2022-10-13 13:14:51 +11:00
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# scipy-yli: Helpful SciPy utilities and recipes
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# Copyright © 2022 Lee Yingtong Li (RunasSudo)
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU Affero General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU Affero General Public License for more details.
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#
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# You should have received a copy of the GNU Affero General Public License
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# along with this program. If not, see <https://www.gnu.org/licenses/>.
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from pytest import approx
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import numpy as np
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import pandas as pd
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import yli
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def test_mannwhitney_ol6_6():
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"""Compare yli.mannwhitney for Ott & Longnecker (2016) example 6.6"""
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df = pd.DataFrame({
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'Sample': ['Before'] * 12 + ['After'] * 12,
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'Oxygen': [11.0, 11.2, 11.2, 11.2, 11.4, 11.5, 11.6, 11.7, 11.8, 11.9, 11.9, 12.1, 10.2, 10.3, 10.4, 10.6, 10.6, 10.7, 10.8, 10.8, 10.9, 11.1, 11.1, 11.3]
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})
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result = yli.mannwhitney(df, 'Oxygen', 'Sample', method='asymptotic', alternative='less')
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assert result.pvalue == approx(0.00007, abs=0.00001)
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2022-10-19 08:13:14 +11:00
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2022-11-09 22:25:17 +11:00
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expected_summary = '''Sample After Before
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Oxygen
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2022-11-09 22:08:27 +11:00
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Median (IQR) 10.75 (10.55–10.95) 11.55 (11.20–11.83)
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Median (range) 10.75 (11.00–12.10) 11.55 (11.00–12.10)
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U = 6.0; p < 0.001*
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2022-10-19 08:13:14 +11:00
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r = 0.92, Before > After'''
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assert result.summary() == expected_summary
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