NLFFF 3D Dataset
Based on the vector magnetic field data observed by Helioseismic and Magnetic Imager(HMI) on the Solar Dynamics Observatory (SDO), we have built a 3D solar active region magnetic field dataset using the Nonlinear Force-Free Coronal Magnetic Field (NLFFF)Extrapolations.
The current total is over 200 TB, 73,000 3D magnetograms spanning the years 2010 to 2019, with a temporal resolution of 96 minutes and a spatial resolution consistent with the original sharp cea magnetograms.
Toolkit
Install
pip install pynlfff
# or
pip install git+https://github.com/deepsolar/pynlfff.git
Usage
Metadata
Release files for pynlfff 0.3.3.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| pynlfff-0.3.3.5.tar.gz | 38.7 kB | Without provenance | Details for pynlfff-0.3.3.5.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| pynlfff-0.3.3.5-py3-none-any.whl | Python 3 | none | any | Details for pynlfff-0.3.3.5-py3-none-any.whl |
Total release size: 83.2 kB
Release files / pynlfff-0.3.3.5.tar.gz
| Download URL | pynlfff-0.3.3.5.tar.gz |
|---|---|
| Size | 38.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
18c9228c0f987bdeda019df244d3cc7989ce2ab49844b97b51d843a1d63a0ac7
|
|
BLAKE2b-256 checksum How to use checksums |
4efe714bc7de1c3cf19e05bf87c5a85ef79bec2d5c4fb9ffcfab6a3a17d7a621
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.7
|
Release files / pynlfff-0.3.3.5-py3-none-any.whl
| Download URL | pynlfff-0.3.3.5-py3-none-any.whl |
|---|---|
| Size | 44.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
53a33bf00845286f5d177c374756edda3015d41fee359d784a1e4166867f3e30
|
|
BLAKE2b-256 checksum How to use checksums |
4b1321244d9243980fe2ab7ebb80187449a4798d7956e339bf8e179295f09a6e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.7
|
Security for pynlfff 0.3.3.5
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.