pointcloudset.pointcloud_core module

class pointcloudset.pointcloud_core.PointCloudCore(data: DataFrame = None, orig_file: str = '', timestamp: datetime = None, columns: list = ['x', 'y', 'z'])

Bases: object

PointCloudCore Class with all the main methods and properties of the PointCloud Class.

timestamp: Timestamp.

orig_file: Path to orginal file. Defaults to empty.

property timestamp_str: str

Timestamp to human readable date and time string.

Returns:: Date/time string.
Return type:: str

property xyz: ndarray

property centroid: ndarray

property data: All the data, x,y,z and auxiliary data such as intensity, range and more.

property bounding_box: DataFrame: The axis aligned boundary box as a pandas.DataFrame.

property has_original_id: bool

Checks if original_id column is present in the data. Original_id identifies a lidar point and makes them comparable.

Returns:: True if the PointCloud contains original_id data, False if PointCloud does not contain original_id data.
Return type:: bool

describe() → DataFrame

Generate descriptive statistics based on PointCloud.data.describe() and therefore on pandas.DataFrame.describe().

Returns:: Summary statistics of the data of the PointCloud.
Return type:: pandas.DataFrame

extract_point(id: int, use_original_id: bool = False) → DataFrame

Extract a specific point from the PointCloud defined by the point id. The id can be the current index of the data from the PointCloud or the original_id.

Parameters:

id (int) – ID number
use_original_id (bool, optional) – If True use original_id, if False use current index in PointCloud. Defaults to False.

Returns:

A pointcloud which only contains the defined point.

Return type:

pandas.DataFrame