def test_make_summary_stat_df_no_warning(self):
df = pd.DataFrame({'A': [1, 2, np.nan], 'B': [np.nan, 2, 3]})
with warnings.catch_warnings():
warnings.simplefilter('error')
Comparer.make_summary_stat_df(df)
def test_make_summary_stat_df_no_warning(self):
df = pd.DataFrame({'A': [1, 2, np.nan],
'B': [np.nan, 2, 3]})
with warnings.catch_warnings():
warnings.simplefilter('error')
Comparer.make_summary_stat_df(df)
def test_make_summary_stat_df(self):
array = np.random.multivariate_normal([100, 25], [[25, .5], [.5, 1]],
5000)
df = pd.DataFrame(array, columns=['A', 'B'])
summary = Comparer.make_summary_stat_df(df)
assert np.isclose(summary.loc['A', 'SD'], 5, rtol=0.1)
assert np.isclose(summary.loc['B', 'SD'], 1, rtol=0.1)
assert np.isclose(summary.loc['A', 'MEAN'], 100, rtol=0.1)
assert np.isclose(summary.loc['B', 'MEAN'], 25, rtol=0.1)
def test_make_summary_stat_df(self):
array = np.random.multivariate_normal([100, 25],
[[25, .5],
[.5, 1]],
5000)
df = pd.DataFrame(array, columns=['A', 'B'])
summary = Comparer.make_summary_stat_df(df)
assert np.isclose(summary.loc['A', 'SD'], 5, rtol=0.1)
assert np.isclose(summary.loc['B', 'SD'], 1, rtol=0.1)
assert np.isclose(summary.loc['A', 'MEAN'], 100, rtol=0.1)
assert np.isclose(summary.loc['B', 'MEAN'], 25, rtol=0.1)