pyleoclim 0.1.1

A Python package for paleoclimate data analysis

|PyPI| |PyPI| |PyPI| |license|

Pyleoclim
=========

**Python Package for the Analysis of Paleoclimate Data**

**Table of contents**

- `What is it? <#what>`__
- `Installation <#install>`__
- `Version Information <#version>`__
- `Quickstart Guide <#quickstart>`__
- `Requirements <#req>`__
- `Further information <#further_info>`__
- `Contact <#contact>`__
- `License <#license>`__
- `Disclaimer <#disclaimer>`__

Current Version: 0.1.1

What is it?
-----------

Pyleoclim is a Python package primarily geared towards the analysis and
visualization of paleoclimate data. Such data often come in the form of
timeseries with missing values and age uncertainties, and the package
includes several-low level methods to deal with these issues, as well as
high-level methods that re-use those to perform scientific workflows.

The packages assumes that data are stored in the Linked Paleo Data
(`LiPD <http://www.clim-past.net/12/1093/2016/>`__) format and makes
extensive use of the `LiPD
utilities <http://nickmckay.github.io/LiPD-utilities/>`__. The package
is aware of age ensembles stored via LiPD and uses them for
time-uncertain analyses very much like
`GeoChronR <http://nickmckay.github.io/GeoChronR/>`__.

**Current capabilities**: - binning - interpolation - plotting maps,
timeseries, and basic age model information - paleo-aware correlation
analysis (isopersistent, isospectral and classical t-test)

**Future capabilities**: - spectral analysis (Multi-Taper Method,
Lomb-Scargle) - weighted wavelet Z transform (WWZ) - cross-wavelet
analysis - index reconstruction - climate reconstruction - ensemble
methods for all of the above

If you have specific requests, please contact [e-mail]

Version Information
-------------------

0.1.1: Freezes the package before to version 0.1.8.2 of LiPD utilities
0.1.0: First release

Installation
--------------

Python v3.5+ is required.

Pyleoclim is published through PyPi and easily installed via ``pip``

::

pip install pyleoclim

Quickstart guide
------------------

1. Open your command line application (Terminal or Command Prompt).

2. Install with command: ``pip install pyleoclim``

3. Wait for installation to complete, then:

3a. Import the package into your favorite Python environment (we
recommend the use of Spyder, which comes standard with the Anaconda
package)

3b. Use Jupyter Notebook to go through the tutorial contained in the
``PyleoclimQuickstart.ipynb`` Notebook, which can be downloaded
`here <https://github.com/LinkedEarth/Pyleoclim_util/tree/master/Example>`__.

4. Help with functionalities can be found in the Documentation folder on
our `GitHub
repository <https://github.com/LinkedEarth/Pyleoclim_util>`__ and on
Pypi.

Requirements
------------

- LiPD v0.1.8.2
- pandas v0.19+
- numpy v1.12+
- matplotlib v2.0+
- Cartopy v0.13+

The installer will automatically check for the needed updates
***except*** for Cartopy.

Cartopy doesn't install properly through pip. Use Conda. See the
instructions on the developer website.

Further information
-------------------

GitHub: https://github.com/LinkedEarth/Pyleoclim\_util

LinkedEarth: http://linked.earth

Python and Anaconda: http://conda.pydata.org/docs/test-drive.html

Jupyter Notebook: http://jupyter.org

Contact
---------

Please report issues to [e-mail]

License
---------

The project is licensed under the GNU Public License. Please refer to
the file call license.

Disclaimer
------------

This material is based upon work supported by the National Science
Foundation under Grant Number ICER-1541029. Any opinions, findings, and
conclusions or recommendations expressed in this material are those of
the investigators and do not necessarily reflect the views of the
National Science Foundation.

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