{5} Assigned, Active Tickets by Owner (Full Description) (15 matches)

Hi Andrew,

One final problem which causes a lot of test failures that I discovered can be exemplified with the following test report:

======================================================================
ERROR: test_reset
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/srv/virtualenv/mle/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
    self.test(*self.arg)
  File "/home/zaytsev/src/nest/pyNN-trunk/test/system/scenarios.py", line 352, in test_reset
    sim.run(10.0)
  File "/srv/virtualenv/mle/lib/python2.7/site-packages/pyNN/nest/__init__.py", line 152, in run
    simulator.run(simtime)
  File "/srv/virtualenv/mle/lib/python2.7/site-packages/pyNN/nest/simulator.py", line 91, in run
    device.connect_to_cells()
  File "/srv/virtualenv/mle/lib/python2.7/site-packages/pyNN/nest/recording.py", line 73, in connect_to_cells
    nest.DivergentConnect(self.device, ids, model='static_synapse')
  File "/home/zaytsev/src/nest/nest-10kproject-work/build/results/lib/python2.7/site-packages/nest/hl_api.py", line 857, in DivergentConnect
    sr('/%s DivergentConnect' % model)
  File "/home/zaytsev/src/nest/nest-10kproject-work/build/results/lib/python2.7/site-packages/nest/__init__.py", line 119, in catching_sr
    raise hl_api.NESTError(errorname + ' in ' + commandname + message)
NESTError: UnknownNode in DivergentConnect_i_ia_a_a_l: Node with id 5 doesn't exist.
-------------------- >> begin captured logging << --------------------
PyNN: DEBUG: rng_seeds = [37454]
PyNN: DEBUG: In Population 'population10', initialising v to -65.0
PyNN: DEBUG: population10.record('v')
PyNN: DEBUG: Adding recorder for v to population10
PyNN: DEBUG: Created multimeter with parameters {'to_file': True, 'withtime': True, 'interval': 1.0, 'to_memory': False, 'withgid': True}
PyNN: DEBUG: Recorder.record(<1 cells>)
PyNN: DEBUG: Recorder.recorded contains 1 ids
--------------------- >> end captured logging << ---------------------

This test is a part of scenarios applied to the NEST backed. However, what happens for one reason or another is that in between the test runs the recording_devices in simulator.py accumulate, and upon simulation run a connection is attempted to the neurons that are no longer part of the current network.

I'm not sure why exactly this is happening, because I have never used PyNN myself and therefore I have no idea of how it is designed. It could be that recording devices are not disposed properly when sim.end() is called, or maybe it is just not done at all in some tests...

Either way, attached patch fixes the issue and the tests now pass, because the module is entirely reloaded between test invocations, and therefore the "device leak" is avoided.

Unfortunately, I don't know how to fix the root cause, and if it is supposed to be fixed at all or not, so my patch is not very constructive in this regard.

Z.

With pyNN.neuron, when the TsodyksMarkramMechanism?(TMM) is used targeting exponential synapses, the synaptic conductance becomes "nan" in specific setups: If the TMM recovery time constant "tau_rec" is equal to the decay time constant of the target synapse ( "tau_syn_E" or "tau_syn_I"), gsyn becomes "nan" and it seems as if there was no synaptic connection at all in the network.

Using the same values for both time constants is probably not very biological, but may be useful when implementing saturating synapses. The facilitation time constant "tau_facil" has no effect on that behavior.

See an example below, reproducing this errors. This is the tsodyksmarkram.py example script, only the time constants were adapted accordingly.

import numpy
from pyNN.utility import get_script_args

simulator_name = get_script_args(1)[0]
exec("import pyNN.%s as sim" % simulator_name)

sim.setup(debug=True, quit_on_end=False)

spike_source = sim.Population(1, sim.SpikeSourceArray,
                              {'spike_times': numpy.arange(10, 100, 10)})

connector = sim.AllToAllConnector(weights=0.01, delays=0.5)

synapse_dynamics = {
    'static': None,
    'depressing': sim.SynapseDynamics(
        fast=sim.TsodyksMarkramMechanism(U=0.5, tau_rec=10.0, tau_facil=0.0)),
    'facilitating': sim.SynapseDynamics(
        fast=sim.TsodyksMarkramMechanism(U=0.04, tau_rec=10.0, tau_facil=1000.0)),
}

populations = {}
projections = {}
for label in 'static', 'depressing', 'facilitating':
    populations[label] = sim.Population(1, sim.IF_cond_exp, {'e_rev_I': -75, 'tau_syn_I':10.}, label=label)
    populations[label].record_v()
    if populations[label].can_record('gsyn'):
        populations[label].record_gsyn()
    projections[label] = sim.Projection(spike_source, populations[label], connector,
                                        target='inhibitory',
                                        synapse_dynamics=synapse_dynamics[label])

spike_source.record()

sim.run(200.0)

for label,p in populations.items():
    p.print_v("Results/tsodyksmarkram_%s_%s.v" % (label, simulator_name))
    if populations[label].can_record('gsyn'):
        p.print_gsyn("Results/tsodyksmarkram_%s_%s.gsyn" % (label, simulator_name))

print spike_source.getSpikes()

sim.end()

Hello

Thanks for providing such a wonderful platform.

I have a put together a little python code to simulate a network of 1000 neurons using pyNN.neuron

I get this error if I place an end() statement. This statement is placed after all print_v(..) and printSpikes(...) statements. If the end() statement is not placed, no error occurs and everything works fine including printing of spikes to files.

Traceback (most recent call last):
  File "net.py", line 229, in <module>
    end()
  File "/usr/lib/pymodules/python2.7/pyNN/neuron/__init__.py", line 73, in end
    recorder.write(gather=True, compatible_output=compatible_output)
  File "/usr/lib/pymodules/python2.7/pyNN/recording/__init__.py", line 146, in write
    filename = file.name
AttributeError: 'NoneType' object has no attribute 'name'

I have the following lines in my code.

Line 208:    if voltagesRequired:
Line 209:      record_v(p1,True)

Line 210:    if spikesRequired:
Line 211:      record(p1,True)
----------------------------------------
----------------------------------------
Line 227:    if voltagesRequired:
Line 228:      print 'Writing Voltage values to Results/noCells'+str(noCells)+'for'+str(tStop)+'voltages.data'
Line 229:      p1.print_v('Results/noCells'+str(noCells)+'for'+str(tStop)+'voltages.data',compatible_output=False)

Line 230:    if spikesRequired:
Line 231:      print 'Writing Spike Times to Results/noCells'+str(noCells)+'for'+str(tStop)+'spikes.data'
Line 232:      p1.printSpikes('Results/noCells'+str(noCells)+'for'+str(tStop)+'spikes.data',compatible_output=False)
Line 233:    end()

Thanks in Advance.

Cheers Ajay.

Following on from ticket:111, since reset() does not change the list of things to record, but it may be desirable to record different things on different runs, we also need a mechanism for resetting the list of things to be recorded, e.g. record(None).

Cell parameters can be accessed using the ID class, e.g. cell1.tau_m. It might also be nice to access variables, such as the membrane potential, as cell1.v, etc.

Sometimes code that follows a long, tedious build or run has incorrect argument types, etc It would be nice to be able to catch these bugs before running the script on the real simulator

My suggested way to do this would be to run with import pyNN.dummy

Some simulators allow writing variables other than spike times and membrane potential to file. To support these, we should have a single function and a single Population method for writing variables to file.

Also, python tends to use write(), rather than print(), for this kind of thing.

This should be done in a separate branch until we've made a release with the current API.