Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 1 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (10.2%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: robertdstein
- License: mit
- Language: Jupyter Notebook
- Default Branch: main
- Size: 1.54 MB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 1
- Releases: 2
Metadata Files
README.md
tdescore
Disclaimer: This code is provided in an open source format in case pieces are helpful to others. However, the ZTF classifications used to train tdescore have not yet been released! You can (and are strongly encouraged to) use tdescore for your own classifier projects, but without access to internal ZTF data you cannot directly reproduce the original tdescore analysis.
Install Instructions
tdescore is a python package. We recommend using conda to install it.
commandline
conda create -n tdescore python=3.11
conda activate tdescore
git clone git@github.com:robertdstein/tdescore.git
pip install -e tdescore
(Python 3.12 is not yet supported as of 2023-11-22, but is expected soon).
Sfdmap
You will also need to install the sfdmap2 package, and sfdmap files.
See instructions at https://github.com/AmpelAstro/sfdmap2
Usage
tdescore is modular.
First you need raw data. ZTF collaboration members can use Ampel to download ZTF lightcurves:
commandline
python -m tdescore.raw
However, any raw data in the appropriate jsonnstyle would work. It does not need to be from ZTF! An example is provided under sample_data.
Next, you should collate the additional data you want to use for classification. You can run these commands in any order, and omit steps you do not want.
For downloading cross-matched data from public catalogs:
commandline python -m tdescore.downloadFor analysing lightcurves with gaussian processes:
commandline python -m tdescore.lightcurve
Owner
- Name: Robert David Stein
- Login: robertdstein
- Kind: user
- Location: Pasadena, CA, USA
- Company: Caltech
- Website: https://robertdstein.github.io/
- Repositories: 45
- Profile: https://github.com/robertdstein
Postdoc at Caltech, working on Multimessenger Astronomy.
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: "Stein" given-names: "Robert" orcid: "https://orcid.org/0000-0003-2434-0387" title: "tdescore" version: 1.0.0 doi: 10.5281/zenodo.1234 date-released: 2024-03-05 url: "https://github.com/robertdstein/tdescore"
GitHub Events
Total
- Release event: 1
- Watch event: 1
- Delete event: 3
- Push event: 17
- Pull request event: 5
- Create event: 3
Last Year
- Release event: 1
- Watch event: 1
- Delete event: 3
- Push event: 17
- Pull request event: 5
- Create event: 3
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 0
- Total pull requests: 3
- Average time to close issues: N/A
- Average time to close pull requests: less than a minute
- Total issue authors: 0
- Total pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 3
- Average time to close issues: N/A
- Average time to close pull requests: less than a minute
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- robertdstein (1)
Pull Request Authors
- robertdstein (5)
Top Labels
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Dependencies
- astropy 4.3.1
- jupyter ^1.0.0
- mosfit ^1.1.8
- mpi4py 3.1.4
- numpy 1.21.0
- python ~3.10
- ruamel.yaml ^0.17.21