Metadata-Version: 1.1
Name: applyaf
Version: 0.2.3
Summary: Apply antenna factor and cable loss tospectrum analyzer measurements
Home-page: http://github.com/questrail/applyaf
Author: Matthew Rankin
Author-email: matthew@questrail.com
License: MIT
Description: # applyaf
        
        [![PyPi Version][pypi ver image]][pypi ver link]
        [![Build Status][travis image]][travis link]
        [![Coverage Status][coveralls image]][coveralls link]
        [![License Badge][license image]][LICENSE.txt]
        
        [applyaf][] is a Python (2.6+/3.3+) module that applies frequency
        dependent antenna factors and cable losses to spectrum analyzer readings
        in order to calculate the incident field. Any duplicate frequency
        entries in the antenna factors or cable losses data are removed before
        interpolating the frequencies to match those of the spectrum analyzer
        readings.
        
        ## Inputs
        
        Three csv files containing the following are required inputs:
        
        1. Spectrum analyzer measurements
        2. Antenna factor data
        3. Cable loss data
        
        Each CSV file should contain data in two columns:
        
        1. Frequency
        2. Amplitude
        
        The amplitude is expected to be in dB.
        
        ## Requirements
        
        - [numpy][]
        - `csv` module from the [Python Standard Library][]
        - `os` module from the [Python Standard Library][]
        
        ## Future Improvements
        
        Some thoughts for future improvements include:
        
        1. Allowing CSV data files that contain non-dB amplitudes and then
        convert as needed. Should this be a per-file setting?
        2. Generalize the code to handle a variable number (>3) of data to be
        interpolated and applied to the given data set.
        3. If the code is generalized, should this be wrapped into the
        [siganalysis][] project or left on its own?
        
        ## Contributing
        
        [applyaf][] is developed using [Scott Chacon][]'s [GitHub Flow][]. To
        contribute, fork [applyaf][], create a feature branch, and then submit
        a pull request.  [GitHub Flow][] is summarized as:
        
        - Anything in the `master` branch is deployable
        - To work on something new, create a descriptively named branch off of
          `master` (e.g., `new-oauth2-scopes`)
        - Commit to that branch locally and regularly push your work to the same
          named branch on the server
        - When you need feedback or help, or you think the brnach is ready for
          merging, open a [pull request][].
        - After someone else has reviewed and signed off on the feature, you can
          merge it into master.
        - Once it is merged and pushed to `master`, you can and *should* deploy
          immediately.
        
        # License
        
        [applyaf] is released under the MIT license. Please see the
        [LICENSE.txt] file for more information.
        
        [applyaf]: https://github.com/questrail/applyaf
        [coveralls image]: http://img.shields.io/coveralls/questrail/applyaf/master.svg
        [coveralls link]: https://coveralls.io/r/questrail/applyaf
        [github flow]: http://scottchacon.com/2011/08/31/github-flow.html
        [LICENSE.txt]: https://github.com/questrail/applyaf/blob/develop/LICENSE.txt
        [license image]: http://img.shields.io/pypi/l/applyaf.svg
        [numpy]: http://www.numpy.org
        [pull request]: https://help.github.com/articles/using-pull-requests
        [pypi ver image]: http://img.shields.io/pypi/v/applyaf.svg
        [pypi ver link]: https://pypi.python.org/pypi/applyaf
        [python standard library]: https://docs.python.org/2/library/
        [scott chacon]: http://scottchacon.com/about.html
        [siganalysis]: https://github.com/questrail/siganalysis
        [travis image]: http://img.shields.io/travis/questrail/applyaf/master.svg
        [travis link]: https://travis-ci.org/questrail/applyaf
        
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: License :: OSI Approved :: MIT License
Classifier: Development Status :: 3 - Alpha
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires: numpy (>=1.6.0)
