def testOneToOne(self):
"""For all connections created with "OneToOne" it should be possible to obtain the weight using pyneuron.getWeight()"""
prj1 = nest.Projection(self.source33, self.target33, 'oneToOne')
prj2 = nest.Projection(self.source33, self.target33,
nest.OneToOneConnector())
assert len(prj1) == self.source33.size
assert len(prj2) == self.source33.size
def testFixedProbability(self):
"""For all connections created with "fixedProbability" it should be possible to obtain the weight using pynest.getWeight()"""
for srcP in [self.source5, self.source22]:
for tgtP in [self.target6, self.target33]:
prj1 = nest.Projection(srcP, tgtP, "fixedProbability", 0.5)
prj2 = nest.Projection(srcP, tgtP,
nest.FixedProbabilityConnector(0.5))
for prj in prj1, prj2:
assert len(prj._sources) == len(prj._targets)
weights = []
for src, tgt in prj.connections():
weights.append(nest.pynest.getWeight(src, tgt))
assert weights == [0.0] * len(prj._sources), weights
def testAllToAll(self):
"""For all connections created with "allToAll" it should be possible to obtain the weight using pynest.getWeight()"""
for srcP in [self.source5, self.source22]:
for tgtP in [self.target6, self.target33]:
prj1 = nest.Projection(srcP, tgtP, "allToAll")
prj2 = nest.Projection(srcP, tgtP, nest.AllToAllConnector())
for prj in prj1, prj2:
assert len(prj._sources) == len(prj._targets)
weights = []
for src, tgt in prj.connections():
weights.append(nest.pynest.getWeight(src, tgt))
assert weights == [0.0] * len(
prj._sources) # default weight is zero
def testSaveAndLoad(self):
prj1 = nest.Projection(self.source22, self.target33, 'allToAll')
prj1.setDelays(0.2)
prj1.setWeights(1.234)
prj1.saveConnections("connections.tmp")
connector = nest.FromFileConnector("connections.tmp")
prj2 = nest.Projection(self.source22, self.target33, connector)
w1 = []
w2 = []
d1 = []
d2 = []
# For a connections scheme saved and reloaded, we test if the connections, their weights and their delays
# are equal.
for src, tgt in prj1.connections():
w1.append(nest.pynest.getWeight(src, tgt))
d1.append(nest.pynest.getDelay(src, tgt))
for src, tgt in prj2.connections():
w2.append(nest.pynest.getWeight(src, tgt))
d2.append(nest.pynest.getDelay(src, tgt))
assert (w1 == w2) and (d1 == d2)
def testrandomizeDelays(self):
# The probability of having two consecutive weights vector that are equal should be 0
prj1 = nest.Projection(self.source5, self.target33, 'allToAll')
prj1.randomizeDelays(self.distrib_Numpy)
d1 = []
d2 = []
for src, tgt in prj1.connections():
d1.append(nest.pynest.getDelay(src, tgt))
prj1.randomizeDelays(self.distrib_Numpy)
for src, tgt in prj1.connections():
d2.append(nest.pynest.getDelay(src, tgt))
self.assertNotEqual(d1, d2)
def testDistantDependentProbability(self):
"""For all connections created with "distanceDependentProbability"..."""
# Test should be improved..."
for rngclass in (nest.NumpyRNG, nest.NativeRNG):
for expr in ('exp(-d)', 'd < 0.5'):
prj1 = nest.Projection(self.source33,
self.target33,
'distanceDependentProbability',
{'d_expression': expr},
rng=rngclass(12345))
prj2 = nest.Projection(
self.source33,
self.target33,
nest.DistanceDependentProbabilityConnector(
d_expression=expr),
rng=rngclass(12345))
assert (0 < len(prj1) < len(self.source33)*len(self.target33)) \
and (0 < len(prj2) < len(self.source33)*len(self.target33))
if rngclass == nest.NumpyRNG:
assert prj1._sources == prj2._sources, "%s %s" % (rngclass,
expr)
assert prj1._targets == prj2._targets, "%s %s" % (rngclass,
expr)
def setUp(self):
nest.setup(max_delay=0.5)
nest.Population.nPop = 0
self.target33 = nest.Population((3, 3), nest.IF_curr_alpha)
self.target6 = nest.Population((6, ), nest.IF_curr_alpha)
self.source5 = nest.Population((5, ), nest.SpikeSourcePoisson)
self.source22 = nest.Population((2, 2), nest.SpikeSourcePoisson)
self.prjlist = []
self.distrib_Numpy = random.RandomDistribution(
rng=random.NumpyRNG(12345),
distribution='uniform',
parameters=(0.1, 0.5))
for tgtP in [self.target6, self.target33]:
for srcP in [self.source5, self.source22]:
for method in ('allToAll', 'fixedProbability'):
self.prjlist.append(
nest.Projection(srcP, tgtP, method,
{'p_connect': 0.5}))