jiangxuejian/jcmt_toolkit

eaosql.py

motivation: run one command to quickly search the internal database, get a info table and get a data file list for subsequent data reduction.

Examples:

python eaosql.py Uu -d 20210901

python eaosql.py Aweoweo -p M21AEC36 -m CO

python eaosql.py -h

usage: eaosql.py eaosql.py [instrument] [-p project-ID] [-d utdate] [-n obsnum] [-o object] [-m molecule]

This script generate a simple SQL file and search the JCMT database; if neither project ID nor UTdate is provided, return all entries of today if available. It also generate a txt file which lists all data file paths. For complex and advance query, please use SQL directly, or use the generated .sql file as a starting point.

positional arguments: {UU,HARP,SCUBA2,AWEOWEO} enter Uu, Aweoweo, HARP or SCUBA2 (required input)

optional arguments: -h, --help show this help message and exit -p PROJECT, --project PROJECT project code -n OBSNUM, --obsnum OBSNUM observation number -o OBJECT, --object OBJECT observing target -m MOLECULE, --molecule MOLECULE observing line -d UTDATE, --utdate UTDATE UT date in format of YYYYMMDD

Returns:

*_sql.sql

sql.tsv

filelist.lis

Polarization-separated reduction (Nāmakanui specific)

sh ./acsis_pol_sep.sh

The Nāmakanui instruments produce data from both sidebands and polarizations. It is strongly recommended by the observatory that users check the data for each polarisation separately before combining them to use the total intensity spectra. To do this, one can make use of the bad receptors mask, and run this script. One need to provide a text file (filelist.lis) containing raw data files to be reduced. Then the spectra in P0-only, P1-only and combined (as normal pipeline would produce) are under the folders p0/, p1/ and both, respectively. Note, for the receptors, N stands for Nāmakanui, the next letter is either A for Alaihi, U for ʻŪʻū or W for ʻĀweoweo. The number corresponds to polarization 0 or 1, and the final letter is L or U for Lower or Upper sideband.

Intensity ratio analysis script

(1) you may run eaosql.py (see above) to get the file list of the data you want to reduce;

(2) run acsis_pol_sep.sh to reduce the data;

(3) run extract_spec_max.sh to extract the peak intensity data as csv file(s).

(4) use the python notebook to analysis and produce figures.

The script can combine multiple standard peak intensity data files for following analysis, which explore the relationships between the peaks at LSB, USB, P0 & P1 and other parameters (LO frequency, Tsys, utdate, etc.). prerequisite: one has extracted the peak intensity data as one or multiple files (stats-max.csv) and one also the sql data files (sql.tsv)

Aweoweo daily SQL update

An automated SQL search which returns the filelist and a table. Please see Jiangxuejian/aweoweo_database

1. aweoweo_file_*.txt show the data file paths of a given date. For example:

/jcmtdata/raw/acsis/spectra/20210407/00007/a20210407_00007_01_0001.sdf

2. aweoweo_sql_*.txt show the SQL records of a given date. Available entries are:

utdate	obsnum	project	object	file_id	msbtitle	obs_sb	subsysnr	subbands	restfreq	molecule	transiti