# `cdips`
Cluster Difference Imaging Photometric Survey
## Description
This repository contains some of the code developed for the [CDIPS
project](https://arxiv.org/abs/1910.01133). If you are interested in light
curves, they can be accessed [through
MAST](https://archive.stsci.edu/hlsp/cdips); planet-finding vetting reports are
available at [ExoFOP-TESS](https://exofop.ipac.caltech.edu/tess/) and have
documentation [available here](http://lgbouma.com/notes/).
The tools in this repo can be understood as answers to the question "what do
you do once the [cdips-pipeline](https://github.com/waqasbhatti/cdips-pipeline)
gives you light curves?".
Some possible answers include "find planets", "measure stellar rotation
periods", and "find weird variable stars". This question is also in many cases
applicable to any time-series data, and some of the tools in this repository
are developed with that generality in mind.
Directory contents are as follows.
* `/drivers/` is the interface to make target catalogs, find planet candidates
and variable stars, classify, vet the classifications, and make plots and
tables for papers. See /drivers/HOWTO.md for instructions.
* `/cdips/` is a python package with tools to make target catalogs, process
light curves, optimize cdips-pipeline parameters, plot and analyze light
curves.
* `/paper_I/` contains the CDIPS method paper.
* `/tests/` has testing scripts for vetting report generation, HLSP light curve
generation, and detrending method comparison. pytest & CI are not set up for
this repo.
## Author
Luke Bouma
## License
MIT
## Install
`pip install cdips`
`git clone https://github.com/lgbouma/cdips`
`python setup.py install`
to verify you have the dependencies (with apologies for not making this
automatic in the installation; some of the dependencies are fairly obscure)
`cd cdips/tests`
`python test_environment.py`
One place to start if you are building an environment from scratch:
`conda env create -f environment.yml -n py38`
## Update env
`conda env export --no-builds > environment.yml`
## Relevant reading
1. [CDIPS-I: Methods](https://ui.adsabs.harvard.edu/abs/2019ApJS..245...13B/abstract)
2. [CDIPS-II: TOI-837b](https://ui.adsabs.harvard.edu/abs/2020AJ....160..239B/abstract)
3. [CDIPS-III: NGC-2516](https://ui.adsabs.harvard.edu/abs/2021AJ....162..197B/abstract)
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"description": "# `cdips`\nCluster Difference Imaging Photometric Survey\n\n## Description\n\nThis repository contains some of the code developed for the [CDIPS\nproject](https://arxiv.org/abs/1910.01133). If you are interested in light\ncurves, they can be accessed [through\nMAST](https://archive.stsci.edu/hlsp/cdips); planet-finding vetting reports are\navailable at [ExoFOP-TESS](https://exofop.ipac.caltech.edu/tess/) and have\ndocumentation [available here](http://lgbouma.com/notes/).\n\nThe tools in this repo can be understood as answers to the question \"what do\nyou do once the [cdips-pipeline](https://github.com/waqasbhatti/cdips-pipeline)\ngives you light curves?\".\n\nSome possible answers include \"find planets\", \"measure stellar rotation\nperiods\", and \"find weird variable stars\". This question is also in many cases\napplicable to any time-series data, and some of the tools in this repository\nare developed with that generality in mind.\n\nDirectory contents are as follows.\n\n* `/drivers/` is the interface to make target catalogs, find planet candidates\n and variable stars, classify, vet the classifications, and make plots and\n tables for papers. See /drivers/HOWTO.md for instructions.\n\n* `/cdips/` is a python package with tools to make target catalogs, process\n light curves, optimize cdips-pipeline parameters, plot and analyze light\n curves.\n\n* `/paper_I/` contains the CDIPS method paper.\n\n* `/tests/` has testing scripts for vetting report generation, HLSP light curve\n generation, and detrending method comparison. pytest & CI are not set up for\n this repo.\n\n## Author\n\nLuke Bouma\n\n## License\n\nMIT\n\n## Install\n\n`pip install cdips`\n\n`git clone https://github.com/lgbouma/cdips`\n`python setup.py install`\n\nto verify you have the dependencies (with apologies for not making this\nautomatic in the installation; some of the dependencies are fairly obscure)\n\n`cd cdips/tests`\n`python test_environment.py`\n\nOne place to start if you are building an environment from scratch:\n\n`conda env create -f environment.yml -n py38`\n\n## Update env\n\n`conda env export --no-builds > environment.yml`\n\n## Relevant reading\n\n1. [CDIPS-I: Methods](https://ui.adsabs.harvard.edu/abs/2019ApJS..245...13B/abstract)\n\n2. [CDIPS-II: TOI-837b](https://ui.adsabs.harvard.edu/abs/2020AJ....160..239B/abstract)\n\n3. [CDIPS-III: NGC-2516](https://ui.adsabs.harvard.edu/abs/2021AJ....162..197B/abstract)\n",
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