Metadata-Version: 1.1
Name: ILAMB
Version: 2.1
Summary: The International Land Model Benchmarking Package
Home-page: https://bitbucket.org/ncollier/ilamb
Author: Nathan Collier
Author-email: nathaniel.collier@gmail.com
License: UNKNOWN
Description: The ILAMB Benchmarking System
        =============================
        
        The International Land Model Benchmarking (ILAMB) project is a
        model-data intercomparison and integration project designed to improve
        the performance of land models and, in parallel, improve the design of
        new measurement campaigns to reduce uncertainties associated with key
        land surface processes. Building upon past model evaluation studies,
        the goals of ILAMB are to:
        
        * develop internationally accepted benchmarks for land model
          performance, promote the use of these benchmarks by the
          international community for model intercomparison,
        * strengthen linkages between experimental, remote sensing, and
          climate modeling communities in the design of new model tests and
          new measurement programs, and
        * support the design and development of a new, open source,
          benchmarking software system for use by the international community.
        
        It is the last of these goals to which this repository is
        concerned. We have developed a python-based generic benchmarking
        system, initially focused on assessing land model performance.
        
        ILAMB 2.1 Release
        -----------------
        
        We are pleased to announce version 2.1 of the ILAMB python package,
        with the following new features:
        
        * Revamped treatment of relationships. Relationship plots now also
          include a difference plot of the distributions as well as a
          representation of the mean relationship function. We have moved the
          relationships to their own tab in the dataset HTML pages and given
          them their own scores. The first is based on the Hellinger distance,
          which quantifies the difference between the model and data
          distributions. The second is a RMSE score used to quantify the
          similarity of the model and observation mean relationship
          curves. This revamp also removed unneeded recomputation, speeding up
          the entire ILAMB run by 25%.
        * Logfiles are now generated when ILAMB is run. They contain more
          information about the python packages used, the amount of time spent
          on each process, and more debugging information when errors are
          encountered. Look for files with the ``.log`` suffix in the
          ``_build`` directory after ILAMB is run.
        * We have removed ``demo/driver.py`` and added an executable version
          ``ilamb-run``. When you install the ILAMB package, this new script
          will be added to your ``bin`` directory. This allows you to run the
          ILAMB package anywhere without needing to copy the driver. Thanks to
          Mark Piper for this contribution.
        * We have added an option to the ``ilamb-run`` script which allows
          users to shift the time representation in the model results. This is
          helpful during model development to compare model results to the
          ILAMB suite without needing to fully spin up the model. The option
          syntax is ``--model_year y0 yf`` which will make the year ``y0`` in
          the models equal to ``yf``, shifting all times by ``yf-y0`` years.
        * The ``ILAMB.Variable`` object now has support for layered data,
          including a new member function ``integrateInDepth``.
        * Improved calendar conversion capability, enabling the use of models
          with calendars other than ``noleap``.
        * All plots now color land areas in a light grey, and oceans with a
          darker grey. Plots over the globe will be in the Robinson projection
          for both globally gridded data as well as sites. Regional plots now
          mask out areas not in the region and will be in the cylindrical
          projection.
        * ILAMB is now listed in the `Python Package Index
          <https://pypi.python.org/pypi>`_ and can now be installed using
          ``pip``. The installation tutorial has been rewritten to reflect
          this change as well as adapted based on user feedback to be more
          helpful.
        * Numerous bugfixes, many cosmetic, but a few substantive fixes include:
          
          * Moved to using the ``with`` statement for handling the opening of
            files. This ensures that files always close, even when errors are
            thrown.
          * Fixed a bug which caused intermittent inconsistencies when running
            in parallel. This would cause the scores for some models/variables
            to appear as Nans, despite the fact that the analysis was run.
          * Fixed a bug relating to the computation of RMSE scores. Scores
            were too low relative to ILAMB v1 because the wrong normalizer was
            being used. Thanks to Alberto Martinez-de la Torre for this patch.
          * Fixed code which triggers depracation warnings from numpy and
            matplotlib.
          
        
          
        Useful Information
        ------------------
        
        * `Documentation
          <http://climate.ornl.gov/~ncf/ILAMB/docs/index.html>`_ of the public
          API is included in the repository, but also hosted if you follow the
          link.
        * `Sample output
          <http://www.climatemodeling.org/~nate/ILAMB/index.html>`_ gives you
          an idea of the scope and magnitude of the package capabilities.
        * You may cite the software package by using the following reference (DOI:10.18139/ILAMB.v002.00/1251621).
        
        Funding
        -------
        
        This research was performed for the Biogeochemistry--Climate Feedbacks
        Scientific Focus Area, which is sponsored by the Regional and Global
        Climate Modeling (RGCM) Program in the Climate and Environmental
        Sciences Division (CESD) of the Biological and Environmental Research
        (BER) Program in the U.S. Department of Energy Office of Science.
        
Keywords: benchmarking,earth system modeling,climate modeling,model intercomparison
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
