# I want to smooth this function plot

• B
In summary, the author is asking for ways to smooth a function so that it does not jump around too much early on in the calculation. They are also asking for a function that can be used to model human decision-making.
Hi,
I have the following function, which is computed by: (x+n)/(x+y+n+m),
where x, y are real numbers
n, m are natural numbers

What techniques I can use to smooth the function preventing it to jump up or down at an early stage.

I would appreciate your suggestion.
Thanks

I'm confused, your axis on the bottom is labeled as T, what does that have to do with your function?

I kind of assumed x and y were both inputs into your function, so I'm confused how you graphed it like this in general.

Office_Shredder said:
I'm confused, your axis on the bottom is labeled as T, what does that have to do with your function?

I kind of assumed x and y were both inputs into your function, so I'm confused how you graphed it like this in general.
Thank you. T represents the time. It seems that n increases quickly in the early timesteps. I am still thinking of ways to use T in the formula.

Thank you. T represents the time. It seems that n increases quickly in the early timesteps. I am still thinking of ways to use T in the formula.
You have still not told us what it is that you have graphed.

The graph in post #1 makes no sense given your formula. The labels on the graph are C and T, but the formula appears to be a function of x and y, as well as m and n.

Disregarding the m and n terms for the moment, if you have ##f(x, y) = \frac x {x + y}##, the graph will be a surface in three dimensions, with a discontinuity along the line y = -x.

Last edited:
adan and jim mcnamara
The formula, as well as the graph, are already smooth within their domain.

Thank you. Yes, I just want to slow down the jump at the beginning.

Thank you. Yes, I just want to slow down the jump at the beginning.
So please provide the following functions, as you've already been asked:

x(T)
n(T)
y(T)
m(T)

fresh_42
berkeman said:
So please provide the following functions, as you've already been asked:

x(T)
n(T)
y(T)
m(T)
x,n,y,m are variables that are changing over time

x,n,y,m are variables
You have a plot with them! Show us the funtion that you used to generate the plot please.

berkeman said:
You have a plot with them! Show us the funtion that you used to generate the plot please.
I construct the function but not fully sure if it is the best way to put all the variables together. I am building a simulation and trying to model human decisions but my model is very simple. The function is above with the question. x and y represent positive and negative personal experiences. n and m represent positive and negative opinions on social media. I assume the combination of all variables specifies the probability of consumption. Because at the beginning of the simulation, social media has 0 opinions, at step 1, multiple opinions are posted.

You have plotted a function ##F\, : \, \mathbb{R}^+\longrightarrow [0,1]## which means for any value ##T\in \mathbb{R}^+## you plotted a point ##(T,F(T)).## Our question is: What is ##F##? It depends only on ##T##, so how do we get from ##\dfrac{x+n}{x+n+y+m}## to ##F(T)##?

fresh_42 said:
You have plotted a function ##F\, : \, \mathbb{R}^+\longrightarrow [0,1]## which means for any value ##T\in \mathbb{R}^+## you plotted a point ##(T,F(T)).## Our question is: What is ##F##? It depends only on ##T##, so how do we get from ##\dfrac{x+n}{x+n+y+m}## to ##F(T)##?
F depends on all x,y,n,m, and T also.

Sigh. Your obfuscations will get you nowhere...

Whatever. If you don't like the first point, then just don't plot it. How's that for a solution?

jim mcnamara and adan
berkeman said:
Sigh. Your obfuscations will get you nowhere...

Whatever. If you don't like the first point, then just don't plot it. How's that for a solution?
Ok, thank you. I will look into your suggestion.

Okay. Will close the thread, we seem to have the kind of answer that the OP wanted.

SammyS and berkeman

## 1. How do I smooth a function plot?

To smooth a function plot, you can use a technique called interpolation. This involves creating a new set of data points that lie between the existing data points and then plotting the new points to create a smoother curve.

## 2. What is the purpose of smoothing a function plot?

The purpose of smoothing a function plot is to reduce noise and make the curve easier to interpret. This can be particularly useful when dealing with large datasets or when trying to identify trends in the data.

## 3. What methods can I use to smooth a function plot?

There are several methods that can be used to smooth a function plot, including moving average, polynomial fitting, and spline interpolation. Each method has its own advantages and disadvantages, so it's important to choose the one that best suits your data.

## 4. Is it possible to over-smooth a function plot?

Yes, it is possible to over-smooth a function plot. This can occur when the smoothing technique removes too much of the original data, resulting in a curve that does not accurately represent the underlying data. It's important to find a balance between smoothing and preserving the integrity of the data.

## 5. Are there any tools or software available for smoothing function plots?

Yes, there are many tools and software available for smoothing function plots. Some popular options include Microsoft Excel, MATLAB, and Python libraries such as NumPy and SciPy. These tools offer various smoothing techniques and allow for customization of the smoothing process.

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