Metadata-Version: 2.4
Name: disptrans
Version: 0.0.1
Summary: Dispersion-compensated algorithm for electromagnetic waveguides
Home-page: https://github.com/garrettj403/DispersionTransform/
Author: John Garrett
Author-email: garrettj403@gmail.com
License: MIT
Project-URL: Changelog, https://github.com/garrettj403/DispersionTransform/blob/master/CHANGES.md
Project-URL: Issue Tracker, https://github.com/garrettj403/DispersionTransform/issues
Keywords: dispersion,waveguide,signal-processing,dsp
Platform: any
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
License-File: LICENSE.md
Requires-Dist: numpy
Provides-Extra: testing
Requires-Dist: pytest; extra == "testing"
Requires-Dist: scikit-rf; extra == "testing"
Provides-Extra: examples
Requires-Dist: matplotlib; extra == "examples"
Requires-Dist: scikit-rf; extra == "examples"
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Dispersion-Compensated Algorithm
================================

*Dispersion-Compensated Algorithm for the Analysis for Electromagnetic Waveguides*

This package allows you to map dispersive waveguide data from the frequency-domain to distance-domain, and vice versa. The benefit of this approach, compared to a standard Fourier transform, is that this algorithm compensates for dispersion. Normally, dispersion causes signals in the time-domain to broaden as the propagate, making it difficult to isolate or supress adjacent signals. In the distance-domain, the signals remain sharp, even over long distances, allowing you to easily identify, isolate or suppress specific signals.

For more information, see: 

   - J. D. Garrett and C. E. Tong, ["A Dispersion-Compensated Algorithm for the Analysis of Electromagnetic Waveguides",](https://ieeexplore.ieee.org/document/9447194) *IEEE Signal Processing Letters*, vol. 28, pp. 1175-1179, Jun. 2021, doi: [10.1109/LSP.2021.3086695](https://doi.org/10.1109/LSP.2021.3086695).

Example: Simple Waveguide Section
---------------------------------

Transmission through a 10" long gold-plated WR-2.8 waveguide:

<p align="center">
<img src="https://raw.githubusercontent.com/garrettj403/DispersionTransform/main/examples/results/simple-waveguide-frequency.jpg" width="400">
</p>

Below, the time-domain response (calculated by an IFFT) is compared to the distance-domain response. Notice how much sharper the distance-domain response is.

<p align="center">
<img src="https://raw.githubusercontent.com/garrettj403/DispersionTransform/main/examples/results/simple-waveguide-time-vs-distance.jpg" width="600">
</p>

Example: Waveguide Cavity Resonator
-----------------------------------

This is a quick example showing the power of the dispersion-compensated algorithm. See [the included notebook](https://github.com/garrettj403/DispersionTransform/blob/main/examples/example-waveguide-cavity.ipynb) for more information.

For this example, we will start with the frequency-domain response of a simple waveguide cavity resonator, as shown below. This is a 1 inch long WR-2.8 cavity. Whenever the length of the cavity is an integer number of the guided wavelength divided by two, there is a peak in transmission.

<p align="center">
<img src="https://raw.githubusercontent.com/garrettj403/DispersionTransform/main/examples/results/cavity-freq-domain.jpg" width="600">
</p>

In the distance-domain, we can see a series of reflections corresponding to different signal paths within the resonator. The first peak is the signal passing straight through the resonator (distance = 1 inch), the second peak is the signal that undergoes ones internal back-and-forth reflection (distance = 3 inch), etc.

<p align="center">
<img src="https://raw.githubusercontent.com/garrettj403/DispersionTransform/main/examples/results/cavity-distance-domain.jpg" width="600">
</p>

In the distance-domain, we can easily isolate the first peak and then return to the frequency-domain. The isolated reflection provides a very close match to theory.

<p align="center">
<img src="https://raw.githubusercontent.com/garrettj403/DispersionTransform/main/examples/results/cavity-peak1.jpg" width="600">
</p>

Likewise, we can easily isolate the 6th peak and return to the frequency-domain. This is impossible in the time-domain because there is too much broadening and overlap between adjacent reflections.

<p align="center">
<img src="https://raw.githubusercontent.com/garrettj403/DispersionTransform/main/examples/results/cavity-peak6.jpg" width="600">
</p>

Note: This example is similar to the example presented by [Garrett & Tong 2021](https://ieeexplore.ieee.org/document/9447194), but it is slightly different (e.g., different dimensions, different iris parameters, etc.). Please see this paper for more information.

Citing This Repo
----------------

If you use this code, please cite the following paper:

    @article{Garrett2021,
      author       = {John D. Garrett and
                      Edward Tong},
      title        = {{A Dispersion-Compensated Algorithm for the Analysis of Electromagnetic Waveguides}},
      volume       = {28},
      pages        = {1175--1179},
      month        = jun,
      year         = {2021},
      journal      = {IEEE Signal Processing Letters},
      doi          = {10.1109/LSP.2021.3086695},
      url          = {https://ieeexplore.ieee.org/document/9447194}
    }
