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Added to #15 more test cases: multiple branch, smaller chunks, loops …
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…within cell type and across cs, cs with same transmitter
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@danilobenozzo
danilobenozzo committed Jul 31, 2024
1 parent af54424 commit f83cd5c
Showing 1 changed file with 362 additions and 3 deletions.
365 changes: 362 additions & 3 deletions tests/test_neuron.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@
import unittest
from copy import copy

from patch import p
from arborize import define_model
from bsb.core import Scaffold
from bsb.services import MPI
Expand Down Expand Up @@ -102,10 +103,10 @@ def setUp(self):
)
self.network.compile()

def test_4ch_all_to_all(self):
def test_4ch_manual(self):
"""
Tests runnability of the NEURON adapter with 4 chunks filled with 100 single
compartment HH cells and ExpSyn synapses connected all to all
Tests runnability of the NEURON adapter with 4 chunks filled with 12x3 single
compartment HH cells and ExpSyn synapses connected manually
"""
sim = self.network.simulations.test
adapter = get_simulation_adapter(sim.simulator)
Expand Down Expand Up @@ -170,3 +171,361 @@ def test_4ch_all_to_all(self):
],
receiving_cells,
)

@unittest.skipIf(not neuron_installed(), "NEURON is not installed")
class TestNeuronSmallChunk(
RandomStorageFixture,
ConfigFixture,
NetworkFixture,
MorphologiesFixture,
unittest.TestCase,
config="chunked",
morpho_filters=["2comp"],
engine_name="hdf5",
):
def setUp(self):
super().setUp()
p.parallel.gid_clear()
self.network.network.chunk_size = [10, 10, 10]
for ct in self.network.cell_types.values():
ct.spatial.morphologies = ["2comp"]
hh_soma = {
"cable_types": {
"soma": {
"cable": {"Ra": 10, "cm": 1},
"mechanisms": {"pas": {}, "hh": {}},
}
},
"synapse_types": {"ExpSyn": {}},
}
self.network.simulations.add(
"test",
simulator="neuron",
duration=1000,
resolution=0.1,
temperature=32,
cell_models=dict(
A=ArborizedModel(model=hh_soma),
B=ArborizedModel(model=hh_soma),
C=ArborizedModel(model=hh_soma),
),
connection_models=dict(
A_to_B=TransceiverModel(synapses=[dict(synapse="ExpSyn")]),
B_to_C=TransceiverModel(synapses=[dict(synapse="ExpSyn")]),
C_to_A=TransceiverModel(synapses=[dict(synapse="ExpSyn")]),
),
devices=dict(),
)
self.network.compile()

def test_smallch_manual(self):
"""
Tests runnability of the NEURON adapter with 500 chunks filled with 12x3 single
compartment HH cells and ExpSyn synapses manually connected
"""
sim = self.network.simulations.test
adapter = get_simulation_adapter(sim.simulator)
simdata = adapter.prepare(sim)
transmitting_cells = sorted(
itertools.chain.from_iterable(
MPI.allgather(
[
(model.name, cell.id, transmitter.gid)
for model, pop in simdata.populations.items()
for cell in pop
if (
transmitter := getattr(cell.sections[0], "_transmitter", None)
)
]
)
)
)
receiving_cells = sorted(
itertools.chain.from_iterable(
MPI.allgather(
[
(model.name, cell.id, synapse.gid)
for model, pop in simdata.populations.items()
for cell in pop
for synapse in getattr(cell.sections[0], "synapses", [])
]
)
)
)
self.assertEqual(
[
# A to B
("A", 0, 0),
("A", 1, 1),
("A", 3, 2),
("A", 5, 3),
# B to C
("B", 5, 4),
# C to A
("C", 1, 5),
("C", 5, 6),
],
transmitting_cells,
)
self.assertEqual(
[
# C to A
("A", 1, 6),
("A", 5, 5),
("A", 11, 6),
# A to B
("B", 0, 0),
("B", 0, 1),
("B", 2, 3),
("B", 3, 1),
("B", 8, 2),
# B to C
("C", 9, 4),
("C", 10, 4),
("C", 11, 4),
],
receiving_cells,
)

@unittest.skipIf(not neuron_installed(), "NEURON is not installed")
class TestNeuronMultiBranch(
RandomStorageFixture,
ConfigFixture,
NetworkFixture,
MorphologiesFixture,
unittest.TestCase,
config="multi",
morpho_filters=["3branch"],
engine_name="hdf5",
):
def setUp(self):
super().setUp()
p.parallel.gid_clear()
for ct in self.network.cell_types.values():
ct.spatial.morphologies = ["3branch"]
hh_soma = {
"cable_types": {
"soma": {
"cable": {"Ra": 10, "cm": 1},
"mechanisms": {"pas": {}, "hh": {}},
}
},
"synapse_types": {"ExpSyn": {}},
}
self.network.simulations.add(
"test",
simulator="neuron",
duration=1000,
resolution=0.1,
temperature=32,
cell_models=dict(
A=ArborizedModel(model=hh_soma),
B=ArborizedModel(model=hh_soma),
C=ArborizedModel(model=hh_soma),
),
connection_models=dict(
A_to_B=TransceiverModel(synapses=[dict(synapse="ExpSyn")]),
B_to_C=TransceiverModel(synapses=[dict(synapse="ExpSyn")]),
C_to_A=TransceiverModel(synapses=[dict(synapse="ExpSyn")]),
),
devices=dict(),
)
self.network.compile()

def test_500ch_multibranch_manualconn(self):
"""
Tests runnability of the NEURON adapter with 500 chunks filled with 12x3 single
compartment HH cells and ExpSyn synapses connected manually
"""
sim = self.network.simulations.test
adapter = get_simulation_adapter(sim.simulator)
simdata = adapter.prepare(sim)
transmitting_cells = sorted(
itertools.chain.from_iterable(
MPI.allgather(
[
(model.name, cell.id, i_sec, transmitter.gid)
for model, pop in simdata.populations.items()
for cell in pop
for i_sec, sec_i in enumerate(cell.sections)
if (
transmitter := getattr(cell.sections[i_sec], "_transmitter", None)
)
]
)
)
)
receiving_cells = sorted(
itertools.chain.from_iterable(
MPI.allgather(
[
(model.name, cell.id, i_sec, synapse.gid)
for model, pop in simdata.populations.items()
for cell in pop
for i_sec, sec_i in enumerate(cell.sections)
for synapse in getattr(cell.sections[i_sec], "synapses", [])
]
)
)
)
self.assertEqual(
[
# A
("A", 0, 0, 0),
("A", 0, 1, 1),
("A", 3, 1, 2),
("A", 5, 0, 3),
# B
("B", 5, 0, 4),
# C
("C", 1, 0, 5),
("C", 5, 0, 6),
],
transmitting_cells,
)
self.assertEqual(
[
# C to A
("A", 1, 0, 6),
("A", 5, 0, 5),
("A", 11, 0, 6),
# A to B
("B", 3, 0, 0),
("B", 3, 0, 1),
("B", 5, 0, 2),
("B", 8, 0, 2),
("B", 10, 1, 3),
# B to C
("C", 9, 0, 4),
("C", 10, 1, 4),
("C", 11, 0, 4),
],
receiving_cells,
)

@unittest.skipIf(not neuron_installed(), "NEURON is not installed")
class TestNeuronMultiBranchLoop(
RandomStorageFixture,
ConfigFixture,
NetworkFixture,
MorphologiesFixture,
unittest.TestCase,
config="complete",
morpho_filters=["3branch"],
engine_name="hdf5",
):
def setUp(self):
super().setUp()
p.parallel.gid_clear()
for ct in self.network.cell_types.values():
ct.spatial.morphologies = ["3branch"]
hh_soma = {
"cable_types": {
"soma": {
"cable": {"Ra": 10, "cm": 1},
"mechanisms": {"pas": {}, "hh": {}},
}
},
"synapse_types": {"ExpSyn": {}},
}
self.network.simulations.add(
"test",
simulator="neuron",
duration=1000,
resolution=0.1,
temperature=32,
cell_models=dict(
A=ArborizedModel(model=hh_soma),
B=ArborizedModel(model=hh_soma),
C=ArborizedModel(model=hh_soma),
),
connection_models=dict(
A_to_A=TransceiverModel(synapses=[dict(synapse="ExpSyn")]),
A_to_B=TransceiverModel(synapses=[dict(synapse="ExpSyn")]),
B_to_C=TransceiverModel(synapses=[dict(synapse="ExpSyn")]),
C_to_A=TransceiverModel(synapses=[dict(synapse="ExpSyn")]),
C_to_B=TransceiverModel(synapses=[dict(synapse="ExpSyn")]),
),
devices=dict(),
)
self.network.compile()

def test_500ch_manualloop(self):
"""
Tests runnability of the NEURON adapter with 500 chunks filled with 12x3 single
compartment HH cells and ExpSyn synapses connected manually with loop (within cell and cs)
"""
sim = self.network.simulations.test
adapter = get_simulation_adapter(sim.simulator)
simdata = adapter.prepare(sim)
transmitting_cells = sorted(
itertools.chain.from_iterable(
MPI.allgather(
[
(model.name, cell.id, i_sec, transmitter.gid)
for model, pop in simdata.populations.items()
for cell in pop
for i_sec, sec_i in enumerate(cell.sections)
if (
transmitter := getattr(cell.sections[i_sec], "_transmitter", None)
)
]
)
)
)
receiving_cells = sorted(
itertools.chain.from_iterable(
MPI.allgather(
[
(model.name, cell.id, i_sec, synapse.gid)
for model, pop in simdata.populations.items()
for cell in pop
for i_sec, sec_i in enumerate(cell.sections)
for synapse in getattr(cell.sections[i_sec], "synapses", [])
]
)
)
)
self.assertEqual(
[
# A
("A", 0, 0, 0),
("A", 0, 1, 1),
("A", 1, 0, 2),
("A", 3, 0, 3),
("A", 3, 1, 4),
("A", 5, 0, 5),
# B
("B", 5, 0, 6),
# C
("C", 1, 0, 7),
("C", 5, 0, 8),
],
transmitting_cells,
)
self.assertEqual(
[

("A", 0, 1, 0), # A to A
("A", 1, 0, 8), # C to A
("A", 3, 0, 2), # A to A
("A", 5, 0, 7), # C to A
("A", 7, 1, 0), # A to A
("A", 7, 1, 4), # A to A
("A", 11, 0, 8), # C to A
("B", 1, 0, 8), # C to B
# A to B
("B", 3, 0, 0),
("B", 3, 0, 1),
("B", 5, 0, 3),
("B", 5, 0, 7), # C to B
("B", 8, 0, 3), # A to B
("B", 10, 0, 5), # A to B
("B", 11, 0, 8), # C to B
# B to C
("C", 9, 0, 6),
("C", 10, 0, 6),
("C", 11, 0, 6),
],
receiving_cells,
)

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