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implemented default constraints

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via m.ensure_default_constraints()
This commit is contained in:
James Hensman 2012-12-06 11:46:34 -08:00
parent ac84f4f34c
commit 50029ca4a7
1 changed files with 14 additions and 0 deletions
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14
GPy/core/model.py
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@ -162,6 +162,20 @@ class model(parameterised):
else: else:
self.expand_param(initial_parameters) self.expand_param(initial_parameters)
def ensure_default_constraints(self,warn=False):
"""
Ensure that any variables which should clearly be positive have been constrained somehow.
"""
positive_strings = ['variance','lengthscale', 'precision']
for s in positive_strings:
for i in self.grep_param_names(s):
if not (i in self.all_constrained_indices()):
name = self.get_param_names()[i]
self.constrain_positive(name)
if warn:
print "Warning! constraining %s postive"%name
def optimize(self, optimizer=None, start=None, **kwargs): def optimize(self, optimizer=None, start=None, **kwargs):
""" """
Optimize the model using self.log_likelihood and self.log_likelihood_gradient, as well as self.priors. Optimize the model using self.log_likelihood and self.log_likelihood_gradient, as well as self.priors.