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Questions tagged [curve-fitting]

Fitting 1-D curve to data points, minimizing pre-defined error/loss function.

From wiki:

Curve fitting is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points.

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scipy curve_fit raises "OptimizeWarning: Covariance of the parameters could not be estimated"

I am trying to fit this function to some data: But when I use my code import numpy as np from scipy.optimize import curve_fit import matplotlib.pyplot as plt def f(x, start, end): res = np.empty_like(x) res[x < start] =-1 res[x > end]…
Jonas
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Using scipy.optimize.curve_fit with weights

According to the documentation, the argument sigma can be used to set the weights of the data points in the fit. These "describe" 1-sigma errors when the argument absolute_sigma=True. I have some data with artificial normally-distributed noise which…
xnx
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Fitting with ggplot2, geom_smooth and nls

I am trying to fit data on an exponential decay function (RC like system) with equation: My data are on the following dataframe: dataset <- data.frame(Exp = c(4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6,…
Oneira
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Use Math.NET's Fit.Polynomial method on functions of multiple parameters

I previously used Math.NET Numerics library's Fit.Polynomial method to fit a cubic polynomial on a set of data that could be modeled as a function of one parameter y=f(x). Now I would like to similarly find a 2 or 3 order polynomial that fits data…
wip
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Fitting data using UnivariateSpline in scipy python

I have a experimental data to which I am trying to fit a curve using UnivariateSpline function in scipy. The data looks like: x y 13 2.404070 12 1.588134 11 1.760112 10 1.771360 09 1.860087 08 1.955789 07 1.910408 06 …
Prakhar Mehrotra
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Smooth spline representation of an arbitrary contour, f(length) --> x,y

Suppose I have a set of x,y coordinates that mark points along contour. Is there a way that I can build a spline representation of the contour that I can evaluate at a particular position along its length and recover interpolated x,y coordinates? It…
ali_m
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Linear / Non-Linear Fit to a Sine Curve

I've had a look at this and this. But I have a slightly different problem. I know that my data is a sine curve, of unknown period and unknown amplitude, with additive non-gaussian distributed noise. I'm attempting to fit it using the GSL non-linear…
Kitchi
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How does the Levenberg–Marquardt algorithm work in detail but in an understandable way?

Im a programmer that wants to learn how the Levenberg–Marquardt curvefitting algorithm works so that i can implement it myself. Is there a good tutorial anywhere that can explain how it works in detail with the reader beeing a programmer and not a…
Per Arneng
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Applying bounds to specific variable during curve_fit (scipy) leads to an error

I am trying to apply bounds onto some of the parameters during curve fitting but I'm getting the following error message when I tried to do so: ValueError: too many values to unpack Doesn't each 2-tuple in the bound command corresponds to x0, k,…
Ang Jit Wei Aaron
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Catmull-Rom interpolation on SVG Paths

I am experimenting with creating high-performance, good-looking pencil tools using SVG paths. I am logging the mouse coordinates to draw a path. To get a high-fidelity path (accurate to the user's movements) I need to log a point for every pixel…
nicholaswmin
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Python and lmfit: How to fit multiple datasets with shared parameters?

I would like to use the lmfit module to fit a function to a variable number of data-sets, with some shared and some individual parameters. Here is an example generating Gaussian data, and fitting to each data-set individually: import numpy as…
Merlin
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scipy.optimize.curvefit() - array must not contain infs or NaNs

I am trying to fit some data to a curve in Python using scipy.optimize.curve_fit. I am running into the error ValueError: array must not contain infs or NaNs. I don't believe either my x or y data contain infs or NaNs: >>> x_array =…
Bryce Thomas
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curve fitting with python

I'm trying to fit some data and stuff, I know there is a simple command to do this with python/numpy/matplotlib, but I can't find it. I think it is something like popt,popc = numpy.curvefit(f,x) where popt is the paramters of f, popc is the fit…
Yotam
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Using Scipy curve_fit with piecewise function

I am getting an optimize warning: OptimizeWarning: Covariance of the parameters could not be estimated category=OptimizeWarning) when trying to fit my piecewise function to my data using scipy.optimize.curve_fit. Meaning no fitting…
lanery
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Fitting a function in R

I have a few datapoints (x and y) that seem to have a logarithmic relationship. > mydata x y 1 0 123 2 2 116 3 4 113 4 15 100 5 48 87 6 75 84 7 122 77 > qplot(x, y, data=mydata, geom="line") Now I would like to find an…
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