diff --git a/bob/learn/libsvm/test_trainer.py b/bob/learn/libsvm/test_trainer.py index 74f4b4d045671e3e448c54f6c739e0d0c8ff38dc..163d88248738c81fdf832644d8ca3876017473f3 100644 --- a/bob/learn/libsvm/test_trainer.py +++ b/bob/learn/libsvm/test_trainer.py @@ -34,6 +34,10 @@ HEART_DATA = F('heart.svmdata') #13 inputs HEART_MACHINE = F('heart.svmmodel') #supports probabilities HEART_EXPECTED = F('heart.out') #expected probabilities +def _check_abs_diff(a, b, maxval): + assert numpy.all(abs(a - b) < maxval), "Maximum " \ + "difference exceeded limit (%g): %g" % (maxval, abs(a - b).max()) + def test_initialization(): # tests and examplifies some initialization parameters @@ -116,10 +120,10 @@ def test_training(): previous = Machine(TEST_MACHINE_NO_PROBS) nose.tools.eq_(machine.machine_type, previous.machine_type) nose.tools.eq_(machine.kernel_type, previous.kernel_type) - nose.tools.eq_(machine.gamma, previous.gamma) + assert numpy.isclose(machine.gamma, previous.gamma) nose.tools.eq_(machine.shape, previous.shape) - assert numpy.all(abs(machine.input_subtract - previous.input_subtract) < 1e-8) - assert numpy.all(abs(machine.input_divide - previous.input_divide) < 1e-8) + _check_abs_diff(machine.input_subtract, previous.input_subtract, 1e-8) + _check_abs_diff(machine.input_divide, previous.input_divide, 1e-8) curr_label = machine.predict_class(data) prev_label = previous.predict_class(data) @@ -131,7 +135,7 @@ def test_training(): curr_scores = numpy.array(curr_scores) prev_scores = numpy.array(prev_scores) - assert numpy.all(abs(curr_scores - prev_scores) < 1e-8) + _check_abs_diff(curr_scores, prev_scores, 5e-7) def test_training_with_probability(): @@ -150,10 +154,10 @@ def test_training_with_probability(): previous = Machine(HEART_MACHINE) nose.tools.eq_(machine.machine_type, previous.machine_type) nose.tools.eq_(machine.kernel_type, previous.kernel_type) - nose.tools.eq_(machine.gamma, previous.gamma) + assert numpy.isclose(machine.gamma, previous.gamma) nose.tools.eq_(machine.shape, previous.shape) - assert numpy.all(abs(machine.input_subtract - previous.input_subtract) < 1e-8) - assert numpy.all(abs(machine.input_divide - previous.input_divide) < 1e-8) + _check_abs_diff(machine.input_subtract, previous.input_subtract, 1e-8) + _check_abs_diff(machine.input_divide, previous.input_divide, 1e-8) # check labels curr_label = machine.predict_class(data) @@ -167,7 +171,7 @@ def test_training_with_probability(): curr_scores = numpy.array(curr_scores) prev_scores = numpy.array(prev_scores) - assert numpy.all(abs(curr_scores - prev_scores) < 1e-8) + _check_abs_diff(curr_scores, prev_scores, 5e-7) # check probabilities -- probA and probB do not get the exact same values # as when using libsvm's svm-train.c. The reason may lie in the order in @@ -176,7 +180,7 @@ def test_training_with_probability(): prev_labels, prev_scores = previous.predict_class_and_probabilities(data) curr_scores = numpy.array(curr_scores) prev_scores = numpy.array(prev_scores) - #assert numpy.all(abs(curr_scores-prev_scores) < 1e-8) + #_check_abs_diff(curr_scores, prev_scores, 1e-8) def test_training_one_class(): @@ -198,10 +202,10 @@ def test_training_one_class(): previous = Machine(TEST_MACHINE_ONE_CLASS) nose.tools.eq_(machine.machine_type, previous.machine_type) nose.tools.eq_(machine.kernel_type, previous.kernel_type) - nose.tools.eq_(machine.gamma, previous.gamma) + assert numpy.isclose(machine.gamma, previous.gamma) nose.tools.eq_(machine.shape, previous.shape) - assert numpy.all(abs(machine.input_subtract - previous.input_subtract) < 1e-8) - assert numpy.all(abs(machine.input_divide - previous.input_divide) < 1e-8) + _check_abs_diff(machine.input_subtract, previous.input_subtract, 1e-8) + _check_abs_diff(machine.input_divide, previous.input_divide, 1e-8) curr_label = machine.predict_class(data) prev_label = previous.predict_class(data) @@ -213,8 +217,7 @@ def test_training_one_class(): curr_scores = numpy.array(curr_scores) prev_scores = numpy.array(prev_scores) - assert numpy.all(abs(curr_scores - prev_scores) < 1e-8) - + _check_abs_diff(curr_scores, prev_scores, 5e-5) def test_successive_training():