コード例 #1
0
def course(lat1, lon1, lat2, lon2):
  """Return course in degrees between two lat/lon points relative to grid north.
  """
  delta_y = trig.sind(lon2 - lon1) * trig.cosd(lat2)
  delta_x = (trig.cosd(lat1) * trig.sind(lat2) -
             trig.sind(lat1) * trig.cosd(lat2) * trig.cosd(lon2 - lon1))
  return trig.atan2d(delta_y, delta_x) % 360.0
コード例 #2
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  def move(self, last_position, curr_position, e1, n1):
    """Given sensor motion, move the relative location of the particle.
    """
    # Calculate how to move the particle relative to the sensor.
    target_bearing = last_position.heading - self.hor_angle

    # In Cartesian coordinates, let (0, 0) represent the sensor's previous
    # position, (e1, n1) represent the sensor's current position, and (e2, n2)
    # represent the target's position.
    e2 = self.surface_range * trig.sind(target_bearing)
    n2 = self.surface_range * trig.cosd(target_bearing)
    predicted_target_bearing = trig.atan2d(e2 - e1, n2 - n1) % 360.0

    self.hor_angle = (curr_position.heading - predicted_target_bearing +
                      random.gauss(0, self.angle_noise))
    self.surface_range = (math.sqrt((e2 - e1)**2 + (n2 - n1)**2) +
                          random.gauss(0, self.range_noise))
コード例 #3
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    def move(self, last_position, curr_position, e1, n1):
        """Given sensor motion, move the relative location of the particle.
    """
        # Calculate how to move the particle relative to the sensor.
        target_bearing = last_position.heading - self.hor_angle

        # In Cartesian coordinates, let (0, 0) represent the sensor's previous
        # position, (e1, n1) represent the sensor's current position, and (e2, n2)
        # represent the target's position.
        e2 = self.surface_range * trig.sind(target_bearing)
        n2 = self.surface_range * trig.cosd(target_bearing)
        predicted_target_bearing = trig.atan2d(e2 - e1, n2 - n1) % 360.0

        self.hor_angle = (curr_position.heading - predicted_target_bearing +
                          random.gauss(0, self.angle_noise))
        self.surface_range = (math.sqrt((e2 - e1)**2 + (n2 - n1)**2) +
                              random.gauss(0, self.range_noise))