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Module « scipy.optimize »

Fonction bisect - module scipy.optimize

Signature de la fonction bisect

def bisect(f, a, b, args=(), xtol=2e-12, rtol=np.float64(8.881784197001252e-16), maxiter=100, full_output=False, disp=True) 

Description

help(scipy.optimize.bisect)

Find root of a function within an interval using bisection.

Basic bisection routine to find a root of the function `f` between the
arguments `a` and `b`. `f(a)` and `f(b)` cannot have the same signs.
Slow but sure.

Parameters
----------
f : function
    Python function returning a number.  `f` must be continuous, and
    f(a) and f(b) must have opposite signs.
a : scalar
    One end of the bracketing interval [a,b].
b : scalar
    The other end of the bracketing interval [a,b].
xtol : number, optional
    The computed root ``x0`` will satisfy ``np.allclose(x, x0,
    atol=xtol, rtol=rtol)``, where ``x`` is the exact root. The
    parameter must be positive.
rtol : number, optional
    The computed root ``x0`` will satisfy ``np.allclose(x, x0,
    atol=xtol, rtol=rtol)``, where ``x`` is the exact root. The
    parameter cannot be smaller than its default value of
    ``4*np.finfo(float).eps``.
maxiter : int, optional
    If convergence is not achieved in `maxiter` iterations, an error is
    raised. Must be >= 0.
args : tuple, optional
    Containing extra arguments for the function `f`.
    `f` is called by ``apply(f, (x)+args)``.
full_output : bool, optional
    If `full_output` is False, the root is returned. If `full_output` is
    True, the return value is ``(x, r)``, where x is the root, and r is
    a `RootResults` object.
disp : bool, optional
    If True, raise RuntimeError if the algorithm didn't converge.
    Otherwise, the convergence status is recorded in a `RootResults`
    return object.

Returns
-------
root : float
    Root of `f` between `a` and `b`.
r : `RootResults` (present if ``full_output = True``)
    Object containing information about the convergence. In particular,
    ``r.converged`` is True if the routine converged.

Examples
--------

>>> def f(x):
...     return (x**2 - 1)

>>> from scipy import optimize

>>> root = optimize.bisect(f, 0, 2)
>>> root
1.0

>>> root = optimize.bisect(f, -2, 0)
>>> root
-1.0

See Also
--------
brentq, brenth, bisect, newton
fixed_point : scalar fixed-point finder
fsolve : n-dimensional root-finding

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