def test_negative_area():
r"""Test error upon negative probe area"""
with pytest.raises(ValueError):
with pytest.warns(FutureWarning):
langmuir.swept_probe_analysis(characteristic, -1 * u.cm**2,
"Ar-40 1+")
def test_nan_area():
r"""Test error upon NaN area"""
with pytest.raises(ValueError):
langmuir.swept_probe_analysis(
characteristic, np.nan * u.cm ** 2, "Ar-40 1+"
)
def test_unit_conversion_error():
r"""Test error upon incorrect probe area unit"""
with pytest.raises(u.UnitTypeError):
with pytest.warns(FutureWarning):
langmuir.swept_probe_analysis(characteristic, 1 * u.cm,
"Ar-40 1+")
def test_ion_mass_unit():
r"""Test equality of float and a.m.u. ion mass"""
sim = characteristic_simulated()
sim_result1 = swept_probe_analysis(sim, 1 * u.cm**2, 40)
sim_result2 = swept_probe_analysis(sim, 1 * u.cm**2, 40 * u.u)
errStr = (f"`swept_probe_analysis` should accept both floats and "
f"a.m.u. Quantities as atomic gas mass input.")
for key in sim_result1:
assert (sim_result1[key] == sim_result2[key]).all(), errStr
def test_ordering_invariance(bimaxwellian, characteristic_simulated):
r"""Test invariance to ordering of the bias and current values"""
sim_result = langmuir.swept_probe_analysis(characteristic_simulated,
1 * u.cm**2,
'Ar-40 1+',
bimaxwellian=bimaxwellian)
sim_result_shuffled = langmuir.swept_probe_analysis(
shuffle_characteristic(characteristic_simulated),
1 * u.cm**2,
'Ar-40 1+',
bimaxwellian=bimaxwellian)
errStr = (f"Analysis should be invariant to the ordering of the "
f"input data.")
for key in sim_result:
assert (sim_result[key] == sim_result_shuffled[key]).all(), errStr
def test_ordering_invariance(bimaxwellian, characteristic_simulated):
r"""Test invariance to ordering of the bias and current values"""
with pytest.warns(FutureWarning):
sim_result = langmuir.swept_probe_analysis(
characteristic_simulated,
1 * u.cm**2,
"Ar-40 1+",
bimaxwellian=bimaxwellian,
)
with pytest.warns(FutureWarning):
sim_result_shuffled = langmuir.swept_probe_analysis(
shuffle_characteristic(characteristic_simulated),
1 * u.cm**2,
"Ar-40 1+",
bimaxwellian=bimaxwellian,
)
errStr = "Analysis should be invariant to the ordering of the input data."
for key in sim_result:
assert (sim_result[key] == sim_result_shuffled[key]).all(), errStr
np.array(current) * 1e3 * u.mA)
# Calculate the cylindrical probe surface area
probe_length = 1.145 * u.mm
probe_diameter = 1.57 * u.mm
probe_area = (probe_length * np.pi * probe_diameter +
np.pi * 0.25 * probe_diameter**2)
######################################################
# Now we can actually perform the analysis. Since the plasma is in Helium an
# ion mass number of 4 is entered. The results are visualized and the obtained
# EEDF is also shown.
print(
swept_probe_analysis(characteristic,
probe_area,
'He-4+',
visualize=True,
plot_EEDF=True))
######################################################
# The cyan and yellow lines indicate the fitted electron and ion currents,
# respectively. The green line is the sum of these and agrees nicely with the
# data. This indicates a successful analysis.
######################################################
# The next sample probe data is provided by David Pace. It is also obtained
# from a low relatively ion temperature and density plasma, in Argon.
# Load the data from a file and create the Characteristic object
path = os.path.join("langmuir_samples", "Pace2015.npy")
bias, current = np.load(path)
np.array(current) * 1e3 * u.mA)
# Calculate the cylindrical probe surface area
probe_length = 1.145 * u.mm
probe_diameter = 1.57 * u.mm
probe_area = (probe_length * np.pi * probe_diameter +
np.pi * 0.25 * probe_diameter**2)
######################################################
# Now we can actually perform the analysis. Since the plasma is in Helium an
# ion mass number of 4 is entered. The results are visualized and the obtained
# EEDF is also shown.
print(
swept_probe_analysis(characteristic,
probe_area,
4 * u.u,
visualize=True,
plot_EEDF=True))
######################################################
# The cyan and yellow lines indicate the fitted electron and ion currents,
# respectively. The green line is the sum of these and agrees nicely with the
# data. This indicates a succesfull analysis.
######################################################
# The next sample probe data is provided by David Pace. It is also obtained
# from a low relatively ion temperature and density plasma, in Argon.
# Load the data from a file and create the Characteristic object
path = os.path.join("langmuir_samples", "Pace2015.npy")
bias, current = np.load(path)
def test_negative_area():
r"""Test error upon negative probe area"""
with pytest.raises(ValueError):
swept_probe_analysis(characteristic, -1 * u.cm**2, 40 * u.u)
def test_unit_conversion_error():
r"""Test error upon incorrect probe area unit"""
with pytest.raises(u.UnitConversionError):
swept_probe_analysis(characteristic, 1 * u.cm, 40 * u.u)
def test_nan_area():
r"""Test error upon NaN area"""
with pytest.raises(ValueError):
swept_probe_analysis(characteristic, np.nan * u.cm**2, 40 * u.u)
