def test_hydro(self):
fn = Path("Raven", "q_sim.nc")
ds = open_dataset(fn)
miss = missing.missing_any(ds.q_sim, freq="YS")
np.testing.assert_array_equal(miss[:-1], False)
np.testing.assert_array_equal(miss[-1], True)
miss = missing.missing_any(ds.q_sim, freq="YS", season="JJA")
np.testing.assert_array_equal(miss, False)
def test_season(self, tasmin_series):
ts = tasmin_series(np.zeros(360))
miss = missing.missing_any(ts, freq="YS", season="MAM")
np.testing.assert_equal(miss, [False])
miss = missing.missing_any(ts, freq="YS", season="JJA")
np.testing.assert_array_equal(miss, [True, True])
miss = missing.missing_any(ts, freq="YS", season="SON")
np.testing.assert_equal(miss, [False])
def test_season(self, tasmin_series, calendar):
ts = tasmin_series(np.zeros(360))
ts = convert_calendar(ts, calendar, missing=0, align_on="date")
miss = missing.missing_any(ts, freq="YS", season="MAM")
np.testing.assert_equal(miss, [False])
miss = missing.missing_any(ts, freq="YS", season="JJA")
np.testing.assert_array_equal(miss, [True, True])
miss = missing.missing_any(ts, freq="YS", season="SON")
np.testing.assert_equal(miss, [False])
def test_missing_days(self, tas_series):
a = np.arange(360.0)
a[5:10] = np.nan
ts = tas_series(a)
out = missing.missing_any(ts, freq="MS")
assert out[0]
assert not out[1]
def test_no_freq(self, tasmin_series):
ts = tasmin_series(np.zeros(360))
miss = missing.missing_any(ts, freq=None)
np.testing.assert_array_equal(miss, False)
t = list(range(31))
t.pop(5)
ts2 = ts.isel(time=t)
miss = missing.missing_any(ts2, freq=None, src_timestep="H")
np.testing.assert_array_equal(miss, True)
# With indexer
miss = missing.missing_any(ts, freq=None, month=[7])
np.testing.assert_array_equal(miss, False)
miss = missing.missing_any(ts2, freq=None, month=[7], src_timestep="H")
np.testing.assert_array_equal(miss, True)
def test_any(self, pr_hr_series):
pr = self.pr(pr_hr_series)
out = missing.missing_any(pr, "D", src_timestep="H")
np.testing.assert_array_equal(
out,
[
True,
] + 8 * [
False,
] + [
True,
],
)
def test_month(self, tasmin_series):
ts = tasmin_series(np.zeros(36))
miss = missing.missing_any(ts, freq="YS", month=7)
np.testing.assert_equal(miss, [False])
miss = missing.missing_any(ts, freq="YS", month=8)
np.testing.assert_equal(miss, [True])
with pytest.raises(ValueError, match=r"No data for selected period."):
missing.missing_any(ts, freq="YS", month=1)
miss = missing.missing_any(ts, freq="YS", month=[7, 8])
np.testing.assert_equal(miss, [True])
ts = tasmin_series(np.zeros(76))
miss = missing.missing_any(ts, freq="YS", month=[7, 8])
np.testing.assert_equal(miss, [False])
def test_to_period_end(self, tasmin_series):
a = np.zeros(365) + K2C + 5.0
a[2] -= 20
ts = tasmin_series(a)
miss = missing.missing_any(ts, freq="A-JUN")
np.testing.assert_equal(miss, [False])
def test_missing_season(self):
n = 378
times = pd.date_range("2001-12-31", freq="1D", periods=n)
da = xr.DataArray(np.arange(n), [("time", times)])
miss = missing.missing_any(da, "Q-NOV")
np.testing.assert_array_equal(miss, [True, False, False, False, True])
def test_missing_months(self):
n = 66
times = pd.date_range("2001-12-30", freq="1D", periods=n)
da = xr.DataArray(np.arange(n), [("time", times)])
miss = missing.missing_any(da, "MS")
np.testing.assert_array_equal(miss, [True, False, False, True])
def test_hourly(self, pr_hr_series):
a = np.arange(2.0 * 32 * 24)
a[5:10] = np.nan
pr = pr_hr_series(a)
out = missing.missing_any(pr, freq="MS")
np.testing.assert_array_equal(out, [True, False, True])
