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White Rabbit Calibration
Commit 1efd31c0 authored by Peter Jansweijer's avatar Peter Jansweijer
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added measurement result to be plotted in "fiber Delay Coefficient (alpha) as a… 

added measurement result to be plotted in "fiber Delay Coefficient (alpha) as a function of wavelength". Greek characters
parent 70ab41cc
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Showing with 114 additions and 5 deletions
sw/insitu_alpha/analyze_sellmeier.py
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......@@ -726,6 +726,7 @@ def analyze_plot(insitu_file, analyse_single, x, y, name, tolerance, use_itu_cha
ly_lin_clean=[]
alpha_tangent=[]
alpha_sellmeier=[]
alpha_stddev_sellmeier=[]
alpha_time_error=[]
#alpha_linear=[]
......@@ -758,6 +759,7 @@ def analyze_plot(insitu_file, analyse_single, x, y, name, tolerance, use_itu_cha
alpha_tangent.append(alpha_tan)
#alpha_tangent.append(calc_alpha_tangent(i/1e9, clean_y, dispersion, fixed_lambda))
alpha_sellmeier.append(alpha_sel)
alpha_stddev_sellmeier.append(alpha_stddev_sel)
#alpha_time_error.append(calc_alpha_error(alpha_sel, alpha_tan, crtt_fixed_lambda))
time_err, time_err_stddev = calc_alpha_error_stddev(alpha_sel, alpha_stddev_sel, alpha_tan, 0, crtt_fixed_lambda, l_stddev)
alpha_time_error.append(time_err)
......@@ -816,23 +818,130 @@ def analyze_plot(insitu_file, analyse_single, x, y, name, tolerance, use_itu_cha
# =====================================================
# Plot alpha as a function of wavelength
# =====================================================
lns = []
fig_alpha = plt.figure("alpha as a function of wavelength")
ax = fig_alpha.add_subplot(111)
ax.set_title("fiber Delay Coefficient (alpha) as a function of wavelength")
ax.set_title(r'fiber Delay Coefficient ($\alpha$) as a function of wavelength')
if use_itu_channels:
ax.set_xlabel('ITU Channel number')
else:
ax.set_xlabel('Wavelenth [nm]')
ax.set_ylabel('Delay Coefficient (alpha)')
ax.set_xlabel(r'$\lambda_{1}$ Wavelength [nm]')
ax.set_ylabel(r'Delay Coefficient ($\alpha$)')
#ax.set_ylabel('Alpha')
#ax.text(0.01, 0.95, 'fiber delayCoefficient (alpha) derived using', transform=ax.transAxes)
#ax.text(0.01, 0.90, 'linear and 5-term Sellmeier fit', transform=ax.transAxes)
ax.axhline(0, color='gray')
ax.axvline(fixed_lambda*1e9, color='red')
ax.plot(x_clean, alpha_sellmeier, color='green', label='dirived from 5-term Sellmeier fit')
label = ax.plot(x_clean, alpha_sellmeier, color='green', label='dirived from 5-term Sellmeier fit')
lns.append(label[0])
#ax.plot(x_clean, alpha_tangent, color='blue', dashes=[5,5,5,5], label='dirived from linear fit')
#ax.plot(x_clean, alpha_linear, color='blue', dashes=[5,5,5,5], label='linear')
ax.legend(loc='lower right', fontsize='medium')
#############################################################################################
## This piece of code plots the measured result alpha_sel(l1), alpha_stddev_sel(l1),
## alpha_3wl(l1) and alpha_3wl_stddev(l1) with error bars in the plot
#############################################################################################
AddMeasuremetResults = True
if AddMeasuremetResults:
## Small Lambda selection
l1_small_selection = [7, 7, 8, 8, 8, 9, 9, 9, 10, 10]
l2_small_selection = [8, 9, 7, 9, 10, 7, 8, 10, 8, 9] # determines color
## Full C-band selection
l1_cband_selection = [0, 0, 0, 16, 16, 16, 32, 32, 32, 49, 49, 49]
l2_cband_selection = [16, 32, 49, 0, 32, 49, 0, 16, 49, 0, 16, 32] # determines color
## concatenate both
l1_selection = l1_small_selection + l1_cband_selection
l2_selection = l2_small_selection + l2_cband_selection
### alpha_3wl(l1), alpha_3wl_stddev(l1)
### data source: p:\App\ASTERICS_Cleopatra_WP5_1\WR_Calibration\wr-calibration\sw\insitu_alpha\data_180914\averaged_err.out
small_alpha3wl_a = [6.433e-06, 6.419e-06, 3.215e-06, 3.205e-06, 3.201e-06, -3.205e-06, -3.201e-06, -3.191e-06, -6.392e-06, -6.379e-06]
small_alpha_3wl_a_stddev= [1.428e-06, 4.772e-07, 7.139e-07, 3.583e-07, 2.395e-07, 2.386e-07, 3.580e-07, 7.187e-07, 4.775e-07, 1.436e-06]
cband_alpha_3wl_a = [2.899e-05, 2.848e-05, 2.792e-05, -2.554e-05, -2.462e-05, -2.410e-05, -7.467e-05, -7.324e-05, -7.023e-05, -1.239e-04, -1.214e-04, -1.189e-04]
cband_alpha_3wl_a_stddev = [3.805e-07, 2.006e-07, 1.359e-07, 3.353e-07, 3.721e-07, 1.851e-07, 5.247e-07, 1.105e-06, 1.086e-06, 5.998e-07, 9.282e-07, 1.838e-06]
alpha_3wl_a = numpy.array(small_alpha3wl_a + cband_alpha_3wl_a)
alpha_3wl_a_stddev = numpy.array(small_alpha_3wl_a_stddev + cband_alpha_3wl_a_stddev)
selected_wavelength = []
selected_alpha_sel = []
selected_alpha_sel_stddev = []
selected_wavelength_a_0 = []
selected_alpha_3wl_a_0 = []
selected_alpha_3wl_a_0_stddev = []
selected_wavelength_a_7 = []
selected_alpha_3wl_a_7 = []
selected_alpha_3wl_a_7_stddev = []
selected_wavelength_a_8 = []
selected_alpha_3wl_a_8 = []
selected_alpha_3wl_a_8_stddev = []
selected_wavelength_a_9 = []
selected_alpha_3wl_a_9 = []
selected_alpha_3wl_a_9_stddev = []
selected_wavelength_a_10 = []
selected_alpha_3wl_a_10 = []
selected_alpha_3wl_a_10_stddev = []
selected_wavelength_a_16 = []
selected_alpha_3wl_a_16 = []
selected_alpha_3wl_a_16_stddev = []
selected_wavelength_a_32 = []
selected_alpha_3wl_a_32 = []
selected_alpha_3wl_a_32_stddev = []
selected_wavelength_a_49 = []
selected_alpha_3wl_a_49 = []
selected_alpha_3wl_a_49_stddev = []
for i in range(len(l1_selection)):
selected_wavelength.append(x_clean[l1_selection[i]])
selected_alpha_sel.append(alpha_sellmeier[l1_selection[i]])
selected_alpha_sel_stddev.append(alpha_stddev_sellmeier[l1_selection[i]])
# Select based on lambda 2 selection to determine color for plot
if l2_selection[i] == 0:
selected_wavelength_a_0.append(x_clean[l1_selection[i]])
selected_alpha_3wl_a_0.append(alpha_3wl_a[i])
selected_alpha_3wl_a_0_stddev.append(alpha_3wl_a_stddev[i])
elif l2_selection[i] == 7:
selected_wavelength_a_7.append(x_clean[l1_selection[i]])
selected_alpha_3wl_a_7.append(alpha_3wl_a[i])
selected_alpha_3wl_a_7_stddev.append(alpha_3wl_a_stddev[i])
elif l2_selection[i] == 8:
selected_wavelength_a_8.append(x_clean[l1_selection[i]])
selected_alpha_3wl_a_8.append(alpha_3wl_a[i])
selected_alpha_3wl_a_8_stddev.append(alpha_3wl_a_stddev[i])
elif l2_selection[i] == 9:
selected_wavelength_a_9.append(x_clean[l1_selection[i]])
selected_alpha_3wl_a_9.append(alpha_3wl_a[i])
selected_alpha_3wl_a_9_stddev.append(alpha_3wl_a_stddev[i])
elif l2_selection[i] == 10:
selected_wavelength_a_10.append(x_clean[l1_selection[i]])
selected_alpha_3wl_a_10.append(alpha_3wl_a[i])
selected_alpha_3wl_a_10_stddev.append(alpha_3wl_a_stddev[i])
elif l2_selection[i] == 16:
selected_wavelength_a_16.append(x_clean[l1_selection[i]])
selected_alpha_3wl_a_16.append(alpha_3wl_a[i])
selected_alpha_3wl_a_16_stddev.append(alpha_3wl_a_stddev[i])
elif l2_selection[i] == 32:
selected_wavelength_a_32.append(x_clean[l1_selection[i]])
selected_alpha_3wl_a_32.append(alpha_3wl_a[i])
selected_alpha_3wl_a_32_stddev.append(alpha_3wl_a_stddev[i])
elif l2_selection[i] == 49:
selected_wavelength_a_49.append(x_clean[l1_selection[i]])
selected_alpha_3wl_a_49.append(alpha_3wl_a[i])
selected_alpha_3wl_a_49_stddev.append(alpha_3wl_a_stddev[i])
lns.append(ax.errorbar(selected_wavelength_a_0, selected_alpha_3wl_a_0, yerr = selected_alpha_3wl_a_0_stddev, fmt='*', capsize=6, color='red', label=r'3-$\lambda$, $\lambda_{2}$ = 1568.77 [nm]'))
lns.append(ax.errorbar(selected_wavelength_a_16, selected_alpha_3wl_a_16, yerr = selected_alpha_3wl_a_16_stddev, fmt='*', capsize=6, color='blue', label=r'3-$\lambda$, $\lambda_{2}$ = 1554.94 [nm]'))
lns.append(ax.errorbar(selected_wavelength_a_32, selected_alpha_3wl_a_32, yerr = selected_alpha_3wl_a_32_stddev, fmt='*', capsize=6, color='grey', label=r'3-$\lambda$, $\lambda_{2}$ = 1542.14 [nm]'))
lns.append(ax.errorbar(selected_wavelength_a_49, selected_alpha_3wl_a_49, yerr = selected_alpha_3wl_a_49_stddev, fmt='*', capsize=6, color='cyan', label=r'3-$\lambda$, $\lambda_{2}$ = 1528.77 [nm]'))
lns.append(ax.errorbar(selected_wavelength_a_7, selected_alpha_3wl_a_7, yerr = selected_alpha_3wl_a_7_stddev, fmt='d', capsize=6, color='orange', label=r'3-$\lambda$, $\lambda_{2}$ = 1563.05 [nm]'))
lns.append(ax.errorbar(selected_wavelength_a_8, selected_alpha_3wl_a_8, yerr = selected_alpha_3wl_a_8_stddev, fmt='d', capsize=6, color='yellow', label=r'3-$\lambda$, $\lambda_{2}$ = 1562.23 [nm]'))
lns.append(ax.errorbar(selected_wavelength_a_9, selected_alpha_3wl_a_9, yerr = selected_alpha_3wl_a_9_stddev, fmt='d', capsize=6, color='brown', label=r'3-$\lambda$, $\lambda_{2}$ = 1560.61 [nm]'))
lns.append(ax.errorbar(selected_wavelength_a_10, selected_alpha_3wl_a_10, yerr = selected_alpha_3wl_a_10_stddev, fmt='d', capsize=6, color='pink', label=r'3-$\lambda$, $\lambda_{2}$ = 1559.79 [nm]'))
lns.append(ax.errorbar(selected_wavelength, selected_alpha_sel, yerr = selected_alpha_sel_stddev, fmt='*', capsize=6, color='green', label='Sellmeier'))
#############################################################################################
labels = [l.get_label() for l in lns]
ax.legend(lns, labels, loc='lower right', fontsize='medium')
#pdb.set_trace()
fig_alpha.subplots_adjust(left=0.17)
......
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