---
tags: diagnostics, langmuir, minutes
---
# PlasmaPy Langmuir Meeting | Monday 2020 November 23 at 11:00 PT / 14:00 ET
[](https://hackmd.io/cxrk4rDlQlit4XDEXRMoQA)
### Video Conference Information
* Instant messaging: [Matrix](https://element.im/app/#/room/#plasmapy:openastronomy.org) and [Gitter](https://gitter.im/PlasmaPy/Lobby)
* [GitHub Minutes Repository](https://github.com/PlasmaPy/plasmapy-meeting-notes)
* [Langmuir Sub-directory](https://github.com/PlasmaPy/plasmapy-meeting-notes/tree/master/langmuir_2020-present)
* [PlasmaPy on GitHub](https://github.com/PlasmaPy/plasmapy) ([pull requests](https://github.com/PlasmaPy/plasmapy/pulls), [issues](https://github.com/PlasmaPy/plasmapy/issues))
* [PlasmaPy Enhancement Proposals on GitHub](https://github.com/PlasmaPy/PlasmaPy-PLEPs)
* [PlasmaPy Google Calendar](https://calendar.google.com/calendar?cid=bzVsb3ZkcW0zaWxsam00ZTlrMDd2cmw5bWdAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ)
* GitHub Project: [Prototype | Analysis, Diagnostic, and the Swept Langmuir](https://github.com/PlasmaPy/PlasmaPy/projects/19)
## Attendees
1. Erik
2. Steve
3. Gurleen
## Action Items
***Erik***
* Open PR to update fit_function Linear.root_solve that handles `m = 0` and `b = 0` cases
* Finish writing tests for `find_floating_potential()`
* Add to list of functionality the ability to find `Te` from fitting to the left side of the dI/dV peak.
***Gurleen***
* Implement a prominence "uncertainty" for `vp` inf `find_plasma_potential_didv()`.
* for "uncertainty" will use FWHM of the peak
* also report the prominence of the peak
***Future***
* open an issue to construct a metric that considers the signal noise when reporting the peaks "prominence" (`find_plasma_potential_didv()`)
## Agenda (please feel free to edit or add items)
1. Introductions
2. GitHub Project: [Prototype | Analysis, Diagnostic, and the Swept Langmuir](https://github.com/PlasmaPy/PlasmaPy/projects/19)
3. ...
4. ...
5. Issues
1. ...
2. ...
6. Pull requests in progress
1. [PR #889](https://github.com/PlasmaPy/PlasmaPy/pull/889): calculating floating potential
2. [PR #897](https://github.com/PlasmaPy/PlasmaPy/pull/897): plasma potential via dI/dV
3. [PR #813](https://github.com/PlasmaPy/PlasmaPy/pull/813): Langmuir & Diagnostic Framework
## Minutes
* fit functions to add
* Gaussian
* Gaussian + DC offset
* Gaussian + Linear offset
* Cauchy-Lorentz distribution
* **Should first update Gaussian distribution in `plasmapy.formulary.distribution` and add the Cauchy distribution.**
* `find_plasma_potential_didv()`
* it's difficult to attribute an uncertainty with the `vp` calculation since we don't have an analytical model to fit to the curve
* a proposed "uncertainty" would use the peak width at some prominence level
* Should this prominence be a fixed value, a level based on the signal-to-noise ratio, and/or an input argument?
* [Steve's suggestion] use the prominence level equivalent to 1 sigma of a Gaussian
* [Steve] prefers using the FWHM as the default width
* Should report the prominence of the peak, but this does not encompass all the info
* this gives the height above the baseline
* it does not factor in the noise level of the signal
* **for now we should stick with the peak prominence and open an issue to construct a metric that considers the signal noise**
* possible peak fitters
* Gaussian
* Lorentzian
* piecewise linear
* piecewise Exponential+Linear
* As an option, have `find_plasma_potential_didv()` find `Te` on request
```python
def find_plasma_potential_didv(get_Te=false):
...
# calculate didv
didv_arr = ...
didv_xpart = ...
# find vp
vp = ....
if get_Te:
# crop data for fit
vp_index = ...
didv_sub = didv_arr[start:vp_index]
vsub = didv_xarr[start:vp_index]
te_resutls = find_electron_temp_didv(vsub, didv_sub)
return vp_results, te_results
def find_electron_temp_didv(vdata, didvdata):
# calc te by fitting
return te_results
```