def test_ray_iterator( self ):
start = [-2, 0, 0]
startvol = dagmc.find_volume( start )
self.assertEqual( startvol, 3 )
direction = [1, 0, 0]
expected_vols = [2, 3, 1, 4]
expected_dists = [1,2,3.156921938,0]
for i, (vol, dist, surf) in enumerate( dagmc.ray_iterator( startvol, start, direction ) ):
self.assertEqual( expected_vols[i], vol )
if expected_dists[i] != 0:
self.assertAlmostEqual( expected_dists[i], dist )
self.assertEqual( i, 3 )
for i, (vol, dist, surf) in enumerate( dagmc.ray_iterator( startvol, start, direction, dist_limit=4 ) ):
self.assertEqual( expected_vols[i], vol )
if expected_dists[i] != 0:
self.assertAlmostEqual( expected_dists[i], dist )
self.assertEqual( i, 1 )
def _alloc_one_ray(self, start_ijk, dim, xyz, uvw, divs, samples):
"""Fire a single ray and store the sampled data to the grid
start_ijk: structured mesh coordinates of the hex from which ray begins
dim: 0, 1, or 2 depending on whether whether ray is x, y, or z-directed.
xyz: start position of ray
uvw: direction of ray
divs: The structured grid divisions along this dimension.
samples: 2D array of zeros used to store ray info
"""
first_vol = self.first_vol
if not first_vol or not dagmc.point_in_volume(first_vol, xyz, uvw):
first_vol = dagmc.find_volume(xyz, uvw)
vol = first_vol
loc = divs[0]
div = 0
for nxtvol, raydist, _ in dagmc.ray_iterator(vol, xyz, uvw):
mat_idx = get_mat_id(self.materials, vol)
vol = nxtvol
for meshdist, meshrat, newloc in self._grid_fragments(
divs, div, loc, raydist):
# The ray fills this voxel for a normalized distance of
# meshrat = (meshdist / length_of_voxel)
samples[div, mat_idx] += meshrat
loc += meshdist
if (newloc):
div += 1
# Save the first detected volume to speed future queries
self.first_vol = first_vol
# prepare an indexing object for self.grid to access the appropriate mesh row.
# It is important to use a slice object rather than a general sequence
# because a general sequence will trigger numpy's advanced iteration,
# which returns copies of data instead of views.
idx_ijk = start_ijk
idx_ijk[dim] = slice(self.scdmesh.dims[dim],
self.scdmesh.dims[dim + 3])
for sample, voxel in itertools.izip_longest(samples,
self.grid[idx_ijk]):
voxel['mats'] += sample
voxel['errs'] += sample**2
def _alloc_one_ray(self, start_ijk, dim, xyz, uvw, divs, samples):
"""Fire a single ray and store the sampled data to the grid
start_ijk: structured mesh coordinates of the hex from which ray begins
dim: 0, 1, or 2 depending on whether whether ray is x, y, or z-directed.
xyz: start position of ray
uvw: direction of ray
divs: The structured grid divisions along this dimension.
samples: 2D array of zeros used to store ray info
"""
first_vol = self.first_vol
if not first_vol or not dagmc.point_in_volume(first_vol,xyz,uvw):
first_vol = dagmc.find_volume(xyz,uvw)
vol = first_vol
loc = divs[0]
div = 0
for nxtvol, raydist, _ in dagmc.ray_iterator( vol, xyz, uvw ):
mat_idx = get_mat_id( self.materials, vol )
vol = nxtvol
for meshdist, meshrat, newloc in self._grid_fragments( divs, div, loc, raydist ):
# The ray fills this voxel for a normalized distance of
# meshrat = (meshdist / length_of_voxel)
samples[div,mat_idx] += meshrat
loc += meshdist
if(newloc):
div += 1
# Save the first detected volume to speed future queries
self.first_vol = first_vol
# prepare an indexing object for self.grid to access the appropriate mesh row.
# It is important to use a slice object rather than a general sequence
# because a general sequence will trigger numpy's advanced iteration,
# which returns copies of data instead of views.
idx_ijk = start_ijk
idx_ijk[dim] = slice(self.scdmesh.dims[dim], self.scdmesh.dims[dim+3])
for sample, voxel in itertools.izip_longest( samples, self.grid[idx_ijk]):
voxel['mats'] += sample
voxel['errs'] += sample**2
localtime = time.asctime(time.localtime(time.time()))
print(float(i) / float(nps)) * 100.0, '% complete', localtime
print 'lost particle fraction = ', (float(num_lost) /
float(nps)) * 100.0, '%'
# call an isotropic source
uvw = source_functions.isotropic()
volumes = list()
positions = list()
# set the iterator to produce xyz hit locations
kw = {"yield_xyz": 'yield_xyz'}
# intialise the ray iterator with appropriate values
dagmc.ray_iterator(first_vol, pos, uvw, **kw)
# loop through the ray history
for (vol, dist, sur, xyz) in dagmc.ray_iterator(first_vol, pos, uvw, **kw):
volumes.append(vol)
positions.append(str(xyz))
# uvw = source_functions.isotropic()
# print xyz
lost = andy_geom_functions.lost_particle(volumes)
if lost == 0:
num_lost += 1
# call dump2vtk, which takes the current ray history and prints it in nice format
andy_geom_functions.dump_2_vtk(pos, positions, num_lost)
andy_geom_functions.extrapolate_ray(pos, positoins, num_lost, 200.0)
if i%(nps/10)==0:
localtime = time.asctime(time.localtime(time.time()))
print (float(i)/float(nps))*100.0,'% complete', localtime
print 'lost particle fraction = ',(float(num_lost)/float(nps))*100.0,'%'
# call an isotropic source
uvw = source_functions.isotropic()
volumes=list()
positions=list()
# set the iterator to produce xyz hit locations
kw={"yield_xyz":'yield_xyz'}
# intialise the ray iterator with appropriate values
dagmc.ray_iterator(first_vol,pos,uvw,**kw)
# loop through the ray history
for (vol,dist,sur,xyz) in dagmc.ray_iterator(first_vol,pos,uvw,**kw):
volumes.append(vol)
positions.append(str(xyz))
# uvw = source_functions.isotropic()
# print xyz
lost = andy_geom_functions.lost_particle(volumes)
if lost == 0:
num_lost +=1
# call dump2vtk, which takes the current ray history and prints it in nice format
andy_geom_functions.dump_2_vtk(pos,positions,num_lost)
andy_geom_functions.extrapolate_ray(pos,positoins,num_lost,200.0)