xarray.Dataset.pr.quantify

xarray.Dataset.pr.quantify#

Dataset.pr.quantify(units=None, **unit_kwargs) → Dataset#

Attaches units to each variable in the Dataset.

Units can be specified as a pint.Unit or as a string. If no units are specified then the units will be parsed from the "units" entry of the Dataset variable’s .attrs. Will raise a ValueError if any of the variables already contain a unit-aware array.

This function is a wrapper for pint_xarrays function with the same name, which uses the primap2 unit registry. Calling ds.pr.quantify() is therefore equivalent to calling ds.pint.quantify(unit_registry=primap2.ureg)

Note

Be aware that unless you’re using dask this will load the data into memory. To avoid that, consider converting to dask first (e.g. using chunk).

As units in dimension coordinates are not supported until xarray changes the way it implements indexes, these units will be set as attributes.

Parameters:
unitsmapping of hashable to unit-like, optional

Physical units to use for particular DataArrays in this Dataset. It should map variable names to units (unit names or pint.Unit objects). If not provided, will try to read them from Dataset[var].attrs['units'] using pint’s parser. The "units" attribute will be removed from all variables except from dimension coordinates.

**unit_kwargs

Keyword argument form of units.

Returns:
quantifiedDataset

The variables in quantified will now contain Quantity arrays with units.

Examples

>>> import xarray as xr
>>> import primap2
>>> ds = xr.Dataset(
...     {"a": ("x", [0, 3, 2], {"units": "m"}), "b": ("x", [5, -2, 1])},
...     coords={"x": [0, 1, 2], "u": ("x", [-1, 0, 1], {"units": "s"})},
... )
>>> ds
<xarray.Dataset> Size: ...
Dimensions:  (x: 3)
Coordinates:
  * x        (x) int... 0 1 2
    u        (x) int... -1 0 1
Data variables:
    a        (x) int... 0 3 2
    b        (x) int... 5 -2 1

>>> ds.pr.quantify()
<xarray.Dataset> Size: ...
Dimensions:  (x: 3)
Coordinates:
  * x        (x) int... 0 1 2
    u        (x) int... [s] -1 0 1
Data variables:
    a        (x) int... [m] 0 3 2
    b        (x) int... 5 -2 1
>>> ds.pr.quantify({"b": "dm"})
<xarray.Dataset> Size: ...
Dimensions:  (x: 3)
Coordinates:
  * x        (x) int... 0 1 2
    u        (x) int... [s] -1 0 1
Data variables:
    a        (x) int... [m] 0 3 2
    b        (x) int... [dm] 5 -2 1
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