Python interface for space weather indices
Project description
PySpaceWeather
Python interface for space weather indices
This python module interfaces the space weather data available at https://celestrak.com/SpaceData/ and https://omniweb.gsfc.nasa.gov/ow.html. It includes the geomagnetic Ap and Kp indices, both the 3h values and the daily sum/averages. The data also include the solar f10.7 cm radio fluxes, the observed values as well as the 1 AU adjusted values, daily values and the 81-day running means. See Data sources below.
:warning: This package is in beta stage, that is, it works for the most part and the interface should not change (much) in future versions.
Documentation is available at https://pyspaceweather.readthedocs.io.
Install
Requirements
numpy
- requiredpandas
- requiredrequests
- required for updating the data filespytest
,pytest-mock
- optional, for testing
spaceweather
A pip
package called spaceweather
is available from the
main package repository, and can be installed with:
$ pip install spaceweather
The latest development version can be installed
with pip
directly from github
(see https://pip.pypa.io/en/stable/reference/pip_install/#vcs-support
and https://pip.pypa.io/en/stable/reference/pip_install/#git):
$ pip install [-e] git+https://github.com/st-bender/pyspaceweather.git
The other option is to use a local clone:
$ git clone https://github.com/st-bender/pyspaceweather.git
$ cd pyspaceweather
and then using pip
(optionally using -e
, see
https://pip.pypa.io/en/stable/reference/pip_install/#install-editable):
$ pip install [-e] .
or using setup.py
:
$ python setup.py install
Optionally, test the correct function of the module with
$ py.test [-v]
or even including the doctests in this document:
$ py.test [-v] --doctest-glob='*.md'
Usage
The python module itself is named spaceweather
and is imported as usual
by calling
>>> import spaceweather
Celestrak
The module provides two functions to access the data from
Celestrak,
sw_daily()
for the daily data
as available from the website, and ap_kp_3h()
for the 3h Ap and Kp values.
Both functions return pandas.DataFrame
s.
When the data available in the packaged version are too old for the use case,
they can be updated by passing update=True
to both functions, or by calling
update_data()
explicitly.
>>> import spaceweather as sw
>>> df_d = sw.sw_daily()
>>> df_d.loc["2000-01-01"].Apavg
30.0
>>> df_3h = sw.ap_kp_3h()
>>> df_3h.loc["2000-01-01 01:30:00"]
Ap 56.0
Kp 5.3
Name: 2000-01-01 01:30:00, dtype: float64
>>> # All 3h values for one day
>>> df_3h.loc["2000-01-01"]
Ap Kp
2000-01-01 01:30:00 56 5.3
2000-01-01 04:30:00 39 4.7
2000-01-01 07:30:00 27 4.0
2000-01-01 10:30:00 18 3.3
2000-01-01 13:30:00 32 4.3
2000-01-01 16:30:00 15 3.0
2000-01-01 19:30:00 32 4.3
2000-01-01 22:30:00 22 3.7
OMNI
The OMNI 1-hour yearly data
are accessible via omnie_hourly(<year>)
or read_omnie(<file>)
.
Both functions should work with the OMNI2 standard and extended text files.
If the data are not already available locally, they can be cached by passing
cache=True
to that function or by calling cache_omnie(<year>)
explicitly.
As for the Celestrak data, pandas.DataFrame
s are returned.
>>> import spaceweather as sw
>>> df_h = sw.omnie_hourly(2000) # doctest: +SKIP
>>> # or with automatic caching (downloading)
>>> df_h = sw.omnie_hourly(2000, cache=True) # doctest: +SKIP
If the data are already available locally, you can point the parser to that location:
>>> import spaceweather as sw
>>> df_h = sw.omnie_hourly(2000, local_path="/path/to/omni/data/") # doctest: +SKIP
Another option is to provide a filename directly to read_omnie()
:
>>> import spaceweather as sw
>>> df = sw.read_omnie("/path/to/omni/data/file.dat") # doctest: +SKIP
Reference
Basic class and method documentation is accessible via pydoc
:
$ pydoc spaceweather
$ pydoc spaceweather.celestrak
$ pydoc spaceweather.omni
License
This python interface is free software: you can redistribute it or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, version 2 (GPLv2), see local copy or online version.
Data sources
Celestrak
The "celestrak" data can be found at https://celestrak.com/SpaceData/ and is included with kind permission from Dr. T.S. Kelso at celestrak, for details see the included COPYING.data file.
The data sources and file format are described at http://celestrak.com/SpaceData/SpaceWx-format.php (see file_format.txt for a local copy of the format description).
OMNI
This package includes part of the hourly-resolved OMNI data, accessible through https://spdf.gsfc.nasa.gov/pub/data/omni/low_res_omni/, and it enables easy downloading of it. The file format is described at https://spdf.gsfc.nasa.gov/pub/data/omni/low_res_omni/omni2.text (local copy omni_format.txt) and the "extended" format at https://spdf.gsfc.nasa.gov/pub/data/omni/low_res_omni/extended/aareadme_extended (local copy omnie_format.txt).
If you use the OMNI data in your work, please read COPYING.omni carefully and cite the following publication:
King, Joseph H. and Natalia E. Papitashvili, Solar wind spatial scales in and comparisons of hourly Wind and ACE plasma and magnetic field data, J. Geophys. Res., 110, A02104, 2005.
Please acknowledge the OMNI sources, using the following DOIs for the OMNI datasets:
Papitashvili, Natalia E. and King, Joseph H. (2022), "OMNI 1-min Data" [Data set], NASA Space Physics Data Facility, https://doi.org/10.48322/45bb-8792
Papitashvili, Natalia E. and King, Joseph H. (2022), "OMNI 5-min Data" [Data set], NASA Space Physics Data Facility, https://doi.org/10.48322/gbpg-5r77
Papitashvili, Natalia E. and King, Joseph H. (2022), "OMNI Hourly Data" [Data Set], NASA Space Physics Data Facility, https://doi.org/10.48322/1shr-ht18
Papitashvili, Natalia E. and King, Joseph H. (2022), "OMNI Daily Data" [Data set], NASA Space Physics Data Facility, https://doi.org/10.48322/5fmx-hv56
Papitashvili, Natalia E. and King, Joseph H. (2022), "OMNI 27-Day Data" [Data set], NASA Space Physics Data Facility, https://doi.org/10.48322/nmh3-jf75
The OMNI data are also available from CDAWeb, and thus available via various other methods https://cdaweb.gsfc.nasa.gov/alternative_access_methods.html In particular, you might find our Python web service library useful https://pypi.org/project/cdasws Or through the HAPI streaming protocol https://github.com/hapi-server/client-python
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