def test_run():
###### Test updating F, G, S in that order
# Test whether a single iteration gives the correct behaviour, updating F, G, S in that order
R = numpy.array([[1,2],[3,4]],dtype='f')
M = numpy.array([[1,1],[0,1]])
K = 3
L = 1
F = numpy.array([[1,2,3],[4,5,6]],dtype='f')
S = numpy.array([[7],[8],[9]],dtype='f')
G = numpy.array([[10],[11]],dtype='f')
#FSG = numpy.array([[500,550],[1220,1342]],dtype='f')
#FS = numpy.array([[50],[122]],dtype='f')
#SG = numpy.array([[70,77],[80,88],[90,99]],dtype='f')
nmtf = NMTF(R,M,K,L)
# Check we get an Exception if W, H are undefined
with pytest.raises(AssertionError) as error:
nmtf.run(0)
assert str(error.value) == "F, S and G have not been initialised - please run NMTF.initialise() first."
nmtf.F = numpy.copy(F)
nmtf.S = numpy.copy(S)
nmtf.G = numpy.copy(G)
nmtf.run(1)
R = numpy.loadtxt(input_folder + "R.txt")
M = numpy.ones((I, J))
# Run the VB algorithm, <repeats> times
times_repeats = []
performances_repeats = []
for i in range(0, repeats):
# Set all the seeds
numpy.random.seed(3)
random.seed(4)
scipy.random.seed(5)
# Run the classifier
nmtf = NMTF(R, M, K, L)
nmtf.initialise(init_S, init_FG, expo_prior)
nmtf.run(iterations)
# Extract the performances and timestamps across all iterations
times_repeats.append(nmtf.all_times)
performances_repeats.append(nmtf.all_performances)
# Check whether seed worked: all performances should be the same
assert all([numpy.array_equal(performances, performances_repeats[0]) for performances in performances_repeats]), \
"Seed went wrong - performances not the same across repeats!"
# Print out the performances, and the average times
all_times_average = list(numpy.average(times_repeats, axis=0))
all_performances = performances_repeats[0]
print "np_all_times_average = %s" % all_times_average
print "np_all_performances = %s" % all_performances
