Hi Anton,
awesome tool, thanks for sharing!
I was wondering if it's also possible to import data containing time steps? Our DLTS setup doesn't sample the capacitance transient equidistant, so its not possible to use the "t_step". Is it already possible to include it in the .DLTS file or would the "read_file.py" module need a change?

Many thanks for you help,
Chris

Hi Anton,

I again want to express my sincere gratitude for sharing your code. I have now spent a significant amount of time delving into it and have been able to understand most of its functionality. I have also successfully implemented some very useful tools, such as a peak-finding algorithm for the heatmap, allowing me to create a scatter plot of emission rates over temperature (Arrhenius plot). Additionally, the code now performs linear regression on the Arrhenius plot to identify defect characteristics, specifically activation energy and capture cross-section.

However, I am still struggling to fully grasp the purpose and functionality of the "process(C, proc)" function. I would be incredibly grateful if you could explain the rationale behind its implementation. Using your original code with my data consistently results in low-frequency noise. Could you perhaps provide some insight into this issue?

This noise vanishes when not performing the "F = F + np.average(F)*2":

Therefore, the "Contin" algorithm appears to perform less effectively in the low-temperature regime. This is likely due to the increased noise in the initial transient data. Unfortunately, the "reSpect" algorithm is incompatible with this specific modification. If you have any experience with the suitability of different transient processing techniques for various data types, I would greatly appreciate your insights.

Thank you very much & best regards,
Chris