From 98fef6d622aba8ef77ccbe1d5bb5689912424fe9 Mon Sep 17 00:00:00 2001
From: gehbiszumeis <16896724+gehbiszumeis@users.noreply.github.com>
Date: Mon, 8 Mar 2021 13:52:22 +0100
Subject: [PATCH] new: Added to_dict() method to Ornstein-Uhlenbeck (OU) kernel

---
 GPy/kern/src/stationary.py         | 18 +++++++++++++++++-
 GPy/testing/serialization_tests.py | 15 ++++++++-------
 2 files changed, 25 insertions(+), 8 deletions(-)

diff --git a/GPy/kern/src/stationary.py b/GPy/kern/src/stationary.py
index 888320a0..527bb9bb 100644
--- a/GPy/kern/src/stationary.py
+++ b/GPy/kern/src/stationary.py
@@ -412,7 +412,6 @@ class Exponential(Stationary):
 #        return (F, L, Qc, H, Pinf)
 
 
-
 class OU(Stationary):
     """
     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'):
         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):
         return self.variance * np.exp(-r)
 
diff --git a/GPy/testing/serialization_tests.py b/GPy/testing/serialization_tests.py
index d147d59c..93ec4b2d 100644
--- a/GPy/testing/serialization_tests.py
+++ b/GPy/testing/serialization_tests.py
@@ -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])
         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])
-        k10 = k1 + k1.copy() + k2 + k3 + k4 + k5 + k6
-        k11 = k1 * k2 * k2.copy() * k3 * k4 * k5
-        k12 = (k1 + k2) * (k3 + k4 + k5)
-        k13 = ((k1 + k2) * k3) + k4 + k5 * k7
-        k14 = ((k1 + k2) * k3) + k4 * k5 + k8
-        k15 = ((k1 * k2) * k3) + k4 * k5 + k8 + k9
+        k10 = GPy.kern.OU(2, variance=2.0, lengthscale=[2.0, 1.0], ARD=True, active_dims=[1, 0])
+        k11 = k1 + k1.copy() + k2 + k3 + k4 + k5 + k6
+        k12 = k1 * k2 * k2.copy() * k3 * k4 * k5
+        k13 = (k1 + k2) * (k3 + k4 + k5)
+        k14 = ((k1 + k2) * k3) + k4 + k5 * k7
+        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:
             kk_dict = kk.to_dict()