def plot_eff_vs_wave_meta(self):
"""plots the efficiency for a set of wavelengths,
Args:
sigma: Full sigma calculation fo the detector
ranges: Ranges calculation
blades: detector blades
result: Efficiency
figure: figure to plot in
Returns:
plotted figure
reference: figure 3.13 On Francesco's Thesis
"""
sigmalist = np.arange(0.0011, 20, 0.1)
sigmaeq = []
for sigma in sigmalist:
# transformation for meeting requirements of functions
sigma = [[sigma], ]
sigmaeq.append(B10.B10().full_sigma_calculation(sigma, self.angle))
ranges = self.calculate_ranges()
blades = self.blades
result = self.calculate_eff()
wavelength = self.wavelength
y = efftools.metadata_diffthick_vs_wave(sigmaeq, blades, ranges, len(blades))
self.metadata.update({'effVsWave': [sigmalist, y]})
print("plot_eff_vs_wave_meta")
def plot_eff_vs_wave(self):
"""plots the efficiency for a set of wavelengths,
Args:
sigma: Full sigma calculation fo the detector
ranges: Ranges calculation
blades: detector blades
result: Efficiency
figure: figure to plot in
Returns:
plotted figure
reference: figure 3.13 On Francesco's Thesis
"""
sigmalist = np.arange(0.0011, 20, 0.1)
sigmaeq = []
for sigma in sigmalist:
# transformation for meeting requirements of functions
sigma = [
[sigma],
]
sigmaeq.append(B10.B10().full_sigma_calculation(sigma, self.angle))
ranges = self.calculate_ranges()
blades = self.blades
result = self.calculate_eff()
wavelength = self.wavelength
y = efftools.metadata_diffthick_vs_wave(sigmaeq, blades, ranges,
len(blades))
cx = plt.figure(1)
plt.subplot(111)
self.metadata.update({'effVsWave': [sigmalist, y]})
plt.plot(sigmalist, np.array(y), color='g')
if len(self.wavelength) == 1:
if self.single:
plt.plot([wavelength[0][0], wavelength[0][1]],
[0, result[0][1]],
'--',
color='k')
plt.plot([0, wavelength[0][0]], [result[0][1], result[0][1]],
'--',
color='k')
else:
plt.plot([wavelength[0][0], wavelength[0][0]],
[0, np.array(result[1])],
'--',
color='k')
plt.plot([0, wavelength[0][0]],
[np.array(result[1]),
np.array(result[1])],
'--',
color='k')
plt.grid(True)
plt.xlabel(r'Neutron wavelength ($\AA$)')
plt.ylabel('Detector efficiency (%)')
# ticks = cx.get_yticks() * 100
# cx.set_yticklabels(ticks)
return cx
def plot_wave_vs_eff(self, sigmaeq, sigmalist, ranges, blades, result,
wavelength, figure):
"""plots the efficiency for a set of wavelengths,
Args:
sigma: Full sigma calculation fo the detector
ranges: Ranges calculation
blades: detector blades
result: Efficiency
figure: figure to plot in
Returns:
plotted figure
reference: figure 3.13 On Francesco's Thesis
"""
if sigmaeq == None:
sigmaeq = self.calculate_sigma()
if ranges == None:
sigmaeq = self.calculate_ranges()
if self.single:
y = efftools.metadata_singleLayer_vs_wave(sigmaeq,
blades[0].backscatter,
ranges, len(blades))
else:
y = efftools.metadata_diffthick_vs_wave(sigmaeq, blades, ranges,
len(blades))
cx = figure.add_subplot(111)
self.metadata.update({'effVsWave': [sigmalist, y]})
cx.plot(sigmalist, y, color='g')
if self.single:
cx.plot([wavelength[0][0], wavelength[0][0]], [0, result[1][0]],
'--',
color='k')
cx.plot([0, wavelength[0][0]], [result[1][0], result[1][0]],
'--',
color='k')
else:
cx.plot([wavelength[0][0], wavelength[0][0]], [0, result[1]],
'--',
color='k')
cx.plot([0, wavelength[0][0]], [result[1], result[1]],
'--',
color='k')
cx.grid(True)
cx.set_xlabel('Neutron wavelength (Angstrom)')
cx.set_ylabel('Detector efficiency (%)')
# ticks = cx.get_yticks() * 100
# cx.set_yticklabels(ticks)
return cx
