Metadata-Version: 2.1
Name: PyGWP
Version: 0.0.30
Summary: A CO2-equivalent computer based on static or dynamic CO2-relative global warming potentials coded in Python27, PyGWP.
Home-page: https://github.com/lfaucheux/PyGWP
Author: Laurent Faucheux
Author-email: laurent.faucheux@hotmail.fr
License: MIT
Download-URL: https://github.com/lfaucheux/PyGWP/archive/0.0.30.tar.gz
Description: # [PyGWP](https://github.com/lfaucheux/PyGWP) - A **CO2-equivalent computer** based on static or dynamic CO2-relative global warming potentials.

        

        ## Sources 

        - **[IPCC WG1 Fourth Assessment Report, 2007](https://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch2s2-10-2.html)**

        - **[Levasseur et al, 2010](http://pubs.acs.org/doi/abs/10.1021/es9030003)**

        

        ## Installation

            git clone git://github.com/lfaucheux/PyGWP.git

            cd PyGWP

            python setup.py install

        

        ## Requirements

        

        - **[numpy](http://www.numpy.org/)**

        

        ## Use cases

        

        - **Scientific modelling**

        

        ## Example usage:

        

            >>> from PyGWP import GWPBasedCO2eq

            >>> dyn_gwp20 = GWPBasedCO2eq(

            ...     first_year      = 2020,

            ...     project_horizon = 5,

            ...     GWP_horizon     = 20,

            ...     static          = False

            ... )

            >>> ghgs_weight_per_weight_of_output_inventory_flow = {'CO2':1., 'N2O':.0, 'CH4':.0}

            >>> co2eq_traj = dyn_gwp20.co2eq_yields_trajectory_computer(

            ...     ghgs_weight_per_weight_of_output_inventory_flow,

            ...     as_row_array=False

            ... )

            >>> co2eq_traj['as_array']

            array([[1.        ],

                   [0.95764081],

                   [0.91469171],

                   [0.87112496],

                   [0.82691128]])

            >>> co2eq_traj['as_dict']

            {2024: 0.82691127746144444, 2020: 1.0, 2021: 0.95764080833063492, 2022: 0.91469171438570718, 2023: 0.87112496115582216}

        

            >>> co2eq_traj = dyn_gwp20.co2eq_yields_trajectory_computer({'CO2':.0,'N2O':1.,'CH4':.0})

            >>> co2eq_traj['as_array']

            array([[292.33637282, 278.90543843, 265.35617058, 251.68752668,

                    237.89845498]])

        

        

            >>> co2eq_traj = dyn_gwp20.co2eq_yields_trajectory_computer({'CO2':.0,'N2O':.0,'CH4':1.})

            >>> co2eq_traj['as_array']

            array([[72.2209832 , 70.75950679, 69.17102216, 67.44449179, 65.56791893]])

        

            >>> sta_gwp20  = GWPBasedCO2eq(

            ...     first_year      = 2020,

            ...     project_horizon = 5,

            ...     GWP_horizon     = 20,

            ...     static          = True

            ... )                                           

            >>> co2eq_traj = sta_gwp20.co2eq_yields_trajectory_computer({'CO2':.0, 'N2O':.0, 'CH4':1.})

            >>> co2eq_traj['as_array']

            array([[72.2209832, 72.2209832, 72.2209832, 72.2209832, 72.2209832]])

        

        

        ## License

        Distributed under the [MIT license](https://opensource.org/licenses/MIT)

        
Keywords: Global Warming Potential,Static Global Warming Potential,Dynamic Global Warming Potential
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2.7
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/markdown
