Merge pull request #558 from SheffieldML/devel

Uniform prior fix for other domains

CHANGELOG.md

@@ -1,5 +1,31 @@
 # Changelog
 
+## v1.8.3 (2017-10-02)
+
+### Fix
+
+* Uniform prior instantiation. [mzwiessele]
+
+* Use paramz 0.8.5. [mzwiessele]
+
+### Other
+
+* Bump version: 1.8.2 → 1.8.3. [mzwiessele]
+
+
+## v1.8.2 (2017-10-02)
+
+### Fix
+
+* Uniform prior tests. [mzwiessele]
+
+* Uniform prior can be positive and negative, depending on lower and upper bound. [mzwiessele]
+
+### Other
+
+* Bump version: 1.8.1 → 1.8.2. [mzwiessele]
+
+
 ## v1.8.1 (2017-10-02)
 
 ### Fix

GPy/__version__.py

@@ -1 +1 @@
-__version__ = "1.8.1"
+__version__ = "1.8.3"

GPy/core/parameterization/priors.py

@@ -5,7 +5,7 @@
 import numpy as np
 from scipy.special import gammaln, digamma
 from ...util.linalg import pdinv
-from paramz.domains import _REAL, _POSITIVE
+from paramz.domains import _REAL, _POSITIVE, _NEGATIVE
 import warnings
 import weakref
 
@@ -92,7 +92,6 @@ class Gaussian(Prior):
 #         self.constant = -0.5 * np.log(2 * np.pi * self.sigma2)
 
 class Uniform(Prior):
-    domain = _REAL
     _instances = []
 
     def __new__(cls, lower=0, upper=1):  # Singleton:
@@ -101,13 +100,24 @@ class Uniform(Prior):
             for instance in cls._instances:
                 if instance().lower == lower and instance().upper == upper:
                     return instance()
-        o = super(Prior, cls).__new__(cls, lower, upper)
+        newfunc = super(Prior, cls).__new__
+        if newfunc is object.__new__:
+            o = newfunc(cls)  
+        else:
+            o = newfunc(cls, lower, upper)     
         cls._instances.append(weakref.ref(o))
         return cls._instances[-1]()
 
     def __init__(self, lower, upper):
         self.lower = float(lower)
         self.upper = float(upper)
+        assert self.lower < self.upper, "Lower needs to be strictly smaller than upper."
+        if self.lower >= 0:
+            self.domain = _POSITIVE
+        elif self.upper <= 0:
+            self.domain = _NEGATIVE
+        else:
+            self.domain = _REAL
 
     def __str__(self):
         return "[{:.2g}, {:.2g}]".format(self.lower, self.upper)

GPy/testing/prior_tests.py

@@ -83,6 +83,35 @@ class PriorTests(unittest.TestCase):
         # should raise an assertionerror.
         self.assertRaises(AssertionError, m.rbf.set_prior, gaussian)
 
+    def test_uniform(self):
+        xmin, xmax = 1, 2.5*np.pi
+        b, C, SNR = 1, 0, 0.1
+        X = np.linspace(xmin, xmax, 500)
+        y  = b*X + C + 1*np.sin(X)
+        y += 0.05*np.random.randn(len(X))
+        X, y = X[:, None], y[:, None]
+        m = GPy.models.SparseGPRegression(X, y)
+        uniform = GPy.priors.Uniform(0, 2)
+        m.rbf.set_prior(uniform)
+        m.randomize()
+        self.assertTrue(m.checkgrad())
+        
+        m.Z.set_prior(uniform)
+        m.randomize()
+        self.assertTrue(m.checkgrad())
+        
+        m.Z.unconstrain()
+        uniform = GPy.priors.Uniform(-1, 10)
+        m.Z.set_prior(uniform)
+        m.randomize()
+        self.assertTrue(m.checkgrad())
+
+        m.Z.constrain_negative()
+        uniform = GPy.priors.Uniform(-1, 0)
+        m.Z.set_prior(uniform)
+        m.randomize()
+        self.assertTrue(m.checkgrad())
+
     def test_set_gaussian_for_reals(self):
         xmin, xmax = 1, 2.5*np.pi
         b, C, SNR = 1, 0, 0.1

appveyor.yml

@@ -3,7 +3,7 @@ environment:
     secure: 8/ZjXFwtd1S7ixd7PJOpptupKKEDhm2da/q3unabJ00=
   COVERALLS_REPO_TOKEN:
     secure: d3Luic/ESkGaWnZrvWZTKrzO+xaVwJWaRCEP0F+K/9DQGPSRZsJ/Du5g3s4XF+tS
-  gpy_version: 1.8.1
+  gpy_version: 1.8.3
   matrix:
     - PYTHON_VERSION: 2.7
       MINICONDA: C:\Miniconda-x64

setup.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 1.8.1
+current_version = 1.8.3
 tag = True
 commit = True
 

setup.py

@@ -150,7 +150,7 @@ setup(name = 'GPy',
       py_modules = ['GPy.__init__'],
       test_suite = 'GPy.testing',
       setup_requires = ['numpy>=1.7'],
-      install_requires = ['numpy>=1.7', 'scipy>=0.16', 'six', 'paramz>=0.8.3'],
+      install_requires = ['numpy>=1.7', 'scipy>=0.16', 'six', 'paramz>=0.8.5'],
       extras_require = {'docs':['sphinx'],
                         'optional':['mpi4py',
                                     'ipython>=4.0.0',