def test_population_units(self, stage="place-pop-unit-random"):
network_path = os.path.join(os.path.dirname(__file__), "networks",
"network_place_pop_unit_random")
cnc = SnuddaInit(struct_def={}, network_path=network_path)
cnc.define_striatum(num_dSPN=1000,
num_iSPN=1000,
num_FS=20,
num_LTS=0,
num_ChIN=0,
volume_type="cube")
cnc.add_population_unit_random(structure_name="Striatum",
neuron_types=["dSPN", "iSPN"],
fraction_of_neurons=0.5)
cnc.add_population_unit_random(structure_name="Striatum",
neuron_types=["dSPN", "iSPN"],
fraction_of_neurons=0.2)
cnc.add_population_unit_random(structure_name="Striatum",
neuron_types=["dSPN"],
fraction_of_neurons=0.3)
cnc.add_population_unit_random(structure_name="Striatum",
neuron_types=["iSPN"],
fraction_of_neurons=0.15)
cnc.add_population_unit_random(structure_name="Striatum",
neuron_types=["iSPN"],
fraction_of_neurons=0.15,
unit_id=10)
cnc.write_json()
npn = SnuddaPlace(network_path=network_path,
h5libver="latest",
verbose=True)
npn.parse_config()
npn.write_data()
def test_init(self):
with self.subTest(stage="init_cube"):
network_path = os.path.join(os.path.dirname(__file__), "networks",
"network_testing_init_cube")
config_name = os.path.join(network_path, "network-config.json")
cnc = SnuddaInit(struct_def={}, config_file=config_name)
cnc.define_striatum(num_dSPN=47500,
num_iSPN=47500,
num_FS=1300,
num_LTS=0,
num_ChIN=0,
volume_type="cube")
cnc.write_json()
# TODO: This only checks that the code runs. Add check for output
with self.subTest(stage="init_slice"):
network_path = os.path.join(os.path.dirname(__file__), "networks",
"network_testing_init_slice")
config_name = os.path.join(network_path)
cnc = SnuddaInit(struct_def={}, network_path=network_path)
cnc.define_striatum(num_dSPN=47500,
num_iSPN=47500,
num_FS=1300,
num_LTS=0,
num_ChIN=0,
volume_type="slice")
cnc.write_json()
with self.subTest(stage="init_full"):
network_path = os.path.join(os.path.dirname(__file__), "networks",
"network_testing_init_full")
config_name = os.path.join(network_path, "network-config.json")
cnc = SnuddaInit(struct_def={},
config_file=config_name,
random_seed=123)
cnc.define_striatum(num_neurons=1670000)
cnc.write_json()
with self.subTest(stage="population-unit-random"):
network_path = os.path.join(os.path.dirname(__file__), "networks",
"network_pop_unit_random")
cnc = SnuddaInit(struct_def={}, network_path=network_path)
cnc.define_striatum(num_dSPN=1000,
num_iSPN=1000,
num_FS=20,
num_LTS=0,
num_ChIN=0,
volume_type="slice")
cnc.add_population_unit_random(structure_name="Striatum",
neuron_types=["dSPN", "iSPN"],
fraction_of_neurons=0.5)
cnc.add_population_unit_random(structure_name="Striatum",
neuron_types=["dSPN", "iSPN"],
fraction_of_neurons=0.2)
cnc.add_population_unit_random(structure_name="Striatum",
neuron_types=["dSPN"],
fraction_of_neurons=0.3)
cnc.add_population_unit_random(structure_name="Striatum",
neuron_types=["iSPN"],
fraction_of_neurons=0.15)
cnc.add_population_unit_random(structure_name="Striatum",
neuron_types=["iSPN"],
fraction_of_neurons=0.15,
unit_id=10)
cnc.write_json()
with self.subTest(stage="population-unit-sphere"):
network_path = os.path.join(os.path.dirname(__file__), "networks",
"network_pop_unit_sphere")
cnc = SnuddaInit(struct_def={}, network_path=network_path)
cnc.define_striatum(num_dSPN=10000,
num_iSPN=10000,
num_FS=200,
num_LTS=0,
num_ChIN=0,
volume_type="slice")
cnc.add_population_unit_density(
structure_name="Striatum",
neuron_types=["dSPN", "iSPN"],
unit_centre=[0, 0, 0],
probability_function="(d < 100e-6)*1")
cnc.add_population_unit_density(
structure_name="Striatum",
neuron_types=["dSPN", "iSPN"],
unit_centre=[300e-6, 0, 0],
probability_function="exp(-d/200e-6)")
cnc.add_population_unit_density(
structure_name="Striatum",
neuron_types=["dSPN"],
unit_centre=[0, 300e-6, 0],
probability_function="exp(-d/150e-6)")
cnc.write_json()