/usr/lib/python2.7/dist-packages/pyNN/multisim.py is in python-pynn 0.7.4-1.1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 | """
A small framework to make it easier to run the same model on multiple
simulators.
:copyright: Copyright 2006-2011 by the PyNN team, see AUTHORS.
:license: CeCILL, see LICENSE for details.
"""
from multiprocessing import Process, Queue
from pyNN import common, recording
def run_simulation(network_model, sim, parameters, input_queue, output_queue):
"""
Build the model defined in the class `network_model`, with parameters
`parameters`, and then consume tasks from `input_queue` until receiving the
command 'STOP'.
"""
print "Running simulation with %s" % sim.__name__
common.simulator = sim.simulator
recording.simulator = sim.simulator
network = network_model(sim, parameters)
print "Network constructed with %s." % sim.__name__
for obj_name, attr, args, kwargs in iter(input_queue.get, 'STOP'):
print "%s processing command %s.%s(%s, %s)" % (sim.__name__, obj_name, attr, args, kwargs)
obj = eval(obj_name)
result = getattr(obj, attr)(*args, **kwargs)
output_queue.put(result)
print "Simulation with %s complete" % sim.__name__
#sim.end()
class MultiSim(object):
"""
Interface that runs a network model on different simulators, with each
simulation in a separate process.
"""
def __init__(self, sim_list, network_model, parameters):
"""
Build the model defined in the class `network_model`, with parameters
`parameters`, for each of the simulator modules specified in `sim_list`.
The `network_model` constructor takes arguments `sim` and `parameters`.
"""
self.processes = {}
self.task_queues = {}
self.result_queues = {}
for sim in sim_list:
task_queue = Queue()
result_queue = Queue()
p = Process(target=run_simulation,
args=(network_model, sim, parameters, task_queue, result_queue))
p.start()
self.processes[sim.__name__] = p
self.task_queues[sim.__name__] = task_queue
self.result_queues[sim.__name__] = result_queue
def __iter__(self):
return self.processes.itervalues()
def __getattr__(self, name):
"""
Assumes `name` is a method of the `network_model` model.
Return a function that runs `net.name()` for all the simulators.
"""
def iterate_over_nets(*args, **kwargs):
retvals = {}
for sim_name in self.processes:
self.task_queues[sim_name].put(('network', name, args, kwargs))
for sim_name in self.processes:
retvals[sim_name] = self.result_queues[sim_name].get()
return retvals
return iterate_over_nets
def run(self, simtime, steps=1): #, *callbacks):
"""
Run the model for a time `simtime` in all simulators.
The run may be broken into a number of steps (each of equal duration).
#Any functions in `callbacks` will be called after each step.
"""
dt = float(simtime)/steps
for i in range(steps):
for sim_name in self.processes:
self.task_queues[sim_name].put(('sim', 'run', [dt], {}))
for sim_name in self.processes:
t = self.result_queues[sim_name].get()
def end(self):
for sim_name in self.processes:
self.task_queues[sim_name].put('STOP')
self.processes[sim_name].join()
|