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scg optimizer enhancments and mrd demo fix

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Max Zwiessele 2013-06-04 15:57:19 +01:00
parent 803b7d3c88
commit 9dabd32e30
2 changed files with 2 additions and 3 deletions
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1
GPy/examples/dimensionality_reduction.py
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@ -284,7 +284,6 @@ def mrd_simulation(optimize=True, plot=True, plot_sim=True, **kw):
from GPy.models import mrd from GPy.models import mrd
from GPy import kern from GPy import kern
from GPy.core.transformations import logexp_clipped
reload(mrd); reload(kern) reload(mrd); reload(kern)

4
GPy/inference/SCG.py
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@ -52,7 +52,7 @@ def SCG(f, gradf, x, optargs=(), maxiters=500, max_f_eval=500, display=True, xto
ftol = 1e-6 ftol = 1e-6
if gtol is None: if gtol is None:
gtol = 1e-5 gtol = 1e-5
sigma0 = 1.0e-4 sigma0 = 1.0e-8
fold = f(x, *optargs) # Initial function value. fold = f(x, *optargs) # Initial function value.
function_eval = 1 function_eval = 1
fnow = fold 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. success = True # Force calculation of directional derivs.
nsuccess = 0 # nsuccess counts number of successes. nsuccess = 0 # nsuccess counts number of successes.
beta = 1.0 # Initial scale parameter. 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. betamax = 1.0e100 # Upper bound on scale.
status = "Not converged" status = "Not converged"