Metadata-Version: 1.1
Name: pyleoclim
Version: 0.4.6
Summary: A Python package for paleoclimate data analysis
Home-page: https://github.com/LinkedEarth/Pyleoclim_util/pyleoclim
Author: Deborah Khider
Author-email: dkhider@gmail.com
License: GNU Public
Download-URL: https://github.com/LinkedEarth/Pyleoclim_util/tarball/0.4.6
Description: .. raw:: html
        
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        |PyPI| |PyPI| |license| |DOI|
        
        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: 0.4.6
        
        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 package 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 - standardization -
        plotting maps, timeseries, and basic age model information - paleo-aware
        correlation analysis (isopersistent, isospectral and classical t-test) -
        weighted wavelet Z transform (WWZ) - age modelling through Bchron
        
        **Future capabilities**: - paleo-aware singular spectrum analysis (AR(1)
        null eigenvalue identification, missing data) - spectral analysis
        (Multi-Taper Method, Lomb-Scargle) - cross-wavelet analysis - index
        reconstruction - climate reconstruction - ensemble methods for most of
        the above
        
        If you have specific requests, please contact linkedearth@gmail.com
        
        Version Information
        -------------------
        
        | 0.4.6: Fix an issue when copying the .so files
        | 0.4.5: Update to setup.py to include proper .so file according to
          version
        | 0.4.4: New fix for .so issue
        | 0.4.3: New fix for .so issue
        | 0.4.2: Fix issue concerning download of .so files
        | 0.4.1: Fix issues with tarball
        | 0.4.0: New functionalities: map nearest records by archive type, plot
          ensemble time series, age modelling through Bchron
        | 0.3.1: New functionalities: segment a timeseries using a gap detection
          criteria, update to summary plot to perform spectral analysis
        | 0.3.0: Compatibility with LiPD 1.3 and Spectral module added
        | 0.2.5: Fix error on loading (Looking for Spectral Module)
        | 0.2.4: Fix load error from init
        | 0.2.3: Freeze LiPD version to 1.2 to avoid conflicts with 1.3
        | 0.2.2: Change progressbar to tqdm and add standardization function
        | 0.2.1: Update package requirements
        | 0.2.0: Restructure the package so that the main functions can be
          called without the use of a LiPD files and associated timeseries
          objects.
        | 0.1.4: Rename function using camel case and consistency with LiPD
          utilities version 0.1.8.5
        | 0.1.3: Compatible with LiPD utilities version 0.1.8.5.
        | Function openLiPD() renamed openLiPDs()
        | 0.1.2: Compatible with LiPD utilities version 0.1.8.3. Uses basemap
          instead of cartopy
        | 0.1.1: Freezes the package prior to version 0.1.8.2 of LiPD utilities
        | 0.1.0: First release
        
         Installation 
        --------------
        
        Python v3.4+ is required. Tested with Python v3.5
        
        Will not run on a Windows system
        
        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
           `here <http://linkedearth.github.io/Pyleoclim_util/>`__.
        
        Requirements
        ------------
        
        -  LiPD 0.2.5+
        -  pandas v0.22+
        -  numpy v1.14+
        -  matplotlib v2.0+
        -  Basemap v1.0.7+
        -  scipy v0.19.0+
        -  statsmodel v0.8.0+
        -  seaborn 0.7.0+
        -  scikit-learn 0.17.1+
        -  tqdm 4.14.0+
        -  pathos 0.2.0+
        -  tqdm 4.14+
        -  rpy2 2.8.4+
        
        The installer will automatically check for the needed updates
        
        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 linkedearth@gmail.com
        
         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.
        
        .. |PyPI| image:: https://img.shields.io/pypi/v/pyleoclim.svg
           :target: 
        .. |PyPI| image:: https://img.shields.io/badge/python-3.5-yellow.svg
           :target: 
        .. |license| image:: https://img.shields.io/github/license/linkedearth/Pyleoclim_util.svg
           :target: 
        .. |DOI| image:: https://zenodo.org/badge/59611213.svg
           :target: https://zenodo.org/badge/latestdoi/59611213
        
Keywords: Paleoclimate, Data Analysis
Platform: UNKNOWN
