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""" This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
Author(s): Marc Glisse
Copyright (C) 2020 Inria
Modification(s):
- YYYY/MM Author: Description of the modification
"""
from gudhi.clustering.tomato import Tomato
import numpy as np
import pytest
def test_tomato_something():
a = [(1, 2), (1.1, 1.9), (0.9, 1.8), (10, 0), (10.1, 0.05), (10.2, -0.1), (5.4, 0)]
t = Tomato(metric="euclidean", n_clusters=2, k=4, n_jobs=-1, eps=0.05)
assert np.array_equal(t.fit_predict(a), [1,1,1,0,0,0,0]) # or with swapped 0 and 1
t = Tomato(density_type='KDE', r=1, k=4)
t.fit(a)
assert np.array_equal(t.leaf_labels_, [1,1,1,0,0,0,0]) # or with swapped 0 and 1
t = Tomato(graph_type='radius', r=4.7, k=4)
t.fit(a)
assert t.max_weight_per_cc_.size == 2
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