def test_00_02_other_ways_to_be_empty(self):
ind = I.Indexes([(0,1),(1,0)])
self.assertEqual(ind.length, 0)
self.assertEqual(len(ind.fwd_idx), 2)
self.assertTrue(np.all(ind.fwd_idx == 0))
self.assertEqual(len(ind.rev_idx), 0)
self.assertEqual(tuple(ind.idx.shape), (2,0))
def test_00_00_oh_so_empty(self):
ind = I.Indexes([[]])
self.assertEqual(ind.length, 0)
self.assertEqual(len(ind.fwd_idx), 0)
self.assertEqual(len(ind.rev_idx), 0)
self.assertEqual(tuple(ind.idx.shape), (1,0))
np.testing.assert_array_equal([[]], ind.counts)
def test_01_01_one_object_1_subobject(self):
ind = I.Indexes([[1]])
self.assertEqual(ind.length, 1)
self.assertEqual(len(ind.fwd_idx), 1)
self.assertEqual(ind.fwd_idx[0], 0)
self.assertEqual(len(ind.rev_idx), 1)
self.assertEqual(ind.rev_idx, 0)
self.assertEqual(tuple(ind.idx.shape), (1,1))
self.assertEqual(ind.idx[0,0], 0)
def test_00_01_all_are_empty(self):
counts = [[0]]
ind = I.Indexes(counts)
self.assertEqual(ind.length, 0)
self.assertEqual(len(ind.fwd_idx), 1)
self.assertEqual(ind.fwd_idx[0], 0)
self.assertEqual(len(ind.rev_idx), 0)
self.assertEqual(tuple(ind.idx.shape), (1,0))
np.testing.assert_array_equal(counts, ind.counts)
def test_01_03_one_object_NxM(self):
counts = np.array([[4],[3]])
hits = np.zeros(counts[:,0], int)
ind = I.Indexes(counts)
self.assertEqual(ind.length, np.prod(counts))
self.assertEqual(len(ind.fwd_idx), 1)
self.assertEqual(ind.fwd_idx[0], 0)
self.assertEqual(len(ind.rev_idx), ind.length)
np.testing.assert_array_equal(ind.rev_idx, 0)
self.assertEqual(tuple(ind.idx.shape), (2, ind.length))
hits[ind.idx[0], ind.idx[1]] = np.arange(ind.length)+1
self.assertEqual(len(np.unique(hits.ravel())), ind.length)
def test_02_02_multiple_objects_and_one_is_0x0(self):
counts = np.array([[4,2,0,3],[3,6,4,5]])
ind = I.Indexes(counts)
self.assertEqual(ind.length, np.sum(np.prod(counts,0)))
self.assertEqual(len(ind.fwd_idx), counts.shape[1])
np.testing.assert_array_equal(ind.fwd_idx, [0,12,24,24])
self.assertEqual(len(ind.rev_idx), ind.length)
start = 0
for i, count in enumerate(ind.counts.transpose()):
if np.prod(count) == 0:
continue
hits = np.zeros(count)
n = np.prod(count)
hits[ind.idx[0,start:(start + n)],
ind.idx[1,start:(start + n)]] = np.arange(np.prod(count))
self.assertEqual(len(np.unique(hits.ravel())), n)
start += n
def test_02_01_two_objects_NxM(self):
counts = [[4,2],[3,6]]
c0 = counts[0][0] * counts[1][0]
ind = I.Indexes(counts)
self.assertEqual(ind.length, np.sum(np.prod(counts,0)))
self.assertEqual(len(ind.fwd_idx), 2)
self.assertEqual(ind.fwd_idx[0], 0)
self.assertEqual(ind.fwd_idx[1], c0)
self.assertEqual(len(ind.rev_idx), ind.length)
np.testing.assert_array_equal(ind.rev_idx[:c0], 0)
np.testing.assert_array_equal(ind.rev_idx[c0:], 1)
start = 0
for i, count in enumerate(ind.counts.transpose()):
hits = np.zeros(count)
n = np.prod(count)
hits[ind.idx[0,start:(start + n)],
ind.idx[1,start:(start + n)]] = np.arange(np.prod(count))
self.assertEqual(len(np.unique(hits.ravel())), n)
start += n
def test_02_03_one_at_end(self):
ind = I.Indexes(np.array([[0,0,1]]))
pass