def test_isotropic_vol_source():
"""Test isotropic volumetric source generation from DAGMC geometry.
"""
try:
from pyne import dagmc
except:
raise SkipTest
if not HAVE_PYMOAB:
raise SkipTest
sc = np.linspace(-25, 25, 6)
m = Mesh(structured=True, structured_coords=[sc, sc, sc])
cells = [14, 15]
spectra = [[0.1, 0.1, 0.1, 0.7], [0.3, 0.3, 0.3, 0.1]]
intensities = [1, 2]
dg, s = partisn.isotropic_vol_source("files_test_partisn/source_boxes.h5m",
m, cells, spectra, intensities,
num_rays=4, tag_name="src", grid=True)
m.src = NativeMeshTag(4, float)
data = m.src[:]
# setup expected result, confirmed by hand calcs and inspection
exp = np.zeros(shape=((len(sc) - 1)**3, len(spectra[0])))
exp[22, :] = [0.025, 0.025, 0.025, 0.175]
exp[62, :] = [0.075, 0.075, 0.075, 0.025]
exp[63, :] = [0.075, 0.075, 0.075, 0.025]
exp[87, :] = [0.075, 0.075, 0.075, 0.025]
exp[88, :] = [0.075, 0.075, 0.075, 0.025]
assert(np.allclose(data, exp))
def step1(cfg):
"""This function writes the PARTISN input file for the adjoint photon
transport
Parameters
----------
cfg : dictionary
User input for step 1 from the config.yml file
"""
# Get user-input from config file
geom = cfg["geom_file"]
cells = [cfg["src_cell"]]
src_vol = [float(cfg["src_vol"])]
try:
origin_x, origin_y, origin_z = cfg["origin"].split(" ")
except:
print("Too few entries in origin location")
xmesh = cfg["xmesh"]
xints = cfg["xints"]
ymesh = cfg["ymesh"]
yints = cfg["yints"]
zmesh = cfg["zmesh"]
zints = cfg["zints"]
# Create structured mesh
sc = [
np.linspace(float(origin_x), float(xmesh), float(xints) + 1),
np.linspace(float(origin_y), float(ymesh), float(yints) + 1),
np.linspace(float(origin_z), float(zmesh), float(zints) + 1),
]
m = Mesh(structured=True, structured_coords=sc)
m.write_hdf5("blank_mesh.h5m")
# Generate 42 photon energy bins [eV]
# First bin has been replaced with 1 for log interpolation
photon_bins = np.array(
[
1e-6,
0.01,
0.02,
0.03,
0.045,
0.06,
0.07,
0.075,
0.1,
0.15,
0.2,
0.3,
0.4,
0.45,
0.51,
0.512,
0.6,
0.7,
0.8,
1,
1.33,
1.34,
1.5,
1.66,
2,
2.5,
3,
3.5,
4,
4.5,
5,
5.5,
6,
6.5,
7,
7.5,
8,
10,
12,
14,
20,
30,
50,
]
)
# ICRP 74 flux-to-dose conversion factors in pico-Sv/s per photon flux
de = np.array(
[
0.01,
0.015,
0.02,
0.03,
0.04,
0.05,
0.06,
0.07,
0.08,
0.1,
0.15,
0.2,
0.3,
0.4,
0.5,
0.6,
0.8,
1,
2,
4,
6,
8,
10,
]
)
df = np.array(
[
0.0485,
0.1254,
0.205,
0.2999,
0.3381,
0.3572,
0.378,
0.4066,
0.4399,
0.5172,
0.7523,
1.0041,
1.5083,
1.9958,
2.4657,
2.9082,
3.7269,
4.4834,
7.4896,
12.0153,
15.9873,
19.9191,
23.76,
]
)
# Convert to Sv/s per photon FLUX
pico = 1.0e-12
df = df * pico
# Convert pointwise data to group data for log interpolation
photon_spectrum = pointwise_collapse(photon_bins, de, df, logx=True, logy=True)
# Anything below 0.01 MeV should be assigned the DF value of 0.01 MeV
photon_spectrum[0] = df[0]
# Total number of groups is 217 (42 photon + 175 neutron)
spectra = [np.append(photon_spectrum, np.zeros(175))]
# The spectrum is normalized by PyNE, so we need to mutliply by the sum of
# intensities in the spectrum.
# Additionally, we divide by the volume of the source cell in order to get
# source density.
intensities = [np.sum(spectra) / src_vol]
# Load geometry into DAGMC
load(geom)
# Generate isotropic photon volume source
source, dg = isotropic_vol_source(geom, m, cells, spectra, intensities)
# PARTISN input
ngroup = 217 # total number of energy groups
cards = _cards(source) # block 1, 3, 5 input values
names_dict = _names_dict() # dictionary of isotopes (PyNE nucids to bxslib names)
write_partisn_input(
m,
geom,
ngroup,
cards=cards,
dg=dg,
names_dict=names_dict,
data_hdf5path="/materials",
nuc_hdf5path="/nucid",
fine_per_coarse=1,
)
