def test_copy_if(ctx_factory):
context = ctx_factory()
queue = cl.CommandQueue(context)
from pyopencl.clrandom import rand as clrand
for n in scan_test_counts:
a_dev = clrand(queue, (n,), dtype=np.int32, a=0, b=1000)
a = a_dev.get()
from pyopencl.algorithm import copy_if
crit = a_dev.dtype.type(300)
selected = a[a>crit]
selected_dev, count_dev = copy_if(a_dev, "ary[i] > myval", [("myval", crit)])
assert (selected_dev.get()[:count_dev.get()] == selected).all()
from gc import collect
collect()
def test_copy_if(ctx_factory):
from pytest import importorskip
importorskip("mako")
from pyopencl.clrandom import rand as clrand
for n in scan_test_counts:
a_dev = clrand(queue, (n,), dtype=np.int32, a=0, b=1000)
#a = a_dev.get()
from pyopencl.algorithm import copy_if
crit = a_dev.dtype.type(6)
#selected = a[a < crit]
selected_dev, count_dev, evt = copy_if(a_dev, "ary[i] < myval", [("myval", crit)])
print count_dev
print selected_dev[selected_dev>0]
def global_qbx_centers(self):
"""Build a list of indices of QBX centers that use global QBX. This
indexes into the global list of targets, (see :meth:`target_info`) of
which the QBX centers occupy the first *ncenters*.
Centers without any associated targets are excluded.
"""
tree = self.tree()
user_target_to_center = self.user_target_to_center()
with cl.CommandQueue(self.cl_context) as queue:
tgt_assoc_result = (
user_target_to_center.with_queue(queue)[self.ncenters:])
center_is_used = cl.array.zeros(queue, self.ncenters, np.int8)
self.code_getter.pick_used_centers(
queue,
center_is_used=center_is_used,
target_to_center=tgt_assoc_result,
ncenters=self.ncenters,
ntargets=len(tgt_assoc_result))
from pyopencl.algorithm import copy_if
result, count, _ = copy_if(
cl.array.arange(queue, self.ncenters,
tree.particle_id_dtype),
"global_qbx_flags[i] != 0 && center_is_used[i] != 0",
extra_args=[
("global_qbx_flags", self.global_qbx_flags()),
("center_is_used", center_is_used)
],
queue=queue)
if self.debug:
logger.debug(
"find global qbx centers: using %d/%d centers"
% (int(count.get()), self.ncenters))
return result[:count.get()].with_queue(None)
def global_qbx_centers(self):
"""Build a list of indices of QBX centers that use global QBX. This
indexes into the global list of targets, (see :meth:`target_info`) of
which the QBX centers occupy the first *ncenters*.
Centers without any associated targets are excluded.
"""
tree = self.tree()
user_target_to_center = self.user_target_to_center()
with cl.CommandQueue(self.cl_context) as queue:
tgt_assoc_result = (
user_target_to_center.with_queue(queue)[self.ncenters:])
center_is_used = cl.array.zeros(queue, self.ncenters, np.int8)
self.code_getter.pick_used_centers(
queue,
center_is_used=center_is_used,
target_to_center=tgt_assoc_result,
ncenters=self.ncenters,
ntargets=len(tgt_assoc_result))
from pyopencl.algorithm import copy_if
result, count, _ = copy_if(
cl.array.arange(queue, self.ncenters, tree.particle_id_dtype),
"global_qbx_flags[i] != 0 && center_is_used[i] != 0",
extra_args=[("global_qbx_flags", self.global_qbx_flags()),
("center_is_used", center_is_used)],
queue=queue)
if self.debug:
logger.debug("find global qbx centers: using %d/%d centers",
int(count.get()), self.ncenters)
return result[:count.get()].with_queue(None)
def __getitem__(self, index):
if isinstance(index, myclArray) and index.dtype == dtbool:
x, y, z = algorithm.copy_if(self.reshape((self.size,)),\
"index[i]!=0",\
# TODO: avoid type convert
[("index", bool2int(index).reshape((index.size,)))])
res = x[:y.get()]
elif isinstance(index, tuple) or isinstance(index, slice):
indices, newshape = self.createshapes(index)
program = programs.sliceget(self.dtype, len(self.shape), indices is None)
res = empty(newshape, self.dtype)
program.mislice(queue, (res.size,), None, indices.data if indices else np.int32(0), self.data, res.data)
elif isinstance(index, myclArray) and self.ndim>0:
program = programs.getndbyids(self.dtype, index.dtype)
resshape = (index.size,) + self.shape[1:] if index.size>1 else self.shape[1:]
dims = (int(np.prod(self.shape[1:])), int(index.size),)
res = empty(resshape, self.dtype)
program.getbyids(queue, dims, None, index.data, self.data, res.data)
else:
res = clarray.Array.__getitem__(self, index)
if not isinstance(res, myclArray):
res.__class__ = myclArray
res.reinit()
return res
def global_qbx_centers(self):
"""Build a list of indices of QBX centers that use global QBX. This
indexes into the global list of targets, (see :meth:`target_info`) of
which the QBX centers occupy the first *ncenters*.
Centers without any associated targets are excluded.
"""
actx = self._setup_actx
tree = self.tree()
user_target_to_center = actx.thaw(self.user_target_to_center())
tgt_assoc_result = user_target_to_center[self.ncenters:]
center_is_used = actx.zeros(self.ncenters, np.int8)
self.code_getter.pick_used_centers(actx.queue,
center_is_used=center_is_used,
target_to_center=tgt_assoc_result,
ncenters=self.ncenters,
ntargets=len(tgt_assoc_result))
from pyopencl.algorithm import copy_if
icenters = actx.from_numpy(
np.arange(self.ncenters, dtype=tree.particle_id_dtype))
result, count, _ = copy_if(
icenters,
"global_qbx_flags[i] != 0 && center_is_used[i] != 0",
extra_args=[("global_qbx_flags", self.global_qbx_flags()),
("center_is_used", center_is_used)],
queue=actx.queue)
count = actx.to_numpy(count).item()
if self.debug:
logger.debug("find global qbx centers: using %d/%d centers", count,
self.ncenters)
return actx.freeze(result[:count])
def global_qbx_centers(self):
"""Build a list of indices of QBX centers that use global QBX. This
indexes into the global list of targets, (see :meth:`target_info`) of
which the QBX centers occupy the first *ncenters*.
"""
tree = self.tree()
with cl.CommandQueue(self.cl_context) as queue:
from pyopencl.algorithm import copy_if
logger.info("find global qbx centers: start")
result, count, _ = copy_if(
cl.array.arange(queue, self.center_info().ncenters,
tree.particle_id_dtype),
"global_qbx_flags[i] != 0",
extra_args=[
("global_qbx_flags", self.global_qbx_flags())
],
queue=queue)
logger.info("find global qbx centers: done")
return result[:count.get()].with_queue(None)
import pyopencl as cl import numpy as np from pyopencl import array from pyopencl.algorithm import copy_if context = cl.create_some_context() queue = cl.CommandQueue(context) mf = cl.mem_flags rand = cl_array.to_device (ctx, queue, numpy.random.randn(4,4).astype(np.int32)) #rand = np.random.random_integers(0,2**10,size=(2**10)*8).astype(np.int32) print rand a = array.to_device(queue, rand, allocator=None, async=False) scan_kernel = copy_if(a, predicate = "(a[i]<104) ? 1:0") #a = cl.array.arange(queue, 10000, dtype=np.int32) out, count, event = scan_kernel(a, queue=queue) print a