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The quantitative evaluation of experimental data and their graphical presentation are integral to teaching and research in chemistry and the life sciences. Data are commonly fitted to physical models, which in all but the simplest cases are expressed as nonlinear mathematical functions. To facilitate data evaluation in both teaching and research contexts, the Fit-o-mat program, implemented in Python, offers versatile nonlinear least-squares curve fitting through a graphical user interface. Fit-o-mat supports near-arbitrary fitting functions, including numerical and discontinuous ones, produces vectorized graphics, runs on different operating systems, and is free of charge, thus promoting the adoption of the program by students and instructors in the classroom and beyond. An embedded tutorial mode facilitates integration of Fit-o-mat into teaching curricula at the undergraduate and graduate levels.
Andreas Möglich (Tue,) studied this question.