Metadata-Version: 2.1
Name: xyzpy
Version: 0.2.4
Summary: Easily generate large parameter space data
Home-page: http://xyzpy.readthedocs.io
Author: Johnnie Gray
Author-email: john.gray.14@ucl.ac.uk
License: MIT
Description: .. image:: https://travis-ci.org/jcmgray/xyzpy.svg?branch=master
          :target: https://travis-ci.org/jcmgray/xyzpy
        .. image:: https://codecov.io/gh/jcmgray/xyzpy/branch/master/graph/badge.svg
          :target: https://codecov.io/gh/jcmgray/xyzpy
        .. image:: https://img.shields.io/lgtm/grade/python/g/jcmgray/xyzpy.svg
          :target: https://lgtm.com/projects/g/jcmgray/xyzpy/
          :alt: LGTM Grade
        .. image:: https://readthedocs.org/projects/xyzpy/badge/?version=latest
          :target: http://xyzpy.readthedocs.io/en/latest/?badge=latest
          :alt: Documentation Status
        
        ----------------------------------------------------------------------------------
        
        `xyzpy <https://github.com/jcmgray/xyzpy>`__ is python library for efficiently generating, manipulating and plotting data with a lot of dimensions, of the type that often occurs in numerical simulations. It stands wholly atop the labelled N-dimensional array library `xarray <http://xarray.pydata.org/en/stable/>`__. The project's documentation is hosted on `readthedocs <http://xyzpy.readthedocs.io/>`__.
        
        The aim is to take the pain and errors out of generating and exploring data with a high number of possible parameters. This means:
        
        - you don't have to write super nested for loops
        - you don't have to remember which arrays/dimensions belong to which variables/parameters
        - you don't have to parallelize over or distribute runs yourself
        - you don't have to worry about loading, saving and merging disjoint data
        - you don't need to guess when a set of runs is going to finish
        
        As well as the ability to automatically parallelize over runs, ``xyzpy`` provides the ``Crop`` object that allows runs and results to be written to disk, these can then be run by any process with access to the files - e.g. a batch system - or just serve as a convenient persistent progress mechanism.
        
        In terms of post-processing, as well as all the power of `xarray <http://xarray.pydata.org/en/stable/>`__, ``xyzpy`` adds uneven step differentiation and error propagation, filtering and interpolation - along any axis just specified by name.
        
        The aim of the plotting functionality is to keep the same interface between interactively plotting the data using `bokeh <https://bokeh.pydata.org/en/latest/>`__, and static, publication ready figures using `matplotlib <https://matplotlib.org/>`__, whilst being able to see the dependence on up to 4 dimensions at once.
        
        .. image:: docs/ex_simple.png
        
        Please see the `docs <http://xyzpy.readthedocs.io/>`__ for more information.
        
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Requires-Python: >=3.5
Provides-Extra: docs
Provides-Extra: tests
