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