def test_bad_filenames() -> None:
"""Checks if exim settings exceptions are handled properly."""
wrong_filename = "very/bad:filename?here*"
with pytest.raises(OSError):
mnprng = NamedPrng(mpurposes, wrong_filename)
with pytest.raises(OSError):
mnprng = NamedPrng(mpurposes, mparticles,
(wrong_filename, None, False))
with pytest.raises(OSError):
mnprng = NamedPrng(mpurposes, mparticles,
(None, wrong_filename, False))
with pytest.raises(OSError):
mnprng = NamedPrng(mpurposes, mparticles)
mnprng.export_particles(wrong_filename)
def test_same_case_after_pickle() -> None:
"""Tests if pickle works as expected.
Exports particles and loads back, and tests if the generated
random numbers for a subset is the same, for one
realization_id for uniform and for a range for gaussian.
"""
# uniform, single realization ID
mnprng_save = NamedPrng(mpurposes, mparticles)
mnprng_save.init_prngs(realizations=0)
generate_arg = (
Distr.UNI, # distribution
["quarks", mpurposes[0]], # particle type and purpose
(remove_quarks, FStrat.EXC)) # filtering
arr_save = mnprng_save.generate(*generate_arg)
mparticles_fname = "test_same_case_after_pickle_random"
mnprng_save.export_particles(mparticles_fname)
del mnprng_save
mnprng_load = NamedPrng(mpurposes, mparticles_fname)
mnprng_load.init_prngs(realizations=0)
arr_load = mnprng_load.generate(*generate_arg)
del mnprng_load
assert arr_save == pytest.approx(arr_load)
if os.path.isfile(mparticles_fname):
os.remove(mparticles_fname)
#
# gaussian, realization ID range
seed_args = ["quarks", mpurposes[0], range(0, 2)]
# distinguishable particles, filtering
mnprng_save = NamedPrng(mpurposes, mparticles)
mnprng_save.init_prngs(realizations=0)
marr_save = mnprng_save.generate_it((Distr.STN, (1, 3)), seed_args,
(None, remove_quarks))
mparticles_fname = "test_same_case_after_pickle_normal"
mnprng_save.export_particles(mparticles_fname)
del mnprng_save
mnprng_load = NamedPrng(mpurposes, mparticles_fname)
mnprng_load.init_prngs(realizations=0)
marr_load = mnprng_load.generate_it((Distr.STN, (1, 3)), seed_args,
(None, remove_quarks))
assert marr_save == pytest.approx(marr_load)
if os.path.isfile(mparticles_fname):
os.remove(mparticles_fname)
# indistinguishable particles, no filtering
unprng_save = NamedPrng(mpurposes, uparticles)
unprng_save.init_prngs(realizations=0)
uarr_save = unprng_save.generate_it((Distr.STN, (1, 3)), seed_args)
uparticles_fname = "test_same_case_after_pickle_normal_indi"
unprng_save.export_particles(uparticles_fname)
del unprng_save
unprng_load = NamedPrng(mpurposes, uparticles_fname)
unprng_load.init_prngs(realizations=0)
uarr_load = unprng_load.generate_it((Distr.STN, (1, 3)), seed_args)
assert uarr_save == pytest.approx(uarr_load)
if os.path.isfile(uparticles_fname):
os.remove(uparticles_fname)
###################################################################""")
Mnprng_gen = NamedPrng(mpurposes,
mparticles,
exim_settings=("tee.dat", "", True))
do_some_stuff(Mnprng_gen)
del Mnprng_gen
print("""
###################################################################
########### Random numbers are read from a file ###########
###################################################################""")
Mnprng_use = NamedPrng(mpurposes,
mparticles,
exim_settings=("", "tee.dat", True))
do_some_stuff(Mnprng_use)
Mnprng_use.export_particles()
del Mnprng_use
Mnprng_stu = NamedPrng(mpurposes)
print(
"\nLoad back the particles and generate random numbers for quarks for random_walk."
)
print(Mnprng_stu.generate_it(Distr.UNI, ["quarks", "random_walk", (0, 1, 2)]))
os.remove("dict_of_particles.pickle")
print(f"\nPrint out {len(range(0,4))} times random number for quarks.",
f"quarks are {len(quarks)} long")
ind_particles = NamedPrng(mpurposes, uparticles)
rnd_array = ind_particles.generate_it(Distr.UNI,
