Least Square Method, Curve Fitting, Python, Residual, Data.
np.exp(-b * x) + c xdata1 = np.linspace(0, 4, 50) y = func(xdata1, 2.5, 1.3, 0.5) rng = np.random.default_rng() # random number generator y_noise = 0.2 * rng.normal(size=xdata1.size) ydata1 = y + y_noise popt, pcov = curve_fit(func, xdata1, ydata1) plt.plot(xdata1, ydata1, 'b-', label='data')