huibintemaspampipeline
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huibintemaspampipeline [2019/02/18 11:37] – [Old hardware-correlator observations] huibintema | huibintemaspampipeline [2020/10/05 17:46] (current) – [EXPERIMENTAL: Processing uGMRT wideband data] huibintema | ||
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- | Feedback: [[huib.intema@curtin.edu.au|Click here]] | + | ==== EXPERIMENTAL: |
+ | |||
+ | SPAM has some options to process uGMRT wideband data. SPAM does not support the processing of large fractional bandwidths (df/ | ||
+ | |||
+ | The first step is to convert LTA to UVFITS format: | ||
+ | <code python> | ||
+ | lta_file_name = " | ||
+ | convert_lta_to_uvfits( lta_file_name ) | ||
+ | </ | ||
+ | Next, we split the UVFITS file into smaller frequency chunks (subbands): | ||
+ | <code python> | ||
+ | uvfits_file_name = " | ||
+ | split_wideband_uvdata( uvfits_file_name ) | ||
+ | </ | ||
+ | The width of the frequency chunks is automatically set to a sensible value. The resulting 4 or 6 UVFITS files are also located in the fits subdirectory and named " | ||
+ | |||
+ | From here, each frequency chunk is processed independently in a similar fashion as a narrow-band GMRT observations, | ||
+ | < | ||
+ | uvfits_file_name = " | ||
+ | reference_frequency = 450.e6 | ||
+ | pre_calibrate_wideband_targets( uvfits_file_name, | ||
+ | </ | ||
+ | Setting a fixed reference frequency ensures that the frequency averaging of all frequency chunks is the same, which is important when jointly imaging the SPAM output visibilities later. Sensible values seem to be: | ||
+ | < | ||
+ | reference_frequency = 450.e6 | ||
+ | reference_frequency = 650.e6 | ||
+ | </ | ||
+ | The pre-calibrated visibilities per target are located in the fits subdirectory and are named per subband. | ||
+ | |||
+ | Next comes the SPAM main pipeline run. This is best done in separate project directories per subband. If possible, use a good, single reference sky model for all runs. For example, this reference model can be obtained from first running SPAM on the narrow-band GMRT (GSB) data that was recorded alongside the uGMRT wideband data, and extracting a sky model from the final SP2B image using PyBDSF. | ||
+ | < | ||
+ | target_uvfits_file_name = " | ||
+ | UVFITS" | ||
+ | catalog_name = "< | ||
+ | catalog = read_pybdsm_ascii_catalog( catalog_name ) | ||
+ | source_list = create_source_list_from_catalog( catalog ) | ||
+ | resolution = 10. # representative resolution of model image in arcsec | ||
+ | process_wideband_target( target_uvfits_file_name, | ||
+ | </ | ||
+ | |||
+ | If all went well, each SPAM pipeline run on a subband yielded a final image and a calibrated visibility data set (.SP2B.CAL.RR.UVFITS). For use in WSClean, the calibrated visibilities all need to be collected in one directory and converted into measurement sets using CASA. Then WSClean can be used to do a final wideband imaging run. Here is an example: | ||
+ | < | ||
+ | wsclean -weight briggs 0 -pol RR -size 5000 5000 -scale 1.5asec -niter 15000 -auto-threshold 0.5 -auto-mask 3 -gain 0.25 -mgain 0.8 -weighting-rank-filter 3 -join-channels -channels-out 6 -j 8 -mem 80 -name SOURCE_UGMRT3 SOURCE_UGMRT3-01.MS SOURCE_UGMRT3-02.MS SOURCE_UGMRT3-03.MS SOURCE_UGMRT3-04.MS SOURCE_UGMRT3-05.MS SOURCE_UGMRT3-06.MS | ||
+ | </ | ||
+ | Here, SOURCE_UGMRT3-0x.MS are the input measurement sets as produced by CASA. Make sure that " | ||
+ | |||
+ | |||
+ | |||
+ | ----- | ||
+ | |||
+ | Feedback: [[intema@strw.leidenuniv.nl|Click here]] | ||
huibintemaspampipeline.txt · Last modified: 2020/10/05 17:46 by huibintema