Generate a report from solar simulator measurement data.
Download and run the latest release for you opterating system from here.
Create and activate a new Python (version 3.10) virtual environment e.g. using conda, venv etc. Then clone this repository using git and navigate to its newly created directory:
git clone https://github.com/jmball/data_analysis.git
cd data_analysis
Install the dependencies into the virtual environment using:
pip install -r requirements.txt
To run the program with a GUI on Windows (or Linux) call:
python data_analysis.py
or on a MacOS call:
pythonw data_analysis.py
To skip the GUI use:
python data_analysis.py --ignore-gooey "[folder]" [fix_ymin_0]
where [folder] is the absolute path to the folder containing data and fix_min_0 is a flag indicating whether you want the y-axes of boxplots to start from zero (yes), or to autoscale (no).
First, install the wxPython prerequisites listed here.
In addition, if your distribution's package manager doesn't include tkinter with your Python installation (e.g. Ubuntu), it must be installed separately (e.g. sudo apt install python3.x-tk, where x denotes your version of python3).
Then follow the instructions for 'Windows and MacOS (Python users)' above.
To compile the program into a standalone binary file first follow the 'Installation and Usage' instructions for 'Windows and MacOS (Python users)' or 'Linux' above until you have installed the dependencies from the requirements.txt file. Then run:
pyinstaller data_analysis.spec
This will create two new folders in the current directory called build and dist. The binary file is in the dist folder and will be called data_analysis.exe on Windows, data_analysis.app on MacOSX, and just data_analysis on Linux.