def test_gauss_peak():
"""
test of gauss function from xrf fit
"""
area = 1
cen = 0
std = 1
x = np.arange(-3, 3, 0.5)
out = gaussian(x, area, cen, std)
y_true = [
0.00443185,
0.0175283,
0.05399097,
0.1295176,
0.24197072,
0.35206533,
0.39894228,
0.35206533,
0.24197072,
0.1295176,
0.05399097,
0.0175283,
]
assert_array_almost_equal(y_true, out)
def test_gauss_peak():
"""
test of gauss function from xrf fit
"""
area = 1
cen = 0
std = 1
x = np.arange(-3, 3, 0.5)
out = gaussian(x, area, cen, std)
y_true = [
0.00443185, 0.0175283, 0.05399097, 0.1295176, 0.24197072, 0.35206533,
0.39894228, 0.35206533, 0.24197072, 0.1295176, 0.05399097, 0.0175283
]
assert_array_almost_equal(y_true, out)
def get_spectrum(ax, name, incident_energy, emax=15):
"""
Plot fluorescence spectrum for a given element.
Parameters
----------
name : str or int
element name, or atomic number
incident_energy : float
xray incident energy for fluorescence emission
emax : float
max value on spectrum
"""
e = XrfElement(name)
lines = e.emission_line.all
ratio = [val for val in e.cs(incident_energy).all if val[1] > 0]
x = np.arange(0, emax, 0.01)
spec = np.zeros(len(x))
i_min = 1e-6
for item in ratio:
for data in lines:
if item[0] == data[0]:
ax.plot([data[1], data[1]], [i_min, item[1]],
'g-',
linewidth=2.0)
std = 0.1
area = std * np.sqrt(2 * np.pi)
for item in ratio:
for data in lines:
if item[0] == data[0]:
spec += gaussian(x, area, data[1], std) * item[1]
#plt.semilogy(x, spec)
ax.set_title('Simulated spectrum for %s at %s eV' %
(name, incident_energy))
ax.set_xlabel('Energy [KeV]')
ax.set_ylabel('Intensity')
ax.plot(x, spec)
def get_spectrum(ax, name, incident_energy, emax=15):
"""
Plot fluorescence spectrum for a given element.
Parameters
----------
name : str or int
element name, or atomic number
incident_energy : float
xray incident energy for fluorescence emission
emax : float
max value on spectrum
"""
e = XrfElement(name)
lines = e.emission_line.all
ratio = [val for val in e.cs(incident_energy).all if val[1] > 0]
x = np.arange(0, emax, 0.01)
spec = np.zeros(len(x))
i_min = 1e-6
for item in ratio:
for data in lines:
if item[0] == data[0]:
ax.plot([data[1], data[1]],
[i_min, item[1]], 'g-', linewidth=2.0)
std = 0.1
area = std * np.sqrt(2 * np.pi)
for item in ratio:
for data in lines:
if item[0] == data[0]:
spec += gaussian(x, area, data[1], std) * item[1]
#plt.semilogy(x, spec)
ax.set_title('Simulated spectrum for %s at %s eV' % (name, incident_energy))
ax.set_xlabel('Energy [KeV]')
ax.set_ylabel('Intensity')
ax.plot(x, spec)