From 9dabd32e30a01c4bd18a15fd266b552b8395cd55 Mon Sep 17 00:00:00 2001 From: Max Zwiessele Date: Tue, 4 Jun 2013 15:57:19 +0100 Subject: [PATCH] scg optimizer enhancments and mrd demo fix --- GPy/examples/dimensionality_reduction.py | 1 - GPy/inference/SCG.py | 4 ++-- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index 24ee7aad..43e1bd78 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -284,7 +284,6 @@ def mrd_simulation(optimize=True, plot=True, plot_sim=True, **kw): from GPy.models import mrd from GPy import kern - from GPy.core.transformations import logexp_clipped reload(mrd); reload(kern) diff --git a/GPy/inference/SCG.py b/GPy/inference/SCG.py index d290bfe7..4318c197 100644 --- a/GPy/inference/SCG.py +++ b/GPy/inference/SCG.py @@ -52,7 +52,7 @@ def SCG(f, gradf, x, optargs=(), maxiters=500, max_f_eval=500, display=True, xto ftol = 1e-6 if gtol is None: gtol = 1e-5 - sigma0 = 1.0e-4 + sigma0 = 1.0e-8 fold = f(x, *optargs) # Initial function value. function_eval = 1 fnow = fold @@ -63,7 +63,7 @@ def SCG(f, gradf, x, optargs=(), maxiters=500, max_f_eval=500, display=True, xto success = True # Force calculation of directional derivs. nsuccess = 0 # nsuccess counts number of successes. beta = 1.0 # Initial scale parameter. - betamin = 1.0e-30 # Lower bound on scale. + betamin = 1.0e-15 # Lower bound on scale. betamax = 1.0e100 # Upper bound on scale. status = "Not converged"