pointcloudset.pointcloud_core module

class pointcloudset.pointcloud_core.PointCloudCore(data: Optional[DataFrame] = None, orig_file: str = '', timestamp: Optional[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 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 centroid: array

Geometric center for the point cloud.

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