def test_block_diagonal_error(self):
with self.assertRaises(ValueError):
block_diagonal(3, 4, 1)
with self.assertRaises(ValueError):
block_diagonal(3, 4, 0)
def test_block_diagonal_error(self):
with self.assertRaises(ValueError):
block_diagonal(3, 4, 1)
with self.assertRaises(ValueError):
block_diagonal(3, 4, 0)
def test_block_diagonal_3x4(self):
np.random.seed(0)
res = block_diagonal(3, 4, 2)
exp = np.array([[0.548814, 0., 0.], [0.715189, 0., 0.],
[0., 0.602763, 0.544883], [0., 0.423655, 0.645894]])
npt.assert_allclose(res, exp, rtol=1e-5, atol=1e-5)
def test_block_diagonal_4x4(self):
np.random.seed(0)
res = block_diagonal(4, 4, 2)
exp = np.array([[0.5488135, 0.71518937, 0., 0.],
[0.60276338, 0.54488318, 0., 0.],
[0., 0., 0.4236548, 0.64589411],
[0., 0., 0.43758721, 0.891773]])
npt.assert_allclose(res, exp, rtol=1e-5, atol=1e-5)
def test_block_diagonal_4x4(self):
np.random.seed(0)
res = block_diagonal(4, 4, 2)
exp = np.array([[0.5488135, 0.71518937, 0., 0.],
[0.60276338, 0.54488318, 0., 0.],
[0., 0., 0.4236548, 0.64589411],
[0., 0., 0.43758721, 0.891773]])
npt.assert_allclose(res, exp, rtol=1e-5, atol=1e-5)
def test_block_diagonal_3x4(self):
np.random.seed(0)
res = block_diagonal(3, 4, 2)
exp = np.array([[0.548814, 0., 0.],
[0.715189, 0., 0.],
[0., 0.602763, 0.544883],
[0., 0.423655, 0.645894]])
npt.assert_allclose(res, exp, rtol=1e-5, atol=1e-5)
def test_highlights(self):
table = pd.DataFrame(block_diagonal(ncols=5, nrows=5, nblocks=2),
index=['0', '1', '2', '3', '4'],
columns=['0', '1', '2', '3', '4'])
t = rank_linkage(
pd.Series([1, 2, 3, 4, 5], index=['0', '1', '2', '3', '4']))
t = SquareDendrogram.from_tree(t)
md = pd.Series(['a', 'a', 'a', 'b', 'b'],
index=['0', '1', '2', '3', '4'])
for i, n in enumerate(t.postorder()):
if not n.is_tip():
n.name = "y%d" % i
n.length = np.random.rand() * 3
highlights = pd.DataFrame({
'y8': ['#FF0000', '#00FF00'],
'y7': ['#0000FF', '#F0000F']
}).T
fig = heatmap(table, t, md, highlights)
# Test to see if the lineages of the tree are ok
lines = list(fig.get_axes()[0].get_lines())
pts = self.t.coords(width=20, height=self.table.shape[0])
pts['y'] = pts['y'] - 0.5 # account for offset
pts['x'] = pts['x'].astype(np.float)
pts['y'] = pts['y'].astype(np.float)
exp_coords = np.array([[6.33333333, 3.5], [6.33333333, 4.],
[6.33333333, 4.], [20., 4.], [12.66666667, 0.5],
[12.66666667, 1.], [12.66666667, 1.], [20., 1.],
[6.33333333, 1.25], [6.33333333, 2.],
[6.33333333, 2.], [20., 2.], [0., 2.375],
[0., 3.5], [0., 3.5], [6.33333333, 3.5],
[6.33333333, 3.5], [6.33333333, 3.],
[6.33333333, 3.], [20., 3.], [12.66666667, 0.5],
[12.66666667, 0.], [12.66666667, 0.], [20., 0.],
[6.33333333, 1.25], [6.33333333, 0.5],
[6.33333333, 0.5], [12.66666667, 0.5],
[0., 2.375], [0., 1.25], [0., 1.25],
[6.33333333, 1.25]])
res = np.vstack([i._xy for i in lines])
npt.assert_allclose(exp_coords, res)
# Make sure that the metadata labels are set properly
res = str(fig.get_axes()[2].get_xticklabels(minor=True)[0])
self.assertEqual(res, "Text(0, 0, 'a')")
res = str(fig.get_axes()[2].get_xticklabels(minor=True)[1])
self.assertEqual(res, "Text(0, 0, 'b')")
print([str(i) for i in fig.get_axes()[1].get_xticklabels()])
# Make sure that the highlight labels are set properly
res = str(fig.get_axes()[1].get_xticklabels()[0])
self.assertEqual(res, "Text(0, 0, 'y8')")
res = str(fig.get_axes()[1].get_xticklabels()[1])
self.assertEqual(res, "Text(0, 0, 'y7')")
# Test to see if the highlights are ok
res = fig.get_axes()[2].get_position()._points
exp = np.array([[0.24, 0.1], [0.808, 0.9]])
npt.assert_allclose(res, exp)
def test_highlights(self):
table = pd.DataFrame(block_diagonal(ncols=5, nrows=5, nblocks=2),
index=['0', '1', '2', '3', '4'],
columns=['0', '1', '2', '3', '4'])
t = rank_linkage(pd.Series([1, 2, 3, 4, 5],
index=['0', '1', '2', '3', '4']))
t = SquareDendrogram.from_tree(t)
md = pd.Series(['a', 'a', 'a', 'b', 'b'],
index=['0', '1', '2', '3', '4'])
for i, n in enumerate(t.postorder()):
if not n.is_tip():
n.name = "y%d" % i
n.length = np.random.rand()*3
highlights = pd.DataFrame({'y8': ['#FF0000', '#00FF00'],
'y7': ['#0000FF', '#F0000F']}).T
fig = heatmap(table, t, md, highlights)
# Test to see if the lineages of the tree are ok
lines = list(fig.get_axes()[0].get_lines())
pts = self.t.coords(width=20, height=self.table.shape[0])
pts['y'] = pts['y'] - 0.5 # account for offset
pts['x'] = pts['x'].astype(np.float)
pts['y'] = pts['y'].astype(np.float)
exp_coords = np.array([[6.33333333, 3.5],
[6.33333333, 4.],
[6.33333333, 4.],
[20., 4.],
[12.66666667, 0.5],
[12.66666667, 1.],
[12.66666667, 1.],
[20., 1.],
[6.33333333, 1.25],
[6.33333333, 2.],
[6.33333333, 2.],
[20., 2.],
[0., 2.375],
[0., 3.5],
[0., 3.5],
[6.33333333, 3.5],
[6.33333333, 3.5],
[6.33333333, 3.],
[6.33333333, 3.],
[20., 3.],
[12.66666667, 0.5],
[12.66666667, 0.],
[12.66666667, 0.],
[20., 0.],
[6.33333333, 1.25],
[6.33333333, 0.5],
[6.33333333, 0.5],
[12.66666667, 0.5],
[0., 2.375],
[0., 1.25],
[0., 1.25],
[6.33333333, 1.25]])
res = np.vstack([i._xy for i in lines])
npt.assert_allclose(exp_coords, res)
# Make sure that the metadata labels are set properly
res = str(fig.get_axes()[2].get_xticklabels(minor=True)[0])
self.assertEqual(res, "Text(0,0,'a')")
res = str(fig.get_axes()[2].get_xticklabels(minor=True)[1])
self.assertEqual(res, "Text(0,0,'b')")
# Make sure that the highlight labels are set properly
res = str(fig.get_axes()[1].get_xticklabels()[0])
self.assertEqual(res, "Text(0,0,'y7')")
res = str(fig.get_axes()[1].get_xticklabels()[1])
self.assertEqual(res, "Text(0,0,'y8')")
# Test to see if the highlights are ok
res = fig.get_axes()[2].get_position()._points
exp = np.array([[0.24, 0.1],
[0.808, 0.9]])
npt.assert_allclose(res, exp)