def test_really_simple0(self):
A = numpy.zeros((3, ))
B = numpy.zeros((3, 5))
D = DistanceMatrix(B, Space())
D.set_source(A)
assert_arrays_almost_equal(D.as_array(), numpy.zeros((5, ), float),
1e-12)
def __init__(self,
projection,
weights=0.0,
delays=None,
allow_self_connections=True,
space=Space(),
safe=True):
Connector.__init__(self, weights, delays, space, safe)
if isinstance(projection.rng, random.NativeRNG):
raise Exception("Use of NativeRNG not implemented.")
else:
self.rng = projection.rng
self.N = projection.pre.size
idx = numpy.arange(self.N * rank(), self.N * (rank() + 1))
self.M = num_processes() * self.N
self.local = numpy.ones(self.N, bool)
self.local_long = numpy.zeros(self.M, bool)
self.local_long[idx] = True
self.weights_generator = WeightGenerator(weights, self.local_long,
projection, safe)
self.delays_generator = DelayGenerator(delays, self.local_long, safe)
self.probas_generator = ProbaGenerator(
random.RandomDistribution('uniform', (0, 1), rng=self.rng),
self.local_long)
self.distance_matrix = DistanceMatrix(projection.pre.positions,
self.space, self.local)
self.projection = projection
self.candidates = projection.pre.all_cells
self.allow_self_connections = allow_self_connections
def test_extract_with_simple_d_expr(self):
B = numpy.zeros((3, 5))
dist = DistanceMatrix(B, Space())
gen = ConnectionAttributeGenerator(source="d*d",
local_mask=None,
safe=False)
dist.set_source(numpy.zeros((3, )))
assert_arrays_almost_equal(gen.extract(5, dist, sub_mask=None),
numpy.zeros((5, ), float), 1e-12)
dist.set_source(numpy.array([1, 0, 0]))
assert_arrays_almost_equal(gen.extract(5, dist, sub_mask=None),
numpy.ones((5, ), float), 1e-12)
dist.set_source(numpy.array([2, 0, 0]))
assert_arrays_almost_equal(gen.extract(5, dist, sub_mask=None),
4 * numpy.ones((5, ), float), 1e-12)
