def draw(morphology, synapses=None, neuron_node_id=None):
"""Draw dendrogram with synapses.
Args:
morphology (Neurite|Morphology): a Morphology instance of NeuroM package.
synapses (DataFrame): synapses dataframe.
neuron_node_id (int|None): node id of ``morphology``. If None then it is taken from
``synapses[TARGET_NODE_ID]``.
Returns:
plotly.graph_objects.Figure: plotly figure
Example
.. literalinclude:: ../../../examples/dendrogram.py
:pyobject: plain_example
"""
assert (is_integer_dtype(synapses[TARGET_NODE_ID].dtype) and
is_integer_dtype(synapses[SOURCE_NODE_ID].dtype) and
is_integer_dtype(synapses[POST_SECTION_ID].dtype) and
is_integer_dtype(synapses[PRE_SECTION_ID].dtype)), \
'Section ids and nodes columns of `synapses` arg must be integers'
dendrogram = SynDendrogram(morphology)
positions = layout_dendrogram(dendrogram, np.array([0, 0]))
w, h = get_size(positions)
positions = move_positions(positions, np.array([.5 * w, 0]))
if not synapses.empty:
if neuron_node_id is None:
neuron_node_id = _get_default_neuron_node_id(synapses)
_position_synapses(positions, synapses, neuron_node_id)
synapses['synapse_id'] = synapses.index.values
# convert 'target node' to string for discrete colormap
synapses = synapses.astype({TARGET_NODE_ID: str})
fig = px.scatter(synapses,
x='x',
y='y',
color=TARGET_NODE_ID,
color_discrete_map=_get_synapse_colormap(synapses),
hover_data=synapses.columns)
else:
fig = graph_objects.Figure()
fig.update_xaxes(range=[-.05 * w, 1.05 * w], zeroline=False)
fig.update_yaxes(range=[-.05 * h, 1.05 * h], zeroline=False)
shapes = _get_draw_shapes(dendrogram, positions)
fig.update_layout(shapes=shapes)
_add_neurite_legend(fig, dendrogram)
return fig
def test_layout_dendrogram():
def assert_layout(dendrogram):
for i, child in enumerate(dendrogram.children):
# child is higher than parent in Y coordinate
assert (positions[child][1] >=
positions[dendrogram][1] + dendrogram.height)
if i < len(dendrogram.children) - 1:
next_child = dendrogram.children[i + 1]
# X space between child is enough for their widths
assert (positions[next_child][0] - positions[child][0] > .5 *
(next_child.width + child.width))
assert_layout(child)
neuron = load_neuron(NEURON_PATH)
dendrogram = dm.Dendrogram(neuron)
positions = dm.layout_dendrogram(dendrogram, np.array([0, 0]))
assert_layout(dendrogram)
def draw(neuron, synapses=None, neuron_node_id=None):
"""Draw dendrogram with synapses.
Args:
neuron (Neurite|Neuron): a Neurite or a Neuron instance of NeuroM package.
synapses (DataFrame): synapses dataframe.
neuron_node_id (int|None): node id of ``neuron``. If None then it is taken from
``synapses[TARGET_NODE_ID]``.
Returns:
plotly.graph_objects.Figure: plotly figure
"""
synapses = synapses.astype({
'@target_node': int,
'@source_node': int,
'afferent_section_id': int,
'efferent_section_id': int
})
dendrogram = SynDendrogram(neuron)
positions = layout_dendrogram(dendrogram, np.array([0, 0]))
w, h = get_size(positions)
positions = move_positions(positions, np.array([.5 * w, 0]))
if not synapses.empty:
if neuron_node_id is None:
neuron_node_id = _get_default_neuron_node_id(synapses)
_position_synapses(positions, synapses, neuron_node_id)
synapses['synapse_id'] = synapses.index.values
# convert 'target node' to string for discrete colormap
synapses = synapses.astype({TARGET_NODE_ID: str})
fig = px.scatter(synapses,
x='x',
y='y',
color=TARGET_NODE_ID,
color_discrete_map=_get_synapse_colormap(synapses),
hover_data=synapses.columns)
else:
fig = graph_objects.Figure()
fig.update_xaxes(range=[-.05 * w, 1.05 * w], zeroline=False)
fig.update_yaxes(range=[-.05 * h, 1.05 * h], zeroline=False)
shapes = _get_draw_shapes(dendrogram, positions)
fig.update_layout(shapes=shapes)
_add_neurite_legend(fig, dendrogram)
return fig
def plot_dendrogram(ax, obj, show_diameters=True):
"""Plots Dendrogram of `obj`.
Args:
ax: matplotlib axes
obj (neurom.Neuron, neurom.Tree): neuron or tree
show_diameters (bool): whether to show node diameters or not
"""
dendrogram = Dendrogram(obj)
positions = layout_dendrogram(dendrogram, np.array([0, 0]))
w, h = get_size(positions)
positions = move_positions(positions, np.array([.5 * w, 0]))
ax.set_xlim([-.05 * w, 1.05 * w])
ax.set_ylim([-.05 * h, 1.05 * h])
ax.set_title('Morphology Dendrogram')
ax.set_xlabel('micrometers (um)')
ax.set_ylabel('micrometers (um)')
shapes = _get_dendrogram_shapes(dendrogram, positions, show_diameters)
ax.add_collection(PatchCollection(shapes, match_original=True))
ax.set_aspect('auto')
ax.legend(handles=_get_dendrogram_legend(dendrogram))
