Hi Python Community!
I am a bit new to Pyhton and need to do some curve fitting for S-curves. I have given data points for x and y and need to find a sigmoid function with parameters L, x0 and k that describes the data best, i.e. curve fitting. I found a code like this below:
import matplotlib.pyplot as plt import numpy as np from scipy.special import expit as logistic x = np.arange(-6, 6.1, 0.1) y = logistic(x) + np.random.normal(loc=0.0, scale=0.03, size=len(x)) fig, ax = plt.subplots(figsize=(15, 6)) _ = ax.plot(x, y) _ = ax.set_title('Generated s-curve data with noise test') from scipy.optimize import curve_fit L_estimate = y.max() x_0_estimate = np.median(x) k_estimate = 1.0 p_0 = [L_estimate, x_0_estimate, k_estimate] popt, pcov = curve_fit(logistic, x, y, p_0, method='dogbox')
However, when I test run it, it shows a TypeError:
TypeError: expit() takes from 1 to 2 positional arguments but 4 were given.
I do not really know what to do about that. And of course in the code so far it is using random data, but would insert my own data afterwards, if it runs smoothly.
Thanks for your help, maybe I am missing an important point.