def load_kd_bricks(self, fn=None):
if fn is None:
fn = '%s_kd_bricks.h5' % self.ds
if self.comm.rank != 0:
self.comm.recv_array(self.comm.rank - 1, tag=self.comm.rank - 1)
try:
f = h5py.File(fn, "a")
for node in depth_traverse(self.tree):
i = node.node_id
if node.grid != -1:
data = [
f["brick_%s_%s" % (hex(i), field)][:].astype('float64')
for field in self.fields
]
node.data = PartitionedGrid(node.grid.id, data,
node.l_corner.copy(),
node.r_corner.copy(),
node.dims.astype('int64'))
self.bricks.append(node.data)
self.brick_dimensions.append(node.dims)
self.bricks = np.array(self.bricks)
self.brick_dimensions = np.array(self.brick_dimensions)
self._initialized = True
f.close()
del f
except:
pass
if self.comm.rank != (self.comm.size - 1):
self.comm.send_array([0], self.comm.rank + 1, tag=self.comm.rank)
def load_kd_bricks(self,fn=None):
if fn is None:
fn = '%s_kd_bricks.h5' % self.ds
if self.comm.rank != 0:
self.comm.recv_array(self.comm.rank-1, tag=self.comm.rank-1)
try:
f = h5py.File(fn,"a")
for node in depth_traverse(self.tree):
i = node.node_id
if node.grid != -1:
data = [f["brick_%s_%s" %
(hex(i), field)][:].astype('float64') for field in self.fields]
node.data = PartitionedGrid(node.grid.id, data,
node.l_corner.copy(),
node.r_corner.copy(),
node.dims.astype('int64'))
self.bricks.append(node.data)
self.brick_dimensions.append(node.dims)
self.bricks = np.array(self.bricks)
self.brick_dimensions = np.array(self.brick_dimensions)
self._initialized=True
f.close()
del f
except:
pass
if self.comm.rank != (self.comm.size-1):
self.comm.send_array([0],self.comm.rank+1, tag=self.comm.rank)
def sum_cells(self, all_cells=False):
cells = 0
for node in depth_traverse(self.trunk):
if node.grid == -1:
continue
if not all_cells and not kd_is_leaf(node):
continue
grid = self.ds.index.grids[node.grid - self._id_offset]
dds = grid.dds
gle = grid.LeftEdge
nle = self.ds.arr(get_left_edge(node), input_units="code_length")
nre = self.ds.arr(get_right_edge(node), input_units="code_length")
li = np.rint((nle - gle) / dds).astype('int32')
ri = np.rint((nre - gle) / dds).astype('int32')
dims = (ri - li).astype('int32')
cells += np.prod(dims)
return cells
def sum_cells(self, all_cells=False):
cells = 0
for node in depth_traverse(self.trunk):
if node.grid == -1:
continue
if not all_cells and not kd_is_leaf(node):
continue
grid = self.ds.index.grids[node.grid - self._id_offset]
dds = grid.dds
gle = grid.LeftEdge
nle = self.ds.arr(get_left_edge(node), input_units="code_length")
nre = self.ds.arr(get_right_edge(node), input_units="code_length")
li = np.rint((nle-gle)/dds).astype('int32')
ri = np.rint((nre-gle)/dds).astype('int32')
dims = (ri - li).astype('int32')
cells += np.prod(dims)
return cells
def check_tree(self):
for node in depth_traverse(self.trunk):
if node.grid == -1:
continue
grid = self.ds.index.grids[node.grid - self._id_offset]
dds = grid.dds
gle = grid.LeftEdge
nle = self.ds.arr(get_left_edge(node), input_units="code_length")
nre = self.ds.arr(get_right_edge(node), input_units="code_length")
li = np.rint((nle - gle) / dds).astype('int32')
ri = np.rint((nre - gle) / dds).astype('int32')
dims = (ri - li).astype('int32')
assert (np.all(grid.LeftEdge <= nle))
assert (np.all(grid.RightEdge >= nre))
assert (np.all(dims > 0))
# print grid, dims, li, ri
# Calculate the Volume
vol = kd_sum_volume(self.trunk)
mylog.debug('AMRKDTree volume = %e' % vol)
kd_node_check(self.trunk)
def check_tree(self):
for node in depth_traverse(self.trunk):
if node.grid == -1:
continue
grid = self.ds.index.grids[node.grid - self._id_offset]
dds = grid.dds
gle = grid.LeftEdge
nle = self.ds.arr(get_left_edge(node), input_units="code_length")
nre = self.ds.arr(get_right_edge(node), input_units="code_length")
li = np.rint((nle-gle)/dds).astype('int32')
ri = np.rint((nre-gle)/dds).astype('int32')
dims = (ri - li).astype('int32')
assert(np.all(grid.LeftEdge <= nle))
assert(np.all(grid.RightEdge >= nre))
assert(np.all(dims > 0))
# print grid, dims, li, ri
# Calculate the Volume
vol = kd_sum_volume(self.trunk)
mylog.debug('AMRKDTree volume = %e' % vol)
kd_node_check(self.trunk)
def store_kd_bricks(self, fn=None):
if not self._initialized:
self.initialize_source()
if fn is None:
fn = '%s_kd_bricks.h5'%self.ds
if self.comm.rank != 0:
self.comm.recv_array(self.comm.rank-1, tag=self.comm.rank-1)
f = h5py.File(fn,'w')
for node in depth_traverse(self.tree):
i = node.node_id
if node.data is not None:
for fi,field in enumerate(self.fields):
try:
f.create_dataset("/brick_%s_%s" % (hex(i),field),
data = node.data.my_data[fi].astype('float64'))
except:
pass
f.close()
del f
if self.comm.rank != (self.comm.size-1):
self.comm.send_array([0],self.comm.rank+1, tag=self.comm.rank)
def store_kd_bricks(self, fn=None):
if not self._initialized:
self.initialize_source()
if fn is None:
fn = '%s_kd_bricks.h5' % self.ds
if self.comm.rank != 0:
self.comm.recv_array(self.comm.rank - 1, tag=self.comm.rank - 1)
f = h5py.File(fn, 'w')
for node in depth_traverse(self.tree):
i = node.node_id
if node.data is not None:
for fi, field in enumerate(self.fields):
try:
f.create_dataset(
"/brick_%s_%s" % (hex(i), field),
data=node.data.my_data[fi].astype('float64'))
except:
pass
f.close()
del f
if self.comm.rank != (self.comm.size - 1):
self.comm.send_array([0], self.comm.rank + 1, tag=self.comm.rank)
def test_amr_kdtree_coverage():
return #TESTDISABLED
domain_dims = (32, 32, 32)
data = np.zeros(domain_dims) + 0.25
fo = [
ic.CoredSphere(0.05, 0.3, [0.7, 0.4, 0.75], {"density": (0.25, 100.0)})
]
rc = [fm.flagging_method_registry["overdensity"](8.0)]
ug = load_uniform_grid({"density": data}, domain_dims, 1.0)
ds = refine_amr(ug, rc, fo, 5)
kd = AMRKDTree(ds)
volume = kd.count_volume()
yield assert_equal, volume, \
np.prod(ds.domain_right_edge - ds.domain_left_edge)
cells = kd.count_cells()
true_cells = ds.all_data().quantities['TotalQuantity']('Ones')[0]
yield assert_equal, cells, true_cells
# This largely reproduces the AMRKDTree.tree.check_tree() functionality
tree_ok = True
for node in depth_traverse(kd.tree.trunk):
if node.grid is None:
continue
grid = ds.index.grids[node.grid - kd._id_offset]
dds = grid.dds
gle = grid.LeftEdge
nle = get_left_edge(node)
nre = get_right_edge(node)
li = np.rint((nle - gle) / dds).astype('int32')
ri = np.rint((nre - gle) / dds).astype('int32')
dims = (ri - li).astype('int32')
tree_ok *= np.all(grid.LeftEdge <= nle)
tree_ok *= np.all(grid.RightEdge >= nre)
tree_ok *= np.all(dims > 0)
yield assert_equal, True, tree_ok
def test_amr_kdtree_coverage():
return #TESTDISABLED
domain_dims = (32, 32, 32)
data = np.zeros(domain_dims) + 0.25
fo = [ic.CoredSphere(0.05, 0.3, [0.7, 0.4, 0.75],
{"density": (0.25, 100.0)})]
rc = [fm.flagging_method_registry["overdensity"](8.0)]
ug = load_uniform_grid({"density": data}, domain_dims, 1.0)
ds = refine_amr(ug, rc, fo, 5)
kd = AMRKDTree(ds)
volume = kd.count_volume()
yield assert_equal, volume, \
np.prod(ds.domain_right_edge - ds.domain_left_edge)
cells = kd.count_cells()
true_cells = ds.all_data().quantities['TotalQuantity']('Ones')[0]
yield assert_equal, cells, true_cells
# This largely reproduces the AMRKDTree.tree.check_tree() functionality
tree_ok = True
for node in depth_traverse(kd.tree.trunk):
if node.grid is None:
continue
grid = ds.index.grids[node.grid - kd._id_offset]
dds = grid.dds
gle = grid.LeftEdge
nle = get_left_edge(node)
nre = get_right_edge(node)
li = np.rint((nle-gle)/dds).astype('int32')
ri = np.rint((nre-gle)/dds).astype('int32')
dims = (ri - li).astype('int32')
tree_ok *= np.all(grid.LeftEdge <= nle)
tree_ok *= np.all(grid.RightEdge >= nre)
tree_ok *= np.all(dims > 0)
yield assert_equal, True, tree_ok
