uavfpy.planner.coverage.polygon

Module Contents

Functions

beta_clusters(clusters: int = 3, ppc: int = 20, alpha: float = 4.0, beta: float = 4.0) → numpy.ndarray

remove_close_points(points: numpy.ndarray, eps: float = 0.07) → numpy.ndarray

stupid_spiky_polygon(R_inner: int, R_outer: int, n=10)

uavfpy.planner.coverage.polygon.beta_clusters(clusters: int = 3, ppc: int = 20, alpha: float = 4.0, beta: float = 4.0) → numpy.ndarray
uavfpy.planner.coverage.polygon.remove_close_points(points: numpy.ndarray, eps: float = 0.07) → numpy.ndarray
class uavfpy.planner.coverage.polygon.RandomPolygon(n, points=None, holes=2)

Bases: object

removable_interiors(self, dt: scipy.spatial.Delaunay) → tuple

find indices of interior simplices that are safe to remove in dt

removable_exteriors(self, dt: scipy.spatial.Delaunay, points: numpy.ndarray, ax: matplotlib.pyplot.Axes = None) → tuple

find indices to safe

del_tri(self, dt: scipy.spatial.Delaunay, rm: int) → scipy.spatial.Delaunay

Alters dt in place to remove tri at rm

_dotself(self, x: numpy.ndarray) → numpy.ndarray
ar(self, M: numpy.ndarray) → numpy.float64

aspect ratio

polygon(self, points: numpy.ndarray, holes: int = 0, removals: int = 30)

Create a non-convex polygon from points. This algorithm works by first creating a convex Delaunay triangulation over the points, and then removing triangles to form a non-convex polygon. Thus, the general shape of the initial point distribution will infrom the subsequent non-convex polygon.

This algorithm is slow for large numbers of points.

Parameters
pointsnp.ndarray, holes, optional

The number of interior holes in the polygon, default 0

Returns
nx.Digraph

Graph containing the polygon.

addcw(self, H: networkx.DiGraph, e1: int, e2: int) → float

determine which way the edge is pointing

e.g.

Q2 │ Q1 ─────┼───── Q3 │ Q4

A “positive” cw value goes from Q2 to Q4. A “negative” cw value means the edge goes from Q4 to Q2. It’s relative so we only look at directions not absolute positions.

plot(self, G: networkx.DiGraph, ax: matplotlib.pyplot.Axes, posattr: str = 'points', arrows: bool = False, nodecolor: str = 'k', ecolor: str = None, ecolorattr: str = 'weight', ecmap='tab10', node_text: bool = True, style: str = '-', m: str = '.', draw_nodes=True) → matplotlib.pyplot.Axes

Draw a DiGraph G with points stored in posattr onto ax

uavfpy.planner.coverage.polygon.stupid_spiky_polygon(R_inner: int, R_outer: int, n=10)