def reversed(self):
"""Create a connectivity matrix where each incoming edge becomes outgoing."""
n_rows = len(self)
reversed = DirectedAdjacencyMatrix(n_rows, self.dtype)
for r, row in enumerate(py.prog_iter(self)):
for c in row:
reversed[c].append(r)
return reversed
def reversed(self):
"""Create a connectivity matrix where each incoming edge becomes outgoing."""
n_rows = len(self)
reversed = DirectedAdjacencyMatrix(n_rows, self.dtype)
for r, row in enumerate(py.prog_iter(self)):
for c in row:
reversed[c].append(r)
return reversed
def connect_randomly(self,
p,
xxx_todo_changeme=(0, None),
xxx_todo_changeme1=(0, None)):
(src_start, src_end) = xxx_todo_changeme
(target_start, target_end) = xxx_todo_changeme1
rows = len(self)
if src_end is None: src_end = rows
if target_end is None: target_end = rows
assert 0 <= src_start <= src_end <= rows
assert 0 <= target_start <= target_end <= rows
assert 0.0 <= p <= 1.0
src_num = src_end - src_start
target_num = target_end - target_start
degree = numpy.random.binomial(target_num, p, src_num)
for i in py.prog_iter(list(range(src_num))):
sample = random.sample(list(range(target_start, target_end)),
degree[i])
py.include_many(self[src_start + i], sample)
def connect_randomly(self, p, (src_start, src_end)=(0, None),
(target_start, target_end)=(0, None)):
rows = len(self)
if src_end is None: src_end = rows
if target_end is None: target_end = rows
assert 0 <= src_start <= src_end <= rows
assert 0 <= target_start <= target_end <= rows
assert 0.0 <= p <= 1.0
src_num = src_end - src_start
target_num = target_end - target_start
degree = numpy.random.binomial(target_num, p, src_num)
for i in py.prog_iter(xrange(src_num)):
sample = random.sample(xrange(target_start, target_end), degree[i])
py.include_many(self[src_start + i], sample)
@property
def packed(self):
"""
each row is placed side-by-side with the length of the row interlaced
the head of the packed matrix contains offsets to this length
e.g. [[11, 22, 33], [44, 55], []] => [3, 7, 10, 3, 11, 22, 33, 2, 44, 55, 0]
"""
# not the most efficient implementation atm but whatever
n_rows = len(self)
size = len(self)*2 + self.n_edges
packed = numpy.empty(size, self.dtype)
offset = n_rows
