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White Rabbit Calibration
Commit 641b11a7 authored by Peter Jansweijer's avatar Peter Jansweijer
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figure fine tune for final paper submit

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sw/insitu_alpha/ReadMe.txt
View file @ 641b11a7
......@@ -14,21 +14,11 @@ Article:
Note that results slightly (a ~10e-21 effect) differ depending on using python analyze scripts under Windows or under Ubuntu!
In the article the Ubuntu results were used.
### OLD ###fig 3: data_180621_snd/averaged.png
### OLD ###fig 4: data_180621_snd/averaged_alpha.png
### OLD ###Table II: data_180621_snd/averaged_err.out
fig 3: data_180914/averaged.png
fig 4: data_180914/averaged_alpha.png
Table II: data_180914/averaged_err.out
data source: ./analyze_sellmeier.py data_180914 -r data_180625 => data_180914/averaged_ddelay.out
### OLD ###Table III: data_180621_snd/result.txt Mean: 932.89774905, StDev: 3.90038933386, StErr: 0.516619187785 however, these are
### OLD ### pure 50 KM wavelength scan measurements while data_180621_snd/averaged.png shows the 1st order fit for these
### OLD ### scans but compensated for the reference setup (directory: data_180625).
Table III, IV:
Table III:
alpha_sel(l1), alpha_stddev_sel(l1), alpha_3wl(l1), alpha_3wl_stddev(l1), time_err (i.e the calculated time error)
3wl based on section~\ref{sec:Comparing_Sellmeier_and_three_lambda}
data source: p:\App\ASTERICS_Cleopatra_WP5_1\WR_Calibration\wr-calibration\sw\insitu_alpha\data_180914\averaged_err.out
......@@ -36,7 +26,7 @@ Table III, IV:
data source ./calc_diff.py data_180926/181030_15_19_37_DeltaDelay_meas data_180926/181031_09_12_18_DeltaDelay_meas -t 400 -o data_180914_pps
data_180914_pps/190409_11_25_10_DeltaDelayDifference
Table V, VI:
Table IV:
alpha_sel(l1), alpha_stddev_sel(l1)
data source: p:\App\ASTERICS_Cleopatra_WP5_1\WR_Calibration\wr-calibration\sw\insitu_alpha\data_180914\averaged_err.out
alpha_3wl(l1), alpha_3wl_stddev(l1)
......@@ -50,18 +40,32 @@ alpha_sel(l1), alpha_stddev_sel(l1)
=> data_180914_pps/190409_11_25_10_DeltaDelayDifference
fig 5:
data source: ./analyze_sellmeier.py data_180914 -r data_180625 => data_180914/Sellmeier_fits.png
zoomed to => Sellmeier_fits_detail.png
fig 6:
data source: .\ArticleErrorbarPlots\errorbarplots.py
data source: .\ArticleErrorbarPlots\errorbarplots_Method_B_only.py
=> time_error_small_wavelenfgth_offset.png
fig 6:
fig 7:
data source: .\ArticleErrorbarPlots\errorbarplots.py
data source: .\ArticleErrorbarPlots\errorbarplots_Method_B_only.py
=> time_error_full_cband.png
Conclusions on uncertainty percentages in chapter Experimental Results (method A, method B)
p:\App\ASTERICS_Cleopatra_WP5_1\WR_Calibration\wr-calibration\sw\insitu_alpha\ArticleErrorbarPlots\fiberDelayCoefficientStdDev_versus_Mean_percentage.xlsx
Draft conclusion on Time error offset between calculated and measured values:
p:\App\ASTERICS_Cleopatra_WP5_1\WR_Calibration\wr-calibration\sw\insitu_alpha\ArticleErrorbarPlots\Table_Terr_calc_meas.xlsx
Temperature variations during method B (general long term variation in office N125)
p:\App\ASTERICS_Cleopatra_WP5_1\WR_Calibration\wr-calibration\sw\insitu_alpha\data_180928\180928_12_09_18_3_combined.xlsx
Based on Alphas: data_180621_snd/averaged_ddelay.out
Combine 50 km fiber data_180627 -r 20 and data_180629 -r 80 into data_180629_combined (100 measurements)
Combine Reference setup data_180626 -r 20 and data_180703 -r 80 into data_180703_combined (100 measurements)
Calc_diff output PPS diff results in Excell:
### OLD ###data_180703_combined/180709_12_17_22_DeltaDelayDifference.xlsx
data_180914_pps\190409_10_07_48_DeltaDelayDifference
Fiber spool CRTT temperature dependency: data_180925/180925_09_49_05_180926_09_22_12_crtt_vs_temp.xlsx
\ No newline at end of file
sw/insitu_alpha/analyze_sellmeier.py
View file @ 641b11a7
......@@ -795,7 +795,7 @@ def analyze_plot(insitu_file, analyse_single, x, y, name, tolerance, use_itu_cha
lns3 = ax.plot(x_clean, y_clean, color = 'red', label='data, outliers removed') # cleaned array in [nm]
lns=lns+lns1+lns2+lns3
lns1 = ax.plot(x_clean, ly_clean, color = 'blue', label='5-term Sellmeier fit') # final clean 5th order sellmeier fit in [nm]
#lns1 = ax.plot(x_clean, ly_clean, color = 'blue', label='5-term Sellmeier fit') # final clean 5th order sellmeier fit in [nm]
#lns2 = ax.plot(x_clean, ly_lin_clean, "-", color = 'blue', dashes=[5,5,5,5], label='linear fit') # final clean linear fit in [nm]
ax2 = ax.twinx()
......@@ -803,9 +803,10 @@ def analyze_plot(insitu_file, analyse_single, x, y, name, tolerance, use_itu_cha
# Calcualte standard deviation of data to fit error and format string
stdev_str = "{0:.3f}".format(data_vs_fit_err_clean.std(ddof=1))
lns3 = ax2.plot(x_clean, data_vs_fit_err_clean, color='grey', label='Residual\n(i.e. data vs. 5-term Sellmeier fit)\nStDev: ' + stdev_str + '[ps]')
# lns3 = ax2.plot(x_clean, data_vs_fit_err_clean, color='grey', label='Residual\n(i.e. data vs. 5-term Sellmeier fit)\nStDev: ' + stdev_str + '[ps]')
lns3 = ax2.plot(x_clean, data_vs_fit_err_clean, color='grey', label='Residual; StDev: ' + stdev_str + '[ps]')
#lns=lns+lns1+lns2+lns3
lns=lns+lns1+lns3 # Removed linear fit from legend
lns=lns+lns3 # Removed linear fit from legend
labels=[l.get_label() for l in lns]
......
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