def test_np_imagesrouce_rt(): shape = (13, 17) test_data = np.array([np.ones(shape) * j for j in range(11)]) np_snk = NPImageSink() with np_snk as snk: for j in range(11): snk.record_frame(test_data[j], j, {'md': j}) np_src = np_snk.make_source() with np_src as src: for j in range(11): assert_true(np.all(src.get_frame(j) == j)) assert_array_equal(src.get_frame(j), test_data[j]) assert_equal(src.get_frame_metadata(j, 'md'), j)
def _check_binary_op(op, tool, a, b): # set up constant arrays as testing sources, use floats srcA = NPImageSource(a * np.ones(_shape, dtype=np.float)) srcB = NPImageSource(b * np.ones(_shape, dtype=np.float)) # set up a sink snkC = NPImageSink() # init the tool and assign input/output T = tool() T.A = srcA T.B = srcB T.out = snkC # run the tool T.run() # compute what the answer should be c = op(a, b) # make and activate a source from the sink with snkC.make_source() as C: # loop over the output and check each frame for j in range(_shape[0]): # assert that all of the entries are equal # to the 'true' result assert_true(np.all(c == C.get_frame(j)))