The Channel Map Modelling Code
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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
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
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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