lmtoy

LMTOY is a toolbox (a mono repository if you wish) for installing and running codes related to LMT spectral line data reduction.

LMT is a large 50m single dish radio telescope located in Mexico (18:59:09N 97:18:53W) at an altitude of 4600m, operating at mm wavelengths. See also http://lmtgtm.org/

LMT software

LMT software is very instrument specific, but LMTOY only supports a few.

• LMT heterodyne: SEQUOIA, MSIP1MM and the future OMAyA

  • LMTSLR (SpectralLineReduction)
  • dvpipe

• RSR (Redshift Search Receiver)

  • dreampy3
  • RSR_driver

• TolTEC - private - no LMTOY support

  • TolTecA
  • CitLali
  • Dash

• B4R (2mm = ALMA band 4) - no LMTOY support

  • B4R

• MUSCAT: 1mm camera (Mexico-UK) - no LMTOY support

  • 4' FOV with 5.5" resolution
  • Will use TolTecA

• CHARM ( <1mm) RAL space (Mexico-UK ) - no LMTOY support

  • 345 GHz

Installation

There are expanded notes in INSTALL.md, and also check out the Makefile for specific targets that simplify the install and updates. Probably the most automated/simple way to install (if you have all the preconditions, most importantly the cfitsio, netcdf and pgplot library) is:

  wget https://astroumd.github.io/lmtoy/install_lmtoy
  bash install_lmtoy

if this worked, activate it in your terminal/shell:

  source lmtoy/lmtoy_start.sh

Assuming you have the raw data in your $DATA_LMT tree, you can check an RSR benchmark with the following shell command

  lmtinfo.py 33551

you can proceed running the SLpipeline, again from the terminal:

  SLpipeline.sh obsnum=33551

and a Timely Analysis Products (TAP) can be viewed in the 2014ARSRCommissioning/33551 directory, or view a version we have online in https://www.astro.umd.edu/~teuben/LMT/live/2014ARSRCommissioning/33551/

The sequoia benchmark is obsnum=79448

DATA

LMT raw telescope data are (mostly) in netCDF-3 format (extension: .nc), which stores data hierarchically, name and type tagged. A typical SLR observation consists of a number of netCDF files in a specific directory hierarchy, starting at $DATA_LMT, and all identified via a 7 digit OBSNUM. Different instruments use a different number of datasets, for example, RSR uses up to 8, SLR uses 10.

Tools like ncdump display structure and contents (as CDL).

The LMTOY software will typically calibrate and convert (grid) these data to the more common FITS format.

Manual

A manual is in preparation. Here is a link of which the contents changes faster than the github source. At the bottom of the index page it lists the last built time. https://www.astro.umd.edu/~teuben/LMT/lmtoy/html

References

• pycdf
• dash or plotly dash
  • https://alpha.iodide.io/ Doing datascience in your browser
• sdfits and https://github.com/timj/aandc-gsdd
• Various related:
  • cygrid - Effelsberg group
  • HCGrid - FAST group
  • gbtgridder - GBT
  • SD gridder - Trey Wenger
  • destriper
  • sdpy - Ginsburg
  • otfmap - Rosolowsky
  • pyInterpolate - an example generic kriging method
• VO links:
  • 2019 radio hackathon - has several VO presentations and links to VO standards
  • IVOA meetings (spring 2020 onwards)
  • A precursor in [gbtoy}(https://github.com/teuben/gbtoy)