### Navigation

- index
- modules |
- modules |
- next |
- previous |
- SciPy v0.9 Reference Guide (DRAFT) »
- Optimization and root finding (`scipy.optimize`) »

# scipy.optimize.bisect

`scipy.optimize.``bisect`(f, a, b, args=(), xtol=9.9999999999999998e-13, rtol=4.4408920985006262e-16, maxiter=100, full_output=False, disp=True)

  Find root of f in [a,b].

  Basic bisection routine to find a zero of the function f between the arguments a and b. f(a) and f(b) can not 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 : number One end of the bracketing interval [a,b]. b : number The other end of the bracketing interval [a,b]. xtol : number, optional The routine converges when a root is known to lie within xtol of the value return. Should be >= 0. The routine modifies this to take into account the relative precision of doubles. maxiter : number, optional if convergence is not achieved in maxiter iterations, and 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 : {True, bool} optional If True, raise RuntimeError if the algorithm didn’t converge.
  Returns : | x0 : float Zero 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.

  See also

  `fixed_point`
    scalar fixed-point finder fsolve – n-dimensional root-finding

### Navigation

- index
- modules |
- modules |
- next |
- previous |
- SciPy v0.9 Reference Guide (DRAFT) »
- Optimization and root finding (`scipy.optimize`) »