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Building a Datacube from a CLASS File

The building of a regular grid in CLASS is done in two steps, in a similar fashion as the production of a PdBI regular grid from UV tables. The first step involves the building of a table: the spectra are written as rows in the Gildas internal data format for efficiency (command table). When creating the TABLE, the spectra are not resampled on a grid. The second step is the resampling of the non-regularly spaced spectra on a regular grid (command xy_map).

A simple example is given below where the cube is produced from a single .30m file. Default parameters are used by the xy_map command to define both the convolution kernel (1/3 of the $HPBW$) and the output grid (1/2 of the $HPBW$).

file in map       ! Open the input file
find              ! Build the index
consistency       ! Check first that the index is consistent
let name thecube  ! Use global SIC variables to define output cube name
let type lmv      ! The output cube is named ``thecube.lmv''
table 'name' new  ! Build the non-gridded table
xy_map 'name'     ! Grid the data from the table
go view           ! Check the quality of the data reduction with the VIEW tool

The following example illustrates the way to build a cube from several .30m files. This is typically the case when the map has been repeated several times and the data have been calibrated and reduced in different files.

file in map1      ! Open the input file
find              ! Build the index
consistency       ! Check first that the index is consistent
let name thecube  ! Use global SIC variables to define output cube name
let type lmv      ! 
table 'name' new  ! Build the non-gridded table as a new table
file in map2      ! Open the input file
find              ! Build the index
table 'name'      ! Append the index to the current table
file in map3      ! Open the input file
find              ! Build the index
table 'name'      ! Append the index to the current table
...
xy_map 'name'     ! Grid the data from the global table
go view           ! Check the quality of the data reduction with the VIEW tool


next up previous contents index
Next: Fitting an HyperFine Structure Up: Cookbook Previous: Exporting a spectrum to   Contents   Index
Gildas manager 2024-03-29