def test_liaf(self,
plot=PLOT_DEFAULT,
print_comparisons=False,
simulators=SIMULATORS_TO_TEST,
dt=0.001,
duration=100.0,
build_mode=BUILD_MODE_DEFAULT,
**kwargs): # @UnusedVariable
# Perform comparison in subprocess
comparer = Comparer(
nineml_model=ninemlcatalog.load('neuron/LeakyIntegrateAndFire',
'PyNNLeakyIntegrateAndFire'),
state_variable='v',
dt=dt,
simulators=simulators,
properties=ninemlcatalog.load(
'neuron/LeakyIntegrateAndFire',
'PyNNLeakyIntegrateAndFireProperties'),
initial_states=self.liaf_initial_states,
initial_regime='subthreshold',
neuron_ref='ResetRefrac',
nest_ref='iaf_psc_alpha',
input_signal=input_step('i_synaptic', 1, 50, 100, dt, 20),
nest_translations=self.liaf_nest_translations,
neuron_translations=self.liaf_neuron_translations,
neuron_build_args={'build_mode': build_mode},
nest_build_args={'build_mode': build_mode},
# auxiliary_states=['end_refractory'],
extra_mechanisms=['pas'])
comparer.simulate(duration * un.ms,
nest_rng_seed=NEST_RNG_SEED,
neuron_rng_seed=NEURON_RNG_SEED)
comparisons = comparer.compare()
if print_comparisons:
for (name1, name2), diff in comparisons.items():
print('{} v {}: {}'.format(name1, name2, diff))
if plot:
comparer.plot()
if 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-neuron', 'Ref-neuron')], 0.55 * pq.mV,
"LIaF NEURON 9ML simulation did not match reference PyNN "
"within {} ({})".format(
0.55 * pq.mV, comparisons[('9ML-neuron', 'Ref-neuron')]))
if 'nest' in simulators:
self.assertLess(
comparisons[('9ML-nest', 'Ref-nest')], 0.01 * pq.mV,
"LIaF NEST 9ML simulation did not match reference built-in "
"within {} ({})".format(0.01 * pq.mV,
comparisons[('9ML-nest', 'Ref-nest')]))
if 'nest' in simulators and 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-nest', '9ML-neuron')], 0.55 * pq.mV,
"LIaF NEURON 9ML simulation did not match NEST 9ML simulation "
"within {} ({})".format(
0.55 * pq.mV, comparisons[('9ML-nest', '9ML-neuron')]))
def test_izhiFS(self, plot=False, print_comparisons=False,
simulators=['nest', 'neuron'], dt=0.001, duration=100.0,
build_mode='force', **kwargs): # @UnusedVariable
# Force compilation of code generation
# Perform comparison in subprocess
comparer = Comparer(
nineml_model=ninemlcatalog.load(
'neuron/Izhikevich', 'IzhikevichFastSpiking'),
state_variable='V', dt=dt, simulators=simulators,
properties=ninemlcatalog.load(
'neuron/Izhikevich', 'SampleIzhikevichFastSpiking'),
initial_states={'U': -1.625 * pq.pA, 'V': -65.0 * pq.mV},
input_signal=input_step('iSyn', 100 * pq.pA, 25.0, 100, dt),
initial_regime='subVb',
neuron_build_args={'build_mode': build_mode,
'external_currents': ['iSyn']},
nest_build_args={'build_mode': build_mode}) #, auxiliary_states=['U']) # @IgnorePep8
comparer.simulate(duration, nest_rng_seed=NEST_RNG_SEED,
neuron_rng_seed=NEURON_RNG_SEED)
comparisons = comparer.compare()
if print_comparisons:
for (name1, name2), diff in comparisons.iteritems():
print '{} v {}: {}'.format(name1, name2, diff)
if plot:
comparer.plot()
if 'nest' in simulators and 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-nest', '9ML-neuron')], 0.4 * pq.mV,
"Izhikevich 2007 NEURON 9ML simulation did not match NEST 9ML")
def test_izhi(self, plot=PLOT_DEFAULT, print_comparisons=False,
simulators=SIMULATORS_TO_TEST,
dt=0.001, duration=100.0,
build_mode=BUILD_MODE_DEFAULT, **kwargs): # @UnusedVariable
# Force compilation of code generation
# Perform comparison in subprocess
comparer = Comparer(
nineml_model=ninemlcatalog.load(
'neuron/Izhikevich', 'Izhikevich'),
state_variable='V', dt=dt, simulators=simulators,
properties=ninemlcatalog.load(
'neuron/Izhikevich', 'SampleIzhikevich'),
initial_states={'U': -14.0 * pq.mV / pq.ms, 'V': -65.0 * pq.mV},
neuron_ref='Izhikevich', nest_ref='izhikevich',
# auxiliary_states=['U'],
input_signal=input_step('Isyn', 0.02, 50, 100, dt, 30),
nest_translations={'V': ('V_m', 1), 'U': ('U_m', 1),
'weight': (None, 1), 'C_m': (None, 1),
'theta': ('V_th', 1),
'alpha': (None, 1), 'beta': (None, 1),
'zeta': (None, 1)},
neuron_translations={'C_m': (None, 1), 'weight': (None, 1),
'V': ('v', 1), 'U': ('u', 1),
'alpha': (None, 1), 'beta': (None, 1),
'zeta': (None, 1), 'theta': ('vthresh', 1)},
neuron_build_args={'build_mode': build_mode,
'build_version': 'TestDyn'},
nest_build_args={'build_mode': build_mode,
'build_version': 'TestDyn'})
comparer.simulate(duration * un.ms, nest_rng_seed=NEST_RNG_SEED,
neuron_rng_seed=NEURON_RNG_SEED)
comparisons = comparer.compare()
if print_comparisons:
for (name1, name2), diff in comparisons.items():
print('{} v {}: {}'.format(name1, name2, diff))
if plot:
comparer.plot()
if 'nest' in simulators and 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-nest', '9ML-neuron')], 0.4 * pq.mV,
"Izhikevich NEURON 9ML simulation did not match NEST 9ML "
"within {} ({})".format(
0.4 * pq.mV, comparisons[('9ML-nest', '9ML-neuron')]))
if 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-neuron', 'Ref-neuron')], 0.01 * pq.mV,
"Izhikevich NEURON 9ML simulation did not match reference "
"PyNN within {} ({})".format(
0.01 * pq.mV, comparisons[('9ML-neuron', 'Ref-neuron')]))
if 'nest' in simulators:
self.assertLess(
comparisons[('9ML-nest', 'Ref-nest')], 0.02 * pq.mV,
"Izhikevich NEST 9ML simulation did not match reference "
"built-in within {} ({})".format(
0.02 * pq.mV, comparisons[('9ML-nest', 'Ref-nest')]))
def test_izhiFS(self,
plot=PLOT_DEFAULT,
print_comparisons=False,
simulators=SIMULATORS_TO_TEST,
dt=0.001,
duration=100.0,
build_mode=BUILD_MODE_DEFAULT,
**kwargs): # @UnusedVariable @IgnorePep8
# Force compilation of code generation
# Perform comparison in subprocess
comparer = Comparer(
nineml_model=ninemlcatalog.load('neuron/Izhikevich',
'IzhikevichFastSpiking'),
state_variable='V',
dt=dt,
simulators=simulators,
properties=ninemlcatalog.load('neuron/Izhikevich',
'SampleIzhikevichFastSpiking'),
initial_states={
'U': -1.625 * pq.pA,
'V': -65.0 * pq.mV
},
input_signal=input_step('iSyn', 100 * pq.pA, 25.0, 100, dt, 15),
initial_regime='subVb',
neuron_build_args={
'build_mode': build_mode,
'build_version': 'TestDyn',
'external_currents': ['iSyn']
},
# auxiliary_states=['U'],
nest_build_args={
'build_mode': build_mode,
'build_version': 'TestDyn'
})
comparer.simulate(duration * un.ms,
nest_rng_seed=NEST_RNG_SEED,
neuron_rng_seed=NEURON_RNG_SEED)
comparisons = comparer.compare()
if print_comparisons:
for (name1, name2), diff in comparisons.items():
print('{} v {}: {}'.format(name1, name2, diff))
if plot:
comparer.plot()
if 'nest' in simulators and 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-nest', '9ML-neuron')], 0.4 * pq.mV,
"Izhikevich 2007 NEURON 9ML simulation did not match NEST 9ML")
def test_izhi(self, plot=False, print_comparisons=False,
simulators=['nest', 'neuron'], dt=0.001, duration=100.0,
build_mode='force', **kwargs): # @UnusedVariable
# Force compilation of code generation
# Perform comparison in subprocess
comparer = Comparer(
nineml_model=ninemlcatalog.load(
'neuron/Izhikevich', 'Izhikevich'),
state_variable='V', dt=dt, simulators=simulators,
properties=ninemlcatalog.load(
'neuron/Izhikevich', 'SampleIzhikevich'),
initial_states={'U': -14.0 * pq.mV / pq.ms, 'V': -65.0 * pq.mV},
neuron_ref='Izhikevich', nest_ref='izhikevich',
input_signal=input_step('Isyn', 0.02, 50, 100, dt),
nest_translations={'V': ('V_m', 1), 'U': ('U_m', 1),
'weight': (None, 1), 'C_m': (None, 1),
'theta': ('V_th', 1),
'alpha': (None, 1), 'beta': (None, 1),
'zeta': (None, 1)},
neuron_translations={'C_m': (None, 1), 'weight': (None, 1),
'V': ('v', 1), 'U': ('u', 1),
'alpha': (None, 1), 'beta': (None, 1),
'zeta': (None, 1), 'theta': ('vthresh', 1)},
neuron_build_args={'build_mode': build_mode},
nest_build_args={'build_mode': build_mode},
build_name='Izhikevich9ML')
comparer.simulate(duration, nest_rng_seed=NEST_RNG_SEED,
neuron_rng_seed=NEURON_RNG_SEED)
comparisons = comparer.compare()
if print_comparisons:
for (name1, name2), diff in comparisons.iteritems():
print '{} v {}: {}'.format(name1, name2, diff)
if plot:
comparer.plot()
if 'nest' in simulators and 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-nest', '9ML-neuron')], 0.4 * pq.mV,
"Izhikevich NEURON 9ML simulation did not match NEST 9ML")
if 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-neuron', 'Ref-neuron')], 0.0015 * pq.mV,
"Izhikevich NEURON 9ML simulation did not match reference "
"PyNN")
if 'nest' in simulators:
self.assertLess(
comparisons[('9ML-nest', 'Ref-nest')], 0.02 * pq.mV,
"Izhikevich NEST 9ML simulation did not match reference "
"built-in")
def test_liaf(self, plot=PLOT_DEFAULT, print_comparisons=False,
simulators=SIMULATORS_TO_TEST, dt=0.001, duration=100.0,
build_mode=BUILD_MODE_DEFAULT, **kwargs): # @UnusedVariable
# Perform comparison in subprocess
comparer = Comparer(
nineml_model=ninemlcatalog.load(
'neuron/LeakyIntegrateAndFire',
'PyNNLeakyIntegrateAndFire'),
state_variable='v', dt=dt, simulators=simulators,
properties=ninemlcatalog.load(
'neuron/LeakyIntegrateAndFire',
'PyNNLeakyIntegrateAndFireProperties'),
initial_states=self.liaf_initial_states,
initial_regime='subthreshold',
neuron_ref='ResetRefrac', nest_ref='iaf_psc_alpha',
input_signal=input_step('i_synaptic', 1, 50, 100, dt, 20),
nest_translations=self.liaf_nest_translations,
neuron_translations=self.liaf_neuron_translations,
neuron_build_args={'build_mode': build_mode},
nest_build_args={'build_mode': build_mode},
# auxiliary_states=['end_refractory'],
extra_mechanisms=['pas'])
comparer.simulate(duration * un.ms, nest_rng_seed=NEST_RNG_SEED,
neuron_rng_seed=NEURON_RNG_SEED)
comparisons = comparer.compare()
if print_comparisons:
for (name1, name2), diff in comparisons.items():
print('{} v {}: {}'.format(name1, name2, diff))
if plot:
comparer.plot()
if 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-neuron', 'Ref-neuron')], 0.55 * pq.mV,
"LIaF NEURON 9ML simulation did not match reference PyNN "
"within {} ({})".format(
0.55 * pq.mV, comparisons[('9ML-neuron', 'Ref-neuron')]))
if 'nest' in simulators:
self.assertLess(
comparisons[('9ML-nest', 'Ref-nest')], 0.01 * pq.mV,
"LIaF NEST 9ML simulation did not match reference built-in "
"within {} ({})".format(
0.01 * pq.mV, comparisons[('9ML-nest', 'Ref-nest')]))
if 'nest' in simulators and 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-nest', '9ML-neuron')], 0.55 * pq.mV,
"LIaF NEURON 9ML simulation did not match NEST 9ML simulation "
"within {} ({})".format(
0.55 * pq.mV, comparisons[('9ML-nest', '9ML-neuron')]))
def test_alpha_syn(self, plot=False, print_comparisons=False,
simulators=['nest', 'neuron'], dt=0.001,
duration=100.0, min_delay=5.0, device_delay=5.0,
build_mode='force', **kwargs): # @UnusedVariable
# Perform comparison in subprocess
iaf = ninemlcatalog.load(
'neuron/LeakyIntegrateAndFire', 'PyNNLeakyIntegrateAndFire')
alpha_psr = ninemlcatalog.load(
'postsynapticresponse/Alpha', 'PyNNAlpha')
static = ninemlcatalog.load(
'plasticity/Static', 'Static')
iaf_alpha = MultiDynamics(
name='IafAlpha',
sub_components={
'cell': iaf,
'syn': MultiDynamics(
name="IafAlaphSyn",
sub_components={'psr': alpha_psr, 'pls': static},
port_connections=[
('pls', 'fixed_weight', 'psr', 'q')],
port_exposures=[('psr', 'i_synaptic'),
('psr', 'spike')])},
port_connections=[
('syn', 'i_synaptic__psr', 'cell', 'i_synaptic')],
port_exposures=[('syn', 'spike__psr', 'spike')])
iaf_alpha_with_syn = MultiDynamicsWithSynapses(
'IafAlpha',
iaf_alpha,
connection_parameter_sets=[
ConnectionParameterSet(
'spike', [iaf_alpha.parameter('weight__pls__syn')])])
initial_states = {'a__psr__syn': 0.0 * pq.nA,
'b__psr__syn': 0.0 * pq.nA}
initial_regime = 'subthreshold___sole_____sole'
liaf_properties = ninemlcatalog.load(
'neuron/LeakyIntegrateAndFire/',
'PyNNLeakyIntegrateAndFireProperties')
alpha_properties = ninemlcatalog.load(
'postsynapticresponse/Alpha', 'SamplePyNNAlphaProperties')
nest_tranlsations = {'tau__psr__syn': ('tau_syn_ex', 1),
'a__psr__syn': (None, 1),
'b__psr__syn': (None, 1),
'spike': ('spike', 1000.0)}
neuron_tranlsations = {'tau__psr__syn': ('psr.tau', 1),
'q__psr__syn': ('psr.q', 1),
'spike': ('spike', 1),
'a__psr__syn': (None, 1),
'b__psr__syn': (None, 1)}
initial_states.update(
(k + '__cell', v) for k, v in self.liaf_initial_states.iteritems())
properties = DynamicsProperties(
name='IafAlphaProperties', definition=iaf_alpha,
properties=dict(
(p.name + '__' + suffix, p.quantity)
for p, suffix in chain(
zip(liaf_properties.properties, repeat('cell')),
zip(alpha_properties.properties, repeat('psr__syn')),
[(Property('weight', 10 * un.nA), 'pls__syn')])))
properties_with_syn = DynamicsWithSynapsesProperties(
'IafAlpha_props_with_syn',
properties, # @IgnorePep8
connection_property_sets=[
ConnectionPropertySet(
'spike',
[properties.property('weight__pls__syn')])])
nest_tranlsations.update(
(k + '__cell', v)
for k, v in self.liaf_nest_translations.iteritems())
neuron_tranlsations.update(
(k + '__cell', v)
for k, v in self.liaf_neuron_translations.iteritems())
build_dir = os.path.join(os.path.dirname(iaf.url), '9build')
comparer = Comparer(
nineml_model=iaf_alpha_with_syn,
state_variable='v__cell', dt=dt,
simulators=simulators,
properties=properties_with_syn,
initial_states=initial_states,
initial_regime=initial_regime,
neuron_ref='ResetRefrac',
nest_ref='iaf_psc_alpha',
input_train=input_freq('spike', 450 * pq.Hz, duration,
weight=[Property('weight__pls__syn',
10 * un.nA)], # 20.680155243 * un.pA
offset=duration / 2.0),
nest_translations=nest_tranlsations,
neuron_translations=neuron_tranlsations,
extra_mechanisms=['pas'],
extra_point_process='AlphaISyn',
neuron_build_args={
'build_mode': build_mode,
'build_dir': os.path.join(build_dir, 'neuron', 'IaFAlpha')},
nest_build_args={
'build_mode': build_mode,
'build_dir': os.path.join(build_dir, 'nest', 'IaFAlpha')},
min_delay=min_delay,
device_delay=device_delay)
comparer.simulate(duration, nest_rng_seed=NEST_RNG_SEED,
neuron_rng_seed=NEURON_RNG_SEED)
comparisons = comparer.compare()
if print_comparisons:
for (name1, name2), diff in comparisons.iteritems():
print '{} v {}: {}'.format(name1, name2, diff)
if plot:
comparer.plot()
if 'nest' in simulators and 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-nest', '9ML-neuron')], 0.015 * pq.mV,
"LIaF with Alpha syn NEST 9ML simulation did not match NEURON "
"9ML simulation")
if 'nest' in simulators:
self.assertLess(
comparisons[('9ML-nest', 'Ref-nest')], 0.04 * pq.mV,
"LIaF with Alpha syn NEST 9ML simulation did not match "
"reference built-in")
if 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-neuron', 'Ref-neuron')], 0.03 * pq.mV,
"LIaF with Alpha syn NEURON 9ML simulation did not match "
"reference PyNN")
def test_hh(self, plot=False, print_comparisons=False,
simulators=['nest', 'neuron'], dt=0.001, duration=100.0,
build_mode='force', **kwargs): # @UnusedVariable
# Perform comparison in subprocess
comparer = Comparer(
nineml_model=ninemlcatalog.load(
'neuron/HodgkinHuxley', 'PyNNHodgkinHuxley'),
state_variable='v', dt=dt, simulators=simulators,
initial_states={'v': -65.0 * pq.mV, 'm': 0.0, 'h': 1.0, 'n': 0.0},
properties=ninemlcatalog.load(
'neuron/HodgkinHuxley', 'PyNNHodgkinHuxleyProperties'),
neuron_ref='hh_traub', nest_ref='hh_cond_exp_traub',
input_signal=input_step('iExt', 0.5, 50, 100, dt),
nest_translations={
'v': ('V_m', 1), 'm': ('Act_m', 1),
'h': ('Act_h', 1), 'n': ('Inact_n', 1),
'eNa': ('E_Na', 1), 'eK': ('E_K', 1), 'C': ('C_m', 1),
'gLeak': ('g_L', 1), 'eLeak': ('E_L', 1),
'gbarNa': ('g_Na', 1), 'gbarK': ('g_K', 1),
'v_rest': ('V_T', 1), 'v_threshold': (None, 1),
'm_alpha_A': (None, 1), 'm_alpha_V0': (None, 1),
'm_alpha_K': (None, 1), 'm_beta_A': (None, 1),
'm_beta_V0': (None, 1), 'm_beta_K': (None, 1),
'h_alpha_A': (None, 1), 'h_alpha_V0': (None, 1),
'h_alpha_K': (None, 1), 'h_beta_A': (None, 1),
'h_beta_V0': (None, 1), 'h_beta_K': (None, 1),
'n_alpha_A': (None, 1), 'n_alpha_V0': (None, 1),
'n_alpha_K': (None, 1), 'n_beta_A': (None, 1),
'n_beta_V0': (None, 1), 'n_beta_K': (None, 1)},
neuron_translations={
'eNa': ('ena', 1), 'eK': ('ek', 1), 'C': ('cm', 1),
'gLeak': ('gl', 1), 'eLeak': ('el', 1),
'gbarNa': ('gnabar', 1), 'gbarK': ('gkbar', 1),
'v_rest': ('vT', 1), 'v_threshold': (None, 1),
'm_alpha_A': (None, 1), 'm_alpha_V0': (None, 1),
'm_alpha_K': (None, 1), 'm_beta_A': (None, 1),
'm_beta_V0': (None, 1), 'm_beta_K': (None, 1),
'h_alpha_A': (None, 1), 'h_alpha_V0': (None, 1),
'h_alpha_K': (None, 1), 'h_beta_A': (None, 1),
'h_beta_V0': (None, 1), 'h_beta_K': (None, 1),
'n_alpha_A': (None, 1), 'n_alpha_V0': (None, 1),
'n_alpha_K': (None, 1), 'n_beta_A': (None, 1),
'n_beta_V0': (None, 1), 'n_beta_K': (None, 1)},
neuron_build_args={'build_mode': build_mode},
nest_build_args={'build_mode': build_mode})
comparer.simulate(duration, nest_rng_seed=NEST_RNG_SEED,
neuron_rng_seed=NEURON_RNG_SEED)
comparisons = comparer.compare()
if print_comparisons:
for (name1, name2), diff in comparisons.iteritems():
print '{} v {}: {}'.format(name1, name2, diff)
if plot:
comparer.plot()
# FIXME: Need to work out what is happening with the reference NEURON
if 'nest' in simulators and 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-nest', '9ML-neuron')], 0.5 * pq.mV,
"HH 9ML NEURON and NEST simulation did not match each other")
if 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-neuron', 'Ref-neuron')], 0.55 * pq.mV,
"HH 9ML NEURON simulation did not match reference built-in")
if 'nest' in simulators:
self.assertLess(
comparisons[('9ML-nest', 'Ref-nest')], 0.0015 * pq.mV,
"HH 9ML NEST simulation did not match reference built-in")
def test_izhi(self,
plot=PLOT_DEFAULT,
print_comparisons=False,
simulators=SIMULATORS_TO_TEST,
dt=0.001,
duration=100.0,
build_mode=BUILD_MODE_DEFAULT,
**kwargs): # @UnusedVariable
# Force compilation of code generation
# Perform comparison in subprocess
comparer = Comparer(
nineml_model=ninemlcatalog.load('neuron/Izhikevich', 'Izhikevich'),
state_variable='V',
dt=dt,
simulators=simulators,
properties=ninemlcatalog.load('neuron/Izhikevich',
'SampleIzhikevich'),
initial_states={
'U': -14.0 * pq.mV / pq.ms,
'V': -65.0 * pq.mV
},
neuron_ref='Izhikevich',
nest_ref='izhikevich',
# auxiliary_states=['U'],
input_signal=input_step('Isyn', 0.02, 50, 100, dt, 30),
nest_translations={
'V': ('V_m', 1),
'U': ('U_m', 1),
'weight': (None, 1),
'C_m': (None, 1),
'theta': ('V_th', 1),
'alpha': (None, 1),
'beta': (None, 1),
'zeta': (None, 1)
},
neuron_translations={
'C_m': (None, 1),
'weight': (None, 1),
'V': ('v', 1),
'U': ('u', 1),
'alpha': (None, 1),
'beta': (None, 1),
'zeta': (None, 1),
'theta': ('vthresh', 1)
},
neuron_build_args={
'build_mode': build_mode,
'build_version': 'TestDyn'
},
nest_build_args={
'build_mode': build_mode,
'build_version': 'TestDyn'
})
comparer.simulate(duration * un.ms,
nest_rng_seed=NEST_RNG_SEED,
neuron_rng_seed=NEURON_RNG_SEED)
comparisons = comparer.compare()
if print_comparisons:
for (name1, name2), diff in comparisons.items():
print('{} v {}: {}'.format(name1, name2, diff))
if plot:
comparer.plot()
if 'nest' in simulators and 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-nest', '9ML-neuron')], 0.4 * pq.mV,
"Izhikevich NEURON 9ML simulation did not match NEST 9ML "
"within {} ({})".format(
0.4 * pq.mV, comparisons[('9ML-nest', '9ML-neuron')]))
if 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-neuron', 'Ref-neuron')], 0.01 * pq.mV,
"Izhikevich NEURON 9ML simulation did not match reference "
"PyNN within {} ({})".format(
0.01 * pq.mV, comparisons[('9ML-neuron', 'Ref-neuron')]))
if 'nest' in simulators:
self.assertLess(
comparisons[('9ML-nest', 'Ref-nest')], 0.02 * pq.mV,
"Izhikevich NEST 9ML simulation did not match reference "
"built-in within {} ({})".format(
0.02 * pq.mV, comparisons[('9ML-nest', 'Ref-nest')]))
def test_alpha_syn(self,
plot=PLOT_DEFAULT,
print_comparisons=False,
simulators=SIMULATORS_TO_TEST,
dt=0.001,
duration=100.0,
min_delay=5.0,
device_delay=5.0,
build_mode=BUILD_MODE_DEFAULT,
**kwargs): # @UnusedVariable @IgnorePep8
# Perform comparison in subprocess
iaf = ninemlcatalog.load('neuron/LeakyIntegrateAndFire',
'PyNNLeakyIntegrateAndFire')
alpha_psr = ninemlcatalog.load('postsynapticresponse/Alpha',
'PyNNAlpha')
static = ninemlcatalog.load('plasticity/Static', 'Static')
iaf_alpha = MultiDynamics(
name='IafAlpha_sans_synapses',
sub_components={
'cell':
iaf,
'syn':
MultiDynamics(name="IafAlaphSyn",
sub_components={
'psr': alpha_psr,
'pls': static
},
port_connections=[('pls', 'fixed_weight', 'psr',
'q')],
port_exposures=[('psr', 'i_synaptic'),
('psr', 'spike')])
},
port_connections=[('syn', 'i_synaptic__psr', 'cell', 'i_synaptic')
],
port_exposures=[('syn', 'spike__psr', 'spike')])
iaf_alpha_with_syn = MultiDynamicsWithSynapses(
'IafAlpha',
iaf_alpha,
connection_parameter_sets=[
ConnectionParameterSet(
'spike', [iaf_alpha.parameter('weight__pls__syn')])
])
initial_states = {
'a__psr__syn': 0.0 * pq.nA,
'b__psr__syn': 0.0 * pq.nA
}
initial_regime = 'subthreshold___sole_____sole'
liaf_properties = ninemlcatalog.load(
'neuron/LeakyIntegrateAndFire/',
'PyNNLeakyIntegrateAndFireProperties')
alpha_properties = ninemlcatalog.load('postsynapticresponse/Alpha',
'SamplePyNNAlphaProperties')
nest_tranlsations = {
'tau__psr__syn': ('tau_syn_ex', 1),
'a__psr__syn': (None, 1),
'b__psr__syn': (None, 1),
'spike': ('spike', 1000.0)
}
neuron_tranlsations = {
'tau__psr__syn': ('psr.tau', 1),
'q__psr__syn': ('psr.q', 1),
'spike': ('spike', 1),
'a__psr__syn': (None, 1),
'b__psr__syn': (None, 1)
}
initial_states.update(
(k + '__cell', v) for k, v in self.liaf_initial_states.items())
properties = DynamicsProperties(
name='IafAlphaProperties',
definition=iaf_alpha,
properties=dict(
(p.name + '__' + suffix, p.quantity) for p, suffix in chain(
list(zip(liaf_properties.properties, repeat('cell'))),
list(zip(alpha_properties.properties, repeat('psr__syn'))),
[(Property('weight', 10 * un.nA), 'pls__syn')])))
properties_with_syn = DynamicsWithSynapsesProperties(
'IafAlpha_props_with_syn',
properties, # @IgnorePep8
connection_property_sets=[
ConnectionPropertySet(
'spike', [properties.property('weight__pls__syn')])
])
nest_tranlsations.update(
(k + '__cell', v) for k, v in self.liaf_nest_translations.items())
neuron_tranlsations.update(
(k + '__cell', v)
for k, v in self.liaf_neuron_translations.items())
comparer = Comparer(
nineml_model=iaf_alpha_with_syn,
state_variable='v__cell',
dt=dt,
simulators=simulators,
properties=properties_with_syn,
initial_states=initial_states,
initial_regime=initial_regime,
neuron_ref='ResetRefrac',
nest_ref='iaf_psc_alpha',
input_train=input_freq(
'spike',
450 * pq.Hz,
duration * pq.ms,
weight=[Property('weight__pls__syn', 10 * un.nA)],
offset=duration / 2.0),
nest_translations=nest_tranlsations,
neuron_translations=neuron_tranlsations,
extra_mechanisms=['pas'],
extra_point_process='AlphaISyn',
neuron_build_args={'build_mode': build_mode},
nest_build_args={'build_mode': build_mode},
min_delay=min_delay,
# auxiliary_states=['end_refractory__cell'],
device_delay=device_delay)
comparer.simulate(duration * un.ms,
nest_rng_seed=NEST_RNG_SEED,
neuron_rng_seed=NEURON_RNG_SEED)
comparisons = comparer.compare()
if print_comparisons:
for (name1, name2), diff in comparisons.items():
print('{} v {}: {}'.format(name1, name2, diff))
if plot:
comparer.plot()
if 'nest' in simulators and 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-nest', '9ML-neuron')], 0.015 * pq.mV,
"LIaF with Alpha syn NEST 9ML simulation did not match NEURON "
"9ML simulation within {} ({})".format(
0.015 * pq.mV, comparisons[('9ML-nest', '9ML-neuron')]))
if 'nest' in simulators:
self.assertLess(
comparisons[('9ML-nest', 'Ref-nest')], 0.04 * pq.mV,
"LIaF with Alpha syn NEST 9ML simulation did not match "
"reference built-in within {} ({})".format(
0.04 * pq.mV, comparisons[('9ML-nest', 'Ref-nest')]))
if 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-neuron', 'Ref-neuron')], 0.03 * pq.mV,
"LIaF with Alpha syn NEURON 9ML simulation did not match "
"reference PyNN within {} ({})".format(
0.03 * pq.mV, comparisons[('9ML-neuron', 'Ref-neuron')]))
def test_hh(self,
plot=PLOT_DEFAULT,
print_comparisons=False,
simulators=SIMULATORS_TO_TEST,
dt=0.001,
duration=100.0,
build_mode=BUILD_MODE_DEFAULT,
**kwargs): # @UnusedVariable
# Perform comparison in subprocess
comparer = Comparer(
nineml_model=ninemlcatalog.load('neuron/HodgkinHuxley',
'PyNNHodgkinHuxley'),
state_variable='v',
dt=dt,
simulators=simulators,
initial_states={
'v': -65.0 * pq.mV,
'm': 0.0,
'h': 1.0,
'n': 0.0
},
properties=ninemlcatalog.load('neuron/HodgkinHuxley',
'PyNNHodgkinHuxleyProperties'),
neuron_ref='hh_traub',
nest_ref='hh_cond_exp_traub',
input_signal=input_step('iExt', 0.5, 50, 100, dt, 10),
nest_translations={
'v': ('V_m', 1),
'm': ('Act_m', 1),
'h': ('Act_h', 1),
'n': ('Inact_n', 1),
'eNa': ('E_Na', 1),
'eK': ('E_K', 1),
'C': ('C_m', 1),
'gLeak': ('g_L', 1),
'eLeak': ('E_L', 1),
'gbarNa': ('g_Na', 1),
'gbarK': ('g_K', 1),
'v_rest': ('V_T', 1),
'v_threshold': (None, 1),
'm_alpha_A': (None, 1),
'm_alpha_V0': (None, 1),
'm_alpha_K': (None, 1),
'm_beta_A': (None, 1),
'm_beta_V0': (None, 1),
'm_beta_K': (None, 1),
'h_alpha_A': (None, 1),
'h_alpha_V0': (None, 1),
'h_alpha_K': (None, 1),
'h_beta_A': (None, 1),
'h_beta_V0': (None, 1),
'h_beta_K': (None, 1),
'n_alpha_A': (None, 1),
'n_alpha_V0': (None, 1),
'n_alpha_K': (None, 1),
'n_beta_A': (None, 1),
'n_beta_V0': (None, 1),
'n_beta_K': (None, 1)
},
neuron_translations={
'eNa': ('ena', 1),
'eK': ('ek', 1),
'C': ('cm', 1),
'gLeak': ('gl', 1),
'eLeak': ('el', 1),
'gbarNa': ('gnabar', 1),
'gbarK': ('gkbar', 1),
'v_rest': ('vT', 1),
'v_threshold': (None, 1),
'm_alpha_A': (None, 1),
'm_alpha_V0': (None, 1),
'm_alpha_K': (None, 1),
'm_beta_A': (None, 1),
'm_beta_V0': (None, 1),
'm_beta_K': (None, 1),
'h_alpha_A': (None, 1),
'h_alpha_V0': (None, 1),
'h_alpha_K': (None, 1),
'h_beta_A': (None, 1),
'h_beta_V0': (None, 1),
'h_beta_K': (None, 1),
'n_alpha_A': (None, 1),
'n_alpha_V0': (None, 1),
'n_alpha_K': (None, 1),
'n_beta_A': (None, 1),
'n_beta_V0': (None, 1),
'n_beta_K': (None, 1)
},
# auxiliary_states=['m', 'h', 'n'],
neuron_build_args={'build_mode': build_mode},
nest_build_args={'build_mode': build_mode})
comparer.simulate(duration * un.ms,
nest_rng_seed=NEST_RNG_SEED,
neuron_rng_seed=NEURON_RNG_SEED)
comparisons = comparer.compare()
if print_comparisons:
for (name1, name2), diff in comparisons.items():
print('{} v {}: {}'.format(name1, name2, diff))
if plot:
comparer.plot()
# FIXME: Need to work out what is happening with the reference NEURON
if 'nest' in simulators and 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-nest', '9ML-neuron')], 0.5 * pq.mV,
"HH 9ML NEURON and NEST simulation did not match each other "
"within {} ({})".format(
0.5 * pq.mV, comparisons[('9ML-nest', '9ML-neuron')]))
if 'neuron' in simulators:
self.assertLess(
comparisons[('9ML-neuron', 'Ref-neuron')], 0.55 * pq.mV,
"HH 9ML NEURON simulation did not match reference built-in "
"within {} ({})".format(
0.55 * pq.mV, comparisons[('9ML-neuron', 'Ref-neuron')]))
if 'nest' in simulators:
self.assertLess(
comparisons[('9ML-nest', 'Ref-nest')], 0.0015 * pq.mV,
"HH 9ML NEST simulation did not match reference built-in "
"within {} ({})".format(0.0015 * pq.mV,
comparisons[('9ML-nest', 'Ref-nest')]))
