Example 21. Comparing simulations: the Hodgkin-Huxley ‘52 channels
Comparing simulations: the Hodgkin-Huxley ‘52 channels
This simulation compares the different ways of implementing the Hodgkin-Huxley channels; we check that the Hodgkin-Huxley channels built-in to NEURON produce the same results as when we create these channels with parameters as an StdChlAlphaBeta.
In you are not familiar with python, then this is an example of the one of the advantages of the laanguage: functions are objects!
In “test_neuron”, we create a neuron morphology, but put the code to add the channels in a different function. This makes it easy to try out different channel types and distributions easily and quickly.
Code
from morphforgecontrib.simulation.channels.neuroml_via_neurounits.neuroml_via_neurounits_core import NeuroML_Via_NeuroUnits_Channel
from morphforgecontrib.simulation.channels.neurounits.neuro_units_bridge import Neuron_NeuroUnitEqnsetMechanism
from morphforge.stdimports import *
from morphforgecontrib.simulation.channels.hh_style.core.mmleak import StdChlLeak
from morphforgecontrib.simulation.channels.hh_style.core.mmalphabeta import StdChlAlphaBeta
from morphforgecontrib.simulation.channels.simulatorbuiltin.sim_builtin_core import BuiltinChannel
from morphforgecontrib.simulation.channels.neuroml_via_xsl.neuroml_via_xsl_core import NeuroML_Via_XSL_Channel
import random as R
variables = ['h', 'm', 'minf', 'mtau', 'm_alpha_rate', 'm_beta_rate']
def apply_hh_chls_neurounits_direct(env, cell, sim):
eqnset_txt_na = """
define_component chlstd_hh_na {
from std.math import exp
i = g * (v-erev) * m**3*h
minf = m_alpha_rate / (m_alpha_rate + m_beta_rate)
mtau = 1.0 / (m_alpha_rate + m_beta_rate)
m' = (minf-m) / mtau
hinf = h_alpha_rate / (h_alpha_rate + h_beta_rate)
htau = 1.0 / (h_alpha_rate + h_beta_rate)
h' = (hinf-h) / htau
StdFormAB(V, a1, a2, a3, a4, a5) = (a1 + a2*V)/(a3+exp((V+a4)/a5))
m_alpha_rate = StdFormAB(V=v, a1=m_a1, a2=m_a2, a3=m_a3, a4=m_a4, a5=m_a5)
m_beta_rate = StdFormAB(V=v, a1=m_b1, a2=m_b2, a3=m_b3, a4=m_b4, a5=m_b5)
h_alpha_rate = StdFormAB(V=v, a1=h_a1, a2=h_a2, a3=h_a3, a4=h_a4, a5=h_a5)
h_beta_rate = StdFormAB(V=v, a1=h_b1, a2=h_b2, a3=h_b3, a4=h_b4, a5=h_b5)
m_a1 = {-4.00 ms-1}
m_a2 = {-0.10 mV-1 ms-1}
m_a3 = -1.00
m_a4 = {40.00 mV}
m_a5 = {-10.00 mV}
m_b1 = {4.00 ms-1}
m_b2 = {0.00 mV-1 ms-1}
m_b3 = {0.00}
m_b4 = {65.00 mV}
m_b5 = {18.00 mV}
h_a1 = {0.07 ms-1}
h_a2 = {0.00 mV-1 ms-1}
h_a3 = {0.00}
h_a4 = {65.00 mV}
h_a5 = {20.00 mV}
h_b1 = {1.00 ms-1}
h_b2 = {0.00 mV-1 ms-1}
h_b3 = {1.00}
h_b4 = {35.00 mV}
h_b5 = {-10.00 mV}
sg = {120.0mS/cm2}
erev = {50.0mV}
<=> PARAMETER g:(S/m2)
<=> OUTPUT i:(A/m2) METADATA {"mf":{"role":"TRANSMEMBRANECURRENT"} }
<=> INPUT v: V METADATA {"mf":{"role":"MEMBRANEVOLTAGE"} }
}
"""
eqnset_txt_k = """
define_component chlstd_hh_k {
from std.math import exp
i = g * (v-erev) * n*n*n*n
ninf = n_alpha_rate / (n_alpha_rate + n_beta_rate)
ntau = 1.0 / (n_alpha_rate + n_beta_rate)
n' = (ninf-n) / ntau
StdFormAB(V, a1, a2, a3, a4, a5) = (a1 + a2*V)/(a3+exp((V+a4)/a5))
n_alpha_rate = StdFormAB(V=v, a1=n_a1, a2=n_a2, a3=n_a3, a4=n_a4, a5=n_a5)
n_beta_rate = StdFormAB(V=v, a1=n_b1, a2=n_b2, a3=n_b3, a4=n_b4, a5=n_b5)
n_a1 = {-0.55 ms-1}
n_a2 = {-0.01 mV-1 ms-1}
n_a3 = -1.00
n_a4 = {55.00 mV}
n_a5 = {-10.00 mV}
n_b1 = {0.125 ms-1}
n_b2 = {0.00 mV-1 ms-1}
n_b3 = {0.00}
n_b4 = {65.00 mV}
n_b5 = {80.00 mV}
g = {36.0mS/cm2}
erev = {-77.0mV}
<=> OUTPUT i:(A/m2) METADATA {"mf":{"role":"TRANSMEMBRANECURRENT"} }
<=> INPUT v: V METADATA {"mf":{"role":"MEMBRANEVOLTAGE"} }
}
"""
eqnset_txt_lk = """
define_component chlstd_hh_lk {
i = g * (v-erev)
g = {0.3 mS/cm2}
erev = -54.3 mV
<=> OUTPUT i:(A/m2) METADATA {"mf":{"role":"TRANSMEMBRANECURRENT"} }
<=> INPUT v: V METADATA {"mf":{"role":"MEMBRANEVOLTAGE"} }
}
"""
na_chl = Neuron_NeuroUnitEqnsetMechanism(name="Chl1", eqnset=eqnset_txt_na, default_parameters={"g":qty("120:mS/cm2")}, )
lk_chl = Neuron_NeuroUnitEqnsetMechanism(name="Chl2", eqnset=eqnset_txt_lk, )
k_chl = Neuron_NeuroUnitEqnsetMechanism(name="Chl3", eqnset=eqnset_txt_k, )
cell.apply_channel( na_chl)
cell.apply_channel( lk_chl)
cell.apply_channel( k_chl)
sim.record(na_chl, what='m', cell_location= cell.soma, user_tags=[StandardTags.StateVariable])
sim.record(na_chl, what='mtau', cell_location= cell.soma, user_tags=[StandardTags.StateTimeConstant])
sim.record(na_chl, what='h', cell_location= cell.soma, user_tags=[StandardTags.StateVariable])
sim.record(na_chl, what='htau', cell_location= cell.soma, user_tags=[StandardTags.StateTimeConstant])
sim.record(k_chl, what='n', cell_location= cell.soma, user_tags=[StandardTags.StateVariable])
sim.record(k_chl, what='ntau', cell_location= cell.soma, user_tags=[StandardTags.StateTimeConstant])
def apply_hh_chls_neuroml_xsl(env, cell, sim):
lk_chl = env.Channel(
StdChlLeak,
name="LkChl",
conductance=qty("0.3:mS/cm2"),
reversalpotential=qty("-54.3:mV"),
)
na_chl = env.Channel(NeuroML_Via_XSL_Channel,
xml_filename = os.path.join(LocMgr.get_test_srcs_path(), "neuroml/channelml/NaChannel_HH.xml"),
xsl_filename = os.path.join(LocMgr.get_test_srcs_path(), "neuroml/channelml/ChannelML_v1.8.1_NEURONmod.xsl"),
)
k_chl = env.Channel(NeuroML_Via_XSL_Channel,
xml_filename = os.path.join(LocMgr.get_test_srcs_path(), "neuroml/channelml/KChannel_HH.xml"),
xsl_filename = os.path.join(LocMgr.get_test_srcs_path(), "neuroml/channelml/ChannelML_v1.8.1_NEURONmod.xsl"),
)
cell.apply_channel( na_chl)
cell.apply_channel( lk_chl)
cell.apply_channel( k_chl)
def apply_hh_chls_neuroml_neurounits(env, cell, sim):
lk_chl = env.Channel(
StdChlLeak,
name="LkChl",
conductance=qty("0.3:mS/cm2"),
reversalpotential=qty("-54.3:mV"),
)
na_chl = env.Channel(NeuroML_Via_NeuroUnits_Channel,
xml_filename = os.path.join(LocMgr.get_test_srcs_path(), "neuroml/channelml/NaChannel_HH.xml"),
)
k_chl = env.Channel(NeuroML_Via_XSL_Channel,
xml_filename = os.path.join(LocMgr.get_test_srcs_path(), "neuroml/channelml/KChannel_HH.xml"),
xsl_filename = os.path.join(LocMgr.get_test_srcs_path(), "neuroml/channelml/ChannelML_v1.8.1_NEURONmod.xsl"),
)
cell.apply_channel( na_chl)
cell.apply_channel( lk_chl)
cell.apply_channel( k_chl)
def apply_hh_chls_morphforge_format(env, cell, sim):
lk_chl = env.Channel(
StdChlLeak,
name="LkChl",
conductance=qty("0.3:mS/cm2"),
reversalpotential=qty("-54.3:mV"),
)
na_state_vars = { "m": {
"alpha":[-4.00, -0.10, -1.00, 40.00, -10.00],
"beta": [4.00, 0.00, 0.00, 65.00, 18.00]},
"h": {
"alpha":[0.07, 0.00, 0.00, 65.00, 20.00] ,
"beta": [1.00, 0.00, 1.00, 35.00, -10.00]}
}
na_chl = env.Channel(
StdChlAlphaBeta,
name="NaChl", ion="na",
equation="m*m*m*h",
conductance=qty("120:mS/cm2"),
reversalpotential=qty("50:mV"),
statevars=na_state_vars,
)
k_state_vars = { "n": {
"alpha":[-0.55, -0.01, -1.0, 55.0, -10.0],
"beta": [0.125, 0, 0, 65, 80]},
}
k_chl = env.Channel(
StdChlAlphaBeta,
name="KChl", ion="k",
equation="n*n*n*n",
conductance=qty("36:mS/cm2"),
reversalpotential=qty("-77:mV"),
statevars=k_state_vars,
)
cell.apply_channel( lk_chl)
cell.apply_channel( na_chl)
cell.apply_channel( k_chl)
def apply_hh_chls_NEURON_builtin(env, cell, sim):
hhChls = env.Channel(BuiltinChannel, sim_chl_name="hh", )
cell.apply_channel( hhChls)
def simulate_chls_on_neuron(chl_applicator_functor):
# Create the environment:
env = NEURONEnvironment()
# Create the simulation:
sim = env.Simulation()
# Create a cell:
morphDict1 = {'root': {'length': 18.8, 'diam': 18.8, 'id':'soma'} }
m1 = MorphologyTree.fromDictionary(morphDict1)
cell = sim.create_cell(name="Cell1", morphology=m1)
# Setup the HH-channels on the cell:
chl_applicator_functor(env, cell, sim)
# Setup passive channels:
cell.set_passive( PassiveProperty.SpecificCapacitance, qty('1.0:uF/cm2'))
# Create the stimulus and record the injected current:
cc = sim.create_currentclamp(name="Stim1", amp=qty("100:pA"), dur=qty("100:ms"), delay=qty("100:ms") * R.uniform(0.95, 1.0), cell_location=cell.soma)
# Define what to record:
sim.record(cell, what=StandardTags.Voltage, name="SomaVoltage", cell_location = cell.soma)
# run the simulation
results = sim.run()
return results
resultsA =None
resultsB =None
resultsC =None
resultsD =None
resultsE =None
resultsA = simulate_chls_on_neuron(apply_hh_chls_morphforge_format)
resultsB = simulate_chls_on_neuron(apply_hh_chls_NEURON_builtin)
resultsC = simulate_chls_on_neuron(apply_hh_chls_neuroml_neurounits)
resultsD = simulate_chls_on_neuron(apply_hh_chls_neuroml_xsl)
resultsE = simulate_chls_on_neuron(apply_hh_chls_neurounits_direct)
#
trs = [resultsA, resultsB, resultsC, resultsD, resultsE]
trs = [tr for tr in trs if tr is not None]
TagViewer(trs, timerange=(95, 200)*units.ms, show=True)
pylab.show()
Figures
Download Figure
Output
No handlers could be found for logger "neurounits"
2013-12-01 17:15:42,771 - morphforge.core.logmgr - INFO - Logger Started OK
2013-12-01 17:15:42,772 - DISABLEDLOGGING - INFO - _run_spawn() [Pickling Sim]
No handlers could be found for logger "neurounits"
2013-12-01 17:15:44,958 - morphforge.core.logmgr - INFO - Logger Started OK
2013-12-01 17:15:44,959 - DISABLEDLOGGING - INFO - Ensuring Modfile is built
NEURON -- Release 7.3 (869:0141cf0aff14) 2013-05-10
Duke, Yale, and the BlueBrain Project -- Copyright 1984-2013
See http://www.neuron.yale.edu/neuron/credits
['DBUS_SESSION_BUS_ADDRESS', 'DEFAULTS_PATH', 'DESKTOP_SESSION', 'DESKTOP_STARTUP_ID', 'DISPLAY', 'GDMSESSION', 'GNOME_KEYRING_CONTROL', 'GNOME_KEYRING_PID', 'GREP_COLOR', 'GREP_OPTIONS', 'GRIN_ARGS', 'GTK_MODULES', 'HOME', 'INFANDANGO_CONFIGFILE', 'INFANDANGO_ROOT', 'LANG', 'LANGUAGE', 'LC_CTYPE', 'LD_LIBRARY_PATH', 'LESS', 'LOGNAME', 'LSCOLORS', 'MANDATORY_PATH', 'MREORG_CONFIG', 'OLDPWD', 'PAGER', 'PATH', 'PWD', 'PYTHONPATH', 'SHELL', 'SHLVL', 'SSH_AGENT_PID', 'SSH_AUTH_SOCK', 'TERM', 'TEXTDOMAIN', 'TEXTDOMAINDIR', 'UBUNTU_MENUPROXY', 'USER', 'WINDOWID', 'XAUTHORITY', 'XDG_CONFIG_DIRS', 'XDG_DATA_DIRS', 'XDG_RUNTIME_DIR', 'XDG_SEAT_PATH', 'XDG_SESSION_COOKIE', 'XDG_SESSION_PATH', 'XTERM_LOCALE', 'XTERM_SHELL', 'XTERM_VERSION', '_', '_JAVA_AWT_WM_NONREPARENTING']
Loading Bundle from: /mnt/scratch/tmp/morphforge/tmp/simulationresults/24/24bbdee3e0bb7fbe00cca5b220278f75.bundle (11k) : 0.832 seconds
set(['conductance', 'reversalpotential'])
__dict__ {'mm_neuronNumber': None, 'cachedNeuronSuffix': None, 'reversalpotential': array(-54.3) * mV, '_name': 'LkChl', '_simulation': None, 'conductance': array(3.0) * s**3*A**2/(kg*m**4)}
loading membrane mechanisms from /mnt/scratch/tmp/morphforge/tmp/modout/mod_af84455a7bd10be7408061ecd02b589b.so
loading membrane mechanisms from /mnt/scratch/tmp/morphforge/tmp/modout/mod_fb18cab9ab8db5d2c968f5e6fba6a942.so
loading membrane mechanisms from /mnt/scratch/tmp/morphforge/tmp/modout/mod_e1d9b15c15cf730d6ad5de223a1b3007.so
Running Hoc File: /mnt/scratch/tmp/morphforge/tmp/tmp_a60cccd31e5b3353f7d1bc7b22a8ecc6.hoc
1
1
0.01
0
1
50000
1
Running Simulation
Time for Extracting Data: (1 records) 0.0017671585083
Running simulation : 0.463 seconds
Size of results file: 0.1 (MB)
Post-processing : 0.007 seconds
Entire load-run-save time : 1.303 seconds
Suceeded
No handlers could be found for logger "neurounits"
NEURON -- Release 7.3 (869:0141cf0aff14) 2013-05-10
Duke, Yale, and the BlueBrain Project -- Copyright 1984-2013
See http://www.neuron.yale.edu/neuron/credits
['DBUS_SESSION_BUS_ADDRESS', 'DEFAULTS_PATH', 'DESKTOP_SESSION', 'DESKTOP_STARTUP_ID', 'DISPLAY', 'GDMSESSION', 'GNOME_KEYRING_CONTROL', 'GNOME_KEYRING_PID', 'GREP_COLOR', 'GREP_OPTIONS', 'GRIN_ARGS', 'GTK_MODULES', 'HOME', 'INFANDANGO_CONFIGFILE', 'INFANDANGO_ROOT', 'LANG', 'LANGUAGE', 'LC_CTYPE', 'LD_LIBRARY_PATH', 'LESS', 'LOGNAME', 'LSCOLORS', 'MANDATORY_PATH', 'MREORG_CONFIG', 'OLDPWD', 'PAGER', 'PATH', 'PWD', 'PYTHONPATH', 'SHELL', 'SHLVL', 'SSH_AGENT_PID', 'SSH_AUTH_SOCK', 'TERM', 'TEXTDOMAIN', 'TEXTDOMAINDIR', 'UBUNTU_MENUPROXY', 'USER', 'WINDOWID', 'XAUTHORITY', 'XDG_CONFIG_DIRS', 'XDG_DATA_DIRS', 'XDG_RUNTIME_DIR', 'XDG_SEAT_PATH', 'XDG_SESSION_COOKIE', 'XDG_SESSION_PATH', 'XTERM_LOCALE', 'XTERM_SHELL', 'XTERM_VERSION', '_', '_JAVA_AWT_WM_NONREPARENTING']
Loading Bundle from: /mnt/scratch/tmp/morphforge/tmp/simulationresults/31/31ef01e2512928ee7dbd4dac5084817f.bundle (9k) : 0.870 seconds
Running Hoc File: /mnt/scratch/tmp/morphforge/tmp/tmp_b55da11a3034a715142adfe4f135acec.hoc
1
1
0.01
0
1
50000
1
Running Simulation
Time for Extracting Data: (1 records) 0.00233507156372
Running simulation : 0.277 seconds
Size of results file: 0.1 (MB)
Post-processing : 0.008 seconds
Entire load-run-save time : 1.155 seconds
Suceeded
['DBUS_SESSION_BUS_ADDRESS', 'DEFAULTS_PATH', 'DESKTOP_SESSION', 'DESKTOP_STARTUP_ID', 'DISPLAY', 'GDMSESSION', 'GNOME_KEYRING_CONTROL', 'GNOME_KEYRING_PID', 'GREP_COLOR', 'GREP_OPTIONS', 'GRIN_ARGS', 'GTK_MODULES', 'HOME', 'INFANDANGO_CONFIGFILE', 'INFANDANGO_ROOT', 'LANG', 'LANGUAGE', 'LC_CTYPE', 'LESS', 'LOGNAME', 'LSCOLORS', 'MANDATORY_PATH', 'MREORG_CONFIG', 'OLDPWD', 'PAGER', 'PATH', 'PWD', 'PYTHONPATH', 'SHELL', 'SHLVL', 'SSH_AGENT_PID', 'SSH_AUTH_SOCK', 'TERM', 'TEXTDOMAIN', 'TEXTDOMAINDIR', 'UBUNTU_MENUPROXY', 'USER', 'WINDOWID', 'XAUTHORITY', 'XDG_CONFIG_DIRS', 'XDG_DATA_DIRS', 'XDG_RUNTIME_DIR', 'XDG_SEAT_PATH', 'XDG_SESSION_COOKIE', 'XDG_SESSION_PATH', 'XTERM_LOCALE', 'XTERM_SHELL', 'XTERM_VERSION', '_', '_JAVA_AWT_WM_NONREPARENTING']
_run_spawn() [Loading results from /mnt/scratch/tmp/morphforge/tmp/simulationresults/24//24bbdee3e0bb7fbe00cca5b220278f75.neuronsim.results.pickle ]
_run_spawn() [Loading results from /mnt/scratch/tmp/morphforge/tmp/simulationresults/31//31ef01e2512928ee7dbd4dac5084817f.neuronsim.results.pickle ]
Loading Channel Type: NaChannel
[('m', 'm_inf'), ('h', 'h_inf')]
CHECKING
<Parameter [id:83571664] Symbol: 'GMAX' >
GMAX
iii 1.0 s**3*A**2/(kg*m**4) <class 'quantities.quantity.Quantity'>
iiii 1200.0 s**3*A**2/(kg*m**4) <class 'quantities.quantity.Quantity'>
OK
CHECKING
<Parameter [id:83572688] Symbol: 'VREV' >
VREV
iii 1.0 kg*m**2/(s**3*A) <class 'quantities.quantity.Quantity'>
iiii 0.05 kg*m**2/(s**3*A) <class 'quantities.quantity.Quantity'>
OK
Output <StateVariable [id:83563088] Symbol: 'h' >
None
Output <StateVariable [id:83564240] Symbol: 'm' >
None
Output <AssignedVariable [id:83566480] Symbol: 'GATEPROP' >
None
Output <AssignedVariable [id:83565392] Symbol: 'I' >
{u'mf': {u'role': u'TRANSMEMBRANECURRENT'}}
Output <AssignedVariable [id:83565200] Symbol: 'g' >
None
Output <AssignedVariable [id:83551504] Symbol: 'h_alpha' >
None
Output <AssignedVariable [id:83570832] Symbol: 'h_beta' >
None
Output <AssignedVariable [id:83565776] Symbol: 'h_inf' >
None
Output <AssignedVariable [id:83565008] Symbol: 'h_tau' >
None
Output <AssignedVariable [id:83564624] Symbol: 'm_alpha' >
None
Output <AssignedVariable [id:83566160] Symbol: 'm_beta' >
None
Output <AssignedVariable [id:83564816] Symbol: 'm_inf' >
None
Output <AssignedVariable [id:83565968] Symbol: 'm_tau' >
None
input <SuppliedValue [id:83573904] Symbol: 'V' >
{u'mf': {u'role': u'MEMBRANEVOLTAGE'}}
m_alpha <class 'neurounits.ast.astobjects.AssignedVariable'>
m_beta <class 'neurounits.ast.astobjects.AssignedVariable'>
m <class 'neurounits.ast.astobjects.StateVariable'>
m <class 'neurounits.ast.astobjects.StateVariable'>
m <class 'neurounits.ast.astobjects.StateVariable'>
h <class 'neurounits.ast.astobjects.StateVariable'>
GMAX <class 'neurounits.ast.astobjects.Parameter'>
GATEPROP <class 'neurounits.ast.astobjects.AssignedVariable'>
h_alpha <class 'neurounits.ast.astobjects.AssignedVariable'>
h_beta <class 'neurounits.ast.astobjects.AssignedVariable'>
T [<class 'neurounits.ast.astobjects.DivOp'>]
V <class 'neurounits.ast.astobjects.SuppliedValue'>
V <class 'neurounits.ast.astobjects.SuppliedValue'>
T [<class 'neurounits.ast.astobjects.MulOp'>]
V <class 'neurounits.ast.astobjects.SuppliedValue'>
T [<class 'neurounits.ast.astobjects.DivOp'>]
V <class 'neurounits.ast.astobjects.SuppliedValue'>
T [<class 'neurounits.ast.astobjects.DivOp'>]
V <class 'neurounits.ast.astobjects.SuppliedValue'>
m_alpha <class 'neurounits.ast.astobjects.AssignedVariable'>
m_alpha <class 'neurounits.ast.astobjects.AssignedVariable'>
m_beta <class 'neurounits.ast.astobjects.AssignedVariable'>
g <class 'neurounits.ast.astobjects.AssignedVariable'>
V <class 'neurounits.ast.astobjects.SuppliedValue'>
VREV <class 'neurounits.ast.astobjects.Parameter'>
h_alpha <class 'neurounits.ast.astobjects.AssignedVariable'>
h_alpha <class 'neurounits.ast.astobjects.AssignedVariable'>
h_beta <class 'neurounits.ast.astobjects.AssignedVariable'>
Writing assignment for: <EqnAssignmentByRegime [id:83566288] Symbol: m_beta >
T [<class 'neurounits.ast.astobjects.DivOp'>]
V <class 'neurNo handlers could be found for logger "neurounits"
2013-12-01 17:15:51,025 - morphforge.core.logmgr - INFO - Logger Started OK
2013-12-01 17:15:51,025 - DISABLEDLOGGING - INFO - Ensuring Modfile is built
NEURON -- Release 7.3 (869:0141cf0aff14) 2013-05-10
Duke, Yale, and the BlueBrain Project -- Copyright 1984-2013
See http://www.neuron.yale.edu/neuron/credits
['DBUS_SESSION_BUS_ADDRESS', 'DEFAULTS_PATH', 'DESKTOP_SESSION', 'DESKTOP_STARTUP_ID', 'DISPLAY', 'GDMSESSION', 'GNOME_KEYRING_CONTROL', 'GNOME_KEYRING_PID', 'GREP_COLOR', 'GREP_OPTIONS', 'GRIN_ARGS', 'GTK_MODULES', 'HOME', 'INFANDANGO_CONFIGFILE', 'INFANDANGO_ROOT', 'LANG', 'LANGUAGE', 'LC_CTYPE', 'LD_LIBRARY_PATH', 'LESS', 'LOGNAME', 'LSCOLORS', 'MANDATORY_PATH', 'MREORG_CONFIG', 'OLDPWD', 'PAGER', 'PATH', 'PWD', 'PYTHONPATH', 'SHELL', 'SHLVL', 'SSH_AGENT_PID', 'SSH_AUTH_SOCK', 'TERM', 'TEXTDOMAIN', 'TEXTDOMAINDIR', 'UBUNTU_MENUPROXY', 'USER', 'WINDOWID', 'XAUTHORITY', 'XDG_CONFIG_DIRS', 'XDG_DATA_DIRS', 'XDG_RUNTIME_DIR', 'XDG_SEAT_PATH', 'XDG_SESSION_COOKIE', 'XDG_SESSION_PATH', 'XTERM_LOCALE', 'XTERM_SHELL', 'XTERM_VERSION', '_', '_JAVA_AWT_WM_NONREPARENTING']
Loading Bundle from: /mnt/scratch/tmp/morphforge/tmp/simulationresults/9f/9fb2f6f970d82de3f4ffd52f1994ca45.bundle (82k) : 1.053 seconds
set(['conductance', 'reversalpotential'])
__dict__ {'mm_neuronNumber': None, 'cachedNeuronSuffix': None, 'reversalpotential': array(-54.3) * mV, '_name': 'LkChl', '_simulation': None, 'conductance': array(3.0) * s**3*A**2/(kg*m**4)}
Executing: /home/michael/opt//x86_64/bin/modlunit /mnt/scratch/tmp/morphforge/tmp/tmp_48cf10999f12f2749f4d65f33d3f5882.mod
/mnt/scratch/tmp/morphforge/tmp/modbuild_23368
Executing: /home/michael/opt//x86_64/bin/nocmodl tmp_48cf10999f12f2749f4d65f33d3f5882.mod
Executing: /home/michael/opt//share/nrn/libtool --mode=compile gcc -DHAVE_CONFIG_H -I"." -I".." -I"/home/michael/opt//include/nrn" -I"/home/michael/opt//x86_64/lib" -g -O2 -c -o tmp_48cf10999f12f2749f4d65f33d3f5882.lo tmp_48cf10999f12f2749f4d65f33d3f5882.c
Executing: /home/michael/opt//share/nrn/libtool --mode=link gcc -module -g -O2 -shared -o tmp_48cf10999f12f2749f4d65f33d3f5882.la -rpath /home/michael/opt//x86_64/libs tmp_48cf10999f12f2749f4d65f33d3f5882.lo -L/home/michael/opt//x86_64/lib -L/home/michael/opt//x86_64/lib /home/michael/opt//x86_64/lib/libnrniv.la -lnrnoc -loc -lmemacs -lnrnmpi -lscopmath -lsparse13 -lreadline -lncurses -livoc -lneuron_gnu -lmeschach -lsundials -lm -ldl
OP1: libtool: compile: gcc -DHAVE_CONFIG_H -I. -I.. -I/home/michael/opt//include/nrn -I/home/michael/opt//x86_64/lib -g -O2 -c tmp_48cf10999f12f2749f4d65f33d3f5882.c -fPIC -DPIC -o .libs/tmp_48cf10999f12f2749f4d65f33d3f5882.o
OP2: libtool: link: gcc -shared -fPIC -DPIC .libs/tmp_48cf10999f12f2749f4d65f33d3f5882.o -Wl,-rpath -Wl,/home/michael/opt/x86_64/lib -Wl,-rpath -Wl,/home/michael/opt/x86_64/lib -L/home/michael/opt//x86_64/lib /home/michael/opt/x86_64/lib/libnrniv.so /home/michael/opt/x86_64/lib/libnrnoc.so /home/michael/opt/x86_64/lib/liboc.so /home/michael/opt/x86_64/lib/libmemacs.so /home/michael/opt/x86_64/lib/libnrnmpi.so /home/michael/opt/x86_64/lib/libscopmath.so /home/michael/opt/x86_64/lib/libsparse13.so -lreadline -lncurses /home/michael/opt/x86_64/lib/libivoc.so /home/michael/opt/x86_64/lib/libneuron_gnu.so /home/michael/opt/x86_64/lib/libmeschach.so /home/michael/opt/x86_64/lib/libsundials.so -lm -ldl -O2 -pthread -Wl,-soname -Wl,tmp_48cf10999f12f2749f4d65f33d3f5882.so.0 -o .libs/tmp_48cf10999f12f2749f4d65f33d3f5882.so.0.0.0
libtool: link: (cd ".libs" && rm -f "tmp_48cf10999f12f2749f4d65f33d3f5882.so.0" && ln -s "tmp_48cf10999f12f2749f4d65f33d3f5882.so.0.0.0" "tmp_48cf10999f12f2749f4d65f33d3f5882.so.0")
libtool: link: (cd ".libs" && rm -f "tmp_48cf10999f12f2749f4d65f33d3f5882.so" && ln -s "tmp_48cf10999f12f2749f4d65f33d3f5882.so.0.0.0" "tmp_48cf10999f12f2749f4d65f33d3f5882.so")
libtool: link: ( cd ".libs" && rm -f "tmp_48cf10999f12f2749f4d65f33d3f5882.la" && ln -s "../tmp_48cf10999f12f2749f4d65f33d3f5882.la" "tmp_48cf10999f12f2749f4d65f33d3f5882.la" )
loading membrane mechanisms from /mnt/scratch/tmp/morphforge/tmp/modout/mod_1b9db84d43b77ec2fb2e53e206df6e31.so
loading membrane mechanisms from /mnt/scratch/tmp/morphforge/tmp/modout/mod_595fd1e1e00ca2d9deba3e407f51424f.so
loading membrane mechanisms from /mnt/scratch/tmp/morphforge/tmp/modout/mod_f0d9052fdfd19f720a7dd9bd9e578ef4.so
Running Hoc File: /mnt/scratch/tmp/morphforge/tmp/tmp_fadcccbfdf6c8eef1cde95e3ec5a28d2.hoc
1
1
0.01
0
1
50000
1
Running Simulation
Time for Extracting Data: (1 records) 0.00188708305359
Running simulation : 1.497 seconds
Size of results file: 0.1 (MB)
Post-processing : 0.027 seconds
Entire load-run-save time : 2.577 seconds
Suceeded
No handlers could be found for logger "neurounits"
2013-12-01 17:15:55,067 - morphforge.core.logmgr - INFO - Logger Started OK
2013-12-01 17:15:55,067 - DISABLEDLOGGING - INFO - Ensuring Modfile is built
NEURON -- Release 7.3 (869:0141cf0aff14) 2013-05-10
Duke, Yale, and the BlueBrain Project -- Copyright 1984-2013
See http://www.neuron.yale.edu/neuron/credits
['DBUS_SESSION_BUS_ADDRESS', 'DEFAULTS_PATH', 'DESKTOP_SESSION', 'DESKTOP_STARTUP_ID', 'DISPLAY', 'GDMSESSION', 'GNOME_KEYRING_CONTROL', 'GNOME_KEYRING_PID', 'GREP_COLOR', 'GREP_OPTIONS', 'GRIN_ARGS', 'GTK_MODULES', 'HOME', 'INFANDANGO_CONFIGFILE', 'INFANDANGO_ROOT', 'LANG', 'LANGUAGE', 'LC_CTYPE', 'LD_LIBRARY_PATH', 'LESS', 'LOGNAME', 'LSCOLORS', 'MANDATORY_PATH', 'MREORG_CONFIG', 'OLDPWD', 'PAGER', 'PATH', 'PWD', 'PYTHONPATH', 'SHELL', 'SHLVL', 'SSH_AGENT_PID', 'SSH_AUTH_SOCK', 'TERM', 'TEXTDOMAIN', 'TEXTDOMAINDIR', 'UBUNTU_MENUPROXY', 'USER', 'WINDOWID', 'XAUTHORITY', 'XDG_CONFIG_DIRS', 'XDG_DATA_DIRS', 'XDG_RUNTIME_DIR', 'XDG_SEAT_PATH', 'XDG_SESSION_COOKIE', 'XDG_SESSION_PATH', 'XTERM_LOCALE', 'XTERM_SHELL', 'XTERM_VERSION', '_', '_JAVA_AWT_WM_NONREPARENTING']
Loading Bundle from: /mnt/scratch/tmp/morphforge/tmp/simulationresults/2a/2a9e13bbc911cf36dff438ab7625f7b4.bundle (20k) : 1.041 seconds
set(['conductance', 'reversalpotential'])
__dict__ {'mm_neuronNumber': None, 'cachedNeuronSuffix': None, 'reversalpotential': array(-54.3) * mV, '_name': 'LkChl', '_simulation': None, 'conductance': array(3.0) * s**3*A**2/(kg*m**4)}
loading membrane mechanisms from /mnt/scratch/tmp/morphforge/tmp/modout/mod_a290c9a645340023c23922c59afedba8.so
loading membrane mechanisms from /mnt/scratch/tmp/morphforge/tmp/modout/mod_493e4afc99901274d3bc57b05062327c.so
loading membrane mechanisms from /mnt/scratch/tmp/morphforge/tmp/modout/mod_f0d9052fdfd19f720a7dd9bd9e578ef4.so
Running Hoc File: /mnt/scratch/tmp/morphforge/tmp/tmp_00eb70358a20f499fd897c2d662fb660.hoc
1
1
0.01
0
1
50000
1
Running Simulation
Time for Extracting Data: (1 records) 0.00178408622742
Running simulation : 0.322 seconds
Size of results file: 0.1 (MB)
Post-processing : 0.008 seconds
Entire load-run-save time : 1.372 seconds
Suceeded
ounits.ast.astobjects.SuppliedValue'>
Writing assignment for: <EqnAssignmentByRegime [id:83564752] Symbol: m_alpha >
V <class 'neurounits.ast.astobjects.SuppliedValue'>
T [<class 'neurounits.ast.astobjects.MulOp'>]
V <class 'neurounits.ast.astobjects.SuppliedValue'>
Writing assignment for: <EqnAssignmentByRegime [id:83566096] Symbol: m_tau >
m_alpha <class 'neurounits.ast.astobjects.AssignedVariable'>
m_beta <class 'neurounits.ast.astobjects.AssignedVariable'>
Writing assignment for: <EqnAssignmentByRegime [id:83564944] Symbol: m_inf >
m_alpha <class 'neurounits.ast.astobjects.AssignedVariable'>
m_alpha <class 'neurounits.ast.astobjects.AssignedVariable'>
m_beta <class 'neurounits.ast.astobjects.AssignedVariable'>
Writing assignment for: <EqnAssignmentByRegime [id:83570960] Symbol: h_beta >
T [<class 'neurounits.ast.astobjects.DivOp'>]
V <class 'neurounits.ast.astobjects.SuppliedValue'>
Writing assignment for: <EqnAssignmentByRegime [id:83566416] Symbol: h_alpha >
T [<class 'neurounits.ast.astobjects.DivOp'>]
V <class 'neurounits.ast.astobjects.SuppliedValue'>
Writing assignment for: <EqnAssignmentByRegime [id:83565904] Symbol: h_inf >
h_alpha <class 'neurounits.ast.astobjects.AssignedVariable'>
h_alpha <class 'neurounits.ast.astobjects.AssignedVariable'>
h_beta <class 'neurounits.ast.astobjects.AssignedVariable'>
Writing assignment for: <EqnAssignmentByRegime [id:83570768] Symbol: GATEPROP >
m <class 'neurounits.ast.astobjects.StateVariable'>
m <class 'neurounits.ast.astobjects.StateVariable'>
m <class 'neurounits.ast.astobjects.StateVariable'>
h <class 'neurounits.ast.astobjects.StateVariable'>
Writing assignment for: <EqnAssignmentByRegime [id:83565328] Symbol: g >
GMAX <class 'neurounits.ast.astobjects.Parameter'>
GATEPROP <class 'neurounits.ast.astobjects.AssignedVariable'>
Writing assignment for: <EqnAssignmentByRegime [id:83565520] Symbol: I >
g <class 'neurounits.ast.astobjects.AssignedVariable'>
V <class 'neurounits.ast.astobjects.SuppliedValue'>
VREV <class 'neurounits.ast.astobjects.Parameter'>
Writing assignment for: <EqnAssignmentByRegime [id:83565136] Symbol: h_tau >
h_alpha <class 'neurounits.ast.astobjects.AssignedVariable'>
h_beta <class 'neurounits.ast.astobjects.AssignedVariable'>
m_inf <class 'neurounits.ast.astobjects.AssignedVariable'>
m <class 'neurounits.ast.astobjects.StateVariable'>
m_tau <class 'neurounits.ast.astobjects.AssignedVariable'>
h_inf <class 'neurounits.ast.astobjects.AssignedVariable'>
h <class 'neurounits.ast.astobjects.StateVariable'>
h_tau <class 'neurounits.ast.astobjects.AssignedVariable'>
Loading Channel Type: KConductance
_run_spawn() [Loading results from /mnt/scratch/tmp/morphforge/tmp/simulationresults/9f//9fb2f6f970d82de3f4ffd52f1994ca45.neuronsim.results.pickle ]
Loading Channel Type: NaChannel
Loading Channel Type: KConductance
_run_spawn() [Loading results from /mnt/scratch/tmp/morphforge/tmp/simulationresults/2a//2a9e13bbc911cf36dff438ab7625f7b4.neuronsim.results.pickle ]
CHECKING
<Parameter [id:87654096] Symbol: 'g' >
g
iii 1.0 s**3*A**2/(kg*m**4) <class 'quantities.quantity.Quantity'>
iiii 1200.0 s**3*A**2/(kg*m**4) <class 'quantities.quantity.Quantity'>
OK
Output <StateVariable [id:87651600] Symbol: 'h' >
None
Output <StateVariable [id:87664080] Symbol: 'm' >
None
Output <AssignedVariable [id:87664784] Symbol: 'h_alpha_rate' >
None
Output <AssignedVariable [id:87664592] Symbol: 'h_beta_rate' >
None
Output <AssignedVariable [id:87670864] Symbol: 'hinf' >
None
Output <AssignedVariable [id:87666512] Symbol: 'htau' >
None
Output <AssignedVariable [id:87672592] Symbol: 'i' >
{u'mf': {u'role': u'TRANSMEMBRANECURRENT'}}
Output <AssignedVariable [id:87666128] Symbol: 'm_alpha_rate' >
None
Output <AssignedVariable [id:87672976] Symbol: 'm_beta_rate' >
None
Output <AssignedVariable [id:87664208] Symbol: 'minf' >
None
Output <AssignedVariable [id:87664976] Symbol: 'mtau' >
None
input <SuppliedValue [id:87673232] Symbol: 'v' >
{u'mf': {u'role': u'MEMBRANEVOLTAGE'}}
T [<class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SuppliedValue'>]
v <class 'neurounits.ast.astobjects.SuppliedValue'>
h_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
h_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
h_beta_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
T [<class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SuppliedValue'>]
v <class 'neurounits.ast.astobjects.SuppliedValue'>
m_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
m_beta_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
g <class 'neurounits.ast.astobjects.Parameter'>
v <class 'neurounits.ast.astobjects.SuppliedValue'>
m <class 'neurounits.ast.astobjects.StateVariable'>
h <class 'neurounits.ast.astobjects.StateVariable'>
T [<class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SuppliedValue'>]
v <class 'neurounits.ast.astobjects.SuppliedValue'>
T [<class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SuppliedValue'>]
v <class 'neurounits.ast.astobjects.SuppliedValue'>
m_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
m_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
m_beta_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
h_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
h_beta_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
Writing assignment for: <EqnAssignmentByRegime [id:87664720] Symbol: h_beta_rate >
T [<class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SuppliedValue'>]
v <class 'neurounits.ast.astobjects.SuppliedValue'>
Writing assignment for: <EqnAssignmentByRegime [id:87664912] Symbol: h_alpha_rate >
T [<class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SuppliedValue'>]
v <class 'neurounits.ast.astobjects.SuppliedValue'>
Writing assignment for: <EqnAssignmentByRegime [id:87670992] Symbol: hinf >
h_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
h_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
h_beta_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
Writing assignment for: <EqnAssignmentByRegime [id:87666256] Symbol: m_alpha_rate >
T [<class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SuppliedValue'>]
v <class 'neurounits.ast.astobjects.SuppliedValue'>
Writing assignment for: <EqnAssignmentByRegime [id:87673104] Symbol: m_beta_rate >
T [<class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SuppliedValue'>]
v <class 'neurounits.ast.astobjects.SuppliedValue'>
Writing assignment for: <EqnAssignmentByRegime [id:87665104] Symbol: mtau >
m_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
m_beta_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
Writing assignment for: <EqnAssignmentByRegime [id:87672720] Symbol: i >
g <class 'neurounits.ast.astobjects.Parameter'>
v <class 'neurounits.ast.astobjects.SuppliedValue'>
m <class 'neurounits.ast.astobjects.StateVariable'>
h <class 'neurounits.ast.astobjects.StateVariable'>
Writing assignment for: <EqnAssignmentByRegime [id:87666640] Symbol: htau >
h_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
h_beta_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
Writing assignment for: <EqnAssignmentByRegime [id:87664336] Symbol: minf >
m_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
m_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
m_beta_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
minf <class 'neurounits.ast.astobjects.AssignedVariable'>
m <class 'neurounits.ast.astobjects.StateVariable'>
mtau <class 'neurounits.ast.astobjects.AssignedVariable'>
hinf <class 'neurounits.ast.astobjects.AssignedVariable'>
h <class 'neurounits.ast.astobjects.StateVariable'>
htau <class 'neurounits.ast.astobjects.AssignedVariable'>
a1 <class 'neurounits.ast.astobjects.FunctionDefParameter'>
a2 <class 'neurounits.ast.astobjects.FunctionDefParameter'>
V <class 'neurounits.ast.astobjects.FunctionDefParameter'>
a3 <class 'neurounits.ast.astobjects.FunctionDefParameter'>
T [<class 'neurounits.ast.astobjects.DivOp'>]
V <class 'neurounits.ast.astobjects.FunctionDefParameter'>
a4 <class 'neurounits.ast.astobjects.FunctionDefParameter'>
a5 <class 'neurounits.ast.astobjects.FunctionDefParameter'>
Output <AssignedVariable [id:87598992] Symbol: 'i' >
{u'mf': {u'role': u'TRANSMEMBRANECURRENT'}}
input <SuppliedValue [id:87630096] Symbol: 'v' >
{u'mf': {u'role': u'MEMBRANEVOLTAGE'}}
v <class 'neurounits.ast.astobjects.SuppliedValue'>
Writing assignment for: <EqnAssignmentByRegime [id:87599568] Symbol: i >
v <class 'neurounits.ast.astobjects.SuppliedValue'>
Output <StateVariable [id:87547280] Symbol: 'n' >
None
Output <AssignedVariable [id:87532304] Symbol: 'i' >
{u'mf': {u'role': u'TRANSMEMBRANECURRENT'}}
Output <AssignedVariable [id:87547152] Symbol: 'n_alpha_rate' >
None
Output <AssignedVariable [id:87534032] Symbol: 'n_beta_rate' >
None
Output <AssignedVariable [id:87533648] Symbol: 'ninf' >
None
Output <AssignedVariable [id:87544976] Symbol: 'ntau' >
None
input <SuppliedValue [id:87535120] Symbol: 'v' >
{u'mf': {u'role': u'MEMBRANEVOLTAGE'}}
T [<class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SuppliedValue'>]
v <class 'neurounits.ast.astobjects.SuppliedValue'>
T [<class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SuppliedValue'>]
v <class 'neurounits.ast.astobjects.SuppliedValue'>
n_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
n_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
n_beta_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
n_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
n_beta_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
v <class 'neurounits.ast.astobjects.SuppliedValue'>
n <class 'neurounits.ast.astobjects.StateVariable'>
No handlers could be found for logger "neurounits"
2013-12-01 17:15:59,651 - morphforge.core.logmgr - INFO - Logger Started OK
2013-12-01 17:15:59,652 - DISABLEDLOGGING - INFO - Ensuring Modfile is built
NEURON -- Release 7.3 (869:0141cf0aff14) 2013-05-10
Duke, Yale, and the BlueBrain Project -- Copyright 1984-2013
See http://www.neuron.yale.edu/neuron/credits
['DBUS_SESSION_BUS_ADDRESS', 'DEFAULTS_PATH', 'DESKTOP_SESSION', 'DESKTOP_STARTUP_ID', 'DISPLAY', 'GDMSESSION', 'GNOME_KEYRING_CONTROL', 'GNOME_KEYRING_PID', 'GREP_COLOR', 'GREP_OPTIONS', 'GRIN_ARGS', 'GTK_MODULES', 'HOME', 'INFANDANGO_CONFIGFILE', 'INFANDANGO_ROOT', 'LANG', 'LANGUAGE', 'LC_CTYPE', 'LD_LIBRARY_PATH', 'LESS', 'LOGNAME', 'LSCOLORS', 'MANDATORY_PATH', 'MREORG_CONFIG', 'OLDPWD', 'PAGER', 'PATH', 'PWD', 'PYTHONPATH', 'SHELL', 'SHLVL', 'SSH_AGENT_PID', 'SSH_AUTH_SOCK', 'TERM', 'TEXTDOMAIN', 'TEXTDOMAINDIR', 'UBUNTU_MENUPROXY', 'USER', 'WINDOWID', 'XAUTHORITY', 'XDG_CONFIG_DIRS', 'XDG_DATA_DIRS', 'XDG_RUNTIME_DIR', 'XDG_SEAT_PATH', 'XDG_SESSION_COOKIE', 'XDG_SESSION_PATH', 'XTERM_LOCALE', 'XTERM_SHELL', 'XTERM_VERSION', '_', '_JAVA_AWT_WM_NONREPARENTING']
Loading Bundle from: /mnt/scratch/tmp/morphforge/tmp/simulationresults/6d/6da8c32e20d060372d72edb98dcfc7e6.bundle (139k) : 0.986 seconds
Executing: /home/michael/opt//x86_64/bin/modlunit /mnt/scratch/tmp/morphforge/tmp/tmp_6c4edc63e462f424e4c70e8cbcc883a0.mod
/mnt/scratch/tmp/morphforge/tmp/modbuild_23593
Executing: /home/michael/opt//x86_64/bin/nocmodl tmp_6c4edc63e462f424e4c70e8cbcc883a0.mod
Executing: /home/michael/opt//share/nrn/libtool --mode=compile gcc -DHAVE_CONFIG_H -I"." -I".." -I"/home/michael/opt//include/nrn" -I"/home/michael/opt//x86_64/lib" -g -O2 -c -o tmp_6c4edc63e462f424e4c70e8cbcc883a0.lo tmp_6c4edc63e462f424e4c70e8cbcc883a0.c
Executing: /home/michael/opt//share/nrn/libtool --mode=link gcc -module -g -O2 -shared -o tmp_6c4edc63e462f424e4c70e8cbcc883a0.la -rpath /home/michael/opt//x86_64/libs tmp_6c4edc63e462f424e4c70e8cbcc883a0.lo -L/home/michael/opt//x86_64/lib -L/home/michael/opt//x86_64/lib /home/michael/opt//x86_64/lib/libnrniv.la -lnrnoc -loc -lmemacs -lnrnmpi -lscopmath -lsparse13 -lreadline -lncurses -livoc -lneuron_gnu -lmeschach -lsundials -lm -ldl
OP1: libtool: compile: gcc -DHAVE_CONFIG_H -I. -I.. -I/home/michael/opt//include/nrn -I/home/michael/opt//x86_64/lib -g -O2 -c tmp_6c4edc63e462f424e4c70e8cbcc883a0.c -fPIC -DPIC -o .libs/tmp_6c4edc63e462f424e4c70e8cbcc883a0.o
OP2: libtool: link: gcc -shared -fPIC -DPIC .libs/tmp_6c4edc63e462f424e4c70e8cbcc883a0.o -Wl,-rpath -Wl,/home/michael/opt/x86_64/lib -Wl,-rpath -Wl,/home/michael/opt/x86_64/lib -L/home/michael/opt//x86_64/lib /home/michael/opt/x86_64/lib/libnrniv.so /home/michael/opt/x86_64/lib/libnrnoc.so /home/michael/opt/x86_64/lib/liboc.so /home/michael/opt/x86_64/lib/libmemacs.so /home/michael/opt/x86_64/lib/libnrnmpi.so /home/michael/opt/x86_64/lib/libscopmath.so /home/michael/opt/x86_64/lib/libsparse13.so -lreadline -lncurses /home/michael/opt/x86_64/lib/libivoc.so /home/michael/opt/x86_64/lib/libneuron_gnu.so /home/michael/opt/x86_64/lib/libmeschach.so /home/michael/opt/x86_64/lib/libsundials.so -lm -ldl -O2 -pthread -Wl,-soname -Wl,tmp_6c4edc63e462f424e4c70e8cbcc883a0.so.0 -o .libs/tmp_6c4edc63e462f424e4c70e8cbcc883a0.so.0.0.0
libtool: link: (cd ".libs" && rm -f "tmp_6c4edc63e462f424e4c70e8cbcc883a0.so.0" && ln -s "tmp_6c4edc63e462f424e4c70e8cbcc883a0.so.0.0.0" "tmp_6c4edc63e462f424e4c70e8cbcc883a0.so.0")
libtool: link: (cd ".libs" && rm -f "tmp_6c4edc63e462f424e4c70e8cbcc883a0.so" && ln -s "tmp_6c4edc63e462f424e4c70e8cbcc883a0.so.0.0.0" "tmp_6c4edc63e462f424e4c70e8cbcc883a0.so")
libtool: link: ( cd ".libs" && rm -f "tmp_6c4edc63e462f424e4c70e8cbcc883a0.la" && ln -s "../tmp_6c4edc63e462f424e4c70e8cbcc883a0.la" "tmp_6c4edc63e462f424e4c70e8cbcc883a0.la" )
loading membrane mechanisms from /mnt/scratch/tmp/morphforge/tmp/modout/mod_b710d7b3064eaabef925f2922f85b448.so
loading membrane mechanisms from /mnt/scratch/tmp/morphforge/tmp/modout/mod_7e798569f10b7cd5b42e75f7cea8a7ea.so
loading membrane mechanisms from /mnt/scratch/tmp/morphforge/tmp/modout/mod_02fe20696304be49ae774511a85392b8.so
Running Hoc File: /mnt/scratch/tmp/morphforge/tmp/tmp_4c11f22d9eebc78affb275e22ffe435e.hoc
1
1
0.01
0
1
50000
1
50000
1
50000
1
50000
1
50000
1
50000
1
50000
1
Running Simulation
Time for Extracting Data: (7 records) 0.0116751194
Running simulation : 1.488 seconds
Size of results file: 0.3 (MB)
Post-processing : 0.048 seconds
Entire load-run-save time : 2.522 seconds
Suceeded
n <class 'neurounits.ast.astobjects.StateVariable'>
n <class 'neurounits.ast.astobjects.StateVariable'>
n <class 'neurounits.ast.astobjects.StateVariable'>
Writing assignment for: <EqnAssignmentByRegime [id:87534160] Symbol: n_beta_rate >
T [<class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SuppliedValue'>]
v <class 'neurounits.ast.astobjects.SuppliedValue'>
Writing assignment for: <EqnAssignmentByRegime [id:87532048] Symbol: n_alpha_rate >
T [<class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SymbolicConstant'>, <class 'neurounits.ast.astobjects.SuppliedValue'>]
v <class 'neurounits.ast.astobjects.SuppliedValue'>
Writing assignment for: <EqnAssignmentByRegime [id:87533776] Symbol: ninf >
n_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
n_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
n_beta_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
Writing assignment for: <EqnAssignmentByRegime [id:87532432] Symbol: i >
v <class 'neurounits.ast.astobjects.SuppliedValue'>
n <class 'neurounits.ast.astobjects.StateVariable'>
n <class 'neurounits.ast.astobjects.StateVariable'>
n <class 'neurounits.ast.astobjects.StateVariable'>
n <class 'neurounits.ast.astobjects.StateVariable'>
Writing assignment for: <EqnAssignmentByRegime [id:87544592] Symbol: ntau >
n_alpha_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
n_beta_rate <class 'neurounits.ast.astobjects.AssignedVariable'>
ninf <class 'neurounits.ast.astobjects.AssignedVariable'>
n <class 'neurounits.ast.astobjects.StateVariable'>
ntau <class 'neurounits.ast.astobjects.AssignedVariable'>
a1 <class 'neurounits.ast.astobjects.FunctionDefParameter'>
a2 <class 'neurounits.ast.astobjects.FunctionDefParameter'>
V <class 'neurounits.ast.astobjects.FunctionDefParameter'>
a3 <class 'neurounits.ast.astobjects.FunctionDefParameter'>
T [<class 'neurounits.ast.astobjects.DivOp'>]
V <class 'neurounits.ast.astobjects.FunctionDefParameter'>
a4 <class 'neurounits.ast.astobjects.FunctionDefParameter'>
a5 <class 'neurounits.ast.astobjects.FunctionDefParameter'>
_run_spawn() [Loading results from /mnt/scratch/tmp/morphforge/tmp/simulationresults/6d//6da8c32e20d060372d72edb98dcfc7e6.neuronsim.results.pickle ]
PlotManger saving: _output/figures/assorted_10compareHHChls/{png,svg}/fig000_Autosave_figure_1.{png,svg}