def test_progressreporting():
'''
Tests whether calling for progress reporting works -- the actual output is
not checked, only that something is printed to the correct output.
'''
real_stdout = sys.stdout
real_stderr = sys.stderr
G = NeuronGroup(1, model=LazyStateUpdater())
net = Network(G)
# Tests various ways to get a (textual) progress report
string_output = StringIO()
sys.stdout = string_output
net.run(defaultclock.dt, report='text')
assert(len(string_output.getvalue()) > 0)
net.run(defaultclock.dt, report='print')
string_output = StringIO()
sys.stdout = string_output
net.run(defaultclock.dt, report='stdout')
assert(len(string_output.getvalue()) > 0)
string_output = StringIO()
sys.stdout = string_output
string_err = StringIO()
sys.stderr = string_err
net.run(defaultclock.dt, report='stderr')
assert(len(string_output.getvalue()) == 0 and len(string_err.getvalue()) > 0)
net.run(defaultclock.dt, report=string_output)
assert(len(string_output.getvalue()) > 0)
net.run(defaultclock.dt, report='text', report_period=5*second)
#explicitely construct a ProgressReporter
string_output = StringIO()
sys.stdout = string_output
reporter = ProgressReporter('text')
reporter.start()
net.run(defaultclock.dt, report=reporter)
assert(len(string_output.getvalue()) > 0)
string_output = StringIO()
sys.stdout = string_output
string_err = StringIO()
sys.stderr = string_err
reporter = ProgressReporter('stderr')
net.run(defaultclock.dt, report=reporter)
assert(len(string_output.getvalue()) == 0 and len(string_err.getvalue()) > 0)
# use MagicNetwork implicitly
string_output = StringIO()
sys.stdout = string_output
run(defaultclock.dt, report='text', report_period=5*second)
assert(len(string_output.getvalue()) > 0)
sys.stdout = real_stdout
sys.stderr = real_stderr
def test_progressreporting():
'''
Tests whether calling for progress reporting works -- the actual output is
not checked, only that something is printed to the correct output.
'''
real_stdout = sys.stdout
real_stderr = sys.stderr
G = NeuronGroup(1, model=LazyStateUpdater())
net = Network(G)
# Tests various ways to get a (textual) progress report
string_output = StringIO()
sys.stdout = string_output
net.run(defaultclock.dt, report='text')
assert (len(string_output.getvalue()) > 0)
net.run(defaultclock.dt, report='print')
string_output = StringIO()
sys.stdout = string_output
net.run(defaultclock.dt, report='stdout')
assert (len(string_output.getvalue()) > 0)
string_output = StringIO()
sys.stdout = string_output
string_err = StringIO()
sys.stderr = string_err
net.run(defaultclock.dt, report='stderr')
assert (len(string_output.getvalue()) == 0
and len(string_err.getvalue()) > 0)
net.run(defaultclock.dt, report=string_output)
assert (len(string_output.getvalue()) > 0)
net.run(defaultclock.dt, report='text', report_period=5 * second)
#explicitely construct a ProgressReporter
string_output = StringIO()
sys.stdout = string_output
reporter = ProgressReporter('text')
reporter.start()
net.run(defaultclock.dt, report=reporter)
assert (len(string_output.getvalue()) > 0)
string_output = StringIO()
sys.stdout = string_output
string_err = StringIO()
sys.stderr = string_err
reporter = ProgressReporter('stderr')
net.run(defaultclock.dt, report=reporter)
assert (len(string_output.getvalue()) == 0
and len(string_err.getvalue()) > 0)
# use MagicNetwork implicitly
string_output = StringIO()
sys.stdout = string_output
run(defaultclock.dt, report='text', report_period=5 * second)
assert (len(string_output.getvalue()) > 0)
sys.stdout = real_stdout
sys.stderr = real_stderr
synapses.connect(G_pre, G_post, rand(len(G_pre), len(G_post)) * gmax)
stdp = ExponentialSTDP(synapses, tau_pre, tau_post, dA_pre, dA_post, wmax=gmax)
M_pre = SpikeMonitor(G_pre)
M_post = SpikeMonitor(G_post)
MV_post = StateMonitor(G_post, 'V', record=True)
G_post.V = Vr
net = MagicNetwork()
weights_before = array(synapses.W).copy()
t_start = time.time()
reporter = ProgressReporter('stderr')
for i in range(repeats):
reporter.equal_subtask(i, repeats)
reinit_default_clock()
# Reinitialise these by hand because we don't want to reinitialise the
# spike and state monitors
PG_start.reinit()
PG_end.reinit()
PG_all.reinit()
G_pre.reinit()
G_post.reinit()
patgroup.reinit()
net.run(total_duration, report=reporter)
t_end = time.time()
weights_after = array(synapses.W).copy()
synapses.connect(G_pre, G_post, rand(len(G_pre), len(G_post))*gmax)
stdp = ExponentialSTDP(synapses, tau_pre, tau_post, dA_pre, dA_post, wmax=gmax)
M_pre = SpikeMonitor(G_pre)
M_post = SpikeMonitor(G_post)
MV_post = StateMonitor(G_post, 'V', record=True)
G_post.V = Vr
net = MagicNetwork()
weights_before = array(synapses.W).copy()
t_start = time.time()
reporter = ProgressReporter('stderr')
for i in range(repeats):
reporter.equal_subtask(i, repeats)
reinit_default_clock()
# Reinitialise these by hand because we don't want to reinitialise the
# spike and state monitors
PG_start.reinit()
PG_end.reinit()
PG_all.reinit()
G_pre.reinit()
G_post.reinit()
patgroup.reinit()
net.run(total_duration, report=reporter)
t_end = time.time()
weights_after = array(synapses.W).copy()
