def test_corr_grid_and_ts_dask(ts_monthly_da, gridded_da_datetime):
"""Tests that correlation works between a grid and a time series with dask."""
x = ts_monthly_da().chunk()
y = gridded_da_datetime().chunk()
expected = corr(x.load(), y.load(), dim='time')
actual = corr(x, y, dim='time').compute()
assert (expected == actual).all()
def test_corr_two_grids_dask(gridded_da_float):
"""Tests that correlations between two grids work with dask."""
x = gridded_da_float().chunk()
y = gridded_da_float().chunk()
expected = corr(x.load(), y.load(), dim='time')
actual = corr(x, y, dim='time').compute()
assert (expected == actual).all()
def test_autocorr(gridded_da_float):
"""Tests that ``autocorr`` functions properly."""
x = gridded_da_float()
actual = autocorr(x, nlags=None)
actual = autocorr(x, nlags=10)
expected = xr.concat([corr(x, x, lead=i) for i in range(10)], 'lead')
assert (actual.values == expected.values).all()
def decorrelation_time(da, r=20, dim="time"):
"""Calculate the decorrelaton time of a time series.
.. math::
\\tau_{d} = 1 + 2 * \\sum_{k=1}^{r}(\\alpha_{k})^{k}
Args:
da (xarray object): Time series.
r (optional int): Number of iterations to run the above formula.
dim (optional str): Time dimension for xarray object.
Returns:
Decorrelation time of time series.
Reference:
* Storch, H. v, and Francis W. Zwiers. Statistical Analysis in Climate
Research. Cambridge ; New York: Cambridge University Press, 1999.,
p.373
"""
one = xr.ones_like(da.isel({dim: 0}))
one = one.where(da.isel({dim: 0}).notnull())
return one + 2 * xr.concat(
[corr(da, da, dim=dim, lead=i)**i
for i in range(1, r)], "it").sum("it")
def test_corr_return_p(gridded_da_float):
"""Tests that p-value is returned properly for correlation."""
x = gridded_da_float()
y = gridded_da_float()
corrcoeff, pval = corr(x, y, dim='time', return_p=True)
assert not (corrcoeff.isnull().any()) & (pval.isnull().any())
def test_corr_two_grids(gridded_da_float):
"""Tests that correlations between two grids work."""
x = gridded_da_float()
y = gridded_da_float()
corrcoeff = corr(x, y, dim='time')
assert not corrcoeff.isnull().any()
def test_corr_lag(gridded_da_float):
"""Tests negative lead for correlation."""
x = gridded_da_float()
y = gridded_da_float()
corrcoeff = corr(x, y, dim='time', lead=-3)
assert not corrcoeff.isnull().any()
def test_corr_grid_and_ts(ts_monthly_da, gridded_da_datetime):
"""Tests that correlation works between a grid and a time series."""
x = ts_monthly_da()
y = gridded_da_datetime()
corrcoeff = corr(x, y, dim='time')
assert not corrcoeff.isnull().any()
def test_corr_lead(gridded_da_float):
"""Tests positive lead for correlation."""
x = gridded_da_float()
y = gridded_da_float()
corrcoeff = corr(x, y, dim="time", lead=3)
assert not corrcoeff.isnull().any()