discminer 0.2.46

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 docs.
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• Model channel maps from molecular line emission of discs by fitting intensity and rotation velocity
• Study 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
• Analyse the disc dynamical structure by modelling Keplerian motion + pressure support + self-gravity at once
• Identify velocity and intensity substructures; study their coherence and degree of localisation
• Non-axisymmetric models are possible; all attributes can be described as a function of $R,\phi,z$ disc coords

Mining tools

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

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 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 velocity into its three-dimensional components.
• Reveal large-scale signatures and quantify their pitch angle, width, extent, and coherence degree.

pick

• Identify small-scale velocity and intensity perturbations, and estimate their localisation degree.

plottools

• Customise intensity channels and residual maps, and highlight coherent and localised perturbations.
• Use sky or disc projections interchangeably for easier visualisation of features.
• Easily overlay the disc geometry (orientation and vertical structure) on any observable product.
• Overlay 1D profiles or 2D maps from external data to e.g. highlight the presence of dust substructures.

Installation

pip install discminer

To upgrade the code,

pip install -U discminer

Optional dependencies

• termtables
• termplotlib
• FilFinder
• schwimmbad
• ipython

How to use

The package documentation is still under construction, but you can find practical examples demonstrating the main functionality of the code in the ./template folder of this repository.

To run the examples on your local machine you can 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}
}