Local Outlier Factor Python Module

Functions related to calculating the local outlier factor of a dataset.

local_outlier_factor

Annotates a dataframe with a column containing the local outlier factor for each data record. The dataframe should contain at least one GeometryType column. Rows must be unique. If one geometry column is present it will be used automatically. If two are present, the one named ‘geometry’ will be used. If more than one are present and neither is named ‘geometry’, the column name must be provided.

def local_outlier_factor(dataframe: DataFrame, k: int, geometry: Optional[str], approximate_knn: bool, handle_ties: bool, use_spheroid, result_column_name: str)

Parameters

DataFrame

required

apache sedona idDataframe containing the point geometries

int

required

number of nearest neighbors that will be considered for the LOF calculation

Optional[str]

name of the geometry column

bool

required

whether to use approximate KNN. When false will use exact KNN join. Default is False

bool

required

whether to handle ties in the k-distance calculation. Default is false

bool

required

whether to use a cartesian or spheroidal distance calculation. Default is false

str

required

the name of the column containing the lof for each row. Default is “lof”

Returns

A PySpark DataFrame containing the lof for each row.

Usage Examples

from local_outlier_factor import *

# Example usage of local_outlier_factor
result = local_outlier_factor(dataframe=example_value, k=example_value, geometry=example_value)

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Local Outlier Factor Python Module