discminer

The Channel Map Modelling Code

Welcome to the discminer repository! Looking for quick examples and tutorials? Check out the example workflows.
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discminer is a Python package for fitting three-dimensional parametric models directly to molecular-line channel maps of protoplanetary discs, then using model–data residuals to reveal their kinematic and intensity substructure.

It enables you to:

Fit intensity and rotation velocity simultaneously across an entire channel-map cube or a selected subset of channels
Model Keplerian rotation, with optional pressure support and disc self-gravity
Reconstruct front- and back-side emitting surfaces and use flexible, non-axisymmetric prescriptions for model attributes
Fit complex line profiles to derive peak-intensity, centroid-velocity, line-width, and line-slope moment maps
Extract rotation curves and radial profiles of intensity, line width, and azimuthal, radial, and vertical velocity
Detect and quantify coherent, localised structures in intensity and velocity residuals

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 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.

pca

See the dedicated PCA workflow documentation.

Installation

pip install discminer

To upgrade the code,

pip install -U discminer

Optional dependencies

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/example/mwc480_12co
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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