'''
Created on 13 Mar 2014
@author: maxz
'''
import unittest, itertools
#import cPickle as pickle
import pickle
import numpy as np
import tempfile
from GPy.examples.dimensionality_reduction import mrd_simulation
from GPy.core.parameterization.variational import NormalPosterior
from GPy.models.gp_regression import GPRegression
import GPy
from nose import SkipTest
[docs]def toy_model():
X = np.linspace(0,1,50)[:, None]
Y = np.sin(X)
m = GPRegression(X=X, Y=Y)
return m
[docs]class ListDictTestCase(unittest.TestCase):
[docs] def assertListDictEquals(self, d1, d2, msg=None):
#py3 fix
#for k,v in d1.iteritems():
for k,v in d1.items():
self.assertListEqual(list(v), list(d2[k]), msg)
[docs] def assertArrayListEquals(self, l1, l2):
for a1, a2 in zip(l1,l2):
np.testing.assert_array_equal(a1, a2)
[docs]class Test(ListDictTestCase):
@SkipTest
def test_load_pickle(self):
import os
m = GPy.load(os.path.join(os.path.abspath(os.path.split(__file__)[0]), 'pickle_test.pickle'))
self.assertTrue(m.checkgrad())
self.assertEqual(m.log_likelihood(), -4.7351019830022087)
[docs] def test_model(self):
par = toy_model()
pcopy = par.copy()
self.assertListEqual(par.param_array.tolist(), pcopy.param_array.tolist())
np.testing.assert_allclose(par.gradient_full, pcopy.gradient_full)
self.assertSequenceEqual(str(par), str(pcopy))
self.assertIsNot(par.param_array, pcopy.param_array)
self.assertIsNot(par.gradient_full, pcopy.gradient_full)
self.assertTrue(pcopy.checkgrad())
self.assert_(np.any(pcopy.gradient!=0.0))
with tempfile.TemporaryFile('w+b') as f:
par.pickle(f)
f.seek(0)
pcopy = pickle.load(f)
self.assertListEqual(par.param_array.tolist(), pcopy.param_array.tolist())
np.testing.assert_allclose(par.gradient_full, pcopy.gradient_full)
self.assertSequenceEqual(str(par), str(pcopy))
self.assert_(pcopy.checkgrad())
[docs] def test_modelrecreation(self):
par = toy_model()
pcopy = GPRegression(par.X.copy(), par.Y.copy(), kernel=par.kern.copy())
np.testing.assert_allclose(par.param_array, pcopy.param_array)
np.testing.assert_allclose(par.gradient_full, pcopy.gradient_full)
self.assertSequenceEqual(str(par), str(pcopy))
self.assertIsNot(par.param_array, pcopy.param_array)
self.assertIsNot(par.gradient_full, pcopy.gradient_full)
self.assertTrue(pcopy.checkgrad())
self.assert_(np.any(pcopy.gradient!=0.0))
np.testing.assert_allclose(pcopy.param_array, par.param_array, atol=1e-6)
par.randomize()
with tempfile.TemporaryFile('w+b') as f:
par.pickle(f)
f.seek(0)
pcopy = pickle.load(f)
np.testing.assert_allclose(par.param_array, pcopy.param_array)
np.testing.assert_allclose(par.gradient_full, pcopy.gradient_full, atol=1e-6)
self.assertSequenceEqual(str(par), str(pcopy))
self.assert_(pcopy.checkgrad())
[docs] def test_posterior(self):
X = np.random.randn(3,5)
Xv = np.random.rand(*X.shape)
par = NormalPosterior(X,Xv)
par.gradient = 10
pcopy = par.copy()
pcopy.gradient = 10
self.assertListEqual(par.param_array.tolist(), pcopy.param_array.tolist())
self.assertListEqual(par.gradient_full.tolist(), pcopy.gradient_full.tolist())
self.assertSequenceEqual(str(par), str(pcopy))
self.assertIsNot(par.param_array, pcopy.param_array)
self.assertIsNot(par.gradient_full, pcopy.gradient_full)
with tempfile.TemporaryFile('w+b') as f:
par.pickle(f)
f.seek(0)
pcopy = pickle.load(f)
self.assertListEqual(par.param_array.tolist(), pcopy.param_array.tolist())
pcopy.gradient = 10
np.testing.assert_allclose(par.gradient_full, pcopy.gradient_full)
np.testing.assert_allclose(pcopy.mean.gradient_full, 10)
self.assertSequenceEqual(str(par), str(pcopy))
[docs] def test_model_concat(self):
par = mrd_simulation(optimize=0, plot=0, plot_sim=0)
par.randomize()
pcopy = par.copy()
self.assertListEqual(par.param_array.tolist(), pcopy.param_array.tolist())
self.assertListEqual(par.gradient_full.tolist(), pcopy.gradient_full.tolist())
self.assertSequenceEqual(str(par), str(pcopy))
self.assertIsNot(par.param_array, pcopy.param_array)
self.assertIsNot(par.gradient_full, pcopy.gradient_full)
self.assertTrue(par.checkgrad())
self.assertTrue(pcopy.checkgrad())
self.assert_(np.any(pcopy.gradient!=0.0))
with tempfile.TemporaryFile('w+b') as f:
par.pickle(f)
f.seek(0)
pcopy = pickle.load(f)
self.assertListEqual(par.param_array.tolist(), pcopy.param_array.tolist())
np.testing.assert_allclose(par.gradient_full, pcopy.gradient_full)
self.assertSequenceEqual(str(par), str(pcopy))
self.assert_(pcopy.checkgrad())
def _callback(self, what, which):
what.count += 1
if __name__ == "__main__":
#import sys;sys.argv = ['', 'Test.test_parameter_index_operations']
unittest.main()