def build(self):
"""Builds the nodes and edges for the network.
"""
self.net = NetworkBuilder("biophysical")
self.net.add_nodes(N=1,
pop_name='Pyrc',
potental='exc',
model_type='biophysical',
model_template='hoc:L5PCtemplate',
morphology=None)
self._build_exc()
self._build_inh()
self._save_nets()
self._make_rasters()
#Final build step.
build_env_bionet(
base_dir='./',
network_dir='./network',
dt=self.params["dt"],
tstop=self.params["time"]["stop"] * 1000.0,
report_vars=['v'],
dL=self.params["dL"], #target length (um) of segments
spikes_threshold=-10,
spikes_inputs=[('exc_stim', 'exc_stim_spikes.h5'),
('prox_inh_stim', 'prox_inh_stim_spikes.h5'),
('dist_inh_stim', 'dist_inh_stim_spikes.h5')],
components_dir='../biophys_components',
compile_mechanisms=False)
def build_sim():
from bmtk.builder.networks import NetworkBuilder
# My all active-model (does not work):
#Model ID 496497595
#Cell ID 487667205
# Other perisomatic model (available on Allen Brain Institute - CellTypes):
#Model ID 491623973
#Cell ID 490387590
print('BMTK import success')
net = NetworkBuilder('mcortex')
print('Network builder initiated')
# Testing other models: # Surprise, surprise, this does not work...
net.add_nodes(cell_name='Pvalb_490387590_m',
model_type='biophysical',
model_template='ctdb:Biophys1.hoc',
model_processing='aibs_perisomatic',
dynamics_params='491623973_fit.json',
morphology='Pvalb_490387590_m.swc')
''' # Standard
net.add_nodes(cell_name='Scnn1a_473845048',
potental='exc',
model_type='biophysical',
model_template='ctdb:Biophys1.hoc',
model_processing='aibs_perisomatic',
dynamics_params='472363762_fit.json',
morphology='Scnn1a_473845048_m.swc')
'''
print('Node added')
net.build()
net.save_nodes(output_dir='network')
for node in net.nodes():
print(node)
print('Node printed')
from bmtk.utils.sim_setup import build_env_bionet
print('Setting environment')
build_env_bionet(
base_dir='sim_ch01', # Where to save the scripts and config files
network_dir='network', # Location of directory containing network files
tstop=1200.0,
dt=0.1, # Run a simulation for 2000 ms at 0.1 ms intervals
report_vars=[
'v'
], # Tells simulator we want to record membrane potential and calcium traces
current_clamp={ # Creates a step current from 500.ms to 1500.0 ms
'amp': 0.61, # 0.12#0.610
'delay': 100.0, # 100, #500
'duration': 1000.0
},
include_examples=True, # Copies components files
compile_mechanisms=True # Will try to compile NEURON mechanisms
)
print('Build done')
def build(self):
"""Builds the nodes and edges for the network.
"""
np.random.seed(self.seed)
self._set_prefixed_directory("mechanisms")
self._set_prefixed_directory("templates")
self.net = NetworkBuilder("biophysical")
self.net.add_nodes(
N=1,
pop_name='Pyrc',
potental='exc',
model_type='biophysical',
dynamics_params=self.params["cell"]["dynamic_params"],
model_template=self.params["cell"]["model_template"],
model_processing=self.params["cell"]["model_processing"],
morphology=self.params["cell"]["morphology"])
self._build_exc()
self._build_inh()
self._save_nets()
self._make_rasters()
#Final build step.
build_env_bionet(
base_dir='./',
network_dir='./network',
dt=self.params["dt"],
tstop=self.params["time"]["stop"] * 1000.0,
report_vars=self.params["record_cellvars"]["vars"],
dL=self.params["dL"], #target length (um) of segments
spikes_threshold=-10,
file_current_clamp=self.file_current_clamp,
spikes_inputs=[('exc_stim', 'exc_stim_spikes.h5'),
('prox_inh_stim', 'prox_inh_stim_spikes.h5'),
('dist_inh_stim', 'dist_inh_stim_spikes.h5')],
components_dir='../biophys_components',
compile_mechanisms=True)
self._modify_jsons()
# Build and save our network
thalamus.build()
thalamus.save_nodes(output_dir='network')
exc_bg_bask.build()
exc_bg_bask.save_nodes(output_dir='network')
#
#print("External nodes and edges built")
t_sim = 10000.0
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(
base_dir='./',
network_dir='./network',
tstop=t_sim,
dt=0.05,
report_vars=['v'],
v_init=-70.0,
celsius=31.0,
spikes_inputs=[
(
'mthalamus', # Name of population which spikes will be generated for
'mthalamus_spikes.h5'),
('exc_bg_bask', 'exc_bg_bask_spikes.h5')
],
components_dir='components',
compile_mechanisms=True)
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(
base_dir='./', # Where to save the scripts and config files
components_dir='../biophys_components',
network_dir='./network', # Location of directory containing network files
tstop=3000.0,
dt=0.1, # Run a simulation for 2000 ms at 0.1 ms intervals
report_vars=['v'],
#clamp_reports=["se"], # Tells simulator we want to record membrane potential and calcium traces
current_clamp={ # Creates a step current from 500.ms to 1500.0 ms
'amp': 0.793,
#'amp': 0.346,
'delay': 700,
'duration': 2000,
'gids': "all"
},
spikes_threshold=-10,
# file_current_clamp={
# "input_file": "PN_IClamp/inputs/amps.h5"
# },
# se_voltage_clamp={
# "amps":[[-70, -70, -70], [-70, -70, -70]],
# "durations": [[2000, 2000, 2000], [2000, 2000, 2000]],
# 'gids': [0, 1],
# 'rs': [0.001, 0.01],
# 'name':"PN_se_clamp"
# },
compile_mechanisms=True # Will try to compile NEURON mechanisms
)
# from crop_raster import crop_raster
# crop_raster("rhythmic_inh_spikes.h5", 'inh_stim_spikes.h5', 120000, num_inh)
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(
base_dir='./',
network_dir='./network',
dt=0.1,
tstop=seconds * 1000.0,
report_vars=['v', 'cai'],
dL=5,
# current_clamp={ # Creates a step current from 500.ms to 1500.0 ms
# 'amp': 0.793,
# #'std': [0.0, 0.0],
# 'delay': 700,
# 'duration': 2000,
# 'gids':"0"
# },
# clamp_reports=['se'],#Records se clamp currents.
# se_voltage_clamp={
# "amps":[[0, 0, 0]],
# "durations": [[120000, 0, 0]],
# 'gids': [0],
# 'rs': [0.01],
# },
spikes_threshold=-10,
spikes_inputs=[('exc_stim', 'exc_stim_spikes.h5')
], #, ('inh_stim', 'inh_stim_spikes.h5')],
components_dir='../biophys_components',
compile_mechanisms=True)
model_type='biophysical',
model_template='hoc:IMG',
morphology='blank.swc')
net.build()
net.save_nodes(output_dir='network')
build_env_bionet(
base_dir='single_cell', # Where to save the scripts and config files
network_dir='network', # Location of directory containing network files
tstop=2000.0,
dt=0.1, # Run a simulation for 2000 ms at 0.1 ms intervals
v_init=-54,
report_vars=[
'v', 'ina', 'ik', 'ninf_k1', 'minf_na1', 'hinf_na1'
], # Tells simulator we want to record membrane potential and calcium traces
current_clamp={ # Creates a step current from 500.ms to 1500.0 ms
'amp': 0.5,
'delay': 500.0,
'duration': 750.0
},
include_examples=True, # Copies components files
compile_mechanisms=True # Will try to compile NEURON mechanisms
)
bionet.pyfunction_cache.add_cell_model(loadHOC,
directive='hoc',
model_type='biophysical')
conf = bionet.Config.from_json('single_cell/simulation_config.json')
conf.build_env()
shock.build()
shock.save_nodes(output_dir='network')
#from bmtk.utils.reports.spike_trains import PoissonSpikeGenerator
#from bmtk.utils.reports.spike_trains.spikes_file_writers import write_csv
#exc_psg = PoissonSpikeGenerator(population='exc_stim')
#exc_psg.add(node_ids=range(np.sum(num_exc)),
# firing_rate=int(exc_fr) / 1000,
# times=(200.0, 500.0))
#exc_psg.to_sonata('exc_stim_spikes.h5')
#inh_psg = PoissonSpikeGenerator(population='inh_stim')
#inh_psg.add(node_ids=range(np.sum(num_inh)),
# firing_rate=int(inh_fr) / 1000,
# times=(200.0, 1200.0))
#inh_psg.to_sonata('inh_stim_spikes.h5')
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(base_dir='./',
network_dir='./network',
tstop=3000.0,
dt=0.1,
report_vars=['v', 'cai'],
spikes_inputs=[('tone', 'tone_spikes.csv'),
('shock', 'shock_spikes.csv')],
components_dir='biophys_components',
compile_mechanisms=True)
exc_psg = PoissonSpikeGenerator(population='exc_stim')
for i in range(num_exc):
exc_psg.add(node_ids=[i],
firing_rate=float(exc_frs[i]/1000),
times=(1.0*1000, 4.0*1000))
exc_psg.to_sonata('exc_stim_spikes.h5')
inh_psg = PoissonSpikeGenerator(population='inh_stim')
inh_psg.add(node_ids=range(num_inh),
firing_rate=inh_fr/1000,
times=(1.0*1000, 4.0*1000))
inh_psg.to_sonata('inh_stim_spikes.h5')
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(base_dir='./',
network_dir='./network',
tstop=4000.0, dt = 0.1,
report_vars=['v', 'cai'],
current_clamp={ # Creates a step current from 500.ms to 1500.0 ms
'amp': [-0.5 for i in range(N)],
#'std': [0.0, 0.0],
'delay': [2000 for i in range(N)],
'duration': [1000 for i in range(N)],
'gids':"all"
},
spikes_threshold=-10,
spikes_inputs=[('exc_stim', 'exc_stim_spikes.h5'), ('inh_stim', 'inh_stim_spikes.h5')],
components_dir='../biophys_components',
compile_mechanisms=True)
exc_bg_bask.build()
exc_bg_bask.save_nodes(output_dir='network')
exc_bg_chn.build()
exc_bg_chn.save_nodes(output_dir='network')
#
# print("External nodes and edges built")
t_sim = 10000 #was 20000
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(base_dir='./',
network_dir='./network',
tstop=t_sim, dt=0.1,
spikes_inputs=[('mthalamus', 'mthalamus_spikes.h5'),
('exc_bg_bask', 'exc_bg_bask_spikes.h5'),
('exc_bg_chn', 'exc_bg_chn_spikes.h5')],
components_dir='biophys_components',
compile_mechanisms=True)
from bmtk.utils.reports.spike_trains import PoissonSpikeGenerator
#
psg = PoissonSpikeGenerator(population='mthalamus')
psg.add(node_ids=range(numPN_A + numPN_C), # Have nodes to match mthalamus
firing_rate=0.2, # 15 Hz, we can also pass in a nonhomoegenous function/array
times=(0.0, t_sim)) # Firing starts at 0 s up to 3 s
psg.to_sonata('mthalamus_spikes.h5')
psg = PoissonSpikeGenerator(population='exc_bg_bask')
psg.add(node_ids=range(numBask), # Have nodes to match mthalamus
net.add_nodes(N=1,
pop_name='Pyrc',
potental='exc',
model_type='biophysical',
model_template='hoc:L5PCtemplate',
morphology=None)
# Build and save our networks
net.build()
net.save_nodes(output_dir='network')
net.save_edges(output_dir='network')
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(
base_dir='./',
network_dir='./network',
tstop=1000.0,
dt=0.1,
report_vars=['v'],
spikes_threshold=-10,
current_clamp={ # Creates a step current from 500.ms to 1500.0 ms
'amp': -0.05,
#'std': [0.0, 0.0],
'delay': 500,
'duration': 400,
'gids': "all"
},
components_dir='../biophys_components',
compile_mechanisms=True)
model_template=syn['PN2PN.json']['level_of_detail'])
# dynamics_params='AMPA_ExcToExc.json',
# model_template='Exp2Syn')
# Build and save our networks
net.build()
net.save_nodes(output_dir='network')
net.save_edges(output_dir='network')
exc_stim.build()
exc_stim.save_nodes(output_dir='network')
import h5py
f = h5py.File('exc_stim_spikes.h5', 'w')
f.create_group('spikes')
f['spikes'].create_group('exc_stim')
f['spikes']['exc_stim'].create_dataset("node_ids", data=[0])
f['spikes']['exc_stim'].create_dataset("timestamps", data=[500])
f.close()
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(base_dir='./',
network_dir='./network',
tstop=700.0,
dt=0.1,
report_vars=['v'],
spikes_inputs=[('exc_stim', 'exc_stim_spikes.h5')],
components_dir='../biophys_components',
include_examples=True,
compile_mechanisms=True)
# Build and save our network
#thalamus.build()
#thalamus.save_nodes(output_dir='network')
#thalamus.save_edges(output_dir='network')
#
#print("External nodes and edges built")
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(base_dir='./',
network_dir='./network',
tstop=1000.0,
dt=0.1,
current_clamp={
'gids': [16483],
'amp': [0.5],
'delay': 100.0,
'duration': 50.0
},
components_dir='biophys_components',
compile_mechanisms=True)
#from bmtk.utils.reports.spike_trains import PoissonSpikeGenerator
#
#psg = PoissonSpikeGenerator(population='mthalamus')
#psg.add(node_ids=range(numPN_A+numPN_C), # Have nodes to match mthalamus
# firing_rate=15.0, # 15 Hz, we can also pass in a nonhomoegenous function/array
# times=(0.0, 3.0)) # Firing starts at 0 s up to 3 s
#psg.to_sonata('mthalamus_spikes.h5')
exc_bg_bask.build()
exc_bg_bask.save_nodes(output_dir='network')
#
#print("External nodes and edges built")
t_sim = 500
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(base_dir='./',
network_dir='./network',
tstop=t_sim, dt = 0.1,
report_vars = ['v'],
spikes_inputs=[('mthalamus', # Name of population which spikes will be generated for
'mthalamus_spikes.h5'),('exc_bg_bask','exc_bg_bask_spikes.h5')],
#current_clamp={
# 'gids': [0],
# 'amp': [0.5],
# 'delay': 100.0,
# 'duration': 50.0
# },
components_dir='biophys_components',
compile_mechanisms=True)
from bmtk.utils.reports.spike_trains import PoissonSpikeGenerator
#
psg = PoissonSpikeGenerator(population='mthalamus')
psg.add(node_ids=range(numPN_A+numPN_C), # Have nodes to match mthalamus
firing_rate=0.002, # 15 Hz, we can also pass in a nonhomoegenous function/array
times=(0.0, t_sim)) # Firing starts at 0 s up to 3 s
psg.to_sonata('mthalamus_spikes.h5')
'''Before running a simulation, we will need to create the runtime environment, including parameter files, run-script
and configuration files. This will also compile mechanisms'''
# Mechanisms need to be compiled?
compile_mechanisms = True
if os.path.isdir('%s/components/mechanisms/x86_64/' % (savedir)):
compile_mechanisms = False
# Build network
build_env_bionet(
base_dir=savedir,
network_dir='%s/network' % (savedir),
tstop=3000.0,
dt=0.1,
report_vars=['v', 'cai'
], # Record membrane potential and calcium (default soma)
spikes_inputs=[
('mthalamus', '%s/inputs/mthalamus_spikes.h5' % (savedir))
], # Name of population which spikes will be generated for
include_examples=True, # Copies components files
compile_mechanisms=
compile_mechanisms # If true, will try to compile NEURON mechanisms
)
# Update the configuration file to read "thalamus_spikes.csv"
inputsFilename = '%s/simulation_config.json' % (savedir)
with open(inputsFilename, 'r') as json_file:
jsonText = json_file.readlines()
for i, line in enumerate(jsonText):
if '"input_file"' in line:
jsonText[
i] = ' "input_file": "${BASE_DIR}/inputs/mthalamus_spikes.h5",\n'
net.build()
net.save(output_dir='network')
thalamus.build()
thalamus.save(output_dir='network')
psg = PoissonSpikeGenerator(population='mthalamus')
psg.add(
node_ids=1, # Have 5 nodes to match mthalamus
firing_rate=8, # 2 Hz
times=(0.0, 1)) # time is in seconds for some reason
psg.to_sonata('virtual_spikes.h5')
print('Number of background spikes: {}'.format(psg.n_spikes()))
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(
base_dir='../',
network_dir='./network',
tstop=1000.0,
dt=0.1,
report_vars=['v'],
spikes_inputs=[('mthalamus', 'virtual_spikes.h5')],
#current_clamp={
# 'amp': -0.100,
# 'delay': 250.0,
# 'duration': 200 #200 for bask 600 for pyr
#},
components_dir='../biophys_components',
config_file='../simulation_config.json',
compile_mechanisms=False)
# Build and save our network
thalamus.build()
thalamus.save_nodes(output_dir='network')
thalamus.save_edges(output_dir='network')
print("External nodes and edges built")
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(
base_dir='./',
network_dir='./network',
tstop=1000.0,
dt=0.1,
spikes_inputs=[(
'mthalamus', # Name of population which spikes will be generated for
'mthalamus_spikes.h5')],
report_vars=['v', 'cai'
], # Record membrane potential and calcium (default soma)
components_dir='biophys_components',
compile_mechanisms=True)
from bmtk.utils.reports.spike_trains import PoissonSpikeGenerator
psg = PoissonSpikeGenerator(population='mthalamus')
psg.add(
node_ids=range(numPN_A + numPN_C +
numBask), # Have nodes to match mthalamus
firing_rate=
15.0, # 15 Hz, we can also pass in a nonhomoegenous function/array
times=(0.0, 3.0)) # Firing starts at 0 s up to 3 s
# model_template='hoc:L5PCtemplate',
# morphology = None)
#L2/3 Cell
net.add_nodes(N=1,
pop_name='Pyrc',
potental='exc',
model_type='biophysical',
dynamics_params="L2-3_fit.json",
model_template="ctdb:Biophys1.hoc",
model_processing="aibs_allactive",
morphology="L2-3.swc")
net.build()
net.save_nodes(output_dir='network')
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(
base_dir='./', # Where to save the scripts and config files
components_dir='../biophys_components',
network_dir='./network', # Location of directory containing network files
tstop=3000.0,
dt=0.1, # Run a simulation for 2000 ms at 0.1 ms intervals
report_vars=['v'],
dL=5,
#clamp_reports=["se"], # Tells simulator we want to record membrane potential and calcium traces
spikes_threshold=-10,
compile_mechanisms=True # Will try to compile NEURON mechanisms
)
net = NetworkBuilder('mcortex')
net.add_nodes(cell_name='Cell_PN',
potental='exc',
model_type='biophysical',
model_template='hoc:Cell_PN',
morphology=None
)
net.build()
net.save_nodes(output_dir='network')
for node in net.nodes():
print(node)
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(base_dir='PN_IClamp', # Where to save the scripts and config files
components_dir='components',
network_dir='network', # Location of directory containing network files
tstop=2000.0, dt=0.1, # Run a simulation for 2000 ms at 0.1 ms intervals
report_vars=['v'], # Tells simulator we want to record membrane potential and calcium traces
current_clamp={ # Creates a step current from 500.ms to 1500.0 ms
'amp': 0.3,
'delay': 500.0,
'duration': 1000.0
},
compile_mechanisms=True # Will try to compile NEURON mechanisms
)
#tone_fr = 2
#exc_psg = PoissonSpikeGenerator(population='tone')
#exc_psg.add(node_ids=0,
# firing_rate=int(tone_fr),
# times=(0.0, t_sim/1000))
#exc_psg.to_sonata('tone_poisson_spikes.h5')
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(base_dir='../',
network_dir='./network',
tstop=t_sim,
dt=0.1,
spikes_inputs=[('tone', './10_cell_spikes/tone_spikes.csv'),
('shock', './10_cell_spikes/shock_spikes.csv'),
('bg_pn', '10_cell_spikes/bg_pn_spikes.h5'),
('bg_pv', '10_cell_spikes/bg_pv_spikes.h5')],
components_dir='../biophys_components',
config_file='config.json',
compile_mechanisms=False)
psg = PoissonSpikeGenerator(population='bg_pn')
psg.add(
node_ids=range(8), # need same number as cells
firing_rate=2, # 1 spike every 1 second Hz
times=(0.0, t_sim / 1000)) # time is in seconds for some reason
psg.to_sonata('10_cell_spikes/bg_pn_spikes.h5')
print('Number of background spikes for pn: {}'.format(psg.n_spikes()))
inh_stim.build()
inh_stim.save_nodes(output_dir='network')
from bmtk.utils.reports.spike_trains import PoissonSpikeGenerator
from bmtk.utils.reports.spike_trains.spikes_file_writers import write_csv
exc_psg = PoissonSpikeGenerator(population='exc_stim')
exc_psg.add(node_ids=range(np.sum(num_exc)),
firing_rate=int(exc_fr) / 1000,
times=(200.0, 1200.0))
exc_psg.to_sonata('exc_stim_spikes.h5')
inh_psg = PoissonSpikeGenerator(population='inh_stim')
inh_psg.add(node_ids=range(np.sum(num_inh)),
firing_rate=int(inh_fr) / 1000,
times=(200.0, 1200.0))
inh_psg.to_sonata('inh_stim_spikes.h5')
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(base_dir='./',
network_dir='./network',
tstop=1200.0,
dt=0.1,
report_vars=['v'],
spikes_inputs=[('exc_stim', 'exc_stim_spikes.h5'),
('inh_stim', 'inh_stim_spikes.h5')],
components_dir='biophys_components',
compile_mechanisms=True)
exc_stim.build()
exc_stim.save_nodes(output_dir='network')
import h5py
f = h5py.File('exc_stim_spikes.h5', 'w')
f.create_group('spikes')
f['spikes'].create_group('exc_stim')
f['spikes']['exc_stim'].create_dataset("node_ids", data=[0])
f['spikes']['exc_stim'].create_dataset("timestamps", data=[400])
f.close()
from bmtk.utils.sim_setup import build_env_bionet
holding_v = -75
build_env_bionet(base_dir='./',
network_dir='./network',
tstop=500.0, dt = 0.1,
report_vars=['v'],
spikes_threshold=-10,
clamp_reports=['se'],#Records se clamp currents.
se_voltage_clamp={
"amps":[[holding_v, holding_v, holding_v]],
"durations": [[500, 0, 0]],
'gids': "all",
'rs': [0.01 for i in range(N)],
},
spikes_inputs=[('exc_stim', 'exc_stim_spikes.h5')],
components_dir='../biophys_components',
compile_mechanisms=True)
# #distance_range=[1250,2000],
# #distance_range=[-500, 500],
# dynamics_params='PN2PN.json',
# model_template=syn['PN2PN.json']['level_of_detail'])
# Build and save our networks
net.build()
net.save_nodes(output_dir='network')
net.save_edges(output_dir='network')
# exc_stim.build()
# exc_stim.save_nodes(output_dir='network')
# import h5py
# f = h5py.File('exc_stim_spikes.h5', 'w')
# f.create_group('spikes')
# f['spikes'].create_group('exc_stim')
# f['spikes']['exc_stim'].create_dataset("node_ids", data=[0])
# f['spikes']['exc_stim'].create_dataset("timestamps", data=[400])
# f.close()
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(base_dir='./',
network_dir='./network',
tstop=500.0, dt = 0.1,
#report_vars=['v'],
spikes_threshold=-10,
#spikes_inputs=[('exc_stim', 'exc_stim_spikes.h5')],
components_dir='../biophys_components',
compile_mechanisms=True)
inh_stim.build()
inh_stim.save_nodes(output_dir='network')
import h5py
f = h5py.File('inh_stim_spikes.h5', 'w')
f.create_group('spikes')
f['spikes'].create_group('inh_stim')
f['spikes']['inh_stim'].create_dataset("node_ids", data=[0])
f['spikes']['inh_stim'].create_dataset("timestamps", data=[500])
f.close()
from bmtk.utils.sim_setup import build_env_bionet
build_env_bionet(
base_dir='./',
network_dir='./network',
tstop=700.0,
dt=0.1,
report_vars=['v'],
clamp_reports=['se'], #Records se clamp currents.
se_voltage_clamp={
"amps": [[-40, -70, -70]],
"durations": [[1000, 0, 0]],
'gids': [0],
'rs': [0.01],
},
spikes_inputs=[('inh_stim', 'inh_stim_spikes.h5')],
components_dir='biophys_components',
include_examples=True,
compile_mechanisms=True)
