Mathematica plot envelope data smoothing

In summary, the conversation discusses a Mathematica code that generates a highly oscillatory plot. The speaker is looking to plot only the lower envelope of the plot but is unsure how to do so. They suggest binning the data and taking the minimum of each bin as a potential solution.
  • #1
carey1000
2
0
The following Mathematica code generates a highly oscillatory plot. I would like to plot only the lower envelope of the plot but do not know how. Any suggestions wouuld be appreciated.

tk0 = \[Theta]'[t]*\[Theta]'[t] - \[Theta][t]*\[Theta]''[t]
tk1 = \[Theta]''[t]*\[Theta]''[t] - \[Theta]'[t]*\[Theta]'''[t]
a = tk0/Sqrt[tk1]
f = Sqrt[tk1/tk0]
s =
NDSolve[{\[Theta]''[t] + \[Theta][t] - 0.167 \[Theta][t]^3 ==
0.005 Cos[t - 0.5*0.00009*t^2], \[Theta][0] == 0, \[Theta]'[0] ==
0}, \[Theta], {t, 0, 1000}]

Plot[Evaluate [f /. s], {t, 0, 1000}, Frame -> {True, True, False, False},
FrameLabel -> {"t", "Frequency"}, FrameStyle -> Directive[FontSize -> 15], Axes -> False]

Thank you, Carey
 
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  • #2
Offhand the easiest way i can think of is to bin the data and take the min of each bin.
 

Related to Mathematica plot envelope data smoothing

What is Mathematica plot envelope data smoothing?

Mathematica plot envelope data smoothing is a method used to smooth out a plot of data by fitting a smooth curve to the data points. This allows for a clearer visualization of trends and patterns in the data.

How does Mathematica plot envelope data smoothing work?

Mathematica plot envelope data smoothing works by using various mathematical techniques, such as regression or interpolation, to fit a curve to the data points. This curve is then used to generate a smoother plot, reducing the noise and making the data easier to analyze.

What are the benefits of using Mathematica plot envelope data smoothing?

Using Mathematica plot envelope data smoothing can help to reveal hidden patterns and trends in the data that may not be easily seen with a raw plot. It also makes it easier to identify outliers and anomalies in the data.

Are there any limitations to using Mathematica plot envelope data smoothing?

Like any data smoothing technique, Mathematica plot envelope data smoothing can potentially oversimplify the data and hide important details. It is important to carefully consider the purpose of the data analysis and determine if smoothing is the best approach.

How can I use Mathematica to plot envelope data smoothing?

To use Mathematica for plot envelope data smoothing, you can use the built-in functions, such as "SmoothHistogram" or "SmoothKernelDistribution", or create your own custom smoothing function using the "Fit" or "Interpolation" functions.

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