- #1
alpha754293
- 29
- 1
If I have a x,y table of discrete datapoints with a discrete dataset, such that delta x is not a constant, what are some of the more advanced techiques that I can use to integrate this?
I remember that there were Trapezoidal rules and Simpson's rule where delta x IS a constant (and there are additional requirements for Simpson's rule, for example), but my data set doesn't fit (and can't be made to fit) those requirements.
Is the trapezoid rule the only option that I have to integrate numerical data sets?
The y=f(x) is a pretty random curve (there's no rhyme or rhythm to it) and for all practical intents and purposes, it's pretty much random.* (*The reality is a little more complicated than that, but I don't want to get into the complication issues right now, because I want to focus on what are the options that are available to me for numerical analysis.)
Help/suggestion/advice would be greatly appreciated.
I remember that there were Trapezoidal rules and Simpson's rule where delta x IS a constant (and there are additional requirements for Simpson's rule, for example), but my data set doesn't fit (and can't be made to fit) those requirements.
Is the trapezoid rule the only option that I have to integrate numerical data sets?
The y=f(x) is a pretty random curve (there's no rhyme or rhythm to it) and for all practical intents and purposes, it's pretty much random.* (*The reality is a little more complicated than that, but I don't want to get into the complication issues right now, because I want to focus on what are the options that are available to me for numerical analysis.)
Help/suggestion/advice would be greatly appreciated.