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Christian-BChristian-B
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test script combined and split
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‎examples/extra_models_examples/IF_cond_exp_stoc.py‎

Lines changed: 104 additions & 85 deletions
Original file line numberDiff line numberDiff line change
@@ -33,88 +33,107 @@
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from pyNN.utility.plotting import Figure, Panel
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import matplotlib.pyplot as plt
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sim.setup(timestep=1.0, min_delay=1.0)
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stoc_cell = sim.Population(1, sim.extra_models.IFCondExpStoc(**{
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'i_offset': 0.1,
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'tau_refrac': 3.0,
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'v_thresh': -51.0,
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'v_reset': -70.0,
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'tau_syn_E': 5.0,
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'tau_syn_I': 5.0}))
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exp_cell = sim.Population(1, sim.IF_cond_exp(**{
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'i_offset': 0.1,
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'tau_refrac': 3.0,
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'v_thresh': -51.0,
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'v_reset': -70.0,
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'tau_syn_E': 5.0,
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'tau_syn_I': 5.0}))
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spike_sourceE = sim.Population(1, sim.SpikeSourceArray(**{
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'spike_times': [float(i) for i in range(5, 105, 10)]}))
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spike_sourceI = sim.Population(1, sim.SpikeSourceArray(**{
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'spike_times': [float(i) for i in range(155, 255, 10)]}))
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sim.Projection(spike_sourceE, exp_cell,
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sim.OneToOneConnector(),
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synapse_type=sim.StaticSynapse(weight=0.15, delay=2.0),
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receptor_type='excitatory')
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sim.Projection(spike_sourceI, exp_cell,
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sim.OneToOneConnector(),
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synapse_type=sim.StaticSynapse(weight=-0.15, delay=4.0),
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receptor_type='inhibitory')
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sim.Projection(spike_sourceE, stoc_cell,
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sim.OneToOneConnector(),
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synapse_type=sim.StaticSynapse(weight=0.15, delay=2.0),
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receptor_type='excitatory')
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sim.Projection(spike_sourceI, stoc_cell,
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sim.OneToOneConnector(),
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synapse_type=sim.StaticSynapse(weight=-0.15, delay=4.0),
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receptor_type='inhibitory')
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stoc_cell.record('all')
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exp_cell.record('all')
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runtime = 200.0
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sim.run(runtime)
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stoc_data = stoc_cell.get_data()
85-
exp_data = exp_cell.get_data()
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# Plot
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Figure(
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# raster plot of the presynaptic neuron spike times
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Panel(stoc_data.segments[0].spiketrains,
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yticks=True, markersize=0.2, xlim=(0, runtime)),
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Panel(exp_data.segments[0].spiketrains,
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yticks=True, markersize=0.2, xlim=(0, runtime)),
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# membrane potential of the postsynaptic neuron
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Panel(stoc_data.segments[0].filter(name='v')[0],
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ylabel="Membrane potential (mV)",
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data_labels=[stoc_cell.label], yticks=True, xlim=(0, runtime)),
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Panel(stoc_data.segments[0].filter(name='gsyn_exc')[0],
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ylabel="gsyn excitatory (mV)",
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data_labels=[stoc_cell.label], yticks=True, xlim=(0, runtime)),
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Panel(stoc_data.segments[0].filter(name='gsyn_inh')[0],
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ylabel="gsyn inhibitory (mV)",
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data_labels=[stoc_cell.label], yticks=True, xlim=(0, runtime)),
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# membrane potential of the postsynaptic neuron
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Panel(exp_data.segments[0].filter(name='v')[0],
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ylabel="Membrane potential (mV)",
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data_labels=[exp_cell.label], yticks=True, xlim=(0, runtime)),
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Panel(exp_data.segments[0].filter(name='gsyn_exc')[0],
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ylabel="gsyn excitatory (mV)",
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data_labels=[exp_cell.label], yticks=True, xlim=(0, runtime)),
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Panel(exp_data.segments[0].filter(name='gsyn_inh')[0],
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ylabel="gsyn inhibitory (mV)",
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data_labels=[exp_cell.label], yticks=True, xlim=(0, runtime)),
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title="IF_cond_exp_stoc example",
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annotations=f"Simulated with {sim.name()}"
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)
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plt.show()
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sim.end()
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pylab.show()
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37+
def run_script(*, split: bool = False) -> None:
38+
"""
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Runs the example script
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:param split: If True will split the Populations that receive data
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into synapse and neuron cores.
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This requires more cores but allows more spikes to be received.
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"""
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sim.setup(timestep=1.0, min_delay=1.0)
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if split:
48+
sim.extra_models.IFCondExpStoc.set_model_n_synapse_cores(1)
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sim.IF_cond_exp.set_model_n_synapse_cores(1)
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51+
stoc_cell = sim.Population(1, sim.extra_models.IFCondExpStoc(**{
52+
'i_offset': 0.1,
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'tau_refrac': 3.0,
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'v_thresh': -51.0,
55+
'v_reset': -70.0,
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'tau_syn_E': 5.0,
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'tau_syn_I': 5.0}))
58+
59+
exp_cell = sim.Population(1, sim.IF_cond_exp(**{
60+
'i_offset': 0.1,
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'tau_refrac': 3.0,
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'v_thresh': -51.0,
63+
'v_reset': -70.0,
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'tau_syn_E': 5.0,
65+
'tau_syn_I': 5.0}))
66+
67+
68+
spike_sourceE = sim.Population(1, sim.SpikeSourceArray(**{
69+
'spike_times': [float(i) for i in range(5, 105, 10)]}))
70+
spike_sourceI = sim.Population(1, sim.SpikeSourceArray(**{
71+
'spike_times': [float(i) for i in range(155, 255, 10)]}))
72+
73+
sim.Projection(spike_sourceE, exp_cell,
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sim.OneToOneConnector(),
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synapse_type=sim.StaticSynapse(weight=0.15, delay=2.0),
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receptor_type='excitatory')
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sim.Projection(spike_sourceI, exp_cell,
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sim.OneToOneConnector(),
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synapse_type=sim.StaticSynapse(weight=-0.15, delay=4.0),
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receptor_type='inhibitory')
81+
sim.Projection(spike_sourceE, stoc_cell,
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sim.OneToOneConnector(),
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synapse_type=sim.StaticSynapse(weight=0.15, delay=2.0),
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receptor_type='excitatory')
85+
sim.Projection(spike_sourceI, stoc_cell,
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sim.OneToOneConnector(),
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synapse_type=sim.StaticSynapse(weight=-0.15, delay=4.0),
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receptor_type='inhibitory')
89+
90+
stoc_cell.record('all')
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exp_cell.record('all')
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runtime = 200.0
94+
95+
sim.run(runtime)
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97+
stoc_data = stoc_cell.get_data()
98+
exp_data = exp_cell.get_data()
99+
100+
# Plot
101+
Figure(
102+
# raster plot of the presynaptic neuron spike times
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Panel(stoc_data.segments[0].spiketrains,
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yticks=True, markersize=0.2, xlim=(0, runtime)),
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Panel(exp_data.segments[0].spiketrains,
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yticks=True, markersize=0.2, xlim=(0, runtime)),
107+
# membrane potential of the postsynaptic neuron
108+
Panel(stoc_data.segments[0].filter(name='v')[0],
109+
ylabel="Membrane potential (mV)",
110+
data_labels=[stoc_cell.label], yticks=True, xlim=(0, runtime)),
111+
Panel(stoc_data.segments[0].filter(name='gsyn_exc')[0],
112+
ylabel="gsyn excitatory (mV)",
113+
data_labels=[stoc_cell.label], yticks=True, xlim=(0, runtime)),
114+
Panel(stoc_data.segments[0].filter(name='gsyn_inh')[0],
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ylabel="gsyn inhibitory (mV)",
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data_labels=[stoc_cell.label], yticks=True, xlim=(0, runtime)),
117+
# membrane potential of the postsynaptic neuron
118+
Panel(exp_data.segments[0].filter(name='v')[0],
119+
ylabel="Membrane potential (mV)",
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data_labels=[exp_cell.label], yticks=True, xlim=(0, runtime)),
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Panel(exp_data.segments[0].filter(name='gsyn_exc')[0],
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ylabel="gsyn excitatory (mV)",
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data_labels=[exp_cell.label], yticks=True, xlim=(0, runtime)),
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Panel(exp_data.segments[0].filter(name='gsyn_inh')[0],
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ylabel="gsyn inhibitory (mV)",
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data_labels=[exp_cell.label], yticks=True, xlim=(0, runtime)),
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title="IF_cond_exp_stoc example",
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annotations=f"Simulated with {sim.name()}"
129+
)
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plt.show()
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sim.end()
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pylab.show()
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# combined binaries_used ['IF_cond_exp_stoc.aplx','IF_cond_exp.aplx']
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# split binaries used(['IF_cond_exp_stoc_neuron.aplx','IF_cond_exp_neuron.aplx'])
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if __name__ == "__main__":
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run_script()

‎integration_tests/test_scripts.py‎

Lines changed: 13 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -183,8 +183,19 @@ def test_examples_extra_models_examples_stdp_example_izk_cond(self):
183183
def test_examples_extra_models_examples_IF_curr_exp_ca2_adaptive(self):
184184
self.check_script("examples/extra_models_examples/IF_curr_exp_ca2_adaptive.py")
185185

186-
def test_examples_extra_models_examples_IF_cond_exp_stoc(self):
187-
self.check_script("examples/extra_models_examples/IF_cond_exp_stoc.py")
186+
def test_examples_extra_models_examples_IF_cond_exp_stoc_combined(self):
187+
from examples.extra_models_examples.IF_cond_exp_stoc import run_script
188+
run_script(split=False)
189+
self.check_binaries_used([
190+
'IF_cond_exp_stoc.aplx',
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'IF_cond_exp.aplx'])
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def test_examples_extra_models_examples_IF_cond_exp_stoc_split(self):
194+
from examples.extra_models_examples.IF_cond_exp_stoc import run_script
195+
run_script(split=True)
196+
self.check_binaries_used([
197+
'IF_cond_exp_stoc_neuron.aplx',
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'IF_cond_exp_neuron.aplx'])
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189200
def test_balanced_random_balanced_random(self):
190201
self.check_script("balanced_random/balanced_random.py")

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