scipy.optimize.

# bisect#

scipy.optimize.bisect(f, a, b, args=(), xtol=2e-12, rtol=np.float64(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 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:
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 positive.

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:
rootfloat

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
```