Source code for pyrfu.mms.feeps_remove_sun
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# 3rd party imports
import numpy as np
import xarray as xr
# Local imports
from .read_feeps_sector_masks_csv import read_feeps_sector_masks_csv
__author__ = "Louis Richard"
__email__ = "louisr@irfu.se"
__copyright__ = "Copyright 2020-2023"
__license__ = "MIT"
__version__ = "2.4.2"
__status__ = "Prototype"
[docs]def feeps_remove_sun(inp_dataset):
r"""Removes the sunlight contamination from FEEPS data.
Parameters
----------
inp_dataset : xarray.Dataset
Dataset of energy spectrum of all eyes.
Returns
-------
out : xarray.Dataset
Dataset of cleaned energy spectrum of all eyes.
See also
--------
pyrfu.mms.get_feeps_alleyes : Read energy spectrum for all FEEPS eyes.
Examples
--------
>>> from pyrfu import mms
Define time interval
>>> tint = ["2017-07-18T13:04:00.000", "2017-07-18T13:07:00.000"]
Spacecraft index
>>> mms_id = 2
Load data from FEEPS
>>> cps_i = mms.get_feeps_alleyes("CPSi_brst_l2", tint, mms_id)
>>> cps_i_clean, _ = mms.feeps_split_integral_ch(cps_i)
>>> cps_i_clean_sun_removed = mms.feeps_remove_sun(cps_i_clean)
"""
var = inp_dataset.attrs
tint = list(np.datetime_as_string(inp_dataset.time.data[[0, -1]], "ns"))
spin_sectors = inp_dataset["spinsectnum"]
mask_sectors = read_feeps_sector_masks_csv(tint)
out_dict = {}
out_dict["spinsectnum"] = inp_dataset["spinsectnum"]
for k in inp_dataset:
out_dict[k] = inp_dataset[k]
if mask_sectors.get(f"mms{var['mmsId']:d}_imask_{k}") is not None:
bad_sectors = mask_sectors[f"mms{var['mmsId']:d}_imask_{k}"]
for bad_sector in bad_sectors:
this_bad_sector = np.where(spin_sectors == bad_sector)[0]
if len(this_bad_sector) != 0:
out_dict[k].data[this_bad_sector] = np.nan
out = xr.Dataset(out_dict, attrs=var)
out.attrs = var
return out