def test_heatmap_wrong_x_shape(self):
with pytest.raises(ValueError) as excinfo:
eda.heatmap(np.random.ranf(1),
col_labels=[0],
title='test heatmap',
xlab='col label',
ylab='row label',
figsize=(10, 10))
with pytest.raises(ValueError) as excinfo:
eda.heatmap(np.random.ranf(1),
title='test heatmap',
xlab='col label',
ylab='row label',
figsize=(10, 10))
def test_heatmap_wrong_col_lab_len(self):
with pytest.raises(ValueError) as excinfo:
eda.heatmap(self.x_10x5, ['cc'] * 1 + ['bb'] * 3 + ['aa'] * 6,
['a'] * 3 + ['b'] * 1,
title='test heatmap',
xlab='col label',
ylab='row label',
figsize=(10, 10))
with pytest.raises(ValueError) as excinfo:
eda.heatmap(self.x_10x5, ['cc'] * 1 + ['bb'] * 3 + ['aa'] * 6,
['a'] * 5 + ['b'] * 1,
title='test heatmap',
xlab='col label',
ylab='row label',
figsize=(10, 10))
def test_heatmap_nolabs(self):
fig = eda.heatmap(self.x_10x5,
title='test heatmap',
xlab='col label',
ylab='row label',
figsize=(10, 10))
return fig
def test_heatmap_clabs(self):
fig = eda.heatmap(self.x_10x5,
col_labels=['a'] * 3 + ['b'] * 2,
title='test heatmap',
xlab='col label',
ylab='row label',
figsize=(10, 10))
return fig
def test_heatmap_str_crlabs(self):
fig = eda.heatmap(self.x_10x5, ['cc'] * 1 + ['bb'] * 3 + ['aa'] * 6,
['a'] * 3 + ['b'] * 2,
title='test heatmap',
xlab='col label',
ylab='row label',
figsize=(10, 10))
return fig
def test_heatmap_rlabs(self):
fig = eda.heatmap(self.x_10x5,
row_labels=[0] * 1 + [1] * 3 + [2] * 6,
title='test heatmap',
xlab='col label',
ylab='row label',
figsize=(10, 10))
return fig
def test_heatmap_crlabs(self):
fig = eda.heatmap(self.x_10x5, [2] * 1 + [1] * 3 + [5] * 6,
[0] + [1] * 2 + [2] + [3],
title='test heatmap',
xlab='col label',
ylab='row label',
figsize=(10, 10))
return fig
def test_heatmap_bilinear_interpolation(self):
fig = eda.heatmap(self.x_10x5, [2] * 1 + [1] * 3 + [5] * 6,
[0] * 3 + [1] * 2,
title='test heatmap',
xlab='col label',
ylab='row label',
interpolation='bilinear',
figsize=(10, 10))
return fig
def test_heatmap_cmap(self):
fig = eda.heatmap(self.x_10x5, [2] * 1 + [1] * 3 + [5] * 6,
[0] * 3 + [1] * 2,
title='test heatmap',
xlab='col label',
ylab='row label',
cmap='viridis',
figsize=(10, 10))
return fig
def test_heatmap_crlabs_cl_ord(self):
fig = eda.heatmap(self.x_10x5, [2] * 1 + [1] * 3 + [5] * 6,
[0] + [1] * 2 + [2] + [3],
title='test heatmap',
xlab='col label',
ylab='row label',
figsize=(10, 10),
col_label_order=[2, 1, 3, 0])
return fig
def test_heatmap_crlabs_shuffle_colc(self):
fig = eda.heatmap(self.x_10x5, [2] * 1 + [1] * 3 + [5] * 6,
[0] + [1] * 2 + [2] + [3],
title='test heatmap',
xlab='col label',
ylab='row label',
figsize=(10, 10),
shuffle_col_colors=True,
random_state=17)
return fig
def dmat_heatmap(self,
selected_labels=None,
col_labels=None,
transform=None,
title=None,
xlab=None,
ylab=None,
figsize=(10, 10),
**kwargs):
# hierarchical clustering tree leaf sample inds ordered from
# left to right
leaf_order = self._hac_tree.leaf_ids()
if len(leaf_order) == 0:
return None
# leaf labels from left to right
leaf_ordered_labs = np.array(self._labs)[leaf_order].tolist()
# check labels not interrupted in leaf order
# in other word, same labels should be adjacent to each other
# Examples:
# - good: [1] and [1, 1, 2, 2, 3]
# - bad: [1, 2, 1, 1, 3, 3]
curr_lab = leaf_ordered_labs[0]
lab_set = set([curr_lab])
for ilab in leaf_ordered_labs:
if ilab != curr_lab:
# reached the next group of labels
if ilab in lab_set:
raise ValueError("Same labels should be grouped "
"together.\n\t"
"iterating lab: {}\n\t"
"iterated lab set: {}\n\t"
"leaf order: {}\n\t"
"leaf ordered labs: {}".format(
ilab, lab_set, leaf_order,
leaf_ordered_labs))
lab_set.add(ilab)
curr_lab = ilab
# generate heatmap
# select labels to plot
s_lab_bool_inds = SLCS.select_labs_bool_inds(leaf_ordered_labs,
selected_labels)
s_leaf_order = list(itertools.compress(leaf_order, s_lab_bool_inds))
s_leaf_ordered_labs = list(
itertools.compress(leaf_ordered_labs, s_lab_bool_inds))
s_d = self._sdm._d[s_leaf_order][:, s_leaf_order]
return eda.heatmap(s_d,
row_labels=s_leaf_ordered_labs,
col_labels=col_labels,
transform=transform,
title=title,
xlab=xlab,
ylab=ylab,
figsize=figsize,
**kwargs)
def test_heatmap_transform(self):
# not callable transform
with pytest.raises(ValueError) as excinfo:
eda.heatmap(self.x_10x5, [2] * 1 + [1] * 3 + [5] * 6,
[0] * 3 + [1] * 2,
title='test heatmap',
xlab='col label',
ylab='row label',
transform=1,
figsize=(10, 10))
with pytest.raises(ValueError) as excinfo:
eda.heatmap(self.x_10x5, [2] * 1 + [1] * 3 + [5] * 6,
[0] * 3 + [1] * 2,
title='test heatmap',
xlab='col label',
ylab='row label',
transform=[],
figsize=(10, 10))
with pytest.raises(ValueError) as excinfo:
eda.heatmap(self.x_10x5, [2] * 1 + [1] * 3 + [5] * 6,
[0] * 3 + [1] * 2,
title='test heatmap',
xlab='col label',
ylab='row label',
transform=self.x_10x5,
figsize=(10, 10))
fig = eda.heatmap(np.arange(50).reshape(10, 5),
[2] * 1 + [1] * 3 + [5] * 6, [0] * 3 + [1] * 2,
title='test heatmap',
xlab='col label',
ylab='row label',
transform=lambda x: x + 100,
figsize=(10, 10))
return fig
def test_heatmap_empty_x(self):
with pytest.raises(ValueError) as excinfo:
eda.heatmap([[]],
col_labels=[],
title='test heatmap',
xlab='col label',
ylab='row label',
figsize=(10, 10))
with pytest.raises(ValueError) as excinfo:
eda.heatmap([[]],
col_labels=[],
title='test heatmap',
xlab='col label',
ylab='row label',
figsize=(10, 10))
with pytest.raises(ValueError) as excinfo:
eda.heatmap([[]],
row_labels=[],
col_labels=[],
title='test heatmap',
xlab='col label',
ylab='row label',
figsize=(10, 10))
def test_heatmap_no_xylab_title(self):
fig = eda.heatmap(self.x_10x5, [2] * 1 + [1] * 3 + [5] * 6,
[0] * 3 + [1] * 2,
figsize=(10, 10))
return fig
