This project is a GUI program written in python, intended to make it easy for solar cell researchers to characterize the electrical properties of the solar cells they make. It's meant to be robust enough to throw all your IV data files at it in one go (hence the "batch"). The code here takes IV (current-voltage sweep) data files (of various formats, new format additions welcome!) and uses it to find values for the components of the following solar cell circuit model:

where R_S is the series resistance
R_SH is the shunt resistance,
I_D is the diode current,
I_L is the light current,
I_0 is the reverse saturation current,
n is the diode's ideality factor,
I is the current out of the positive terminal of the cell (measured)
and V is the voltage across the cell (measured)
which is described by

I_L, I_0, n, R_S and R_SH are found by nonlinear regression via scipy.optimize.curve_fit() and the user can place arbitrary constraints on these fit parameters (such as specifying ranges for them or setting them to a specific value).

Feel free to shoot me an email with comments or suggestions. grey [AT] christoforo [DOT] net
I'd be super happy to accept pull requests or ideas you have for improving this and I can probably help add support for your own custom IV data file input format.

• Hover over the column headers for a little blurb on what that column contains
• Double click anywhere in the table to bring up a graph to compare the fitted curve with the raw data associated with the line you clicked (this is a way to quickly check if the fit is good or bad)
• This feature seems to crash under windows if you do this without closing a previously opened graph window
• Hover over the file name in each column to see the LabVIEW generated summary data for that file (for comparison purposes)
• The numbers shown in the table for Pmax, Vmax, Voc, I/Jsc and FF are calculated from a spline fit to the data.
• Hovering over these values will show those calculated from the fit to the characteristic solar cell equation
• Hovering over other numbers in the table will show +/- 95% confidence intervals for that value
• Can read and plot i,v vs time data files generated by i-v-vs-time-taker. Does no analysis on them currently (but could in the future).

• batch-iv-analysis.py
• Main python script. Run this to use the tool. You can edit the code in this file directly using your favorite editor.
• batch-iv-analysis.ui
• Contains user interface design for main window, edit with Qt Designer (I used version 5.6.0)
• batch_iv_analysis_UI.py
• Do not edit this file directly. Instead generate it from batch-iv-analysis.ui by issuing:
  pyuic5 -o batch_iv_analysis_UI.py batch-iv-analysis.ui
• Use this file to generate standalone release packages (see instructions below)

1. Make sure you have the very latest Python 3 version of Anaconda installed from here
2. Run the Anaconda Navigator program
3. Click the "Channels" button
4. Add a new channel called greyltc
5. Add a new channel called conda-forge
6. Click the "Home" button
7. Click Install for the batch-iv-analysis app that appears there

1. Download the python 3.6 miniconda from here
2. Run Anaconda Prompt (or get to your Anaconda command prompt however you please) and type:

conda update conda
conda update --all
conda config --append channels conda-forge
conda update --all
conda config --prepend channels greyltc
conda install batch-iv-analysis
# now you can run the program with
batch-iv-analysis
# and later you can make sure to keep everything up to date by periodically running
conda update --all

yay --needed -S git python python-mpmath python-gmpy2 python-sympy python-scipy python-pyqt5 python-pyqt5  python-matplotlib python-dill python-scikit-umfpack python-lmfit python-h5py
git clone https://github.com/greysAcademicCode/batch-iv-analysis.git
cd batch-iv-analysis
./batch-iv-analysis.py

1. Make sure you have the very latest Python 3 version of Anaconda installed from here
2. Run the "Anaconda Prompt" program that was installed in step #1 (on a Mac just run these commands in your terminal) and type the following in:

conda update conda
conda update --all
conda config --append channels conda-forge
conda update --all
conda install git conda-build
git clone https://github.com/greysAcademicCode/batch-iv-analysis.git
cd batch-iv-analysis
conda install --use-local batch-iv-analysis
batch-iv-analysis

# TODO: install deps
git clone https://github.com/greysAcademicCode/batch-iv-analysis.git
cd batch-iv-analysis
./batch-iv-analysis.py