TurbuStat

NOTE - this package is still under development. API may change!

See the documentation at http://turbustat.readthedocs.org/

Statistics of Turbulence

This package is aimed at facilitating comparisons between spectral line data cubes. Included in this package are several techniques described in the literature which aim to describe some property of a data cube (or its moments/integrated intensity). We extend these techniques to be used as comparisons.

Distance Metrics

Ideally, we require a distance metric to satisfy several properties. A full description is shown in Yeremi et al. (2014). The key properties are:

• cubes with similar physics should have a small distance
• unaffected by coordinate shifts
• sensitive to differences in physical scale
• independent of noise levels in the data

Not all of the metrics satisfy the idealized properties. A full description of all statistics in this package will be shown in Koch et al. (submitted). The paper results can be reproduced using the scripts in AstroStat_Results.

Installing

Currently, the only way install TurbuStat is to clone the repository and run

python setup.py install

Due to conflicts with the dependencies, TurbuStat will NOT automatically install all dependencies (only numpy and astropy). To check if your version of python has all the dependencies installed, run:

python setup.py check_deps

Package Dependencies

Requires:

• astropy>=1.0
• numpy>=1.7
• matplotlib>=1.2
• scipy>=0.12
• sklearn>=0.13.0
• pandas>=0.13
• statsmodels>=0.4.0

Recommended:

• spectral-cube - Efficient handling of PPV cubes. Required for calculating moment arrays in turbustat.data_reduction.Mask_and_Moments
• astrodendro-development - Required for calculating dendrograms in turbustat.statistics.dendrograms

Optional:

• signal-id - Noise estimation in PPV cubes.
• radio_beam - A class for handling radio beams and useful utilities. Used for noise estimation in signal-id

Credits

This package was developed by:

• Eric Koch
• Caleb Ward
• Erik Rosolowsky
• Jason Loeppky

If you make use of this package in a publication, please cite our accompanying paper:

   @ARTICLE{Koch2016,
    author = {{Koch}, Eric~W. and {Ward}, Caleb~G. and {Offner}, Stella and {Loeppky}, Jason~L. and {Rosolowsky}, Erik~W.},
    title = {Tools for Critically Evaluating Simulations of Star Formation},
    journal = {MNRAS},
    year = {submitted}
    }