Figuring Out Function from Curve: Is it Possible?

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SUMMARY

Curve fitting is a mathematical technique used to determine a function that represents a given curve, particularly when the curve is not a standard shape like a parabola or ellipse. This process can yield simple polynomial functions or more complex representations, depending on the desired accuracy. It is essential to consider measurement errors, as fitting a curve to every data point may not be practical. The technique allows for the simplification of complicated functions into more manageable approximations while maintaining close accuracy over specific regions.

PREREQUISITES
  • Understanding of polynomial functions and their properties
  • Familiarity with curve fitting techniques and algorithms
  • Knowledge of measurement error analysis
  • Basic skills in data visualization tools, such as MATLAB or Python's Matplotlib
NEXT STEPS
  • Research advanced curve fitting techniques using Python's SciPy library
  • Explore polynomial regression methods and their applications
  • Learn about measurement error analysis and its impact on data fitting
  • Investigate data visualization best practices for effective curve representation
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Mathematicians, data scientists, engineers, and anyone involved in data analysis or modeling who seeks to understand or apply curve fitting techniques.

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Given a function, it is easy enough to plot its curve, just by substituting numerical values.

But is the reverse possible? I mean, if you're given a curve's figure, can you figure out the function that represents it (provided that the curve is not a well-known one like a parabola or ellipse) ?
 
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There is a whole branch of mathematics devoted to curve fitting. Depending on how precise you want your curve to fit, you can end up with a simple polynomial or something very complicated. Sometimes it would be absurd to have the curve go exactly through every data point on your plotted data, especially when it's clear that one or more of your data points involve an erroneous reading or the reading errors in most measurements are significant.

Curve-fitting also offers the opportunity to replace a complicated function with a much simpler function but still a very close approximation, over a region of interest, to make calculations easier or more efficient.

Any particular plot of data can be fitted by an almost infinite number of curves, so there is plenty of scope for originality!
 

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