Added test generator (not quite finished yet)

This commit is contained in:
Alan Saul 2013-03-11 17:05:18 +00:00
parent 9b4cb78fdb
commit c39af496a6
3 changed files with 58 additions and 26 deletions

View file

@ -194,7 +194,7 @@ def multiple_optima(gene_number=937,resolution=80, model_restarts=10, seed=10000
# Remove the mean (no bias kernel to ensure signal/noise is in RBF/white)
data['Y'] = data['Y'] - np.mean(data['Y'])
lls = GPy.examples.regression.contour_data(data, length_scales, log_SNRs, GPy.kern.rbf)
lls = GPy.examples.regression._contour_data(data, length_scales, log_SNRs, GPy.kern.rbf)
pb.contour(length_scales, log_SNRs, np.exp(lls), 20)
ax = pb.gca()
pb.xlabel('length scale')
@ -229,7 +229,7 @@ def multiple_optima(gene_number=937,resolution=80, model_restarts=10, seed=10000
ax.set_ylim(ylim)
return (models, lls)
def contour_data(data, length_scales, log_SNRs, signal_kernel_call=GPy.kern.rbf):
def _contour_data(data, length_scales, log_SNRs, signal_kernel_call=GPy.kern.rbf):
"""Evaluate the GP objective function for a given data set for a range of signal to noise ratios and a range of lengthscales.
:data_set: A data set from the utils.datasets director.

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@ -6,14 +6,14 @@
Code of Tutorials
"""
import pylab as pb
pb.ion()
import numpy as np
import GPy
def tuto_GP_regression():
"""The detailed explanations of the commands used in this file can be found in the tutorial section"""
import pylab as pb
pb.ion()
import numpy as np
import GPy
X = np.random.uniform(-3.,3.,(20,1))
Y = np.sin(X) + np.random.randn(20,1)*0.05
@ -39,11 +39,6 @@ def tuto_GP_regression():
# 2-dimensional example #
###########################
import pylab as pb
pb.ion()
import numpy as np
import GPy
# sample inputs and outputs
X = np.random.uniform(-3.,3.,(50,2))
Y = np.sin(X[:,0:1]) * np.sin(X[:,1:2])+np.random.randn(50,1)*0.05
@ -67,9 +62,6 @@ def tuto_GP_regression():
def tuto_kernel_overview():
"""The detailed explanations of the commands used in this file can be found in the tutorial section"""
import pylab as pb
import numpy as np
import GPy
pb.ion()
ker1 = GPy.kern.rbf(1) # Equivalent to ker1 = GPy.kern.rbf(D=1, variance=1., lengthscale=1.)

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@ -4,23 +4,63 @@
import unittest
import numpy as np
import GPy
import inspect
import pkgutil
import os
class ExamplesTests(unittest.TestCase):
def test_check_model_returned(self):
pass
def _checkgrad(self, model):
self.assertTrue(model.checkgrad())
def test_model_checkgrads(self):
pass
def _model_instance(self, model):
self.assertTrue(isinstance(model, GPy.models))
def test_all_examples(self):
examples_module = __import__("GPy").examples
#Load models
"""
def model_instance_generator(model):
def check_model_returned(self):
self._model_instance(model)
return check_model_returned
#Loop through models
#for model in models:
#self.assertTrue(m.checkgrad())
def checkgrads_generator(model):
def model_checkgrads(self):
self._checkgrad(model)
return model_checkgrads
"""
def model_checkgrads(model):
assert model.checkgrad() is True
def model_instance(model):
assert model.checkgrad() is True
def test_models():
examples_path = os.path.dirname(GPy.examples.__file__)
#Load modules
for loader, module_name, is_pkg in pkgutil.iter_modules([examples_path]):
#Load examples
module_examples = loader.find_module(module_name).load_module(module_name)
functions = [ func for func in [inspect.getmembers(module_examples, predicate=inspect.isfunction)[0]] if func[0].startswith('_') is False ]
for example in functions:
print "Testing example: ", example[0]
#Generate model
model = example[1]()
print model
#Create tests for instance check
"""
test = model_instance_generator(model)
test.__name__ = 'test_instance_%s' % example[0]
setattr(ExamplesTests, test.__name__, test)
#Create tests for checkgrads check
test = checkgrads_generator(model)
test.__name__ = 'test_checkgrads_%s' % example[0]
setattr(ExamplesTests, test.__name__, test)
"""
model_checkgrads.description = 'test_checkgrads_%s' % example[0]
yield model_checkgrads, model
model_instance.description = 'test_checkgrads_%s' % example[0]
yield model_instance, model
if __name__ == "__main__":
print "Running unit tests, please be (very) patient..."
unittest.main()