Method cov

xarray/computation/rolling_exp.py:228–256

Exponentially weighted moving covariance. `keep_attrs` is always True for this method. Drop attrs separately to remove attrs. Examples -------- >>> da = xr.DataArray([1, 1, 2, 2, 2], dims="x") >>> da.rolling_exp(x=2, window_type="span").cov(da**2)

(self, other: T_DataWithCoords)

        ).transpose(*dim_order)

    def cov(self, other: T_DataWithCoords) -> T_DataWithCoords:
        """
        Exponentially weighted moving covariance.

        `keep_attrs` is always True for this method. Drop attrs separately to remove attrs.

        Examples
        --------
        >>> da = xr.DataArray([1, 1, 2, 2, 2], dims="x")
        >>> da.rolling_exp(x=2, window_type="span").cov(da**2)
        <xarray.DataArray (x: 5)> Size: 40B
        array([       nan, 0.        , 1.38461538, 0.55384615, 0.19338843])
        Dimensions without coordinates: x
        """

        dim_order = self.obj.dims
        import numbagg

        return apply_ufunc(
            numbagg.move_exp_nancov,
            self.obj,
            other,
            input_core_dims=[[self.dim], [self.dim]],
            kwargs=self.kwargs,
            output_core_dims=[[self.dim]],
            keep_attrs=True,
            on_missing_core_dim="copy",
            dask="parallelized",
        ).transpose(*dim_order)

    def corr(self, other: T_DataWithCoords) -> T_DataWithCoords:
        """