[Feature Request] Surface fitting for simple data, and example that shows the surface in plotly about fsharp.stats HOT 5 OPEN

@7sharp9 if you just want to visualize your data and do not care about the fit function that creates the surface, you can just use Chart.Surface from Plotly.NET as @bvenn suggested. However i think if you are interested in the coefficients that fit the surface, we'd need an equivalent of numpy.polyfit which to my knowledge is not implemented in FSharp.Stats.

As i do not know how your data looks like, here is a example that contains some boilerplate to generate some 2D data that also visualizes the points from the input across the surface:

//---------------------- Generate linearly spaced vector ----------------------
let linspace (min, max, n) =
    if n <= 2 then
        failwithf "n needs to be larger then 2"

    let bw = float (max - min) / (float n - 1.)
    Array.init n (fun i -> min + (bw * float i))

//---------------------- Create example data ----------------------
let size = 100

let x = linspace (-2. * Math.PI, 2. * Math.PI, size) // 100 evenly spaced samples between -2π and 2π
let y = linspace (-2. * Math.PI, 2. * Math.PI, size) // 100 evenly spaced samples between -2π and 2π

let f x y = -(5. * x / (x ** 2. + y ** 2. + 1.)) // function to generate z based on x and y: f(x,y) = -(5 * x / (x^2 + y^2 + 1))

let xyz = Array.init size (fun i -> Array.init size (fun j -> x.[j], y.[i], f x.[j] y.[i])) |> Array.concat // generate x,y,z triplets for point plot
let zArray = Array.init size (fun i -> Array.init size (fun j -> f x.[j] y.[i])) // generate z values for surface plot

[
    Chart.Point3D(xyz, Marker = Marker.init(Size = 1, Color = Color.fromString "blue"))
    Chart.Surface(zData = z, X = x, Y = y)
]
|> Chart.combine

from fsharp.stats.

Do you just want to have some kind of regression or just a smoothed interpolation of each point?
Currently FSharp.Stats is capable of smoothing two-dimensional data only, but if you just need and interpolation and the visualization to be smooth, you can just use a Plotly surface plot. The smooting is performed automatically and may even be adjustable (https://plotly.net/reference/plotly-net-chart3d-chart.html#Surface).

An example can be seen here or here.

from fsharp.stats.

Hi, thanks for the reply, to be honest just looking for any particular solutions, I have a certain amount of data which I want tto plot a surface for, the surface points should not stray away from the data set I have to interpolation like the thin plate spline seem to match my data the best but Ive also managed to replicate in 2d each dimension using tanh or arctan curves. So a F# solution of any sort would suffice for me. F# is th eeasy bits its just figuring out how from samples really.

from fsharp.stats.

If regression is a really close match to my input data I could use that too, but only if the surface is only ever higher than my plotted points, and not by very much.

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