle_0_area_div_list.append(c_not_r_area / opt_area)
angle_0_not_clipped_area_div_list.append(c_not_r_not_opt_area / opt_area)
opt_area_list.append(opt_area)
polygon_count_list.append(len(polygons))
if save_container:
......@@ -88,7 +90,7 @@ def collect_rect_containers_data(rect_width: float, rect_height: float, cutted_p
'opt-area': opt_area_list,
'polygon count': polygon_count_list}
if end_container_list_plots:
rect_containers_data_dict['End-Container']=end_container_list_plots
rect_containers_data_dict['End-Container'] = end_container_list_plots
return rect_containers_data_dict
......@@ -107,8 +109,8 @@ def collect_rect_containers_data(rect_width: float, rect_height: float, cutted_p
# average = sum(list_optimal_areas) / len(list_optimal_areas)
# average_list.append((rep, average))
# return average_list
#
#
# # deviation=0.05, accept=10
# def find_repition_factor_rectangle_cutter(cut, rep_high, deviation=0.05, accept_number=10, rep_low=1, rep_steps=1,
# display_flag=True, intervals=[0, 0.01, 0.05, 1], weights=[0, 0, 0.5, 1]):
......@@ -120,16 +122,16 @@ def collect_rect_containers_data(rect_width: float, rect_height: float, cutted_p
# average_top_bound = average_canidate + average_canidate * deviation
# average_bot_bound = average_canidate - average_canidate * deviation
# for rep in range(rep_low, rep_high + rep_steps, rep_steps):
#
# data = build_dataset_with_rectangle_cutter(1000, 1000, rep, cut_min=cut, cut_max=cut, cut_steps=1,
# intervals=[0, 0.01, 0.05, 1], weights=[0, 0, 0.5, 1])
# df = pd.DataFrame(data[0])
# if display_flag:
# display(df.sort_values(by="area", ascending=False))
#
# list_optimal_areas = df["area/opt_area"].tolist()
# average = sum(list_optimal_areas) / len(list_optimal_areas)
#
# if average_bot_bound <= average <= average_top_bound:
# accept_counter -= 1
# else:
......
mysite/plots/templates/plots/index.html
+ 3
− 3
View file @ 4b9e8b61
......@@ -49,7 +49,7 @@
<div>
<form action="/packing_rect_container/" target="_blank" method="get">
{% csrf_token %}
<label for="pack_rect_container"><b>Packing Rectengular Container</b></label>
<label for="pack_rect_container"><b>Packing axis-parallel Rectengular Container</b></label>
<input id="pack_rect_container" type="hidden" name="pack_polygon" value="test">
<button type="submit" onclick="packPolygons()">pack</button>
</form>
......@@ -57,7 +57,7 @@
<div>
<form action="/packing_rotated_rect_container/" target="_blank" method="get">
{% csrf_token %}
<label for="pack_rotated_rect_container"><b>Packing Rotated Rectengular Container</b></label>
<label for="pack_rotated_rect_container"><b>Packing Rectengular Container with rotating optimization 0, 90, 180, 270</b></label>
<input id="pack_rotated_rect_container" type="hidden" name="pack_polygon" value="test">
<button type="submit" onclick="packPolygons()">pack</button>
</form>
......@@ -65,7 +65,7 @@
<div>
<form action="/packing_convex_container/" target="_blank" method="post">
{% csrf_token %}
<label for="pack_convex_container"><b>Packing Convex Container (degree between 1-360)</b></label>
<label for="pack_convex_container"><b>Packing Rectangular Container (degree between 1-360)</b></label>
<input id="pack_convex_container" type="number" min="1" max="360" name="angle" value=10>
<button type="submit">pack</button>
</form>
......
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