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new: Added to_dict() method to Ornstein-Uhlenbeck (OU) kernel

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gehbiszumeis 2021-03-08 13:52:22 +01:00
parent 426ba1dc27
commit 98fef6d622
2 changed files with 25 additions and 8 deletions
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18
GPy/kern/src/stationary.py
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@ -412,7 +412,6 @@ class Exponential(Stationary):
# return (F, L, Qc, H, Pinf) # return (F, L, Qc, H, Pinf)
class OU(Stationary): class OU(Stationary):
""" """
OU kernel: OU kernel:
@ -426,6 +425,23 @@ class OU(Stationary):
def __init__(self, input_dim, variance=1., lengthscale=None, ARD=False, active_dims=None, name='OU'): def __init__(self, input_dim, variance=1., lengthscale=None, ARD=False, active_dims=None, name='OU'):
super(OU, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name) super(OU, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name)
def to_dict(self):
"""
Convert the object into a json serializable dictionary.
Note: It uses the private method _save_to_input_dict of the parent.
:return dict: json serializable dictionary containing the needed information to instantiate the object
"""
input_dict = super(OU, self)._save_to_input_dict()
input_dict["class"] = "GPy.kern.OU"
return input_dict
@staticmethod
def _build_from_input_dict(kernel_class, input_dict):
useGPU = input_dict.pop('useGPU', None)
return OU(**input_dict)
def K_of_r(self, r): def K_of_r(self, r):
return self.variance * np.exp(-r) return self.variance * np.exp(-r)

15
GPy/testing/serialization_tests.py
View file

@ -26,14 +26,15 @@ class Test(unittest.TestCase):
k7 = GPy.kern.Matern32(2, variance=1.0, lengthscale=[1.0,3.0], ARD=True, active_dims = [1,1]) k7 = GPy.kern.Matern32(2, variance=1.0, lengthscale=[1.0,3.0], ARD=True, active_dims = [1,1])
k8 = GPy.kern.Matern52(2, variance=2.0, lengthscale=[2.0,1.0], ARD=True, active_dims = [1,0]) k8 = GPy.kern.Matern52(2, variance=2.0, lengthscale=[2.0,1.0], ARD=True, active_dims = [1,0])
k9 = GPy.kern.ExpQuad(2, variance=3.0, lengthscale=[1.0,2.0], ARD=True, active_dims = [0,1]) k9 = GPy.kern.ExpQuad(2, variance=3.0, lengthscale=[1.0,2.0], ARD=True, active_dims = [0,1])
k10 = k1 + k1.copy() + k2 + k3 + k4 + k5 + k6 k10 = GPy.kern.OU(2, variance=2.0, lengthscale=[2.0, 1.0], ARD=True, active_dims=[1, 0])
k11 = k1 * k2 * k2.copy() * k3 * k4 * k5 k11 = k1 + k1.copy() + k2 + k3 + k4 + k5 + k6
k12 = (k1 + k2) * (k3 + k4 + k5) k12 = k1 * k2 * k2.copy() * k3 * k4 * k5
k13 = ((k1 + k2) * k3) + k4 + k5 * k7 k13 = (k1 + k2) * (k3 + k4 + k5)
k14 = ((k1 + k2) * k3) + k4 * k5 + k8 k14 = ((k1 + k2) * k3) + k4 + k5 * k7
k15 = ((k1 * k2) * k3) + k4 * k5 + k8 + k9 k15 = ((k1 + k2) * k3) + k4 * k5 + k8 * k10
k16 = ((k1 * k2) * k3) + k4 * k5 + k8 + k9
k_list = [k1,k2,k3,k4,k5,k6,k7,k8,k9,k10,k11,k12,k13,k14,k15] k_list = [k1,k2,k3,k4,k5,k6,k7,k8,k9,k10,k11,k12,k13,k14,k15,k16]
for kk in k_list: for kk in k_list:
kk_dict = kk.to_dict() kk_dict = kk.to_dict()