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Commits (30)
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@prompt $$$s
rem convert all commandline arguments that end in .svg to .pdf files using inkscape
for %%a in (*.svg) do call :do_convert %%a
goto donext
:do_convert
set PREFIX=%~n1
echo "Converting %1 to pdf"
start /wait inkscape -z -D --file=%1 --export-pdf=%PREFIX%.pdf
rem start /wait inkscape -z -D --file=%1 --export-eps=%PREFIX%.eps
goto :eof
:donext
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=======================================================================================
This file is a guide and index to the measurement data that are used in the article
"In-situ determination of the fiber Delay Coefficient in time-dissemination networks"
=======================================================================================
Select:
50 km fiber wr_serial.py => data_180621_snd (57 measurements, 0.0967317 degrees MaxTempVariation.xlsx)
Reference setup: wr_serial.py => data_180625 (31 measurements, 0.0515712 degrees MaxTempVariation.xlsx)
analyze_sellmeier.py data_180621_snd -r data_180625 => data_180621_snd/averaged_ddelay.out
Raw data from data_180621_snd copied into data_180914 (= same data set!)
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.
fig 3: data_180914/averaged.png
Table II: data_180914/averaged_err.out
data source: ./analyze_sellmeier.py data_180914 -r data_180625 => data_180914/averaged_ddelay.out
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
time_meas_3wl, time_meas_3wl_stddev (i.e. PPS diff results)
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 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)
3wl based on section~\ref{sec:determination_using_three_lambda}
data source: data_180926/180926_15_47_01_3_lambda_insitu_alpha_scan_result.txt
calculated time_error
data source: .\ArticleErrorbarPlots\errorbarplots.py
=> time_error_result.txt
time_meas_3wl, time_meas_3wl_stddev (i.e. PPS diff results)
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
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 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:
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
......@@ -355,19 +355,21 @@ if __name__ == "__main__":
print (name + extension + ": wrong file type")
continue
"""
for data_set_key,data_set_value in data_set.items():
print("===============")
print(data_set_key) # Is one of "_l1_a", "_l2_a", "_l1_b", "_l2_b"
#print(data_set_value)
print("===============")
# For each "_l1_a", "_l2_a", "_l1_b", "_l2_b"
# get keys (for example: "ITU-Lambda1 = 18.0, ITU-Lambda2 = 21.0")
# get values (number of measurements, mean crtt value, stddev of crtt values)
for key,value in data_set_value.items():
print(key)
print(value)
"""
dbg_print = False
if dbg_print:
for data_set_key,data_set_value in data_set.items():
print("===============")
print(data_set_key) # Is one of "_l1_a", "_l2_a", "_l1_b", "_l2_b"
#print(data_set_value)
print("===============")
# For each "_l1_a", "_l2_a", "_l1_b", "_l2_b"
# get keys (for example: "ITU-Lambda1 = 18.0, ITU-Lambda2 = 21.0")
# get values (number of measurements, mean crtt value, stddev of crtt values)
for key,value in data_set_value.items():
print(key)
print(value)
l1_stddev = 3e-12 # 3 [pm]
l2_stddev = 3e-12 # 3 [pm]
fixed_lambda_stddev = 3e-12 # 3 [pm]
......
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......@@ -62,11 +62,21 @@ def save_plot(out_file, name, nameref, measurement_str, measurement_lst, outlier
meas_arr= numpy.array(measurement_lst)
mean = meas_arr.mean()
stdev = meas_arr.std(ddof=1)
# output in [ps] with one digit
mean_str = "{0:.1f}".format(mean*1e12)
stdev_str = "{0:.1f}".format(stdev*1e12)
#out_file.write("outliers: " + str(outliers) + "\n")
#out_file.write("mean: " + str(mean) + "\n")
#out_file.write("stdev: " + str(stdev) + "\n")
out_file.write(str(mean) + ", " + str(stdev) + ", " +str(outliers) + ", " +str(measurement_str_shortend) + "\n")
ScientificNotation = False
if ScientificNotation:
out_file.write(str(mean) + ", " + str(stdev) + ", " +str(outliers) + ", " +str(measurement_str_shortend) + "\n")
else:
out_file.write(mean_str + ", " + stdev_str + ", " +str(outliers) + ", " +str(measurement_str_shortend) + "\n")
fig = plt.figure("PPS_skew_fiberspool - PPS_skew_reference [ps]")
ax = fig.add_subplot(111)
......