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better f_inv

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This commit is contained in:
Nicolò Fusi 2013-05-08 15:47:06 +02:00
parent 323545f2d1
commit b17cc60182
2 changed files with 25 additions and 10 deletions
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11
GPy/models/warped_GP.py
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@ -23,6 +23,7 @@ class warpedGP(GP):
self.warping_function = TanhWarpingFunction_d(warping_terms)
self.warping_params = (np.random.randn(self.warping_function.n_terms*3+1,) * 1)
Y = self._scale_data(Y)
self.has_uncertain_inputs = False
self.Y_untransformed = Y.copy()
self.predict_in_warped_space = False
@ -30,6 +31,14 @@ class warpedGP(GP):
GP.__init__(self, X, likelihood, kernel, normalize_X=normalize_X, Xslices=Xslices)
def _scale_data(self, Y):
self._Ymax = Y.max()
self._Ymin = Y.min()
return (Y-self._Ymin)/(self._Ymax-self._Ymin) - 0.5
def _unscale_data(self, Y):
return (Y + 0.5)*(self._Ymax - self._Ymin) + self._Ymin
def _set_params(self, x):
self.warping_params = x[:self.warping_function.num_parameters]
Y = self.transform_data()
@ -79,5 +88,5 @@ class warpedGP(GP):
if self.predict_in_warped_space:
mu = self.warping_function.f_inv(mu, self.warping_params)
var = self.warping_function.f_inv(var, self.warping_params)
mu = self._unscale_data(mu)
return mu, var