scipy.optimize.bisect¶

scipy.optimize.bisect(f, a, b, args=(), xtol=2e-12, rtol=8.881784197001252e-16, maxiter=100, full_output=False, disp=True)[source]¶

Find root of a function within an interval using bisection.

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

Parameters

ffunction: Python function returning a number. f must be continuous, and f(a) and f(b) must have opposite signs.
ascalar: One end of the bracketing interval [a,b].
bscalar: The other end of the bracketing interval [a,b].
xtolnumber, 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 nonnegative.
rtolnumber, 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.
maxiterint, optional: if convergence is not achieved in maxiter iterations, an error is raised. Must be >= 0.
argstuple, optional: containing extra arguments for the function f. f is called by apply(f, (x)+args).
full_outputbool, 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.
dispbool, optional: If True, raise RuntimeError if the algorithm didn’t converge. Otherwise the convergence status is recorded in a RootResults return object.

Returns

x0float: Zero of f between a and b.
rRootResults (present if full_output = True): Object containing information about the convergence. In particular, r.converged is True if the routine converged.