def qualify_adjacency(data, **kwargs):
qualify_adjacency.relation_set = 'adj'
qualify_adjacency.arity = 2
relata_list = list()
relata_list.append(ff.filter(data, type_list=['boma', 'olopololi']))
relata_list.append(ff.filter(data, type_list=['mountain', 'boundary']))
qcn = []
for relata in relata_list:
max_min_dist = compute_max_min_dist([r['geometry'] for r in relata])
for i in range(len(relata) - 1):
for sec in relata[i + 1:]:
o1 = relata[i]['attributes']['ssm_id']
o2 = sec['attributes']['ssm_id']
g1 = relata[i]['geometry']
g2 = sec['geometry']
relation = compute_adjacency(g1, g2, max_min_dist)
qcn.append({'obj_1': o1, 'obj_2': o2, 'relation': relation})
return 'ADJACENCY', 2, {}, qcn
else:
return 'ADJACENCY', 2, {}, []
def get_qualifier_functions(data):
"""Loops through a list of qualifiers, initializing them
and returning a list of qualifier functions that can be applied on
any 'well formed' data.
"""
# append qualifier for each aspect and return list
qualifier_function_list = []
# 1. rcc8
qualifier_function_list.append((qualify_rcc8, None))
# 2. rcc11
qualifier_function_list.append((qualify_rcc11, None))
# 3. RegionStarVars
fargs = {'num_sectors': 4}
regstarvars_ref_objects = filter(data, type_list=['mountain'])
regstarvars_ref_pairs = grp(perm(regstarvars_ref_objects, 2),
key=lambda x: x[0])
fargs['reference_pair_groups'] = regstarvars_ref_pairs
qualifier_function_list.append((qualify_relative_direction, fargs))
# 4. relative distance
qualifier_function_list.append((qualify_relative_distance, None))
# 5. left-right relations
qualifier_function_list.append((qualify_left_right, None))
# 6. adjacency
qualifier_function_list.append((qualify_adjacency, None))
return qualifier_function_list
def qualify_relative_distance(data, **kwargs):
# every qualifier function must specify these two parameters\n",
qualify_relative_distance.relation_set = 'REL_DIST'
qualify_relative_distance.arity = 2,
relata_list = []
relata_list.append(
ff.filter(data,
type_list=[
'boma', 'olopololi', 'school', 'borehole', 'church',
'river', 'marsh'
]))
relata_list.append(
ff.filter(data, type_list=['mountain', 'marsh', 'river', 'road']))
qcn = []
near_ends, far_ends = [], []
for relata in relata_list:
near_end, far_end = compute_relative_dist_ranges(
[r['geometry'] for r in relata])
near_ends.append(near_end), far_ends.append(far_end)
for k in range(len(relata_list)):
relata = relata_list[k]
near_end, far_end = near_ends[k], far_ends[k]
for i in range(len(relata) - 1):
for sec in relata[i + 1:]:
if relata[i]['attributes']['feat_type'] in ['road', 'river', 'marsh'] \
and sec['attributes']['feat_type'] in ['road', 'river', 'marsh'] \
and i == 0:
continue
o1 = relata[i]['attributes']['ssm_id']
o2 = sec['attributes']['ssm_id']
g1 = relata[i]['geometry']
g2 = sec['geometry']
relation = distance_relation(g1, g2, near_end, far_end)
qcn.append({'obj_1': o1, 'obj_2': o2, 'relation': relation})
return 'REL_DIST', 2, {}, qcn
def qualify_rcc8(data, **kwargs):
f_data = ff.filter(data, filter_geoms=ff.FILTER_POLYGONS)
qcn = []
for i in range(len(f_data[:-1])):
for sec in f_data[i + 1:]:
o1 = f_data[i]['attributes']['ssm_id']
o2 = sec['attributes']['ssm_id']
relation = polygonal_topology(f_data[i]['geometry'],
sec['geometry'])
qcn.append({'obj_1': o1, 'obj_2': o2, 'relation': relation})
return 'RCC8', 2, {}, qcn
def qualify_left_right(data, **kwargs):
# every qualifier function must specify these two parameters\n",
relation_set = 'LEFT_RIGHT'
arity = 2
relata = ff.filter(data)
referents = ff.filter(relata, type_list=['river', 'road'])
for ref in referents:
relata.remove(ref)
qcn = []
for referent in referents:
for relatum in relata:
o1 = referent['attributes']['ssm_id']
o2 = relatum['attributes']['ssm_id']
g1 = referent['geometry']
g2 = relatum['geometry']
relation = left_or_right(g1, g2)
qcn.append({'obj_1': o1, 'obj_2': o2, 'relation': relation})
return relation_set, arity, {}, qcn
def compute_tiles(self,d):
tiles ={}
relatum = d[0]['geometry']
secondary_object_list=(ff.filter(self.data, type_list=self.type_list))
near_end, far_end, vfar_end = compute_relative_dis_ranges_1_to_M(relatum, secondary_object_list)
#print(near_end, far_end,vfar_end)
base_bounds = relatum.bounds # returns the tuple (minx, miny, maxx, maxy)
diam = sqrt((base_bounds[2] - base_bounds[0]) ** 2 + (base_bounds[3] - base_bounds[1]) ** 2)
relatum_nearEnd = relatum.buffer( near_end)
relatum_farEnd = relatum.buffer( far_end)
relatum_vfarEnd = relatum.buffer( far_end)
#print(relatum_nearEnd, relatum_farEnd,relatum_vfarEnd)
tiles['near'] = relatum_nearEnd
tiles['far'] = relatum_farEnd
tiles['vfar'] = relatum_vfarEnd
return tiles
def qualify_relative_direction(data, **kwargs):
relation_set = 'REGION_STAR_VARS'
arity = 2
# get random pair of polygons
f_data = ff.filter(data, filter_geoms=ff.FILTER_POINTS_POLYGONS)
or_obj1 = rnd.choice(f_data)
or_obj2 = rnd.choice(f_data)
while or_obj1 == or_obj2:
or_obj2 = rnd.choice(f_data)
reference_pair_groups = [(or_obj1, [(or_obj1, or_obj2)]),
(or_obj2, [(or_obj2, or_obj1)])]
num_sectors = kwargs.get('num_sectors', 4)
reference_pair_groups = kwargs.get('reference_pair_groups',
reference_pair_groups)
modifiers = {'reference_pair_groups': [], 'number_of_sectors': num_sectors}
# f_data = ff.filter(data, filter_geoms=ff.FILTER_POINTS_POLYGONS)
qcn = []
for ref, reference_pairs in reference_pair_groups:
reference_obj_1 = {
'ssm_id': ref['attributes']['ssm_id'],
'feat_type': ref['attributes']['feat_type'],
'geometry': ref['geometry']
}
modifiers['reference_pair_groups'].append(reference_obj_1['ssm_id'])
d_sectors_list = []
# generate all orientations for ref
for reference_pair in reference_pairs:
# determine the centroids of their convex hulls
reference_obj_2 = {
'ssm_id': reference_pair[1]['attributes']['ssm_id'],
'feat_type': reference_pair[1]['attributes']['feat_type'],
'geometry': reference_pair[1]['geometry']
}
cntr1 = reference_obj_1['geometry'].convex_hull.centroid
cntr2 = reference_obj_2['geometry'].convex_hull.centroid
# determine the global orientation of the ray from centroid 1 to centroid 2
v = np.array(cntr2.coords[:][0]) - np.array(cntr1.coords[:][0])
# using degrees instead of radians
dir_deg = np.rad2deg(vector_angle(v))
d_sectors_list.append(
calculate_sectors(dir_deg, 360.0, num_sectors))
o1 = ref['attributes']['ssm_id']
g1 = ref['geometry']
for sec in f_data:
o2 = sec['attributes']['ssm_id']
g2 = sec['geometry']
relation = []
for d_sectors in d_sectors_list:
relation.append([
sector_range(
directional_relation(g1, g2, dir_deg, 360.0,
d_sectors), num_sectors),
sector_range(
directional_relation(g2, g1, dir_deg, 360.0,
d_sectors), num_sectors)
])
qcn.append({'obj_1': o1, 'obj_2': o2, 'relation': relation})
return relation_set, arity, modifiers, qcn