Code for Pitt's CHEM 1430 HCl/DCl IR Spectroscopy Lab. This lab had a lot of data analysis, but a lot of it was essentially programming the same thing over again for a different transition. So I took the code I had written and condensed it into a few functions that you can use for any transition. I will clean and add the remaining code I have written, which fit the peak wavenumbers vs their transition number to a function, and then returns the fitting parameters, along with computing other interesting/necessary values needed for this lab. Examples of how to use the functions can be found in either the Examples.py or the Examples.ipynb, which will render in the browser.
- Read exported csv spectroscopy file into python
- Plot entire spectrum
- Better documentation
- Automatically detect peaks
- Label peaks with transition number, wavenumber
- Label Branches
- Fit functions to wavenumber vs transition number
- Plot fitted function, wavenumber vs transition number with title and proper axis labels
- Automatic Peak Detection
- Functions to fit peak wavenumbers/associated quantum numbers to functions
- Updated plotting function to only label peaks with integer values to prevent overlap
- Centered labels overtop their associated peaks.
- Tested with another data set.
- Fixed Peak Detection algorithm to account for noise potentially larger than prominance.
- This could have ruined filtering algorithm, as 37Cl peaks would be higher than noise, meaning they would not be filtered.
- Identify true initial P and R-Branch peaks. (J = 1, J = 0)
- These peaks were previously at risk at being filtered out since they can be lower than peaks on either side.
This library is written in Python 3 and depends on Numpy, Scipy, and Matplotlib.
Special thanks to my lab partner Forrest, and colleague Erik who provided data for testing.