def test_store_restore(): source = NeuronGroup(10, '''dv/dt = rates : 1 rates : Hz''', threshold='v>1', reset='v=0') source.rates = 'i*100*Hz' target = NeuronGroup(10, 'v:1') synapses = Synapses(source, target, model='w:1', pre='v+=w', connect='i==j') synapses.w = 'i*1.0' synapses.delay = 'i*ms' state_mon = StateMonitor(target, 'v', record=True) spike_mon = SpikeMonitor(source) net = Network(source, target, synapses, state_mon, spike_mon) net.store() # default time slot net.run(10*ms) net.store('second') net.run(10*ms) v_values = state_mon.v[:, :] spike_indices, spike_times = spike_mon.it_ net.restore() # Go back to beginning assert defaultclock.t == 0*ms assert net.t == 0*ms net.run(20*ms) assert_equal(v_values, state_mon.v[:, :]) assert_equal(spike_indices, spike_mon.i[:]) assert_equal(spike_times, spike_mon.t_[:]) # Go back to middle net.restore('second') assert defaultclock.t == 10*ms assert net.t == 10*ms net.run(10*ms) assert_equal(v_values, state_mon.v[:, :]) assert_equal(spike_indices, spike_mon.i[:]) assert_equal(spike_times, spike_mon.t_[:])
def test_dt_restore(): defaultclock.dt = 0.5*ms G = NeuronGroup(1, 'dv/dt = -v/(10*ms) : 1') mon = StateMonitor(G, 'v', record=True) net = Network(G, mon) net.store() net.run(1*ms) assert_equal(mon.t[:], [0, 0.5]*ms) defaultclock.dt = 1*ms net.run(2*ms) assert_equal(mon.t[:], [0, 0.5, 1, 2]*ms) net.restore() assert_equal(mon.t[:], []) net.run(1*ms) assert defaultclock.dt == 0.5*ms assert_equal(mon.t[:], [0, 0.5]*ms)
def test_store_restore_to_file_differing_nets(): # Check that the store/restore mechanism is not used with differing # networks filename = tempfile.mktemp(suffix='state', prefix='brian_test') source = SpikeGeneratorGroup(5, [0, 1, 2, 3, 4], [0, 1, 2, 3, 4]*ms, name='source_1') mon = SpikeMonitor(source, name='monitor') net = Network(source, mon) net.store(filename=filename) source_2 = SpikeGeneratorGroup(5, [0, 1, 2, 3, 4], [0, 1, 2, 3, 4]*ms, name='source_2') mon = SpikeMonitor(source_2, name='monitor') net = Network(source_2, mon) assert_raises(KeyError, lambda: net.restore(filename=filename)) net = Network(source) # Without the monitor assert_raises(KeyError, lambda: net.restore(filename=filename))
def test_store_restore_to_file_differing_nets(): # Check that the store/restore mechanism is not used with differing # networks filename = tempfile.mktemp(suffix='state', prefix='brian_test') source = SpikeGeneratorGroup(5, [0, 1, 2, 3, 4], [0, 1, 2, 3, 4] * ms, name='source_1') mon = SpikeMonitor(source, name='monitor') net = Network(source, mon) net.store(filename=filename) source_2 = SpikeGeneratorGroup(5, [0, 1, 2, 3, 4], [0, 1, 2, 3, 4] * ms, name='source_2') mon = SpikeMonitor(source_2, name='monitor') net = Network(source_2, mon) assert_raises(KeyError, lambda: net.restore(filename=filename)) net = Network(source) # Without the monitor assert_raises(KeyError, lambda: net.restore(filename=filename))
def test_store_restore_to_file(): filename = tempfile.mktemp(suffix='state', prefix='brian_test') source = NeuronGroup(10, '''dv/dt = rates : 1 rates : Hz''', threshold='v>1', reset='v=0') source.rates = 'i*100*Hz' target = NeuronGroup(10, 'v:1') synapses = Synapses(source, target, model='w:1', on_pre='v+=w') synapses.connect(j='i') synapses.w = 'i*1.0' synapses.delay = 'i*ms' state_mon = StateMonitor(target, 'v', record=True) spike_mon = SpikeMonitor(source) net = Network(source, target, synapses, state_mon, spike_mon) net.store(filename=filename) # default time slot net.run(10 * ms) net.store('second', filename=filename) net.run(10 * ms) v_values = state_mon.v[:, :] spike_indices, spike_times = spike_mon.it_ net.restore(filename=filename) # Go back to beginning assert defaultclock.t == 0 * ms assert net.t == 0 * ms net.run(20 * ms) assert_equal(v_values, state_mon.v[:, :]) assert_equal(spike_indices, spike_mon.i[:]) assert_equal(spike_times, spike_mon.t_[:]) # Go back to middle net.restore('second', filename=filename) assert defaultclock.t == 10 * ms assert net.t == 10 * ms net.run(10 * ms) assert_equal(v_values, state_mon.v[:, :]) assert_equal(spike_indices, spike_mon.i[:]) assert_equal(spike_times, spike_mon.t_[:]) try: os.remove(filename) except OSError: pass
def test_store_restore_to_file(): filename = tempfile.mktemp(suffix='state', prefix='brian_test') source = NeuronGroup(10, '''dv/dt = rates : 1 rates : Hz''', threshold='v>1', reset='v=0') source.rates = 'i*100*Hz' target = NeuronGroup(10, 'v:1') synapses = Synapses(source, target, model='w:1', on_pre='v+=w') synapses.connect(j='i') synapses.w = 'i*1.0' synapses.delay = 'i*ms' state_mon = StateMonitor(target, 'v', record=True) spike_mon = SpikeMonitor(source) net = Network(source, target, synapses, state_mon, spike_mon) net.store(filename=filename) # default time slot net.run(10*ms) net.store('second', filename=filename) net.run(10*ms) v_values = state_mon.v[:, :] spike_indices, spike_times = spike_mon.it_ net.restore(filename=filename) # Go back to beginning assert defaultclock.t == 0*ms assert net.t == 0*ms net.run(20*ms) assert_equal(v_values, state_mon.v[:, :]) assert_equal(spike_indices, spike_mon.i[:]) assert_equal(spike_times, spike_mon.t_[:]) # Go back to middle net.restore('second', filename=filename) assert defaultclock.t == 10*ms assert net.t == 10*ms net.run(10*ms) assert_equal(v_values, state_mon.v[:, :]) assert_equal(spike_indices, spike_mon.i[:]) assert_equal(spike_times, spike_mon.t_[:]) try: os.remove(filename) except OSError: pass