def test_gen_xrf_spectrum_2():
r"""Failing test of ``gen_xrf_spectrum``: invalid types of parameter ``element_line_groups``"""
# 'element_groups' == None is valid
element_groups = None
spectrum_expected = np.zeros(shape=(4096, ), dtype=float)
spectrum, xx = gen_xrf_spectrum(element_groups, incident_energy=12.0)
npt.assert_array_equal(
spectrum,
spectrum_expected,
err_msg="Values in the spectrum array are not all zeros")
# Try submit a list instead of dict
with pytest.raises(
RuntimeError,
match="Parameter 'element_line_groups' has invalid type"):
gen_xrf_spectrum([1, 2, 3], incident_energy=12.0)
def test_gen_xrf_spectrum_3():
r"""Failing test of ``gen_xrf_spectrum``: unsupported emission line in the list"""
# 'Fe_L' is not supported
element_groups = {
"Fe_L": {
"area": 800
},
"Se_L": {
"area": 900
},
"W_M": {
"area": 1000
}
}
with pytest.raises(RuntimeError):
gen_xrf_spectrum(element_groups, incident_energy=12.0)
def test_gen_xrf_spectrum_1():
r"""Successful operation of ``gen_xrf_spectrum``. Some tests are empirical and don't guarantee
accurate operation of the function."""
element_groups = {
"Fe_K": {
"area": 800
},
"Se_L": {
"area": 900
},
"W_M": {
"area": 1000
}
}
total_area = sum([_["area"] for _ in element_groups.values()])
# Expected (known) number of peaks due to emission lines in the spectrum
# The number of peak is not equal to the number of emission lines (some peaks overlap)
n_peaks_expected = 5
spectrum, xx = gen_xrf_spectrum(element_groups, incident_energy=12.0)
npt.assert_almost_equal(sum(spectrum),
total_area,
err_msg="Total spectrum area is incorrect")
# Compute the number of peaks (the number of lines) using primitive algorithm
# (there is no noise in simulated data)
n_peaks = 0
for n in range(1, len(spectrum) - 1):
if (spectrum[n] > 1e-20) and (spectrum[n] == max(
spectrum[n - 1:n + 2])):
n_peaks += 1
assert n_peaks == n_peaks_expected, "The number of peaks in simulated data is incorrect"
# Test if the energy axis has correct values (for default parameters)
xx_expected = 0.01 * np.arange(4096)
npt.assert_array_almost_equal(
xx,
xx_expected,
err_msg="The returned energy axis values are incorrect")