Apply antenna factor and cable loss tospectrum analyzer measurements
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[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.
Three csv files containing the following are required inputs:
Each CSV file should contain data in two columns:
The amplitude is expected to be in dB.
csvmodule from the [Python Standard Library]
osmodule 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?
[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:
masterbranch is deployable
master, you can and should deploy immediately.
[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