root_scalar(method=’newton’)#

scipy.optimize.root_scalar(f,args=(),method=None,bracket=None,fprime=None,fprime2=None,x0=None,x1=None,xtol=None,rtol=None,maxiter=None,options=None)

See also

For documentation for the rest of the parameters, seescipy.optimize.root_scalar

Options:
——-
argstuple, optional

Extra arguments passed to the objective function and its derivative.

xtolfloat, optional

Tolerance (absolute) for termination.

rtolfloat, optional

Tolerance (relative) for termination.

maxiterint, optional

Maximum number of iterations.

x0float, required

Initial guess.

fprimebool or callable, optional

Iffprime is a boolean and is True,f is assumed to return thevalue of derivative along with the objective function.fprime can also be a callable returning the derivative off. Inthis case, it must accept the same arguments asf.

options: dict, optional

Specifies any method-specific options not covered above.