def compute_prob_neighbors(geometry: Geometry, grid: Grid, ped: Pedestrian,
floorfield, weight_direction: bool):
prob = {}
# compute visible area
x, y = grid.get_coordinates(ped.i(), ped.j())
vis = geometry.visible_area(x, y)
# compute voronoi polygons of neighbors
neighbor_voronoi_polygons = compute_voronoi_neighbors(geometry, grid, ped)
intersections = []
weight_distance = compute_point_distance(geometry, grid,
[ped.i(), ped.j()])
weight_prob = distance_to_prob_dec(weight_distance, 40, 0.15)
weighted_floorfield = weight_prob * floorfield
inside = grid.get_inside_polygon_cells(geometry, vis.exterior.coords)
# sum up every cell in neighbor polygon to neighbor cell
# sum is weighted by distance, closer = more important
for key, polygon in neighbor_voronoi_polygons.items():
if key == Neighbors.self:
intersections.append(polygon)
prob[key] = floorfield.filled(0)[ped.i()][ped.j()]
elif polygon is not None:
p = Polygon(polygon.coords)
inter = p.intersection(vis)
points = []
if inter.geom_type == 'Polygon':
points = inter.exterior.coords
elif inter.geom_type == 'GeometryCollection':
for i in inter.geoms:
if i.geom_type == 'Polygon':
for ppp in i.exterior.coords:
points.append([ppp[0], ppp[1]])
elif inter.geom_type == 'MultiPolygon':
for i in inter.geoms:
if i.geom_type == 'Polygon':
for ppp in i.exterior.coords:
points.append([ppp[0], ppp[1]])
else:
print(inter)
if len(points) == 0:
prob[key] = 0
else:
intersection = sg.Polygon(points)
intersections.append(intersection)
inside_cells = grid.get_inside_polygon_cells(geometry, points)
combination = inside_cells * weighted_floorfield
prob[key] = np.ma.max(combination, fill_value=0)
# weight cells by moving direction
if weight_direction:
weights = {}
for key, p in prob.items():
weights[key] = weighted_neighbors[ped.direction][key]
weights = normalize_dict(weights)
for key, p in prob.items():
prob[key] = p * weights[key]
prob = normalize_dict(prob)
return prob
