Metadata-Version: 1.1
Name: tstoolbox
Version: 0.9.1
Summary: Command line script to manipulate time series files.
Home-page: http://pypi.python.org/pypi/tstoolbox
Author: Tim Cera, P.E.
Author-email: tim@cerazone.net
License: UNKNOWN
Description: TSToolbox - Quick Guide
        =======================
        The tstoolbox is a Python script to manipulate time-series on the command line
        or by function calls within Python.  Uses pandas (http://pandas.pydata.org/)
        or numpy (http://numpy.scipy.org) for any heavy lifting.
        
        Requirements
        ------------
        * pandas - on Windows this is part scientific Python distributions like
          Python(x,y), Anaconda, or Enthought.
        
        * mando - command line parser
        
        Installation
        ------------
        Should be as easy as running ``pip install tstoolbox`` or ``easy_install
        tstoolbox`` at any command line.  Not sure on Windows whether this will bring
        in pandas, but as mentioned above, if you start with scientific Python
        distribution then you won't have a problem.
        
        Usage - Command Line
        --------------------
        Just run 'tstoolbox' to get a list of subcommands
        
        .. program-output:: tstoolbox --help
        
        The default for all of the subcommands is to accept data from stdin (typically
        a pipe).  If a subcommand accepts an input file for an argument, you can use
        "--input_ts=input_file_name.csv", or to explicitly specify from stdin (the
        default) "--input_ts='-'" .  
        
        For the subcommands that output data it is printed to the screen and you can
        then redirect to a file.
        
        Sub-command Detail
        ''''''''''''''''''
        
        accumulate
        ~~~~~~~~~~
        .. program-output:: tstoolbox accumulate --help
        
        add_trend
        ~~~~~~~~~
        .. program-output:: tstoolbox add_trend --help
        
        aggregate
        ~~~~~~~~~
        .. program-output:: tstoolbox aggregate --help
        
        calculate_fdc
        ~~~~~~~~~~~~~
        .. program-output:: tstoolbox calculate_fdc --help
        
        clip
        ~~~~
        .. program-output:: tstoolbox clip --help
        
        convert
        ~~~~~~~
        .. program-output:: tstoolbox convert --help
        
        date_slice
        ~~~~~~~~~~
        .. program-output:: tstoolbox date_slice --help
        
        describe
        ~~~~~~~~
        .. program-output:: tstoolbox describe --help
        
        equation
        ~~~~~~~~
        .. program-output:: tstoolbox equation --help
        
        fill
        ~~~~
        .. program-output:: tstoolbox fill --help
        
        filter
        ~~~~~~
        .. program-output:: tstoolbox filter --help
        
        normalization
        ~~~~~~~~~~~~~
        .. program-output:: tstoolbox normalization --help
        
        peak_detection
        ~~~~~~~~~~~~~~
        .. program-output:: tstoolbox peak_detection --help
        
        pick
        ~~~~
        .. program-output:: tstoolbox pick --help
        
        plot
        ~~~~
        .. program-output:: tstoolbox plot --help
        
        read
        ~~~~
        .. program-output:: tstoolbox read --help
        
        remove_trend
        ~~~~~~~~~~~~
        .. program-output:: tstoolbox remove_trend --help
        
        rolling_window
        ~~~~~~~~~~~~~~
        .. program-output:: tstoolbox rolling_window --help
        
        stack
        ~~~~~
        .. program-output:: tstoolbox stack --help
        
        stdtozrxp
        ~~~~~~~~~
        .. program-output:: tstoolbox stdtozrxp --help
        
        tstopickle
        ~~~~~~~~~~
        .. program-output:: tstoolbox tstopickle --help
        
        unstack
        ~~~~~~~
        .. program-output:: tstoolbox unstack --help
        
        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 tstoolbox::
        
            from tstoolbox import tstoolbox
        
            # Then you could call the functions
            ntsd = tstoolbox.fill(method='linear', input_ts='tests/test_fill_01.csv')
        
            # Once you have a PANDAS DataFrame you can use that as input.
            ntsd = tstoolbox.aggregate(statistic='mean', agg_interval='daily', input_ts=ntsd)
        
        Author
        ------
        Tim Cera, P.E.
        
        tim at cerazone dot net
        
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 :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Libraries :: Python Modules
