JoostScheffer / Uncertainty-Propagator

An ipynb widget for propagating and evaluating the uncertainty when evaluating a function.

⚠️ This widget is still work in progress ⚠️

Error propagation widget

An ipynb widget for propagating and evaluating the uncertainty when evaluating a function.

Usages

First import the Propagator class from the propagator module.

from uncertainty_propagator import Propagator
import numpy as np

Basic usage

prop = Propagator("I_0 * cos(theta + theta_0) + I_background")

Then use either the widget or the set_variables method to set the variables and their uncertainties. Use the following methods to evaluate the function and the uncertainty at one or multiple points.

y = prop.evaluate_function()
y_err = prop.evaluate_error_function()

Usage with predefined variables

1.  from uncertainties import ufloat as uf
   
    x, a, b = sp.symbols("x a b")
    func = a * x + b
   
    prop = Propagator(func, {b: uf(20, 0), x: uf(10, 1)})

2.  prop = Propagator("I_0 * cos(theta + theta_0) + I_background")
   
    theta = np.linspace(0, 2 * np.pi, 100)
    theta_err = 0.01 * theta
   
    prop.set_variables({
        "I_0": (1.0, 0.1),
        "theta": (theta, theta_err),
        "theta_0": 0.0,
        "I_background": 0.0
    })