FPFM Implemented as LMFIT2

Summary

This is the first release of the First-Principles Fitting Methodology (FPFM) algorithm that can be used to fit SuperDARN rawacf data. The details of this algorithm are described in Reimer et. al. (2018) https://doi.org/10.1002/2017RS006450.

This release is the version of the LMFIT2 software used in Reimer et. al. (2018). Please see the README.md for installation instructions.

Modifications Since Publication

No modifications have been made to the C code since before the publication of Reimer et. al. (2018). Unit testing was added to the C code, but this is extra software added in separate files with no modification to the actual C code. The point of saying this is that one should be able to use this code to reproduce the results shown in the publication.

Several modifications were made to the python version of the code, with many thanks to @samuelwharton for independent testing help. These modifications include a couple bug fixes that makes the python code work almost identically to the C code, addition of unit testing.

Usage

This code was written with the intention that the C version would be used for any serious application. The python code was written because python is much more readable, so one can use the python code to study how the FPFM algorithm works. The python code is much slower than the C code and should only be used for testing and learning.