Installation

The package can be installed from a gitlab repository or if you want a stable version from pypi via pip. For details see https://gitlab.astro.rug.nl/prodimo/prodimopy.

There you find also the instructions on how to update the code. You will also find a binder link that allows you to try some features of the package without installing anything.

Usage

prodimopy was initially developed to read and analyze (plotting) the output of the ProDiMo code. But besides that it includes now also stand-alone tools such as the 0d/1D slab models. Furthermore it includes utilities for interfaces to other codes, or to manipulate Parameter files for ProDiMo.

One major concept of prodimopy is to separate the reading (such as model outputs) and the analysing of the data. For example there is one module that includes everything to read the data for a disk model from ProDiMo. Then there is another separate module that is used for plotting. This way a user can easily implement it’s on plotting routines or even use a completely different plotting package.

As we encourage the user to develop own plots (and maybe even contribute them to prodimopy), we highly recommend to not develop new reading routines for the data. The output structure of PRoDiMo models is rather complex and it can change, so it is easy to make mistakes. If the reading modules are missing something please let us know and do not develop your onw routines, but rather contact one of the developers

prodimopy can be used in different ways. The most common way is to use it in a python script or in a Jupyter notebook. But it also includes some command line utilities, that are installed automatically.

Jupyter notebook

You can find various examples for how to use prodimopy in a Jupyter notebooks here

Command-line utilities

prodimopy also installs a few command line utils which can be used without launching a python interpreter or writing any python code. The all include some help just type scriptname -h.

pplot

Produces plots for a single ProDiMo model. Useful to check the prodimopy installation or to take a quick look on a ProDiMo model. For details see Plotting routines for a single model.

pplot_models

Produces plots for a given set of ProDiMo models. Useful to quickly compare visually different ProDiMo models. For details see Plotting routines for a set of models.

pcompare

Compares the results of two ProDiMo models. For details see Compare two models.

pparam

Simple script to manipulate the Parameter.in file from the command line. Just call pparam` from the command line and check the help.

pcpforrestart

Script to duplicate an existing model and prepare it for restart. This is useful for cases where one wants to rerun a model with restart but change some parameters. It only copies the required files (i.e. no output files) of an existing model to a new directory (i.e. the new model). For more details just type pcpforrestart -h in the command line.

prunprodimo

Convenience script to run prodimo from the command line. It is a wrapper around the prodimo command that automatically writes the log output to prodimo.log and allows for setting the number of threads for the prodimo run. This is still experimental and further functionality might be added in the future. For more details just type prunprodimo -h in the command line.

pgrid

Command line script to generate, run and check simple ProDiMo grids. For further details also see Creating model grids.

Plot style

The plotting routines of prodimopy use matplotlib in the background. That means all matplotlib features are also available in prodimopy.

To define the style of the plots the matplotlib style sheets can be used (see the matplotlib customization guide). prodimopy includes a default matplotlib style sheet the can be used by calling the function prodimopy.plot.load_style() (or with prodimopy.utils.load_mplstyle()).

In case you want to adapt it, the mplstyle file is located in the prodimopy package and can download it here: prodimopy.mplstyle. Place it in your matplotlib style directory, and give it a different name (i.e. myprodimopy.mplstyle). However, although we are trying very hard, it can be that some colours or styles are hardcoded in the plotting routines. If you find such a case, please let us know.

Citation

We hope to have a proper ascl and ADS entry soon.

In case you use the slab model part please make sure to also cite Arabhavi+ (2024)

@ARTICLE{2024Sci...384.1086A,
    author = {{Arabhavi}, A.~M. and {Kamp}, I. and {Henning}, Th. and {van Dishoeck}, E.~F. and {Christiaens}, V. and {Gasman}, D. and {Perrin}, A. and {G{\"u}del}, M. and {Tabone}, B. and {Kanwar}, J. and {Waters}, L.~B.~F.~M. and {Pascucci}, I. and {Samland}, M. and {Perotti}, G. and {Bettoni}, G. and {Grant}, S.~L. and {Lagage}, P.~O. and {Ray}, T.~P. and {Vandenbussche}, B. and {Absil}, O. and {Argyriou}, I. and {Barrado}, D. and {Boccaletti}, A. and {Bouwman}, J. and {Caratti o Garatti}, A. and {Glauser}, A.~M. and {Lahuis}, F. and {Mueller}, M. and {Olofsson}, G. and {Pantin}, E. and {Scheithauer}, S. and {Morales-Calder{\'o}n}, M. and {Franceschi}, R. and {Jang}, H. and {Pawellek}, N. and {Rodgers-Lee}, D. and {Schreiber}, J. and {Schwarz}, K. and {Temmink}, M. and {Vlasblom}, M. and {Wright}, G. and {Colina}, L. and {{\"O}stlin}, G.},
    title = "{Abundant hydrocarbons in the disk around a very-low-mass star}",
    journal = {Science},
    keywords = {Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Solar and Stellar Astrophysics},
    year = 2024,
    month = jun,
    volume = {384},
    number = {6700},
    pages = {1086-1090},
    doi = {10.1126/science.adi8147},
    archivePrefix = {arXiv},
    eprint = {2406.14293},
    primaryClass = {astro-ph.EP},
    adsurl = {https://ui.adsabs.harvard.edu/abs/2024Sci...384.1086A},
    adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}