Metadata-Version: 1.2
Name: pdrtpy
Version: 2.0b3
Summary: PhotoDissociation Region Toolbox (PDRT), astrophysics analysis tools
Home-page: https://dustem.astro.umd.edu
Author: Marc W. Pound
Author-email: mpound@umd.edu
License: GPLv3
Project-URL: Documentation, https://pdrtpy.readthedocs.io
Project-URL: Source Code, https://github.com/mpound/pdrtpy
Description: pdrtpy, a toolbox for analyzing photodissociation regions
        #########################################################
        
        
        PhotoDissociation Region Toolbox Python
        ***************************************
        
        *Reliable astrophysics at everyday low, low prices!* |reg| 
        
        ``pdrtpy`` is the new and improved version of the classic `PhotoDissociation Region Toolbox <http://dustem.astro.umd.edu/pdrt>`_, rewritten in Python with new capabilities and giving more flexibility to end users. 
        
        The new PDR Toolbox will cover many more spectral lines and metallicities
        and allows map-based analysis so users can quickly compute spatial images
        of density and radiation field from map data.  We provide example Jupyter
        notebooks for data analysis.  It also can support other PDR model codes
        enabling comparison of derived properties between codes.
        
        The underlying model code has improved physics and chemistry. Critical updates include those discussed in 
        `Neufeld & Wolfire 2016 <https://ui.adsabs.harvard.edu/abs/2016ApJ...826..183N/abstract>`_, plus photo rates from 
        `Heays et al. 2017 <https://ui.adsabs.harvard.edu/abs/2017A%26A...602A.105H/abstract>`_, oxygen chemistry rates from 
        `Kovalenko et al. 2018 <https://ui.adsabs.harvard.edu/abs/2018ApJ...856..100K/abstract>`_ and 
        `Tran et al. 2018 <https://ui.adsabs.harvard.edu/abs/2018ApJ...854...25T/abstract>`_, 
        and carbon chemistry rates from 
        `Dagdigian 2019 <https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.3427D/abstract>`_. We have also implemented new collisional
        excitation rates for [O I] from
        `Lique et al. 2018 <https://ui.adsabs.harvard.edu/abs/2018MNRAS.474.2313L/abstract>`_ (and Lique private
        communication) and have included |13C| chemistry along with the
        emitted line intensities for  |13CII| and |13CO|
        
        
        Getting Started
        ===============
        
        Installation
        ------------
        
        ``pdrtpy`` can be installed with 
        
        .. code-block:: sh
        
           pip install pdrtpy
        
        or 
        
        .. code-block:: sh
        
           git clone https://github.com/mpound/pdrtpy
           sudo apt-get install python3-venv
           python -m venv venv
           source venv/bin/activate
           pip install -r requirements.txt
        
        Requirements
        ------------
        Python 3 and recent versions of  astropy, numpy, scipy, matplotlib. And jupyter if you want to run the example notebooks.
        
        What is a PDR? 
        ==============
        Photodissociation regions (PDRs) include all of the neutral gas in the
        ISM where far-ultraviolet (FUV) photons dominate the chemistry and/or
        heating.  In regions of massive star formation, PDRS are created at
        the boundaries between the HII regions and neutral molecular cloud,
        as photons with energies 6 eV < E < 13.6 eV 
        photodissociate molecules and photoionize other elements.  The gas is
        heated from photo-electrons and cools mostly through far-infrared fine
        structure lines like [O I] and  [C II].
        
        For a full review of PDR physics and chemistry, see `Hollenbach & Tielens 1997 <https://ui.adsabs.harvard.edu/abs/1997ARA&A..35..179H>`_.
        
        .. |reg|    unicode:: U+000AE .. REGISTERED SIGN
        .. |13C|    replace:: :sup:`13`\ C
        .. |13CO|   replace:: :sup:`13`\ CO
        .. |13CII|  replace:: [\ :sup:`13`\ C II]
        
Keywords: PDR photodissociation
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.6
