False positive probabilities for all KOIs in the Q1-Q17 (DR24) Kepler table. The one-stop-shop table for the summarized FPP results is fpp_final_table.csv.
If you're curious about individual KOIs and want to browse the diagnostic/result plots, please go here.
If you're really curious, all the data files produced by these
calculations are currently hosted at Princeton. To browse the
results from a given KOI, visit
tigress-web.princeton.edu/~tmorton/koi-fpp/K?????.??
, with the
appropriate KOI identifier. These directories contain the entire
vespa
and isochrones
outputs for every KOI (including the stellar
posteriors for the single-, binary- and triple-star fits). If you
have specific questions, please feel free to contact me.
The manuscript PDF can be generated by entering the document
directory
and running make
.
The fpp-results-analysis.ipynb
and starprop-analysis.ipynb
notebooks
contain all the commands to make the figures & tables that live in
the document
directory, with the exception of the Santerne+ (2015)
comparison table, which is created by santerne_compare.ipynb
.
You can run your own FPP calculations using all of the same data and constraints that I used for this work. If you wish to do this, first test out the calculation for the KOI for which I provide example data in this repository (KOI-7016.01/Kepler-452b).
First, clone this repository and hop on in:
git clone https://github.com/timothydmorton/koi-fpp
cd koi-fpp
Then define some temporary enivronment variables (assuming you're calling this from inside this repository):
export KOI_FPPDIR="$PWD/example_data"
export JROWE_DIR="$PWD/example_data/photometry"
Then, set up the python environment using the environment.yml
file in the top
level of this repository, as follows. [If you do not have conda
available, install miniconda first.]
conda env create -f environment.yml
source activate koifpp
This should install all the required packages. Now from within this environment you can run the following:
koifpp-config K07016.01
This will set up the vespa
and isochrones
config files in a
K07016.01
directory under KOI_FPPDIR
(if you haven't yet used
isochrones
, then be prepared for a few minutes' worth of stellar
model downloads). It will also do the
trapezoid shape fitting to the photometry. Take a look at the
fpp.ini
and star.ini
files to see what the inputs look like. You
can then run the calculation as follows:
cd $KOI_FPPDIR
calcfpp K07016.01
Note that the stellar parameter inference (and thus the FPP
calculation) will be much more reliable if you have
multinest
/pymultinest
installed. The calculations will run just
using the default emcee
sampler, but I stronly recommend using
multinest
becaues of the inherently multimodal nature of the
problem. Follow these
instructions
to install.
In order to get the data necessary for all the KOI FPP calculations beyond this single example, you will need the following:
- TRILEGAL starfield simulations. Define a
KOI_FPPDIR
environment variable to be somewhere sensible to you, and unpack thisstarfield
directory within that. - Kepler photometry. This is in two separate tarballs (Zenodo max file size is 2Gb), so unpack them both and combine their contents (all the koi*.n sub-directories) into a single directory. Define a
JROWE_DIR
environment variable referring to this location.
Then you can run the koifpp-config
and calcfpp
commands for your favorite KOI(s).
The data
directory contains the following files:
fpp_all.txt
: concatenation of all theresults.txt
files from all the successfulvespa
calculations. [TDM note: created bysummarize_fpp.py
script in/tigress/tmorton/kepler
]fpp_err.txt
: concatenation of all the exceptions raised by all the failedvespa
calculations. [TDM note: created bysummarize_fpp.py
script]ttvdata.txt
: table of whether TTV information was used to create the folded Kepler photometry used for the trapezoid fits. [TDM note: created bycompile_ttv.py
]starprops_all.txt
: summarized information from all the single-starisochrones
fits to all the KOI stars. [TDM note: created bysummarize_starprops.py
after runningstarfit-summarize
on all KOIs]positional_probability.csv
: table of positional probability data from Steve Bryson. This should correspond to the "positional probability" table at the NASA Exoplanet Archive.
Running the make_finale_fpptable.py
script uses the data from these files
as well as the DR24 table to produce the fpp_final_table.csv
file in the top
level of this repository.