def test_search():
# Check whether we get no exceptions...
I, J = 10, 9
values_K = [1, 2, 4, 5]
R = 2 * numpy.ones((I, J))
R[0, 0] = 1
M = numpy.ones((I, J))
priors = {'alpha': 3, 'beta': 4, 'lambdaU': 5, 'lambdaV': 6}
initUV = 'exp'
iterations = 1
linesearch = LineSearch(classifier, values_K, R, M, priors, initUV,
iterations)
linesearch.search()
# Generate data
(_, _, _, _, R) = generate_dataset(I, J, true_K, lambdaU, lambdaV, tau)
M = numpy.ones((I, J))
#M = try_generate_M(I,J,fraction_unknown,attempts_M)
# Run the line search. The priors lambdaU and lambdaV need to be a single value (recall K is unknown)
priors = {
'alpha': alpha,
'beta': beta,
'lambdaU': lambdaU[0, 0] / 10,
'lambdaV': lambdaV[0, 0] / 10
}
line_search = LineSearch(classifier, values_K, R, M, priors, initUV,
iterations, restarts)
line_search.search(burn_in, thinning)
# Plot the performances of all three metrics - but MSE separately
metrics = ['loglikelihood', 'BIC', 'AIC', 'MSE']
for metric in metrics:
plt.figure()
plt.plot(values_K, line_search.all_values(metric), label=metric)
plt.legend(loc=3)
# Also print out all values in a dictionary
all_values = {}
for metric in metrics:
all_values[metric] = line_search.all_values(metric)
print "all_values = %s" % all_values
'''
# Generate data
(_, _, _, _, R) = generate_dataset(I, J, true_K, lambdaU, lambdaV, tau)
M = numpy.ones((I, J))
#M = try_generate_M(I,J,fraction_unknown,attempts_M)
# Run the line search. The priors lambdaU and lambdaV need to be a single value (recall K is unknown)
priors = {
'alpha': alpha,
'beta': beta,
'lambdaU': lambdaU[0, 0] / 10,
'lambdaV': lambdaV[0, 0] / 10
}
line_search = LineSearch(classifier, values_K, R, M, priors, initUV,
iterations, restarts)
line_search.search()
# Plot the performances of all three metrics
metrics = ['loglikelihood', 'BIC', 'AIC', 'MSE', 'ELBO']
for metric in metrics:
plt.figure()
plt.plot(values_K, line_search.all_values(metric), label=metric)
plt.legend(loc=3)
# Also print out all values in a dictionary
all_values = {}
for metric in metrics:
all_values[metric] = line_search.all_values(metric)
print "all_values = %s" % all_values
'''