Merge branch 'master' into alpha_complex_3d_python

1 files changed, 65 insertions, 0 deletions

diff --git a/src/python/test/test_tomato.py b/src/python/test/test_tomato.py
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+++ b/src/python/test/test_tomato.py
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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
+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()