import HHTut # import parameters file
from netpyne import sim # import netpyne sim module
np = HHTut.netParams
print("********************\n*\n* Note: setting noise to 1, since noise can only be 0 or 1 in NeuroML export currently!\n*\n********************")
np.stimSourceParams['bkg']['noise'] = 1
sim.createExportNeuroML2(netParams = np,
simConfig = HHTut.simConfig,
reference = 'HHTut') # create and export network to NeuroML 2
import HybridTut # import parameters file
from netpyne import sim # import netpyne sim module
sim.createExportNeuroML2(
netParams=HybridTut.netParams,
simConfig=HybridTut.simConfig,
reference='HybridTut') # create and export network to NeuroML 2
import sandbox # import parameters file
from netpyne import sim # import netpyne sim module
sim.createExportNeuroML2(netParams = sandbox.netParams,
simConfig = sandbox.simConfig,
reference = 'sandbox') # create and export network to NeuroML 2
"""
workdir = re.sub("(?<={})[\w\W]*".format(PROJECT), "", os.getcwd())
os.chdir(workdir)
## Set up pipeline folder if missing
"""
The code below will automatically create a pipeline folder for this code file if it does not exist.
"""
pipeline = os.path.join('2_pipeline', NAME)
if not os.path.exists(pipeline):
os.makedirs(pipeline)
for folder in ['out', 'store', 'tmp']:
os.makedirs(os.path.join(pipeline, folder))
np = prms_control.netParams
print(
"********************\n*\n* Note: setting noise to 1, since noise can only be 0 or 1 in NeuroML export currently!\n*\n********************"
)
np.stimSourceParams['background_E']['noise'] = 1
np.stimSourceParams['background_I']['noise'] = 1
sim.createExportNeuroML2(
netParams=np,
simConfig=prms_control.simConfig,
reference='M1',
connections=True,
stimulations=True) # create and export network to NeuroML 2
import HHSmall # import parameters file
from netpyne import sim # import netpyne sim module
sim.createExportNeuroML2(
netParams=HHSmall.netParams,
simConfig=HHSmall.simConfig,
reference='HHSmall') # create and export network to NeuroML 2
import M1 # import parameters file
from netpyne import sim # import netpyne sim module
np = M1.netParams
print("********************\n*\n* Note: setting noise to 1, since noise can only be 0 or 1 in NeuroML export currently!\n*\n********************")
np.popParams['background_E']['noise'] = 1
np.popParams['background_I']['noise'] = 1
sim.createExportNeuroML2(netParams = np,
simConfig = M1.simConfig,
reference = 'M1',
connections=True,
stimulations=True) # create and export network to NeuroML 2
import HybridTut # import parameters file
from netpyne import sim # import netpyne sim module
np = HybridTut.netParams
print("********************\n*\n* Note: setting noise to 1, since noise can only be 0 or 1 in NeuroML export currently!\n*\n********************")
np.popParams['background']['noise'] = 1
sim.createExportNeuroML2(netParams = np,
simConfig = HybridTut.simConfig,
reference = 'HybridTut') # create and export network to NeuroML 2
import HybridSmall # import parameters file
from netpyne import sim # import netpyne sim module
sim.createExportNeuroML2(netParams = HybridSmall.netParams,
simConfig = HybridSmall.simConfig,
reference = 'HybridSmall') # create and export network to NeuroML 2
import M1 # import parameters file
from netpyne import sim # import netpyne sim module
np = M1.netParams
print(
"********************\n*\n* Note: setting noise to 1, since noise can only be 0 or 1 in NeuroML export currently!\n*\n********************"
)
np.stimSourceParams['background_E']['noise'] = 1
np.stimSourceParams['background_I']['noise'] = 1
sim.createExportNeuroML2(
netParams=np,
simConfig=M1.simConfig,
reference='M1_100percent',
connections=True,
stimulations=True,
format='hdf5') # create and export network to NeuroML 2
netparms.stimSourceParams['background_I']['noise'] = 1
if disable_output:
M1.simConfig.analysis = {}
M1.simConfig.recordTraces = {}
M1.simConfig.recordCellsSpikes = []
if do_simulate:
tic = time.time()
sim.create(netparms, M1.simConfig, output=False)
sim.runSim()
print(sim.simData, len(sim.simData['spkid']))
print(sim.timingData)
# print( len(sim.simData) )
# print( len( sim.simData['V']['cell_10'] ) )
# print( M1.simConfig.analysis )
# print( sim.simData['spkid'] )
# print( len( sim.simData['spkid'] ) )
# print( [ x for x in sim.simData['V']['cell_10'] ] )
else:
sim.createExportNeuroML2(
netParams=netparms,
simConfig=M1.simConfig,
reference=('M1_p_%dpercent') % (int(net_scale * 100)),
connections=True,
stimulations=True,
#format='hdf5'
) # create and export network to NeuroML 2