import functools
import xarray as xr
# <PATTERN>
[docs]def decorator(func):
@functools.wraps(func)
def wrapper_decorator(*args, **kwargs):
# Do something before
value = func(*args, **kwargs)
# Do something after
return value
return wrapper_decorator
# </PATTERN>
[docs]def can_use_xr_dataarray(func):
"""
Intended as a decorator. Most of the windowed time series methods are
intended to work with xarray.Dataset class. But I would like to be able
to pass them xarray.DataArray objects. This class casts a DataArray to a
Dataset, runs it through func and casts back to a DataArray.
A simuilar decorator should be written for numpy arrays.
Parameters
----------
func
Returns
-------
"""
@functools.wraps(func)
def wrapper_decorator(*args, **kwargs):
if isinstance(kwargs["data"], xr.DataArray):
kwargs["data"] = kwargs["data"].to_dataset("channel")
input_was_dataarray = True
else:
input_was_dataarray = False
if isinstance(func, staticmethod):
callable_func = func.__get__(None, object)
processed_obj = callable_func(*args, **kwargs)
else:
processed_obj = func(*args, **kwargs)
if input_was_dataarray:
processed_obj = processed_obj.to_dataarray()
return processed_obj
return wrapper_decorator