def test_area(self):
d = Point3DWithDiam(x=0.2, y=2.4, z=3.5, diameter=0.6)
p = Point3DWithDiam(x=0.5, y=2.0, z=1.8, diameter=0.9)
seg = Segment(proximal=p, distal=d)
self.assertAlmostEqual(seg.surface_area, 4.19011944, places=7)
def generateRandomMorphology():
morphology = Morphology()
p = Point3DWithDiam(x=0, y=0, z=0, diameter=soma_diam)
d = Point3DWithDiam(x=soma_len, y=0, z=0, diameter=soma_diam)
soma = Segment(proximal=p, distal=d, name='Soma', id=0)
morphology.segments.append(soma)
parent_seg = soma
for dend_id in range(0, dend_num):
p = Point3DWithDiam(x=d.x, y=d.y, z=d.z, diameter=dend_diam)
d = Point3DWithDiam(x=p.x, y=p.y + dend_len, z=p.z, diameter=dend_diam)
dend = Segment(proximal=p,
distal=d,
name='Dend_%i' % dend_id,
id=1 + dend_id)
dend.parent = SegmentParent(segments=parent_seg.id)
parent_seg = dend
morphology.segments.append(dend)
morphology.id = "TestMorphology"
return morphology
def test_length(self):
d = Point3DWithDiam(x=0.2, y=2.4, z=3.5, diameter=0.6)
p = Point3DWithDiam(x=0.5, y=2.0, z=1.8, diameter=0.9)
seg = Segment(proximal=p, distal=d)
self.assertAlmostEqual(seg.length, 1.772004514, places=7)
def test_volume1(self):
diam = 1.
len = 1.
d = Point3DWithDiam(x=0, y=0, z=0, diameter=diam)
p = Point3DWithDiam(x=0, y=len, z=0, diameter=diam * 1.01)
seg = Segment(proximal=p, distal=d)
self.assertAlmostEqual(seg.volume, 0.793278324, places=7)
def test_length0(self):
diam = 1.
len = 1.
d = Point3DWithDiam(x=0, y=0, z=0, diameter=diam)
p = Point3DWithDiam(x=0, y=len, z=0, diameter=diam)
seg = Segment(proximal=p, distal=d)
self.assertAlmostEqual(seg.length, 1, places=7)
def test_area1(self):
diam = 1.
len = 1.
d = Point3DWithDiam(x=0, y=0, z=0, diameter=diam)
p = Point3DWithDiam(x=0, y=len, z=0, diameter=diam * 1.01)
seg = Segment(proximal=p, distal=d)
self.assertAlmostEqual(seg.surface_area, 3.15734008, places=7)
def test_volume0(self):
diam = 1.
len = 1.
d = Point3DWithDiam(x=0, y=0, z=0, diameter=diam)
p = Point3DWithDiam(x=0, y=len, z=0, diameter=diam)
seg = Segment(proximal=p, distal=d)
self.assertAlmostEqual(seg.volume,
math.pi * (diam / 2)**2 * len,
places=7)
def test_area0(self):
diam = 1.
len = 1.
d = Point3DWithDiam(x=0, y=0, z=0, diameter=diam)
p = Point3DWithDiam(x=0, y=len, z=0, diameter=diam)
seg = Segment(proximal=p, distal=d)
self.assertAlmostEqual(seg.surface_area,
math.pi * diam * len,
places=7)
def test_distal_coordinates(self):
distal_point = Point3DWithDiam(x=0.1, y=0.2, z=0.3)
seg = Segment(distal=distal_point)
self.assertEqual(seg.distal.x, 0.1)
self.assertEqual(seg.distal.y, 0.2)
self.assertEqual(seg.distal.z, 0.3)
def test_proximal_coordinates(self):
proximal_point = Point3DWithDiam(x=0.1, y=0.2, z=0.3)
seg = Segment(proximal=proximal_point)
self.assertEqual(seg.proximal.x, 0.1)
self.assertEqual(seg.proximal.y, 0.2)
self.assertEqual(seg.proximal.z, 0.3)
def add_segment(obj, p0, p1, name=None):
p = Point3DWithDiam(x=p0[0], y=p0[1], z=p0[2], diameter=p0[3])
d = Point3DWithDiam(x=p1[0], y=p1[1], z=p1[2], diameter=p1[3])
segid = len(obj.morphology.segments)
parent = None if segid == 0 else SegmentParent(segments=segid - 1)
segment = Segment(id=segid, proximal=p, distal=d, parent=parent)
if name:
segment.name = name
obj.morphology.segment_groups[0].members.append(Member(segments=segid))
obj.morphology.segments.append(segment)
return segment
def asPoint(nodeID):
""" Return the node as a Point3DWithDiam, in micrometers. """
p = points.get(nodeID)
if not p:
props = nodes[nodeID]
radius = props[2]
if radius < 0:
radius = 0.1 # FUTURE Will have to change
loc = props[1]
# Point in micrometers
p = Point3DWithDiam(loc[0] / 1000.0, loc[1] / 1000.0,
loc[2] / 1000.0, radius)
points[nodeID] = p
return p
def create_models(self):
self.generic_cell = Cell(id = "GenericCell")
morphology = Morphology()
morphology.id = "morphology_"+self.generic_cell.id
self.generic_cell.morphology = morphology
prox_point = Point3DWithDiam(x="0", y="0", z="0", diameter=self.get_bioparameter("cell_diameter").value)
dist_point = Point3DWithDiam(x="0", y="0", z=self.get_bioparameter("cell_length").value, diameter=self.get_bioparameter("cell_diameter").value)
segment = Segment(id="0",
name="soma",
proximal = prox_point,
distal = dist_point)
morphology.segments.append(segment)
self.generic_cell.biophysical_properties = BiophysicalProperties(id="biophys_"+self.generic_cell.id)
mp = MembraneProperties()
self.generic_cell.biophysical_properties.membrane_properties = mp
mp.init_memb_potentials.append(InitMembPotential(value=self.get_bioparameter("initial_memb_pot").value))
mp.specific_capacitances.append(SpecificCapacitance(value=self.get_bioparameter("specific_capacitance").value))
mp.spike_threshes.append(SpikeThresh(value=self.get_bioparameter("spike_thresh").value))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("leak_cond_density").value,
id="Leak_all",
ion_channel="Leak",
erev=self.get_bioparameter("leak_erev").value,
ion="non_specific"))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("k_slow_cond_density").value,
id="k_slow_all",
ion_channel="k_slow",
erev=self.get_bioparameter("k_slow_erev").value,
ion="k"))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("k_fast_cond_density").value,
id="k_fast_all",
ion_channel="k_fast",
erev=self.get_bioparameter("k_fast_erev").value,
ion="k"))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("ca_boyle_cond_density").value,
id="ca_boyle_all",
ion_channel="ca_boyle",
erev=self.get_bioparameter("ca_boyle_erev").value,
ion="ca"))
ip = IntracellularProperties()
self.generic_cell.biophysical_properties.intracellular_properties = ip
# NOTE: resistivity/axial resistance not used for single compartment cell models, so value irrelevant!
ip.resistivities.append(Resistivity(value="0.1 kohm_cm"))
# NOTE: Ca reversal potential not calculated by Nernst, so initial_ext_concentration value irrelevant!
species = Species(id="ca",
ion="ca",
concentration_model="CaPool",
initial_concentration="0 mM",
initial_ext_concentration="2E-6 mol_per_cm3")
ip.species.append(species)
self.exc_syn = GradedSynapse(id="exc_syn",
conductance = self.get_bioparameter("exc_syn_conductance").value,
delta = self.get_bioparameter("exc_syn_delta").value,
Vth = self.get_bioparameter("exc_syn_vth").value,
erev = self.get_bioparameter("exc_syn_erev").value,
k = self.get_bioparameter("exc_syn_k").value)
self.inh_syn = GradedSynapse(id="inh_syn",
conductance = self.get_bioparameter("inh_syn_conductance").value,
delta = self.get_bioparameter("inh_syn_delta").value,
Vth = self.get_bioparameter("inh_syn_vth").value,
erev = self.get_bioparameter("inh_syn_erev").value,
k = self.get_bioparameter("inh_syn_k").value)
self.elec_syn = GapJunction(id="elec_syn",
conductance = self.get_bioparameter("elec_syn_gbase").value)
self.offset_current = PulseGenerator(id="offset_current",
delay=self.get_bioparameter("unphysiological_offset_current_del").value,
duration=self.get_bioparameter("unphysiological_offset_current_dur").value,
amplitude=self.get_bioparameter("unphysiological_offset_current").value)
def cvt_pt(p):
from neuroml import Point3DWithDiam
return Point3DWithDiam(x=p.x, y=p.y, z=p.z, diameter=p.diameter)
def cvt_pt(p):
return Point3DWithDiam(x=p.x * WRL_UPSCALE,
y=p.y * WRL_UPSCALE,
z=p.z * WRL_UPSCALE,
diameter=p.diameter)
def create_cell():
"""Create the cell.
:returns: name of the cell nml file
"""
# Create the nml file and add the ion channels
hh_cell_doc = NeuroMLDocument(id="cell", notes="HH cell")
hh_cell_fn = "HH_example_cell.nml"
hh_cell_doc.includes.append(IncludeType(href=create_na_channel()))
hh_cell_doc.includes.append(IncludeType(href=create_k_channel()))
hh_cell_doc.includes.append(IncludeType(href=create_leak_channel()))
# Define a cell
hh_cell = Cell(id="hh_cell", notes="A single compartment HH cell")
# Define its biophysical properties
bio_prop = BiophysicalProperties(id="hh_b_prop")
# notes="Biophysical properties for HH cell")
# Membrane properties are a type of biophysical properties
mem_prop = MembraneProperties()
# Add membrane properties to the biophysical properties
bio_prop.membrane_properties = mem_prop
# Append to cell
hh_cell.biophysical_properties = bio_prop
# Channel density for Na channel
na_channel_density = ChannelDensity(id="na_channels", cond_density="120.0 mS_per_cm2", erev="50.0 mV", ion="na", ion_channel="na_channel")
mem_prop.channel_densities.append(na_channel_density)
# Channel density for k channel
k_channel_density = ChannelDensity(id="k_channels", cond_density="360 S_per_m2", erev="-77mV", ion="k", ion_channel="k_channel")
mem_prop.channel_densities.append(k_channel_density)
# Leak channel
leak_channel_density = ChannelDensity(id="leak_channels", cond_density="3.0 S_per_m2", erev="-54.3mV", ion="non_specific", ion_channel="leak_channel")
mem_prop.channel_densities.append(leak_channel_density)
# Other membrane properties
mem_prop.spike_threshes.append(SpikeThresh(value="-20mV"))
mem_prop.specific_capacitances.append(SpecificCapacitance(value="1.0 uF_per_cm2"))
mem_prop.init_memb_potentials.append(InitMembPotential(value="-65mV"))
intra_prop = IntracellularProperties()
intra_prop.resistivities.append(Resistivity(value="0.03 kohm_cm"))
# Add to biological properties
bio_prop.intracellular_properties = intra_prop
# Morphology
morph = Morphology(id="hh_cell_morph")
# notes="Simple morphology for the HH cell")
seg = Segment(id="0", name="soma", notes="Soma segment")
# We want a diameter such that area is 1000 micro meter^2
# surface area of a sphere is 4pi r^2 = 4pi diam^2
diam = math.sqrt(1000 / math.pi)
proximal = distal = Point3DWithDiam(x="0", y="0", z="0", diameter=str(diam))
seg.proximal = proximal
seg.distal = distal
morph.segments.append(seg)
hh_cell.morphology = morph
hh_cell_doc.cells.append(hh_cell)
pynml.write_neuroml2_file(nml2_doc=hh_cell_doc, nml2_file_name=hh_cell_fn, validate=True)
return hh_cell_fn
def create_generic_neuron_cell(self):
self.generic_neuron_cell = Cell(id="GenericNeuronCell")
morphology = Morphology()
morphology.id = "morphology_" + self.generic_neuron_cell.id
self.generic_neuron_cell.morphology = morphology
prox_point = Point3DWithDiam(
x="0",
y="0",
z="0",
diameter=self.get_bioparameter("cell_diameter").value)
dist_point = Point3DWithDiam(
x="0",
y="0",
z="0",
diameter=self.get_bioparameter("cell_diameter").value)
segment = Segment(id="0",
name="soma",
proximal=prox_point,
distal=dist_point)
morphology.segments.append(segment)
self.generic_neuron_cell.biophysical_properties = BiophysicalProperties(
id="biophys_" + self.generic_neuron_cell.id)
mp = MembraneProperties()
self.generic_neuron_cell.biophysical_properties.membrane_properties = mp
mp.init_memb_potentials.append(
InitMembPotential(
value=self.get_bioparameter("initial_memb_pot").value))
mp.specific_capacitances.append(
SpecificCapacitance(value=self.get_bioparameter(
"neuron_specific_capacitance").value))
mp.spike_threshes.append(
SpikeThresh(
value=self.get_bioparameter("neuron_spike_thresh").value))
mp.channel_densities.append(
ChannelDensity(cond_density=self.get_bioparameter(
"neuron_leak_cond_density").value,
id="Leak_all",
ion_channel="Leak",
erev=self.get_bioparameter("leak_erev").value,
ion="non_specific"))
mp.channel_densities.append(
ChannelDensity(cond_density=self.get_bioparameter(
"neuron_k_slow_cond_density").value,
id="k_slow_all",
ion_channel="k_slow",
erev=self.get_bioparameter("k_slow_erev").value,
ion="k"))
'''
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("neuron_k_fast_cond_density").value,
id="k_fast_all",
ion_channel="k_fast",
erev=self.get_bioparameter("k_fast_erev").value,
ion="k"))'''
mp.channel_densities.append(
ChannelDensity(cond_density=self.get_bioparameter(
"neuron_ca_simple_cond_density").value,
id="ca_simple_all",
ion_channel="ca_simple",
erev=self.get_bioparameter("ca_simple_erev").value,
ion="ca"))
ip = IntracellularProperties()
self.generic_neuron_cell.biophysical_properties.intracellular_properties = ip
# NOTE: resistivity/axial resistance not used for single compartment cell models, so value irrelevant!
ip.resistivities.append(Resistivity(value="0.1 kohm_cm"))
# NOTE: Ca reversal potential not calculated by Nernst, so initial_ext_concentration value irrelevant!
species = Species(id="ca",
ion="ca",
concentration_model="CaPool",
initial_concentration="0 mM",
initial_ext_concentration="2E-6 mol_per_cm3")
ip.species.append(species)
def test_distal_diameter(self):
distal_point = Point3DWithDiam(diameter=3.21)
seg = Segment(distal=distal_point)
self.assertEqual(seg.distal.diameter, 3.21)
def test_proximal_diameter(self):
proximal_point = Point3DWithDiam(diameter=3.21)
seg = Segment(proximal=proximal_point)
self.assertEqual(seg.proximal.diameter, 3.21)
def test_volume(self):
d = Point3DWithDiam(x=0.2, y=2.4, z=3.5, diameter=0.6)
p = Point3DWithDiam(x=0.5, y=2.0, z=1.8, diameter=0.9)
seg = Segment(proximal=p, distal=d)
self.assertAlmostEqual(seg.volume, 0.7932855820702964, places=7)
def cvt_pt(p):
return Point3DWithDiam(x=p.x, y=p.y, z=p.z, diameter=p.diameter)
def add_segment(cell,
prox,
dist,
name=None,
parent=None,
fraction_along=1.0,
group=None):
# type: (Cell, List[float], List[float], str, SegmentParent, float, SegmentGroup) -> Segment
"""Add a segment to the cell.
Convention: use axon_, soma_, dend_ prefixes for axon, soma, and dendrite
segments respectivey. This will allow this function to add the correct
neurolex IDs to the group.
The created segment is also added to the default segment groups that were
created by the `create_cell` function: "all", "dendrite_group",
"soma_group", "axon_group" if the convention is followed.
:param cell: cell to add segment to
:type cell: Cell
:param prox: proximal segment information
:type prox: list with 4 float entries: [x, y, z, diameter]
:param dist: dist segment information
:type dist: list with 4 float entries: [x, y, z, diameter]
:param name: name of segment
:type name: str
:param parent: parent segment
:type parent: SegmentParent
:param fraction_along: where the new segment is connected to the parent (0: distal point, 1: proximal point)
:type fraction_along: float
:param group: segment group to add the segment to
:type group: SegmentGroup
:returns: the created segment
"""
try:
if prox:
p = Point3DWithDiam(x=prox[0],
y=prox[1],
z=prox[2],
diameter=prox[3])
else:
p = None
except IndexError as e:
print_function("{}: prox must be a list of 4 elements".format(e))
try:
d = Point3DWithDiam(x=dist[0], y=dist[1], z=dist[2], diameter=dist[3])
except IndexError as e:
print_function("{}: dist must be a list of 4 elements".format(e))
segid = len(cell.morphology.segments)
sp = SegmentParent(segments=parent.id,
fraction_along=fraction_along) if parent else None
segment = Segment(id=segid, proximal=p, distal=d, parent=sp)
if name:
segment.name = name
if group:
seg_group = None
seg_group = get_seg_group_by_id(group, cell)
seg_group_all = get_seg_group_by_id("all", cell)
seg_group_default = None
neuro_lex_id = None
if "axon_" in group:
neuro_lex_id = neuro_lex_ids[
"axon"] # See http://amigo.geneontology.org/amigo/term/GO:0030424
seg_group_default = get_seg_group_by_id("axon_group", cell)
if "soma_" in group:
neuro_lex_id = neuro_lex_ids["soma"]
seg_group_default = get_seg_group_by_id("soma_group", cell)
if "dend_" in group:
neuro_lex_id = neuro_lex_ids["dend"]
seg_group_default = get_seg_group_by_id("dendrite_group", cell)
if seg_group is None:
seg_group = SegmentGroup(id=group, neuro_lex_id=neuro_lex_id)
cell.morphology.segment_groups.append(seg_group)
seg_group.members.append(Member(segments=segment.id))
# Ideally, these higher level segment groups should just include other
# segment groups using Include, which would result in smaller NML
# files. However, because these default segment groups are defined
# first, they are printed in the NML file before the new segments and their
# groups. The jnml validator does not like this.
# TODO: clarify if the order of definition is important, or if the jnml
# validator needs to be updated to manage this use case.
if seg_group_default:
seg_group_default.members.append(Member(segments=segment.id))
seg_group_all.members.append(Member(segments=segment.id))
cell.morphology.segments.append(segment)
return segment