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d765bd031f
Co-authored-by: John Tramm <john.tramm@gmail.com> Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
from pathlib import Path
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import openmc
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import pytest
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from tests.testing_harness import config
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@pytest.fixture
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def model():
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mat = openmc.Material()
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mat.add_nuclide('N14', 1.0)
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mat.set_density('g/cm3', 1e-5)
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s1 = openmc.Sphere(r=80.0)
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s2 = openmc.Sphere(r=90.0)
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s3 = openmc.Sphere(r=100.0, boundary_type='vacuum')
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cell1 = openmc.Cell(fill=mat, region=-s1)
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cell2 = openmc.Cell(fill=mat, region=+s2 & -s3)
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model = openmc.Model()
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model.geometry = openmc.Geometry([cell1, cell2])
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model.settings.run_mode = 'fixed source'
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model.settings.batches = 10
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model.settings.inactive = 5
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model.settings.particles = 50
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model.settings.max_lost_particles = 1000
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model.settings.source = openmc.IndependentSource(space=openmc.stats.Point())
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return model
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def test_max_write_lost_particles(model: openmc.Model, run_in_tmpdir):
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# Set maximum number of lost particle restart files
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model.settings.max_write_lost_particles = 5
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# Run OpenMC to generate lost particle files. Use one thread so that we know
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# exactly how much will be produced. If running in MPI mode, setup proper
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# keyword arguments for run()
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kwargs = {'openmc_exec': config['exe']}
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if config['mpi']:
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kwargs['mpi_args'] = [config['mpiexec'], '-n', config['mpi_np']]
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model.run(threads=1, **kwargs)
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# Make sure number of lost particle files is as expected
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lost_particle_files = list(Path.cwd().glob('particle*.h5'))
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n_procs = int(config['mpi_np']) if config['mpi'] else 1
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assert len(lost_particle_files) == model.settings.max_write_lost_particles * n_procs
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