DBSCAN Clustering

plot_results


def plot_results(
    p4id, labels, data:NoneType=None, kind:NoneType=None, reduced_data:NoneType=None, ax:NoneType=None
):

Plots the results of a clustering algorithm. Parameters ———- p4id : object An object that contains methods for plotting and showing subframes. labels : array-like Cluster labels for each point in the dataset. data : pandas.DataFrame, optional The original data points with ‘x’ and ‘y’ coordinates. Default is None. kind : str, optional The type of marking to plot (e.g., ‘blotch’, ‘fan’). Default is None. reduced_data : pandas.DataFrame, optional The reduced data points to be plotted. Default is None. ax : matplotlib.axes.Axes, optional The axes on which to plot. If None, a new figure and axes are created. Default is None. Returns ——- None

source

get_average_objects


def get_average_objects(
    clusters, # table with rows of markings (fans or blotches) to be averaged
    kind, # Switch to control the circularity for the average angle calculation.
):

Create the average object out of a sequence of clusters.

source

DBScanner


def DBScanner(
    msf:float=0.13, savedir:NoneType=None, with_angles:bool=True, with_radii:bool=True, do_large_run:bool=True,
    save_results:bool=True, only_core_samples:bool=False, data:NoneType=None, dbname:NoneType=None
):