ess.sans.beam_center_finder.minimize(fun, x0, args=(), bounds=None, method='Nelder-Mead', tol=0.1)#

Minimize the supplied cost function using Scipy’s optimize.minimize. See the Scipy docs for more details.

  • fun – The cost function to minimize.

  • x0 – Initial guess.

  • args – Additional arguments passed to the cost function.

  • bounds – Bounds on the variables.

  • method (str, default: 'Nelder-Mead') – The minimization method to use.

  • tol (float, default: 0.1) – The tolerance for termination.


The result of the minimization.