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# ----------------------------------------------------------------------------
# Copyright (c) 2013--, scikit-bio development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE.txt, distributed with this software.
# ----------------------------------------------------------------------------
import unittest
import numpy as np
import numpy.testing as npt
from skbio.diversity.alpha import ace
class AceTests(unittest.TestCase):
def test_ace(self):
npt.assert_almost_equal(ace(np.array([2, 0])), 1.0)
npt.assert_almost_equal(ace(np.array([12, 0, 9])), 2.0)
npt.assert_almost_equal(ace(np.array([12, 2, 8])), 3.0)
npt.assert_almost_equal(ace(np.array([12, 2, 1])), 4.0)
npt.assert_almost_equal(ace(np.array([12, 1, 2, 1])), 7.0)
npt.assert_almost_equal(ace(np.array([12, 3, 2, 1])), 4.6)
npt.assert_almost_equal(ace(np.array([12, 3, 6, 1, 10])), 5.62749672)
# Just return the number of taxa when all are abundant.
npt.assert_almost_equal(ace(np.array([12, 12, 13, 14])), 4.0)
# Border case: only singletons and 10-tons, no abundant taxa.
npt.assert_almost_equal(ace([0, 1, 1, 0, 0, 10, 10, 1, 0, 0]),
9.35681818182)
def test_ace_only_rare_singletons(self):
with self.assertRaises(ValueError):
ace([0, 0, 43, 0, 1, 0, 1, 42, 1, 43])
if __name__ == '__main__':
unittest.main()
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