amep.functions.Fit

class amep.functions.Fit(g, **kwargs)

Bases: BaseFunction

Fitting a 1d function.

__init__(g, **kwargs)

General fit class that allows to fit a 1d user-defined function to data.

Parameters:

• g (function) – The function that will be fitted to the data

• **kwargs – Other keyword arguments are forwarded to the function g. These parameters will be kept constant in the fitting process.

Return type:

None.

Examples

>>> import amep
>>> import numpy as np
>>> x = np.linspace(-np.pi, np.pi, 100)
>>> y = (1+np.random.random((100,)))*np.sin(2*x)
>>> def f(x, amp=1, omega=1, phi=0):
...     return amp*np.sin(omega*x+phi)
>>> fit = amep.functions.Fit(f)
>>> fit.fit(x, y, p0=[1,2,3])
>>> print(fit.results)
{'amp': (-1.6707345639977673, 0.03611365715752075),
 'omega': (1.980453842406803, 0.018014280164672856),
 'phi': (3.0950628128156383, 0.03345686981008855)}

>>> fit = amep.functions.Fit(f, omega=2)
>>> fit.fit(x, y, p0=[1,2])
>>> print(fit.results)
{'amp': (1.6786964141227352, 0.03291999452138418),
 'phi': (0.07093556110237159, 0.03115340006227788)}

>>> fig, axs = amep.plot.new()
>>> axs.plot(x, y, label="data", ls="")
>>> axs.plot(x, fit.generate(x), marker="", label="fit")
>>> axs.legend()
>>> axs.set_xlabel(r"$x$")
>>> axs.set_ylabel(r"$\sin(2x)$")
>>> fig.savefig("./figures/functions/functions-Fit.png")

Methods

__init__(g, **kwargs)	General fit class that allows to fit a 1d user-defined function to data.
f(p, x)
fit(xdata, ydata[, p0, sigma, maxit, verbose])	Fits the function self.f to the given data by using ODR (orthogonal distance regression).
generate(x[, p])	Returns the y values for given x values.

Attributes

errors	Returns the fit errors for each parameter as an array.
keys
name
nparams
output
params	Returns an array of the optimal fit parameters.
results	Returns the dictionary of fit results including parameter names, parameter values, and fit errors.

property errors: ndarray

Returns the fit errors for each parameter as an array.

Returns:

Fit errors.

Return type:

np.ndarray

fit(xdata: ndarray, ydata: ndarray, p0: list | None = None, sigma: ndarray | None = None, maxit: int | None = None, verbose: bool = False) → None

Fits the function self.f to the given data by using ODR (orthogonal distance regression).

Parameters:

• xdata (np.ndarray) – x values.

• ydata (np.ndarray) – y values.

• p0 (list or None, optional) – List of initial values. The default is None.

• sigma (np.ndarray or None, optional) – Absolute error for each data point. The default is None.

• maxit (int, optional) – Maximum number of iterations. The default is 200.

• verbose (bool, optional) – If True, the main results are printed. The default is False.

Return type:

None.

generate(x: ndarray, p: list | None = None) → ndarray

Returns the y values for given x values.

Parameters:

• x (np.ndarray) – x values.

• p (list, optional) – List of parameters. The default is None.

Returns:

y – f(x)

Return type:

np.ndarray

property params: ndarray

Returns an array of the optimal fit parameters.

Returns:

Fit parameter values.

Return type:

np.ndarray

property results: dict

Returns the dictionary of fit results including parameter names, parameter values, and fit errors.

Returns:

Fit results.

Return type:

dict