def test_NumpyBinaryFile():
nbf = files.NumpyBinaryFile("tmp.npz", "w")
data = [(0, 2.3), (1, 3.4), (2, 4.3)]
metadata = {'a': 1, 'b': 9.99}
nbf.write(data, metadata)
nbf.close()
nbf = files.NumpyBinaryFile("tmp.npz", "r")
assert_equal(nbf.get_metadata(), metadata)
assert_arrays_equal(nbf.read().flatten(), numpy.array(data).flatten())
nbf.close()
os.remove("tmp.npz")
def test(cases=[1]):
sp = Space(periodic_boundaries=((0, 1), (0, 1), None), axes='xy')
safe = False
callback = progress_bar.set_level
autapse = False
parallel_safe = True
render = True
to_file = True
for case in cases:
#w = RandomDistribution('uniform', (0,1))
w = "0.2 + d/0.2"
#w = 0.1
#w = lambda dist : 0.1 + numpy.random.rand(len(dist[0]))*sqrt(dist[0]**2 + dist[1]**2)
#delay = RandomDistribution('uniform', (0.1,5.))
#delay = "0.1 + d/0.2"
delay = 0.1
#delay = lambda distances : 0.1 + numpy.random.rand(len(distances))*distances
d_expression = "exp(-d**2/(2*0.1**2))"
#d_expression = "(d[0] < 0.05) & (d[1] < 0.05)"
#d_expression = "(d[0]/(0.05**2) + d[1]/(0.1**2)) < 100*numpy.random.rand()"
timer = Timer()
np = num_processes()
timer.start()
synapse = StaticSynapse(weight=w, delay=delay)
rng = NumpyRNG(23434, parallel_safe=parallel_safe)
if case is 1:
conn = DistanceDependentProbabilityConnector(
d_expression,
safe=safe,
callback=callback,
allow_self_connections=autapse,
rng=rng)
fig_name = "DistanceDependent_%s_np_%d.png" % (simulator_name, np)
elif case is 2:
conn = FixedProbabilityConnector(0.02,
safe=safe,
callback=callback,
allow_self_connections=autapse,
rng=rng)
fig_name = "FixedProbability_%s_np_%d.png" % (simulator_name, np)
elif case is 3:
conn = AllToAllConnector(delays=delay,
safe=safe,
callback=callback,
allow_self_connections=autapse)
fig_name = "AllToAll_%s_np_%d.png" % (simulator_name, np)
elif case is 4:
conn = FixedNumberPostConnector(50,
safe=safe,
callback=callback,
allow_self_connections=autapse,
rng=rng)
fig_name = "FixedNumberPost_%s_np_%d.png" % (simulator_name, np)
elif case is 5:
conn = FixedNumberPreConnector(50,
safe=safe,
callback=callback,
allow_self_connections=autapse,
rng=rng)
fig_name = "FixedNumberPre_%s_np_%d.png" % (simulator_name, np)
elif case is 6:
conn = OneToOneConnector(safe=safe, callback=callback)
fig_name = "OneToOne_%s_np_%d.png" % (simulator_name, np)
elif case is 7:
conn = FromFileConnector(files.NumpyBinaryFile(
'Results/connections.dat', mode='r'),
safe=safe,
callback=callback,
distributed=True)
fig_name = "FromFile_%s_np_%d.png" % (simulator_name, np)
elif case is 8:
conn = SmallWorldConnector(degree=0.1,
rewiring=0.,
safe=safe,
callback=callback,
allow_self_connections=autapse)
fig_name = "SmallWorld_%s_np_%d.png" % (simulator_name, np)
print "Generating data for %s" % fig_name
prj = Projection(x, x, conn, synapse, space=sp)
mytime = timer.diff()
print "Time to connect the cell population:", mytime, 's'
print "Nb synapses built", prj.size()
if to_file:
if not (os.path.isdir('Results')):
os.mkdir('Results')
print "Saving Connections...."
prj.save('all',
files.NumpyBinaryFile('Results/connections.dat',
mode='w'),
gather=True)
mytime = timer.diff()
print "Time to save the projection:", mytime, 's'
if render and to_file:
print "Saving Positions...."
x.save_positions('Results/positions.dat')
end()
if node_id == 0 and render and to_file:
figure()
print "Generating and saving %s" % fig_name
positions = numpy.loadtxt('Results/positions.dat')
positions[:, 0] -= positions[:, 0].min()
connections = files.NumpyBinaryFile('Results/connections.dat',
mode='r').read()
print positions.shape, connections.shape
connections[:, 0] -= connections[:, 0].min()
connections[:, 1] -= connections[:, 1].min()
idx_pre = connections[:, 0].astype(int)
idx_post = connections[:, 1].astype(int)
d = distances(positions[idx_pre, 1:3], positions[idx_post, 1:3], 1)
subplot(231)
title('Cells positions')
plot(positions[:, 1], positions[:, 2], '.')
subplot(232)
title('Weights distribution')
hist(connections[:, 2], 50)
subplot(233)
title('Delay distribution')
hist(connections[:, 3], 50)
subplot(234)
numpy.random.seed(74562)
ids = numpy.random.permutation(positions[:, 0])[0:6]
colors = ['k', 'r', 'b', 'g', 'c', 'y']
for count, cell in enumerate(ids):
draw_rf(cell, positions, connections, colors[count])
subplot(235)
plot(d, connections[:, 2], '.')
subplot(236)
plot(d, connections[:, 3], '.')
savefig("Results/" + fig_name)
#os.remove('Results/connections.dat')
#os.remove('Results/positions.dat')
show()