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> kagra-cal/Observation/Phase1/tutorials/extr --cache=k1.cache.4 --channel=CALIB_AFL,CALIB_CFL,CALIB_MIN,CALIB_MOU,CALIB_C01,CALIB_C02  GPS: 1209288324 1209288348 > kagra-cal/Observation/Phase1/tutorials/extr --cache=k1.cache.4 --channel=CALIB_AFL,CALIB_CFL,CALIB_MIN,CALIB_MOU,CALIB_C01,CALIB_C02
GPS: 1209288324 1209288348

Step 8: Check the transfer function of FIR filters

  • We will check the transfer functions of the output frame files produced instep7

  • First we will merge short-duration frame files into one long-duration frame file. Please not that the last file is dropped which contains incomplete frame length.

> ls K-K1_TEST-12092883* | head -n 6 | $LAL_PREFIX/bin/lalapps_path2cache > k1.cache.4
> kagra-cal/Observation/Phase1/tutorials/extr --cache=k1.cache.4 --channel=CALIB_AFL,CALIB_CFL,CALIB_MIN,CALIB_MOU,CALIB_C01,CALIB_C02                                    
GPS:  1209288324 1209288348
[('K1', 'CALIB_AFL'), ('K1', 'CALIB_CFL'), ('K1', 'CALIB_MIN'), ('K1', 'CALIB_MOU'), ('K1', 'CALIB_C01'), ('K1', 'CALIB_C02')]
seeking GPS start and stop times ...
setting pipeline state to playing ...
set to playing successfully
running pipeline ...
progress_src_CH3 (00:00:00): 1209288348 / 24 seconds (5038701450.0 %)
progress_src_CH4 (00:00:00): 1209288348 / 24 seconds (5038701450.0 %)
progress_src_CH5 (00:00:00): 1209288348 / 24 seconds (5038701450.0 %)
progress_src_CH6 (00:00:00): 1209288348 / 24 seconds (5038701450.0 %)
progress_src_CH1 (00:00:00): 1209288348 / 24 seconds (5038701450.0 %)
progress_src_CH2 (00:00:00): 1209288348 / 24 seconds (5038701450.0 %)
progress_sink_K1 (00:00:05): 1209288324 seconds
progress_sink_K1 (00:00:05): 1209288348 / 24 seconds (5038701450.0 %)
  • Check the transfer function of Inverse sensing filter (CFL/MICH_IN)

> kagra-cal/Observation/Phase1/tutorials/trf --frame=K-TEST-1209288324-24.gwf  --channel=CALIB_CFL,CALIB_MIN --output=cfl.png
Channels: K1:CALIB_CFL K1:CALIB_MIN
  • The bode plot shows the frequency response of the inverse-sensing FIR filter, where you can see the low-frequency cutoff

Frequency response of the inverse-sensing FIR filter

  • Check the transfer function of Actuation filter (AFL/MICH_OUT)

> kagra-cal/Observation/Phase1/tutorials/trf --frame=K-TEST-1209288324-24.gwf --channel=CALIB_AFL,CALIB_MOU --output=afl.png --logy --invph
Channels: K1:CALIB_AFL K1:CALIB_MOU
  • The bode plot shows the frequency response of the actuation FIR filter, where you can see the low-frequency cutoff

Frequency response of the actuation FIR filter

  • Check the transfer function of C01(DELTA_TM+RESIDUAL) and C02(MICH_OUT*A+MICH_IN1/C)

> kagra-cal/Observation/Phase1/tutorials/trf --frame=K-TEST-1209288324-24.gwf --channel=CALIB_C02,CALIB_C01 --output=c02.png
Channels: K1:CALIB_C02 K1:CALIB_C01
  • The bode plot shows the frequency response of the two strain data (C01, C02)

Frequency response of the two strain data (C01, C02)

KAGRA/Subgroups/CAL/GstLAL/tutorials/step8 (last edited 2018-08-08 03:06:19 by SadakazuHaino)