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-1.0.15.tar.gz (25.9 kB view details)

Uploaded Source

Built Distribution

smurfs-1.0.15-py3-none-any.whl (29.9 kB view details)

Uploaded Python 3

File details

Details for the file smurfs-1.0.15.tar.gz.

File metadata

  • Download URL: smurfs-1.0.15.tar.gz
  • Upload date:
  • Size: 25.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/44.0.0 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.7.3

File hashes

Hashes for smurfs-1.0.15.tar.gz
Algorithm Hash digest
SHA256 6486a6dd2c090548b81296d47e6c643591090bad7743c031aa854d69f9dee613
MD5 0d86705eac88a1931cd887dd81101fca
BLAKE2b-256 bdd3356f1aed24f2c392f4d9d10008e67ea4dfd391146050a39c9a6e00e162b4

See more details on using hashes here.

File details

Details for the file smurfs-1.0.15-py3-none-any.whl.

File metadata

  • Download URL: smurfs-1.0.15-py3-none-any.whl
  • Upload date:
  • Size: 29.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/44.0.0 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.7.3

File hashes

Hashes for smurfs-1.0.15-py3-none-any.whl
Algorithm Hash digest
SHA256 adbadf862b454fd82ca7d266a2bebb4bac1a3f3df4244dce07ff55ce1aba9573
MD5 0e5b5e7c4c5486a820d2a8dedcc7fb64
BLAKE2b-256 8323fd4cb3ead2a9868b3b7799dd0180abbc432d49ffe6a9004a5d161b245b70

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