Tools for downloading and reading space-weather data and geomagnetic indices.
Project description
SWVO @ GFZ
Introduction
This package provides a set of tools for managing solar data in Python. It includes functionalities for reading, writing, and processing data from various sources.
Example
from datetime import datetime, timezone
from swvo.io.solar_wind import SWACE
ACE_DIR = "./ace_data/" #data directory for ACE data
start = datetime(2024, 11, 20, 0, 0, tzinfo=timezone.utc)
end = datetime(2024, 11, 20, 6, 0, tzinfo=timezone.utc)
#Read ACE solar wind data with downloading
ace_df = swace.read(start, end, download=True)
See here for a detailed example docs/examples/solar_wind_example.ipynb
Space Weather Data Overview
This package provides tools to read, process, and analyze several key solar and geomagnetic indices. For each index, the available data sources and the corresponding reader classes are listed below:
-
Kp Index:
A global geomagnetic activity index with a 3-hour cadence, ranging from 0 (quiet) to 9 (extremely disturbed). Used to assess geomagnetic storm conditions.- Sources & Classes:
- OMNI:
KpOMNI - SWPC:
KpSWPC - Niemegk:
KpNiemegk - Ensemble:
KpEnsemble - Combined:
read_kp_from_multiple_models
- OMNI:
- Sources & Classes:
-
Dst Index:
The Disturbance Storm Time (Dst) index measures the intensity of the Earth's ring current, related to geomagnetic storms. Provided hourly and is negative during storm conditions.- Sources & Classes:
- OMNI:
DSTOMNI - WDC:
DSTWDC - Combined:
read_dst_from_multiple_models
- OMNI:
- Sources & Classes:
-
Hp Index:
The Hp30 and Hp60 indices are high-cadence (30-minute and 60-minute) geomagnetic indices provided by GFZ, used for detailed geomagnetic activity studies.- Sources & Classes:
- GFZ:
HpGFZ - Ensemble:
HpEnsemble - Combined:
read_hp_from_multiple_models
- GFZ:
- Sources & Classes:
-
F10.7 Index:
The F10.7 solar radio flux index is a daily measure of solar activity (flux density at 10.7 cm), a standard proxy for solar EUV emissions.- Sources & Classes:
- OMNI:
F107OMNI - SWPC:
F107SWPC - Combined:
read_f107_from_multiple_models
- OMNI:
- Sources & Classes:
-
Solar Wind Parameters:
Access to solar wind data (speed, density, magnetic field components) from various spacecraft. Essential for solar-terrestrial interaction studies.- Sources & Classes:
- ACE:
SWACE - DSCOVR:
DSCOVR - OMNI:
SWOMNI - SWIFT:
SWSWIFTEnsemble - Combined:
read_solar_wind_from_multiple_models
- ACE:
- Sources & Classes:
Each index can be accessed via these dedicated reader classes, which handle downloading and read methods. See the code in swvo/io or API documentation for details on each index's implementation.
Installation
To install the package, run the following command:
uv venv
source .venv/bin/activate
python -m ensurepip --upgrade
uv pip install --upgrade pip
uv pip install -e .
or it can be installed directly from PyPI:
uv pip install swvo
All the above uv commands assume you have uv installed, if not then remove uv prefix from the commands and run them directly.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file swvo-1.2.1.tar.gz.
File metadata
- Download URL: swvo-1.2.1.tar.gz
- Upload date:
- Size: 36.1 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e1e8cca40ef4995564cd0e9e9ddacc7e855b1383ab6f389abc2eaa33074ccdba
|
|
| MD5 |
4faf8f1fe2dc03fe818ab32846ed789e
|
|
| BLAKE2b-256 |
512a42c1bcbb7e77afa8fbe5b977fd1cd8d61fa24a305ee5097ddd36ea79c8a3
|
File details
Details for the file swvo-1.2.1-py3-none-any.whl.
File metadata
- Download URL: swvo-1.2.1-py3-none-any.whl
- Upload date:
- Size: 107.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
36c7b32b1b60b80c8ccb05821a7e17f347bff0de4b681ac57313b6034850f0e1
|
|
| MD5 |
939a07531672ce722eeeb045708fd5a9
|
|
| BLAKE2b-256 |
e68a8aa3734682720f41b4829022d7cd915dabe0a825b8e1a5fa7dd547d142c6
|