def calibrate( self, cpus=1, maxiter=100, lambdax=0.001, minchange=1.0e-16, minlambdax=1.0e-6, verbose=False,
workdir=None, reuse_dirs=False, h=1.e-6):
""" Calibrate MATK model using Levenberg-Marquardt algorithm based on
original code written by Ernesto P. Adorio PhD.
(UPDEPP at Clarkfield, Pampanga)
:param cpus: Number of cpus to use
:type cpus: int
:param maxiter: Maximum number of iterations
:type maxiter: int
:param lambdax: Initial Marquardt lambda
:type lambdax: fl64
:param minchange: Minimum change between successive ChiSquares
:type minchange: fl64
:param minlambdax: Minimum lambda value
:type minlambdax: fl4
:param verbose: If True, additional information written to screen during calibration
:type verbose: bool
:returns: best fit parameters found by routine
:returns: best Sum of squares.
:returns: covariance matrix
"""
from minimizer import Minimizer
fitter = Minimizer(self)
fitter.calibrate(cpus=cpus,maxiter=maxiter,lambdax=lambdax,minchange=minchange,
minlambdax=minlambdax,verbose=verbose,workdir=workdir,reuse_dirs=reuse_dirs,h=h)
