pyerrors.roots

#!/usr/bin/env python
# coding: utf-8

import scipy.optimize
from autograd import jacobian
from .obs import derived_observable, pseudo_Obs


def find_root(d, func, guess=1.0, **kwargs):
    """Finds the root of the function func(x, d) where d is an Obs.

    Parameters
    -----------------
    d -- Obs passed to the function.
    func -- Function to be minimized. Any numpy functions have to use the autograd.numpy wrapper
    guess -- Initial guess for the minimization.
    """
    root = scipy.optimize.fsolve(func, guess, d.value)

    # Error propagation as detailed in arXiv:1809.01289
    dx = jacobian(func)(root[0], d.value)
    da = jacobian(lambda u, v: func(v, u))(d.value, root[0])
    deriv = - da / dx

    return derived_observable(lambda x, **kwargs: x[0], [pseudo_Obs(root, 0.0, d.names[0], d.shape[d.names[0]]), d], man_grad=[0, deriv])

def find_root(d, func, guess=1.0, **kwargs):
    """Finds the root of the function func(x, d) where d is an Obs.

    Parameters
    -----------------
    d -- Obs passed to the function.
    func -- Function to be minimized. Any numpy functions have to use the autograd.numpy wrapper
    guess -- Initial guess for the minimization.
    """
    root = scipy.optimize.fsolve(func, guess, d.value)

    # Error propagation as detailed in arXiv:1809.01289
    dx = jacobian(func)(root[0], d.value)
    da = jacobian(lambda u, v: func(v, u))(d.value, root[0])
    deriv = - da / dx

    return derived_observable(lambda x, **kwargs: x[0], [pseudo_Obs(root, 0.0, d.names[0], d.shape[d.names[0]]), d], man_grad=[0, deriv])