Tohban EOVSA Imaging Tutorial A-Z: Difference between revisions

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=== Connection details to pipeline server ===
=== Connection details to pipeline server ===
==== Step 1: Downloading raw data (IDB) on pipeline server====
==== Step 1: Downloading raw data (IDB) on pipeline server====
On pipeline, CASA
On CASA of the Pipeline machine,  


<pre style="background-color: #FCEBD9">
<pre style="background-color: #FCEBD9">
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                                   modelms="", doscaling=False, keep_nsclms=False, udb_corr=True)
                                   modelms="", doscaling=False, keep_nsclms=False, udb_corr=True)
</pre>
</pre>


==== Step 2: Concatenate all the 10 mins data====
==== Step 2: Concatenate all the 10 mins data====

Revision as of 14:16, 6 October 2021

Connection details to pipeline server

Step 1: Downloading raw data (IDB) on pipeline server

On CASA of the Pipeline machine,

from astropy.time import Time
import os
trange = Time(['2017-08-21 20:15:00', '2017-08-21 20:25:00'])
#### (Optional) change output path, default current directory "./" #####
outpath = './msdata/'
if not os.path.exists(outpath):
    os.makedirs(outpath)
######################################################
msfiles = importeovsa(idbfiles=trange, ncpu=1[, visprefix=outpath])

OR

from suncasa.tasks import task_calibeovsa as calibeovsa
from suncasa.tasks import task_importeovsa as timporteovsa
from split_cli import split_cli as split
import dump_tsys as dt
from util import Time
import numpy as np
import os
from glob import glob
from eovsapy import util


trange = Time(['2020-06-07 21:35:00', '2020-06-07 21:55:00'])
idbdir = util.get_idbdir(trange[0])

info = dt.rd_fdb(trange[0])
sidx = np.where(
    np.logical_and(info['SOURCEID'] == 'Sun', info['PROJECTID'] == 'NormalObserving') & np.logical_and(
        info['ST_TS'].astype(np.float) >= trange[0].lv,
        info['ST_TS'].astype(np.float) <= trange[
            1].lv))
filelist = info['FILE'][sidx]

outpath = './msdata/'
if not os.path.exists(outpath):
    os.makedirs(outpath)
inpath = idbdir + '{}/'.format(trange[0].datetime.strftime("%Y%m%d"))
ncpu = 1

msfiles = timporteovsa.importeovsa(idbfiles=[inpath + ll for ll in filelist], ncpu=ncpu, timebin="0s", width=1,
                                   visprefix=outpath,
                                   nocreatms=False, doconcat=False,
                                   modelms="", doscaling=False, keep_nsclms=False, udb_corr=True)

Step 2: Concatenate all the 10 mins data

# This is to set the path/name for the concatenated files
concatvis = os.path.basename(msfiles[0])[:11] + '_concat.ms'
vis = calibeovsa(msfiles, doconcat=True, concatvis=concatvis[, msoutdir=outpath])


Step 3: Calibration

calibeovsa(vis='IDB20170821202020.ms', caltype=['refpha','phacal'], doimage=True)

Connection details to Inti server

Transferring details between servers

Software details on the servers

On Inti, when logging in for the first time, please add the following lines to your accounts .bashrc file.

>>vi .bashrc Insert the text given below and save it.

#### setting start ####
if [ $HOSTNAME == "baozi.hpcnet.campus.njit.edu" ]; then
    source /srg/.setenv_baozi
fi
if [ $HOSTNAME == "inti.hpcnet.campus.njit.edu" ]; then
    source /inti/.setenv_inti
fi
if [ $HOSTNAME == "guko.resource.campus.njit.edu" ]; then
    source /data/data/.setenv_guko
fi
#### setting end ####

Both CASA 5 and 6 are available on Inti.

Please enter the bash environment on inti, and load the desired casa environment with the alias below. To load CASA 5: Enter bash environment by giving >>bash

>> loadcasa5
>> casa  or suncasa              #This should load the software and you are ready for analysis

To load CASA 6: Enter bash environment by giving >>bash

>>loadcasa6
>>ipython                       #This should load the software and you are ready for analysis

Here, for example, to use clean, first start ipython as given above, then type in >>from casatasks import tclean

Step 4: Self-calibration on Inti server

https://github.com/binchensun/casa-eovsa/blob/master/slfcal_example.py

Step 5: Quick-look imaging

Step 6: Final imaging