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[setxy] always run the update after updating X and Y

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Max Zwiessele 2015-09-04 16:01:44 +01:00
parent d28483807d
commit a980c201a9
1 changed files with 9 additions and 10 deletions
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19
GPy/core/gp.py
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@ -114,7 +114,7 @@ class GP(Model):
self._predictive_variable = self.X self._predictive_variable = self.X
def set_XY(self, X=None, Y=None, trigger_update=True): def set_XY(self, X=None, Y=None):
""" """
Set the input / output data of the model Set the input / output data of the model
This is useful if we wish to change our existing data but maintain the same model This is useful if we wish to change our existing data but maintain the same model
@ -124,7 +124,7 @@ class GP(Model):
:param Y: output observations :param Y: output observations
:type Y: np.ndarray :type Y: np.ndarray
""" """
if trigger_update: self.update_model(False) self.update_model(False)
if Y is not None: if Y is not None:
if self.normalizer is not None: if self.normalizer is not None:
self.normalizer.scale_by(Y) self.normalizer.scale_by(Y)
@ -140,34 +140,33 @@ class GP(Model):
assert isinstance(X, type(self.X)), "The given X must have the same type as the X in the model!" assert isinstance(X, type(self.X)), "The given X must have the same type as the X in the model!"
self.unlink_parameter(self.X) self.unlink_parameter(self.X)
self.X = X self.X = X
self.link_parameters(self.X) self.link_parameter(self.X)
else: else:
self.unlink_parameter(self.X) self.unlink_parameter(self.X)
from ..core import Param from ..core import Param
self.X = Param('latent mean',X) self.X = Param('latent mean',X)
self.link_parameters(self.X) self.link_parameter(self.X)
else: else:
self.X = ObsAr(X) self.X = ObsAr(X)
if trigger_update: self.update_model(True) self.update_model(True)
if trigger_update: self._trigger_params_changed()
def set_X(self,X, trigger_update=True): def set_X(self,X):
""" """
Set the input data of the model Set the input data of the model
:param X: input observations :param X: input observations
:type X: np.ndarray :type X: np.ndarray
""" """
self.set_XY(X=X, trigger_update=trigger_update) self.set_XY(X=X)
def set_Y(self,Y, trigger_update=True): def set_Y(self,Y):
""" """
Set the output data of the model Set the output data of the model
:param X: output observations :param X: output observations
:type X: np.ndarray :type X: np.ndarray
""" """
self.set_XY(Y=Y, trigger_update=trigger_update) self.set_XY(Y=Y)
def parameters_changed(self): def parameters_changed(self):
""" """