vespa
Validation of Exoplanet Signals using a Probabilistic Algorithm--- calculating false positive probabilities for transit signals
Science Score: 46.0%
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Found 2 DOI reference(s) in README -
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Low similarity (15.9%) to scientific vocabulary
Last synced: 7 months ago
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Validation of Exoplanet Signals using a Probabilistic Algorithm--- calculating false positive probabilities for transit signals
Basic Info
- Host: GitHub
- Owner: timothydmorton
- License: mit
- Language: Jupyter Notebook
- Default Branch: master
- Size: 180 MB
Statistics
- Stars: 37
- Watchers: 8
- Forks: 21
- Open Issues: 18
- Releases: 7
Created about 11 years ago
· Last pushed almost 3 years ago
Metadata Files
Readme
License
README.rst
Note: Current recommendation is to retire VESPA in favor of TRICERATOPS (https://github.com/stevengiacalone/triceratops); see research note posted at https://iopscience.iop.org/article/10.3847/2515-5172/acd9a6 for more details.
VESPA
======
.. image:: https://travis-ci.com/timothydmorton/VESPA.svg?branch=master
:target: https://travis-ci.com/timothydmorton/VESPA
Validation of Exoplanet Signals using a Probabilistic Algorithm--- calculating false positive probabilities for transit signals
For usage and more info, `check out the documentation `_.
Installation
------------
To install, you can get the most recently released version from PyPI::
pip install vespa [--user]
Or you can clone the repository::
git clone https://github.com/timothydmorton/vespa.git
cd vespa
python setup.py install [--user]
The ``--user`` argument may be necessary if you don't have root privileges.
Depends on typical scientific packages (e.g. `numpy`, `scipy`, `pandas`),
as well as `isochrones `_, and (in several corners of the code), another package of mine called `simpledist `_. All dependencies *should* get resolved upon install, though this has only been tested under the anaconda Python distribution, which has all the scientific stuff already well-organized.
For best results, it is also recommended to have ``MultiNest`` and ``pymultinest`` installed. Without this, ``emcee`` will be used for stellar modeling, but the ``MulitNest`` results are a bit more trustworthy given the often multi-modal nature of stellar model fitting.
Basic Usage
-----------
The simplest way to run an FPP calculation straight out of the box is
as follows.
1. Make a text file containing the transit photometry in three columns: ``t_from_midtransit`` [days], ``flux`` [relative, where out-of-transit is normalized to unity], and ``flux_err``. The file should not have a header row (no titles); and can be either whitespace or comma-delimited (will be ingested by ``np.loadtxt``).
2. Make a ``star.ini`` file that contains the observed properties of the target star (photometric and/or spectroscopic, whatever is available)::
#provide spectroscopic properties if available
#Teff = 3503, 80 #value, uncertainty
#feh = 0.09, 0.09
#logg = 4.89, 0.1
#observed magnitudes of target star
# If uncertainty provided, will be used to fit StarModel
J = 9.763, 0.03
H = 9.135, 0.03
K = 8.899, 0.02
Kepler = 12.473
3. Make a ``fpp.ini`` file containing the following information::
name = k2oi #anything
ra = 11:30:14.510 #can be decimal form too
dec = +07:35:18.21
period = 32.988 #days
rprs = 0.0534 #Rp/Rstar best estimate
photfile = lc_k2oi.csv #contains transit photometry
[constraints]
maxrad = 12 # aperture radius [arcsec]
secthresh = 1e-4 # Maximum allowed depth of potential secondary eclipse
4. Run the following from the command line (from within the same folder that has ``star.ini`` and ``fpp.ini``)::
$ calcfpp
Or, if you put the files in a folder called ``mycandidate``, then you can run ``calcfpp mycandidate``::
This will run the calculation for you, creating result files, diagnostic plots, etc.
It should take 20-30 minutes. If you want to do a shorter
version to test, you can try ``calcfpp -n 1000`` (the default is 20000). The first
time you run it though, about half the time is doing the stellar modeling, so it will still
take a few minutes.
Attribution
-----------
If you use this code, please cite both the paper and the code.
Paper citation::
@ARTICLE{2012ApJ...761....6M,
author = {{Morton}, T.~D.},
title = "{An Efficient Automated Validation Procedure for Exoplanet Transit Candidates}",
journal = {\apj},
archivePrefix = "arXiv",
eprint = {1206.1568},
primaryClass = "astro-ph.EP",
keywords = {planetary systems, stars: statistics },
year = 2012,
month = dec,
volume = 761,
eid = {6},
pages = {6},
doi = {10.1088/0004-637X/761/1/6},
adsurl = {http://adsabs.harvard.edu/abs/2012ApJ...761....6M},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
code::
@MISC{2015ascl.soft03011M,
author = {{Morton}, T.~D.},
title = "{VESPA: False positive probabilities calculator}",
howpublished = {Astrophysics Source Code Library},
year = 2015,
month = mar,
archivePrefix = "ascl",
eprint = {1503.011},
adsurl = {http://adsabs.harvard.edu/abs/2015ascl.soft03011M},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
Owner
- Name: Timothy Morton
- Login: timothydmorton
- Kind: user
- Repositories: 101
- Profile: https://github.com/timothydmorton
GitHub Events
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Last Year
Committers
Last synced: over 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| Timothy Morton | t****n@g****m | 547 |
| Timothy Morton | t****m@a****u | 79 |
| Ben Bar-Or | b****r@g****m | 6 |
| Dan F-M | d****m@n****u | 1 |
| Guest User | G****t@i****u | 1 |
| iancrossfield | i****d | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 7 months ago
All Time
- Total issues: 30
- Total pull requests: 8
- Average time to close issues: about 2 months
- Average time to close pull requests: 11 months
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- Total pull request authors: 7
- Average comments per issue: 3.5
- Average comments per pull request: 0.5
- Merged pull requests: 4
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Past Year
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- Pull requests: 0
- Average time to close issues: N/A
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- Average comments per issue: 0
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- elisabethadams (2)
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Packages
- Total packages: 1
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Total downloads:
- pypi 139 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 24
- Total maintainers: 1
pypi.org: vespa
Calculate astrophysical false positive probabilities for transiting exoplanet signals
- Homepage: https://github.com/timothydmorton/VESPA
- Documentation: https://vespa.readthedocs.io/
- License: mit
-
Latest release: 0.5.1
published over 7 years ago
Rankings
Forks count: 8.4%
Dependent packages count: 10.0%
Stargazers count: 10.7%
Average: 14.3%
Downloads: 20.7%
Dependent repos count: 21.7%
Maintainers (1)
Last synced:
7 months ago
Dependencies
setup.py
pypi
- batman-package >=2.1
- configobj *
- emcee *
- isochrones >=1.1.1
- pandas >=0.21
- simpledist >=0.1.13