Metadata-Version: 1.1
Name: eemeter
Version: 2.1.5
Summary: Open Energy Efficiency Meter
Home-page: http://github.com/openeemeter/eemeter
Author: Phil Ngo
Author-email: admin@openee.io
License: Apache 2.0
Description: 
        EEmeter: tools for calculating metered energy savings
        =====================================================
        
        .. image:: https://travis-ci.org/openeemeter/eemeter.svg?branch=master
          :target: https://travis-ci.org/openeemeter/eemeter
          :alt: Build Status
        
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          :target: https://github.com/openeemeter/eemeter
          :alt: License
        
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          :alt: Documentation Status
        
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          :alt: PyPI Version
        
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          :alt: Code Coverage Status
        
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        ---------------
        
        **EEmeter** — open source implementations of standard methods for calculating
        metered energy savings.
        
        The eemeter contains the reference implementation of the CalTRACK methods for
        computing metered energy usage differences at sites with building efficiency
        interventions or at control sites without known interventions.
        
        Installation
        ------------
        
        EEmeter is a python package and can be installed with pip.
        
        ::
        
            $ pip install eemeter
        
        Features
        --------
        
        - Candidate model selection
        - Data sufficiency checking
        - Reference implementation of standard methods
        
          - CalTRACK Daily Method
          - CalTRACK Monthly Method
        
        - Flexible sources of temperature data. See `EEweather <https://eeweather.readthedocs.io>`_.
        - Model serialization
        - First-class warnings reporting
        - Pandas dataframe support
        - Visualization tools
        
        Command-line Usage
        ------------------
        
        Once installed, ``eemeter`` can be run from the command-line. To see all available commands, run ``eemeter --help``.
        
        Use CalTRACK methods on sample data::
        
            $ eemeter caltrack --sample=il-electricity-cdd-hdd-daily
        
        Save output::
        
            $ eemeter caltrack --sample=il-electricity-cdd-only-billing_monthly --output-file=/path/to/output.json
        
        Load custom data (see ``eemeter.meter_data_from_csv`` and ``eemeter.temperature_data_from_csv`` for formatting)::
        
            $ eemeter caltrack --meter-file=/path/to/meter/data.csv --temperature-file=/path/to/temperature/data.csv
        
        Do not fit CDD-based candidate models (intended for gas data)::
        
            $ eemeter caltrack --sample=il-gas-hdd-only-billing_bimonthly --no-fit-cdd
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
