waypoint

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class RelativeWaypoints

Inherits from: pydantic.BaseModel

View Source

class RelativeWaypoints(BaseModel):
    pass 

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class Waypoints

Inherits from: pydantic.BaseModel

Datatype representing a list of geolocation waypoints.

Takes in a list of geolocations and transforms them into waypoints given a slicing algorithm. The slicing algorithm determines how the waypoints will be visited; edge visits the exact geolocations and survey/corridor divide the geolocations into lines which are traversed in order. These are used to scan over an area.

Attributes

attr  area  (Union[str, List[Location]]) — can be either a KML reference or a list of geolocation points; if a KML reference, use the name of the polyshape, otherwise provide a list of Location objects

attr  alt  (float) — altitude at which the waypoints will be visited; altitudes provided by Location objects are ignored

attr  algo  (Optional[Literal['edge', 'corridor', 'survey']]) — determines how the waypoints are sliced, edge follows the points in order and survey/corridor attempt to cover the area enclosed by the points (default: edge)

attr  spacing  (Optional[float]) — must be set for survey and corridor, ignored otherwise; spacing in between survey columns [meters]

attr  angle_degrees  (Optional[float]) — must be set for survey and corridor, ignored otherwise; the angle of the survey columns [degrees]

attr  trigger_distance  (Optional[float]) — must be set for survey, ignored otherwise; the distance before a snapshot is triggered

method calculate

Call Type: normal

View Source

@register_data
class Waypoints(BaseModel):
    """Datatype representing a list of geolocation waypoints.

    Takes in a list of geolocations and transforms them into waypoints given
    a slicing algorithm. The slicing algorithm determines how the waypoints
    will be visited; `edge` visits the exact geolocations and `survey`/`corridor`
    divide the geolocations into lines which are traversed in order. These
    are used to scan over an area.

    Attributes:
        area (Union[str, List[Location]]): can be either a KML reference or a list
            of geolocation points; if a KML reference, use the name of the polyshape, otherwise
            provide a list of `Location` objects
        alt (float): altitude at which the waypoints will be visited; _altitudes provided by Location objects are ignored_
        algo (Optional[Literal["edge", "corridor", "survey"]]): determines how the waypoints are sliced, `edge`
            follows the points in order and `survey`/`corridor` attempt to cover the area enclosed by the points (default: `edge`)
        spacing (Optional[float]): must be set for `survey` and `corridor`, ignored otherwise; spacing in between survey columns [meters]
        angle_degrees (Optional[float]): must be set for `survey` and `corridor`, ignored otherwise; the angle of the survey columns [degrees]
        trigger_distance (Optional[float]): must be set for `survey`, ignored otherwise; the distance before a snapshot is triggered
    """
    area: Union[str, List[Location]]
    alt: float
    algo: Optional[Literal["edge", "corridor", "survey"]] = "edge"
    spacing: Optional[float] = None
    angle_degrees: Optional[float] = None
    trigger_distance: Optional[float] = None

    def calculate(self) -> Dict[str, List[Dict[str, float]]]:
        raw = None # Raw geopoints

        # Check to see if a KML map has been sent or if Locations have been provided
        if MISSION_MAP is None and type(area) == str:
            raise ValueError("MISSION_MAP is not set. Set map_mod.MISSION_MAP to a fastkml.kml.KML before calling calculate().")
        elif MISSION_MAP:
            raw_map: Dict[str, GeoPoints] = parse_kml_file(MISSION_MAP)
            if not raw_map:
                logger.warning("No valid areas found in mission map (KML).")
                return {}
    
            if self.area not in raw_map:
                available = ", ".join(sorted(raw_map.keys()))
                raise ValueError(f"Area '{self.area}' not found in mission map. Available areas: {available}")
    
            raw = raw_map[self.area]
            if len(raw) < 3:
                logger.warning("Area %s has < 3 points; skipping.", self.area)
                return {}
        else:
            raw = GeoPoints([(p.latitude, p.longitude) for p in area])

        # Choose partitioner
        if self.algo == "edge":
            partition = EdgePartition()
        elif self.algo == "survey":
            if self.spacing is None or self.angle_degrees is None or self.trigger_distance is None:
                raise ValueError("For 'survey' algo, 'spacing', 'angle_degrees', and 'trigger_distance' must be set.")
            partition = SurveyPartition(
                spacing=self.spacing,
                angle_degrees=self.angle_degrees,
                trigger_distance=self.trigger_distance,
            )
        elif self.algo == "corridor":
            if self.spacing is None or self.angle_degrees is None:
                raise ValueError("For 'corridor' algo, 'spacing' and 'angle_degrees' must be set.")
            partition = CorridorPartition(
                spacing=self.spacing,
                angle_degrees=self.angle_degrees,
            )
        else:
            raise ValueError("Unknown algo '%s'. Expected one of: 'edge', 'survey', 'corridor'." % self.algo)

        origin_wgs = raw.centroid()
        projected = raw.convert_to_projected()
        poly = projected.to_polygon()

        parts_m = partition.generate_partitioned_geopoints(poly)  
        parts_wgs = [GeoPoints(p).inverse_project_from(origin_wgs) for p in parts_m]

        # Flatten segments to per-point waypoints
        waypoints: List[Dict[str, float]] = []
        for gp in parts_wgs:
            for lon, lat in gp:
                waypoints.append({"lat": float(lat), "lon": float(lon), "alt": float(self.alt)})

        logger.info(
            "Partitioned '%s' with %s: %d segment(s), %d point(s)",
            self.area, self.algo, len(parts_wgs), len(waypoints),
        )

        return {self.area: waypoints}

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