bird_cloud_gnn.fake

Generation of fake point cloud radar data.

Module Contents

Functions

generate_data([filename, num_points, min_range, ...])

Generate fake point cloud radar data
bird_cloud_gnn.fake.generate_data(filename=None, num_points=2**13, min_range=50.0, max_range=300000.0, azimuth_skip=2.0, elevations=np.array([0.3, 0.8, 1.2, 2, 2.8, 4.5, 6, 8, 10, 12, 15, 20, 25]), add_na=False, z_position=343.0, radius_influence=300.0)[source]

Generate fake point cloud radar data

The fake data containts polar coordinates range, azimuth, and elevation; cartesian coordinates x, y, z; random numerical features useless_feature, feat1, feat2, and feat3; and the target class with values 0 or 1.

  • range is generated like a exponential decay.

  • azimuth is generated uniformly in the interval [0.5, 365.5).

  • elevation is taken from an input array.

  • x, y, and z are converted from these polar values.

  • useless_feature is taken from a Normal(0, 1) distribution.

  • feat1, feat2, and feat3 are randomly constructed to remain in the interval [0, 1].

The columns are range, azimuth and elevation for the polar coordinates,

x, y, and z for the cartesian coordinates, useless_feature, feat1, feat2, feat3 for the numerical features, and class for the target.

Parameters:

  • filename (str, optional) – Filename to save the data. Use None to ignore.

  • num_points (int, optional) – Number of points. Defaults to 2**13.

  • max_range (float, optional) – Maximum generated range. Defaults to 300_000.0.

  • azimuth_skip (float, optional) – Size between azimuth values. Defaults to 2.0.

  • elevations (array of floats, optional) – List of elevations. Defaults to np.array([0.3, 0.8, 1.2, 2, 2.8, 4.5, 6, 8, 10, 12, 15, 20, 25]).

  • add_na (bool, optional) – Whether to add missing data. Defaults to False.

  • z_position (float, optional) – z position of the radar. Used for offsetting z after converting from polar to cartesian. Defaults to 343.0.

  • radius_influence (float, optional) – Radius used to compute the number of neighbours used internally for predicting the target class. Defaults to 300.0.

Returns:

Generated data. It is also saved to filename if that argument is passed.

Return type:

pandas.DataFrames