Reduce an ACSIS narrow-line science observation using advanced
algorithms REDUCE_SCIENCE_FSW
This recipe first creates a spatial cube from the raw time series data. Then, working on the raw time series data, it subtracts a median time-series signal, thresholds the data, then trims the ends of the frequency range to remove high-noise regions.
After the time-series manipulation has been done to every member of the current group, every member is run through MAKECUBE to create a group spatial cube. This cube then has its baseline removed through a smoothing process, and moments maps are created.
A baseline mask formed from the group cube is run through UNMAKECUBE to form baseline masks for the input time-series data, which are then baselined. The baselined time-series data are then run through MAKECUBE to create observation cubes, from which moments maps are created.
This recipe is suitable for ACSIS data.
The ’ nearest’ method is used for creating cubes with MAKECUBE.
A 10-pixel box smooth is used in the frequency domain. This may be too large for some narrow-line data.
" -50.0" for setting the limit to -50 km/s). " 50.0" for setting the limit to 50 km/s). " -50.0" for restricting to -50 km/s). " 100.0" for
restricting to 100 km/s). For individual time-series data: median time-series removed with the _tss suffix; thresholded data with the _thr suffix; frequency ends removed with the _em suffix; baseline-only mask with the _tsmask suffix; non-baseline regions masked with the _msk suffix; baselined data with the _bl suffix.
For individual spatial/spectral cubes: baselined cube with the _cube suffix; baseline region ma sk with the _blmask suffix.
For group cubes: cube with the _cube suffix; baseline region mask with the _blmask suffix; baselined cube with the _bl suffix;
For moments maps: integrated intensity map with the _integ suffix; velocity map with the _iwc suffix.