Metadata-Version: 2.1
Name: xarrayutils
Version: 0.1.4
Summary: A collection of various tools for data analysis built on top of xarray and xgcm
Home-page: https://github.com/jbusecke/xarrayutils
Author: xarrayutils Developers
Author-email: julius@ldeo.columbia.edu
License: MIT
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: xarray (>=0.14.1)
Requires-Dist: dask
Requires-Dist: numpy
Provides-Extra: complete
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Requires-Dist: dask ; extra == 'complete'
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Requires-Dist: numpy ; extra == 'dev'
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# A collection of various tools for data analysis built on top of xarray and xgcm

This package contains a variety of utility functions I have used in the past few years for data analysis.

Please be aware that I am currently refactoring a lot of the code, which might cause breaking changes.

Hopefully soon it will be better tested and documented.

## Installation

To install from source use pip:

`pip install git+https://github.com/jbusecke/xarrayutils.git`

> Make sure to install these packages to your environment `conda install astropy gsw cartopy`

> In order to use dask > 2.0 you need the newest upstream xarray version. For xarray <= 0.14.1, please downgrade to dask < 2.0


## Contents (not complete yet)

### Converting between vertical coordinate systems

`xarrayutils.vertical_coordinates` provides several tool to move between various vertical ocean grids, e.g. z, density, sigma or hybrid coordinates. See [this notebook](https://github.com/jbusecke/xarrayutils/blob/master/doc/vertical_coords.ipynb) for an early example.

### Plotting utilities
`xarrayutils.plotting` provides several small utility functions to make common tasks I find in my workflow in matplotlib easier. [Examples](doc/plotting.ipynb)

### Utilities for large scale climate data analysis
`xarrayutils.utils` provides some helpful tools to simplify common tasks in climate data
analysis workflows. [This notebook](doc/utils.ipynb), provides some examples on how to
use linear regression, work with multi-member data and seperate mixed layer values.


