Conversion of a MATLAB Code to Python: Increasing Accessibility to Surface Plasmon Resonance Biosensing Studies

In this paper, a Python coded simulation of a surface plasmon resonance (SPR) biosensor that considers the application of electrical bias across the sensor surface is compared to the same simulation written in MATLAB. MATLAB is a high-level, expensive, and hardware demanding programming language that is commonly used in the data science domain due to its efficiency and convenience in calculation-heavy programming. However, Python is a high-level, free-to-use, popular, and extremely accessible programming language that is comparatively less demanding of hardware. The goal of this comparison was aimed at investigating the process of converting the MATLAB program to Python and determining the advantages and disadvantages of the Python simulation to determine the feasibility of performing the simulation on a more accessible computing device such as a Raspberry Pi. The conversion process included manual translation and translation performed by artificial intelligence. Upon completion of the conversion, the MATLAB simulation dramatically outperformed the Python counterpart by completing the calculations in times between 30 and 50 min; compared to Python’s completion times between 90 and 120 min. Ultimately, it was determined that while MATLAB has many disadvantages involving costs, with the use of dynamic translation it is able to execute the simulation program much more efficiently than the Python program. Therefore, economic and performance factors must be balanced for the subject utilizing the program.