Metadata-Version: 2.1
Name: metintos
Version: 0.2.2
Summary: Meteorological Interpolation Toolbox for Optimization and Simulation
Home-page: https://github.com/javiergarciaheras/mitos
Author: Daniel González Arribas
Author-email: dangonza@ing.uc3m.es
License: lgpl-3.0
Download-URL: https://github.com/javiergarciaheras/mitos/archive/v_01.tar.gz
Description: # METeorological INterpolation Toolbox for Optimization and Simulation (METINTOS)
        
        [![Build Status](https://travis-ci.org/javiergarciaheras/metintos.svg?branch=master)](https://travis-ci.org/javiergarciaheras/metintos)
        [![GitHub](https://img.shields.io/github/license/javiergarciaheras/metintos)]()
        [![GitHub release (latest by date)](https://img.shields.io/github/v/release/javiergarciaheras/metintos)]()
        [![Documentation Status](https://readthedocs.org/projects/metintos/badge/?version=latest)](https://metintos.readthedocs.io/en/latest/?badge=latest)
              
        ## What is METINTOS?
        
        METINTOS is a libray that interpolates meteorological variables in time.
        It is distributed under the GNU Lesser General Public License v3.0.
        
        **Citation info**: D. Daniel González-Arribas, J. García-Heras, M. Soler and E.A. Enderiz, METeorological Interpolation Toolbox for Optimization and Simulation (METINTOS) an open source meteorological variable interpolator.
        
        ## How to run the library
        
        1. Clone or download the repository.
        2. Install all the dependencies.
        
        
        ## How to use it
        
        1. From your meteorological files you have to create the dataset, you have to use xarray.open_mfdataset, you can obtain information in the xarray documentation ([xarray.open_mfdataset link](http://xarray.pydata.org/en/stable/generated/xarray.open_mfdataset.html)).
        
        
        ```python
        ds = xr.open_mfdataset(files, engine='h5netcdf', concat_dim=['step'], combine='nested')
        ```
        
        2. Create the DatasetHandler calling metintos.io.DatasetHandler.
        
        ```python
        dsh = metintos.io.DatasetHandler(cls.ds)
        ```
        
        3. Create CoordinateGenerator object and new axis, i.e.: latitudes, longitudes, steps.
        
        ```python
        cg = metintos.io.CoordinateGenerator()
        cg.add_axis_lims_n_points('latitude', l0, lf, ls)
        cg.add_axis_lims_n_points('longitude', lo0, lof, los)
        cg.add_axis_lims_resolution('step', s0, sf, ss)
        ```
        
        4. Produce the new dataset interpolated with optical flow
        
        ```python
        dsn = dsh.get_optical_flow_interpolated_dataset(cg.axes)
        ```
        
        ## How to compile documentation pdf
        
        
        You can use the Makefile created by Sphinx to create your documentation. Locate yourself in the documentation path.
        
        First clean the _build directory to avoid error or legacy information. Just call:
        
        ```bash
        make clean
        ```
        
        In case you want to build your documentation in latex call **twice**:
        
        ```bash
        make latexpdf
        ```
        
        if you want to do build your in html call:
        
        ```bash
        make html
        ```
        
        Note that you **should not see** any error or warning, this information appears as red text in the terminal.
        
        
        
        
        ## Contents
        
        
        Check METINTOS documentation in the following link: [METINTOS documentation link](https://metintos.readthedocs.io/en/latest/).
        
        
        
        ## Acknowledmgements
        
        
        
        This library has been developed within [FMP-Met Project](https://fmp-met.com). *FMP-Met has received funding from the SESAR Joint Undertaking (JU) under grant agreement No 885919. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and the SESAR JU members other than the Union*.
        
           
           
           
        
Keywords: Optical flow,Meteorological,Interpolation,Optimization,Simulation
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
Provides-Extra: tuning
