gsee

GSEE: Global Solar Energy Estimator

https://github.com/renewables-ninja/gsee

Science Score: 57.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 3 DOI reference(s) in README
  • Academic publication links
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (14.6%) to scientific vocabulary

Keywords

electricity energy irradiance ninja pandas photovoltaic pv solar
Last synced: 6 months ago · JSON representation ·

Repository

GSEE: Global Solar Energy Estimator

Basic Info
  • Host: GitHub
  • Owner: renewables-ninja
  • License: bsd-3-clause
  • Language: Python
  • Default Branch: main
  • Homepage: https://gsee.readthedocs.io/
  • Size: 391 KB
Statistics
  • Stars: 137
  • Watchers: 13
  • Forks: 46
  • Open Issues: 8
  • Releases: 0
Topics
electricity energy irradiance ninja pandas photovoltaic pv solar
Created over 9 years ago · Last pushed 10 months ago
Metadata Files
Readme Changelog License Citation Authors

README.md

Master branch build status Test coverage PyPI version conda-forge version

GSEE: Global Solar Energy Estimator

GSEE is a solar energy simulation library designed for rapid calculations and ease of use. Renewables.ninja uses GSEE.

The development of GSEE predates the existence of pvlib-python but builds on its functionality as of v0.4.0. Use GSEE if you want fast simulations with sensible defaults and solar energy technologies other than PV, and pvlib-python if you need control over the nuts and bolts of simulating PV systems.

Installation

GSEE requires Python 3. The recommended way to install is through the Anaconda Python distribution and conda-forge:

conda install -c conda-forge gsee

You can also install with pip install gsee, but if you do so, and do not already have numpy installed, you will get a compiler error when pip tries to build to climatedata_interface Cython extension.

Documentation

See the documentation for more information on GSEE's functionality and for examples.

Credits and contact

Contact Stefan Pfenninger for questions about GSEE. GSEE is also a component of the Renewables.ninja project, developed by Stefan Pfenninger and Iain Staffell. Use the contact page there if you want more information about Renewables.ninja.

Citation

If you use GSEE or code derived from it in academic work, please cite:

Stefan Pfenninger and Iain Staffell (2016). Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data. Energy 114, pp. 1251-1265. doi: 10.1016/j.energy.2016.08.060

License

BSD-3-Clause

Owner

  • Name: Renewables.ninja
  • Login: renewables-ninja
  • Kind: organization

Renewable energy simulations, ninja style.

Citation (CITATION)

To reference GSEE in publications, please cite the following paper:

Stefan Pfenninger and Iain Staffell (2016). Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data. Energy 114, pp. 1251-1265. https://dx.doi.org/10.1016/j.energy.2016.08.060

GitHub Events

Total
  • Issues event: 1
  • Watch event: 15
  • Push event: 5
  • Fork event: 6
  • Create event: 1
Last Year
  • Issues event: 1
  • Watch event: 15
  • Push event: 5
  • Fork event: 6
  • Create event: 1

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 66
  • Total Committers: 3
  • Avg Commits per committer: 22.0
  • Development Distribution Score (DDS): 0.061
Past Year
  • Commits: 9
  • Committers: 1
  • Avg Commits per committer: 9.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Stefan Pfenninger s****n@p****g 62
muelljoh 4****h 3
tsaoyu t****u@t****m 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 7
  • Total pull requests: 11
  • Average time to close issues: 2 months
  • Average time to close pull requests: about 1 month
  • Total issue authors: 7
  • Total pull request authors: 6
  • Average comments per issue: 0.43
  • Average comments per pull request: 0.73
  • Merged pull requests: 4
  • Bot issues: 0
  • Bot pull requests: 1
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • phumthep (1)
  • ChanceQZ (1)
  • moijn001 (1)
  • mfleschutz (1)
  • jwohland (1)
  • rabwent11 (1)
Pull Request Authors
  • muelljoh (5)
  • tsaoyu (2)
  • knyghty (1)
  • arjunane (1)
  • jwohland (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 2
  • Total downloads:
    • pypi 86 last-month
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 1
    (may contain duplicates)
  • Total versions: 5
  • Total maintainers: 1
pypi.org: gsee

GSEE: Global Solar Energy Estimator

  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 86 Last month
Rankings
Forks count: 6.4%
Stargazers count: 7.1%
Dependent packages count: 7.4%
Average: 11.2%
Downloads: 12.8%
Dependent repos count: 22.2%
Maintainers (1)
Last synced: 6 months ago
conda-forge.org: gsee

GSEE is a solar energy simulation library designed for rapid calculations and ease of use.

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Forks count: 26.4%
Stargazers count: 31.3%
Dependent repos count: 34.0%
Average: 35.7%
Dependent packages count: 51.2%
Last synced: 6 months ago

Dependencies

requirements_docs.txt pypi
  • mkautodoc *
  • mkdocs ==1.0.4
  • mkdocs-material ==4.6.0
  • mkdocs-minify-plugin *
  • pymdown-extensions ==6.2
pyproject.toml pypi
requirements.txt pypi
  • pandas ==1.4.3
  • pvlib >=0.10.4,<0.11
  • pyephem >=9.99,<10
  • xarray ==2022.6