def test_lhc_creation_best_knowledge():
_create_input_lhc()
opt_dict = dict(type="best_knowledge",
accel="lhc",
year="2018",
ats=True,
beam=1,
nat_tunes=[0.31, 0.32],
dpp=0.0,
energy=6.5,
modifiers=join(BASE_OUTPUT, MODIFIERS_MADX),
outputdir=BASE_OUTPUT,
writeto=join(BASE_OUTPUT, "job.twiss_best_knowledge.madx"),
logfile=join(BASE_OUTPUT, "madx_log_best_knowledge.txt"))
create_instance_and_model(opt_dict)
_clean_up(BASE_OUTPUT)
def test_lhc_creation_relative_modeldir_path(request, tmp_path):
os.chdir(tmp_path) # switch cwd to tmp_path
model_dir_relpath = Path("test_model")
model_dir_relpath.mkdir()
optics_file_relpath = Path("opticsfile.24_ctpps2")
shutil.copy(COMP_MODEL / optics_file_relpath,
model_dir_relpath / optics_file_relpath)
accel_opt = dict(
accel="lhc",
year="2018",
ats=True,
beam=1,
nat_tunes=[0.31, 0.32],
dpp=0.0,
energy=6.5,
modifiers=[optics_file_relpath],
)
# sometimes create_instance_and_model seems to run but does not create twiss-files ...
accel = create_instance_and_model(outputdir=model_dir_relpath,
type="nominal",
logfile=tmp_path / "madx_log.txt",
**accel_opt)
# ... which is then caught here:
check_accel_from_dir_vs_options(model_dir_relpath,
accel_opt,
accel,
required_keys=["beam", "year"])
os.chdir(request.config.invocation_dir) # return to original cwd
def test_ps_creation_nominal():
_create_input_ps()
opt_dict = dict(type="nominal",
accel="ps",
nat_tunes=[6.32, 6.29],
drv_tunes=[0.325, 0.284],
driven_excitation="acd",
dpp=0.0,
energy=1.4,
modifiers=join(BASE_OUTPUT, MODIFIERS_MADX),
fullresponse=True,
outputdir=BASE_OUTPUT,
writeto=join(BASE_OUTPUT, "job.twiss.madx"),
logfile=join(BASE_OUTPUT, "madx_log.txt"))
create_instance_and_model(opt_dict)
_clean_up(BASE_OUTPUT)
def test_lhc_creation_modifier_nonexistent(tmp_path):
accel_opt = dict(
accel="lhc",
year="2018",
ats=True,
beam=1,
nat_tunes=[0.31, 0.32],
dpp=0.0,
energy=6.5,
modifiers=[COMP_MODEL / "opticsfile.non_existent"],
)
with pytest.raises(AcceleratorDefinitionError) as creation_error:
create_instance_and_model(outputdir=tmp_path,
type="nominal",
logfile=tmp_path / "madx_log.txt",
**accel_opt)
assert "opticsfile.non_existent" in str(creation_error.value)
def test_booster_creation_nominal():
iotools.create_dirs(BASE_OUTPUT)
iotools.write_string_into_new_file(join(BASE_OUTPUT, MODIFIERS_MADX), "\n")
opt_dict = dict(type="nominal",
accel="psbooster",
ring=1,
nat_tunes=[4.21, 4.27],
drv_tunes=[0.205, 0.274],
driven_excitation="acd",
dpp=0.0,
energy=0.16,
modifiers=join(BASE_OUTPUT, MODIFIERS_MADX),
fullresponse=True,
outputdir=BASE_OUTPUT,
writeto=join(BASE_OUTPUT, "job.twiss.madx"),
logfile=join(BASE_OUTPUT, "madx_log.txt"))
create_instance_and_model(opt_dict)
_clean_up(BASE_OUTPUT)
def test_lhc_creation_nominal():
_create_input_lhc()
opt_dict = dict(type="nominal",
accel="lhc",
year="2018",
ats=True,
beam=1,
nat_tunes=[0.31, 0.32],
drv_tunes=[0.298, 0.335],
driven_excitation="acd",
dpp=0.0,
energy=6.5,
modifiers=join(BASE_OUTPUT, MODIFIERS_MADX),
fullresponse=True,
outputdir=BASE_OUTPUT,
writeto=join(BASE_OUTPUT, "job.twiss.madx"),
logfile=join(BASE_OUTPUT, "madx_log.txt"))
create_instance_and_model(opt_dict)
_clean_up(BASE_OUTPUT)
def test_booster_creation_nominal_free(tmp_path):
accel_opt = dict(
accel="psbooster",
ring=1,
nat_tunes=[4.21, 4.27],
dpp=0.0,
energy=0.16,
modifiers=None,
)
accel = create_instance_and_model(type="nominal",
outputdir=tmp_path,
logfile=tmp_path / "madx_log.txt",
**accel_opt)
check_accel_from_dir_vs_options(tmp_path,
accel_opt,
accel,
required_keys=["ring"])
def test_ps_creation_nominal_free_2021(tmp_path):
accel_opt = dict(
accel="ps",
nat_tunes=[6.32, 6.29],
dpp=0.0,
energy=1.4,
year=2021,
modifiers=[PS_MODEL / "2021" / "strength" / "ps_fb_lhc.str"],
)
accel = create_instance_and_model(type="nominal",
outputdir=tmp_path,
logfile=tmp_path / "madx_log.txt",
**accel_opt)
check_accel_from_dir_vs_options(tmp_path,
accel_opt,
accel,
required_keys=["year"])
def test_lhc_creation_best_knowledge(tmp_path):
(tmp_path /
LhcBestKnowledgeCreator.EXTRACTED_MQTS_FILENAME).write_text("\n")
(tmp_path / LhcBestKnowledgeCreator.CORRECTIONS_FILENAME).write_text("\n")
accel_opt = dict(
accel="lhc",
year="2018",
ats=True,
beam=1,
nat_tunes=[0.31, 0.32],
dpp=0.0,
energy=6.5,
modifiers=[COMP_MODEL / "opticsfile.24_ctpps2"],
)
accel = create_instance_and_model(outputdir=tmp_path,
type="best_knowledge",
logfile=tmp_path / "madx_log.txt",
**accel_opt)
def test_lhc_creation_nominal_free(tmp_path):
accel_opt = dict(
accel="lhc",
year="2018",
beam=1,
nat_tunes=[0.31, 0.32],
dpp=0.0,
energy=6.5,
modifiers=[COMP_MODEL / "opticsfile.24_ctpps2"],
)
accel = create_instance_and_model(outputdir=tmp_path,
type="nominal",
logfile=tmp_path / "madx_log.txt",
**accel_opt)
check_accel_from_dir_vs_options(tmp_path,
accel_opt,
accel,
required_keys=["beam", "year"])
def test_ps_creation_nominal_driven_2018(tmp_path):
accel_opt = dict(
accel="ps",
nat_tunes=[6.32, 6.29],
drv_tunes=[0.325, 0.284],
driven_excitation="acd",
dpp=0.0,
energy=1.4,
year=2018,
modifiers=[
PS_MODEL / "2018" / "strength" / "PS_LE_LHC_low_chroma.str"
],
)
accel = create_instance_and_model(type="nominal",
outputdir=tmp_path,
logfile=tmp_path / "madx_log.txt",
**accel_opt)
check_accel_from_dir_vs_options(tmp_path,
accel_opt,
accel,
required_keys=["year"])