discminer 0.4.9

Python package for parametric modelling of intensity channel maps from gas discs

The Channel Map Modelling Code

Welcome to the discminer repository! Looking for quick examples and tutorials? Check out the example/ folder.
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• Model channel maps from molecular line emission of discs by fitting intensity and rotation velocity
• Analyse the disc's dynamics by modelling Keplerian motion, and optionally pressure support + self-gravity
• Investigate the disc vertical structure by modelling front and back side emission surfaces
• Compute moment maps that accurately capture complex line profile morphologies
• Extract rotation curves, radial and meridional velocities, intensity, and line width profiles
• Identify velocity and intensity substructures, and examine their coherence and degree of localisation
• Support non-axisymmetric models; all attributes can be described in three-dimensional coordinates

Mining tools

Discminer offers a wide range of analysis and visualisation tools to fully explore the physical and dynamical structure of discs.

cube

• Compute moment maps that accurately capture complex line profile morphologies.
• Output moment maps include peak intensity, line width, line slope, and centroid velocity.
• Easily clip, downsample, and convert data to brightness temperature units.
• Quickly visualise model versus data channels and interactively extract spectra.

rail

• Extract azimuthal and radial profiles of intensity, line width, and velocity from moment maps.
• Compute rotation curves and decompose disc velocities into their three-dimensional components.
• Identify large-scale structures and quantify their pitch angle, width, extent, and degree of coherence.

pick

• Identify small-scale perturbations and estimate their degree of localisation.

plottools

• Customise intensity channels, moments, and residual maps.
• Use sky or disc projections interchangeably for improved visualisation of features.
• Easily overlay disc geometry (considering orientation and vertical structure) onto any observable product.
• Load in 1D profiles or 2D maps from external data e.g. to highlight the presence of dust substructures.

Installation

pip install discminer

To upgrade the code,

pip install -U discminer

Optional dependencies

• termplotlib
• FilFinder
• bettermoments
• schwimmbad
• ipython

How to use

You can find practical examples demonstrating the main functionality of the code in the ./example folder of this repository.

To run the examples on your local machine, clone this repository and follow the instructions provided in the README file,

git clone https://github.com/andizq/discminer.git
cd discminer/template
less README.rst

Citation

If you find discminer useful for your research please cite the work of Izquierdo et al. 2021,

@ARTICLE{2021A&A...650A.179I,
       author = {{Izquierdo}, A.~F. and {Testi}, L. and {Facchini}, S. and {Rosotti}, G.~P. and {van Dishoeck}, E.~F.},
        title = "{The Disc Miner. I. A statistical framework to detect and quantify kinematical perturbations driven by young planets in discs}",
      journal = {\aap},
     keywords = {planet-disk interactions, planets and satellites: detection, protoplanetary disks, radiative transfer, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Solar and Stellar Astrophysics},
         year = 2021,
        month = jun,
       volume = {650},
          eid = {A179},
        pages = {A179},
          doi = {10.1051/0004-6361/202140779},
archivePrefix = {arXiv},
       eprint = {2104.09596},
 primaryClass = {astro-ph.EP},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2021A&A...650A.179I},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}