From 5d8ddd35dbdd1d015e08b96a364e4e607a9f684f Mon Sep 17 00:00:00 2001 From: ErikOrm Date: Tue, 23 Jan 2024 09:57:46 +0100 Subject: [PATCH] Update gpgpytorch.py Fixed a type with respect to noise priors --- hypermapper/bo/models/gpgpytorch.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/hypermapper/bo/models/gpgpytorch.py b/hypermapper/bo/models/gpgpytorch.py index d2c7a53..2ad82bf 100644 --- a/hypermapper/bo/models/gpgpytorch.py +++ b/hypermapper/bo/models/gpgpytorch.py @@ -38,13 +38,13 @@ def __init__( else: # define noise priors if settings["noise_prior"]["name"] == "gamma": - alpha = float(settings["lengthscale_prior"]["parameters"][0]) - beta = float(settings["lengthscale_prior"]["parameters"][1]) + alpha = float(settings["noise_prior"]["parameters"][0]) + beta = float(settings["noise_prior"]["parameters"][1]) noise_prior = GammaPrior(concentration=alpha, rate=beta) elif settings["noise_prior"]["name"] == "lognormal": - mu = float(settings["lengthscale_prior"]["parameters"][0]) - sigma = float(settings["lengthscale_prior"]["parameters"][1]) + mu = float(settings["noise_prior"]["parameters"][0]) + sigma = float(settings["noise_prior"]["parameters"][1]) noise_prior = LogNormalPrior(loc=mu, scale=sigma) else: