Curve fit python stack overflow. The y is approximated to .

Curve fit python stack overflow. curve_fit command which takes as arguments the function name (func), and the xdata and ydata. But this array can be filled with arbitrary data: The underlying problem with your load data is that you cast it to float32, but in scipy 0. I'm new to Python, got the frame code from my PhD advisor, and managed to add few hundred lines of code to the frame. For global optimization, other choices of objective function, and other advanced features, consider using SciPy’s Global optimization tools or the LMFIT package. Sep 14, 2023 · I asked the following question yesterday and this is an extension of this question: Python - curve_fitting doesn't work properly with high x-values For completeness, I will explain the situation again. mean (d_spacing_2) sigma=np. This went all great when I tried to generate a curve with the curve_fit example but not when I use my own data. I have initially copied the code suggested by the docs. It looks alright, but the red line on the left portion does not fit so well to the data (green dots). I have two known Nov 9, 2016 · I've been trying to fit an exponential to some data for a while using scipy. Jun 2, 2019 · I'm using scipy. optimize import curve_fit mu=np. turn it into a numpy array with xdata = np. 03 t = 0 dt = 0 Apr 11, 2020 · Optimization procedures can get trapped in local maxima (when any change to the parameters would first make the fit worse before it would get better). May 19, 2019 · I have a post, and I need to predict the final score as close as I can. Jun 1, 2025 · 0. The curve_fit function takes inputs as curve_fit(f, xdata, ydata, ), in which f callable is the model function, f(x, ). Nov 27, 2016 · I want to fit a function with vector output using Scipy's curve_fit (or something more appropriate if available). optimize import curve_fit from lmfit import minimize, Parameters, Parameter, report_fit# import xlwings as xw import os import Apr 25, 2016 · line 15 (the curve_fit() call), there is an additional right paranthesis at the end of the line xdata is a python list, so this won't work once you try to multiply it with a parameter in func, i. curve_fit(eq_m, x, y,maxfev=50000) lamb , mu, sigm Jun 2, 2023 · I am trying to curve fit a multivariable model with 2 parameters without any luck. Your example works with float64. curve_fit function. curve_fit(linear, xp Apr 19, 2017 · that I know my dataset follows, I am trying to fit my data to eq_m so that I can use the fitted parameters to predict new data. First, I generated a random exponential decay graph, where A, w, T2 are randomly generated u Jun 4, 2023 · The curve_fit method provides an option to define the initial function parameters. The documentation I found focuses mostly on a single variable. optimize. I've tried passing the DataFrame to scipy. An all-too-common question, I'm afraid, but: Since you plot the data on a log-log plot, are you also fitting with the log (y) and log (x)? Since your y data varies by 5 or 6 orders of magnitude, if you are not fitting in log-space, only those 3 or 4 data points with the highest y value will matter. curve_fit is checking to see if you have at least as many data points as fitted parameters by comparing the length of func's parameter list (a,b,c) as 3 with the length of the dependent variable (z,v) as 2. Fitting the logs with linear regression effectively weights the data at low x values more than the data at higher x values. Jun 26, 2015 · I have to use the curve_fit numpy function over a large set of data (5 000 000). import numpy as np from scipy. How c Sep 3, 2021 · I am using 3 different packages (Scipy-minimize, Scipy-curve_fit and lmfit - Model) for this but I find different parameter results in each one. Apr 25, 2023 · I am trying to fit a function with two independent variables a and k to an exponential curve using scipy's curve_fit. Oct 11, 2013 · I've been trying to fit a function to some data for a while using scipy. Oct 26, 2016 · def model (A, x, mu, sigma): return A*exp (- ( (x-mu)**2)/ (2*sigma**2)) from scipy. It takes a string, counts the occurence of the different letters and plots the According to the documentation, the argument sigma can be used to set the weights of the data points in the fit. Nov 16, 2023 · Note: This is a follow-up of this question User Nick ODell gave a great answer to the problem of curve_fit not fitting well to a normal curve --- as it turns out, the objective function with respec May 8, 2015 · I'm trying to use scipy. curve_fit but i'm having real difficulty. This blog post will delve into the fundamental concepts, usage methods The actual curve fitting is then performed with the opt. fmin_slsqp(), which allows do perform constrained optimizations. https://docs. e. I've tried different initial guesses. Jun 5, 2019 · I am trying to fit my data using curve_fit library of python. datetime", I can't fit it using a Gaussian function. curve_fit to do an optimization problem in Python. The default initial guess for curve_fit is all 1s, which is a very bad guess for your problem--warnings are generated, overflow occurs, and the returned pcov is an array of all inf values (did you check it?). array(xdata) If you fix these two issues, the fit should work. This works well for strong peaks, but it is more difficult with weaker peaks. In some cases you'll find they are quite different. This is far to the data where the plateau is almost reached at x=0. github. Actually that function for scipy. curve_fit to approximate peaks in my data with Gaussian functions. I would like to fit my data to a second order equation. Sep 16, 2018 · In addition to the very fine answers from Welcome to Stack Overflow that "there is no easy, universal approach and James Phillips that "differential evolution often helps find good starting points (or even good solutions!) if somewhat slower than curve_fit() ", allow me to give a separate answer that you may find helpful. My fitting function is a power law. optimize imp I want to fit a data with sum of exponentials. Sep 28, 2012 · I have a set of points which approximate a 2D curve. So curve_fit by definition cannot produce a solution you'll like unless you move the initial estimate closer to reality; or you use and carefully tune a global solver. Of course the found approximates a=74. 9 ; b=728 ; c=-0. pyplot as plt import numpy as np import scipy as sp from scipy. # encoding: utf-8 from Aug 1, 2016 · 2 Since curve_fit() uses a least squares approach, you might want to look at scipy. 10. I am trying to use sigmoid function provided that 'y' is given and 'x' need to be found. curve_fit (function, dataBincenters, dataCounts) never satisfy this condition. Jul 25, 2019 · If you had printed out the full fit report from lmfit (or properly untangled to components of the covariance matrix from curve_fit) you would see that the parameters a and b are 100% correlated. warn('Covariance of the parameters could not be Dec 27, 2019 · I had a quick question regarding global fitting using scipy. I would like to use Python with numpy and scipy to find a cubic Bézier path which approximately fits the points, where I specify the exact coord Dec 20, 2017 · An alternative would be an outer minimize_scalar loop with a manual curve-fit-like (manual because it's not that nice to fix params with curve_fit's API) inner-calculation where offset get's fixed. I had the same problem fitting a function that took 15 parameters in total and I had only 13 data points. 545 could be used as very good initial estimate for an usual iterative method of regression. cos(b*t) v = 0 x = 0. Currently I'm working on a 1st o Mar 29, 2023 · Many scipy functions use args to pass extra values to the function. polyfit. pyplot as plt from scipy import optimize import numpy as np def f(t,a,b): return a*np. Jul 12, 2022 · I am trying to fit a curve to the data that I have. curve_fit function in python. Oct 4, 2020 · can anyone help me struggle with fitting issue from curve. But I obtained a result like a linear equation. Feb 10, 2017 · I'm trying to fit a sine wave curve this data distribution, but for some reason, the fit is incorrect: import matplotlib. Yes, both z and v have more than three data points, but the length of (z,v) is two. optimize to fit experimental data and got: optimizeWarning: Covariance of the parameters could not be estimated warnings. 1, curve_fit works with float64 but not float32 (it's a bug, not a feature). I currently want to fit data with errors in x and y and im using the scipy. In taking account of a convenient shift on the x-axis the fitting becommes good. These "describe" 1-sigma errors when the argument absolute_sigma=True. To avoid this problem (and to speed up the computations), scipy. my objective function is a polynomial function: def objective(x, a, b, c): return a * x + b * x**2 + c I used curve_fit from scipy. The following MCVE explains my problem: MCVE python snippet from scipy. Is there something wrong with the format or the layout that's causing this issue? Or is a logarithmic issue since my y-values are log for the large values? Jun 30, 2020 · In principle I want to fit this function (a convolution of a gaussian and exponential) like this: from scipy. fit tries to fit the parameters of a normal distribution based on the data. I really can't see any reason why this wouldn't work but it just produ Apr 25, 2018 · Allow me to recommend lmfit (https://lmfit. curve_fit has this p0 parameter as we know. exp(-t*ta Dec 18, 2024 · Note that least squares is not the only way to fit a curve and each method yields different errors because the optimization functions are differently curved in parameter space. If you don't have that, what do you mean by "curve-fitting"? Mar 22, 2023 · A curve needs to be caliberated and extrapolated for y decreasing from 1 to 0 by using curve_fit in python. time(), for example 1663847528. With lmfit, your fit problem would look like (I changed a few variable names for clarity): import numpy as np Dec 19, 2021 · I have the code below, my problem is in the format "datetime. Aug 1, 2016 · I'd like to be able to perform fits that allows me to fit an arbitrary curve function to data, and allows me to set arbitrary bounds on parameters, for example I want to fit function: f(x) = a1(x Feb 1, 2023 · Curve fitting with three unknowns Python Asked 2 years, 5 months ago Modified 2 years, 5 months ago Viewed 414 times Jul 8, 2018 · I am having trouble in understanding the optimize. The y is approximated to Mar 27, 2020 · 1 I'm trying to write a script with python/numpy/scipy for data manipulation, fitting and plotting of angle dependent magnetoresistance measurements. curve_fit but I have real difficulty. Jul 7, 2017 · I'm trying to perform what are many iterations of Scipy's curve_fit at once in order to avoid loops and therefore increase speed. Apr 6, 2017 · I have a hypothetical y function of x and trying to find/fit a lognormal distribution curve that would shape over the data best. Should I do this point by point through a loop or can I use the whole array in curve_fit? curve_fit is for local optimization of parameters to minimize the sum of squares of residuals. Sep 22, 2022 · To determine trends over time, I use scipy curve_fit with X values from time. scipy. Doing a linear interpolation sometimes creates erroneous results, Here's how I generate my data and the tried fit: import matplotlib. 7147126 (1. But I don't know exactly what should be the second value in the plot command? First we have Dec 14, 2024 · However, sometimes when Fit Curve is pressed, the curve fit flatlines past 10 degrees. curve_fit and probably has something to do with recursion. The outputs that we get from the curve_fit function are stored in param and param_cov which represent an array with our fit parameters and a 2D array containing the approximate covariance matrix. optimize curve_fit in Python inside a for loop throughout the files with the data points. The problem is the number of the exponentials is not constant. optimize import curve_fit popt, pcov = curve_fit(f, x_data, y_data) but I am kinda stuck, as I am not even sure on how to call the fitted values (assuming this would work), given that f (x_data) will be bigger than x_data. Sep 4, 2021 · 0 curve_fit (like many iterative fitting and optimization methods) performs best when it is given a reasonable starting point. com Jul 8, 2025 · So given a dataset comprising of a group of points, Curve Fitting helps to find the best fit representing the Data. The curve_fit optimization just spits out wha Mar 31, 2015 · the problem is in optimize. optimize` library. Since I would like to test different values of the constant, I would like to avoid wri I am a beginner with both Python and all its libs. Jan 23, 2025 · In the realm of data analysis and scientific computing, fitting curves to data points is a crucial task. I have experimental data, x and y, and I have uncertainty on both of them. least_squares documents this; curve_fit doesn't, but talks about passing the task on to least_squares. For example, consider the following function: import numpy as np def fmodel(x, a, Jan 12, 2023 · I am trying to use scipy. 6 billion). curve_fit(func, x, y) will return a numpy array containing two arrays: the first will contain values for a and b that best fit your data, and the second will be the covariance of the optimal fit parameters. curve_fit or lmfit to calculate the confidence intervals and prediction intervals using the delta method: Oct 13, 2017 · It seems like it only fits the first parameter. The first describes the two-dimensional surface with variables X,Y and parameters P; lambda1 (X, Y, P). Here is my raw data: https://pasteb Apr 19, 2021 · I'm trying to fit a function using SciPy's optimize. fit. Feb 28, 2017 · Suggestions for fitting noisy exponentials with scipy curve_fit? Asked 8 years, 6 months ago Modified 8 years, 6 months ago Viewed 3k times Sep 13, 2023 · I have two variables, and I am trying to use curve_fit in scipy optimize to fit the data. curve_fit. Mar 4, 2022 · But because I used SciPy's optimization curve_fit, which finds the curve with the lowest square difference, it's going to look like the red curve in the image. Thus the cause of the trouble is the equation model which isn't good. . I would like the output to be a dataframe with the optimal values fitting the da So there's 36e6 separate curve fits with independent fit parameters that you want to do, or are the parameters consistent across the 36e6 instances? If the former, I think you're stuck with a for loop, though you could parallelize it, and if the latter you can simply reshape. Say you want linear regression, then you use: def linear(x, a, b): return a*x + b fit_params, _ = scipy. std (d_spacing_2) f Nov 3, 2020 · The model is non-linear with respect to the independent variable and all the parameters. I have defined the function and tried to calculate it like this: print(np. Apparently using curve_fit should do the trick, although I am not really understanding how I should use it. Jan 21, 2025 · curve_fit() fits a custom function to data by adjusting its parameters to minimize the difference between the function’s predictions and the actual data points, ensuring the best possible match. To fit the model, I use scipy. def func(t, a, taus): # plus more exponential functions return sum(a*np. Aug 23, 2018 · If I use numpy. curve_fit () allows you to specify your best guesses for the parameters with the p0 keyword argument. Here is my code: import numpy Apr 18, 2021 · For my bachelor's thesis I need to fit a Generalized Maxwell Function. Obviously, the integral of the resulting function should always be equal to 1, but the results of simple scipy. While I would want the red curve to match up with the crests and troughs of the blue curve. curve_fit to some scattered data, but I need the area under the fitted curve to be the same as that calculated based on the scattered data, and a The usual method of fitting (such as in Python) involves an iterative process starting from "guessed" values of the parameters which must be not too far from the unknown exact values. DataFrame with with multiple columns and I would like to apply a curve_fit function to each of them. So you should pass the parameter values you used for your plot of the Apr 28, 2021 · I am trying to fit data points with an equation using curve_fit, with two variable arguments and one constant. I have some Sep 11, 2016 · Here is a link to some Jupyter Notebooks and Python scripts I wrote that show how to use the output of the optimum parameters and the covariance matrix from scipy. odr package to get my results. Aug 13, 2024 · 0 My goal is to achieve a two dimensional curve fit using scipy curve_fit function (I'm a bit lazy and just wanted to apply my typical 1D curve fitting to a 2D surface). Seems like an easy thing to do but whenever I fit the curve, the optimization doesn't seem to work. polyfit (x, y, 1, cov=True) and scipy. Dec 2, 2019 · Okay, this is exactly what I want, the slope :) , I have a large data set as a numpy array 38X240X240, I was using just one point as my si array. curve_fit using curve_fit(func, table, table. I want to tell whether the fit is good or not. pyplot a Apr 13, 2023 · I am fitting a function to data in Python using lmfit. polyfit and polyfit1d. Jul 26, 2025 · The fitted curve ( in red on the figures above ) is quite indistinguishable from the curve obtained by Reinderien. Lets How to plot error bars in python curve fit? Asked 5 years, 2 months ago Modified 5 years, 2 months ago Viewed 7k times Oct 13, 2014 · coeff, var_matrix = curve_fit(sin_fit, t, data, p0=p0) I guess either there is something obvious wrong, which I am missing at the moment, or I cannot use the curve fit from scipy for this problem. What is the best way to solve this Jan 29, 2025 · I'm trying to fit my thermal conductivity into the Debye-Callaway equation. curve_fit (lambda: x, a, b: a*x+b, x, y) on the same set of data points, I get nearly the same coefficients a and b. What I essentially want is a curve fit that looks very similar to the blue line but with a smoother change in gradient at points 1 and 2 (meaning I don't require the line to pass through these points). Feb 5, 2014 · I intend to fit a 2D Gaussian function to images showing a laser beam to get its parameters like FWHM and position. io/lmfit-py) which provides a higher level interface to curve fitting that is easier to use, better at avoiding bad behavior, and has lots of useful features unavailable with curve_fit(). curve_fit but as far as I can tell, this isn't what I should be using because this uses a predefined function which in my case I don't have. So I'm attaching a code with Aug 16, 2022 · python curve-fitting model-fitting goodness-of-fit asked Aug 16, 2022 at 8:55 Kanan Yagublu 119 1 3 11 Mar 31, 2023 · Your equation model is on the form y (x)=a* (1-Erf (b*x) with parameters a and b. It will work for some values but then not work when put on those values again. Nov 18, 2022 · I have a 2D array and I am trying to fit a curve on the data. First dimension is the number of fittings to perform, second dimension is the Mar 7, 2018 · Scipy curve_fit allows for passing the parameter sigma, which is designed to be the standard deviation for weighting the fit. 62889555 -0. However, one of my parameters is coming back negative. Aug 31, 2018 · scipy. Im just wondering about the correct use of errors sx and sy. The problem is that the model function is within the class and needs to access the variables and members of the class to compute the data. I am using curve_fit function and was able to fit normal distributio Dec 19, 2017 · poptI, pcovI = curve_fit(Imaginary, x_interpolate, y_interpolate, pI, bounds=bounds_I) In some situations I want to keep the parameter f_peak fixed during the fitting process. I really can't see any reason why this wouldn't work. curve_fit are roughly half of the values from numpy. And indeed in the example above mean is approximately 5 and std is approximately 2. Is there any way I can improve the quality of the fit? Here Aug 7, 2015 · I have a pandas. without that function/class as a reference, not much help to provide. Consider this example (which is actually my data): Most humans will agree in that the fit in the Jan 17, 2022 · I try to use the explanation (first answer) from this topic, to create an lsq fit for a 2D function with 6 parameters, which finds the optimized parameters from the data (an image, so a 2D array). Python provides a powerful tool for this purpose - `curve_fit` from the `scipy. The function goes as follows: I get the data (x,y) from a . 29865196] This demonstrates that there is severe locality in the cost function (guided optimum at 0, p0 optimum at 500). Scipy is the scientific computing module of Python providing in-built functions on a lot of well-known Mathematical functions. import numpy as np import datetime as datetime import matplotlib. `curve_fit` allows us to find the optimal parameters of a given function that best fit a set of observed data points. This implies that y (0)=a/2 that is half the heigh of the plateau. Check this tutorial on how to use it. csv file and use it to curve_fit. Jan 19, 2017 · I don't understand curve_fit isn't able to estimate the covariance of the parameter, thus raising the OptimizeWarning below. So basically I've created a 2D array. I then changed the equation slightly and it was fi May 14, 2013 · 25 I'm trying to fit the distribution of some experimental values with a custom probability density function. Although I can capture the pattern of the data the real fit is rather poor. However this eq_m is non linear hence I used scipy's curve_fit to get the lambda, mu, sigma parameter values, using the following snippet: opt_parms, parm_cov = o. Jan 14, 2021 · I am using curve_fit to fit a curve to some set of data points (x,y) in the 2D space. Here's an example for a linear fit with the data you provided. But I have managed to make a small program that works as intended. I begin with two lambda functions. It Jun 11, 2017 · norm. This is very similar to this problem, which was solved. org/doc/scipy Jan 14, 2020 · Please provide a more complete script for your fit, with results. But the values of the covariance matrix of scipy. Python's curve_fit calculates the best-fit parameters for a function with a single independent variable, but is there a way, using curve_fit or something else, to fit for a function with multiple Dec 18, 2019 · I have come across a problem when playing with the parameters of the curve_fit from scipy. loc[:, 'Z_real']) but for some reason each func instance is passed the whole datatable as its first argument rather than the Series for each row. See full list on pythonguides. Choosing the initial height and position of the bell curve to the y and x coordinates of the "highest" point in the series works very well on my data. stats as sp from scipy. So here is an example. However, I think fixing a Jun 30, 2017 · Add the noise back, and compare the results computed with the logs to the results produced by curve_fit. It seems to me that I can only get ~ 8 digits of accuracy when I desire ~ 15 digits. Oct 29, 2013 · The blue curve indicates the data entered (in this case 4 points) with the green being a curve fit using np. min(x Jan 12, 2018 · The curve is: import numpy as np import scipy. From my understanding, the only difference in setting up the script between local fitting versus global fitting, is the Oct 8, 2020 · Python curve_fit: optimal paramaters not found Asked 4 years, 5 months ago Modified 4 years, 5 months ago Viewed 1k times May 8, 2019 · I tried reading about scipy. Feb 6, 2016 · I use the Pandas Series so that different functions can use different combinations of columns. It must take the independent variable as the first argument and the parameters to fit as separate remaining arguments. However, the Jun 17, 2022 · I would like to use the uncertainty package in python to propagate errors in a Gaussian fitting. scipy. curve_fit for this, and it needs me to pass in a model function. For each file, I get the best fitting parameters (A,B,C) and the model fits great to all the files. curve_fit is the model you want to fit. I can't understand why. optimize import curve_fit Jul 8, 2013 · I am having issues with the numerical accuracy of scipy. Jan 20, 2018 · 3 I am using scipy. Dec 25, 2013 · The default curve_fit method needs you to have fewer parameters for the fitted function fitFunc than data points. Jul 16, 2021 · I made a random graph, and tried to use SciPy curve_fit to fit the best curve to the plot, but it fails. So far I tried to understand how to define a 2D Gaussian function in Python and h Mar 15, 2020 · If you have that, curve-fitting can help: you write that function (which probably depends on a few Parameters) to model the data in python and find the best values for the Parameters so that the model matches your data. xfmyouq 1oc ved0k drfdtc jcrtn n6g acri1ual g7maefyv 7y3pe hhoyv5l