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discminer

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

  • 0.2.46
  • Source
  • PyPI
  • Socket score

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The Channel Map Modelling Code

License Pull request? andizq Code style: black
Welcome to the discminer repository! Looking for quick examples and tutorials? Check out the docs.
Report a Bug · Request a Feature · Ask a Question
  • 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

Discminer workflow and capabilities

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

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}
}

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