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        "author": "Marco M\u00fcllner",
        "author_email": "muellnermarco@gmail.com",
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            "License :: OSI Approved :: MIT License",
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            "Programming Language :: Python :: 3.7"
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        "description": "# SMURFS\n![SMURFS Image](https://i.imgur.com/wWe1q0y.png)\n\nThe **SMURFS** (**SM**art **U**se**R** **F**requency analy**S**er) provides automatic extraction of frequencies from\na Timeseries data. It provides various interfaces, from a standalone command line tool, to jupyter and python \nintegrations. It also automatically computes possible frequency combinations, directly downloads of TESS/Kepler/K2 \ndata and more. \n\n## Getting started\n\nTo install smurfs, you need python > 3.5, pip as well as cmake. If you don't have these, install them through the\npacket manager of your choice (f.e. _brew_(Mac) or _apt_ (Debian)). For pip check \n[here](https://pip.pypa.io/en/stable/installing/).\n\n## Installation\n\nFirst off, create a virtual environment\n\n```bash\ncd /Path/\npython3 -m venv venv/\nsource venv/bin/activate\n```\n\nInstall smurfs through pip\n\n```bash\npip install smurfs\n```\n\n## Quickstart\n\nUsing SMURFS as a standalone command line tool is very simple. Simply call ```smurfs``` with a **target**, signal to noise\nratio cutoff and the window size. The target can be either:\n\n- A path to a file, containing 2 columns with time and flux\n- Any name of a star, that is resolvable by Simbad and has been observed by the **Kepler**,**K2** or **TESS** missions.\n\nAs an example, we can take a look at the star Gamma Doradus:\n```\nsmurfs \"Gamma Doradus\" 4 2\n```\nExecuting this command will make smurfs search for light curves of the star. It starts by using the \n[lightkurve.search.search_lightcurvefile](https://docs.lightkurve.org/api/lightkurve.search.search_lightcurvefile.html#lightkurve.search.search_lightcurvefile)\nmethod, which queries MAST for processed light curves of the object. If this doesn't return any light curves, SMURFS \nwill then check if the star has been observed by the TESS mission. It queries Simbad for the coordinates of the object \nand then checks if that point was observed by TESS. If so, we use [TessCut](https://mast.stsci.edu/tesscut/) and \nthe [Eleanor](https://adina.feinste.in/eleanor/) pipeline to extract the light curve. \n\nIn the case of Gamma Doradus, we have existing TESS SC light curves. Smurfs will give the following output:\n![Gamma Doradus output](images/gamma_doradus_output.png)\n\nSMURFS creates a result folder after running the code. In this case it has the following structure\n```\n- Gamma_Doradus\n    - data\n        - _combinations.csv\n        - _result.csv\n        - LC_residual.txt\n        - LC.txt\n        - PS_residual.txt\n        - PS.txt         \n    - plots\n        - LC_residual.pdf\n        - LC.pdf\n        - PS_residual.pdf\n        - PS_result.pdf\n        - PS.pdf\n```\nThe ```LC*.txt``` files contain the light curves, original and residual. The ```PS*.txt``` files contain the \noriginal as well as the residual amplitude spectrum. ```_combinations.csv``` shows all combination frequencies for the \nresult and ```_result.csv``` gives the result for a given run.\n\n## Documentation\n\nFull documenation is available [here](https://smurfs.readthedocs.io/en/master/)\n\n## Features\n\nSMURFS provides various nice to have features, setting it apart\nfrom common frequency analysers. These include\n\n* Python only. No more Fortran, IDL or other more obfuscating languages \n* Fast runs due to the usage of optimized libraries, including numpy, scipy and astropy,\ndedicated to scientific work\n* Generates a full result set that can be used for further analysis, including \nspectra of the first and last frequency, spectrograms, machine readable results and so on.\n\n\n",
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