Metadata-Version: 1.2
Name: hspf_utils
Version: 4.2.1.2
Summary: Utilities to work with Hydrological Simulation Program - FORTRAN (HSPF) models.
Home-page: http://timcera.bitbucket.io/hspf_utils/docsrc/index.html
Author: Tim Cera, P.E.
Author-email: tim@cerazone.net
License: UNKNOWN
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        hspf_utils - Quick Guide
        ================================
        The hspf_utils is a command line script and Python library of utilities to work
        with the Hydrological Simulation Program - FORTRAN (HSPF).  Uses pandas
        (http://pandas.pydata.org/) or numpy (http://numpy.scipy.org) for any heavy
        lifting.
        
        Requirements
        ------------
        * tstoolbox - Time-series toolbox; collected and installed by 'pip' or
          'easy_install' command.  
        * hspfbintoolbox - Utility to extract time-series from HSFP binary output
          files; collected and installed by 'pip' or 'easy_install' command.
        
        Installation
        ------------
        Should be as easy as running ``pip install hspf_utils`` or
        ``easy_install hspf_utils`` at any command line.
        
        Usage - Command Line
        --------------------
        Just run 'hspf_utils --help' to get a list of subcommands::
        
          usage: hspf_utils [-h] {about,detailed,summary,mapping,parameters} ...
          
          positional arguments:
            {about,detailed,summary,mapping,parameters}
              about               Display version number and system information.
              detailed            Develops a detailed water balance.
              summary             Develops a summary water balance.
              mapping             Develops a csv file appropriate for joining to a GIS
                                  layer.
              parameters          Develops a table of parameter values.
          
          optional arguments:
            -h, --help            show this help message and exit
        
        For the subcommands that output data it is printed to the screen and you can
        then redirect to a file.
        
        Usage - API
        -----------
        You can use all of the command line subcommands as functions.  The function
        signature is identical to the command line subcommands.  The return is always
        a PANDAS DataFrame.  Input can be a CSV or TAB separated file, or a PANDAS
        DataFrame and is supplied to the function via the 'input_ts' keyword.
        
        Simply import hspf_utils::
        
          from hspf_utils import hspf_utils
        
          # Then you could call the functions
        
          # Once you have a PANDAS DataFrame you can use that as input to other 
          # hspf_utils functions.
          ntsd = hspf_utils.aggregate(statistic='mean', agg_interval='daily', input_ts=ntsd)
        
        
Keywords: time_series
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Developers
Classifier: Environment :: Console
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.6
