Skip to main content

Smart UseR Frequency analySer, a fast and easy to use frequency analyser.

Project description

SMURFS

SMURFS Image

The SMURFS (SMart UseR Frequency analySer) provides automatic extraction of frequencies from a Timeseries data. It provides various interfaces, from a standalone command line tool, to jupyter and python integrations. It also automatically computes possible frequency combinations, directly downloads of TESS/Kepler/K2 data and more.

Getting started

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.

Installation

First off, create a virtual environment

cd /Path/
python3 -m venv venv/
source venv/bin/activate

Install smurfs through pip

pip install smurfs

Quickstart

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:

  • A path to a file, containing 2 columns with time and flux
  • Any name of a star, that is resolvable by Simbad and has been observed by the Kepler,K2 or TESS missions.

As an example, we can take a look at the star Gamma Doradus:

smurfs "Gamma Doradus" 4 2

Executing this command will make smurfs search for light curves of the star. It starts by using the lightkurve.search.search_lightcurvefile method, which queries MAST for processed light curves of the object. If this doesn't return any light curves, SMURFS will then check if the star has been observed by the TESS mission. It queries Simbad for the coordinates of the object and then checks if that point was observed by TESS. If so, we use TessCut and the Eleanor pipeline to extract the light curve.

In the case of Gamma Doradus, we have existing TESS SC light curves. Smurfs will give the following output: Gamma Doradus output

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.

Documentation

Full documenation is available here

Features

SMURFS provides various nice to have features, setting it apart from common frequency analysers. These include

  • Python only. No more Fortran, IDL or other more obfuscating languages
  • Fast runs due to the usage of optimized libraries, including numpy, scipy and astropy, dedicated to scientific work
  • Generates a full result set that can be used for further analysis, including spectra of the first and last frequency, spectrograms, machine readable results and so on.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

smurfs-1.0.9.tar.gz (25.4 kB view details)

Uploaded Source

Built Distribution

smurfs-1.0.9-py3-none-any.whl (29.3 kB view details)

Uploaded Python 3

File details

Details for the file smurfs-1.0.9.tar.gz.

File metadata

  • Download URL: smurfs-1.0.9.tar.gz
  • Upload date:
  • Size: 25.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.14.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.7.3

File hashes

Hashes for smurfs-1.0.9.tar.gz
Algorithm Hash digest
SHA256 fd409d85c9360283974fbeec7cf977421df57449aec89f87ba86d4cfe1ec5188
MD5 58b96746c40144eb2c990cd8ca794cde
BLAKE2b-256 a6f1856186e933747703866e5a98eee6ad65bfd0ef924ac02a289afe7702b5ee

See more details on using hashes here.

File details

Details for the file smurfs-1.0.9-py3-none-any.whl.

File metadata

  • Download URL: smurfs-1.0.9-py3-none-any.whl
  • Upload date:
  • Size: 29.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.14.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.7.3

File hashes

Hashes for smurfs-1.0.9-py3-none-any.whl
Algorithm Hash digest
SHA256 5cd5136d0a76961d3c7211424d351e44dc4f1ee565b32209d5e45c0542864f06
MD5 fa0f96a9ddd99ee9f08e5f7f69187192
BLAKE2b-256 c980e6e8a91e58a552f802d70c0b7b91ab0e9aa564fd37e4d01e8a81a406f2c7

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page