The Kuttruff Clustering Algorithm

Readers are referred to the section on clustering for a detailed description of the clustering algorithms.

Luna Command

./tpx3dump process -i /Users/Ciaran/atlassian-bitbucket-pipelines-runner/temp/e71169e4-520a-5b30-a5ab-ee8a44eb5fac/build/docs/source/_static/example_data.tpx3 -o /Users/Ciaran/atlassian-bitbucket-pipelines-runner/temp/e71169e4-520a-5b30-a5ab-ee8a44eb5fac/build/docs/source/_static/example_data.h5 --layout single --clustering-algorithm Kuttruff2024 --eps-t 170ns --eps-s 6 --kuttruff-buffer-size 15

Python Script

Using the Kuttruff clustering algorithm

import os, sys
import h5py  # ensure you have `pip install h5py`
import pandas as pd  # ensure you have `pip install pandas`
from typing import *
import matplotlib.pyplot as plt
import seaborn as sns
import warnings

warnings.filterwarnings("ignore")  # suppress warnings from plotting libraries.

sns.set_context(context="talk")

# add some paths to PYTHONPATH
for directory in ["..", "."]:
    sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), directory)))

# on our system "EXAMPLE_DATA_HDF5" refers to the absolute path
# to a hdf5 file generated by luna. Replace with your own!
from env_vars_for_docs_examples import EXAMPLE_DATA_HDF5, PLOTS_DIRECTORY

# re-use functions from previous example
from ex2_read_data_time_units import TimeUnit, load_clusters

TOA_UNIT = TimeUnit.Nanoseconds

from ex5_plot_cluster_2d_histogram import plot_2d_histogram_cluster_data



if __name__ == "__main__":

    fname = os.path.join(PLOTS_DIRECTORY, f"ex13_kuttruff_clustering_algorithm.png")

    cluster_data: pd.DataFrame = load_clusters(EXAMPLE_DATA_HDF5, toa_unit=TOA_UNIT)

    plot_2d_histogram_cluster_data(cluster_data=cluster_data, variable="ctot", fname=fname)

Script Output

Example Output