def test_interpolate_dataset(ds):
actual = ds.interpolate_na(dim='time')
# no missing values in var1
assert actual['var1'].count('time') == actual.dims['time']
# var2 should be the same as it was
assert_array_equal(actual['var2'], ds['var2'])
def test_interpolate_dataset(ds):
actual = ds.interpolate_na(dim="time")
# no missing values in var1
assert actual["var1"].count("time") == actual.dims["time"]
# var2 should be the same as it was
assert_array_equal(actual["var2"], ds["var2"])
def test_interpolate_dataset(ds):
actual = ds.interpolate_na(dim='time')
# no missing values in var1
assert actual['var1'].count('time') == actual.dims['time']
# var2 should be the same as it was
assert_array_equal(actual['var2'], ds['var2'])
def test_ffill_limit():
da = xr.DataArray(
[0, np.nan, np.nan, np.nan, np.nan, 3, 4, 5, np.nan, 6, 7],
dims='time')
result = da.ffill('time')
expected = xr.DataArray([0, 0, 0, 0, 0, 3, 4, 5, 5, 6, 7], dims='time')
assert_array_equal(result, expected)
result = da.ffill('time', limit=1)
expected = xr.DataArray([0, 0, np.nan, np.nan, np.nan, 3, 4, 5, 5, 6, 7],
dims='time')
def test_ffill_limit():
da = xr.DataArray(
[0, np.nan, np.nan, np.nan, np.nan, 3, 4, 5, np.nan, 6, 7],
dims='time')
result = da.ffill('time')
expected = xr.DataArray([0, 0, 0, 0, 0, 3, 4, 5, 5, 6, 7], dims='time')
assert_array_equal(result, expected)
result = da.ffill('time', limit=1)
expected = xr.DataArray(
[0, 0, np.nan, np.nan, np.nan, 3, 4, 5, 5, 6, 7], dims='time')
def test_get_loc(date_type, index):
result = index.get_loc('0001')
expected = [0, 1]
assert_array_equal(result, expected)
result = index.get_loc(date_type(1, 2, 1))
expected = 1
assert result == expected
result = index.get_loc('0001-02-01')
expected = 1
assert result == expected
def test_get_loc(date_type, index):
result = index.get_loc('0001')
expected = [0, 1]
assert_array_equal(result, expected)
result = index.get_loc(date_type(1, 2, 1))
expected = 1
assert result == expected
result = index.get_loc('0001-02-01')
expected = 1
assert result == expected
def test_interpolators_complex_out_of_bounds():
"""Ensure complex nans are used for complex data"""
xi = np.array([-1, 0, 1, 2, 5], dtype=np.float64)
yi = np.exp(1j * xi)
x = np.array([-2, 1, 6], dtype=np.float64)
expected = np.array(
[np.nan + np.nan * 1j, np.exp(1j), np.nan + np.nan * 1j], dtype=yi.dtype
)
for method, interpolator in [
("linear", NumpyInterpolator),
("linear", ScipyInterpolator),
]:
f = interpolator(xi, yi, method=method)
actual = f(x)
assert_array_equal(actual, expected)
def test_rolling_wrapped_bottleneck(self, da, name, center, min_periods) -> None:
bn = pytest.importorskip("bottleneck", minversion="1.1")
# Test all bottleneck functions
rolling_obj = da.rolling(time=7, min_periods=min_periods)
func_name = f"move_{name}"
actual = getattr(rolling_obj, name)()
expected = getattr(bn, func_name)(
da.values, window=7, axis=1, min_count=min_periods
)
assert_array_equal(actual.values, expected)
with pytest.warns(DeprecationWarning, match="Reductions are applied"):
getattr(rolling_obj, name)(dim="time")
# Test center
rolling_obj = da.rolling(time=7, center=center)
actual = getattr(rolling_obj, name)()["time"]
assert_equal(actual, da["time"])
def test_rolling_wrapped_bottleneck(
self, ds, name, center, min_periods, key
) -> None:
bn = pytest.importorskip("bottleneck", minversion="1.1")
# Test all bottleneck functions
rolling_obj = ds.rolling(time=7, min_periods=min_periods)
func_name = f"move_{name}"
actual = getattr(rolling_obj, name)()
if key == "z1": # z1 does not depend on 'Time' axis. Stored as it is.
expected = ds[key]
elif key == "z2":
expected = getattr(bn, func_name)(
ds[key].values, window=7, axis=0, min_count=min_periods
)
else:
raise ValueError
assert_array_equal(actual[key].values, expected)
# Test center
rolling_obj = ds.rolling(time=7, center=center)
actual = getattr(rolling_obj, name)()["time"]
assert_equal(actual, ds["time"])
def test_cftimeindex_field_accessors(index, field, expected):
result = getattr(index, field)
assert_array_equal(result, expected)
def test_cftimeindex_days_in_month_accessor(index):
result = index.days_in_month
expected = [date.daysinmonth for date in index]
assert_array_equal(result, expected)
def test_cftimeindex_dayofweek_accessor(index):
result = index.dayofweek
expected = [date.dayofwk for date in index]
assert_array_equal(result, expected)
def test_cftimeindex_dayofweek_accessor(index):
result = index.dayofweek
expected = [date.dayofwk for date in index]
assert_array_equal(result, expected)
def test_cftimeindex_field_accessors(index, field, expected):
result = getattr(index, field)
assert_array_equal(result, expected)