def cell_definition(self, **kwargs) -> Cell:
cell = Cell(name="cell")
morpho_path = os.path.join(path, "..",
"commons/morphologies/swc/my.swc")
cell.load_morpho(filepath=morpho_path)
cell.insert("pas")
cell.insert("hh")
return cell
def cell_function():
cell = Cell(name="cell")
morpho_path = os.path.join(path, "..", "commons/morphologies/asc/cell1.asc")
cell.load_morpho(filepath=morpho_path)
cell.insert("pas")
cell.insert("hh")
cell.make_spike_detector(seg=cell.filter_secs("soma")(0.5))
return cell
def test_distance(self):
path = os.path.dirname(os.path.abspath(__file__))
filepath = os.path.join(path, "..",
"commons/morphologies/asc/cell1.asc")
cell = Cell("cell")
cell.load_morpho(filepath=filepath)
soma = cell.filter_secs("soma")
# Filter sections by distance to the soma (return only those distance > 1000 um)
far_secs = cell.filter_secs(
obj_filter=lambda s: h.distance(soma.hoc(0.5), s.hoc(0.5)) > 1000)
self.assertEqual(len(far_secs), 32)
def setUpClass(cls):
morpho_path = os.path.join(path, "..",
"commons/morphologies/asc/cell2.asc")
# Create cell
cell = Cell(name="cell")
cell.load_morpho(filepath=morpho_path)
cell.insert("pas")
cell.insert("hh")
soma = cell.filter_secs("soma")
dend = cell.filter_secs("apic[10]")
syn = cell.add_synapse(source=None, mod_name="ExpSyn", seg=dend(0.5))
# Prepare EPSP and AP (IClamp) protocols
experiment = Experiment(iti=40)
experiment.add_epsp(num=3,
synapse=syn,
init=20,
interval=20,
weight=0.02)
experiment.add_iclamp(num=3,
segment=soma(0.5),
init=60,
interval=20,
dur=3,
amp=1.6)
experiment.build()
# Prepare plots
rec = Record([soma(0.5), dend(0.5)], variables='v')
# Run
sim = Simulation(init_v=-70,
warmup=20,
with_neuron_gui=False,
constant_timestep=True)
sim.run(runtime=100)
cls.v_soma = rec.as_numpy('v', segment_name=soma(.5).name)
cls.v_apic = rec.as_numpy('v', segment_name=dend(.5).name)
syn.remove_immediate_from_neuron()
soma.remove_immediate_from_neuron()
dend.remove_immediate_from_neuron()
rec.remove_immediate_from_neuron()
experiment.remove_immediate_from_neuron()
cell.remove_immediate_from_neuron()
sim.remove_immediate_from_neuron()
cls.sections_left = len(list(h.allsec()))
import os
import matplotlib.pyplot as plt
from neuronpp.cells.cell import Cell
from neuronpp.utils.simulation import Simulation
from neuronpp.utils.record import Record
from neuronpp.utils.iclamp import IClamp
from neuronpp.utils.utils import make_shape_plot
from neuronpp.core.cells.netstim_cell import NetStimCell
# Create cell
cell = Cell(name="cell")
path = os.path.dirname(os.path.abspath(__file__))
morpho_path = os.path.join(path, "..", "commons/morphologies/asc/cell2.asc")
cell.load_morpho(filepath=morpho_path)
cell.insert("pas")
cell.insert("hh")
# Create stim and synapses
ns_cell = NetStimCell("stim_cell")
ns = ns_cell.make_netstim(start=30, number=5, interval=10)
syns = cell.add_synapses_with_spine(source=ns,
secs=cell.filter_secs("apic"),
mod_name="ExpSyn",
netcon_weight=0.01,
delay=1,
number=100)
soma = cell.filter_secs("soma")
def cell_template():
cell = Cell(name="cell")
cell.load_morpho(filepath=morpho_path)
cell.insert("pas")
cell.insert("hh")
return cell
class TestSimulation(unittest.TestCase):
def setUp(self):
"""
Setup call after each test, however from the NEURON point of view - all created HOC
objects exist, so each new call of setUp() creates a separated new cell on which tests are
performed
"""
morpho_path = os.path.join(path, "..", "commons/morphologies/asc/cell2.asc")
self.cell = Cell(name="cell")
self.cell.load_morpho(filepath=morpho_path)
self.cell.insert("pas")
self.cell.insert("hh")
self.soma = self.cell.filter_secs("soma")
self.apic1 = self.cell.filter_secs('apic[1]')
def tearDown(self):
self.soma.remove_immediate_from_neuron()
self.apic1.remove_immediate_from_neuron()
self.cell.remove_immediate_from_neuron()
l = len(list(h.allsec()))
if len(list(h.allsec())) != 0:
raise RuntimeError("Not all section have been removed after teardown. "
"Sections left: %s" % l)
def test_empty_method(self):
sim = Simulation()
self.assertFalse(sim.is_neuron_empty())
self.soma.remove_immediate_from_neuron()
self.apic1.remove_immediate_from_neuron()
self.cell.remove_immediate_from_neuron()
self.assertTrue(sim.is_neuron_empty())
def test_size_method(self):
sim = Simulation()
self.assertEqual(198, sim.size)
self.soma.remove_immediate_from_neuron()
self.apic1.remove_immediate_from_neuron()
self.cell.remove_immediate_from_neuron()
self.assertEqual(0, sim.size)
def test_dt(self):
rec = Record(self.soma(0.5))
sim = Simulation(dt=10)
sim.run(100)
r1 = rec.as_numpy('v')
sim = Simulation(dt=0.01)
sim.run(100)
r2 = rec.as_numpy('v')
sim.remove_immediate_from_neuron()
rec.remove_immediate_from_neuron()
self.assertEqual(11, r1.size)
self.assertEqual(10001, r2.size)
def test_init_v(self):
rec = Record(self.soma(0.5))
sim = Simulation(init_v=-100)
sim.run(100)
r1 = rec.as_numpy('v')
sim = Simulation(init_v=100)
sim.run(100)
r2 = rec.as_numpy('v')
sim.remove_immediate_from_neuron()
rec.remove_immediate_from_neuron()
self.assertEqual(-100, r1.records[0])
self.assertEqual(100, r2.records[0])
def test_timestep_constant(self):
rec = Record(self.soma(0.5))
sim = Simulation(constant_timestep=True, dt=1)
sim.run(100)
r1 = rec.as_numpy('v')
sim = Simulation(constant_timestep=False, dt=1)
sim.run(100)
r2 = rec.as_numpy('v')
sim = Simulation(constant_timestep=False, dt=10)
sim.run(100)
r3 = rec.as_numpy('v')
sim = Simulation(constant_timestep=False, dt=0.0001)
sim.run(100)
r4 = rec.as_numpy('v')
sim.remove_immediate_from_neuron()
rec.remove_immediate_from_neuron()
self.assertEqual(101, r1.size)
self.assertEqual(188, r2.size)
self.assertEqual(180, r3.size)
self.assertEqual(189, r4.size)
def test_warmup(self):
rec = Record(self.soma(0.5))
value_error = False
try:
sim = Simulation(warmup=-100)
sim.run(100)
r1 = rec.as_numpy('v')
except ValueError:
value_error = True
self.assertTrue(value_error)
sim = Simulation(warmup=100, dt=1)
sim.run(100)
r2 = rec.as_numpy('v')
sim = Simulation(warmup=100, dt=1, warmup_dt=1)
sim.run(100)
r3 = rec.as_numpy('v')
sim.remove_immediate_from_neuron()
rec.remove_immediate_from_neuron()
self.assertEqual(111, r2.size)
self.assertEqual(201, r3.size)
def test_netstim_before_sim(self):
"""
NetStim run in a regular way before Simulation run, in this cale (netcon weight=1.0)
we have spike of the soma.
However NetStim start is in the absolute time.
"""
# Netstim to synapse
stim = NetStimCell("stim").add_netstim(start=25, number=10, interval=2)
self.cell.add_synapse(source=stim, netcon_weight=1.0, mod_name="ExpSyn", delay=1,
seg=self.apic1(0.5))
# Record
rec = Record(self.soma(0.5))
# Run
sim = Simulation(init_v=-70, warmup=20)
sim.run(1)
sim.run(100)
r = rec.as_numpy(variable="v")
stim.remove_immediate_from_neuron()
sim.remove_immediate_from_neuron()
rec.remove_immediate_from_neuron()
# Make assertions
self.assertEqual(4051, r.size)
self.assertEqual(34.5205, round(r.records.max(), 4))
self.assertEqual(-75.3053, round(r.records.min(), 4))
self.assertEqual(319, r.records.argmax())
# time in ms of max mV value
self.assertEqual(27.725, round(r.time[r.records.argmax()], 4))
def test_netcon_event_before_sim(self):
"""
Netcon created before sim init or start is not effective and should return error
"""
sim = Simulation()
sim.reinit()
syn = self.cell.add_synapse(source=None, netcon_weight=1.0, mod_name="ExpSyn", delay=1,
seg=self.apic1(0.5))
error = False
try:
syn.make_event(50)
except ConnectionRefusedError:
error = True
self.assertTrue(error)
def test_netcon_event_after_sim(self):
syn = self.cell.add_synapse(source=None, netcon_weight=1.0, mod_name="ExpSyn", delay=1,
seg=self.apic1(0.5))
# Record
rec = Record(self.soma(0.5))
# Run
sim = Simulation(init_v=-70, warmup=20)
sim.run(1)
syn.make_event(50)
sim.run(100)
r = rec.as_numpy(variable="v")
syn.remove_immediate_from_neuron()
sim.remove_immediate_from_neuron()
rec.remove_immediate_from_neuron()
# Make assertions
self.assertEqual(4051, r.size)
self.assertEqual(34.4582, round(r.records.max(), 4))
self.assertEqual(-75.3478, round(r.records.min(), 4))
self.assertEqual(2159, r.records.argmax())
# time in ms of max mV value
self.assertEqual(73.725, round(r.time[r.records.argmax()], 4))
def test_netstim_after_sim(self):
"""
NetStim created after simulation run has no effect, it won't go on this simulation at all.
However NetStim start is in the absolute time.
"""
# Record
rec = Record(self.soma(0.5))
# Run
sim = Simulation(init_v=-70, warmup=20)
sim.run(1)
# Netstim to synapse
stim = NetStimCell("stim").add_netstim(start=25, number=10, interval=2)
self.cell.add_synapse(source=stim, netcon_weight=0.5, mod_name="ExpSyn", delay=1,
seg=self.apic1(0.5))
sim.run(100)
r = rec.as_numpy(variable="v")
# Make assertions
self.assertEqual(4051, r.size)
self.assertEqual(-67.1917, round(r.records.max(), 4))
self.assertEqual(-70.0, round(r.records.min(), 4))
self.assertEqual(3, r.records.argmax())
# time in ms of max mV value
self.assertEqual(6, r.time[r.records.argmax()])
stim.remove_immediate_from_neuron()
sim.remove_immediate_from_neuron()
rec.remove_immediate_from_neuron()
def test_iclamp_before_sim(self):
"""
IClamp works in a regular way before simulation run. in this case (amplitude 3 pA)
we have spike at the soma.
However IClamp delay is in the absolute time.
"""
# Record
rec = Record(self.soma(0.5))
# IClamp to soma
iclamp = IClamp(segment=self.soma(0.5))
iclamp.stim(delay=25, dur=3, amp=3)
# Run
sim = Simulation(init_v=-70, warmup=20)
sim.run(1)
sim.run(100)
r = rec.as_numpy(variable="v")
sim.remove_immediate_from_neuron()
rec.remove_immediate_from_neuron()
iclamp.remove_immediate_from_neuron()
# Make assertions
self.assertEqual(4051, r.size)
self.assertEqual(34.3815, round(r.records.max(), 4))
self.assertEqual(-75.3247, round(r.records.min(), 4))
self.assertEqual(330, r.records.argmax())
# time in ms of max mV value
self.assertEqual(28, round(r.time[r.records.argmax()], 4))
def test_iclamp_after_sim(self):
"""
IClamp works in a regular way after simulation run. in this case (amplitude 3 pA)
we have spike at the soma.
However IClamp delay is in the absolute time.
"""
# Record
rec = Record(self.soma(0.5))
# Run
sim = Simulation(init_v=-70, warmup=20)
sim.run(1)
# IClamp to soma
iclamp = IClamp(segment=self.soma(0.5))
iclamp.stim(delay=25, dur=3, amp=3)
sim.run(100)
r = rec.as_numpy(variable="v")
sim.remove_immediate_from_neuron()
rec.remove_immediate_from_neuron()
iclamp.remove_immediate_from_neuron()
# Make assertions
self.assertEqual(4051, r.size)
self.assertEqual(34.3815, round(r.records.max(), 4))
self.assertEqual(-75.3247, round(r.records.min(), 4))
self.assertEqual(330, r.records.argmax())
# time in ms of max mV value
self.assertEqual(28, round(r.time[r.records.argmax()], 4))
def test_2_runs(self):
"""
Test setup for 2 cells and their records which should be the same.
After each creation of the Simulation object, the Record object is cleaned up
(inside vector is empty) however on other Hoc object is removed eg. Sections.
That means - each new sections and cell are retained in the current NEURON run.
"""
def run_and_get_rec():
rec = Record(self.soma(0.5))
iclamp = IClamp(segment=self.soma(0.5))
iclamp.stim(delay=25, dur=3, amp=3)
sim = Simulation(init_v=-70, warmup=20)
sim.run(100)
return rec
rec1 = run_and_get_rec()
r1 = rec1.as_numpy('v').records
self.tearDown()
self.setUp()
rec2 = run_and_get_rec()
r2 = rec2.as_numpy('v').records
sim = Simulation(init_v=-70, warmup=20)
sim.run(100)
# Make assertions
self.assertEqual(4011, r1.size)
self.assertEqual(4011, r2.size)
self.assertTrue(np.alltrue(r1 == r2))
def test_record_before_sim(self):
"""
Record created before simulation run is full of data
"""
# Record
rec = Record(self.soma(0.5))
# IClamp to soma
iclamp = IClamp(segment=self.soma(0.5))
iclamp.stim(delay=25, dur=3, amp=3)
# Run
sim = Simulation(init_v=-70, warmup=20)
sim.run(1)
print(h.t)
sim.run(100)
r = rec.as_numpy(variable="v")
# Make assertions
self.assertEqual(4051, r.size)
self.assertEqual(34.3815, round(r.records.max(), 4))
self.assertEqual(-75.3247, round(r.records.min(), 4))
self.assertEqual(330, r.records.argmax())
# time in ms of max mV value
self.assertEqual(28, round(r.time[r.records.argmax()], 4))
def test_record_after_sim(self):
"""
record created after simulation run is empty
"""
# IClamp to soma
iclamp = IClamp(segment=self.soma(0.5))
iclamp.stim(delay=25, dur=3, amp=3)
# Run
sim = Simulation(init_v=-70, warmup=20)
sim.run(1)
print(h.t)
# Record
rec = Record(self.soma(0.5))
sim.run(100)
r = rec.as_numpy(variable="v")
# Make assertion
self.assertEqual(0, r.size)
import os
from neuronpp.utils.simulation import Simulation
from neuronpp.cells.cell import Cell
from neuronpp.utils.record import Record
from neuronpp.core.cells.netstim_cell import NetStimCell
path = os.path.dirname(os.path.abspath(__file__))
model_path1 = os.path.join(path, "..", "commons/mods/ebner2019")
model_path2 = os.path.join(path, "..", "commons/morphologies/swc/my.swc")
# Prepare cell
cell = Cell(name="cell", compile_paths=model_path1)
cell.load_morpho(filepath=model_path2)
cell.add_sec("dend[1]", diam=10, l=10, nseg=10)
cell.connect_secs(source="dend[1]", target="soma")
cell.insert("pas")
cell.insert("hh")
# Two examples of synapses with NetStim:
stim_cell = NetStimCell("stim_cell")
stim = stim_cell.make_netstim(start=250, number=30, interval=1)
soma = cell.filter_secs("soma")
# 1) Hoc-style synapse
pp = cell.add_point_process(mod_name="ExpSyn", seg=soma(0.5))
cell.add_netcon(source=stim, point_process=pp, netcon_weight=0.01, delay=1)
# 2) Recommended synapse
syn1 = cell.add_synapse(source=stim,
import os
from neuron import h
from neuronpp.cells.cell import Cell
path = os.path.dirname(os.path.abspath(__file__))
filepath = os.path.join(path, "..",
"commons/morphologies/asc/cell1.asc")
cell = Cell("cell")
cell.load_morpho(filepath=filepath)
soma = cell.filter_secs("soma")
# Filter sections by distance to the soma (return only those distance > 1000 um)
far_secs = cell.filter_secs(hoc=lambda s: h.distance(soma(0.5).hoc, s(0.5)) > 1000)
# Create a list of distances to check if it works well
distances = [(h.distance(soma(0.5).hoc, s(0.5).hoc), s.name) for s in far_secs]
# Print results
print(len(far_secs))
for d in distances:
print(d)
from neuronpp.cells.cell import Cell
from neuronpp.utils.record import Record
from neuronpp.utils.experiment import Experiment
from neuronpp.utils.simulation import Simulation
# Create cell
cell = Cell(name="cell")
cell.load_morpho(filepath="../commons/morphologies/asc/cell2.asc")
cell.insert("pas")
cell.insert("hh")
soma = cell.filter_secs("soma")
dend = cell.filter_secs("apic[10]")
syn = cell.add_synapse(source=None, mod_name="ExpSyn", seg=dend(0.5))
# Prepare EPSP and AP (IClamp) protocols
experiment = Experiment(iti=40)
experiment.add_epsp(num=3, synapse=syn, init=20, interval=20, weight=0.02)
experiment.add_iclamp(num=3,
segment=soma(0.5),
init=60,
interval=20,
dur=3,
amp=1.6)
experiment.build()
# Prepare plots
rec = Record([soma(0.5), dend(0.5)], variables='v')
# Run
sim = Simulation(init_v=-70,
