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 connect(self, projection):
"""Connect-up a Projection."""
if self.distributed:
self.filename += ".%d" % common.rank()
# open the file...
f = open(self.filename, 'r', 10000)
lines = f.readlines()
f.close()
# gather all the data in a list of tuples (one per line)
input_tuples = []
for line in lines:
single_line = line.rstrip()
src, tgt, w, d = single_line.split("\t", 4)
src = "[%s" % src.split("[",1)[1]
tgt = "[%s" % tgt.split("[",1)[1]
input_tuples.append((eval(src), eval(tgt), float(w), float(d)))
self.conn_list = input_tuples
FromListConnector.connect(self, projection)
def connect(self, projection):
"""Connect-up a Projection."""
if self.distributed:
self.filename += ".%d" % common.rank()
# open the file...
f = open(self.filename, 'r', 10000)
lines = f.readlines()
f.close()
# gather all the data in a list of tuples (one per line)
input_tuples = []
for line in lines:
single_line = line.rstrip()
src, tgt, w, d = single_line.split("\t", 4)
src = "[%s" % src.split("[", 1)[1]
tgt = "[%s" % tgt.split("[", 1)[1]
input_tuples.append((eval(src), eval(tgt), float(w), float(d)))
self.conn_list = input_tuples
FromListConnector.connect(self, projection)
def connect(self, projection):
"""Connect-up a Projection."""
if self.distributed:
self.file.rename("%s.%d" % (self.file.name, common.rank()))
self.conn_list = self.file.read()
FromListConnector.connect(self, projection)
def progression(self, count):
self.prog.update_amount(count)
if self.verbose and common.rank() == 0:
print self.prog, "\r",
sys.stdout.flush()
def progression(self, count):
self.prog.update_amount(count)
if self.verbose and common.rank() == 0:
print self.prog, "\r",
sys.stdout.flush()