def test_distribute():
class MyComm(object):
def __init__(self, rank, size):
self.rank = rank
self.size = size
if size > 1:
return
def func(a, r, shape, shapes):
assert_equal(a[r], shape[0])
assert_equal(shapes[r], shape)
for n in range(10):
for sz in range(1, 7):
work = np.zeros(n, int)
for i in range(n):
work[i] = i % sz
a = np.zeros(sz, int)
for r in range(sz):
a[r] = sum(work == r)
stop = tuple(np.cumsum(a))
start = (0, ) + stop[:-1]
comm = MyComm(0, sz)
for s in [(), (1, ), (3, 4)]:
shapes = distribute_shapes((n, ) + s, comm=comm)
for r in range(sz):
shape = distribute_shape((n, ) + s, rank=r, size=sz)
yield func, a, r, shape, shapes
if len(s) > 0:
continue
sl = slice(start[r], stop[r])
yield assert_eq, sl, split(n, sz, r)
def test_distribute():
class MyComm(object):
def __init__(self, rank, size):
self.rank = rank
self.size = size
if size > 1:
return
def func(a, r, shape, shapes):
assert_equal(a[r], shape[0])
assert_equal(shapes[r], shape)
for n in range(10):
for sz in range(1, 7):
work = np.zeros(n, int)
for i in range(n):
work[i] = i % sz
a = np.zeros(sz, int)
for r in range(sz):
a[r] = sum(work == r)
stop = tuple(np.cumsum(a))
start = (0,) + stop[:-1]
comm = MyComm(0, sz)
for s in [(), (1,), (3, 4)]:
shapes = distribute_shapes((n,) + s, comm=comm)
for r in range(sz):
shape = distribute_shape((n,) + s, rank=r, size=sz)
yield func, a, r, shape, shapes
if len(s) > 0:
continue
sl = slice(start[r], stop[r])
yield assert_eq, sl, split(n, sz, r)
def test_read():
shape_global = ref.shape
shape_local = distribute_shape(shape_global)
assert_equal(shape_local, lmap.shape)
lmaps = MPI.COMM_WORLD.allgather(lmap)
gmap = np.concatenate(lmaps, axis=0).magnitude
assert_all_eq(ref, gmap)
def test_read():
shape_global = ref.shape
shape_local = distribute_shape(shape_global)
assert_equal(shape_local, lmap.shape)
lmaps = MPI.COMM_WORLD.allgather(lmap)
gmap = np.concatenate(lmaps, axis=0).magnitude
assert_all_eq(ref, gmap)
def __init__(self, mask, operator=MPI.SUM, commin=MPI.COMM_WORLD,
**keywords):
commout = commin
shapeout = mask.size - int(np.sum(mask))
shapein = distribute_shape(mask.shape, comm=commin)
Operator.__init__(self, shapein=shapein, shapeout=shapeout,
commin=commin, commout=commout, **keywords)
self.mask = mask
self.chunk_size = product(mask.shape[1:])
self.operator = operator
def __init__(self,
mask,
operator=MPI.SUM,
commin=MPI.COMM_WORLD,
**keywords):
commout = commin
shapeout = mask.size - int(np.sum(mask))
shapein = distribute_shape(mask.shape, comm=commin)
Operator.__init__(self,
shapein=shapein,
shapeout=shapeout,
commin=commin,
commout=commout,
**keywords)
self.mask = mask
self.chunk_size = product(mask.shape[1:])
self.operator = operator
def func(comm, s1, s2):
shape_global = (s1,) + s2
shape_local = distribute_shape(shape_global, comm=comm)
shape_global2 = combine_shape(shape_local, comm=comm)
assert shape_global == shape_global2
def func(comm, s1, s2):
shape_global = (s1, ) + s2
shape_local = distribute_shape(shape_global, comm=comm)
shape_global2 = combine_shape(shape_local, comm=comm)
assert shape_global == shape_global2
