Package paramz :: Package optimization :: Module scg

Module scg

Scaled Conjuagte Gradients, originally in Matlab as part of the Netlab toolbox by I. Nabney, converted to python N. Lawrence and given a pythonic interface by James Hensman.

Edited by Max Zwiessele for efficiency and verbose optimization.

Functions

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SCG(f, gradf, x, optargs=(), maxiters=500, max_f_eval=inf, xtol=None, ftol=None, gtol=None)
Optimisation through Scaled Conjugate Gradients (SCG) source code

Variables

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__package__ = 'paramz.optimization'

Function Details

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SCG(f, gradf, x, optargs=`()`, maxiters=500, max_f_eval=inf, xtol=None, ftol=None, gtol=None)

source code

Optimisation through Scaled Conjugate Gradients (SCG)

f: the objective function gradf : the gradient function (should return a 1D np.ndarray) x : the initial condition

Returns x the optimal value for x flog : a list of all the objective values function_eval number of fn evaluations status: string describing convergence status

Module scg

SCG(f, gradf, x, optargs=(), maxiters=500, max_f_eval=inf, xtol=None, ftol=None, gtol=None)

SCG(f, gradf, x, optargs=`()`, maxiters=500, max_f_eval=inf, xtol=None, ftol=None, gtol=None)