asreimer / lmfit2 Goto Github PK

Hi Ashton,
I've been trying to run your lmfit2 code and I've been having some problems. I'm using python 2.7.13 and numpy 1.11.2. I'm trying to create the lmfit2 file from the rawacf file (20120614.0001.00.sas.rawacf) for the saskatoon data from Reimer et al. (2018) paper and keep I getting the following error:

Traceback (most recent call last):
  File "lmfit2.py", line 648, in <module>
    fitted_records = [p.get() for p in temp]
  File "/cm/shared/apps/python/gcc/2.7.13/lib/python2.7/multiprocessing/pool.py", line 567, in get
    raise self._value
TypeError: only integer arrays with one element can be converted to an index

Any help would be brilliant!
Thanks,
Samuel

Python version is missing some of the structure essential to a python module.

Standard SuperDARN processing usually fits both an Exponential and Gaussian envelope models. Currently, LMFIT2 only supports Exponential envelope fitting.

Hei @asreimer!

I'm reaching out because there have been several requests to add this library to the RST. We can take care of the implementation, but I just wanted to touch base first. Are you happy for us to copy the code? And do you recommend that we copy the develop branch (which seems to include some bug fixes)? RST and lmfit2 are both licensed under the GPLv3 so there will be no problems there.

Thanks!
Emma

XCF fitting is currently missing and needs to be implemented.

Gave up on installing the C version and went to use the python. There are no docstrings on the routines, and the README doesn't describe how the routines are supposed to be used. Help?

Currently C code depends on deprecated VTRST3.5 or RSTLite. Should be migrated to new supported SuperDARN/rst.

I'm having trouble getting the C code to compile. Problems I've had:

• Bstatic/dynamic flag unknown (-static/dynamic work)
• The library for "-lz" isn't found. Which library is this referencing for you? I didn't see anything about this in the README.

Instead of allowing mpfit to numerically estimate the jacobian, construct the jacobian analytically and provide this to mpfit.

mpfit is called here.

Documentation on how to provide user-specified derivatives to mpfit is here