Metadata-Version: 2.1
Name: velociraptor
Version: 0.13.2
Summary: Velociraptor catalogue reading routines.
Home-page: https://github.com/swiftsim/velociraptor-python
Author: Josh Borrow
Author-email: joshua.borrow@durham.ac.uk
License: UNKNOWN
Description: Velociraptor Python Library
        ===========================
        
        [![Documentation Status](https://readthedocs.org/projects/velociraptor-python/badge/?version=latest)](https://velociraptor-python.readthedocs.io/en/latest/?badge=latest)
        
        [Velociraptor](http://github.com/pelahi/velociraptor-stf) catalogues provide
        a signifciant amount of information, but applying units to it can be painful.
        Here, the `unyt` python library is used to automatically apply units to
        velociraptor data and perform generic halo-catalogue reduction. This library
        is primarily intended to be used on [SWIFT](http://swiftsim.com) data that
        has been post-processed with velociraptor, but can be used for any
        velociraptor catalogue.
        
        The internals of this library are based heavily on the internals of the
        [`swiftsimio`](http://github.com/swiftsim/swiftsimio) library, and essentially
        allow the velociraptor catalogue to be accessed in a lazy, object-oriented
        way. This enables users to be able to reduce data quickly and in a
        computationally efficient manner, without having to resort to using the
        `h5py` library to manually load data (and hence manually apply units)!
        
        Requirements
        ------------
        
        The velociraptor library requires:
        
        + `unyt` and its dependencies
        + `h5py` and its dependencies
        + `python3.6` or above
        
        Note that for development, we suggest that you have `pytest` and `black`
        installed. To create the plots in the example directory, you will need
        the plotting framework `matplotlib`.
        
        Installation
        ------------
        
        You can install this library from PyPI using:
        ```
        pip3 install velociraptor
        ```
        
        Documentation
        -------------
        
        Full documentation is available on [ReadTheDocs](https://velociraptor-python.readthedocs.io/).
        
        Why a custom library?
        ---------------------
        
        This custom library, instead of something like `pandas`, allows us to
        only load in the data that we require, and provide significant
        context-dependent features that would not be available for something
        generic. One example of this is the automatic labelling of properties,
        as shown in the below example.
        
        ```python
        from velociraptor import load
        from velociraptor.tools import get_full_label
        
        catalogue = load("/path/to/catalogue.properties")
        
        stellar_masses = catalogue.apertures.mass_star_30_kpc
        stellar_masses.convert_to_units("msun")
        
        print(get_full_label(stellar_masses))
        ```
        This outputs "Stellar Mass $M_*$ (30 kpc) $\left[M_\odot\right]$", which is
        easy to add as, for example, a label on a plot.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
