def setUp(self):
self.morphology = Morphology(
basic_nodes(),
node_id_cb=lambda node: node["id"],
parent_id_cb=lambda node: node["parent_id"],
)
self.data = Data(self.morphology, relative_soma_depth=0.25)
def build(self):
""" Construct a Morphology object using this builder. This is a non-
destructive operation. The Morphology will be validated at this stage.
"""
return Morphology(self.nodes,
node_id_cb=lambda node: node["id"],
parent_id_cb=lambda node: node["parent"])
def setUp(self):
# morphology with 3/4 axons below soma in z
self.morphology = Morphology(
[
{
"id": 0,
"parent_id": -1,
"type": SOMA,
"x": 0,
"y": 0,
"z": 100,
"radius": 5
},
{
"id": 1,
"parent_id": 0,
"type": AXON,
"x": 0,
"y": 0,
"z": 110,
"radius": 1
},
{
"id": 2,
"parent_id": 1,
"type": AXON,
"x": 0,
"y": 0,
"z": 90,
"radius": 1
},
{
"id": 3,
"parent_id": 2,
"type": AXON,
"x": 0,
"y": 0,
"z": 80,
"radius": 1
},
{
"id": 4,
"parent_id": 3,
"type": AXON,
"x": 0,
"y": 0,
"z": 70,
"radius": 1
},
],
node_id_cb=lambda node: node["id"],
parent_id_cb=lambda node: node["parent_id"],
)
self.data = Data(self.morphology)
def test_independent_axon_count_zero(self):
nodes = [
test_node(id=1, type=SOMA, parent_node_id=-1),
test_node(id=2, type=AXON, parent_node_id=1)
]
test_morphology = Morphology(nodes,
node_id_cb=lambda node: node['id'],
parent_id_cb=lambda node: node['parent'])
test_morphology.validate(strict=False)
stat = morphology_statistics(test_morphology)
self.assertEqual(stat["Number of Independent Axons"], 0)
def setUp(self):
self.morphology = Morphology(
[
{
"id": 0,
"parent_id": -1,
"type": SOMA,
"x": 0,
"y": 0,
"z": 100,
"radius": 1
},
{
"id": 1,
"parent_id": 0,
"type": AXON,
"x": 0,
"y": 0,
"z": 110,
"radius": 20
},
{
"id": 2,
"parent_id": 1,
"type": AXON,
"x": 0,
"y": 0,
"z": 120,
"radius": 1
},
{
"id": 3,
"parent_id": 0,
"type": APICAL_DENDRITE,
"x": 0,
"y": 3,
"z": 100,
"radius": 10
},
{
"id": 4,
"parent_id": 3,
"type": APICAL_DENDRITE,
"x": 0,
"y": 6,
"z": 100,
"radius": 1
},
],
node_id_cb=lambda node: node["id"],
parent_id_cb=lambda node: node["parent_id"],
)
def setUp(self):
nodes = basic_nodes()
self.sizes = np.random.rand(len(nodes))
for sz, node in zip(self.sizes, nodes):
node["radius"] = sz
self.morphology = Morphology(
nodes,
node_id_cb=lambda node: node["id"],
parent_id_cb=lambda node: node["parent_id"],
)
self.mean_diameter = np.mean(self.sizes) * 2
def test_morphology_from_data_file_by_node_type(node_types=None):
morphology = swc.morphology_from_swc(test_file)
nodes = morphology.get_node_by_types(node_types)
for node in nodes:
# unfortunately, pandas automatically promotes numeric types to float in to_dict
node['parent'] = int(node['parent'])
node['id'] = int(node['id'])
node['type'] = int(node['type'])
node_id_cb = lambda node: node['id']
parent_id_cb = lambda node: node['parent']
axon_only_morphology = Morphology(nodes, node_id_cb, parent_id_cb)
return axon_only_morphology
def morphology_from_swc(swc_path):
swc_data = read_swc(swc_path, sep=' ')
nodes = swc_data.to_dict('record')
for node in nodes:
# unfortunately, pandas automatically promotes numeric types to float in to_dict
node['parent'] = int(node['parent'])
node['id'] = int(node['id'])
node['type'] = int(node['type'])
return Morphology(
nodes,
node_id_cb=lambda node: node['id'],
parent_id_cb=lambda node: node['parent']
)
def test_tree(nodes=None, strict_validation=False):
if not nodes:
return None
for node in nodes:
# unfortunately, pandas automatically promotes numeric types to float in to_dict
node['parent'] = int(node['parent'])
node['id'] = int(node['id'])
node['type'] = int(node['type'])
node_id_cb = lambda node: node['id']
parent_id_cb = lambda node: node['parent']
morpho = Morphology(nodes, node_id_cb, parent_id_cb)
morpho.validate(strict=strict_validation)
return morpho
def test_morphology_large():
nodes = [
test_node(id=1,
type=SOMA,
x=800,
y=610,
z=30,
radius=35,
parent_node_id=-1),
test_node(id=2,
type=BASAL_DENDRITE,
x=400,
y=600,
z=10,
radius=3,
parent_node_id=1),
test_node(id=3,
type=BASAL_DENDRITE,
x=430,
y=630,
z=20,
radius=3,
parent_node_id=2),
test_node(id=4,
type=BASAL_DENDRITE,
x=460,
y=660,
z=30,
radius=3,
parent_node_id=3),
test_node(id=5,
type=BASAL_DENDRITE,
x=490,
y=690,
z=40,
radius=3,
parent_node_id=4),
test_node(id=6,
type=APICAL_DENDRITE,
x=600,
y=300,
z=20,
radius=3,
parent_node_id=1),
test_node(id=7,
type=APICAL_DENDRITE,
x=630,
y=330,
z=30,
radius=3,
parent_node_id=6),
test_node(id=8,
type=APICAL_DENDRITE,
x=660,
y=360,
z=40,
radius=3,
parent_node_id=7),
test_node(id=9,
type=APICAL_DENDRITE,
x=690,
y=390,
z=50,
radius=3,
parent_node_id=8),
test_node(id=10,
type=APICAL_DENDRITE,
x=710,
y=420,
z=60,
radius=3,
parent_node_id=9),
test_node(id=11,
type=APICAL_DENDRITE,
x=740,
y=450,
z=70,
radius=3,
parent_node_id=10),
test_node(id=12,
type=AXON,
x=900,
y=600,
z=30,
radius=3,
parent_node_id=1),
test_node(id=13,
type=AXON,
x=930,
y=630,
z=40,
radius=3,
parent_node_id=12),
test_node(id=14,
type=AXON,
x=960,
y=660,
z=50,
radius=3,
parent_node_id=13),
test_node(id=15,
type=AXON,
x=990,
y=690,
z=60,
radius=3,
parent_node_id=14),
test_node(id=16,
type=AXON,
x=1020,
y=720,
z=70,
radius=3,
parent_node_id=15),
test_node(id=17,
type=AXON,
x=1050,
y=750,
z=80,
radius=3,
parent_node_id=16)
]
for node in nodes:
# unfortunately, pandas automatically promotes numeric types to float in to_dict
node['parent'] = int(node['parent'])
node['id'] = int(node['id'])
node['type'] = int(node['type'])
return Morphology(nodes,
node_id_cb=lambda node: node['id'],
parent_id_cb=lambda node: node['parent'])
def test_morphology_small_multiple_trees():
nodes = [
test_node(id=1,
type=SOMA,
x=800,
y=610,
z=30,
radius=35,
parent_node_id=-1),
test_node(id=2,
type=BASAL_DENDRITE,
x=400,
y=600,
z=10,
radius=3,
parent_node_id=1),
test_node(id=3,
type=APICAL_DENDRITE,
x=600,
y=300,
z=20,
radius=3,
parent_node_id=1),
test_node(id=4,
type=AXON,
x=900,
y=600,
z=30,
radius=3,
parent_node_id=1),
test_node(id=5,
type=AXON,
x=900,
y=600,
z=30,
radius=3,
parent_node_id=-1),
test_node(id=6,
type=AXON,
x=900,
y=600,
z=30,
radius=3,
parent_node_id=5),
test_node(id=7,
type=AXON,
x=900,
y=600,
z=30,
radius=3,
parent_node_id=6),
test_node(id=8,
type=AXON,
x=900,
y=600,
z=30,
radius=3,
parent_node_id=7),
test_node(id=9,
type=AXON,
x=900,
y=600,
z=30,
radius=3,
parent_node_id=8)
]
for node in nodes:
# unfortunately, pandas automatically promotes numeric types to float in to_dict
node['parent'] = int(node['parent'])
node['id'] = int(node['id'])
node['type'] = int(node['type'])
return Morphology(nodes,
node_id_cb=lambda node: node['id'],
parent_id_cb=lambda node: node['parent'])
def setUp(self):
# Create an axon that extends positively,
# and a basal dendrite that extends negatively
self.one_dim_neuron = Morphology(
[
{
"id": 0,
"parent_id": -1,
"type": SOMA,
"x": 0,
"y": 100,
"z": 0,
"radius": 10
},
# Axon node [100, 125, 150, 175, 200]
{
"id": 1,
"parent_id": 0,
"type": AXON,
"x": 0,
"y": 100,
"z": 0,
"radius": 3
},
{
"id": 2,
"parent_id": 1,
"type": AXON,
"x": 0,
"y": 125,
"z": 0,
"radius": 3
},
{
"id": 3,
"parent_id": 2,
"type": AXON,
"x": 0,
"y": 150,
"z": 0,
"radius": 3
},
{
"id": 4,
"parent_id": 3,
"type": AXON,
"x": 0,
"y": 175,
"z": 0,
"radius": 3
},
{
"id": 5,
"parent_id": 4,
"type": AXON,
"x": 0,
"y": 200,
"z": 0,
"radius": 3
},
# Basal node [100, 75, 50]
{
"id": 11,
"parent_id": 0,
"type": BASAL_DENDRITE,
"x": 0,
"y": 100,
"z": 0,
"radius": 3
},
{
"id": 12,
"parent_id": 11,
"type": BASAL_DENDRITE,
"x": 0,
"y": 75,
"z": 0,
"radius": 3
},
{
"id": 13,
"parent_id": 12,
"type": BASAL_DENDRITE,
"x": 0,
"y": 50,
"z": 0,
"radius": 3
},
],
node_id_cb=lambda node: node["id"],
parent_id_cb=lambda node: node["parent_id"],
)
self.one_dim_neuron_data = Data(self.one_dim_neuron)
self.dimension_features = nested_specialize(
di.dimension,
[COORD_TYPE_SPECIALIZATIONS, NEURITE_SPECIALIZATIONS])
def setUp(self):
self.morphology = Morphology(
basic_nodes(),
node_id_cb=lambda node: node["id"],
parent_id_cb=lambda node: node["parent_id"],
)
def setUp(self):
self.morphology = Morphology([
{
"id": 0,
"parent_id": -1,
"type": SOMA,
"x": 0,
"y": 0,
"z": 100,
"radius": 1
},
{
"id": 1,
"parent_id": 0,
"type": AXON,
"x": 0,
"y": 0,
"z": 101,
"radius": 1
},
{
"id": 2,
"parent_id": 0,
"type": APICAL_DENDRITE,
"x": 0,
"y": 0,
"z": 102,
"radius": 1
},
{ # bifurcates
"id": 3,
"parent_id": 1,
"type": AXON,
"x": 0,
"y": 0,
"z": 110,
"radius": 1
},
{
"id": 4,
"parent_id": 3,
"type": AXON,
"x": 0,
"y": 0,
"z": 140,
"radius": 1
},
{ # this node backtracks, causing the path distance to differ from the euclidean
"id": 11,
"parent_id": 4,
"type": AXON,
"x": 0,
"y": 0,
"z": 130,
"radius": 1
},
{ # bifurcates
"id": 5,
"parent_id": 3,
"type": AXON,
"x": 0,
"y": 0,
"z": 130,
"radius": 1
},
{
"id": 6,
"parent_id": 5,
"type": AXON,
"x": 0,
"y": 0,
"z": 135,
"radius": 1
},
{
"id": 7,
"parent_id": 5,
"type": AXON,
"x": 30,
"y": 0,
"z": 103,
"radius": 1
},
{ # bifurcates
"id": 8,
"parent_id": 2,
"type": APICAL_DENDRITE,
"x": 0,
"y": 0,
"z": 125,
"radius": 1
},
{
"id": 9,
"parent_id": 8,
"type": APICAL_DENDRITE,
"x": 0,
"y": 0,
"z": 126,
"radius": 1
},
{
"id": 10,
"parent_id": 8,
"type": APICAL_DENDRITE,
"x": 0,
"y": 0,
"z": 127,
"radius": 1
},
],
node_id_cb=lambda node: node["id"],
parent_id_cb=lambda node: node["parent_id"],
)
def setUp(self):
self.one_dim_neuron = Morphology([
{
"id": 0,
"parent_id": -1,
"type": SOMA,
"x": 0,
"y": 0,
"z": 100,
"radius": 1
},
{
"id": 1,
"parent_id": 0,
"type": AXON,
"x": 0,
"y": 0,
"z": 101,
"radius": 1
},
{
"id": 2,
"parent_id": 0,
"type": APICAL_DENDRITE,
"x": 0,
"y": 0,
"z": 102,
"radius": 1
},
{ # bifurcates and is within 120
"id": 3,
"parent_id": 1,
"type": AXON,
"x": 0,
"y": 0,
"z": 110,
"radius": 1
},
{ # This is the farthest node from the root
"id": 4,
"parent_id": 3,
"type": AXON,
"x": 0,
"y": 0,
"z": 140,
"radius": 1
},
{ # bifurcates, and is beyond 120
"id": 5,
"parent_id": 3,
"type": AXON,
"x": 0,
"y": 0,
"z": 130,
"radius": 1
},
{
"id": 6,
"parent_id": 5,
"type": AXON,
"x": 0,
"y": 0,
"z": 135,
"radius": 1
},
{
"id": 7,
"parent_id": 5,
"type": AXON,
"x": 0,
"y": 0,
"z": 136,
"radius": 1
},
{ # bifurcates and is beyond 120
"id": 8,
"parent_id": 2,
"type": APICAL_DENDRITE,
"x": 0,
"y": 0,
"z": 125,
"radius": 1
},
{
"id": 9,
"parent_id": 8,
"type": APICAL_DENDRITE,
"x": 0,
"y": 0,
"z": 126,
"radius": 1
},
{
"id": 10,
"parent_id": 8,
"type": APICAL_DENDRITE,
"x": 0,
"y": 0,
"z": 127,
"radius": 1
},
],
node_id_cb=lambda node: node["id"],
parent_id_cb=lambda node: node["parent_id"],
)
self.one_dim_neuron_data = Data(self.one_dim_neuron)
self.neurite_features = specialize(
bf.num_outer_bifurcations,
{AxonSpec, ApicalDendriteSpec, BasalDendriteSpec}
)
def setUp(self):
# Create an Axon that extends y 100 to 120
# and Basal Dendrite that extends y 100 to 110 and 100 to 80
# So that 3/4 axon nodes overlap, 1/4 are above basal
# and that 3/6 basal are below, and 3/6 overlap
self.one_dim_neuron = Morphology(
[
{
"id": 0,
"parent_id": -1,
"type": SOMA,
"x": 0,
"y": 100,
"z": 0,
"radius": 10
},
# Axon y 100 to 150
{
"id": 1,
"parent_id": 0,
"type": AXON,
"x": 0,
"y": 101,
"z": 0,
"radius": 3
},
{
"id": 2,
"parent_id": 1,
"type": AXON,
"x": 0,
"y": 102,
"z": 0,
"radius": 3
},
{
"id": 3,
"parent_id": 2,
"type": AXON,
"x": 0,
"y": 110,
"z": 0,
"radius": 3
},
{
"id": 4,
"parent_id": 3,
"type": AXON,
"x": 0,
"y": 120,
"z": 0,
"radius": 3
},
{
"id": 11,
"parent_id": 0,
"type": BASAL_DENDRITE,
"x": 0,
"y": 101,
"z": 0,
"radius": 3
},
{
"id": 12,
"parent_id": 11,
"type": BASAL_DENDRITE,
"x": 0,
"y": 102,
"z": 0,
"radius": 3
},
{
"id": 13,
"parent_id": 12,
"type": BASAL_DENDRITE,
"x": 0,
"y": 110,
"z": 0,
"radius": 3
},
# Basal Dendrite y 100 to 80
{
"id": 14,
"parent_id": 12,
"type": BASAL_DENDRITE,
"x": 0,
"y": 99,
"z": 0,
"radius": 3
},
{
"id": 15,
"parent_id": 14,
"type": BASAL_DENDRITE,
"x": 0,
"y": 90,
"z": 0,
"radius": 3
},
{
"id": 16,
"parent_id": 15,
"type": BASAL_DENDRITE,
"x": 0,
"y": 80,
"z": 0,
"radius": 3
},
],
node_id_cb=lambda node: node["id"],
parent_id_cb=lambda node: node["parent_id"],
)
self.one_dim_neuron_data = Data(self.one_dim_neuron)
self.overlap_features = nested_specialize(
ol.overlap,
[
NEURITE_SPECIALIZATIONS, #.remove(AllNeuriteSpec),
NEURITE_COMPARISON_SPECIALIZATIONS
] #.remove(AllNeuriteCompareSpec)]
)