def test_mean_2(date_func):
s1mask = s1(date_func).mask((
timestamp(2020, 1, 2, date_func=date_func, use_str=True),
timestamp(2020, 1, 4, date_func=date_func, use_str=True),
))
s2mask = (s2(date_func).mask((
timestamp(2020, 1, 7, date_func=date_func, use_str=True),
timestamp(2020, 1, 9, date_func=date_func, use_str=True),
)).mask((None, timestamp(2019, 12, 31, date_func=date_func,
use_str=True))))
result = sc.mean([s1mask, s2mask])
pd.testing.assert_series_equal(
result.step_values,
pd.Series({
timestamp(2019, 12, 31, date_func=date_func): -1.75,
timestamp(2020, 1, 1, date_func=date_func): -1.125,
timestamp(2020, 1, 2, date_func=date_func): np.nan,
timestamp(2020, 1, 4, date_func=date_func): 1.125,
timestamp(2020, 1, 5, date_func=date_func): 0.75,
timestamp(2020, 1, 6, date_func=date_func): -0.5,
timestamp(2020, 1, 7, date_func=date_func): np.nan,
timestamp(2020, 1, 9, date_func=date_func): -1.5,
timestamp(2020, 1, 10, date_func=date_func): 0.0,
timestamp(2020, 1, 11, date_func=date_func): 2.5,
timestamp(2020, 1, 13, date_func=date_func): 0.0,
}),
check_names=False,
check_index_type=False,
)
assert np.isnan(result.initial_value)
def test_mean_1(date_func):
s1mask = s1(date_func).mask((
timestamp(2020, 1, 2, date_func=date_func, use_str=True),
timestamp(2020, 1, 4, date_func=date_func, use_str=True),
))
s2mask = s2(date_func).mask((
timestamp(2020, 1, 7, date_func=date_func, use_str=True),
timestamp(2020, 1, 9, date_func=date_func, use_str=True),
))
pd.testing.assert_series_equal(
sc.mean([s1mask, s2mask]).step_values,
pd.Series({
timestamp(2019, 12, 27, date_func=date_func): -0.875,
timestamp(2019, 12, 29, date_func=date_func): -1.75,
timestamp(2020, 1, 1, date_func=date_func): -1.125,
timestamp(2020, 1, 2, date_func=date_func): np.nan,
timestamp(2020, 1, 4, date_func=date_func): 1.125,
timestamp(2020, 1, 5, date_func=date_func): 0.75,
timestamp(2020, 1, 6, date_func=date_func): -0.5,
timestamp(2020, 1, 7, date_func=date_func): np.nan,
timestamp(2020, 1, 9, date_func=date_func): -1.5,
timestamp(2020, 1, 10, date_func=date_func): 0.0,
timestamp(2020, 1, 11, date_func=date_func): 2.5,
timestamp(2020, 1, 13, date_func=date_func): 0.0,
}),
check_names=False,
check_index_type=False,
)
def test_mean_1():
s1mask = s1().mask((2, 4))
s2mask = s2().mask((7, 9))
pd.testing.assert_series_equal(
sc.mean([s1mask, s2mask]).step_values,
pd.Series({
-4.0: -0.875,
-2.0: -1.75,
1.0: -1.125,
2.0: np.nan,
4.0: 1.125,
5.0: 0.75,
6.0: -0.5,
7.0: np.nan,
9.0: -1.5,
10.0: 0.0,
11.0: 2.5,
13.0: 0.0,
}),
check_names=False,
check_index_type=False,
)
def test_mean_3(IS1, IS2):
pd.testing.assert_series_equal(
sc.mean(np.array([IS1, IS2])).step_changes,
pd.Series(
{
-4.0: -0.875,
-2.0: -0.875,
1.0: 0.625,
2.0: 2.25,
2.5: -1.25,
3.0: 1.25,
4.0: 1.25,
5.0: -2.625,
6.0: -1.25,
7.0: 1.25,
8.0: 2.5,
10.0: -2.25,
}
),
check_names=False,
check_index_type=False,
)
def test_mean_2():
s1mask = s1().mask((2, 4))
s2mask = s2().mask((7, 9)).mask((None, 0))
result = sc.mean([s1mask, s2mask])
pd.testing.assert_series_equal(
result.step_values,
pd.Series({
0.0: -1.75,
1.0: -1.125,
2.0: np.nan,
4.0: 1.125,
5.0: 0.75,
6.0: -0.5,
7.0: np.nan,
9.0: -1.5,
10.0: 0.0,
11.0: 2.5,
13.0: 0.0,
}),
check_names=False,
check_index_type=False,
)
assert np.isnan(result.initial_value)
