def union_negative_overlap_sb(parent, child, siblings):
sibling_polygons = mp.map_layoutsamples_to_geometricobjects(
siblings, shape_name="shape")
child_polygon = mp.map_layoutsamples_to_geometricobjects(
[child], shape_name="shape")[0]
return -(cascaded_union([
sibling_polygon.intersection(child_polygon)
for sibling_polygon in sibling_polygons
]).area)
def combinatory_surface_ratio_absolute(parent,siblings,target_ratio):
if not 0<= target_ratio <=1:
raise ValueError("Target ration should be between 0 and 1, it's values was: ",target_ratio)
sibling_polygons=mp.map_layoutsamples_to_geometricobjects(siblings,shape_name="shape")
parent_polygon=mp.map_layoutsamples_to_geometricobjects([parent],shape_name="shape")[0]
sibling_union=cascaded_union(sibling_polygons)
area_siblings_parent= sibling_union.intersection(parent_polygon).area
area_diff=np.abs(area_siblings_parent/parent_polygon.area-target_ratio)
return -area_diff
def centroid_dist_sb(parent,child,siblings,dist_metric=np.linalg.norm):
sibling_polygons=mp.map_layoutsamples_to_geometricobjects(siblings,shape_name="shape")
child_polygon=mp.map_layoutsamples_to_geometricobjects([child],shape_name="shape")
parent_polygon_centr=np.array(mp.map_layoutsample_to_geometricobject(parent,shape_name="shape")[0].centroid)
sibling_polygons_group_centr = np.array(MultiPolygon(sibling_polygons).centroid)
sibling_child_polygons_group_centr = np.array(MultiPolygon(sibling_polygons+child_polygon).centroid)
centr_dist_without_child=dist_metric(sibling_polygons_group_centr-parent_polygon_centr)
centr_dist_with_child=dist_metric(sibling_child_polygons_group_centr-parent_polygon_centr)
#if the distance grows by adding a child it is bad
return centr_dist_without_child-centr_dist_with_child
def combinatory_surface_ratio_absolute(parent, siblings, target_ratio):
if not 0 <= target_ratio <= 1:
raise ValueError(
"Target ration should be between 0 and 1, it's values was: ",
target_ratio)
sibling_polygons = mp.map_layoutsamples_to_geometricobjects(
siblings, shape_name="shape")
parent_polygon = mp.map_layoutsamples_to_geometricobjects(
[parent], shape_name="shape")[0]
sibling_union = cascaded_union(sibling_polygons)
area_siblings_parent = sibling_union.intersection(parent_polygon).area
area_diff = np.abs(area_siblings_parent / parent_polygon.area -
target_ratio)
return -area_diff
def draw_node_sample_tree(root, color, ax=None):
samples = root.get_flat_list()
polygons = mp.map_layoutsamples_to_geometricobjects(samples, "shape")
draw_polygons(polygons=polygons,
ax=ax,
color=color,
size=1.3,
set_range=True)
def centroid_dist_sb(parent, child, siblings, dist_metric=np.linalg.norm):
sibling_polygons = mp.map_layoutsamples_to_geometricobjects(
siblings, shape_name="shape")
child_polygon = mp.map_layoutsamples_to_geometricobjects(
[child], shape_name="shape")
parent_polygon_centr = np.array(
mp.map_layoutsample_to_geometricobject(parent,
shape_name="shape")[0].centroid)
sibling_polygons_group_centr = np.array(
MultiPolygon(sibling_polygons).centroid)
sibling_child_polygons_group_centr = np.array(
MultiPolygon(sibling_polygons + child_polygon).centroid)
centr_dist_without_child = dist_metric(sibling_polygons_group_centr -
parent_polygon_centr)
centr_dist_with_child = dist_metric(sibling_child_polygons_group_centr -
parent_polygon_centr)
#if the distance grows by adding a child it is bad
return centr_dist_without_child - centr_dist_with_child
def closest_side_alignment_norm(sample0,sample1):
polygons=mp.map_layoutsamples_to_geometricobjects([sample0,sample1],shape_name="shape")
min_dist=float("inf")
min_l0=None
min_l1=None
for p00,p01 in ut.pairwise(polygons[0].exterior.coords):
for p10,p11 in ut.pairwise(polygons[1].exterior.coords):
l0=LineString([p00,p01])
l1=LineString([p10,p11])
dist=l1.distance(l0)
if dist<min_dist:
min_dist=dist
min_l0=l0.coords
min_l1=l1.coords
#the constraint of alignement between 2 closest sides of 2 polygons as defined in a paper
#the difference is defined over 90 degrees
angle0=_angle(min_l0)
angle1=_angle(min_l1)
return (1+np.cos(4*(angle0-angle1)))/2
def closest_side_alignment_norm(sample0, sample1):
polygons = mp.map_layoutsamples_to_geometricobjects([sample0, sample1],
shape_name="shape")
min_dist = float("inf")
min_l0 = None
min_l1 = None
for p00, p01 in ut.pairwise(polygons[0].exterior.coords):
for p10, p11 in ut.pairwise(polygons[1].exterior.coords):
l0 = LineString([p00, p01])
l1 = LineString([p10, p11])
dist = l1.distance(l0)
if dist < min_dist:
min_dist = dist
min_l0 = l0.coords
min_l1 = l1.coords
#the constraint of alignement between 2 closest sides of 2 polygons as defined in a paper
#the difference is defined over 90 degrees
angle0 = _angle(min_l0)
angle1 = _angle(min_l1)
return (1 + np.cos(4 * (angle0 - angle1))) / 2
def draw_node_sample_tree(root,color,ax=None):
samples=root.get_flat_list()
polygons = mp.map_layoutsamples_to_geometricobjects(samples,"shape")
draw_polygons(polygons=polygons,ax=ax,color=color,size=1.3,set_range=True)
def positive_overlap(sample0, sample1):
polygons = mp.map_layoutsamples_to_geometricobjects([sample0, sample1],
shape_name="shape")
return ((polygons[0].intersection(polygons[1])).area)
def norm_overlap_pc(parent, child):
polygons = mp.map_layoutsamples_to_geometricobjects([parent, child],
shape_name="shape")
noemer = min(polygons[0].area, polygons[1].area)
return 1 - ((polygons[0].intersection(polygons[1])).area) / noemer
def negative_overlap(sample0,sample1):
polygons=mp.map_layoutsamples_to_geometricobjects([sample0,sample1],shape_name="shape")
return -((polygons[0].intersection(polygons[1])).area)
def union_negative_overlap_sb(parent,child,siblings):
sibling_polygons=mp.map_layoutsamples_to_geometricobjects(siblings,shape_name="shape")
child_polygon=mp.map_layoutsamples_to_geometricobjects([child],shape_name="shape")[0]
return -(cascaded_union([sibling_polygon.intersection(child_polygon) for sibling_polygon in sibling_polygons]).area)
def norm_overlap_pc(parent,child):
polygons=mp.map_layoutsamples_to_geometricobjects([parent,child],shape_name="shape")
noemer=min(polygons[0].area,polygons[1].area)
return 1-((polygons[0].intersection(polygons[1])).area)/noemer