def test_all_values():
I,J = 10,9
values_K = [1,2,4,5]
R = 2*numpy.ones((I,J))
M = numpy.ones((I,J))
priors = { 'alpha':3, 'beta':4, 'lambdaU':5, 'lambdaV':6 }
initUV = 'exp'
iterations = 11
linesearch = LineSearch(classifier,values_K,R,M,priors,initUV,iterations)
linesearch.all_performances = {
'BIC' : [10,9,8,7],
'AIC' : [11,13,12,14],
'loglikelihood' : [16,15,18,17]
}
assert numpy.array_equal(linesearch.all_values('BIC'), [10,9,8,7])
assert numpy.array_equal(linesearch.all_values('AIC'), [11,13,12,14])
assert numpy.array_equal(linesearch.all_values('loglikelihood'), [16,15,18,17])
with pytest.raises(AssertionError) as error:
linesearch.all_values('FAIL')
assert str(error.value) == "Unrecognised metric name: FAIL."
def test_all_values():
I, J = 10, 9
values_K = [1, 2, 4, 5]
R = 2 * numpy.ones((I, J))
M = numpy.ones((I, J))
priors = {'alpha': 3, 'beta': 4, 'lambdaU': 5, 'lambdaV': 6}
initUV = 'exp'
iterations = 11
linesearch = LineSearch(classifier, values_K, R, M, priors, initUV,
iterations)
linesearch.all_performances = {
'BIC': [10, 9, 8, 7],
'AIC': [11, 13, 12, 14],
'loglikelihood': [16, 15, 18, 17]
}
assert numpy.array_equal(linesearch.all_values('BIC'), [10, 9, 8, 7])
assert numpy.array_equal(linesearch.all_values('AIC'), [11, 13, 12, 14])
assert numpy.array_equal(linesearch.all_values('loglikelihood'),
[16, 15, 18, 17])
with pytest.raises(AssertionError) as error:
linesearch.all_values('FAIL')
assert str(error.value) == "Unrecognised metric name: FAIL."
