def plain_example():
"""Example that shows how to plot a neuron dendrogram with a plain synapses dataframe."""
# Those properties are required in synapses dataframe for positioning
required_synapse_properties = [
consts.SOURCE_NODE_ID,
consts.TARGET_NODE_ID,
consts.POST_SECTION_ID,
consts.POST_SECTION_POS,
consts.PRE_SECTION_ID,
consts.PRE_SECTION_POS,
]
# or use plain strings
# required_columns = ['@source_node', '@target_node',
# 'afferent_section_id', 'afferent_section_pos',
# 'efferent_section_id', 'efferent_section_pos']
data = np.array([
[0, 116, 4, 0.81408846, 3, 0.7344886],
[0, 116, 5, 0.145983203, 4, 0.24454929],
[0, 116, 3, 0.968469656, 1, 0.4290702],
[116, 0, 2, 0.84480673, 1, 0.29180855],
[116, 0, 2, 0.5815143, 1, 0.68261607],
])
synapses = pd.DataFrame(columns=required_synapse_properties, data=data)
synapses = synapses.astype({
'@target_node': int,
'@source_node': int,
'afferent_section_id': int,
'efferent_section_id': int
})
m = nm.load_morphology('dendrogram_plain_example.swc')
fig = dendrogram.draw(m, synapses, 116)
fig.show()
# If you want to show additional data with synapses then just use additional columns in you
# dataframe. These data properties can have any names.
synapse_data_properties = [
'u_syn', 'depression_time', 'facilitation_time', 'conductance'
]
data = np.array([
[0.16718547, 153.8097, 8.452671, 1.9140357],
[0.16718547, 153.8097, 8.452671, 1.9140357],
[0.16718547, 153.8097, 8.452671, 1.9140357],
[0.29116565, 116.06434, 10.367496, 3.1585026],
[0.29116565, 116.06434, 10.367496, 3.1585026],
])
synapses_data = pd.DataFrame(columns=synapse_data_properties, data=data)
synapses = pd.concat([synapses, synapses_data], axis=1)
fig = dendrogram.draw(m, synapses, 116)
fig.show()
def test_explicit_neuron_node_id():
neuron_node_id = 1
fig = dendrogram.draw(_create_test_neuron(),
_create_test_synapses([neuron_node_id, 2]),
neuron_node_id)
# returns a string that contains the HTML <div>, without saving to file
plot(fig, auto_open=False, output_type='div')
def circuit_example():
"""Example that shows how to plot a neuron dendrogram with synapses from a bluepysnap circuit.
To make this example work, you would need a proper SONATA circuit.
"""
from bluepysnap import Circuit
from bluepysnap.sonata_constants import Edge
from bluepysnap.bbp import Synapse
circuit = Circuit('/path/to/sonata_circuit_config.json')
# you can use `bluepysnap.sonata_constants.Edge` instead of `morph_tool.draw.consts`
edge_properties = [
Edge.SOURCE_NODE_ID,
Edge.TARGET_NODE_ID,
Edge.POST_SECTION_ID,
Edge.POST_SECTION_POS,
Edge.PRE_SECTION_ID,
Edge.PRE_SECTION_POS,
Synapse.U_SYN,
Synapse.D_SYN,
Synapse.F_SYN,
Synapse.G_SYNX,
]
source_node_id = 0
target_node_id = 116
synapses1 = circuit.edges['default'].pair_edges(source_node_id,
target_node_id,
edge_properties)
synapses2 = circuit.edges['default'].pair_edges(target_node_id,
source_node_id,
edge_properties)
synapses = pd.concat([synapses1, synapses2])
morph_filepath = circuit.nodes['default'].morph.get_filepath(
target_node_id)
m = nm.load_morphology(morph_filepath)
fig = dendrogram.draw(m, synapses, target_node_id)
fig.show()
def test_implicit_invalid_neuron_node_id():
neuron_node_id = 1
with pytest.raises(ValueError, match='neuron_node_id'):
dendrogram.draw(_create_test_neuron(),
_create_test_synapses([neuron_node_id, 2]))