Step 5: Demodulate a calibration line
For the initialization and running the pipeline, please refer step1
Access frame cache file by specifying frame_cache and instrument as in step2
Define a frame multiplexer(mux) to write channels into a frame as in step3
- Here is an example of pipeline implementation for the demodulation part
1 demod_rate = 16 # compute_factors_sr in Hz
2 demod_filt = 20 # demodulation_filter_time in second
3 line_freq = 15 # line_freq
4 td = True # Using time-domain filter
5
6 compute_factors_sr = 1 # Output sampling rate in Hz
7 factors_averaging_time = 10 # factors_averaging_time in second
8 median_smoothing_time = 128 # median_smoothing_time in second
9
10 integ_samples = int(demod_filt) * demod_rate
11 fac_ave_samples = int(factors_averaging_time) * demod_rate
12 med_smt_samples = int(median_smoothing_time) * demod_rate
13
14 ###
15
16 cin = cp.hook_up(pipeline, demux, chan_in, instrument, buf_length)
17 cin = cp.caps_and_progress(pipeline, cin, capsf, "input")
18
19 cin_line = cp.demodulate(pipeline, cin, line_freq, td, capsz, integ_samples)
20 rline,iline = cp.split_into_real(pipeline, cin_line)
21
22 rlsq = pp.mkpow(pipeline, rline, exponent = 2)
23 ilsq = pp.mkpow(pipeline, iline, exponent = 2)
24 kapp = cp.mkadder(pipeline, cp.list_srcs(pipeline, [rlsq, queue], [ilsq, queue]))
25 kapp = pp.mkpow(pipeline, kapp, exponent = 0.5)
26
27 skp = pp.mkgeneric(pipeline, kapp, "lal_smoothkappas",\
28 default_kappa_re = 0, default_kappa_im = 0,\
29 array_size = med_smt_samples,\
30 avg_array_size = fac_ave_samples, default_to_median = 1)
31
32 skp = cp.mkresample(pipeline, skp, 0, False, capsl)
33
34 pp.mknxydumpsink(pipeline, skp, options.output)
- The python script is available at git repository
> kagra-cal/Observation/Phase1/tutorials/demod --help
Usage: demod [options]
Options:
-h, --help show this help message and exit
--cache=cache Set the name of the LAL cache listing the frame files
--gps-start-time=seconds
Set the start time of the segment to analyze in GPS
seconds.
--gps-end-time=seconds
Set the end time of the segment to analyze in GPS
seconds.
--ifo=name Name of the IFO (default= K1)
--channel=name Set input channel name (default= CAL-
CS_PROC_MICH_DELTA_TM_DQ)
--line-freq=freq Set line frequency to demodulate (default= 15)
--output=name Set output file name (default= line.txt)
--ch-rate=rate Set input channel data rate (default= 16384)
--compute-factors-sr=Hz
Sample rate at which calibration factors are computed.
(Default = 16 Hz)
--out-rate=rate Set output data rate (default= 1)
--demodulation-filter-time=sec
Length in seconds of low-pass FIR filter used in
demodulation of the calibration lines. (Default = 20
seconds)
--factors-averaging-time=sec
Time (in seconds) over which to average the smoothed
time-varying calibration factors. (Default = 10
seconds)
--median-smoothing-time=sec
Time (in seconds) to smooth out \kappas with a median-
like method. (Default = 128 s)- Here is an example to demodulate the 15Hz line at MICH_DELTA_TM channel with short demodulation, averaging and smoothing time (2 sec)
- Data in the first few seconds (depending on demodulation-filter-time) are 0
- Data for another few seconds (depending on factors-averaging-time and median-smoothing-time) should be also skipped
> kagra-cal/Observation/Phase1/tutorials/demod --cache=k1.cache --line-freq=15 --demodulation-filter-time=2 --factors-averaging-time=2 --median-smoothing-time=2 GPS: 1209288320 1209288352 channel= CAL-CS_PROC_MICH_DELTA_TM_DQ line_freq= 15.0 demod_filt= 2 factors_averaging_time= 2 median_smoothing_time= 2 seeking GPS start and stop times ... setting pipeline state to playing ... set to playing successfully running pipeline ... progress_src_input (00:00:01): 1209288352 / 32 seconds (3779026100.0 %)
- Check the contents of the output file (line.txt). The results fluctuate a lot because of the short averaging time
> head line.txt 1209288329.000000000 0 1209288330.000000000 3.560465675995634e-12 1209288331.000000000 7.646600407236563e-12 1209288332.000000000 8.539456647868739e-12 1209288333.000000000 8.575756283841539e-12 1209288334.000000000 7.98591111548684e-12 1209288335.000000000 7.453681848598155e-12 1209288336.000000000 7.295988171755139e-12 1209288337.000000000 8.008110390651456e-12 1209288338.000000000 8.639079959287761e-12
(Optional) Using frame files based on the lock flag in step 2 you can plot line amplitudes for the whole period of phase-1 run for example with MICH1_IN1 (MICH Error signal)
> kagra-cal/Observation/Phase1/tutorials/lines --dirn=demod --output=lines.png freq,aref= 15 0.20679702541 freq,aref= 51 0.156144672263 freq,aref= 94 0.0959660527234
