def test_update_result_matrix_with_scalars(self):
init = 0.0
result = core.update_result_matrix(init, 0.2)
# The first time we apply this formula on a 0.0 value,
# result is equal to the first new value we apply.
self.assertAlmostEqual(0.2, result)
result = core.update_result_matrix(result, 0.3)
self.assertAlmostEqual(0.44, result)
def test_update_result_matrix_with_scalars(self):
init = 0.0
result = core.update_result_matrix(init, 0.2)
# The first time we apply this formula on a 0.0 value,
# result is equal to the first new value we apply.
self.assertAlmostEqual(0.2, result)
result = core.update_result_matrix(result, 0.3)
self.assertAlmostEqual(0.44, result)
def test_update_result_matrix_numpy_arrays(self):
init = numpy.zeros((4, 4))
first = numpy.array([0.2] * 16).reshape((4, 4))
result = core.update_result_matrix(init, first)
numpy.testing.assert_allclose(first, result)
second = numpy.array([0.3] * 16).reshape((4, 4))
result = core.update_result_matrix(result, second)
expected = numpy.array([0.44] * 16).reshape((4, 4))
numpy.testing.assert_allclose(expected, result)
def test_update_result_matrix_numpy_arrays(self):
init = numpy.zeros((4, 4))
first = numpy.array([0.2] * 16).reshape((4, 4))
result = core.update_result_matrix(init, first)
numpy.testing.assert_allclose(first, result)
second = numpy.array([0.3] * 16).reshape((4, 4))
result = core.update_result_matrix(result, second)
expected = numpy.array([0.44] * 16).reshape((4, 4))
numpy.testing.assert_allclose(expected, result)
