def test_all_particles_are_loaded():
Particle.load_table(data.open_text(data, "particle2018.csv"))
assert len(Particle.all()) == 605
Particle.load_table(data.open_text(data, "particle2019.csv"))
assert len(Particle.all()) == 610
Particle.load_table(data.open_text(data, "particle2020.csv"))
assert len(Particle.all()) == 610
Particle.load_table(data.open_text(data, "nuclei2020.csv"))
assert len(Particle.all()) == 5880
# Load default table to restore global state
Particle.load_table()
def test_generate(tmp_path):
'This verifies that the input and output files match.'
particle2008 = tmp_path / 'particle2008.csv'
particle2018 = tmp_path / 'particle2018.csv'
produce_files(particle2008, particle2018, '2018')
particle2008_data = data.open_text(data, 'particle2008.csv')
with particle2008.open() as src, particle2008_data as res:
assert src.read() == res.read()
particle2018_data = data.open_text(data, 'particle2018.csv')
with particle2018.open() as src, particle2018_data as res:
assert src.read() == res.read()
def test_generate(tmp_path):
"This verifies that the input and output files match."
particle2008 = tmp_path / "particle2008.csv"
particle2019 = tmp_path / "particle2019.csv"
produce_files(particle2008, particle2019, "2019")
particle2008_data = data.open_text(data, "particle2008.csv")
with particle2008.open() as src, particle2008_data as res:
assert src.read() == res.read()
particle2019_data = data.open_text(data, "particle2019.csv")
with particle2019.open() as src, particle2019_data as res:
assert src.read() == res.read()
def test_DirectionalMaps():
filename = data.open_text(data, "pdgid_to_pythiaid.csv")
PDG2PyIDMap, Py2PDGIDMap = DirectionalMaps(
"PDGID", "PythiaID", filename=filename, converters=(int, int)
)
assert len(PDG2PyIDMap) == 538
assert len(Py2PDGIDMap) == 538
assert "DirectionalMap(PDGID->PYTHIAID)" in str(PDG2PyIDMap)
assert "DirectionalMap(PYTHIAID->PDGID)" in str(Py2PDGIDMap)
with pytest.raises(MatchingIDNotFound):
pyid = PDG2PyIDMap[PDGID(9000221)]
with pytest.raises(MatchingIDNotFound):
pdgid = Py2PDGIDMap[PythiaID(9000221)]
def test_generate(tmp_path):
"This verifies that the input and output files match."
particle2018 = tmp_path / "particle2018.csv"
particle2019 = tmp_path / "particle2019.csv"
produce_files(particle2018, particle2019, "DUMMY", "2019")
"""
# No longer test this file, which eventually will be removed
particle2018_data = data.open_text(data, "particle2018.csv")
with particle2018.open() as src, particle2018_data as res:
src = [l for l in src.readlines() if not l.startswith("#")]
res = [l for l in res.readlines() if not l.startswith("#")]
assert src == res
"""
particle2019_data = data.open_text(data, "particle2019.csv")
with particle2019.open() as src, particle2019_data as res:
src = [l for l in src.readlines() if not l.startswith("#")]
res = [l for l in res.readlines() if not l.startswith("#")]
assert src == res
def read_pdg(year, constraints):
"""Read particle masses and widths from the PDG data file of a given year."""
FlavioParticle.load_table(p_data.open_text(p_data, "particle{}.csv".format(year)))
for particle in FlavioParticle.flavio_all():
for data in (particle.flavio_m, particle.flavio_tau):
if data is None:
continue
name, tex, description, central, right, left = data
try:
# if parameter already exists, remove existing constraints on it
p = Parameter[name]
constraints.remove_constraint(name)
except KeyError:
# otherwise, create it
p = Parameter(name)
p.tex = tex
p.description = description
if right == left:
constraints.add_constraint([name],
NormalDistribution(central, right))
else:
constraints.add_constraint([name],
AsymmetricNormalDistribution(central,
right_deviation=right, left_deviation=left))
def test_explicit_table_loading():
Particle.load_table(data.open_text(data, "particle2019.csv"))
assert Particle.table_loaded() == True
assert len(Particle.table_names()) == 1
assert Particle.all() is not None
def test_file_has_latex(filename):
particle_data = data.open_text(data, filename)
p = pd.read_csv(particle_data)
assert p[p.Latex == ''].empty
def test_file_dup(filename):
particle_data = data.open_text(data, filename)
p = pd.read_csv(particle_data)
duplicates = {item for item, count in Counter(p.ID).items() if count > 1}
assert duplicates == set()
def test_file_has_latex(filename):
with data.open_text(data, filename) as particle_data:
p = pd.read_csv(particle_data, comment="#")
assert p[p.Latex == ""].empty
def test_file_dup(filename):
with data.open_text(data, filename) as particle_data:
p = pd.read_csv(particle_data, comment="#")
duplicates = {item for item, count in Counter(p.ID).items() if count > 1}
assert duplicates == set()
