def test_mst_matrix_as_array(self):
# Verifies MST matrix func returns array with dict/trees in each cell
for i in self.ifgs[3:]:
i.phase_data[0, 1] = 0 # partial stack of NODATA to one cell
for i in self.ifgs:
i.convert_to_nans() # zeros to NaN/NODATA
epochs = algorithm.get_epochs(self.ifgs)[0]
res = mst._mst_matrix_as_array(self.ifgs)
ys, xs = res.shape
for y, x in product(range(ys), range(xs)):
r = res[y, x]
num_nodes = len(r)
self.assertTrue(num_nodes < len(epochs.dates))
stack = array([i.phase_data[y, x]
for i in self.ifgs]) # 17 ifg stack
self.assertTrue(
0 == nsum(stack == 0)) # all 0s should be converted
nc = nsum(isnan(stack))
exp_count = len(epochs.dates) - 1
if nc == 0:
self.assertEqual(num_nodes, exp_count)
elif nc > 5:
# rough test: too many nans must reduce the total tree size
self.assertTrue(num_nodes <= (17 - nc))
def test_all_nan_pixel_stack(self):
# ensure full stack of NaNs in an MST pixel classifies to NaN
mock_ifgs = [MockIfg(i, 1, 1) for i in self.ifgs]
for m in mock_ifgs:
m.phase_data[:] = nan
res = mst._mst_matrix_as_array(mock_ifgs)
exp = empty((1, 1)) #, dtype=object)
exp[:] = nan
shape = (mock_ifgs[0].nrows, mock_ifgs[0].ncols)
self.assertTrue(res.shape == shape)
self.assertTrue(res.shape == exp.shape)
self.assertTrue(isnan(res[0][0]) and isnan(exp[0][0]))
def assert_equal():
res = mst._mst_matrix_as_array(mock_ifgs)
self.assertEqual(len(res[0, 0]), num_coherent)