1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
|
""" 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
import matplotlib.pyplot as plt
# Disable graphics for testing purposes
plt.show = lambda: None
def test_tomato_1():
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
assert np.array_equal(t.children_, [[0, 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
assert t.n_clusters_ == 2
t.merge_threshold_ = 10
assert t.n_clusters_ == 1
assert (t.labels_ == 0).all()
t = Tomato(graph_type="radius", r=0.1, metric="cosine", k=3)
assert np.array_equal(t.fit_predict(a), [1, 1, 1, 0, 0, 0, 0]) # or with swapped 0 and 1
t = Tomato(metric="euclidean", graph_type="radius", r=4.7, k=4)
t.fit(a)
assert t.max_weight_per_cc_.size == 2
assert np.array_equal(t.neighbors_, [[0, 1, 2], [0, 1, 2], [0, 1, 2], [3, 4, 5, 6], [3, 4, 5], [3, 4, 5], [3, 6]])
t.plot_diagram()
t = Tomato(graph_type="radius", r=4.7, k=4, symmetrize_graph=True)
t.fit(a)
assert t.max_weight_per_cc_.size == 2
assert [set(i) for i in t.neighbors_] == [{1, 2}, {0, 2}, {0, 1}, {4, 5, 6}, {3, 5}, {3, 4}, {3}]
t = Tomato(n_clusters=2, k=4, symmetrize_graph=True)
t.fit(a)
assert [set(i) for i in t.neighbors_] == [
{1, 2, 6},
{0, 2, 6},
{0, 1, 6},
{4, 5, 6},
{3, 5, 6},
{3, 4, 6},
{0, 1, 2, 3, 4, 5},
]
t.plot_diagram()
t = Tomato(k=6, metric="manhattan")
t.fit(a)
assert t.diagram_.size == 0
assert t.max_weight_per_cc_.size == 1
t.plot_diagram()
|