SMURFS provides automatic extraction of frequencies from timeseries. It provides various interfaces, from a standalone command line tool, to jupyter and python integrations and computes possible frequency combinations, directly downloads and reduces (if necessary) data of TESS/Kepler/K2 observations and much much more.Smart UseR Frequency analySer
To install smurfs, you need python > 3.5, pip as well as cmake. If you don't have these, install them through the packet manager of your choice (f.e. brew(Mac) or apt (Debian)). For pip check here.
First off, create a virtual environment
cd /Path/
python3 -m venv venv/
source venv/bin/activate
Install smurfs through pip
pip install smurfs
Using SMURFS as a standalone command line tool is very simple. Simply call smurfs with a target, signal to noise
ratio cutoff and the window size. The target can be either:
As an example, we can take a look at the star Gamma Doradus:
smurfs "Gamma Doradus" 4 2
SMURFS creates a result folder after running the code. In this case it has the following structure
- Gamma_Doradus
- data
- _combinations.csv
- _result.csv
- LC_residual.txt
- LC.txt
- PS_residual.txt
- PS.txt
- plots
- LC_residual.pdf
- LC.pdf
- PS_residual.pdf
- PS_result.pdf
- PS.pdf
The LC*.txt files contain the light curves, original and residual. The PS*.txt files contain the
original as well as the residual amplitude spectrum. _combinations.csv shows all combination frequencies for the
result and _result.csv gives the result for a given run.
If you use this software in your research, consider citing it using Zenodo.
If you use SMURFS to extract LC data from FFIs, you should also cite the awesome people of Eleanor.
Full documentation is available here
FAQs
Smart UseR Frequency analySer
We found that smurfs demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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