import pyspedas
import copy
import logging
[docs]
def interp_nan(tvar, newname=None, s_limit=None):
"""
Interpolates the tplot variable through NaNs in the data. This is basically just a wrapper for xarray's interpolate_na function.
.. note::
This analysis routine assumes the data is no more than 2 dimensions. If there are more, they may become flattened!
Parameters
----------
tvar : str
Name of tplot variable.
newname : str
Name of new tvar for added data. If not set, then the original tvar is replaced.
s_limit : int or float, optional
The maximum size of the gap in seconds to not interpolate over. I.e. if there are too many NaNs in a row, leave them there.
Returns
-------
None
Examples
--------
>>> import pyspedas
>>> import numpy as np
>>> pyspedas.store_data('e', data={'x':[2,5,8,11,14,17,21], 'y':[[np.nan,1,1],[np.nan,2,3],[4,np.nan,47],[4,np.nan,5],[5,5,99],[6,6,25],[7,np.nan,-5]]})
>>> pyspedas.interp_nan('e','e_nonan',s_limit=5)
"""
x = pyspedas.tplot_tools.data_quants[tvar].interpolate_na(dim="time", limit=s_limit)
x.attrs = copy.deepcopy(pyspedas.tplot_tools.data_quants[tvar].attrs)
if newname is None:
pyspedas.tplot_tools.data_quants[tvar] = x
x.name = tvar
else:
pyspedas.tplot_tools.data_quants[newname] = x
pyspedas.tplot_tools.data_quants[newname].name = newname