Download PACS Data Reduction Guide: Photometry - Herschel

In the Beginning is the Pipeline. Photometry
Build 13.0.5130
map = runMadMap(todproduct=tod, calTree=calTree, maxerror=<a Double>,
maxiterations=<an Integer>, runNaiveMapper=<Boolean>, useAvgInvntt=<Boolean>)
With parameters:
• tod — (class PacsTodProduct) the result of makeTodArray, MANDATORY
• calTree — Pacs calibration tree. For your information: the particular calibration file used has
the InvNtt information stored as an array of size max(n_correlation+1) x n_all_detectors. Each row
represents the InvNtt information for each detector pixel. MANDATORY.
• maxerror — Default = 1e-5, maximum relative error allowed in PCG routine (the conjugate
gradient routine, which is part of MADmap)
• maxiterations — Default = 200, maximum number of iterations in PCG routine
• runNaiveMapper — Default = false, run MadMapper; when true, run NaiveMapper (i.e. something that is similar to what you would get with the pipeline task photProject, but less accurate.
• useAvgInvntt — Default = false, use InvNtt data for each pixel; when true, use InvNtt data
averaged for all pixels in a detector
Two calls are needed if you want to produce both the MadMap and the NaiveMap simple image
products (runNaiveMapper=true yields Naivemap product and runNaivMapper=false yields MadMap
product). The NaiveMap image will be similar, but less accurate, than what is produced by the pipeline
task photProject. The output from a single run on runMadMap is:
• map — Output product consisting of following:
1. image — Sky map image (either a Naive map or MADmap) with WCS information
2. coverage — Coverage map corresponding to sky map, with WCS (units are seconds, values are
exposure time)
3. error — Uncertainty image associated with the map, with WCS
The error map is currently only made properly for NaiveMapper, although note also that error maps
do not reflect all the uncertainties in the data: this is an issue we are still working on. As this task runs
there is an intermediate output TOD file created, this is saved in a directory specified by the property
var.hcss.workdir (as mentioned before, there is not need for the user to interact with this file, it is
removed after MADmap finishes and at the exit of HIPE, but if you wish to have it saved somewhere
else, you will need to change properties via the HIPE preferences panel).
Functionality
1. Build InvNtt from input calibration tree.
Format of InvNtt chunk:
Header-LONG:
min_sample starting sample index
max_sample last sample index
n_correlation correlation width of matrix
Data-DOUBLE:
invntt(n_correlation+1)
The min/max samples are the "tos" and "froms" calculated from a method within makeTodArray.
The sample indices need to be consistent between the TOD chunked files and the InvNtt file.
2. Run MADmap module.
3. If runNaiveMapper = true run NaiveMapper module.
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