def time2filename(msfile, timerange='', spw=''):
from astropy.time import Time
tb.open(msfile)
starttim = Time(tb.getcell('TIME', 0) / 24. / 3600., format='mjd')
endtim = Time(tb.getcell('TIME', tb.nrows() - 1) / 24. / 3600., format='mjd')
tb.close()
datstr = starttim.iso[:10]
ms.open(msfile)
metadata = ms.metadata()
observatory = metadata.observatorynames()[0]
ms.close()
if timerange is None or timerange == '':
starttim1 = starttim
endtim1 = endtim
else:
(tstart, tend) = timerange.split('~')
if tstart[2] == ':':
starttim1 = Time(datstr + 'T' + tstart)
endtim1 = Time(datstr + 'T' + tend)
else:
starttim1 = Time(qa.quantity(tstart, 'd')['value'], format='mjd')
endtim1 = Time(qa.quantity(tend, 'd')['value'], format='mjd')
midtime = Time((starttim1.mjd + endtim1.mjd) / 2., format='mjd')
tstr = midtime.to_datetime().strftime('{}_%Y%m%dT%H%M%S'.format(observatory))
if spw:
spstr = 'spw{}'.format(spw.replace('~', '-'))
filename = '.'.join([tstr, spstr])
else:
filename = tstr
return filename
def get_trange(msfile):
from astropy.time import Time
tb.open(msfile)
tr = np.array([tb.getcell('TIME', 0),
tb.getcell('TIME',
tb.nrows() - 1)]) / 24. / 3600.
tb.close()
return Time(tr, format='mjd')
def concateovsa(msname,
msfiles,
visprefix='./',
doclearcal=True,
keep_orig_ms=False,
cols2rm=["MODEL_DATA", "CORRECTED_DATA"]):
concatvis = visprefix + msname
msfiles_ = []
for idx, ll in enumerate(msfiles):
if str(ll).endswith('/'):
msfiles[idx] = str(ll)[:-1]
if doclearcal:
print 'Warning: Corrected column in the input ms file will be cleared!!!'
for ll in msfiles:
clearcal(vis=str(ll), addmodel=True)
else:
try:
tmpdir = visprefix + '/tmp_ms/'
if not os.path.exists(tmpdir):
os.makedirs(tmpdir)
for ll in msfiles:
msfile_ = tmpdir + os.path.basename(str(ll))
msfiles_.append(msfile_)
split(vis=str(ll), outputvis=msfile_, datacolumn='corrected')
clearcal(vis=msfile_, addmodel=True)
except:
print 'Warning: Corrected column not found in the input ms file.'
msfiles_ = msfiles
if msfiles_:
concat(vis=msfiles_, concatvis=concatvis, timesort=True)
else:
concat(vis=msfiles, concatvis=concatvis, timesort=True)
# Change all observation ids to be the same (zero)
tb.open(concatvis + '/OBSERVATION', nomodify=False)
nobs = tb.nrows()
tim0 = tb.getcell('TIME_RANGE', 0)[0]
tim1 = tb.getcell('TIME_RANGE', nobs - 1)[1]
tb.removerows([i + 1 for i in range(nobs - 1)])
tb.putcell('TIME_RANGE', 0, [tim0, tim1])
tb.close()
tb.open(concatvis, nomodify=False)
obsid = tb.getcol('OBSERVATION_ID')
newobsid = np.zeros(len(obsid), dtype='int')
tb.putcol('OBSERVATION_ID', newobsid)
colnames = tb.colnames()
for l in range(len(cols2rm)):
if cols2rm[l] in colnames:
try:
tb.removecols(cols2rm[l])
except:
pass
tb.close()
if msfiles_ != [] and msfiles_ != msfiles:
for ll in msfiles_:
os.system('rm -rf {}'.format(ll))
if not keep_orig_ms:
for ll in msfiles:
os.system('rm -rf {}'.format(ll))
def verifyMS(msname,
expnumspws,
expnumchan,
inspw,
expchanfreqs=[],
ignoreflags=False):
'''Function to verify spw and channels information in an MS
msname --> name of MS to verify
expnumspws --> expected number of SPWs in the MS
expnumchan --> expected number of channels in spw
inspw --> SPW ID
expchanfreqs --> numpy array with expected channel frequencies
ignoreflags --> do not check the FLAG column
Returns a list with True or False and a state message'''
msg = ''
tb.open(msname + '/SPECTRAL_WINDOW')
nc = tb.getcell("NUM_CHAN", inspw)
nr = tb.nrows()
cf = tb.getcell("CHAN_FREQ", inspw)
tb.close()
# After channel selection/average, need to know the exact row number to check,
# ignore this check in these cases.
if not ignoreflags:
tb.open(msname)
dimdata = tb.getcell("FLAG", 0)[0].size
tb.close()
if not (nr == expnumspws):
msg = "Found " + str(nr) + ", expected " + str(
expnumspws) + " spectral windows in " + msname
return [False, msg]
if not (nc == expnumchan):
msg = "Found " + str(nc) + ", expected " + str(
expnumchan) + " channels in spw " + str(inspw) + " in " + msname
return [False, msg]
if not ignoreflags and (dimdata != expnumchan):
msg = "Found " + str(dimdata) + ", expected " + str(
expnumchan) + " channels in FLAG column in " + msname
return [False, msg]
if not (expchanfreqs == []):
print "Testing channel frequencies ..."
# print cf
# print expchanfreqs
if not (expchanfreqs.size == expnumchan):
msg = "Internal error: array of expected channel freqs should have dimension ", expnumchan
return [False, msg]
df = (cf - expchanfreqs) / expchanfreqs
if not (abs(df) < 1E-8).all:
msg = "channel frequencies in spw " + str(
inspw
) + " differ from expected values by (relative error) " + str(df)
return [False, msg]
return [True, msg]
def verifyMS(msname, expnumspws, expnumchan, inspw, expchanfreqs=[], ignoreflags=False):
'''Function to verify spw and channels information in an MS
msname --> name of MS to verify
expnumspws --> expected number of SPWs in the MS
expnumchan --> expected number of channels in spw
inspw --> SPW ID
expchanfreqs --> numpy array with expected channel frequencies
ignoreflags --> do not check the FLAG column
Returns a list with True or False and a state message'''
msg = ''
tb.open(msname+'/SPECTRAL_WINDOW')
nc = tb.getcell("NUM_CHAN", inspw)
nr = tb.nrows()
cf = tb.getcell("CHAN_FREQ", inspw)
tb.close()
# After channel selection/average, need to know the exact row number to check,
# ignore this check in these cases.
if not ignoreflags:
tb.open(msname)
dimdata = tb.getcell("FLAG", 0)[0].size
tb.close()
if not (nr==expnumspws):
msg = "Found "+str(nr)+", expected "+str(expnumspws)+" spectral windows in "+msname
return [False,msg]
if not (nc == expnumchan):
msg = "Found "+ str(nc) +", expected "+str(expnumchan)+" channels in spw "+str(inspw)+" in "+msname
return [False,msg]
if not ignoreflags and (dimdata != expnumchan):
msg = "Found "+ str(dimdata) +", expected "+str(expnumchan)+" channels in FLAG column in "+msname
return [False,msg]
if not (expchanfreqs==[]):
print "Testing channel frequencies ..."
# print cf
# print expchanfreqs
if not (expchanfreqs.size == expnumchan):
msg = "Internal error: array of expected channel freqs should have dimension ", expnumchan
return [False,msg]
df = (cf - expchanfreqs)/expchanfreqs
if not (abs(df) < 1E-8).all:
msg = "channel frequencies in spw "+str(inspw)+" differ from expected values by (relative error) "+str(df)
return [False,msg]
return [True,msg]
def splitX(vis, datacolumn2='MODEL_DATA', **kwargs):
import os
from clearcal_cli import clearcal_cli as clearcal
from split_cli import split_cli as split
'''
:param msfile:
:param datacolumn:
:param datacolumn2:
:return:
'''
kwargs2 = kwargs.copy()
datacolumn2 = datacolumn2.upper()
outmsfile = kwargs['outputvis']
if outmsfile.endswith('/'):
outmsfile = outmsfile[:-1]
if os.path.exists(outmsfile):
os.system('rm -rf {}'.format(outmsfile))
if os.path.exists('{}.flagversions'.format(outmsfile)):
os.system('rm -rf {}.flagversions'.format(outmsfile))
split(vis, **kwargs)
for k in ['datacolumn', 'outputvis']:
if k in kwargs2:
kwargs2.pop(k)
kwargs2['outputvis'] = 'tmpms.ms'
kwargs2['datacolumn'] = datacolumn2.replace('_DATA', '')
if os.path.exists('tmpms.ms'):
os.system('rm -rf tmpms.ms')
split(vis, **kwargs2)
tb.open('tmpms.ms')
nrows = tb.nrows()
data = []
for row in tqdm(range(nrows),
desc='getting {} column'.format(datacolumn2),
ascii=True):
data.append(tb.getcell('DATA', row))
tb.close()
clearcal(outmsfile, addmodel=True)
tb.open(outmsfile, nomodify=False)
for row in tqdm(range(nrows),
desc='writing {} column'.format(datacolumn2),
ascii=True):
tb.putcell(datacolumn2, row, data[row])
tb.close()
os.system('rm -rf tmpms.ms')
return outmsfile
def get_channel_freqs_widths(msname, spwid):
'''
Get frequencies and widths of all the channels for an spw ID
msname --> name of MS
spwid --> spw ID
Return two numpy arrays (frequencies, widths), each of the same length as the number of
channels'''
try:
spw_table = os.path.join(msname, 'SPECTRAL_WINDOW')
try:
tb.open(spw_table)
except RuntimeError:
print 'Cannot open table: {0}'.format(spw_table)
freqs = tb.getcell("CHAN_FREQ", spwid)
widths = tb.getcell("CHAN_WIDTH", spwid)
finally:
tb.close()
return freqs, widths
def getObservatoryName(ms):
"""
Returns the observatory name in the specified ms, using the tb tool.
-- Todd Hunter
"""
antTable = ms + '/OBSERVATION'
try:
tb.open(antTable)
myName = tb.getcell('TELESCOPE_NAME')
tb.close()
except:
print("Could not open OBSERVATION table to get the telescope name: {}".
format(antTable))
myName = ''
return (myName)
def getChannels(msname, spwid, chanlist):
'''From a list of channel indices, return their frequencies
msname --> name of MS
spwid --> spw ID
chanlist --> list of channel indices
Return a numpy array, the same size of chanlist, with the frequencies'''
try:
try:
tb.open(msname+'/SPECTRAL_WINDOW')
except:
print 'Cannot open table '+msname+'SPECTRAL_WINDOW'
cf = tb.getcell("CHAN_FREQ", spwid)
# Get only the requested channels
b = [cf[i] for i in chanlist]
selchans = np.array(b)
finally:
tb.close()
return selchans
def getChannels(msname, spwid, chanlist):
'''From a list of channel indices, return their frequencies
msname --> name of MS
spwid --> spw ID
chanlist --> list of channel indices
Return a numpy array, the same size of chanlist, with the frequencies'''
try:
try:
tb.open(msname + '/SPECTRAL_WINDOW')
except:
print 'Cannot open table ' + msname + 'SPECTRAL_WINDOW'
cf = tb.getcell("CHAN_FREQ", spwid)
# Get only the requested channels
b = [cf[i] for i in chanlist]
selchans = np.array(b)
finally:
tb.close()
return selchans
def read_horizons(t0=None,
dur=None,
vis=None,
observatory=None,
verbose=False):
import urllib2
import ssl
if not t0 and not vis:
t0 = Time.now()
if not dur:
dur = 1. / 60. / 24. # default to 2 minutes
if t0:
try:
btime = Time(t0)
except:
print('input time ' + str(t0) + ' not recognized')
return -1
if vis:
if not os.path.exists(vis):
print 'Input ms data ' + vis + ' does not exist! '
return -1
try:
# ms.open(vis)
# summary = ms.summary()
# ms.close()
# btime = Time(summary['BeginTime'], format='mjd')
# etime = Time(summary['EndTime'], format='mjd')
## alternative way to avoid conflicts with importeovsa, if needed -- more time consuming
if observatory == 'geocentric':
observatory = '500'
else:
ms.open(vis)
metadata = ms.metadata()
if metadata.observatorynames()[0] == 'EVLA':
observatory = '-5'
elif metadata.observatorynames()[0] == 'EOVSA':
observatory = '-81'
elif metadata.observatorynames()[0] == 'ALMA':
observatory = '-7'
ms.close()
tb.open(vis)
btime_vis = Time(tb.getcell('TIME', 0) / 24. / 3600., format='mjd')
etime_vis = Time(tb.getcell('TIME',
tb.nrows() - 1) / 24. / 3600.,
format='mjd')
tb.close()
if verbose:
print "Beginning time of this scan " + btime_vis.iso
print "End time of this scan " + etime_vis.iso
# extend the start and end time for jpl horizons by 0.5 hr on each end
btime = Time(btime_vis.mjd - 0.5 / 24., format='mjd')
dur = etime_vis.mjd - btime_vis.mjd + 1.0 / 24.
except:
print 'error in reading ms file: ' + vis + ' to obtain the ephemeris!'
return -1
# default the observatory to VLA, if none provided
if not observatory:
observatory = '-5'
etime = Time(btime.mjd + dur, format='mjd')
try:
cmdstr = "https://ssd.jpl.nasa.gov/horizons_batch.cgi?batch=1&TABLE_TYPE='OBSERVER'&QUANTITIES='1,17,20'&CSV_FORMAT='YES'&ANG_FORMAT='DEG'&CAL_FORMAT='BOTH'&SOLAR_ELONG='0,180'&CENTER='{}@399'&COMMAND='10'&START_TIME='".format(
observatory
) + btime.iso.replace(
' ', ','
) + "'&STOP_TIME='" + etime.iso[:-4].replace(
' ', ','
) + "'&STEP_SIZE='1m'&SKIP_DAYLT='NO'&EXTRA_PREC='YES'&APPARENT='REFRACTED'"
cmdstr = cmdstr.replace("'", "%27")
try:
context = ssl._create_unverified_context()
f = urllib2.urlopen(cmdstr, context=context)
except:
f = urllib2.urlopen(cmdstr)
lines = f.readlines()
f.close()
except:
#todo use geocentric coordinate for the new VLA data
import requests, collections
params = collections.OrderedDict()
params['batch'] = '1'
params['TABLE_TYPE'] = "'OBSERVER'"
params['QUANTITIES'] = "'1,17,20'"
params['CSV_FORMAT'] = "'YES'"
params['ANG_FORMAT'] = "'DEG'"
params['CAL_FORMAT'] = "'BOTH'"
params['SOLAR_ELONG'] = "'0,180'"
if observatory == '500':
params['CENTER'] = "'500'"
else:
params['CENTER'] = "'{}@399'".format(observatory)
params['COMMAND'] = "'10'"
params['START_TIME'] = "'{}'".format(btime.iso[:-4].replace(' ', ','))
params['STOP_TIME'] = "'{}'".format(etime.iso[:-4].replace(' ', ','))
params['STEP_SIZE'] = "'1m'"
params['SKIP_DAYLT'] = "'NO'"
params['EXTRA_PREC'] = "'YES'"
params['APPAENT'] = "'REFRACTED'"
results = requests.get("https://ssd.jpl.nasa.gov/horizons_batch.cgi",
params=params)
lines = [ll for ll in results.iter_lines()]
nline = len(lines)
istart = 0
for i in range(nline):
line = lines[i]
if line[0:5] == '$$SOE': # start recording
istart = i + 1
if line[0:5] == '$$EOE': # end recording
iend = i
newlines = lines[istart:iend]
nrec = len(newlines)
ephem_ = []
t = []
ra = []
dec = []
p0 = []
delta = []
for line in newlines:
items = line.split(',')
t.append(Time(float(items[1]), format='jd').mjd)
ra.append(np.radians(float(items[4])))
dec.append(np.radians(float(items[5])))
p0.append(float(items[6]))
delta.append(float(items[8]))
# convert list of dictionary to a dictionary of arrays
ephem = {'time': t, 'ra': ra, 'dec': dec, 'p0': p0, 'delta': delta}
return ephem
def compVarColTables(referencetab, testtab, varcol, tolerance=0.):
'''Compare a variable column of two tables.
referencetab --> a reference table
testtab --> a table to verify
varcol --> the name of a variable column (str)
Returns True or False.
'''
retval = True
tb2 = casac.table()
tb.open(referencetab)
cnames = tb.colnames()
tb2.open(testtab)
col = varcol
if tb.isvarcol(col) and tb2.isvarcol(col):
try:
# First check
if tb.nrows() != tb2.nrows():
print 'Length of %s differ from %s, %s!=%s' % (
referencetab, testtab, len(rk), len(tk))
retval = False
else:
for therow in xrange(tb.nrows()):
rdata = tb.getcell(col, therow)
tdata = tb2.getcell(col, therow)
# if not (rdata==tdata).all():
if not rdata.all() == tdata.all():
if (tolerance > 0.):
differs = False
for j in range(0, len(rdata)):
### if (type(rdata[j])==float or type(rdata[j])==int):
if ((isinstance(rdata[j], float))
or (isinstance(rdata[j], int))):
if (abs(rdata[j] - tdata[j]) > tolerance *
abs(rdata[j] + tdata[j])):
# print 'Column ', col,' differs in tables ', referencetab, ' and ', testtab
# print therow, j
# print rdata[j]
# print tdata[j]
differs = True
### elif (type(rdata[j])==list or type(rdata[j])==np.ndarray):
elif (isinstance(rdata[j],
list)) or (isinstance(
rdata[j], np.ndarray)):
for k in range(0, len(rdata[j])):
if (abs(rdata[j][k] - tdata[j][k]) >
tolerance * abs(rdata[j][k] +
tdata[j][k])):
# print 'Column ', col,' differs in tables ', referencetab, ' and ', testtab
# print therow, j, k
# print rdata[j][k]
# print tdata[j][k]
differs = True
if differs:
print 'ERROR: Column %s of %s and %s do not agree within tolerance %s' % (
col, referencetab, testtab, tolerance)
retval = False
break
else:
print 'ERROR: Column %s of %s and %s do not agree.' % (
col, referencetab, testtab)
print 'ERROR: First row to differ is row=%s' % therow
retval = False
break
finally:
tb.close()
tb2.close()
else:
print 'Columns are not varcolumns.'
retval = False
if retval:
print 'Column %s of %s and %s agree' % (col, referencetab, testtab)
return retval
def get_dspec(vis=None, savespec=True, specfile=None, bl='', uvrange='', field='', scan='', datacolumn='data',
domedian=False, timeran=None, spw=None, timebin='0s', regridfreq=False, fillnan=None, verbose=False):
# from split_cli import split_cli as split
if vis.endswith('/'):
vis = vis[:-1]
msfile = vis
if not spw:
spw = ''
if not timeran:
timeran = ''
if not bl:
bl = ''
if domedian:
if not uvrange:
uvrange = '0.2~0.8km'
bl = ''
else:
uvrange = ''
# Open the ms and plot dynamic spectrum
if verbose:
print('Splitting selected data...')
vis_spl = './tmpms.splitted'
if os.path.exists(vis_spl):
os.system('rm -rf ' + vis_spl)
# split(vis=msfile, outputvis=vis_spl, timerange=timeran, antenna=bl, field=field, scan=scan, spw=spw,
# uvrange=uvrange, timebin=timebin, datacolumn=datacolumn)
ms.open(msfile, nomodify=False)
ms.split(outputms=vis_spl, whichcol=datacolumn, time=timeran, spw=spw, baseline=bl, field=field, scan=scan,
uvrange=uvrange, timebin=timebin)
ms.close()
if verbose:
print('Regridding into a single spectral window...')
# print('Reading data spw by spw')
try:
tb.open(vis_spl + '/POLARIZATION')
corrtype = tb.getcell('CORR_TYPE', 0)
pols = [stokesenum[p] for p in corrtype]
tb.close()
except:
pols = []
if regridfreq:
ms.open(vis_spl, nomodify=False)
ms.cvel(outframe='LSRK', mode='frequency', interp='nearest')
ms.selectinit(datadescid=0, reset=True)
data = ms.getdata(['amplitude', 'time', 'axis_info'], ifraxis=True)
specamp = data['amplitude']
freq = data['axis_info']['freq_axis']['chan_freq']
else:
ms.open(vis_spl)
ms.selectinit(datadescid=0, reset=True)
spwinfo = ms.getspectralwindowinfo()
specamp = []
freq = []
time = []
for descid in range(len(spwinfo.keys())):
ms.selectinit(datadescid=0, reset=True)
ms.selectinit(datadescid=descid)
data = ms.getdata(['amplitude', 'time', 'axis_info'], ifraxis=True)
specamp_ = data['amplitude']
freq_ = data['axis_info']['freq_axis']['chan_freq']
time_ = data['time']
if fillnan is not None:
flag_ = ms.getdata(['flag', 'time', 'axis_info'], ifraxis=True)['flag']
if type(fillnan) in [int, float, long]:
specamp_[flag_] = float(fillnan)
else:
specamp_[flag_] = 0.0
specamp.append(specamp_)
freq.append(freq_)
time.append(time_)
specamp = np.concatenate(specamp, axis=1)
freq = np.concatenate(freq, axis=0)
ms.selectinit(datadescid=0, reset=True)
ms.close()
os.system('rm -rf ' + vis_spl)
(npol, nfreq, nbl, ntim) = specamp.shape
freq = freq.reshape(nfreq)
if verbose:
print('npol, nfreq, nbl, ntime:', (npol, nfreq, nbl, ntim))
spec = np.swapaxes(specamp, 2, 1)
tim = data['time']
if domedian:
if verbose:
print('doing median of all the baselines')
# mask zero values before median
spec_masked = np.ma.masked_where(spec < 1e-9, spec)
spec_med = np.ma.filled(np.ma.median(spec_masked, axis=1), fill_value=0.)
nbl = 1
ospec = spec_med.reshape((npol, nbl, nfreq, ntim))
else:
ospec = spec
# Save the dynamic spectral data
if savespec:
if not specfile:
specfile = msfile + '.dspec.npz'
if os.path.exists(specfile):
os.system('rm -rf ' + specfile)
np.savez(specfile, spec=ospec, tim=tim, freq=freq,
timeran=timeran, spw=spw, bl=bl, uvrange=uvrange, pol=pols)
if verbose:
print('Median dynamic spectrum saved as: ' + specfile)
return {'spec': ospec, 'tim': tim, 'freq': freq, 'timeran': timeran, 'spw': spw, 'bl': bl, 'uvrange': uvrange,
'pol': pols}
visa.append(
'/srg/ywei/data/eovsa/sep6_dofinal/slfcal/IDB20170906T190319-195320.ms.corrected.xx.slfcal'
)
visa.append(
'/srg/ywei/data/eovsa/sep6_dofinal/slfcal/IDB20170906T190319-195320.ms.corrected.xx.slfcal0'
)
visa.append(
'/srg/ywei/data/eovsa/sep6_dofinal/slfcal/IDB20170906T190319-195320.ms.corrected.xx.slfcal01'
)
visa.append(
'/srg/ywei/data/eovsa/sep6_dofinal/slfcal/IDB20170906T190319-195320.ms.corrected.xx.slfcaled'
)
tb.open(
'/srg/ywei/data/eovsa/sep6_dofinal/slfcal/IDB20170906T190319-195320.ms.corrected.xx.slfcal'
)
starttim = Time(tb.getcell('TIME', 0) / 24. / 3600., format='mjd')
endtim = Time(tb.getcell('TIME', tb.nrows() - 1) / 24. / 3600., format='mjd')
tb.close()
trange = '{0}~{1}'.format(
starttim.iso.replace('-', '/').replace(' ', '/'),
endtim.iso.replace('-', '/').replace(' ', '/'))
workdir = '/srg/ywei/data/eovsa/sep6_dofinal'
for index in range(4):
imgprefix = workdir + '/slfcal/images/' + str(index) + 'testing_slf_192920'
img_final = imgprefix + '_final'
spws = [str(s + 1) for s in range(30)]
slfcaledms = visa[index]
tb.open(slfcaledms + '/SPECTRAL_WINDOW')
reffreqs = tb.getcol('REF_FREQUENCY')
bdwds = tb.getcol('TOTAL_BANDWIDTH')
cfreqs = reffreqs + bdwds / 2.
def mk_qlook_image(trange,
doimport=False,
docalib=False,
ncpu=10,
twidth=12,
stokes=None,
antenna='0~12',
lowcutoff_freq=3.7,
imagedir=None,
spws=['1~5', '6~10', '11~15', '16~25'],
toTb=True,
overwrite=True,
doslfcal=False,
verbose=False):
'''
trange: can be 1) a single Time() object: use the entire day
2) a range of Time(), e.g., Time(['2017-08-01 00:00','2017-08-01 23:00'])
3) a single or a list of UDBms file(s)
4) None -- use current date Time.now()
'''
antenna0 = antenna
if type(trange) == Time:
mslist = trange2ms(trange=trange, doimport=doimport)
vis = mslist['ms']
tsts = [l.to_datetime() for l in mslist['tstlist']]
if type(trange) == str:
try:
date = Time(trange)
mslist = trange2ms(trange=trange, doimport=doimport)
vis = mslist['ms']
tsts = [l.to_datetime() for l in mslist['tstlist']]
except:
vis = [trange]
tsts = []
for v in vis:
tb.open(v + '/OBSERVATION')
tsts.append(
Time(tb.getcell('TIME_RANGE')[0] / 24 / 3600,
format='mjd').datetime)
tb.close()
subdir = [tst.strftime("%Y/%m/%d/") for tst in tsts]
for idx, f in enumerate(vis):
if f[-1] == '/':
vis[idx] = f[:-1]
if not stokes:
stokes = 'XX'
if not imagedir:
imagedir = './'
imres = {
'Succeeded': [],
'BeginTime': [],
'EndTime': [],
'ImageName': [],
'Spw': [],
'Vis': [],
'Synoptic': {
'Succeeded': [],
'BeginTime': [],
'EndTime': [],
'ImageName': [],
'Spw': [],
'Vis': []
}
}
for n, msfile in enumerate(vis):
msfilebs = os.path.basename(msfile)
imdir = imagedir + subdir[n]
if not os.path.exists(imdir):
os.makedirs(imdir)
if doslfcal:
slfcalms = './' + msfilebs + '.xx'
split(msfile,
outputvis=slfcalms,
datacolumn='corrected',
correlation='XX')
cfreqs = getspwfreq(msfile)
for spw in spws:
antenna = antenna0
if spw == '':
continue
spwran = [s.zfill(2) for s in spw.split('~')]
freqran = [cfreqs[int(s)] for s in spw.split('~')]
cfreq = np.mean(freqran)
bmsz = max(150. / cfreq, 20.)
uvrange = '<10klambda'
if doslfcal:
slfcal_img = './' + msfilebs + '.slf.spw' + spw.replace(
'~', '-') + '.slfimg'
slfcal_tb = './' + msfilebs + '.slf.spw' + spw.replace(
'~', '-') + '.slftb'
try:
clean(vis=slfcalms,
antenna=antenna,
imagename=slfcal_img,
spw=spw,
mode='mfs',
timerange='',
imagermode='csclean',
psfmode='clark',
imsize=[512, 512],
cell=['5arcsec'],
niter=100,
gain=0.05,
stokes='I',
weighting='natural',
restoringbeam=[str(bmsz) + 'arcsec'],
pbcor=False,
interactive=False,
usescratch=True)
except:
print('error in cleaning spw: ' + spw)
break
gaincal(vis=slfcalms,
refant='0',
antenna=antenna,
caltable=slfcal_tb,
spw=spw,
uvrange='',
gaintable=[],
selectdata=True,
timerange='',
solint='600s',
gaintype='G',
calmode='p',
combine='',
minblperant=3,
minsnr=2,
append=False)
if not os.path.exists(slfcal_tb):
print('No solution found in spw: ' + spw)
break
else:
clearcal(slfcalms)
delmod(slfcalms)
applycal(vis=slfcalms,
gaintable=[slfcal_tb],
spw=spw,
selectdata=True,
antenna=antenna,
interp='nearest',
flagbackup=False,
applymode='calonly',
calwt=False)
msfile = slfcalms
imsize = 512
cell = ['5arcsec']
if len(spwran) == 2:
spwstr = spwran[0] + '~' + spwran[1]
else:
spwstr = spwran[0]
restoringbeam = ['{0:.1f}arcsec'.format(bmsz)]
imagesuffix = '.spw' + spwstr.replace('~', '-')
if cfreq > 10.:
antenna = antenna + ';!0&1;!0&2' # deselect the shortest baselines
# else:
# antenna = antenna + ';!0&1' # deselect the shortest baselines
res = ptclean3(vis=msfile,
imageprefix=imdir,
imagesuffix=imagesuffix,
twidth=twidth,
uvrange=uvrange,
spw=spw,
ncpu=ncpu,
niter=1000,
gain=0.05,
antenna=antenna,
imsize=imsize,
cell=cell,
stokes=stokes,
doreg=True,
usephacenter=False,
overwrite=overwrite,
toTb=toTb,
restoringbeam=restoringbeam,
specmode="mfs",
deconvolver="hogbom",
datacolumn='data',
pbcor=True)
if res:
imres['Succeeded'] += res['Succeeded']
imres['BeginTime'] += res['BeginTime']
imres['EndTime'] += res['EndTime']
imres['ImageName'] += res['ImageName']
imres['Spw'] += [spwstr] * len(res['ImageName'])
imres['Vis'] += [msfile] * len(res['ImageName'])
else:
continue
if len(vis) == 1:
# produce the band-by-band whole-day images
ms.open(msfile)
ms.selectinit()
timfreq = ms.getdata(['time', 'axis_info'], ifraxis=True)
tim = timfreq['time']
ms.close()
cfreqs = getspwfreq(msfile)
imdir = imagedir + subdir[0]
if not os.path.exists(imdir):
os.makedirs(imdir)
for spw in spws:
antenna = antenna0
if spw == '':
spw = '{:d}~{:d}'.format(
next(x[0] for x in enumerate(cfreqs)
if x[1] > lowcutoff_freq),
len(cfreqs) - 1)
spwran = [s.zfill(2) for s in spw.split('~')]
freqran = [cfreqs[int(s)] for s in spw.split('~')]
cfreq = np.mean(freqran)
bmsz = max(150. / cfreq, 20.)
uvrange = ''
imsize = 512
cell = ['5arcsec']
if len(spwran) == 2:
spwstr = spwran[0] + '~' + spwran[1]
else:
spwstr = spwran[0]
restoringbeam = ['{0:.1f}arcsec'.format(bmsz)]
imagesuffix = '.synoptic.spw' + spwstr.replace('~', '-')
antenna = antenna + ';!0&1' # deselect the shortest baselines
res = ptclean3(vis=msfile,
imageprefix=imdir,
imagesuffix=imagesuffix,
twidth=len(tim),
uvrange=uvrange,
spw=spw,
ncpu=1,
niter=0,
gain=0.05,
antenna=antenna,
imsize=imsize,
cell=cell,
stokes=stokes,
doreg=True,
usephacenter=False,
overwrite=overwrite,
toTb=toTb,
restoringbeam=restoringbeam,
specmode="mfs",
deconvolver="hogbom",
datacolumn='data',
pbcor=True)
if res:
imres['Synoptic']['Succeeded'] += res['Succeeded']
imres['Synoptic']['BeginTime'] += res['BeginTime']
imres['Synoptic']['EndTime'] += res['EndTime']
imres['Synoptic']['ImageName'] += res['ImageName']
imres['Synoptic']['Spw'] += [spwstr] * len(res['ImageName'])
imres['Synoptic']['Vis'] += [msfile] * len(res['ImageName'])
else:
continue
# save it for debugging purposes
np.savez('imres.npz', imres=imres)
return imres
def WEI_plot(dofile=True,
vis=None,
timerange=None,
spw='',
aiafits='',
imagehead='',
workdir='',
spwCol=3,
phasecenter='J2000 11h00m48 06d14m60'):
if vis[-1] == '/':
vis = vis[:-1]
ms.open(vis)
spwInfo = ms.getspectralwindowinfo()
ms.close()
tb.open(vis)
starttim = Time(tb.getcell('TIME', 0) / 24. / 3600., format='mjd')
endtim = Time(tb.getcell('TIME',
tb.nrows() - 1) / 24. / 3600.,
format='mjd')
tb.close()
tb.open(vis + '/SPECTRAL_WINDOW')
reffreqs = tb.getcol('REF_FREQUENCY')
bdwds = tb.getcol('TOTAL_BANDWIDTH')
cfreqs = reffreqs + bdwds / 2.
tb.close()
sbeam = 35.
#get timerange from vis file
if not timerange:
timerange = '{0}~{1}'.format(
starttim.iso.replace('-', '/').replace(' ', '/'),
endtim.iso.replace('-', '/').replace(' ', '/'))
nspw = len(spwInfo)
#draw plot aia
fig = plt.figure(figsize=(12, 7), dpi=100)
gs1 = gridspec.GridSpec(4, 3)
gs1.update(left=0.08, right=0.32, wspace=0.05)
ax1 = plt.subplot(gs1[11])
aiamap = smap.Map(aiafits)
aiamap.plot(axes=ax1)
#do clean spwCol by spwCol
for cur_spwCol in range(0, np.floor_divide(nspw, spwCol)):
if ((cur_spwCol + 1) * spwCol) < nspw:
cur_spwRange = str(cur_spwCol * spwCol + 1) + '~' + str(
(cur_spwCol + 1) * spwCol)
else:
cur_spwRange = str(cur_spwCol * spwCol + 1) + '~' + '31'
imagename = imagehead + cur_spwRange + 'SPWs'
cur_eovsaFits = imagename + '.fits'
if cur_spwCol < 6:
cur_mask = '/srg/ywei/data/eovsa/mask/sep_6mask_' + str(
cur_spwCol + 1) + '.rgn'
else:
cur_mask = '/srg/ywei/data/eovsa/mask/sep_6/mask_6.rgn'
if dofile:
#clean(vis=vis, spw=cur_spwRange, timerange=timerange, imagename=imagename, imsize=[256,256], niter=100, cell=['2arcsec'] )
#clean(vis=vis, spw=cur_spwRange, timerange=timerange, imagename=imagename, imsize=[512,512], niter=1000, cell=['1arcsec'],stokes='XX', gain=0.05,weighting='briggs', mode='mfs',imagermode='csclean',psfmode='clark',robust=0.0,restoringbeam = ['10.0arcsec'], mask=cur_mask,pbcor=True)
clean(vis=vis,
spw=cur_spwRange,
timerange=timerange,
imagename=imagename,
imsize=[512, 512],
niter=1000,
cell=['1arcsec'],
stokes='XX',
gain=0.05,
weighting='briggs',
mode='mfs',
imagermode='csclean',
psfmode='clark',
robust=0.0,
restoringbeam=['10.0arcsec'],
mask='',
pbcor=True)
print 'fits name =' + str(cur_eovsaFits)
hf.imreg(vis=vis,
imagefile=imagename + '.image',
fitsfile=imagename + '.fits',
timerange=timerange)
#plot eovsa
cur_emap = smap.Map(cur_eovsaFits)
cur_axname = plt.subplot(gs1[cur_spwCol + 1])
(npol, nf, nx, ny) = cur_emap.data.shape
print 'shape = ' + str(cur_emap.data.shape)
if npol != 1:
print 'To be determined'
else:
cur_emap.data = cur_emap.data.reshape((512, 512))
cur_emap.plot_settings['cmap'] = plt.get_cmap('jet')
cur_emap.plot(axes=cur_axname)
def make_ephem(vis, ephemfile=None):
import urllib2, ssl
from taskinit import tb
quantities = ['1', '14', '15', '17', '19', '20', '24', '32']
quantities = ','.join(quantities)
tb.open(vis)
btime = Time(tb.getcell('TIME', 0) / 24. / 3600., format='mjd')
etime = Time(tb.getcell('TIME',
tb.nrows() - 1) / 24. / 3600.,
format='mjd')
tb.close()
print "Beginning time of this scan " + btime.iso
print "End time of this scan " + etime.iso
btime = Time((btime.mjd - 1.0 / 60. / 24.), format='mjd')
etime = Time((etime.mjd + 1.0 / 60. / 24.), format='mjd')
startdate = btime.iso.replace(' ', ',')[:-7]
enddate = etime.iso.replace(' ', ',')[:-7]
cmd = [
"COMMAND= '10'", "CENTER= '-5@399'", "MAKE_EPHEM= 'YES'",
"TABLE_TYPE= 'OBSERVER'",
"START_TIME= '%s'" % startdate,
"STOP_TIME= '%s'" % enddate, "STEP_SIZE= '1m'", "CAL_FORMAT= 'CAL'",
"TIME_DIGITS= 'MINUTES'", "ANG_FORMAT= 'DEG'", "OUT_UNITS= 'KM-S'",
"RANGE_UNITS= 'AU'", "APPARENT= 'AIRLESS'", "SOLAR_ELONG= '0,180'",
"SUPPRESS_RANGE_RATE= 'NO'", "SKIP_DAYLT= 'NO'", "EXTRA_PREC= 'NO'",
"R_T_S_ONLY= 'NO'", "REF_SYSTEM= 'J2000'", "CSV_FORMAT= 'YES'",
"OBJ_DATA= 'YES'", "TIME_DIGITS ='MIN'",
"QUANTITIES= '{}'".format(quantities)
]
cmdstr = "http://ssd.jpl.nasa.gov/horizons_batch.cgi?batch=l&" + '&'.join(
cmd)
try:
context = ssl._create_unverified_context()
f = urllib2.urlopen(cmdstr, context=context)
except:
f = urllib2.urlopen(cmdstr)
lines = f.readlines()
f.close()
istart = 0
for i, l in enumerate(lines):
if l[0:5] == '$$SOE': # start recording
istart = i + 1
if l[0:5] == '$$EOE': # end recording
iend = i
if not ephemfile:
ephemfile = 'sun-ephem-geo.txt'
with open(ephemfile, 'w') as fb:
for i, l in enumerate(lines):
if i == istart - 3:
fb.write(
' Date__(UT)__HR:MN R.A.___(J2000.0)___DEC. Ob-lon Ob-lat Sl-lon Sl-lat NP.ang NP.dist r rdot delta deldot S-T-O'
)
if i >= istart and i < iend:
l_s = l.split(',')
l_s.pop(1)
l_s.pop(1)
fb.write(' '.join(l_s))
else:
fb.write(l)
def calc_phasecenter_from_solxy(vis,
timerange='',
xycen=None,
usemsphacenter=True):
'''
return the phase center in RA and DEC of a given solar coordinates
:param vis: input measurement sets file
:param timerange: can be a string or astropy.time.core.Time object, or a 2-element list of string or Time object
:param xycen: solar x-pos and y-pos in arcsec
:param usemsphacenter:
:return:
phasecenter
midtim: mid time of the given timerange
'''
tb.open(vis + '/POINTING')
tst = Time(tb.getcell('TIME_ORIGIN', 0) / 24. / 3600., format='mjd')
ted = Time(tb.getcell('TIME_ORIGIN',
tb.nrows() - 1) / 24. / 3600.,
format='mjd')
tb.close()
datstr = tst.iso[:10]
if isinstance(timerange, Time):
try:
(sttim, edtim) = timerange
except:
sttim = timerange
edtim = sttim
else:
if timerange == '':
sttim = tst
edtim = ted
else:
try:
(tstart, tend) = timerange.split('~')
if tstart[2] == ':':
sttim = Time(datstr + 'T' + tstart)
edtim = Time(datstr + 'T' + tend)
# timerange = '{0}/{1}~{0}/{2}'.format(datstr.replace('-', '/'), tstart, tend)
else:
sttim = Time(qa.quantity(tstart, 'd')['value'],
format='mjd')
edtim = Time(qa.quantity(tend, 'd')['value'], format='mjd')
except:
try:
if timerange[2] == ':':
sttim = Time(datstr + 'T' + timerange)
edtim = sttim
else:
sttim = Time(qa.quantity(timerange, 'd')['value'],
format='mjd')
edtim = sttim
except ValueError:
print("keyword 'timerange' in wrong format")
ms.open(vis)
metadata = ms.metadata()
observatory = metadata.observatorynames()[0]
ms.close()
midtim_mjd = (sttim.mjd + edtim.mjd) / 2.
midtim = Time(midtim_mjd, format='mjd')
eph = read_horizons(t0=midtim)
if observatory == 'EOVSA' or (not usemsphacenter):
print('This is EOVSA data')
# use RA and DEC from FIELD ID 0
tb.open(vis + '/FIELD')
phadir = tb.getcol('PHASE_DIR').flatten()
tb.close()
ra0 = phadir[0]
dec0 = phadir[1]
else:
ra0 = eph['ra'][0]
dec0 = eph['dec'][0]
if not xycen:
# use solar disk center as default
phasecenter = 'J2000 ' + str(ra0) + 'rad ' + str(dec0) + 'rad'
else:
x0 = np.radians(xycen[0] / 3600.)
y0 = np.radians(xycen[1] / 3600.)
p0 = np.radians(eph['p0'][0]) # p angle in radians
raoff = -((x0) * np.cos(p0) - y0 * np.sin(p0)) / np.cos(eph['dec'][0])
decoff = (x0) * np.sin(p0) + y0 * np.cos(p0)
newra = ra0 + raoff
newdec = dec0 + decoff
phasecenter = 'J2000 ' + str(newra) + 'rad ' + str(newdec) + 'rad'
return phasecenter, midtim
def read_horizons(t0=None,
dur=None,
vis=None,
observatory=None,
verbose=False):
'''
This function visits JPL Horizons to retrieve J2000 topocentric RA and DEC of the solar disk center
as a function of time.
Keyword arguments:
t0: Referece time in astropy.Time format
dur: duration of the returned coordinates. Default to 2 minutes
vis: CASA visibility dataset (in measurement set format). If provided, use entire duration from
the visibility data
observatory: observatory code (from JPL Horizons). If not provided, use information from visibility.
if no visibility found, use earth center (code=500)
verbose: True to provide extra information
Usage:
>>> from astropy.time import Time
>>> out = read_horizons(t0=Time('2017-09-10 16:00:00'), observatory='-81')
>>> out = read_horizons(vis = 'mydata.ms')
History:
BC (sometime in 2014): function was first wrote, followed by a number of edits by BC and SY
BC (2019-07-16): Added docstring documentation
'''
try:
# For Python 3.0 and later
from urllib.request import urlopen
except ImportError:
# Fall back to Python 2's urllib2
from urllib2 import urlopen
import ssl
if not t0 and not vis:
t0 = Time.now()
if not dur:
dur = 1. / 60. / 24. # default to 2 minutes
if t0:
try:
btime = Time(t0)
except:
print('input time ' + str(t0) + ' not recognized')
return -1
if vis:
if not os.path.exists(vis):
print('Input ms data ' + vis + ' does not exist! ')
return -1
try:
# ms.open(vis)
# summary = ms.summary()
# ms.close()
# btime = Time(summary['BeginTime'], format='mjd')
# etime = Time(summary['EndTime'], format='mjd')
## alternative way to avoid conflicts with importeovsa, if needed -- more time consuming
if observatory == 'geocentric':
observatory = '500'
else:
ms.open(vis)
metadata = ms.metadata()
if metadata.observatorynames()[0] == 'EVLA':
observatory = '-5'
elif metadata.observatorynames()[0] == 'EOVSA':
observatory = '-81'
elif metadata.observatorynames()[0] == 'ALMA':
observatory = '-7'
ms.close()
tb.open(vis)
btime_vis = Time(tb.getcell('TIME', 0) / 24. / 3600., format='mjd')
etime_vis = Time(tb.getcell('TIME',
tb.nrows() - 1) / 24. / 3600.,
format='mjd')
tb.close()
if verbose:
print("Beginning time of this scan " + btime_vis.iso)
print("End time of this scan " + etime_vis.iso)
# extend the start and end time for jpl horizons by 0.5 hr on each end
btime = Time(btime_vis.mjd - 0.5 / 24., format='mjd')
dur = etime_vis.mjd - btime_vis.mjd + 1.0 / 24.
except:
print('error in reading ms file: ' + vis +
' to obtain the ephemeris!')
return -1
# default the observatory to geocentric, if none provided
if not observatory:
observatory = '500'
etime = Time(btime.mjd + dur, format='mjd')
try:
cmdstr = "https://ssd.jpl.nasa.gov/horizons_batch.cgi?batch=1&TABLE_TYPE='OBSERVER'&QUANTITIES='1,17,20'&CSV_FORMAT='YES'&ANG_FORMAT='DEG'&CAL_FORMAT='BOTH'&SOLAR_ELONG='0,180'&CENTER='{}@399'&COMMAND='10'&START_TIME='".format(
observatory
) + btime.iso.replace(
' ', ','
) + "'&STOP_TIME='" + etime.iso[:-4].replace(
' ', ','
) + "'&STEP_SIZE='1m'&SKIP_DAYLT='NO'&EXTRA_PREC='YES'&APPARENT='REFRACTED'"
cmdstr = cmdstr.replace("'", "%27")
try:
context = ssl._create_unverified_context()
f = urlopen(cmdstr, context=context)
except:
f = urlopen(cmdstr)
lines = f.readlines()
f.close()
except:
# todo use geocentric coordinate for the new VLA data
import requests, collections
params = collections.OrderedDict()
params['batch'] = '1'
params['TABLE_TYPE'] = "'OBSERVER'"
params['QUANTITIES'] = "'1,17,20'"
params['CSV_FORMAT'] = "'YES'"
params['ANG_FORMAT'] = "'DEG'"
params['CAL_FORMAT'] = "'BOTH'"
params['SOLAR_ELONG'] = "'0,180'"
if observatory == '500':
params['CENTER'] = "'500'"
else:
params['CENTER'] = "'{}@399'".format(observatory)
params['COMMAND'] = "'10'"
params['START_TIME'] = "'{}'".format(btime.iso[:-4].replace(' ', ','))
params['STOP_TIME'] = "'{}'".format(etime.iso[:-4].replace(' ', ','))
params['STEP_SIZE'] = "'1m'"
params['SKIP_DAYLT'] = "'NO'"
params['EXTRA_PREC'] = "'YES'"
params['APPAENT'] = "'REFRACTED'"
results = requests.get("https://ssd.jpl.nasa.gov/horizons_batch.cgi",
params=params)
lines = [ll for ll in results.iter_lines()]
# add a check for python 3
if py3:
lines = [l.decode('utf-8', 'backslashreplace') for l in lines]
nline = len(lines)
istart = 0
for i in range(nline):
if lines[i][0:5] == '$$SOE': # start recording
istart = i + 1
if lines[i][0:5] == '$$EOE': # end recording
iend = i
newlines = lines[istart:iend]
nrec = len(newlines)
ephem_ = []
t = []
ra = []
dec = []
p0 = []
delta = []
for line in newlines:
items = line.split(',')
t.append(Time(float(items[1]), format='jd').mjd)
ra.append(np.radians(float(items[4])))
dec.append(np.radians(float(items[5])))
p0.append(float(items[6]))
delta.append(float(items[8]))
# convert list of dictionary to a dictionary of arrays
ephem = {'time': t, 'ra': ra, 'dec': dec, 'p0': p0, 'delta': delta}
return ephem
def concateovsa(vis, concatvis, datacolumn='corrected', keep_orig_ms=True, cols2rm="model,corrected", freqtol="", dirtol="", respectname=False,
timesort=True, copypointing=True, visweightscale=[], forcesingleephemfield=""):
if concatvis[-1] == os.path.sep:
concatvis = concatvis[:-1]
if os.path.sep not in concatvis:
visprefix = './'
else:
visprefix = os.path.dirname(concatvis) + os.path.sep
msfiles = vis
msfiles_ = []
for idx, ll in enumerate(msfiles):
if str(ll).endswith('/'):
msfiles[idx] = str(ll)[:-1]
datacolumn = datacolumn.lower()
if datacolumn == 'data':
print 'DATA columns will be concatenated.'
for ll in msfiles:
clearcal(vis=str(ll), addmodel=True)
elif datacolumn == 'corrected':
# try:
print 'CORRECTED columns will be concatenated.'
tmpdir = os.path.join(visprefix, 'tmp_ms') + os.path.sep
if not os.path.exists(tmpdir):
os.makedirs(tmpdir)
for ll in msfiles:
msfile_ = os.path.join(tmpdir, os.path.basename(str(ll)))
msfiles_.append(msfile_)
split(vis=str(ll), outputvis=msfile_, datacolumn='corrected')
clearcal(vis=msfile_, addmodel=True)
else:
raise ValueError('Please set datacolumn to be "data" or "corrected"!')
if msfiles_:
concat(vis=msfiles_, concatvis=concatvis, freqtol=freqtol, dirtol=dirtol, respectname=respectname, timesort=timesort,
copypointing=copypointing, visweightscale=visweightscale, forcesingleephemfield=forcesingleephemfield)
os.system('rm -rf {}'.format(tmpdir))
else:
concat(vis=msfiles, concatvis=concatvis, freqtol=freqtol, dirtol=dirtol, respectname=respectname, timesort=timesort,
copypointing=copypointing, visweightscale=visweightscale, forcesingleephemfield=forcesingleephemfield)
# Change all observation ids to be the same (zero)
tb.open(concatvis + '/OBSERVATION', nomodify=False)
nobs = tb.nrows()
tim0 = tb.getcell('TIME_RANGE', 0)[0]
tim1 = tb.getcell('TIME_RANGE', nobs - 1)[1]
tb.removerows([i + 1 for i in range(nobs - 1)])
tb.putcell('TIME_RANGE', 0, [tim0, tim1])
tb.close()
tb.open(concatvis + '/DATA_DESCRIPTION', nomodify=False)
nrows = tb.nrows()
pol_id = tb.getcol('POLARIZATION_ID')
tb.removerows(np.where(pol_id != 0)[0])
tb.close()
tb.open(concatvis, nomodify=False)
dd_id = tb.getcol('DATA_DESC_ID')
idx_dd_id, = np.where(dd_id >= nrows / 2)
dd_id[idx_dd_id] = dd_id[idx_dd_id] - nrows / 2
tb.putcol('DATA_DESC_ID', dd_id)
tb.close()
tb.open(concatvis + '/FIELD', nomodify=False)
nobs = tb.nrows()
tb.removerows([i + 1 for i in range(nobs - 1)])
tb.close()
tb.open(concatvis + '/SOURCE', nomodify=False)
nobs = tb.nrows()
tb.removerows([i + 1 for i in range(nobs - 1)])
tb.close()
tb.open(concatvis, nomodify=False)
obsid = tb.getcol('OBSERVATION_ID')
newobsid = np.zeros(len(obsid), dtype='int')
tb.putcol('OBSERVATION_ID', newobsid)
fldid = tb.getcol('FIELD_ID')
newfldid = np.zeros(len(fldid), dtype='int')
tb.putcol('FIELD_ID', newfldid)
colnames = tb.colnames()
cols2rm = cols2rm.upper()
cols2rm = cols2rm.split(',')
for l in range(len(cols2rm)):
col = cols2rm[l] + '_DATA'
if col in colnames:
try:
tb.removecols(col)
print 'Column {} removed.'.format(col)
except:
pass
tb.close()
if msfiles_ != [] and msfiles_ != msfiles:
for ll in msfiles_:
os.system('rm -rf {}'.format(ll))
if not keep_orig_ms:
for ll in msfiles:
os.system('rm -rf {}'.format(ll))
def calibeovsa(vis=None,
caltype=None,
interp=None,
docalib=True,
doflag=True,
flagant=None,
doimage=False,
imagedir=None,
antenna=None,
timerange=None,
spw=None,
stokes=None,
doconcat=False,
msoutdir=None,
keep_orig_ms=True):
'''
:param vis: EOVSA visibility dataset(s) to be calibrated
:param caltype:
:param interp:
:param docalib:
:param qlookimage:
:param flagant:
:param stokes:
:param doconcat:
:return:
'''
if type(vis) == str:
vis = [vis]
for idx, f in enumerate(vis):
if f[-1] == '/':
vis[idx] = f[:-1]
for msfile in vis:
casalog.origin('calibeovsa')
if not caltype:
casalog.post(
"Caltype not provided. Perform reference phase calibration and daily phase calibration."
)
caltype = [
'refpha', 'phacal', 'fluxcal'
] ## use this line after the phacal is applied # caltype = ['refcal']
if not os.path.exists(msfile):
casalog.post("Input visibility does not exist. Aborting...")
continue
if msfile.endswith('/'):
msfile = msfile[:-1]
if not msfile[-3:] in ['.ms', '.MS']:
casalog.post(
"Invalid visibility. Please provide a proper visibility file ending with .ms"
)
# if not caltable:
# caltable=[os.path.basename(vis).replace('.ms','.'+c) for c in caltype]
# get band information
tb.open(msfile + '/SPECTRAL_WINDOW')
nspw = tb.nrows()
bdname = tb.getcol('NAME')
bd_nchan = tb.getcol('NUM_CHAN')
bd = [int(b[4:]) - 1 for b in bdname] # band index from 0 to 33
# nchans = tb.getcol('NUM_CHAN')
# reffreqs = tb.getcol('REF_FREQUENCY')
# cenfreqs = np.zeros((nspw))
tb.close()
tb.open(msfile + '/ANTENNA')
nant = tb.nrows()
antname = tb.getcol('NAME')
antlist = [str(ll) for ll in range(len(antname) - 1)]
antennas = ','.join(antlist)
tb.close()
# get time stamp, use the beginning of the file
tb.open(msfile + '/OBSERVATION')
trs = {'BegTime': [], 'EndTime': []}
for ll in range(tb.nrows()):
tim0, tim1 = Time(tb.getcell('TIME_RANGE', ll) / 24 / 3600,
format='mjd')
trs['BegTime'].append(tim0)
trs['EndTime'].append(tim1)
tb.close()
trs['BegTime'] = Time(trs['BegTime'])
trs['EndTime'] = Time(trs['EndTime'])
btime = np.min(trs['BegTime'])
etime = np.max(trs['EndTime'])
# ms.open(vis)
# summary = ms.summary()
# ms.close()
# btime = Time(summary['BeginTime'], format='mjd')
# etime = Time(summary['EndTime'], format='mjd')
## stop using ms.summary to avoid conflicts with importeovsa
t_mid = Time((btime.mjd + etime.mjd) / 2., format='mjd')
print "This scan observed from {} to {} UTC".format(
btime.iso, etime.iso)
gaintables = []
if ('refpha' in caltype) or ('refamp' in caltype) or ('refcal'
in caltype):
refcal = ra.sql2refcalX(btime)
pha = refcal['pha'] # shape is 15 (nant) x 2 (npol) x 34 (nband)
pha[np.where(refcal['flag'] == 1)] = 0.
amp = refcal['amp']
amp[np.where(refcal['flag'] == 1)] = 1.
t_ref = refcal['timestamp']
# find the start and end time of the local day when refcal is registered
try:
dhr = t_ref.LocalTime.utcoffset().total_seconds() / 60. / 60.
except:
dhr = -7.
bt = Time(np.fix(t_ref.mjd + dhr / 24.) - dhr / 24., format='mjd')
et = Time(bt.mjd + 1., format='mjd')
(yr, mon, day) = (bt.datetime.year, bt.datetime.month,
bt.datetime.day)
dirname = caltbdir + str(yr) + str(mon).zfill(2) + '/'
if not os.path.exists(dirname):
os.mkdir(dirname)
# check if there is any ROACH reboot between the reference calibration found and the current data
t_rbts = db.get_reboot(Time([t_ref, btime]))
if not t_rbts:
casalog.post(
"Reference calibration is derived from observation at " +
t_ref.iso)
print "Reference calibration is derived from observation at " + t_ref.iso
else:
casalog.post(
"Oh crap! Roach reboot detected between the reference calibration time "
+ t_ref.iso + ' and the current observation at ' +
btime.iso)
casalog.post("Aborting...")
print "Oh crap! Roach reboot detected between the reference calibration time " + t_ref.iso + ' and the current observation at ' + btime.iso
print "Aborting..."
para_pha = []
para_amp = []
calpha = np.zeros((nspw, 15, 2))
calamp = np.zeros((nspw, 15, 2))
for s in range(nspw):
for n in range(15):
for p in range(2):
calpha[s, n, p] = pha[n, p, bd[s]]
calamp[s, n, p] = amp[n, p, bd[s]]
para_pha.append(np.degrees(pha[n, p, bd[s]]))
para_amp.append(amp[n, p, bd[s]])
if 'fluxcal' in caltype:
calfac = pc.get_calfac(Time(t_mid.iso.split(' ')[0] + 'T23:59:59'))
t_bp = Time(calfac['timestamp'], format='lv')
if int(t_mid.mjd) == int(t_bp.mjd):
accalfac = calfac['accalfac'] # (ant x pol x freq)
# tpcalfac = calfac['tpcalfac'] # (ant x pol x freq)
caltb_autoamp = dirname + t_bp.isot[:-4].replace(
':', '').replace('-', '') + '.bandpass'
if not os.path.exists(caltb_autoamp):
bandpass(vis=msfile,
caltable=caltb_autoamp,
solint='inf',
refant='eo01',
minblperant=0,
minsnr=0,
bandtype='B',
docallib=False)
tb.open(caltb_autoamp, nomodify=False) # (ant x spw)
bd_chanidx = np.hstack([[0], bd_nchan.cumsum()])
for ll in range(nspw):
antfac = np.sqrt(
accalfac[:, :, bd_chanidx[ll]:bd_chanidx[ll + 1]])
# # antfac *= tpcalfac[:, :,bd_chanidx[ll]:bd_chanidx[ll + 1]]
antfac = np.moveaxis(antfac, 0, 2)
cparam = np.zeros((2, bd_nchan[ll], nant))
cparam[:, :, :-3] = 1.0 / antfac
tb.putcol('CPARAM', cparam + 0j, ll * nant, nant)
paramerr = tb.getcol('PARAMERR', ll * nant, nant)
paramerr = paramerr * 0
tb.putcol('PARAMERR', paramerr, ll * nant, nant)
bpflag = tb.getcol('FLAG', ll * nant, nant)
bpant1 = tb.getcol('ANTENNA1', ll * nant, nant)
bpflagidx, = np.where(bpant1 >= 13)
bpflag[:] = False
bpflag[:, :, bpflagidx] = True
tb.putcol('FLAG', bpflag, ll * nant, nant)
bpsnr = tb.getcol('SNR', ll * nant, nant)
bpsnr[:] = 100.0
bpsnr[:, :, bpflagidx] = 0.0
tb.putcol('SNR', bpsnr, ll * nant, nant)
tb.close()
msg_prompt = "Scaling calibration is derived for {}.".format(
msfile)
casalog.post(msg_prompt)
print msg_prompt
gaintables.append(caltb_autoamp)
else:
msg_prompt = "Caution: No TPCAL is available on {}. No scaling calibration is derived for {}.".format(
t_mid.datetime.strftime('%b %d, %Y'), msfile)
casalog.post(msg_prompt)
print msg_prompt
if ('refpha' in caltype) or ('refcal' in caltype):
# caltb_pha = os.path.basename(vis).replace('.ms', '.refpha')
# check if the calibration table already exists
caltb_pha = dirname + t_ref.isot[:-4].replace(':', '').replace(
'-', '') + '.refpha'
if not os.path.exists(caltb_pha):
gencal(vis=msfile,
caltable=caltb_pha,
caltype='ph',
antenna=antennas,
pol='X,Y',
spw='0~' + str(nspw - 1),
parameter=para_pha)
gaintables.append(caltb_pha)
if ('refamp' in caltype) or ('refcal' in caltype):
# caltb_amp = os.path.basename(vis).replace('.ms', '.refamp')
caltb_amp = dirname + t_ref.isot[:-4].replace(':', '').replace(
'-', '') + '.refamp'
if not os.path.exists(caltb_amp):
gencal(vis=msfile,
caltable=caltb_amp,
caltype='amp',
antenna=antennas,
pol='X,Y',
spw='0~' + str(nspw - 1),
parameter=para_amp)
gaintables.append(caltb_amp)
# calibration for the change of delay center between refcal time and beginning of scan -- hopefully none!
xml, buf = ch.read_calX(4, t=[t_ref, btime], verbose=False)
if buf:
dly_t2 = Time(stf.extract(buf[0], xml['Timestamp']), format='lv')
dlycen_ns2 = stf.extract(buf[0], xml['Delaycen_ns'])[:15]
xml, buf = ch.read_calX(4, t=t_ref)
dly_t1 = Time(stf.extract(buf, xml['Timestamp']), format='lv')
dlycen_ns1 = stf.extract(buf, xml['Delaycen_ns'])[:15]
dlycen_ns_diff = dlycen_ns2 - dlycen_ns1
for n in range(2):
dlycen_ns_diff[:, n] -= dlycen_ns_diff[0, n]
print 'Multi-band delay is derived from delay center difference at {} & {}'.format(
dly_t1.iso, dly_t2.iso)
# print '=====Delays relative to Ant 14====='
# for i, dl in enumerate(dlacen_ns_diff[:, 0] - dlacen_ns_diff[13, 0]):
# ant = antlist[i]
# print 'Ant eo{0:02d}: x {1:.2f} ns & y {2:.2f} ns'.format(int(ant) + 1, dl
# dlacen_ns_diff[i, 1] - dlacen_ns_diff[13, 1])
# caltb_mbd0 = os.path.basename(vis).replace('.ms', '.mbd0')
caltb_dlycen = dirname + dly_t2.isot[:-4].replace(':', '').replace(
'-', '') + '.dlycen'
if not os.path.exists(caltb_dlycen):
gencal(vis=msfile,
caltable=caltb_dlycen,
caltype='mbd',
pol='X,Y',
antenna=antennas,
parameter=dlycen_ns_diff.flatten().tolist())
gaintables.append(caltb_dlycen)
if 'phacal' in caltype:
phacals = np.array(
ra.sql2phacalX([bt, et], neat=True, verbose=False))
if not phacals.any() or len(phacals) == 0:
print "Found no phacal records in SQL database, will skip phase calibration"
else:
# first generate all phacal calibration tables if not already exist
t_phas = Time([phacal['t_pha'] for phacal in phacals])
# sort the array in ascending order by t_pha
sinds = t_phas.mjd.argsort()
t_phas = t_phas[sinds]
phacals = phacals[sinds]
caltbs_phambd = []
for i, phacal in enumerate(phacals):
# filter out phase cals with reference time stamp >30 min away from the provided refcal time
if (phacal['t_ref'].jd -
refcal['timestamp'].jd) > 30. / 1440.:
del phacals[i]
del t_phas[i]
continue
else:
t_pha = phacal['t_pha']
phambd_ns = phacal['pslope']
for n in range(2):
phambd_ns[:, n] -= phambd_ns[0, n]
# set all flagged values to be zero
phambd_ns[np.where(phacal['flag'] == 1)] = 0.
caltb_phambd = dirname + t_pha.isot[:-4].replace(
':', '').replace('-', '') + '.phambd'
caltbs_phambd.append(caltb_phambd)
if not os.path.exists(caltb_phambd):
gencal(vis=msfile,
caltable=caltb_phambd,
caltype='mbd',
pol='X,Y',
antenna=antennas,
parameter=phambd_ns.flatten().tolist())
# now decides which table to apply depending on the interpolation method ("neatest" or "linear")
if interp == 'nearest':
tbind = np.argmin(np.abs(t_phas.mjd - t_mid.mjd))
dt = np.min(np.abs(t_phas.mjd - t_mid.mjd)) * 24.
print "Selected nearest phase calibration table at " + t_phas[
tbind].iso
gaintables.append(caltbs_phambd[tbind])
if interp == 'linear':
# bphacal = ra.sql2phacalX(btime)
# ephacal = ra.sql2phacalX(etime,reverse=True)
bt_ind, = np.where(t_phas.mjd < btime.mjd)
et_ind, = np.where(t_phas.mjd > etime.mjd)
if len(bt_ind) == 0 and len(et_ind) == 0:
print "No phacal found before or after the ms data within the day of observation"
print "Skipping daily phase calibration"
elif len(bt_ind) > 0 and len(et_ind) == 0:
gaintables.append(caltbs_phambd[bt_ind[-1]])
elif len(bt_ind) == 0 and len(et_ind) > 0:
gaintables.append(caltbs_phambd[et_ind[0]])
elif len(bt_ind) > 0 and len(et_ind) > 0:
bphacal = phacals[bt_ind[-1]]
ephacal = phacals[et_ind[0]]
# generate a new table interpolating between two daily phase calibrations
t_pha_mean = Time(np.mean(
[bphacal['t_pha'].mjd, ephacal['t_pha'].mjd]),
format='mjd')
phambd_ns = (bphacal['pslope'] +
ephacal['pslope']) / 2.
for n in range(2):
phambd_ns[:, n] -= phambd_ns[0, n]
# set all flagged values to be zero
phambd_ns[np.where(bphacal['flag'] == 1)] = 0.
phambd_ns[np.where(ephacal['flag'] == 1)] = 0.
caltb_phambd_interp = dirname + t_pha_mean.isot[:-4].replace(
':', '').replace('-', '') + '.phambd'
if not os.path.exists(caltb_phambd_interp):
gencal(vis=msfile,
caltable=caltb_phambd_interp,
caltype='mbd',
pol='X,Y',
antenna=antennas,
parameter=phambd_ns.flatten().tolist())
print "Using phase calibration table interpolated between records at " + bphacal[
't_pha'].iso + ' and ' + ephacal['t_pha'].iso
gaintables.append(caltb_phambd_interp)
if docalib:
clearcal(msfile)
applycal(vis=msfile,
gaintable=gaintables,
applymode='calflag',
calwt=False)
# delete the interpolated phase calibration table
try:
caltb_phambd_interp
except:
pass
else:
if os.path.exists(caltb_phambd_interp):
shutil.rmtree(caltb_phambd_interp)
if doflag:
# flag zeros and NaNs
flagdata(vis=msfile, mode='clip', clipzeros=True)
if flagant:
try:
flagdata(vis=msfile, antenna=flagant)
except:
print "Something wrong with flagant. Abort..."
if doimage:
from matplotlib import pyplot as plt
from suncasa.utils import helioimage2fits as hf
from sunpy import map as smap
if not antenna:
antenna = '0~12'
if not stokes:
stokes = 'XX'
if not timerange:
timerange = ''
if not spw:
spw = '1~3'
if not imagedir:
imagedir = '.'
#(yr, mon, day) = (bt.datetime.year, bt.datetime.month, bt.datetime.day)
#dirname = imagedir + str(yr) + '/' + str(mon).zfill(2) + '/' + str(day).zfill(2) + '/'
#if not os.path.exists(dirname):
# os.makedirs(dirname)
bds = [spw]
nbd = len(bds)
imgs = []
for bd in bds:
if '~' in bd:
bdstr = bd.replace('~', '-')
else:
bdstr = str(bd).zfill(2)
imname = imagedir + '/' + os.path.basename(msfile).replace(
'.ms', '.bd' + bdstr)
print 'Cleaning image: ' + imname
try:
clean(vis=msfile,
imagename=imname,
antenna=antenna,
spw=bd,
timerange=timerange,
imsize=[512],
cell=['5.0arcsec'],
stokes=stokes,
niter=500)
except:
print 'clean not successfull for band ' + str(bd)
else:
imgs.append(imname + '.image')
junks = ['.flux', '.mask', '.model', '.psf', '.residual']
for junk in junks:
if os.path.exists(imname + junk):
shutil.rmtree(imname + junk)
tranges = [btime.iso + '~' + etime.iso] * nbd
fitsfiles = [img.replace('.image', '.fits') for img in imgs]
hf.imreg(vis=msfile,
timerange=tranges,
imagefile=imgs,
fitsfile=fitsfiles,
usephacenter=False)
plt.figure(figsize=(6, 6))
for i, fitsfile in enumerate(fitsfiles):
plt.subplot(1, nbd, i + 1)
eomap = smap.Map(fitsfile)
sz = eomap.data.shape
if len(sz) == 4:
eomap.data = eomap.data.reshape((sz[2], sz[3]))
eomap.plot_settings['cmap'] = plt.get_cmap('jet')
eomap.plot()
eomap.draw_limb()
eomap.draw_grid()
plt.show()
if doconcat:
if len(vis) > 1:
# from suncasa.eovsa import concateovsa as ce
from suncasa.tasks import concateovsa_cli as ce
if msoutdir is None:
msoutdir = './'
concatvis = os.path.basename(vis[0])
concatvis = msoutdir + '/' + concatvis.split('.')[0] + '_concat.ms'
ce.concateovsa(vis,
concatvis,
datacolumn='corrected',
keep_orig_ms=keep_orig_ms,
cols2rm="model,corrected")
return [concatvis]
else:
return vis
def read_horizons(vis):
import urllib2
import ssl
if not os.path.exists(vis):
print 'Input ms data ' + vis + ' does not exist! '
return -1
try:
#ms.open(vis)
#summary = ms.summary()
#ms.close()
#btime = Time(summary['BeginTime'], format='mjd')
#etime = Time(summary['EndTime'], format='mjd')
## alternative way to avoid conflicts with importeovsa, if needed -- more time consuming
tb.open(vis)
btime = Time(tb.getcell('TIME', 0) / 24. / 3600., format='mjd')
etime = Time(tb.getcell('TIME',
tb.nrows() - 1) / 24. / 3600.,
format='mjd')
tb.close()
print "Beginning time of this scan " + btime.iso
print "End time of this scan " + etime.iso
try:
context = ssl._create_unverified_context()
f = urllib2.urlopen(
"http://ssd.jpl.nasa.gov/horizons_batch.cgi?batch=l&TABLE_TYPE='OBSERVER'&QUANTITIES='1,17,20'&CSV_FORMAT='YES'&ANG_FORMAT='DEG'&CAL_FORMAT='BOTH'&SOLAR_ELONG='0,180'&CENTER='-81@399'&COMMAND='10'&START_TIME='"
+ btime.iso.replace(' ', ',') + "'&STOP_TIME='" +
etime.iso[:-4].replace(' ', ',') +
"'&STEP_SIZE='1m'&SKIP_DAYLT='NO'",
context=context)
except:
f = urllib2.urlopen(
"http://ssd.jpl.nasa.gov/horizons_batch.cgi?batch=l&TABLE_TYPE='OBSERVER'&QUANTITIES='1,17,20'&CSV_FORMAT='YES'&ANG_FORMAT='DEG'&CAL_FORMAT='BOTH'&SOLAR_ELONG='0,180'&CENTER='-81@399'&COMMAND='10'&START_TIME='"
+ btime.iso.replace(' ', ',') + "'&STOP_TIME='" +
etime.iso[:-4].replace(' ', ',') +
"'&STEP_SIZE='1m'&SKIP_DAYLT='NO'")
except:
print 'error in reading ms file: ' + vis + ' to obtain the ephemeris!'
return -1
# inputs:
# ephemfile:
# OBSERVER output from JPL Horizons for topocentric coordinates with for example
# target=Sun, observer=VLA=-5
# extra precision, quantities 1,17,20, REFRACTION
# routine goes through file to find $$SOE which is start of ephemeris and ends with $$EOE
# outputs: a Python dictionary containing the following:
# timestr: date and time as a string
# time: modified Julian date
# ra: right ascention, in rad
# dec: declination, in rad
# rastr: ra in string
# decstr: dec in string
# p0: solar p angle, CCW with respect to the celestial north pole
# delta: distance from the disk center to the observer, in AU
# delta_dot: time derivative of delta, in the light of sight direction. Negative means it is moving toward the observer
#
# initialize the return dictionary
ephem0 = dict.fromkeys(['time', 'ra', 'dec', 'delta', 'p0'])
lines = f.readlines()
f.close()
nline = len(lines)
istart = 0
for i in range(nline):
line = lines[i]
if line[0:5] == '$$SOE': # start recording
istart = i + 1
if line[0:5] == '$$EOE': # end recording
iend = i
newlines = lines[istart:iend]
nrec = len(newlines)
ephem_ = []
t = []
ra = []
dec = []
p0 = []
delta = []
for line in newlines:
items = line.split(',')
# t.append({'unit':'mjd','value':Time(float(items[1]),format='jd').mjd})
# ra.append({'unit': 'rad', 'value': np.radians(float(items[4]))})
# dec.append({'unit': 'rad', 'value': np.radians(float(items[5]))})
# p0.append({'unit': 'deg', 'value': float(items[6])})
# delta.append({'unit': 'au', 'value': float(items[8])})
t.append(Time(float(items[1]), format='jd').mjd)
ra.append(np.radians(float(items[4])))
dec.append(np.radians(float(items[5])))
p0.append(float(items[6]))
delta.append(float(items[8]))
# convert list of dictionary to a dictionary of arrays
ephem = {'time': t, 'ra': ra, 'dec': dec, 'p0': p0, 'delta': delta}
return ephem
def get_dspec(vis=None, savespec=True, specfile=None, bl='', uvrange='', field='', scan='', datacolumn='data',
domedian=False, timeran=None, spw=None, timebin='0s', regridfreq=False, fillnan=None, verbose=False,
usetbtool=False):
# from split_cli import split_cli as split
if vis.endswith('/'):
vis = vis[:-1]
msfile = vis
if not spw:
spw = ''
if not timeran:
timeran = ''
if domedian:
if not uvrange:
uvrange = '0.2~0.8km'
# bl = ''
else:
uvrange = ''
if not bl:
bl = ''
else:
uvrange = ''
# Open the ms and plot dynamic spectrum
if verbose:
print('Splitting selected data...')
if usetbtool:
try:
tb.open(vis + '/POLARIZATION')
corrtype = tb.getcell('CORR_TYPE', 0)
pols = [stokesenum[p] for p in corrtype]
tb.close()
except:
pols = []
antmask = []
if uvrange is not '' or bl is not '':
ms.open(vis)
ms.selectinit(datadescid=0)
mdata = ms.metadata()
antlist = mdata.antennaids()
mdata.done()
staql = {'uvdist': uvrange, 'baseline': bl, 'spw': spw, 'field': field, 'scan': scan, 'timerange': timeran}
### todo the selection only works for uvrange and bl. To make the selection of other items works,
## I need to make mask for other items.
a = ms.msselect(staql)
mdata = ms.metadata()
baselines = mdata.baselines()
for lidx, l in enumerate(antlist):
antmask.append(baselines[l][antlist[lidx:]])
antmask = np.hstack(antmask)
mdata.done()
ms.close()
tb.open(vis)
spwtb = tbtool()
spwtb.open(vis + '/SPECTRAL_WINDOW')
ptb = tbtool()
ptb.open(vis + '/POLARIZATION')
ms.open(vis)
spwlist = []
mdata = ms.metadata()
nspw = mdata.nspw()
nbl = mdata.nbaselines() + mdata.nantennas()
nscans = mdata.nscans()
spw_nfrq = [] # List of number of frequencies in each spw
for i in range(nspw):
spw_nfrq.append(mdata.nchan(i))
spw_nfrq = np.array(spw_nfrq)
nf = np.sum(spw_nfrq)
smry = mdata.summary()
scan_ntimes = [] # List of number of times in each scan
for iscan in range(nscans):
scan_ntimes.append(
smry['observationID=0']['arrayID=0']['scan=' + str(iscan)]['fieldID=0']['nrows'] / nspw / nbl)
scan_ntimes = np.array(scan_ntimes)
scan_ntimes_integer = scan_ntimes.astype(np.int)
if len(np.where(scan_ntimes % scan_ntimes_integer != 0)[0]) != 0:
# if True:
scan_ntimes = [] # List of number of times in each scan
for iscan in range(nscans):
scan_ntimes.append(
len(smry['observationID=0']['arrayID=0']['scan=' + str(iscan)]['fieldID=0'].keys()) - 6)
scan_ntimes = np.array(scan_ntimes)
else:
scan_ntimes = scan_ntimes_integer
nt = np.sum(scan_ntimes)
times = tb.getcol('TIME')
if times[nbl] - times[0] != 0:
# This is frequency/scan sort order
order = 'f'
elif times[nbl * nspw - 1] - times[0] != 0:
# This is time sort order
order = 't'
npol = ptb.getcol('NUM_CORR', 0, 1)[0]
ptb.close()
freq = np.zeros(nf, float)
times = np.zeros(nt, float)
if order == 't':
specamp = np.zeros((npol, nf, nbl, nt), np.complex)
for j in range(nt):
fptr = 0
# Loop over spw
for i in range(nspw):
# Get channel frequencies for this spw (annoyingly comes out as shape (nf, 1)
cfrq = spwtb.getcol('CHAN_FREQ', i, 1)[:, 0]
if j == 0:
# Only need this the first time through
spwlist += [i] * len(cfrq)
if i == 0:
times[j] = tb.getcol('TIME', nbl * (i + nspw * j), 1) # Get the time
spec_ = tb.getcol('DATA', nbl * (i + nspw * j), nbl) # Get complex data for this spw
flag = tb.getcol('FLAG', nbl * (i + nspw * j), nbl) # Get flags for this spw
nfrq = len(cfrq)
# Apply flags
if type(fillnan) in [int, float]:
spec_[flag] = float(fillnan)
else:
spec_[flag] = 0.0
# Insert data for this spw into larger array
specamp[:, fptr:fptr + nfrq, :, j] = spec_
freq[fptr:fptr + nfrq] = cfrq
fptr += nfrq
else:
specf = np.zeros((npol, nf, nt, nbl), np.complex) # Array indexes are swapped
iptr = 0
for j in range(nscans):
# Loop over scans
for i in range(nspw):
# Loop over spectral windows
s = scan_ntimes[j]
f = spw_nfrq[i]
s1 = np.sum(scan_ntimes[:j]) # Start time index
s2 = np.sum(scan_ntimes[:j + 1]) # End time index
f1 = np.sum(spw_nfrq[:i]) # Start freq index
f2 = np.sum(spw_nfrq[:i + 1]) # End freq index
spec_ = tb.getcol('DATA', iptr, nbl * s)
flag = tb.getcol('FLAG', iptr, nbl * s)
if j == 0:
cfrq = spwtb.getcol('CHAN_FREQ', i, 1)[:, 0]
freq[f1:f2] = cfrq
spwlist += [i] * len(cfrq)
times[s1:s2] = tb.getcol('TIME', iptr, nbl * s).reshape(s, nbl)[:, 0] # Get the times
iptr += nbl * s
# Apply flags
if type(fillnan) in [int, float]:
spec_[flag] = float(fillnan)
else:
spec_[flag] = 0.0
# Insert data for this spw into larger array
specf[:, f1:f2, s1:s2] = spec_.reshape(npol, f, s, nbl)
# Swap the array indexes back to the desired order
specamp = np.swapaxes(specf, 2, 3)
tb.close()
spwtb.close()
ms.close()
if len(antmask) > 0:
specamp = specamp[:, :, np.where(antmask)[0], :]
(npol, nfreq, nbl, ntim) = specamp.shape
tim = times
else:
# Open the ms and plot dynamic spectrum
if verbose:
print('Splitting selected data...')
vis_spl = './tmpms.splitted'
if os.path.exists(vis_spl):
os.system('rm -rf ' + vis_spl)
# split(vis=msfile, outputvis=vis_spl, timerange=timeran, antenna=bl, field=field, scan=scan, spw=spw,
# uvrange=uvrange, timebin=timebin, datacolumn=datacolumn)
try:
from split_cli import split_cli as split
split(vis=msfile, outputvis=vis_spl, datacolumn=datacolumn, timerange=timeran, spw=spw, antenna=bl,
field=field,
scan=scan, uvrange=uvrange, timebin=timebin)
except:
ms.open(msfile, nomodify=True)
ms.split(outputms=vis_spl, whichcol=datacolumn, time=timeran, spw=spw, baseline=bl, field=field, scan=scan,
uvrange=uvrange, timebin=timebin)
ms.close()
if verbose:
print('Regridding into a single spectral window...')
# print('Reading data spw by spw')
try:
tb.open(vis_spl + '/POLARIZATION')
corrtype = tb.getcell('CORR_TYPE', 0)
pols = [stokesenum[p] for p in corrtype]
tb.close()
except:
pols = []
if regridfreq:
ms.open(vis_spl, nomodify=False)
ms.cvel(outframe='LSRK', mode='frequency', interp='nearest')
ms.selectinit(datadescid=0, reset=True)
data = ms.getdata(['amplitude', 'time', 'axis_info'], ifraxis=True)
specamp = data['amplitude']
freq = data['axis_info']['freq_axis']['chan_freq']
else:
ms.open(vis_spl)
ms.selectinit(datadescid=0, reset=True)
spwinfo = ms.getspectralwindowinfo()
specamp = []
freq = []
time = []
for descid in range(len(spwinfo.keys())):
ms.selectinit(datadescid=0, reset=True)
ms.selectinit(datadescid=descid)
data = ms.getdata(['amplitude', 'time', 'axis_info'], ifraxis=True)
specamp_ = data['amplitude']
freq_ = data['axis_info']['freq_axis']['chan_freq']
time_ = data['time']
if fillnan is not None:
flag_ = ms.getdata(['flag', 'time', 'axis_info'], ifraxis=True)['flag']
if type(fillnan) in [int, float, long]:
specamp_[flag_] = float(fillnan)
else:
specamp_[flag_] = 0.0
specamp.append(specamp_)
freq.append(freq_)
time.append(time_)
specamp = np.concatenate(specamp, axis=1)
freq = np.concatenate(freq, axis=0)
ms.selectinit(datadescid=0, reset=True)
ms.close()
os.system('rm -rf ' + vis_spl)
(npol, nfreq, nbl, ntim) = specamp.shape
freq = freq.reshape(nfreq)
tim = data['time']
if verbose:
print('npol, nfreq, nbl, ntime:', (npol, nfreq, nbl, ntim))
spec = np.swapaxes(specamp, 2, 1)
if domedian:
if verbose:
print('doing median of all the baselines')
# mask zero values before median
# spec_masked = np.ma.masked_where(spec < 1e-9, spec)
# spec_masked2 = np.ma.masked_invalid(spec)
# spec_masked = np.ma.masked_array(spec, mask=np.logical_or(spec_masked.mask, spec_masked2.mask))
# spec_med = np.ma.filled(np.ma.median(spec_masked, axis=1), fill_value=0.)
spec = np.abs(spec)
spec_med = np.nanmedian(spec, axis=1)
nbl = 1
ospec = spec_med.reshape((npol, nbl, nfreq, ntim))
else:
ospec = spec
# Save the dynamic spectral data
if savespec:
if not specfile:
specfile = msfile + '.dspec.npz'
if os.path.exists(specfile):
os.system('rm -rf ' + specfile)
np.savez(specfile, spec=ospec, tim=tim, freq=freq,
timeran=timeran, spw=spw, bl=bl, uvrange=uvrange, pol=pols)
if verbose:
print('Median dynamic spectrum saved as: ' + specfile)
return {'spec': ospec, 'tim': tim, 'freq': freq, 'timeran': timeran, 'spw': spw, 'bl': bl, 'uvrange': uvrange,
'pol': pols}
def compVarColTables(referencetab, testtab, varcol, tolerance=0.):
'''Compare a variable column of two tables.
referencetab --> a reference table
testtab --> a table to verify
varcol --> the name of a variable column (str)
Returns True or False.
'''
retval = True
tb2 = casac.table()
tb.open(referencetab)
cnames = tb.colnames()
tb2.open(testtab)
col = varcol
if tb.isvarcol(col) and tb2.isvarcol(col):
try:
# First check
if tb.nrows() != tb2.nrows():
print 'Length of %s differ from %s, %s!=%s'%(referencetab,testtab,len(rk),len(tk))
retval = False
else:
for therow in xrange(tb.nrows()):
rdata = tb.getcell(col,therow)
tdata = tb2.getcell(col,therow)
# if not (rdata==tdata).all():
if not rdata.all()==tdata.all():
if (tolerance>0.):
differs=False
for j in range(0,len(rdata)):
### if (type(rdata[j])==float or type(rdata[j])==int):
if ((isinstance(rdata[j],float)) or (isinstance(rdata[j],int))):
if (abs(rdata[j]-tdata[j]) > tolerance*abs(rdata[j]+tdata[j])):
# print 'Column ', col,' differs in tables ', referencetab, ' and ', testtab
# print therow, j
# print rdata[j]
# print tdata[j]
differs = True
### elif (type(rdata[j])==list or type(rdata[j])==np.ndarray):
elif (isinstance(rdata[j],list)) or (isinstance(rdata[j],np.ndarray)):
for k in range(0,len(rdata[j])):
if (abs(rdata[j][k]-tdata[j][k]) > tolerance*abs(rdata[j][k]+tdata[j][k])):
# print 'Column ', col,' differs in tables ', referencetab, ' and ', testtab
# print therow, j, k
# print rdata[j][k]
# print tdata[j][k]
differs = True
if differs:
print 'ERROR: Column %s of %s and %s do not agree within tolerance %s'%(col,referencetab, testtab, tolerance)
retval = False
break
else:
print 'ERROR: Column %s of %s and %s do not agree.'%(col,referencetab, testtab)
print 'ERROR: First row to differ is row=%s'%therow
retval = False
break
finally:
tb.close()
tb2.close()
else:
print 'Columns are not varcolumns.'
retval = False
if retval:
print 'Column %s of %s and %s agree'%(col,referencetab, testtab)
return retval
def svplot(vis, timerange=None, spw='', workdir='./', specfile=None, bl=None, uvrange=None,
stokes='RR,LL', dmin=None, dmax=None,
goestime=None, reftime=None,
xycen=None, fov=[500.,500.], xyrange=None, restoringbeam=[''], robust=0.0,
niter=500, imsize=[512], cell=['5.0arcsec'],interactive=False,
usemsphacenter=True, imagefile=None, fitsfile=None, plotaia=True,
aiawave=171, aiafits=None, savefig=False, mkmovie=False, overwrite=True, ncpu=10, twidth=1, verbose=True):
'''
Required inputs:
vis: calibrated CASA measurement set
Important optional inputs:
timerange: timerange for clean. Standard CASA time selection format.
If not provided, use the entire range (*BE CAREFUL, COULD BE VERY SLOW*)
spw: spectral window selection following the CASA syntax.
Examples: spw='1:2~60' (spw id 1, channel range 2-60); spw='*:1.2~1.3GHz' (selects all channels within 1.2-1.3 GHz; note the *)
specfile: supply dynamic spectrum save file (from suncasa.utils.dspec2.get_dspec()). Otherwise
generate a median dynamic spectrum on the fly
Optional inputs:
bl: baseline to generate dynamic spectrum
uvrange: uvrange to select baselines for generating dynamic spectrum
stokes: polarization of the clean image, can be 'RR,LL' or 'I,V'
dmin,dmax: color bar parameter
goestime: goes plot time, example ['2016/02/18 18:00:00','2016/02/18 23:00:00']
rhessisav: rhessi savefile
reftime: reftime for the image
xycen: center of the image in helioprojective coordinates (HPLN/HPLT), in arcseconds. Example: [900, -150.]
fov: field of view in arcsecs. Example: [500., 500.]
xyrange: field of view in solar XY coordinates. Format: [[x1,x2],[y1,y2]]. Example: [[900., 1200.],[0,300]]
***NOTE: THIS PARAMETER OVERWRITES XYCEN AND FOV***
aiawave: wave length of aia file in a
imagefile: if imagefile provided, use it. Otherwise do clean and generate a new one.
fitsfile: if fitsfile provided, use it. Otherwise generate a new one
savefig: whether to save the figure
Example:
'''
if xycen:
xc, yc = xycen
xlen, ylen = fov
if parse_version(sunpy.__version__)>parse_version('0.8.0'):
xyrange = [[xc - xlen / 2.0, yc - ylen / 2.0], [xc + xlen / 2.0, yc + ylen / 2.0]]
else:
xyrange = [[xc - xlen / 2.0, xc + xlen / 2.0], [yc - ylen / 2.0, yc + ylen / 2.0]]
stokes_allowed = ['RR,LL', 'I,V', 'RRLL', 'IV']
if not stokes in stokes_allowed:
print 'wrong stokes parameter ' + str(stokes) + '. Allowed values are ' + ', '.join(stokes_allowed)
return -1
if stokes == 'RRLL':
stokes = 'RR,LL'
if stokes == 'IV':
stokes = 'I,V'
if vis[-1] == '/':
vis = vis[:-1]
if not os.path.exists(vis):
print 'input measurement not exist'
return -1
if aiafits is None:
aiafits = ''
# split the data
# generating dynamic spectrum
if not os.path.exists(workdir):
os.makedirs(workdir)
if specfile:
try:
specdata = np.load(specfile)
except:
print('Provided dynamic spectrum file not numpy npz. Generating one from the visibility data')
specfile = os.path.join(workdir, os.path.basename(vis) + '.dspec.npz')
dspec_external(vis, workdir=workdir, specfile=specfile)
specdata = np.load(specfile) # specdata = ds.get_dspec(vis, domedian=True, verbose=True)
else:
print('Dynamic spectrum file not provided; Generating one from the visibility data')
# specdata = ds.get_dspec(vis, domedian=True, verbose=True)
specfile = os.path.join(workdir, os.path.basename(vis) + '.dspec.npz')
dspec_external(vis, workdir=workdir, specfile=specfile)
specdata = np.load(specfile)
tb.open(vis)
starttim = Time(tb.getcell('TIME', 0) / 24. / 3600., format='mjd')
endtim = Time(tb.getcell('TIME', tb.nrows() - 1) / 24. / 3600., format='mjd')
tb.close()
datstr = starttim.iso[:10]
if timerange is None or timerange == '':
starttim1 = starttim
endtim1 = endtim
timerange = '{0}~{1}'.format(starttim.iso.replace('-', '/').replace(' ', '/'), endtim.iso.replace('-', '/').replace(' ', '/'))
else:
try:
(tstart, tend) = timerange.split('~')
if tstart[2] == ':':
starttim1 = Time(datstr + 'T' + tstart)
endtim1 = Time(datstr + 'T' + tend)
timerange = '{0}/{1}~{0}/{2}'.format(datstr.replace('-', '/'), tstart, tend)
else:
starttim1 = Time(qa.quantity(tstart, 'd')['value'], format='mjd')
endtim1 = Time(qa.quantity(tend, 'd')['value'], format='mjd')
except ValueError:
print "keyword 'timerange' in wrong format"
midtime_mjd = (starttim1.mjd + endtim1.mjd) / 2.
if vis.endswith('/'):
vis = vis[:-1]
visname = os.path.basename(vis)
bt = starttim1.plot_date
et = endtim1.plot_date
# find out min and max frequency for plotting in dynamic spectrum
ms.open(vis)
metadata = ms.metadata()
observatory = metadata.observatorynames()[0]
spwInfo = ms.getspectralwindowinfo()
nspw = len(spwInfo)
if not spw:
spw = '0~' + str(nspw - 1)
staql = {'timerange': timerange, 'spw': spw}
if ms.msselect(staql, onlyparse=True):
ndx = ms.msselectedindices()
chan_sel = ndx['channel']
nspw = chan_sel.shape[0]
bspw = chan_sel[0, 0]
bchan = chan_sel[0, 1]
espw = chan_sel[-1, 0]
echan = chan_sel[-1, 2]
bfreq = spwInfo[str(bspw)]['Chan1Freq'] + spwInfo[str(bspw)]['ChanWidth'] * bchan
efreq = spwInfo[str(espw)]['Chan1Freq'] + spwInfo[str(espw)]['ChanWidth'] * echan
bfreqghz = bfreq / 1e9
efreqghz = efreq / 1e9
if verbose:
print 'selected timerange {}'.format(timerange)
print 'selected frequency range {0:6.3f} to {1:6.3f} GHz'.format(bfreqghz, efreqghz)
else:
print "spw or timerange selection failed. Aborting..."
ms.close()
return -1
ms.close()
if observatory == 'EOVSA':
print 'Provide stokes: ' + str(stokes) + '. However EOVSA has linear feeds. Force stokes to be IV'
stokes = 'I,V'
if mkmovie:
plt.ioff()
# fig = plt.figure(figsize=(12, 7.5), dpi=100)
if fitsfile:
pass
else:
if not imagefile:
# from ptclean_cli import ptclean_cli as ptclean
eph = hf.read_horizons(t0=Time(midtime_mjd, format='mjd'))
if observatory == 'EOVSA' or (not usemsphacenter):
phasecenter = ''
else:
phasecenter = 'J2000 ' + str(eph['ra'][0])[:15] + 'rad ' + str(eph['dec'][0])[:15] + 'rad'
print 'use phasecenter: ' + phasecenter
qlookfitsdir = os.path.join(workdir, 'qlookfits/')
qlookfigdir = os.path.join(workdir, 'qlookimgs/')
imresfile = os.path.join(qlookfitsdir, '{}.imres.npz'.format(os.path.basename(vis)))
if overwrite:
imres = mk_qlook_image(vis, twidth=twidth, ncpu=ncpu, imagedir=qlookfitsdir, phasecenter=phasecenter, stokes=stokes,
c_external=True)
else:
if os.path.exists(imresfile):
imres = np.load(imresfile)
imres = imres['imres'].item()
else:
print('Image results file not found; Creating new images.')
imres = mk_qlook_image(vis, twidth=twidth, ncpu=ncpu, imagedir=qlookfitsdir, phasecenter=phasecenter, stokes=stokes,
c_external=True)
if not os.path.exists(qlookfigdir):
os.makedirs(qlookfigdir)
plt_qlook_image(imres, figdir=qlookfigdir, specdata=specdata, verbose=True, stokes=stokes, fov=xyrange)
else:
spec = specdata['spec']
(npol, nbl, nfreq, ntim) = spec.shape
tidx = range(ntim)
fidx = range(nfreq)
tim = specdata['tim']
freq = specdata['freq']
freqghz = freq / 1e9
spec_tim = Time(specdata['tim'] / 3600. / 24., format='mjd')
timstrr = spec_tim.plot_date
plt.ion()
fig = plt.figure(figsize=(12, 7), dpi=100)
gs1 = gridspec.GridSpec(3, 1)
gs1.update(left=0.08, right=0.32, wspace=0.05)
gs2 = gridspec.GridSpec(2, 2)
gs2.update(left=0.38, right=0.98, hspace=0.02, wspace=0.02)
spec_1 = np.absolute(spec[0, 0, :, :])
spec_2 = np.absolute(spec[1, 0, :, :])
if observatory == 'EVLA':
# circular feeds
polstr = ['RR', 'LL']
if observatory == 'EOVSA' or observatory == 'ALMA':
# linear feeds
polstr = ['XX', 'YY']
print 'plot the dynamic spectrum in pol ' + ' & '.join(polstr)
ax1 = plt.subplot(gs1[0])
ax1.pcolormesh(timstrr, freqghz, spec_1, cmap='jet', vmin=dmin, vmax=dmax)
ax1.set_xlim(timstrr[tidx[0]], timstrr[tidx[-1]])
ax1.xaxis_date()
ax1.xaxis.set_major_formatter(DateFormatter("%H:%M:%S"))
# ax1.set_xticklabels(['']*10)
ax1.set_ylim(freqghz[fidx[0]], freqghz[fidx[-1]])
ax1.set_ylabel('Frequency (GHz)', fontsize=10)
ax1.set_title(observatory + ' ' + datstr + ' ' + polstr[0] + ' & ' + polstr[1], fontsize=12)
ax1.set_autoscale_on(False)
ax1.add_patch(patches.Rectangle((bt, bfreqghz), et - bt, efreqghz - bfreqghz, ec='w', fill=False))
ax1.plot([(bt + et) / 2.], [(bfreqghz + efreqghz) / 2.], '*w', ms=12)
for tick in ax1.get_xticklabels():
tick.set_fontsize(8)
for tick in ax1.get_yticklabels():
tick.set_fontsize(8)
ax2 = plt.subplot(gs1[1])
ax2.pcolormesh(timstrr, freqghz, spec_2, cmap='jet', vmin=dmin, vmax=dmax)
ax2.set_xlim(timstrr[tidx[0]], timstrr[tidx[-1]])
ax2.xaxis_date()
ax2.xaxis.set_major_formatter(DateFormatter("%H:%M:%S"))
ax2.set_ylim(freqghz[fidx[0]], freqghz[fidx[-1]])
ax2.set_ylabel('Frequency (GHz)', fontsize=10)
for tick in ax2.get_xticklabels():
tick.set_fontsize(8)
for tick in ax2.get_yticklabels():
tick.set_fontsize(8)
ax2.set_autoscale_on(False)
ax2.add_patch(patches.Rectangle((bt, bfreqghz), et - bt, efreqghz - bfreqghz, ec='w', fill=False))
ax2.plot([(bt + et) / 2.], [(bfreqghz + efreqghz) / 2.], '*w', ms=12)
# Second part: GOES plot
if goestime:
btgoes = goestime[0]
etgoes = goestime[1]
else:
datstrg = datstr.replace('-', '/')
btgoes = datstrg + ' ' + qa.time(qa.quantity(tim[0] - 1800, 's'), form='clean', prec=9)[0]
etgoes = datstrg + ' ' + qa.time(qa.quantity(tim[tidx[-1] - 1] + 1800, 's'), form='clean', prec=9)[0]
if verbose:
print 'Acquire GOES soft X-ray data in from ' + btgoes + ' to ' + etgoes
ax3 = plt.subplot(gs1[2])
try:
from sunpy import lightcurve as lc
from sunpy.time import TimeRange
goest = lc.GOESLightCurve.create(TimeRange(btgoes, etgoes))
except:
goesscript = os.path.join(workdir, 'goes.py')
goesdatafile = os.path.join(workdir, 'goes.dat')
os.system('rm -rf {}'.format(goesscript))
fi = open(goesscript, 'wb')
fi.write('import os \n')
fi.write('from sunpy.time import TimeRange \n')
fi.write('from sunpy import lightcurve as lc \n')
fi.write('import pickle \n')
fi.write('goesplottim = TimeRange("{0}", "{1}") \n'.format(btgoes, etgoes))
fi.write('goes = lc.GOESLightCurve.create(goesplottim) \n')
fi.write('fi2 = open("{}", "wb") \n'.format(goesdatafile))
fi.write('pickle.dump(goes, fi2) \n')
fi.write('fi2.close()')
fi.close()
try:
os.system('python {}'.format(goesscript))
os.system('rm -rf {}'.format(goesscript))
except NameError:
print "Bad input names"
except ValueError:
print "Bad input values"
except:
print "Unexpected error:", sys.exc_info()[0]
print "Error in generating GOES light curves. Proceed without GOES..."
if os.path.exists(goesdatafile):
fi1 = file(goesdatafile, 'rb')
goest = pickle.load(fi1)
fi1.close()
try:
dates = mpl.dates.date2num(parse_time(goest.data.index))
goesdif = np.diff(goest.data['xrsb'])
gmax = np.nanmax(goesdif)
gmin = np.nanmin(goesdif)
ran = gmax - gmin
db = 2.8 / ran
goesdifp = goesdif * db + gmin + (-6)
ax3.plot_date(dates, np.log10(goest.data['xrsb']), '-', label='1.0--8.0 $\AA$', color='red', lw=2)
ax3.plot_date(dates[0:-1], goesdifp, '-', label='derivate', color='blue', lw=0.4)
ax3.set_ylim([-7, -3])
ax3.set_yticks([-7, -6, -5, -4, -3])
ax3.set_yticklabels([r'$10^{-7}$', r'$10^{-6}$', r'$10^{-5}$', r'$10^{-4}$', r'$10^{-3}$'])
ax3.set_title('Goes Soft X-ray', fontsize=12)
ax3.set_ylabel('Watts m$^{-2}$')
ax3.set_xlabel(datetime.datetime.isoformat(goest.data.index[0])[0:10])
ax3.axvspan(dates[899], dates[dates.size - 899], alpha=0.2)
ax2 = ax3.twinx()
# ax2.set_yscale("log")
ax2.set_ylim([-7, -3])
ax2.set_yticks([-7, -6, -5, -4, -3])
ax2.set_yticklabels(['B', 'C', 'M', 'X', ''])
ax3.yaxis.grid(True, 'major')
ax3.xaxis.grid(False, 'major')
ax3.legend(prop={'size': 6})
formatter = mpl.dates.DateFormatter('%H:%M')
ax3.xaxis.set_major_formatter(formatter)
ax3.fmt_xdata = mpl.dates.DateFormatter('%H:%M')
except:
print 'Error in downloading GOES soft X-ray data. Proceeding with out soft X-ray plot.'
# third part
# start to download the fits files
if plotaia:
if not aiafits:
newlist = []
items = glob.glob('*.fits')
for names in items:
str1 = starttim1.iso[:4] + '_' + starttim1.iso[5:7] + '_' + starttim1.iso[8:10] + 't' + starttim1.iso[
11:13] + '_' + starttim1.iso[14:16]
str2 = str(aiawave)
if names.endswith(".fits"):
if names.find(str1) != -1 and names.find(str2) != -1:
newlist.append(names)
newlist.append('0')
if newlist and os.path.exists(newlist[0]):
aiafits = newlist[0]
else:
print 'downloading the aiafits file'
wave1 = aiawave - 3
wave2 = aiawave + 3
t1 = Time(starttim1.mjd - 0.02 / 24., format='mjd')
t2 = Time(endtim1.mjd + 0.02 / 24., format='mjd')
try:
from sunpy.net import vso
client = vso.VSOClient()
qr = client.query(vso.attrs.Time(t1.iso, t2.iso), vso.attrs.Instrument('aia'), vso.attrs.Wave(wave1 * u.AA, wave2 * u.AA))
res = client.get(qr, path='{file}')
except:
SdoDownloadscript = os.path.join(workdir, 'SdoDownload.py')
os.system('rm -rf {}'.format(SdoDownloadscript))
fi = open(SdoDownloadscript, 'wb')
fi.write('from sunpy.net import vso \n')
fi.write('from astropy import units as u \n')
fi.write('client = vso.VSOClient() \n')
fi.write(
"qr = client.query(vso.attrs.Time('{0}', '{1}'), vso.attrs.Instrument('aia'), vso.attrs.Wave({2} * u.AA, {3} * u.AA)) \n".format(
t1.iso, t2.iso, wave1, wave2))
fi.write("res = client.get(qr, path='{file}') \n")
fi.close()
try:
os.system('python {}'.format(SdoDownloadscript))
except NameError:
print "Bad input names"
except ValueError:
print "Bad input values"
except:
print "Unexpected error:", sys.exc_info()[0]
print "Error in Downloading AIA fits files. Proceed without AIA..."
# Here something is needed to check whether it has finished downloading the fits files or not
if not aiafits:
newlist = []
items = glob.glob('*.fits')
for nm in items:
str1 = starttim1.iso[:4] + '_' + starttim1.iso[5:7] + '_' + starttim1.iso[8:10] + 't' + starttim1.iso[
11:13] + '_' + starttim1.iso[14:16]
str2 = str(aiawave)
if nm.find(str1) != -1 and nm.find(str2) != -1:
newlist.append(nm)
if newlist:
aiafits = newlist[0]
print 'AIA fits ' + aiafits + ' selected'
else:
print 'no AIA fits files found. Proceed without AIA'
try:
aiamap = smap.Map(aiafits)
except:
print 'error in reading aiafits. Proceed without AIA'
# RCP or I
ax4 = plt.subplot(gs2[0, 0])
ax5 = plt.subplot(gs2[1, 0])
# LCP or V
ax6 = plt.subplot(gs2[0, 1])
ax7 = plt.subplot(gs2[1, 1])
if fitsfile:
pass
else:
if not imagefile:
eph = hf.read_horizons(t0=Time(midtime_mjd, format='mjd'))
if observatory == 'EOVSA' or (not usemsphacenter):
print 'This is EOVSA data'
# use RA and DEC from FIELD ID 0
tb.open(vis+'/FIELD')
phadir = tb.getcol('PHASE_DIR').flatten()
tb.close()
ra0 = phadir[0]
dec0 = phadir[1]
if stokes == 'RRLL' or stokes == 'RR,LL':
print 'Provide stokes: ' + str(stokes) + '. However EOVSA has linear feeds. Force stokes to be IV'
stokes = 'I,V'
else:
ra0 = eph['ra'][0]
dec0 = eph['dec'][0]
if not xycen:
# use solar disk center as default
phasecenter = 'J2000 ' + str(ra0) + 'rad ' + str(dec0) + 'rad'
else:
x0 = np.radians(xycen[0]/3600.)
y0 = np.radians(xycen[1]/3600.)
p0 = np.radians(eph['p0'][0]) # p angle in radians
raoff = -((x0) * np.cos(p0) - y0 * np.sin(p0))/np.cos(eph['dec'][0])
decoff = (x0) * np.sin(p0) + y0 * np.cos(p0)
newra = ra0 + raoff
newdec = dec0 + decoff
phasecenter = 'J2000 ' + str(newra) + 'rad ' + str(newdec) + 'rad'
imagename = os.path.join(workdir, visname + '.outim')
if os.path.exists(imagename + '.image') or os.path.exists(imagename + '.flux'):
os.system('rm -rf ' + imagename + '.*')
sto = stokes.replace(',', '')
print 'do clean for ' + timerange + ' in spw ' + spw + ' stokes ' + sto
print 'Original phasecenter: '+ str(ra0) + str(dec0)
print 'use phasecenter: ' + phasecenter
clean(vis=vis, imagename=imagename, selectdata=True, spw=spw, timerange=timerange, stokes=sto,
niter=niter, interactive=interactive, npercycle=50, imsize=imsize, cell=cell, restoringbeam=restoringbeam,
weighting='briggs', robust=robust, phasecenter=phasecenter)
os.system('rm -rf ' + imagename + '.psf')
os.system('rm -rf ' + imagename + '.flux')
os.system('rm -rf ' + imagename + '.model')
os.system('rm -rf ' + imagename + '.mask')
os.system('rm -rf ' + imagename + '.residual')
imagefile = imagename + '.image'
fitsfile = imagefile + '.fits'
hf.imreg(vis=vis, ephem=eph, imagefile=imagefile, timerange=timerange, reftime=reftime, fitsfile=fitsfile, verbose=True, overwrite=True)
print 'fits file ' + fitsfile + ' selected'
ax4.cla()
ax5.cla()
ax6.cla()
ax7.cla()
rfits = fitsfile
try:
hdulist = fits.open(rfits)
hdu = hdulist[0]
(npol, nf, nx, ny) = hdu.data.shape
rmap = smap.Map(hdu.data[0, 0, :, :], hdu.header)
except:
print 'radio fits file not recognized by sunpy.map. Aborting...'
return -1
if npol > 1:
rmap1 = smap.Map(hdu.data[0, 0, :, :], hdu.header)
rmap2 = smap.Map(hdu.data[1, 0, :, :], hdu.header)
XX, YY = np.meshgrid(np.arange(rmap.data.shape[1]), np.arange(rmap.data.shape[0]))
try:
rmapx, rmapy = rmap.pixel_to_data(XX * u.pix, YY * u.pix)
except:
rmapxy = rmap.pixel_to_data(XX * u.pix, YY * u.pix)
rmapx = rmapxy.Tx
rmapy = rmapxy.Ty
if not xyrange:
if xycen:
x0 = xycen[0] * u.arcsec
y0 = xycen[1] * u.arcsec
if not xycen:
row, col = rmap1.data.shape
positon = np.nanargmax(rmap1.data)
m, n = divmod(positon, col)
x0 = rmap1.xrange[0] + rmap1.scale[1] * (n + 0.5) * u.pix
y0 = rmap1.yrange[0] + rmap1.scale[0] * (m + 0.5) * u.pix
if len(fov) == 1:
fov=[fov]*2
sz_x = fov[0] * u.arcsec
sz_y = fov[1] * u.arcsec
x1 = x0 - sz_x/2.
x2 = x0 + sz_x/2.
y1 = y0 - sz_y/2.
y2 = y0 + sz_y/2.
xyrange = [[x1.value, x2.value], [y1.value, y2.value]]
else:
sz_x = xyrange[0][1] - xyrange[0][0]
sz_y = xyrange[1][1] - xyrange[1][0]
clevels1 = np.linspace(0.2, 0.9, 5)
if stokes.split(',')[1] == 'V':
clevels2 = np.array([0.8, -0.6, -0.4, -0.2, 0.2, 0.4, 0.6, 0.8])
else:
clevels2 = np.linspace(0.2, 0.9, 5)
if 'aiamap' in vars():
aiamap.plot_settings['cmap'] = plt.get_cmap('binary')
if rmap:
title = 'AIA {0:.0f} + {1} {2:6.3f} GHz'.format(aiamap.wavelength.value, observatory, (bfreqghz + efreqghz) / 2.0)
else:
title = 'AIA {0:.0f}'.format(aiamap.wavelength.value)
aiamap.plot(axes=ax4)
ax4.set_title(title + ' ' + stokes.split(',')[0], fontsize=12)
aiamap.draw_limb()
aiamap.draw_grid()
aiamap.draw_rectangle((xyrange[0][0], xyrange[1][0]) * u.arcsec, sz_x, sz_y)
aiamap.plot(axes=ax6)
ax6.set_title(title + ' ' + stokes.split(',')[1], fontsize=12)
aiamap.draw_limb()
aiamap.draw_grid()
aiamap.draw_rectangle((xyrange[0][0], xyrange[1][0]) * u.arcsec, sz_x, sz_y)
if rmap:
ax4.contour(rmapx.value, rmapy.value, rmap1.data, levels=clevels1 * np.nanmax(rmap1.data), cmap=cm.jet)
ax6.contour(rmapx.value, rmapy.value, rmap2.data, levels=clevels2 * np.nanmax(rmap2.data), cmap=cm.RdBu)
ax4.text(0.02, 0.02, 'AIA {0:.0f} '.format(aiamap.wavelength.value) + aiamap.date.strftime('%H:%M:%S'),
verticalalignment='bottom', horizontalalignment='left', transform=ax4.transAxes, color='k',
fontsize=10)
ax6.text(0.02, 0.02, 'AIA {0:.0f} '.format(aiamap.wavelength.value) + aiamap.date.strftime('%H:%M:%S'),
verticalalignment='bottom', horizontalalignment='left', transform=ax6.transAxes, color='k',
fontsize=10)
else:
title = '{0} {1:6.3f} GHz'.format(observatory, (bfreqghz + efreqghz) / 2.0)
rmap1.plot(axes=ax4, cmap=cm.jet)
ax4.set_title(title + ' ' + stokes.split(',')[0], fontsize=12)
rmap1.draw_limb()
rmap1.draw_grid()
rmap1.draw_rectangle((xyrange[0][0], xyrange[1][0]) * u.arcsec, sz_x, sz_y)
rmap2.plot(axes=ax6, cmap=cm.RdBu)
ax6.set_title(title + ' ' + stokes.split(',')[1], fontsize=12)
rmap2.draw_limb()
rmap2.draw_grid()
# ax4.contour(rmapx.value, rmapy.value, rmap1.data, levels=np.linspace(0.2, 0.9, 5) * np.nanmax(rmap1.data),
# cmap=cm.gray)
# ax6.contour(rmapx.value, rmapy.value, rmap2.data, levels=np.linspace(0.2, 0.9, 5) * np.nanmax(rmap2.data),
# cmap=cm.gray)
rmap2.draw_rectangle((xyrange[0][0], xyrange[1][0]) * u.arcsec, sz_x, sz_y)
ax4.set_xlim(-1200, 1200)
ax4.set_ylim(-1200, 1200)
ax6.set_xlim(-1200, 1200)
ax6.set_ylim(-1200, 1200)
try:
subrmap1 = rmap1.submap(xyrange[0] * u.arcsec, xyrange[1] * u.arcsec)
subrmap2 = rmap2.submap(xyrange[0] * u.arcsec, xyrange[1] * u.arcsec)
except:
bl = SkyCoord(xyrange[0][0] * u.arcsec, xyrange[1][0] * u.arcsec, frame=rmap1.coordinate_frame)
tr = SkyCoord(xyrange[0][1] * u.arcsec, xyrange[1][1] * u.arcsec, frame=rmap1.coordinate_frame)
subrmap1 = rmap1.submap(bl, tr)
subrmap2 = rmap2.submap(bl, tr)
XX, YY = np.meshgrid(np.arange(subrmap1.data.shape[1]), np.arange(subrmap1.data.shape[0]))
try:
subrmapx, subrmapy = subrmap1.pixel_to_data(XX * u.pix, YY * u.pix)
except:
subrmapxy = subrmap1.pixel_to_data(XX * u.pix, YY * u.pix)
subrmapx = subrmapxy.Tx
subrmapy = subrmapxy.Ty
if 'aiamap' in vars():
try:
subaiamap = aiamap.submap(xyrange[0] * u.arcsec, xyrange[1] * u.arcsec)
except:
bl = SkyCoord(xyrange[0][0] * u.arcsec, xyrange[1][0] * u.arcsec, frame=aiamap.coordinate_frame)
tr = SkyCoord(xyrange[0][1] * u.arcsec, xyrange[1][1] * u.arcsec, frame=aiamap.coordinate_frame)
subaiamap = aiamap.submap(bl, tr)
subaiamap.plot(axes=ax5, title='')
subaiamap.draw_limb()
subaiamap.draw_grid()
subaiamap.plot(axes=ax7, title='')
subaiamap.draw_limb()
subaiamap.draw_grid()
ax5.contour(subrmapx.value, subrmapy.value, subrmap1.data, levels=clevels1 * np.nanmax(subrmap1.data), cmap=cm.jet)
ax7.contour(subrmapx.value, subrmapy.value, subrmap2.data, levels=clevels2 * np.nanmax(subrmap2.data),
cmap=cm.RdBu) # subaiamap.draw_rectangle((fov[0][0], fov[1][0]) * u.arcsec, 400 * u.arcsec, 400 * u.arcsec)
else:
subrmap1.plot(axes=ax5, cmap=cm.jet, title='')
subrmap1.draw_limb()
subrmap1.draw_grid()
subrmap2.plot(axes=ax7, cmap=cm.RdBu, title='')
subrmap2.draw_limb()
subrmap2.draw_grid() # ax5.contour(subrmapx.value, subrmapy.value, subrmap1.data, # levels=clevels1 * np.nanmax(subrmap1.data), cmap=cm.gray) # ax7.contour(subrmapx.value, subrmapy.value, subrmap2.data, # levels=clevels2 * np.nanmax(subrmap2.data), cmap=cm.gray) # subrmap1.draw_rectangle((fov[0][0], fov[1][0]) * u.arcsec, 400 * u.arcsec, 400 * u.arcsec) # subrmap2.draw_rectangle((fov[0][0], fov[1][0]) * u.arcsec, 400 * u.arcsec, 400 * u.arcsec)
ax5.set_xlim(xyrange[0])
ax5.set_ylim(xyrange[1])
ax5.text(0.02, 0.02, observatory + ' ' + rmap.date.strftime('%H:%M:%S.%f')[:-3], verticalalignment='bottom',
horizontalalignment='left', transform=ax5.transAxes, color='k', fontsize=10)
ax7.set_xlim(xyrange[0])
ax7.set_ylim(xyrange[1])
ax7.text(0.02, 0.02, observatory + ' ' + rmap.date.strftime('%H:%M:%S.%f')[:-3], verticalalignment='bottom',
horizontalalignment='left', transform=ax7.transAxes, color='k', fontsize=10)
fig.show()
def make_ephem(vis, ephemfile=None):
'''
make ephemeris table from JPLhorizon:
Cautioned that the tab created in CASA 5+ lacks many columns such as Rho, RadVel, etc., which are essential for fixplanets
The issue comes from a update on jplreader after 2015. some keys are not write to the ephemeris table.
This only works with CASA 4+
:param vis:
:param ephemfile:
:return:
'''
import urllib2, ssl
from taskinit import tb
quantities = ['1', '14', '15', '17', '19', '20', '24', '32']
quantities = ','.join(quantities)
tb.open(vis + '/OBSERVATION')
trs = {'BegTime': [], 'EndTime': []}
for ll in range(tb.nrows()):
tim0, tim1 = Time(tb.getcell('TIME_RANGE', ll) / 24 / 3600,
format='mjd')
trs['BegTime'].append(tim0)
trs['EndTime'].append(tim1)
tb.close()
trs['BegTime'] = Time(trs['BegTime'])
trs['EndTime'] = Time(trs['EndTime'])
btime = np.min(trs['BegTime'])
etime = np.max(trs['EndTime'])
print("Beginning time of this scan " + btime.iso)
print("End time of this scan " + etime.iso)
btime = Time((btime.mjd - 1.0 / 60 / 24), format='mjd')
etime = Time((etime.mjd + 1.0 / 60 / 24), format='mjd')
startdate = btime.iso.replace(' ', ',')[:-7]
enddate = etime.iso.replace(' ', ',')[:-7]
cmd = [
"COMMAND= '10'", "CENTER= '-5@399'", "MAKE_EPHEM= 'YES'",
"TABLE_TYPE= 'OBSERVER'",
"START_TIME= '%s'" % startdate,
"STOP_TIME= '%s'" % enddate, "STEP_SIZE= '1m'", "CAL_FORMAT= 'CAL'",
"TIME_DIGITS= 'MINUTES'", "ANG_FORMAT= 'DEG'", "OUT_UNITS= 'KM-S'",
"RANGE_UNITS= 'AU'", "APPARENT= 'AIRLESS'", "SOLAR_ELONG= '0,180'",
"SUPPRESS_RANGE_RATE= 'NO'", "SKIP_DAYLT= 'NO'", "EXTRA_PREC= 'NO'",
"R_T_S_ONLY= 'NO'", "REF_SYSTEM= 'J2000'", "CSV_FORMAT= 'YES'",
"OBJ_DATA= 'YES'", "TIME_DIGITS ='MIN'",
"QUANTITIES= '{}'".format(quantities)
]
cmdstr = "http://ssd.jpl.nasa.gov/horizons_batch.cgi?batch=l&" + '&'.join(
cmd)
try:
context = ssl._create_unverified_context()
f = urllib2.urlopen(cmdstr, context=context)
except:
f = urllib2.urlopen(cmdstr)
lines = f.readlines()
f.close()
istart = 0
for i, l in enumerate(lines):
if l[0:5] == '$$SOE': # start recording
istart = i + 1
if l[0:5] == '$$EOE': # end recording
iend = i
if not ephemfile:
ephemfile = 'sun-ephem-geo.txt'
with open(ephemfile, 'w') as fb:
for i, l in enumerate(lines):
if i == istart - 3:
fb.write(
' Date__(UT)__HR:MN R.A.___(J2000.0)___DEC. Ob-lon Ob-lat Sl-lon Sl-lat NP.ang NP.dist r rdot delta deldot S-T-O'
)
if i >= istart and i < iend:
l_s = l.split(',')
l_s.pop(1)
l_s.pop(1)
fb.write(' '.join(l_s))
else:
fb.write(l)
# with open(ephemfile,'w') as fb:
# for i,l in enumerate(lines):
# fb.write(l.replace('*m','').replace('*t',''))
return ephemfile
