a lot of work but not addressing the fundamentals

[tokkenT]

Unsure of this... 85 contributors 3.3k "users". A great detail of documentation on its capability. However, the fundamental core usage howto non-existent.

There should be a usage section on the main or the readme file. where it shows exactly how to run this after installation is set. major disconnect on this very basic ability. Should require "thinking" just simple her run this.. here run this for additional capability.... new tool adoption shouldn't require such efforts. Will prevent adoption...

[newville]

@tokkenT Do you mean to say that you want a gentler introduction in the documentation for this code?

I would not necessarily disagree with that, but for a topic that would typically be regarded as "senior undergraduate level" math/science/engineering/data processing, the "gentle introduction" might make many assumptions that might not be considered "gentle" to everyone:
a. do we assume the reader is familiar with derivatives, matrices?
b. do we assume the reader is familiar with linear regression, and understands the a "non-linear" polynomial
is actually "linear" in the sense used here?
c. do we assume the user is familiar with numpy?
d. do we assume the user is familiar with scipy.optimize and its curve_fit?

That's just to say that "gentle" is relative.

There is a basic example in https://lmfit.github.io/lmfit-py/intro.html, and lots of examples. Concrete suggestions are welcome. If I had more time, I would like to do a series of videos, and adopt GUIs I've written to be more "general-purpose lmfit GUIs".

Having started this more than 10 years ago, I do not consider this to be "a new tool". We're happy to make it useful for other people, and lots of people find this useful.

For me, the biggest take-away here is that GH allowed you to create a blank issue, whereas we have worked to make clear separations of actual issues (which this most certainly is not) and discussions. I'll have to look into fixing that.

[tokkenT]

my bad wrong project https://github.com/AlexsJones/llmfit was what I was looking for