def test_readAndParseTbuff(self):
'''flaghelper: compare the read and parse and apply tbuff'''
print ''
# MJD in seconds of timeranges are these
# <startTime>4891227930515540000 <endTime>4891227932453838000
# <startTime>4891228473545856000 <endTime>4891228473731891000
# <startTime>4891226924455911000 <endTime>4891226927502314000
# <startTime>4891228838164987000 <endTime>4891228838418996000
# <startTime>4891228609440808000 <endTime>4891228612489617000
online = ["antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'",
"antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'",
"antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'",
"antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'",
"antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'"]
myinput = "antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'\n"\
"antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'\n"\
"antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'\n"\
"antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'\n"\
"antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'"
filename1 = 'flaghelperonline2.txt'
create_input(myinput, filename1)
# First timerange from online before padding
origt = timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'
# Apply tbuff to timeranges
timebuffer = 1.1
dlist1 = fh.readAndParse([filename1], tbuff=timebuffer)
self.assertEqual(len(dlist1), 5)
# Get the first padded timerange from output
padt = dlist1[0]['timerange']
# Revert the tbuff application manually
t0,t1 = padt.split('~',1)
startTime = qa.totime(t0)['value']
startTimeSec = float((startTime * 24 * 3600) + timebuffer)
startTimeSec = qa.quantity(startTimeSec, 's')
paddedT0 = qa.time(startTimeSec,form='ymd',prec=9)[0]
# end time
endTime = qa.totime(t1)['value']
endTimeSec = float((endTime * 24 * 3600) - timebuffer)
endTimeSec = qa.quantity(endTimeSec, 's')
paddedT1 = qa.time(endTimeSec,form='ymd',prec=9)[0]
newtimerange = paddedT0+'~'+paddedT1
# Compare with the original
self.assertEqual(origt, newtimerange)
# Compare with original values from Flag.xml
xmlt0 = float(4891227930515540000) * 1.0E-9
xmlt1 = float(4891227932453838000) * 1.0E-9
self.assertAlmostEqual(xmlt0, startTimeSec['value'], places=3)
self.assertAlmostEqual(xmlt1, endTimeSec['value'], places=3)
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 randomCoords(imagenames, ncoords=10):
import random
from taskinit import ia, qa
xmin, xmax = [], []
ymin, ymax = [], []
for image in imagenames:
ia.open(image)
print image, ia.boundingbox()
trc = ia.boundingbox()['trcf'].split(', ')
blc = ia.boundingbox()['blcf'].split(', ')
xmin.append(qa.convert(qa.quantity(trc[0]), 'rad')['value'])
xmax.append(qa.convert(qa.quantity(blc[0]), 'rad')['value'])
ymin.append(qa.convert(qa.quantity(blc[1]), 'rad')['value'])
ymax.append(qa.convert(qa.quantity(trc[1]), 'rad')['value'])
ia.done()
randomcoords = CoordList(imagenames)
for i in range(ncoords):
imageid = random.randint(0, len(imagenames) - 1)
x = random.uniform(xmin[imageid], xmax[imageid])
y = random.uniform(ymin[imageid], ymax[imageid])
c = Coord(x, y, 1.0)
randomcoords.append(c)
return randomcoords
def __axis(self, idx, unit):
refpix = self.coordsys.referencepixel()['numeric'][idx]
refval = self.coordsys.referencevalue()['numeric'][idx]
increment = self.coordsys.increment()['numeric'][idx]
_unit = self.units[idx]
if _unit != unit:
refval = qa.convert(qa.quantity(refval,_unit),unit)['value']
increment = qa.convert(qa.quantity(increment,_unit),unit)['value']
#return numpy.array([refval+increment*(i-refpix) for i in xrange(self.nchan)])
return (refpix, refval, increment)
def __axis(self, idx, unit):
refpix = self.coordsys.referencepixel()['numeric'][idx]
refval = self.coordsys.referencevalue()['numeric'][idx]
increment = self.coordsys.increment()['numeric'][idx]
_unit = self.units[idx]
if _unit != unit:
refval = qa.convert(qa.quantity(refval,_unit),unit)['value']
increment = qa.convert(qa.quantity(increment,_unit),unit)['value']
#return numpy.array([refval+increment*(i-refpix) for i in xrange(self.nchan)])
return (refpix, refval, increment)
def select(self, rowid=None, rasterid=None):
if not ((rowid is None) ^ (rasterid is None)):
raise RuntimeError('one of rowid or rasterid must be specified')
if (rowid is not None) and (rowid >= self.nrow):
raise IndexError('row index %s is out of range (number of rows detected: %s)'%(rowid,self.nrow))
if (rasterid is not None) and (rasterid >= self.nraster):
raise IndexError('row index %s is out of range (number of rasters detected: %s)'%(rasterid,self.nraster))
with selection_manager(self.scantab, self.original_selection, types=0, ifs=self.spw, pols=self.pol) as s:
alltimes = numpy.array(map(lambda x: qa.quantity(x)['value'], s.get_time(prec=16)))
mean_interval = numpy.array(s.get_inttime()).mean()
self.margin = 0.1 * mean_interval
mjd_margin = self.margin / 86400.0
if rowid is not None:
times = alltimes[self.gaplist[rowid]:self.gaplist[rowid+1]]
else:
times = alltimes[self.gaplist_raster[rasterid]:self.gaplist_raster[rasterid+1]]
tmp_mjd_range = (times.min() - mjd_margin, times.max() + mjd_margin,)
tmp_mjd_range_nomargin = (times.min(), times.max(),)
casalog.post('time range: %s ~ %s'%(tmp_mjd_range_nomargin), priority='DEBUG')
if rowid is not None:
self.mjd_range = tmp_mjd_range
self.mjd_range_nomargin = tmp_mjd_range_nomargin
else:
self.mjd_range_raster = tmp_mjd_range
self.mjd_range_nomargin_raster = tmp_mjd_range_nomargin
def select(self, rowid=None, rasterid=None):
if not ((rowid is None) ^ (rasterid is None)):
raise RuntimeError('one of rowid or rasterid must be specified')
if (rowid is not None) and (rowid >= self.nrow):
raise IndexError('row index %s is out of range (number of rows detected: %s)'%(rowid,self.nrow))
if (rasterid is not None) and (rasterid >= self.nraster):
raise IndexError('row index %s is out of range (number of rasters detected: %s)'%(rasterid,self.nraster))
with selection_manager(self.scantab, self.original_selection, types=0, ifs=self.spw, pols=self.pol) as s:
alltimes = numpy.array(map(lambda x: qa.quantity(x)['value'], s.get_time(prec=16)))
mean_interval = numpy.array(s.get_inttime()).mean()
self.margin = 0.1 * mean_interval
mjd_margin = self.margin / 86400.0
if rowid is not None:
times = alltimes[self.gaplist[rowid]:self.gaplist[rowid+1]]
else:
times = alltimes[self.gaplist_raster[rasterid]:self.gaplist_raster[rasterid+1]]
tmp_mjd_range = (times.min() - mjd_margin, times.max() + mjd_margin,)
tmp_mjd_range_nomargin = (times.min(), times.max(),)
casalog.post('time range: %s ~ %s'%(tmp_mjd_range_nomargin), priority='DEBUG')
if rowid is not None:
self.mjd_range = tmp_mjd_range
self.mjd_range_nomargin = tmp_mjd_range_nomargin
else:
self.mjd_range_raster = tmp_mjd_range
self.mjd_range_nomargin_raster = tmp_mjd_range_nomargin
def detect_gap(scantab, spw, pol):
with selection_manager(scantab, scantab.get_selection(), types=0, ifs=spw, pols=pol) as s:
alldir = numpy.array([s.get_directionval(i) for i in xrange(s.nrow())]).transpose()
timestamp = numpy.array(map(lambda x: qa.quantity(x)['value'], s.get_time(prec=16)))
row_gap = _detect_gap(timestamp)
ras_gap = _detect_gap_raster(timestamp, alldir, row_gap=row_gap)
return row_gap, ras_gap
def detect_gap(scantab, spw, pol):
with selection_manager(scantab, scantab.get_selection(), types=0, ifs=spw, pols=pol) as s:
alldir = numpy.array([s.get_directionval(i) for i in xrange(s.nrow())]).transpose()
timestamp = numpy.array(map(lambda x: qa.quantity(x)['value'], s.get_time(prec=16)))
row_gap = _detect_gap(timestamp)
ras_gap = _detect_gap_raster(timestamp, alldir, row_gap=row_gap)
return row_gap, ras_gap
def asdatestring(mjd, digit, timeonly=False):
datedict = qa.splitdate(qa.quantity(mjd, 'd'))
if digit > 10 : digit = 10
sstr_tmp = str(numpy.round(datedict['s'], digit)).split('.')
sstr = sstr_tmp[0] + '.' + sstr_tmp[1][0:digit]
if timeonly:
return '%s:%s:%s'%(datedict['hour'],datedict['min'],sstr)
else:
return '%s/%s/%s/%s:%s:%s'%(datedict['year'],datedict['month'],datedict['monthday'],datedict['hour'],datedict['min'],sstr)
def asdatestring(mjd, digit, timeonly=False):
datedict = qa.splitdate(qa.quantity(mjd, 'd'))
if digit > 10 : digit = 10
sstr_tmp = str(numpy.round(datedict['s'], digit)).split('.')
sstr = sstr_tmp[0] + '.' + sstr_tmp[1][0:digit]
if timeonly:
return '%s:%s:%s'%(datedict['hour'],datedict['min'],sstr)
else:
return '%s/%s/%s/%s:%s:%s'%(datedict['year'],datedict['month'],datedict['monthday'],datedict['hour'],datedict['min'],sstr)
def to_velocity(self, frequency, freq_unit='GHz', restfreq=None):
rest_frequency = self.coordsys.restfrequency()
# user-defined rest frequency takes priority
if restfreq is not None:
vrf = qa.convert(qa.quantity(restfreq), freq_unit)['value']
elif rest_frequency['unit'] != freq_unit:
vrf = qa.convert(rest_frequency, freq_unit)['value']
else:
vrf = rest_frequency['value']
return (1.0 - (frequency / vrf)) * LightSpeed
def to_velocity(self, frequency, freq_unit='GHz', restfreq=None):
rest_frequency = self.coordsys.restfrequency()
# user-defined rest frequency takes priority
if restfreq is not None:
vrf = qa.convert(qa.quantity(restfreq), freq_unit)['value']
elif rest_frequency['unit'] != freq_unit:
vrf = qa.convert(rest_frequency, freq_unit)['value']
else:
vrf = rest_frequency['value']
return (1.0 - (frequency / vrf)) * LightSpeed
def format_coord(x, y):
col = np.argmin(np.absolute(tim - x))
row = np.argmin(np.absolute(freqghz - y))
if col >= 0 and col < ntim and row >= 0 and row < nfreq:
timv = tim[col]
timstr = qa.time(qa.quantity(timv, 's'),
form='clean',
prec=9)[0]
flux = spec_plt[row, col]
return 'time {0} = {1}, freq = {2:.3f} GHz, flux = {3:.2f} Jy'.format(
col, timstr, y, flux)
else:
return 'x = {0}, y = {1:.3f}'.format(x, y)
def coordsTocl(name, flux, coords):
from taskinit import cl, qa
flux = qa.quantity(flux)
cl.done()
cl.rename(name)
for coord in coords:
clpars = {}
clpars['flux'] = -flux['value']
clpars['fluxunit'] = flux['unit']
clpars['dir'] = ['J2000', str(coord.x) + 'rad', str(coord.y) + 'rad']
clpars['shape'] = 'point'
cl.addcomponent(**clpars)
cl.done()
def read_msinfo(vis=None, msinfofile=None):
# read MS information #
msinfo = dict.fromkeys(['vis', 'scans', 'fieldids', 'btimes', 'btimestr', \
'inttimes', 'ras', 'decs'])
ms.open(vis)
scans = ms.getscansummary()
scanids = sorted(scans.keys(), key=lambda x: int(x))
nscanid = len(scanids)
btimes = []
btimestr = []
etimes = []
fieldids = []
inttimes = []
dirs = []
ras = []
decs = []
for i in range(nscanid):
btimes.append(scans[scanids[i]]['0']['BeginTime'])
etimes.append(scans[scanids[i]]['0']['EndTime'])
fieldid = scans[scanids[i]]['0']['FieldId']
fieldids.append(fieldid)
dir = ms.getfielddirmeas('PHASE_DIR', fieldid)
dirs.append(dir)
ras.append(dir['m0'])
decs.append(dir['m1'])
inttimes.append(scans[scanids[i]]['0']['IntegrationTime'])
ms.close()
btimestr = [qa.time(qa.quantity(btimes[i], 'd'), form='fits', prec=10)[0] \
for i in range(nscanid)]
msinfo['vis'] = vis
msinfo['scans'] = scans
msinfo['fieldids'] = fieldids
msinfo['btimes'] = btimes
msinfo['btimestr'] = btimestr
msinfo['inttimes'] = inttimes
msinfo['ras'] = ras
msinfo['decs'] = decs
if msinfofile:
np.savez(msinfofile, vis=vis, scans=scans, fieldids=fieldids, \
btimes=btimes, btimestr=btimestr, inttimes=inttimes, \
ras=ras, decs=decs)
return msinfo
def parse_figsize(figsize):
"""
return figsize in inches
"""
casalog.post('parse_figsize input: {input}'.format(input=figsize),
priority='DEBUG')
parsed = None
if figsize is not None and isinstance(figsize, str) and len(figsize) > 0:
size_list = figsize.split(',')
size_inch_list = [
x / 25.4 for s in size_list
for x in qa.getvalue(qa.convert(qa.quantity(s), outunit='mm'))
]
if len(size_inch_list) == 1:
s = size_inch_list[0]
parsed = (s, s)
else:
parsed = tuple(size_inch_list[:2])
casalog.post('parse_figsize output: {output}'.format(output=parsed),
priority='DEBUG')
return parsed
def parse_figsize(figsize):
"""
return figsize in inches
"""
casalog.post('parse_figsize input: {input}'.format(input=figsize), priority='DEBUG')
parsed = None
if figsize is not None and isinstance(figsize, str) and len(figsize) > 0:
size_list = figsize.split(',')
size_inch_list = [x / 25.4 for s in size_list for x in qa.getvalue(qa.convert(qa.quantity(s),outunit='mm'))]
if len(size_inch_list) == 1:
s = size_inch_list[0]
parsed = (s, s)
else:
parsed = tuple(size_inch_list[:2])
casalog.post('parse_figsize output: {output}'.format(output=parsed), priority='DEBUG')
return parsed
def imreg(vis=None,
ephem=None,
msinfo=None,
imagefile=None,
timerange=None,
reftime=None,
fitsfile=None,
beamfile=None,
offsetfile=None,
toTb=None,
scl100=None,
verbose=False,
p_ang=False,
overwrite=True,
usephacenter=True,
deletehistory=False):
'''
main routine to register CASA images
Required Inputs:
vis: STRING. CASA measurement set from which the image is derived
imagefile: STRING or LIST. name of the input CASA image
timerange: STRING or LIST. timerange used to generate the CASA image, must have the same length as the input images.
Each element should be in CASA standard time format, e.g., '2012/03/03/12:00:00~2012/03/03/13:00:00'
Optional Inputs:
msinfo: DICTIONARY. CASA MS information, output from read_msinfo. If not provided, generate one from the supplied vis
ephem: DICTIONARY. solar ephem, output from read_horizons.
If not provided, query JPL Horizons based on time info of the vis (internet connection required)
fitsfile: STRING or LIST. name of the output registered fits files
reftime: STRING or LIST. Each element should be in CASA standard time format, e.g., '2012/03/03/12:00:00'
offsetfile: optionally provide an offset with a series of solar x and y offsets with timestamps
toTb: Bool. Convert the default Jy/beam to brightness temperature?
scl100: Bool. If True, scale the image values up by 100 (to compensate VLA 20 dB attenuator)
verbose: Bool. Show more diagnostic info if True.
usephacenter: Bool -- if True, correct for the RA and DEC in the ms file based on solar empheris.
Otherwise assume the phasecenter is correctly pointed to the solar disk center
(EOVSA case)
'''
ia = iatool()
if deletehistory:
msclearhistory(vis)
if verbose:
import time
t0 = time.time()
prtidx = 1
print('point {}: {}'.format(prtidx, time.time() - t0))
prtidx += 1
if not imagefile:
raise ValueError, 'Please specify input image'
if not timerange:
raise ValueError, 'Please specify timerange of the input image'
if type(imagefile) == str:
imagefile = [imagefile]
if type(timerange) == str:
timerange = [timerange]
if not fitsfile:
fitsfile = [img + '.fits' for img in imagefile]
if type(fitsfile) == str:
fitsfile = [fitsfile]
nimg = len(imagefile)
if len(timerange) != nimg:
raise ValueError, 'Number of input images does not equal to number of timeranges!'
if len(fitsfile) != nimg:
raise ValueError, 'Number of input images does not equal to number of output fits files!'
nimg = len(imagefile)
if verbose:
print str(nimg) + ' images to process...'
if verbose:
print('point {}: {}'.format(prtidx, time.time() - t0))
prtidx += 1
if reftime: # use as reference time to find solar disk RA and DEC to register the image, but not the actual timerange associated with the image
if type(reftime) == str:
reftime = [reftime] * nimg
if len(reftime) != nimg:
raise ValueError, 'Number of reference times does not match that of input images!'
helio = ephem_to_helio(vis,
ephem=ephem,
msinfo=msinfo,
reftime=reftime,
usephacenter=usephacenter)
else:
# use the supplied timerange to register the image
helio = ephem_to_helio(vis,
ephem=ephem,
msinfo=msinfo,
reftime=timerange,
usephacenter=usephacenter)
if verbose:
print('point {}: {}'.format(prtidx, time.time() - t0))
prtidx += 1
for n, img in enumerate(imagefile):
if verbose:
print 'processing image #' + str(n)
fitsf = fitsfile[n]
timeran = timerange[n]
# obtain duration of the image as FITS header exptime
try:
[tbg0, tend0] = timeran.split('~')
tbg_d = qa.getvalue(qa.convert(qa.totime(tbg0), 'd'))[0]
tend_d = qa.getvalue(qa.convert(qa.totime(tend0), 'd'))[0]
tdur_s = (tend_d - tbg_d) * 3600. * 24.
dateobs = qa.time(qa.quantity(tbg_d, 'd'), form='fits', prec=10)[0]
except:
print 'Error in converting the input timerange: ' + str(
timeran) + '. Proceeding to the next image...'
continue
if verbose:
print('point {}: {}'.format(prtidx, time.time() - t0))
prtidx += 1
hel = helio[n]
if not os.path.exists(img):
raise ValueError, 'Please specify input image'
if os.path.exists(fitsf) and not overwrite:
raise ValueError, 'Specified fits file already exists and overwrite is set to False. Aborting...'
else:
p0 = hel['p0']
ia.open(img)
imr = ia.rotate(pa=str(-p0) + 'deg')
imr.tofits(fitsf, history=False, overwrite=overwrite)
imr.close()
imsum = ia.summary()
ia.close()
if verbose:
print('point {}: {}'.format(prtidx, time.time() - t0))
prtidx += 1
# construct the standard fits header
# RA and DEC of the reference pixel crpix1 and crpix2
(imra, imdec) = (imsum['refval'][0], imsum['refval'][1])
# find out the difference of the image center to the CASA phase center
# RA and DEC difference in arcseconds
ddec = degrees((imdec - hel['dec_fld'])) * 3600.
dra = degrees((imra - hel['ra_fld']) * cos(hel['dec_fld'])) * 3600.
# Convert into image heliocentric offsets
prad = -radians(hel['p0'])
dx = (-dra) * cos(prad) - ddec * sin(prad)
dy = (-dra) * sin(prad) + ddec * cos(prad)
if offsetfile:
try:
offset = np.load(offsetfile)
except:
raise ValueError, 'The specified offsetfile does not exist!'
reftimes_d = offset['reftimes_d']
xoffs = offset['xoffs']
yoffs = offset['yoffs']
timg_d = hel['reftime']
ind = bisect.bisect_left(reftimes_d, timg_d)
xoff = xoffs[ind - 1]
yoff = yoffs[ind - 1]
else:
xoff = hel['refx']
yoff = hel['refy']
if verbose:
print 'offset of image phase center to visibility phase center (arcsec): ', dx, dy
print 'offset of visibility phase center to solar disk center (arcsec): ', xoff, yoff
(crval1, crval2) = (xoff + dx, yoff + dy)
# update the fits header to heliocentric coordinates
if verbose:
print('point {}: {}'.format(prtidx, time.time() - t0))
prtidx += 1
hdu = pyfits.open(fitsf, mode='update')
if verbose:
print('point {}: {}'.format(prtidx, time.time() - t0))
prtidx += 1
header = hdu[0].header
(cdelt1,
cdelt2) = (-header['cdelt1'] * 3600., header['cdelt2'] * 3600.
) # Original CDELT1, 2 are for RA and DEC in degrees
header['cdelt1'] = cdelt1
header['cdelt2'] = cdelt2
header['cunit1'] = 'arcsec'
header['cunit2'] = 'arcsec'
header['crval1'] = crval1
header['crval2'] = crval2
header['ctype1'] = 'HPLN-TAN'
header['ctype2'] = 'HPLT-TAN'
header['date-obs'] = dateobs # begin time of the image
if not p_ang:
hel['p0'] = 0
try:
# this works for pyfits version of CASA 4.7.0 but not CASA 4.6.0
if tdur_s:
header.set('exptime', tdur_s)
else:
header.set('exptime', 1.)
header.set('p_angle', hel['p0'])
header.set('dsun_obs',
sun.sunearth_distance(Time(dateobs)).to(u.meter).value)
header.set(
'rsun_obs',
sun.solar_semidiameter_angular_size(Time(dateobs)).value)
header.set('rsun_ref', sun.constants.radius.value)
header.set('hgln_obs', 0.)
header.set('hglt_obs',
sun.heliographic_solar_center(Time(dateobs))[1].value)
except:
# this works for astropy.io.fits
if tdur_s:
header.append(('exptime', tdur_s))
else:
header.append(('exptime', 1.))
header.append(('p_angle', hel['p0']))
header.append(
('dsun_obs',
sun.sunearth_distance(Time(dateobs)).to(u.meter).value))
header.append(
('rsun_obs',
sun.solar_semidiameter_angular_size(Time(dateobs)).value))
header.append(('rsun_ref', sun.constants.radius.value))
header.append(('hgln_obs', 0.))
header.append(
('hglt_obs',
sun.heliographic_solar_center(Time(dateobs))[1].value))
if verbose:
print('point {}: {}'.format(prtidx, time.time() - t0))
prtidx += 1
# update intensity units, i.e. to brightness temperature?
if toTb:
# get restoring beam info
(bmajs, bmins, bpas, beamunits,
bpaunits) = getbeam(imagefile=imagefile, beamfile=beamfile)
bmaj = bmajs[n]
bmin = bmins[n]
beamunit = beamunits[n]
data = hdu[
0].data # remember the data order is reversed due to the FITS convension
dim = data.ndim
sz = data.shape
keys = header.keys()
values = header.values()
# which axis is frequency?
faxis = keys[values.index('FREQ')][-1]
faxis_ind = dim - int(faxis)
if header['BUNIT'].lower() == 'jy/beam':
header['BUNIT'] = 'K'
header['BTYPE'] = 'Brightness Temperature'
for i in range(sz[faxis_ind]):
nu = header['CRVAL' + faxis] + header['CDELT' + faxis] * (
i + 1 - header['CRPIX' + faxis])
if header['CUNIT' + faxis] == 'KHz':
nu *= 1e3
if header['CUNIT' + faxis] == 'MHz':
nu *= 1e6
if header['CUNIT' + faxis] == 'GHz':
nu *= 1e9
if len(bmaj) > 1: # multiple (per-plane) beams
bmajtmp = bmaj[i]
bmintmp = bmin[i]
else: # one single beam
bmajtmp = bmaj[0]
bmintmp = bmin[0]
if beamunit == 'arcsec':
bmaj0 = np.radians(bmajtmp / 3600.)
bmin0 = np.radians(bmajtmp / 3600.)
if beamunit == 'arcmin':
bmaj0 = np.radians(bmajtmp / 60.)
bmin0 = np.radians(bmintmp / 60.)
if beamunit == 'deg':
bmaj0 = np.radians(bmajtmp)
bmin0 = np.radians(bmintmp)
if beamunit == 'rad':
bmaj0 = bmajtmp
bmin0 = bmintmp
beam_area = bmaj0 * bmin0 * np.pi / (4. * log(2.))
k_b = qa.constants('k')['value']
c_l = qa.constants('c')['value']
factor = 2. * k_b * nu**2 / c_l**2 # SI unit
jy_to_si = 1e-26
# print nu/1e9, beam_area, factor
factor2 = 1.
if scl100:
factor2 = 100.
if faxis == '3':
data[:,
i, :, :] *= jy_to_si / beam_area / factor * factor2
if faxis == '4':
data[
i, :, :, :] *= jy_to_si / beam_area / factor * factor2
if verbose:
print('point {}: {}'.format(prtidx, time.time() - t0))
prtidx += 1
hdu.flush()
hdu.close()
if verbose:
print('point {}: {}'.format(prtidx, time.time() - t0))
prtidx += 1
def subvs(vis=None,
outputvis=None,
timerange=None,
spw=None,
subtime1=None,
subtime2=None,
splitsel=True,
reverse=False,
overwrite=False):
"""Perform vector subtraction for visibilities
Keyword arguments:
vis -- Name of input visibility file (MS)
default: none; example: vis='ngc5921.ms'
outputvis -- Name of output uv-subtracted visibility file (MS)
default: none; example: outputvis='ngc5921_src.ms'
timerange -- Time range of performing the UV subtraction:
default='' means all times. examples:
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
timerange = 'hh:mm:ss~hh:mm:ss'
spw -- Select spectral window/channel.
default = '' all the spectral channels. Example: spw='0:1~20'
subtime1 -- Time range 1 of the background to be subtracted from the data
default='' means all times. format:
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
timerange = 'hh:mm:ss~hh:mm:ss'
subtime2 -- Time range 2 of the backgroud to be subtracted from the data
default='' means all times. examples:
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
timerange = 'hh:mm:ss~hh:mm:ss'
splitsel -- True or False. default = False. If splitsel = False, then the entire input
measurement set is copied as the output measurement set (outputvis), with
background subtracted at selected timerange and spectral channels.
If splitsel = True,then only the selected timerange and spectral channels
are copied into the output measurement set (outputvis).
reverse -- True or False. default = False. If reverse = False, then the times indicated
by subtime1 and/or subtime2 are treated as background and subtracted; If reverse
= True, then reverse the sign of the background-subtracted data. The option can
be used for mapping absorptive structure.
overwrite -- True or False. default = False. If overwrite = True and
outputvis already exists, the selected subtime and spw in the
output measurment set will be replaced with background subtracted
visibilities
"""
#check the visbility ms
if not outputvis or outputvis.isspace():
raise ValueError, 'Please specify outputvis'
if os.path.exists(outputvis):
if overwrite:
print "The already existing output measurement set will be updated."
else:
raise ValueError, "Output MS %s already exists - will not overwrite." % outputvis
else:
if not splitsel:
shutil.copytree(vis, outputvis)
else:
ms.open(vis, nomodify=True)
ms.split(outputvis, spw=spw, time=timerange, whichcol='DATA')
ms.close()
#define and check the time ranges
if subtime1 and (type(subtime1) == str):
[bsubtime1, esubtime1] = subtime1.split('~')
bsubtime1sec = qa.getvalue(qa.convert(qa.totime(bsubtime1), 's'))
esubtime1sec = qa.getvalue(qa.convert(qa.totime(esubtime1), 's'))
timebin1sec = esubtime1sec - bsubtime1sec
if timebin1sec < 0:
raise Exception, 'Negative timebin! Please check the "subtime1" parameter.'
casalog.post('Selected timerange 1: ' + subtime1 +
' as background for uv subtraction.')
else:
raise Exception, 'Please enter at least one timerange as the background'
if subtime2 and (type(subtime2) == str):
[bsubtime2, esubtime2] = subtime2.split('~')
bsubtime2sec = qa.getvalue(qa.convert(qa.totime(bsubtime2), 's'))
esubtime2sec = qa.getvalue(qa.convert(qa.totime(esubtime2), 's'))
timebin2sec = esubtime2sec - bsubtime2sec
if timebin2sec < 0:
raise Exception, 'Negative timebin! Please check the "subtime2" parameter.'
timebin2 = str(timebin2sec) + 's'
casalog.post('Selected timerange 2: ' + subtime2 +
' as background for uv subtraction.')
#plus 1s is to ensure averaging over the entire timerange
else:
casalog.post(
'Timerange 2 not selected, using only timerange 1 as background')
if timerange and (type(timerange) == str):
[btimeo, etimeo] = timerange.split('~')
btimeosec = qa.getvalue(qa.convert(qa.totime(btimeo), 's'))
etimeosec = qa.getvalue(qa.convert(qa.totime(etimeo), 's'))
timebinosec = etimeosec - btimeosec
if timebinosec < 0:
raise Exception, 'Negative timebin! Please check the "timerange" parameter.'
casalog.post('Selected timerange: ' + timerange +
' as the time for UV subtraction.')
else:
casalog.post(
'Output timerange not specified, using the entire timerange')
if spw and (type(spw) == str):
[spwid, chanran] = spw.split(':')
[bchan, echan] = chanran.split('~')
else:
casalog.post('spw not specified, use all frequency channels')
#Select the background indicated by subtime1
ms.open(vis, nomodify=True)
#Select the spw id
ms.msselect({'time': subtime1})
if spw and (type(spw) == str):
ms.selectinit(datadescid=int(spwid))
nchan = int(echan) - int(bchan) + 1
ms.selectchannel(nchan, int(bchan), 1, 1)
rec1 = ms.getdata(['data', 'time', 'axis_info'], ifraxis=True)
#print 'shape of the frequency matrix ',rec1['axis_info']['freq_axis']['chan_freq'].shape
sz1 = rec1['data'].shape
print 'dimension of selected background 1', rec1['data'].shape
#the data shape is (n_pol,n_channel,n_baseline,n_time), no need to reshape
#rec1['data']=rec1['data'].reshape(sz1[0],sz1[1],sz1[2],nspw,sz1[3]/nspw,order='F')
#print 'reshaped rec1 ', rec1['data'].shape
rec1avg = np.average(rec1['data'], axis=3)
casalog.post('Averaging the visibilities in subtime1: ' + subtime1)
ms.close()
if subtime2 and (type(subtime2) == str):
ms.open(vis, nomodify=True)
#Select the spw id
ms.msselect({'time': subtime2})
if spw and (type(spw) == str):
ms.selectinit(datadescid=0)
nchan = int(echan) - int(bchan) + 1
ms.selectchannel(nchan, int(bchan), 1, 1)
rec2 = ms.getdata(['data', 'time', 'axis_info'], ifraxis=True)
sz2 = rec2['data'].shape
print 'dimension of selected background 2', rec2['data'].shape
#rec2['data']=rec2['data'].reshape(sz2[0],sz2[1],sz2[2],nspw,sz2[3]/nspw,order='F')
#print 'reshaped rec1 ', rec2['data'].shape
rec2avg = np.average(rec2['data'], axis=3)
ms.close()
casalog.post('Averaged the visibilities in subtime2: ' + subtime2)
#do UV subtraction, according to timerange and spw
ms.open(outputvis, nomodify=False)
if not splitsel:
#outputvis is identical to input visibility, do the selection
if timerange and (type(timerange == str)):
ms.msselect({'time': timerange})
if spw and (type(spw) == str):
ms.selectinit(datadescid=int(spwid))
nchan = int(echan) - int(bchan) + 1
ms.selectchannel(nchan, int(bchan), 1, 1)
else:
#outputvis is splitted, selections have already applied, select all the data
ms.selectinit(datadescid=0)
orec = ms.getdata(['data', 'time', 'axis_info'], ifraxis=True)
b_rows = orec['data'].shape[2]
nchan = orec['data'].shape[1]
#szo=orec['data'].shape
print 'dimension of output data', orec['data'].shape
#orec['data']=orec['data'].reshape(szo[0],szo[1],szo[2],nspw,szo[3]/nspw,order='F')
#print 'reshaped rec1 ', orec['data'].shape
t_rows = orec['data'].shape[3]
casalog.post('Number of baselines: ' + str(b_rows))
casalog.post('Number of spectral channels: ' + str(nchan))
casalog.post('Number of time pixels: ' + str(t_rows))
if subtime1 and (not subtime2):
casalog.post(
'Only "subtime1" is defined, subtracting background defined in subtime1: '
+ subtime1)
t1 = (np.amax(rec1['time']) + np.amin(rec1['time'])) / 2.
print 't1: ', qa.time(qa.quantity(t1, 's'), form='ymd', prec=10)
for i in range(t_rows):
orec['data'][:, :, :, i] -= rec1avg
if reverse:
orec['data'][:, :, :, i] = -orec['data'][:, :, :, i]
if subtime1 and subtime2 and (type(subtime2) == str):
casalog.post(
'Both subtime1 and subtime2 are specified, doing linear interpolation between "subtime1" and "subtime2"'
)
t1 = (np.amax(rec1['time']) + np.amin(rec1['time'])) / 2.
t2 = (np.amax(rec2['time']) + np.amin(rec2['time'])) / 2.
touts = orec['time']
print 't1: ', qa.time(qa.quantity(t1, 's'), form='ymd', prec=10)
print 't2: ', qa.time(qa.quantity(t2, 's'), form='ymd', prec=10)
for i in range(t_rows):
tout = touts[i]
if tout > np.amax([t1, t2]):
tout = np.amax([t1, t2])
elif tout < np.amin([t1, t2]):
tout = np.amin([t1, t2])
orec['data'][:, :, :,
i] -= (rec2avg - rec1avg) * (tout -
t1) / (t2 - t1) + rec1avg
if reverse:
orec['data'][:, :, :, i] = -orec['data'][:, :, :, i]
#orec['data']=orec['data'].reshape(szo[0],szo[1],szo[2],szo[3],order='F')
#put the modified data back into the output visibility set
del orec['time']
del orec['axis_info']
ms.putdata(orec)
ms.close()
def ephem_to_helio(vis=None,
ephem=None,
msinfo=None,
reftime=None,
polyfit=None,
usephacenter=False):
'''1. Take a solar ms database, read the scan and field information, find out the pointings (in RA and DEC)
2. Compare with the ephemeris of the solar disk center (in RA and DEC)
3. Generate VLA pointings in heliocentric coordinates
inputs:
msinfo: CASA MS information, output from read_msinfo
ephem: solar ephem, output from read_horizons
reftime: list of reference times (e.g., used for imaging)
CASA standard time format, either a single time (e.g., '2012/03/03/12:00:00'
or a time range (e.g., '2012/03/03/12:00:00~2012/03/03/13:00:00'. If the latter,
take the midpoint of the timerange for reference. If no date specified, take
the date of the first scan
polyfit: ONLY works for MS database with only one source with continously tracking;
not recommanded unless scan length is too long and want to have very high accuracy
usephacenter: Bool -- if True, correct for the RA and DEC in the ms file based on solar empheris.
Otherwise assume the phasecenter is correctly pointed to the solar disk center
(EOVSA case)
return value:
helio: a list of VLA pointing information
reftimestr: reference time, in FITS format string
reftime: reference time, in mjd format
ra: actual RA of phasecenter in the ms file at the reference time (interpolated)
dec: actual DEC of phasecenter in the ms file at the reference time (interpolated)
# CASA uses only RA and DEC of the closest field (e.g. in clean) #
ra_fld: right ascention of the CASA reference pointing direction
dec_fld: declination of the CASA reference pointing direction
raoff: RA offset of the phasecenter in the ms file to solar center
decoff: DEC offset of the phasecenter in the ms file to solar center
refx: heliocentric X offset of the phasecenter in the ms file to solar center
refy: heliocentric Y offset of the phasecenter in the ms file to solar center
######## Example #########
msfile='sun_C_20140910T221952-222952.10s.cal.ms'
ephemfile='horizons_sun_20140910.radecp'
ephem=vla_prep.read_horizons(ephemfile=ephemfile)
msinfo=vla_prep.read_msinfo(msfile=msfile)
polyfit=0
reftime = '22:25:20~22:25:40'
'''
if not vis or not os.path.exists(vis):
raise ValueError, 'Please provide information of the MS database!'
if not ephem:
ephem = read_horizons(vis)
if not msinfo:
msinfo0 = read_msinfo(vis)
else:
if isinstance(msinfo, str):
try:
msinfo0 = np.load(msinfo)
except:
raise ValueError, 'The specified input msinfo file does not exist!'
elif isinstance(msinfo, dict):
msinfo0 = msinfo
else:
raise ValueError, 'msinfo should be either a numpy npz or a dictionary'
print 'msinfo is derived from: ', msinfo0['vis']
scans = msinfo0['scans']
fieldids = msinfo0['fieldids']
btimes = msinfo0['btimes']
inttimes = msinfo0['inttimes']
ras = msinfo0['ras']
decs = msinfo0['decs']
ra_rads = [ra['value'] for ra in ras]
dec_rads = [dec['value'] for dec in decs]
# fit 2nd order polynomial fits to the RAs and DECs #
if polyfit:
cra = np.polyfit(btimes, ra_rads, 2)
cdec = np.polyfit(btimes, dec_rads, 2)
# find out phase center infomation in ms according to the input time or timerange #
if not reftime:
raise ValueError, 'Please specify a reference time of the image'
if type(reftime) == str:
reftime = [reftime]
if (not isinstance(reftime, list)):
print 'input "reftime" is not a valid list. Abort...'
nreftime = len(reftime)
helio = []
for reftime0 in reftime:
helio0 = dict.fromkeys(['reftimestr', 'reftime', \
'ra', 'dec', 'ra_fld', 'dec_fld', \
'raoff', 'decoff', 'refx', 'refy', 'p0'])
helio0['reftimestr'] = reftime0
if '~' in reftime0:
# if reftime0 is specified as a timerange
[tbg0, tend0] = reftime0.split('~')
tbg_d = qa.getvalue(qa.convert(qa.totime(tbg0), 'd'))[0]
tend_d = qa.getvalue(qa.convert(qa.totime(tend0), 'd'))[0]
tdur_s = (tend_d - tbg_d) * 3600. * 24.
# if no date is specified, add up the date of the first scan
if tend_d < 1.:
if tend_d >= tbg_d:
tend_d += int(btimes[0])
else:
tend_d += int(btimes[0]) + 1
if tbg_d < 1.:
tbg_d += int(btimes[0])
tref_d = (tbg_d + tend_d) / 2.
else:
# if reftime0 is specified as a single value
tref_d = qa.getvalue(qa.convert(qa.totime(reftime0), 'd'))
# if no date is specified, add up the date of the first scan
if tref_d < 1.:
tref_d += int(btimes[0])
tbg_d = tref_d
# use the intergration time
ind = bisect.bisect_left(btimes, tref_d)
tdur_s = inttims[ind - 1]
helio0['reftime'] = tref_d
helio0['date-obs'] = qa.time(qa.quantity(tbg_d, 'd'),
form='fits',
prec=10)[0]
helio0['exptime'] = tdur_s
# find out phase center RA and DEC in the measurement set according to the reference time
# if polyfit, then use the 2nd order polynomial coeffs
ind = bisect.bisect_left(btimes, tref_d)
if ind > 1:
dt = tref_d - btimes[ind - 1]
if ind < len(btimes):
scanlen = btimes[ind] - btimes[ind - 1]
(ra_b, ra_e) = (ras[ind - 1]['value'], ras[ind]['value'])
(dec_b, dec_e) = (decs[ind - 1]['value'], decs[ind]['value'])
if ind >= len(btimes):
scanlen = btimes[ind - 1] - btimes[ind - 2]
(ra_b, ra_e) = (ras[ind - 2]['value'], ras[ind - 1]['value'])
(dec_b, dec_e) = (decs[ind - 2]['value'],
decs[ind - 1]['value'])
if ind == 1: # only one scan exists (e.g., imported from AIPS)
ra_b = ras[ind - 1]['value']
ra_e = ra_b
dec_b = decs[ind - 1]['value']
dec_e = dec_b
scanlen = 10. # radom value
dt = 0.
if ind < 1:
raise ValueError, 'Reference time does not fall into the scan list!'
if polyfit:
ra = cra[0] * tref_d**2. + cra[1] * tref_d + cra[2]
dec = cdec[0] * tref_d**2. + cdec[1] * tref_d + cdec[2]
# if not, use linearly interpolated RA and DEC at the beginning of this scan and next scan
else:
ra = ra_b + (ra_e - ra_b) / scanlen * dt
dec = dec_b + (dec_e - dec_b) / scanlen * dt
if ra < 0:
ra += 2. * np.pi
if ra_b < 0:
ra_b += 2. * np.pi
# compare with ephemeris from JPL Horizons
time0 = ephem['time']
ra0 = ephem['ra']
dec0 = ephem['dec']
p0 = ephem['p0']
delta0 = ephem['delta']
ind = bisect.bisect_left(time0, tref_d)
dt0 = time0[ind] - time0[ind - 1]
dt_ref = tref_d - time0[ind - 1]
dra0 = ra0[ind] - ra0[ind - 1]
ddec0 = dec0[ind] - dec0[ind - 1]
dp0 = p0[ind] - p0[ind - 1]
ddelta0 = delta0[ind] - delta0[ind - 1]
ra0 = ra0[ind - 1] + dra0 / dt0 * dt_ref
dec0 = dec0[ind - 1] + ddec0 / dt0 * dt_ref
p0 = p0[ind - 1] + dp0 / dt0 * dt_ref
delta0 = delta0[ind - 1] + ddelta0 / dt0 * dt_ref
if ra0 < 0:
ra0 += 2. * np.pi
# RA and DEC offset in arcseconds
decoff = degrees((dec - dec0)) * 3600.
raoff = degrees((ra - ra0) * cos(dec)) * 3600.
# Convert into heliocentric offsets
prad = -radians(p0)
refx = (-raoff) * cos(prad) - decoff * sin(prad)
refy = (-raoff) * sin(prad) + decoff * cos(prad)
helio0['ra'] = ra # ra of the actual pointing
helio0['dec'] = dec # dec of the actual pointing
helio0[
'ra_fld'] = ra_b # ra of the field, used as the reference in e.g., clean
helio0[
'dec_fld'] = dec_b # dec of the field, used as the refenrence in e.g., clean
helio0['raoff'] = raoff
helio0['decoff'] = decoff
if usephacenter:
helio0['refx'] = refx
helio0['refy'] = refy
else:
helio0['refx'] = 0.
helio0['refy'] = 0.
helio0['p0'] = p0
# helio['r_sun']=np.degrees(R_sun.value/(au.value*delta0))*3600. #in arcsecs
helio.append(helio0)
return helio
def test_readAndParseIrregularTbuff(self):
'''flaghelper: compare the read and parse and apply of irregular tbuff'''
print ''
# MJD in seconds of timeranges are these
# <startTime>4891227930515540000 <endTime>4891227932453838000
# <startTime>4891228473545856000 <endTime>4891228473731891000
# <startTime>4891226924455911000 <endTime>4891226927502314000
# <startTime>4891228838164987000 <endTime>4891228838418996000
# <startTime>4891228609440808000 <endTime>4891228612489617000
online = ["antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'",
"antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'",
"antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'",
"antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'",
"antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'"]
myinput = "antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'\n"\
"antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'\n"\
"antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'\n"\
"antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'\n"\
"antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'"
filename1 = 'flaghelperonline2.txt'
create_input(myinput, filename1)
# timeranges from online before padding, for comparison later
timeranges=[]
for cmd in online:
a,b = cmd.split(' ')
b = b.lstrip('timerange=')
timeranges.append(b.strip("'"))
# Apply 2 values of tbuff to timeranges
timebuffer = [0.4, 0.7]
dlist1 = fh.readAndParse([filename1], tbuff=timebuffer)
self.assertEqual(len(dlist1), 5)
# check the padded time ranges before and after the application
n = 0
for cmd in dlist1:
padt = cmd['timerange']
# padt = dlist1[0]['timerange']
# Revert the tbuff application manually
t0,t1 = padt.split('~',1)
startTime = qa.totime(t0)['value']
startTimeSec = float((startTime * 24 * 3600) + timebuffer[0])
startTimeSec = qa.quantity(startTimeSec, 's')
paddedT0 = qa.time(startTimeSec,form='ymd',prec=9)[0]
# end time
endTime = qa.totime(t1)['value']
endTimeSec = float((endTime * 24 * 3600) - timebuffer[1])
endTimeSec = qa.quantity(endTimeSec, 's')
paddedT1 = qa.time(endTimeSec,form='ymd',prec=9)[0]
newtimerange = paddedT0+'~'+paddedT1
# Compare with the original
self.assertEqual(timeranges[n], newtimerange)
n += 1
def plt_dspec(specdata,
pol='I',
dmin=None,
dmax=None,
timerange=None,
freqrange=None,
timestr=True,
movie=False,
framedur=60.,
dtframe=10.,
goessav=None,
goes_trange=None,
savepng=True,
savepdf=False):
"""
timerange: format: ['2012/03/10/18:00:00','2012/03/10/19:00:00']
freqrange: format: [1000.,1500.] in MHz
movie: do a movie of dynamic spectrum?
framedur: time range of each frame
dtframe: time difference of consecutive frames
goessav: provide an IDL save file from the sswidl GOES widget output
goes_trange: plot only the specified time range for goes
timestr: display time as strings on X-axis -- currently the times do not update themselves when zooming in
"""
# Set up variables
import matplotlib.pyplot as plt
import numpy
from numpy import log10
from astropy.time import Time
if pol != 'RR' and pol != 'LL' and pol != 'RRLL' and pol != 'I' and pol != 'V' and pol != 'IV':
print "Please enter 'RR', 'LL', 'RRLL', 'I', 'V', 'IV' for pol"
return 0
if type(specdata) is str:
specdata = np.load(specdata)
bl = specdata['bl'].item()
try:
(npol, nbl, nfreq, ntim) = specdata['spec'].shape
spec = specdata['spec']
tim = specdata['tim']
tim_ = Time(tim / 3600. / 24., format='mjd')
tim_plt = tim_.plot_date
freq = specdata['freq']
if not 'bl' in vars():
bl = specdata['bl']
except:
print('format of specdata not recognized. Check your input')
return -1
if timerange:
if type(timerange[0]) is str:
timerange = [
qa.convert(qa.quantity(t), 's')['value'] for t in timerange
]
tidx = np.where((tim >= timerange[0]) & (tim <= timerange[1]))[0]
else:
tidx = range(ntim)
if freqrange:
fidx = np.where((freq >= freqrange[0] * 1e6)
& (freq <= freqrange[1] * 1e6))[0]
else:
fidx = range(nfreq)
# setup plot parameters
print 'ploting dynamic spectrum...'
spec_med = np.median(np.absolute(spec))
# if not dmin:
# dmin = spec_med / 20.
# if not dmax:
# dmax = spec_med * 5.
# do the plot
for b in range(nbl):
if pol != 'RRLL' and pol != 'IV':
if pol == 'RR':
spec_plt = spec[0, b, :, :]
elif pol == 'LL':
spec_plt = spec[1, b, :, :]
elif pol == 'I':
spec_plt = (spec[0, b, :, :] + spec[1, b, :, :]) / 2.
elif pol == 'V':
spec_plt = (spec[0, b, :, :] - spec[1, b, :, :]) / 2.
if movie:
f = plt.figure(figsize=(16, 8), dpi=100)
if goessav:
gs = gridspec.GridSpec(2, 1, height_ratios=[2, 1])
gs.update(left=0.06, right=0.97, top=0.95, bottom=0.06)
ax1 = f.add_subplot(gs[0])
ax2 = f.add_subplot(gs[1])
if os.path.exists(goessav):
goes = readsav(goessav)
# IDL anytim 0 sec correspond to 1979 Jan 01, convert to mjd time
anytimbase = qa.convert(
qa.quantity('1979/01/01/00:00:00'), 's')['value']
mjdbase = goes['utbase'] + anytimbase
ts = goes['tarray'] + mjdbase
lc0 = goes['yclean'][0, :]
lc1 = goes['yclean'][1, :]
else:
ax1 = f.add_subplot(211)
tstart = tim[tidx[0]]
tend = tim[tidx[-1]]
tstartstr = qa.time(qa.quantity(tstart, 's'))[0]
tendstr = qa.time(qa.quantity(tend, 's'))[0]
nfrm = int((tend - tstart) / dtframe) + 1
print 'Movie mode set. ' + str(
nfrm
) + ' frames to plot from ' + tstartstr + ' to ' + tendstr
for i in range(nfrm):
if (i != 0) and (i % 10 == 0):
print str(i) + ' frames done'
timeran = [
tstart + i * dtframe, tstart + i * dtframe + framedur
]
tidx1 = np.where((tim >= timeran[0])
& (tim <= timeran[1]))[0]
tim1 = tim_[tidx1]
freq1 = freq[fidx] / 1e9
spec_plt1 = spec_plt[fidx, :][:, tidx1]
ax1.pcolormesh(tim1.plot_date,
freq1,
spec_plt1,
cmap='jet',
vmin=dmin,
vmax=dmax)
ax1.set_xlim(tim1[0].plot_date, tim1[-1].plot_date)
ax1.set_ylim(freq1[0], freq1[-1])
ax1.set_ylabel('Frequency (GHz)')
ax1.set_title('Dynamic spectrum @ bl ' + bl.split(';')[b] +
', pol ' + pol)
if timestr:
# date_format = mdates.DateFormatter('%H:%M:%S.%f')
# ax1.xaxis_date()
# ax1.xaxis.set_major_formatter(date_format)
locator = AutoDateLocator()
ax1.xaxis.set_major_locator(locator)
ax1.xaxis.set_major_formatter(
AutoDateFormatter(locator))
ax1.set_autoscale_on(False)
if goessav:
if goes_trange:
if type(goes_trange[0]) is str:
goes_trange = [
qa.convert(qa.quantity(t), 's')['value']
for t in goes_trange
]
idx = np.where((ts >= goes_trange[0])
& (ts <= goes_trange[1]))[0]
else:
idx = range(len(ts))
ts_plt = ts[idx]
lc0_plt = lc0[idx]
utbase = qa.convert(qa.quantity('0001/01/01/00:00:00'),
'd')['value'] + 1
ts_plt_d = ts_plt / 3600. / 24. - utbase
ax2.plot_date(ts_plt_d, lc0_plt, 'b-')
ax2.axvspan(tim1[0].mjd - utbase,
tim1[-1].mjd - utbase,
color='red',
alpha=0.5)
ax2.set_yscale('log')
ax2.set_title('GOES 1-8 A')
tstartstr_ = tim1[0].datetime.strftime(
'%Y-%m-%dT%H%M%S.%f')[:-3]
tendstr_ = tim1[1].datetime.strftime('%H%M%S.%f')[:-3]
timstr = tstartstr_ + '-' + tendstr_
figfile = 'dspec_t' + timstr + '.png'
if not os.path.isdir('dspec'):
os.makedirs('dspec')
f.savefig('dspec/' + figfile)
plt.cla()
else:
f = plt.figure(figsize=(8, 4), dpi=100)
ax = f.add_subplot(111)
freqghz = freq / 1e9
ax.pcolormesh(tim_plt,
freqghz,
spec_plt,
cmap='jet',
vmin=dmin,
vmax=dmax)
ax.set_xlim(tim_plt[tidx[0]], tim_plt[tidx[-1]])
ax.set_ylim(freqghz[fidx[0]], freqghz[fidx[-1]])
try:
from sunpy import lightcurve
from sunpy.time import TimeRange, parse_time
t1 = tim_[tidx[0]]
t2 = tim_[tidx[-1]]
tr = TimeRange(t1.iso, t2.iso)
goes = lightcurve.GOESLightCurve.create(tr)
goes.data['xrsb'] = 2 * (np.log10(goes.data['xrsb'])) + 26
xx = [str(ll) for ll in np.array(goes.data.index)]
yy = np.array(goes.data['xrsb'])
ax.plot(Time(xx).mjd * 24 * 3600, yy, c='yellow')
rightaxis_label_time = Time(xx[-1]).mjd * 24 * 3600
ax.text(rightaxis_label_time, 9.6, 'A', fontsize='15')
ax.text(rightaxis_label_time, 11.6, 'B', fontsize='15')
ax.text(rightaxis_label_time, 13.6, 'C', fontsize='15')
ax.text(rightaxis_label_time, 15.6, 'M', fontsize='15')
ax.text(rightaxis_label_time, 17.6, 'X', fontsize='15')
except:
pass
def format_coord(x, y):
col = np.argmin(np.absolute(tim_plt - x))
row = np.argmin(np.absolute(freqghz - y))
if col >= 0 and col < ntim and row >= 0 and row < nfreq:
timstr = tim_[col].isot
flux = spec_plt[row, col]
return 'time {0} = {1}, freq = {2:.3f} GHz, flux = {3:.2f} Jy'.format(
col, timstr, y, flux)
else:
return 'x = {0}, y = {1:.3f}'.format(x, y)
ax.format_coord = format_coord
ax.set_ylabel('Frequency (GHz)')
if bl:
ax.set_title('Dynamic spectrum @ bl ' + bl.split(';')[b] +
', pol ' + pol)
else:
ax.set_title('Medium dynamic spectrum')
if timestr:
# date_format = mdates.DateFormatter('%H:%M:%S.%f')
# ax.xaxis_date()
# ax.xaxis.set_major_formatter(date_format)
locator = AutoDateLocator()
ax.xaxis.set_major_locator(locator)
ax.xaxis.set_major_formatter(AutoDateFormatter(locator))
ax.set_autoscale_on(False)
else:
f = plt.figure(figsize=(8, 6), dpi=100)
R_plot = np.absolute(spec[0, b, :, :])
L_plot = np.absolute(spec[1, b, :, :])
I_plot = (R_plot + L_plot) / 2.
V_plot = (R_plot - L_plot) / 2.
if pol == 'RRLL':
spec_plt_1 = R_plot
spec_plt_2 = L_plot
polstr = ['RR', 'LL']
if pol == 'IV':
spec_plt_1 = I_plot
spec_plt_2 = V_plot
polstr = ['I', 'V']
ax1 = f.add_subplot(211)
freqghz = freq / 1e9
ax1.pcolormesh(tim_plt,
freqghz,
spec_plt_1,
cmap='jet',
vmin=dmin,
vmax=dmax)
ax1.set_xlim(tim_plt[tidx[0]], tim_plt[tidx[-1]])
ax1.set_ylim(freqghz[fidx[0]], freqghz[fidx[-1]])
def format_coord(x, y):
col = np.argmin(np.absolute(tim_plt - x))
row = np.argmin(np.absolute(freqghz - y))
if col >= 0 and col < ntim and row >= 0 and row < nfreq:
timstr = tim_[col].isot
flux = spec_plt[row, col]
return 'time {0} = {1}, freq = {2:.3f} GHz, flux = {3:.2f} Jy'.format(
col, timstr, y, flux)
else:
return 'x = {0}, y = {1:.3f}'.format(x, y)
ax1.format_coord = format_coord
ax1.set_ylabel('Frequency (GHz)')
if timestr:
# date_format = mdates.DateFormatter('%H:%M:%S.%f')
# ax1.xaxis_date()
# ax1.xaxis.set_major_formatter(date_format)
locator = AutoDateLocator()
ax1.xaxis.set_major_locator(locator)
ax1.xaxis.set_major_formatter(AutoDateFormatter(locator))
ax1.set_title('Dynamic spectrum @ bl ' + bl.split(';')[b] +
', pol ' + polstr[0])
ax1.set_autoscale_on(False)
ax2 = f.add_subplot(212)
ax2.pcolormesh(tim_plt,
freqghz,
spec_plt_2,
cmap='jet',
vmin=dmin,
vmax=dmax)
ax2.set_xlim(tim_plt[tidx[0]], tim_plt[tidx[-1]])
ax2.set_ylim(freqghz[fidx[0]], freqghz[fidx[-1]])
if timestr:
# date_format = mdates.DateFormatter('%H:%M:%S.%f')
# ax2.xaxis_date()
# ax2.xaxis.set_major_formatter(date_format)
locator = AutoDateLocator()
ax2.xaxis.set_major_locator(locator)
ax2.xaxis.set_major_formatter(AutoDateFormatter(locator))
def format_coord(x, y):
col = np.argmin(np.absolute(tim_plt - x))
row = np.argmin(np.absolute(freqghz - y))
if col >= 0 and col < ntim and row >= 0 and row < nfreq:
timstr = tim_[col].isot
flux = spec_plt[row, col]
return 'time {0} = {1}, freq = {2:.3f} GHz, flux = {3:.2f} Jy'.format(
col, timstr, y, flux)
else:
return 'x = {0}, y = {1:.3f}'.format(x, y)
ax2.format_coord = format_coord
ax2.set_ylabel('Frequency (GHz)')
ax2.set_title('Dynamic spectrum @ bl ' + bl.split(';')[b] +
', pol ' + polstr[1])
ax2.set_autoscale_on(False)
def test_readAndParseIrregularTbuff(self):
'''flaghelper: compare the read and parse and apply of irregular tbuff'''
print ''
# MJD in seconds of timeranges are these
# <startTime>4891227930515540000 <endTime>4891227932453838000
# <startTime>4891228473545856000 <endTime>4891228473731891000
# <startTime>4891226924455911000 <endTime>4891226927502314000
# <startTime>4891228838164987000 <endTime>4891228838418996000
# <startTime>4891228609440808000 <endTime>4891228612489617000
online = [
"antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'",
"antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'",
"antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'",
"antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'",
"antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'"
]
myinput = "antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'\n"\
"antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'\n"\
"antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'\n"\
"antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'\n"\
"antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'"
filename1 = 'flaghelperonline2.txt'
create_input(myinput, filename1)
# timeranges from online before padding, for comparison later
timeranges = []
for cmd in online:
a, b = cmd.split(' ')
b = b.lstrip('timerange=')
timeranges.append(b.strip("'"))
# Apply 2 values of tbuff to timeranges
timebuffer = [0.4, 0.7]
dlist1 = fh.readAndParse([filename1], tbuff=timebuffer)
self.assertEqual(len(dlist1), 5)
# check the padded time ranges before and after the application
n = 0
for cmd in dlist1:
padt = cmd['timerange']
# padt = dlist1[0]['timerange']
# Revert the tbuff application manually
t0, t1 = padt.split('~', 1)
startTime = qa.totime(t0)['value']
startTimeSec = float((startTime * 24 * 3600) + timebuffer[0])
startTimeSec = qa.quantity(startTimeSec, 's')
paddedT0 = qa.time(startTimeSec, form='ymd', prec=9)[0]
# end time
endTime = qa.totime(t1)['value']
endTimeSec = float((endTime * 24 * 3600) - timebuffer[1])
endTimeSec = qa.quantity(endTimeSec, 's')
paddedT1 = qa.time(endTimeSec, form='ymd', prec=9)[0]
newtimerange = paddedT0 + '~' + paddedT1
# Compare with the original
self.assertEqual(timeranges[n], newtimerange)
n += 1
def test_readAndParseTbuff(self):
'''flaghelper: compare the read and parse and apply tbuff'''
print ''
# MJD in seconds of timeranges are these
# <startTime>4891227930515540000 <endTime>4891227932453838000
# <startTime>4891228473545856000 <endTime>4891228473731891000
# <startTime>4891226924455911000 <endTime>4891226927502314000
# <startTime>4891228838164987000 <endTime>4891228838418996000
# <startTime>4891228609440808000 <endTime>4891228612489617000
online = [
"antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'",
"antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'",
"antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'",
"antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'",
"antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'"
]
myinput = "antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'\n"\
"antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'\n"\
"antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'\n"\
"antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'\n"\
"antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'"
filename1 = 'flaghelperonline2.txt'
create_input(myinput, filename1)
# First timerange from online before padding
origt = timerange = '2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'
# Apply tbuff to timeranges
timebuffer = 1.1
dlist1 = fh.readAndParse([filename1], tbuff=timebuffer)
self.assertEqual(len(dlist1), 5)
# Get the first padded timerange from output
padt = dlist1[0]['timerange']
# Revert the tbuff application manually
t0, t1 = padt.split('~', 1)
startTime = qa.totime(t0)['value']
startTimeSec = float((startTime * 24 * 3600) + timebuffer)
startTimeSec = qa.quantity(startTimeSec, 's')
paddedT0 = qa.time(startTimeSec, form='ymd', prec=9)[0]
# end time
endTime = qa.totime(t1)['value']
endTimeSec = float((endTime * 24 * 3600) - timebuffer)
endTimeSec = qa.quantity(endTimeSec, 's')
paddedT1 = qa.time(endTimeSec, form='ymd', prec=9)[0]
newtimerange = paddedT0 + '~' + paddedT1
# Compare with the original
self.assertEqual(origt, newtimerange)
# Compare with original values from Flag.xml
xmlt0 = float(4891227930515540000) * 1.0E-9
xmlt1 = float(4891227932453838000) * 1.0E-9
self.assertAlmostEqual(xmlt0, startTimeSec['value'], places=3)
self.assertAlmostEqual(xmlt1, endTimeSec['value'], places=3)
def mk_diskmodel(outname='disk', bdwidth='325MHz', direction='J2000 10h00m00.0s 20d00m00.0s',
reffreq='2.8GHz', flux=660000.0, eqradius='16.166arcmin', polradius='16.166arcmin',
pangle='21.1deg', index=None, cell='2.0arcsec', overwrite=True):
''' Create a blank solar disk model image (or optionally a data cube)
outname String to use for part of the image and fits file names (default 'disk')
direction String specifying the position of the Sun in RA and Dec. Default
means use the standard string "J2000 10h00m00.0s 20d00m00.0s"
reffreq The reference frequency to use for the disk model (the frequency at which
the flux level applies). Default is '2.8GHz'.
flux The flux density, in Jy, for the entire disk. Default is 66 sfu.
eqradius The equatorial radius of the disk. Default is
16 arcmin + 10" (for typical extension of the radio limb)
polradius The polar radius of the disk. Default is
16 arcmin + 10" (for typical extension of the radio limb)
pangle The solar P-angle (geographic position of the N-pole of the Sun) in
degrees E of N. This only matters if eqradius != polradius
index The spectral index to use at other frequencies. Default None means
use a constant flux density for all frequencies.
cell The cell size (assumed square) to use for the image. The image size
is determined from a standard radius of 960" for the Sun, divided by
cell size, increased to nearest power of 512 pixels. The default is '2.0arcsec',
which results in an image size of 1024 x 1024.
Note that the frequency increment used is '325MHz', which is the width of EOVSA bands
(not the width of individual science channels)
'''
diskim = outname + reffreq + '.im'
if os.path.exists(diskim):
if overwrite:
os.system('rm -rf {}'.format(diskim))
else:
return diskim
ia = iatool()
cl = cltool()
cl.done()
ia.done()
try:
aspect = 1.01 # Enlarge the equatorial disk by 1%
eqradius = qa.quantity(eqradius)
diamajor = qa.quantity(2 * aspect * eqradius['value'], eqradius['unit'])
polradius = qa.quantity(polradius)
diaminor = qa.quantity(2 * polradius['value'], polradius['unit'])
solrad = qa.convert(polradius, 'arcsec')
except:
print('Radius', eqradius, polradius,
'does not have the expected format, number + unit where unit is arcmin or arcsec')
return
try:
cell = qa.convert(qa.quantity(cell), 'arcsec')
cellsize = float(cell['value'])
diskpix = solrad['value'] * 2 / cellsize
cell_rad = qa.convert(cell, 'rad')
except:
print('Cell size', cell, 'does not have the expected format, number + unit where unit is arcmin or arcsec')
return
# Add 90 degrees to pangle, due to angle definition in addcomponent() -- it puts the majoraxis vertical
pangle = qa.add(qa.quantity(pangle), qa.quantity('90deg'))
mapsize = ((int(diskpix) / 512) + 1) * 512
# Flux density is doubled because it is split between XX and YY
cl.addcomponent(dir=direction, flux=flux * 2, fluxunit='Jy', freq=reffreq, shape='disk',
majoraxis=diamajor, minoraxis=diaminor, positionangle=pangle)
cl.setrefdirframe(0, 'J2000')
ia.fromshape(diskim, [mapsize, mapsize, 1, 1], overwrite=True)
cs = ia.coordsys()
cs.setunits(['rad', 'rad', '', 'Hz'])
cell_rad_val = cell_rad['value']
cs.setincrement([-cell_rad_val, cell_rad_val], 'direction')
epoch, ra, dec = direction.split()
cs.setreferencevalue([qa.convert(ra, 'rad')['value'], qa.convert(dec, 'rad')['value']], type="direction")
cs.setreferencevalue(reffreq, 'spectral')
cs.setincrement(bdwidth, 'spectral')
ia.setcoordsys(cs.torecord())
ia.setbrightnessunit("Jy/pixel")
ia.modify(cl.torecord(), subtract=False)
ia.close()
ia.done()
# cl.close()
cl.done()
return diskim
def split_core(vis, outputvis, datacolumn, field, spw, width, antenna,
timebin, timerange, scan, intent, array, uvrange,
correlation, observation, combine, keepflags):
retval = True
if not outputvis or outputvis.isspace():
raise ValueError, 'Please specify outputvis'
myms = mstool()
mytb = None
if ((type(vis)==str) & (os.path.exists(vis))):
myms.open(vis, nomodify=True)
else:
raise ValueError, 'Visibility data set not found - please verify the name'
if os.path.exists(outputvis):
myms.close()
raise ValueError, "Output MS %s already exists - will not overwrite." % outputvis
if (os.path.exists(outputvis+".flagversions")):
myms.close()
raise ValueError, "The flagversions \"%s.flagversions\" for the output MS already exist. Please delete." % outputvis
# No longer needed. When did it get put in? Note that the default
# spw='*' in myms.split ends up as '' since the default type for a variant
# is BOOLVEC. (Of course!) Therefore both split and myms.split must
# work properly when spw=''.
#if(spw == ''):
# spw = '*'
if(type(antenna) == list):
antenna = ', '.join([str(ant) for ant in antenna])
## Accept digits without units ...assume seconds
timebin = qa.convert(qa.quantity(timebin), 's')['value']
timebin = str(timebin) + 's'
if timebin == '0s':
timebin = '-1s'
# MSStateGram is picky ('CALIBRATE_WVR.REFERENCE, OBSERVE_TARGET_ON_SOURCE'
# doesn't work, but 'CALIBRATE_WVR.REFERENCE,OBSERVE_TARGET_ON_SOURCE'
# does), and I don't want to mess with bison now. A .upper() might be a
# good idea too, but the MS def'n v.2 does not say whether OBS_MODE should
# be case-insensitive.
intent = intent.replace(', ', ',')
if '^' in spw:
casalog.post("The interpretation of ^n in split's spw strings has changed from 'average n' to 'skip n' channels!", 'WARN')
casalog.post("Watch for Slicer errors", 'WARN')
if type(width) == str:
try:
if(width.isdigit()):
width=[string.atoi(width)]
elif(width.count('[') == 1 and width.count(']') == 1):
width = width.replace('[', '')
width = width.replace(']', '')
splitwidth = width.split(',')
width = []
for ws in splitwidth:
if(ws.isdigit()):
width.append(string.atoi(ws))
else:
width = [1]
except:
raise TypeError, 'parameter width is invalid...using 1'
if type(correlation) == list:
correlation = ', '.join(correlation)
correlation = correlation.upper()
if hasattr(combine, '__iter__'):
combine = ', '.join(combine)
if type(spw) == list:
spw = ','.join([str(s) for s in spw])
elif type(spw) == int:
spw = str(spw)
do_chan_mod = spw.find('^') > -1 # '0:2~11^1' would be pointless.
if not do_chan_mod: # ...look in width.
if type(width) == int and width > 1:
do_chan_mod = True
elif hasattr(width, '__iter__'):
for w in width:
if w > 1:
do_chan_mod = True
break
do_both_chan_and_time_mod = (do_chan_mod and
string.atof(timebin[:-1]) > 0.0)
if do_both_chan_and_time_mod:
# Do channel averaging first because it might be included in the spw
# string.
import tempfile
# We want the directory outputvis is in, not /tmp, because /tmp
# might not have enough space.
# outputvis is itself a directory, so strip off a trailing slash if
# it is present.
# I don't know if giving tempfile an absolute directory is necessary -
# dir='' is effectively '.' in Ubuntu.
workingdir = os.path.abspath(os.path.dirname(outputvis.rstrip('/')))
cavms = tempfile.mkdtemp(suffix=outputvis, dir=workingdir)
casalog.post('Channel averaging to ' + cavms)
if not myms.split(outputms=cavms, field=field,
spw=spw, step=width,
baseline=antenna, subarray=array,
timebin='', time=timerange,
whichcol=datacolumn,
scan=scan, uvrange=uvrange,
combine=combine,
correlation=correlation, intent=intent,
obs=str(observation)):
myms.close()
if os.path.isdir(cavms):
import shutil
shutil.rmtree(cavms)
return False
# The selection was already made, so blank them before time averaging.
field = ''
spw = ''
width = [1]
antenna = ''
array = ''
timerange = ''
datacolumn = 'all'
scan = ''
intent = ''
uvrange = ''
observation = ''
myms.close()
myms.open(cavms)
casalog.post('Starting time averaging')
if keepflags:
taqlstr = ''
else:
taqlstr = 'NOT (FLAG_ROW OR ALL(FLAG))'
if not myms.split(outputms=outputvis, field=field,
spw=spw, step=width,
baseline=antenna, subarray=array,
timebin=timebin, time=timerange,
whichcol=datacolumn,
scan=scan, uvrange=uvrange,
combine=combine,
correlation=correlation,
taql=taqlstr, intent=intent,
obs=str(observation)):
myms.close()
return False
myms.close()
if do_both_chan_and_time_mod:
import shutil
shutil.rmtree(cavms)
# Write history to output MS, not the input ms.
try:
param_names = split_core.func_code.co_varnames[:split_core.func_code.co_argcount]
param_vals = [eval(p) for p in param_names]
retval &= write_history(myms, outputvis, 'oldsplit', param_names, param_vals,
casalog)
except Exception, instance:
casalog.post("*** Error \'%s\' updating HISTORY" % (instance),
'WARN')
def clean_iter(
tim, vis, imageprefix, imagesuffix, twidth, doreg, usephacenter,
reftime, ephem, msinfo, toTb, overwrite, selectdata, field, spw,
uvrange, antenna, scan, observation, intent, datacolumn, imsize, cell,
phasecenter, stokes, projection, startmodel, specmode, reffreq, nchan,
start, width, outframe, veltype, restfreq, interpolation, gridder,
facets, chanchunks, wprojplanes, vptable, usepointing, mosweight,
aterm, psterm, wbawp, conjbeams, cfcache, computepastep, rotatepastep,
pblimit, normtype, deconvolver, scales, nterms, smallscalebias,
restoration, restoringbeam, pbcor, outlierfile, weighting, robust,
npixels, uvtaper, niter, gain, threshold, nsigma, cycleniter,
cyclefactor, minpsffraction, maxpsffraction, interactive, usemask,
mask, pbmask, sidelobethreshold, noisethreshold, lownoisethreshold,
negativethreshold, smoothfactor, minbeamfrac, cutthreshold,
growiterations, dogrowprune, minpercentchange, verbose, restart,
savemodel, calcres, calcpsf, parallel, subregion, tmpdir, btidx):
from tclean_cli import tclean_cli as tclean
from split_cli import split_cli as split
bt = btidx # 0
if bt + twidth < len(tim) - 1:
et = btidx + twidth - 1
else:
et = len(tim) - 1
if bt == 0:
bt_d = tim[bt] - ((tim[bt + 1] - tim[bt]) / 2)
else:
bt_d = tim[bt] - ((tim[bt] - tim[bt - 1]) / 2)
if et == (len(tim) - 1) or et == -1:
et_d = tim[et] + ((tim[et] - tim[et - 1]) / 2)
else:
et_d = tim[et] + ((tim[et + 1] - tim[et]) / 2)
timerange = qa.time(qa.quantity(bt_d, 's'), prec=9, form='ymd')[0] + '~' + \
qa.time(qa.quantity(et_d, 's'), prec=9, form='ymd')[0]
btstr = qa.time(qa.quantity(bt_d, 's'), prec=9, form='fits')[0]
etstr = qa.time(qa.quantity(et_d, 's'), prec=9, form='fits')[0]
print('cleaning timerange: ' + timerange)
image0 = btstr.replace(':', '').replace('-', '')
imname = imageprefix + image0 + imagesuffix
# ms_tmp = tmpdir + image0 + '.ms'
# print('checkpoint 1')
# # split(vis=vis, outputvis=ms_tmp, field=field, scan=scan, antenna=antenna, timerange=timerange,
# # datacolumn=datacolumn)
# ms.open(vis)
# print('checkpoint 1-1')
# ms.split(ms_tmp,field=field, scan=scan, baseline=antenna, time=timerange,whichcol=datacolumn)
# print('checkpoint 1-2')
# ms.close()
# print('checkpoint 2')
if overwrite or (len(glob.glob(imname + '*')) == 0):
os.system('rm -rf {}*'.format(imname))
try:
tclean(vis=vis,
selectdata=selectdata,
field=field,
spw=spw,
timerange=timerange,
uvrange=uvrange,
antenna=antenna,
scan=scan,
observation=observation,
intent=intent,
datacolumn=datacolumn,
imagename=imname,
imsize=imsize,
cell=cell,
phasecenter=phasecenter,
stokes=stokes,
projection=projection,
startmodel=startmodel,
specmode=specmode,
reffreq=reffreq,
nchan=nchan,
start=start,
width=width,
outframe=outframe,
veltype=veltype,
restfreq=restfreq,
interpolation=interpolation,
gridder=gridder,
facets=facets,
chanchunks=chanchunks,
wprojplanes=wprojplanes,
vptable=vptable,
usepointing=usepointing,
mosweight=mosweight,
aterm=aterm,
psterm=psterm,
wbawp=wbawp,
conjbeams=conjbeams,
cfcache=cfcache,
computepastep=computepastep,
rotatepastep=rotatepastep,
pblimit=pblimit,
normtype=normtype,
deconvolver=deconvolver,
scales=scales,
nterms=nterms,
smallscalebias=smallscalebias,
restoration=restoration,
restoringbeam=restoringbeam,
pbcor=pbcor,
outlierfile=outlierfile,
weighting=weighting,
robust=robust,
npixels=npixels,
uvtaper=uvtaper,
niter=niter,
gain=gain,
threshold=threshold,
nsigma=nsigma,
cycleniter=cycleniter,
cyclefactor=cyclefactor,
minpsffraction=minpsffraction,
maxpsffraction=maxpsffraction,
interactive=interactive,
usemask=usemask,
mask=mask,
pbmask=pbmask,
sidelobethreshold=sidelobethreshold,
noisethreshold=noisethreshold,
lownoisethreshold=lownoisethreshold,
negativethreshold=negativethreshold,
smoothfactor=smoothfactor,
minbeamfrac=minbeamfrac,
cutthreshold=cutthreshold,
growiterations=growiterations,
dogrowprune=dogrowprune,
minpercentchange=minpercentchange,
verbose=verbose,
restart=restart,
savemodel=savemodel,
calcres=calcres,
calcpsf=calcpsf,
parallel=parallel)
# print('checkpoint 3')
if pbcor:
clnjunks = [
'.flux', '.mask', '.model', '.psf', '.residual', '.pb',
'.sumwt', '.image'
]
else:
clnjunks = [
'.flux', '.mask', '.model', '.psf', '.residual', '.pb',
'.sumwt', '.image.pbcor'
]
for clnjunk in clnjunks:
if os.path.exists(imname + clnjunk):
shutil.rmtree(imname + clnjunk)
if pbcor:
os.system('mv {} {}'.format(imname + '.image.pbcor',
imname + '.image'))
except:
print('error in cleaning image: ' + btstr)
return [False, btstr, etstr, '']
else:
print(imname + ' exists. Clean task aborted.')
if doreg and not os.path.isfile(imname + '.fits'):
# ephem.keys()
# msinfo.keys()
try:
# check if ephemfile and msinfofile exist
if not ephem:
print(
"ephemeris info does not exist, querying from JPL Horizons on the fly"
)
ephem = hf.read_horizons(vis=vis)
if not msinfo:
print("ms info not provided, generating one on the fly")
msinfo = hf.read_msinfo(vis)
hf.imreg(vis=vis,
ephem=ephem,
msinfo=msinfo,
timerange=timerange,
reftime=reftime,
imagefile=imname + '.image',
fitsfile=imname + '.fits',
toTb=toTb,
scl100=False,
usephacenter=usephacenter,
subregion=subregion)
if os.path.exists(imname + '.fits'):
shutil.rmtree(imname + '.image')
return [True, btstr, etstr, imname + '.fits']
else:
return [False, btstr, etstr, '']
except:
print('error in registering image: ' + btstr)
return [False, btstr, etstr, imname + '.image']
else:
if os.path.exists(imname + '.image'):
return [True, btstr, etstr, imname + '.image']
else:
return [False, btstr, etstr, '']
def predictcomp(objname=None,
standard=None,
epoch=None,
minfreq=None,
maxfreq=None,
nfreqs=None,
prefix=None,
antennalist=None,
showplot=None,
savefig=None,
symb=None,
include0amp=None,
include0bl=None,
blunit=None,
bl0flux=None):
"""
Writes a component list named clist to disk and returns a dict of
{'clist': clist,
'objname': objname,
'angdiam': angular diameter in radians (if used in clist),
'standard': standard,
'epoch': epoch,
'freqs': pl.array of frequencies, in GHz,
'uvrange': pl.array of baseline lengths, in m,
'amps': pl.array of predicted visibility amplitudes, in Jy,
'savedfig': False or, if made, the filename of a plot.}
or False on error.
objname: An object supported by standard.
standard: A standard for calculating flux densities, as in setjy.
Default: 'Butler-JPL-Horizons 2010'
epoch: The epoch to use for the calculations. Irrelevant for
extrasolar standards.
minfreq: The minimum frequency to use.
Example: '342.0GHz'
maxfreq: The maximum frequency to use.
Default: minfreq
Example: '346.0GHz'
Example: '', anything <= 0, or None: use minfreq.
nfreqs: The number of frequencies to use.
Default: 1 if minfreq == maxfreq,
2 otherwise.
prefix: The component list will be saved to
prefix + '<objname>_spw0_<minfreq><epoch>.cl'
Default: ''
antennalist: An array configuration file as used by simdata.
If given, a plot of S vs. |u| will be made.
Default: '' (None, just make clist.)
showplot: Whether or not to show the plot on screen.
Subparameter of antennalist.
Default: Necessarily False if antennalist is not specified.
True otherwise.
savefig: Filename for saving a plot of S vs. |u|.
Subparameter of antennalist.
Default: False (necessarily if antennalist is not specified)
Examples: True (save to prefix + '.png')
'myplot.png' (save to myplot.png)
symb: One of matplotlib's codes for plot symbols: .:,o^v<>s+xDd234hH|_
default: '.'
include0amp: Force the lower limit of the amplitude axis to 0.
Default: False
include0bl: Force the lower limit of the baseline length axis to 0.
blunit: Unit of the baseline length
bl0flux: show zero baseline flux
"""
retval = False
try:
casalog.origin('predictcomp')
# some parameter minimally required
if objname == '':
raise Exception, "Error, objname is undefined"
if minfreq == '':
raise Exception, "Error, minfreq is undefined"
minfreqq = qa.quantity(minfreq)
minfreqHz = qa.convert(minfreqq, 'Hz')['value']
try:
maxfreqq = qa.quantity(maxfreq)
except Exception, instance:
maxfreqq = minfreqq
frequnit = maxfreqq['unit']
maxfreqHz = qa.convert(maxfreqq, 'Hz')['value']
if maxfreqHz <= 0.0:
maxfreqq = minfreqq
maxfreqHz = minfreqHz
if minfreqHz != maxfreqHz:
if nfreqs < 2:
nfreqs = 2
else:
nfreqs = 1
freqs = pl.linspace(minfreqHz, maxfreqHz, nfreqs)
myme = metool()
mepoch = myme.epoch('UTC', epoch)
#if not prefix:
## meanfreq = {'value': 0.5 * (minfreqHz + maxfreqHz),
## 'unit': frequnit}
## prefix = "%s%s_%.7g" % (objname, epoch.replace('/', '-'),
## minfreqq['value'])
## if minfreqHz != maxfreqHz:
## prefix += "to" + maxfreq
## else:
## prefix += minfreqq['unit']
## prefix += "_"
# prefix = ''
#
if not prefix:
if not os.access("./", os.W_OK):
casalog.post(
"No write access in the current directory, trying to write cl to /tmp...",
"WARN")
prefix = "/tmp/"
if not os.access(prefix, os.W_OK):
casalog.post("No write access to /tmp to write cl file",
"SEVERE")
return False
else:
prefixdir = os.path.dirname(prefix)
if prefixdir == '/' and len(prefix) > 1:
prefix = prefix + '/'
prefixdir = os.path.dirname(prefix)
if not os.path.exists(prefixdir):
prefixdirs = prefixdir.split('/')
if prefixdirs[0] == "" and len(prefixdirs) > 1:
rootdir = "/" + prefixdirs[1]
else:
rootdir = "./"
if os.access(rootdir, os.W_OK):
if prefixdir != '':
os.makedirs(prefixdir)
else:
casalog.post(
"No write access to " + rootdir + " to write cl file",
"SEVERE")
return False
# Get clist
myim = imtool()
if hasattr(myim, 'predictcomp'):
casalog.post('local im instance created', 'DEBUG1')
else:
casalog.post('Error creating a local im instance.', 'SEVERE')
return False
#print "FREQS=",freqs
# output CL file name is fixed : prefix+"spw0_"+minfreq+mepoch.cl
minfreqGHz = qa.convert(qa.quantity(minfreq), 'GHz')['value']
decimalfreq = minfreqGHz - int(minfreqGHz)
decimalepoch = mepoch['m0']['value'] - int(mepoch['m0']['value'])
if decimalfreq == 0.0:
minfreqGHzStr = str(int(minfreqGHz)) + 'GHz'
else:
minfreqGHzStr = str(minfreqGHz) + 'GHz'
if decimalepoch == 0.0:
epochStr = str(int(mepoch['m0']['value'])) + 'd'
else:
epochStr = str(mepoch['m0']['value']) + 'd'
outfilename = "spw0_" + objname + "_" + minfreqGHzStr + epochStr + '.cl'
outfilename = prefix + outfilename
if (os.path.exists(outfilename) and os.path.isdir(outfilename)):
shutil.rmtree(outfilename)
casalog.post("Removing the existing componentlist, " + outfilename)
if standard == 'Butler-JPL-Horizons 2012':
clist = predictSolarObjectCompList(objname, mepoch, freqs.tolist(),
prefix)
else:
clist = myim.predictcomp(objname, standard, mepoch, freqs.tolist(),
prefix)
#print "created componentlist =",clist
if os.path.isdir(clist):
# The spw0 is useless here, but it is added by FluxStandard for the sake of setjy.
casalog.post('The component list was saved to ' + clist)
retval = {
'clist': clist,
'objname': objname,
'standard': standard,
'epoch': mepoch,
'freqs (GHz)': 1.0e-9 * freqs,
'antennalist': antennalist
}
mycl = cltool()
mycl.open(clist)
comp = mycl.getcomponent(0)
zeroblf = comp['flux']['value']
if standard == 'Butler-JPL-Horizons 2012':
f0 = comp['spectrum']['frequency']['m0']['value']
else:
f0 = retval['freqs (GHz)'][0]
casalog.post("Zero baseline flux %s @ %sGHz " % (zeroblf, f0),
'INFO')
mycl.close(False) # False prevents the stupid warning.
for k in ('shape', 'spectrum'):
retval[k] = comp[k]
if antennalist:
retval['spectrum']['bl0flux'] = {}
retval['spectrum']['bl0flux']['value'] = zeroblf[0]
retval['spectrum']['bl0flux']['unit'] = 'Jy'
retval['savedfig'] = savefig
if not bl0flux:
zeroblf = [0.0]
retval.update(
plotcomp(retval,
showplot,
wantdict=True,
symb=symb,
include0amp=include0amp,
include0bl=include0bl,
blunit=blunit,
bl0flux=zeroblf[0]))
else:
retval['savedfig'] = None
else:
casalog.post("There was an error in making the component list.",
'SEVERE')
def ptclean(vis, imageprefix, ncpu, twidth, doreg, overwrite, ephemfile,
msinfofile, outlierfile, field, spw, selectdata, timerange,
uvrange, antenna, scan, observation, intent, mode, resmooth,
gridmode, wprojplanes, facets, cfcache, rotpainc, painc, aterm,
psterm, mterm, wbawp, conjbeams, epjtable, interpolation, niter,
gain, threshold, psfmode, imagermode, ftmachine, mosweight,
scaletype, multiscale, negcomponent, smallscalebias, interactive,
mask, nchan, start, width, outframe, veltype, imsize, cell,
phasecenter, restfreq, stokes, weighting, robust, uvtaper,
outertaper, innertaper, modelimage, restoringbeam, pbcor, minpb,
usescratch, noise, npixels, npercycle, cyclefactor, cyclespeedup,
nterms, reffreq, chaniter, flatnoise, allowchunk):
if not (type(ncpu) is int):
casalog.post('ncpu should be an integer')
ncpu = 8
if doreg:
# check if ephemfile and msinfofile exist
try:
ephem = vla_prep.read_horizons(ephemfile=ephemfile)
except ValueError:
print("error in reading ephemeris file")
if not os.path.isfile(msinfofile):
print("msinfofile does not exist!")
else:
ephem = None
# get number of time pixels
ms.open(vis)
ms.selectinit()
timfreq = ms.getdata(['time', 'axis_info'], ifraxis=True)
tim = timfreq['time']
# dt = tim[1]-tim[0] #need to change to median of all time intervals
dt = np.median(np.diff(tim))
freq = timfreq['axis_info']['freq_axis']['chan_freq'].flatten()
ms.close()
if twidth < 1 or twidth > len(tim):
casalog.post(
'twidth not between 1 and # of time pixels in the dataset. Change to 1'
)
twidth = 1
# find out the start and end time index according to the parameter timerange
# if not defined (empty string), use start and end from the entire time of the ms
if not timerange:
btidx = 0
etidx = len(tim) - 1
else:
try:
(tstart, tend) = timerange.split('~')
bt_s = qa.convert(qa.quantity(tstart, 's'), 's')['value']
et_s = qa.convert(qa.quantity(tend, 's'), 's')['value']
# only time is given but not date, add the date (at 0 UT) from the first record
if bt_s < 86400. or et_s < 86400.:
bt_s += np.fix(
qa.convert(qa.quantity(tim[0], 's'),
'd')['value']) * 86400.
et_s += np.fix(
qa.convert(qa.quantity(tim[0], 's'),
'd')['value']) * 86400.
btidx = np.argmin(np.abs(tim - bt_s))
etidx = np.argmin(np.abs(tim - et_s))
# make the indice back to those bracket by the timerange
if tim[btidx] < bt_s:
btidx += 1
if tim[etidx] > et_s:
etidx -= 1
if etidx <= btidx:
print "ending time must be greater than starting time"
print "reinitiating to the entire time range"
btidx = 0
etidx = len(tim) - 1
except ValueError:
print "keyword 'timerange' has a wrong format"
btstr = qa.time(qa.quantity(tim[btidx], 's'), prec=9, form='fits')[0]
etstr = qa.time(qa.quantity(tim[etidx], 's'), prec=9, form='fits')[0]
iterable = range(btidx, etidx + 1, twidth)
print 'First time pixel: ' + btstr
print 'Last time pixel: ' + etstr
print str(len(iterable)) + ' images to clean...'
res = []
# partition
clnpart = partial(
clean_iter, tim, freq, vis, imageprefix, ncpu, twidth, doreg,
overwrite, ephemfile, ephem, msinfofile, outlierfile, field, spw,
selectdata, uvrange, antenna, scan, observation, intent, mode,
resmooth, gridmode, wprojplanes, facets, cfcache, rotpainc, painc,
aterm, psterm, mterm, wbawp, conjbeams, epjtable, interpolation, niter,
gain, threshold, psfmode, imagermode, ftmachine, mosweight, scaletype,
multiscale, negcomponent, smallscalebias, interactive, mask, nchan,
start, width, outframe, veltype, imsize, cell, phasecenter, restfreq,
stokes, weighting, robust, uvtaper, outertaper, innertaper, modelimage,
restoringbeam, pbcor, minpb, usescratch, noise, npixels, npercycle,
cyclefactor, cyclespeedup, nterms, reffreq, chaniter, flatnoise,
allowchunk)
timelapse = 0
t0 = time()
# parallelization
para = 1
if para:
casalog.post('Perform clean in parallel ...')
pool = mp.Pool(ncpu)
# res = pool.map_async(clnpart, iterable)
res = pool.map(clnpart, iterable)
pool.close()
pool.join()
else:
for i in iterable:
res.append(clnpart(i))
t1 = time()
timelapse = t1 - t0
print 'It took %f secs to complete' % timelapse
# repackage this into a single dictionary
results = {'succeeded': [], 'timestamps': [], 'imagenames': []}
for r in res:
results['succeeded'].append(r[0])
results['timestamps'].append(r[1])
results['imagenames'].append(r[2])
return results
def clean_iter(tim, freq, vis, imageprefix, ncpu, twidth, doreg, overwrite,
ephemfile, ephem, msinfofile, outlierfile, field, spw,
selectdata, uvrange, antenna, scan, observation, intent, mode,
resmooth, gridmode, wprojplanes, facets, cfcache, rotpainc,
painc, aterm, psterm, mterm, wbawp, conjbeams, epjtable,
interpolation, niter, gain, threshold, psfmode, imagermode,
ftmachine, mosweight, scaletype, multiscale, negcomponent,
smallscalebias, interactive, mask, nchan, start, width,
outframe, veltype, imsize, cell, phasecenter, restfreq, stokes,
weighting, robust, uvtaper, outertaper, innertaper, modelimage,
restoringbeam, pbcor, minpb, usescratch, noise, npixels,
npercycle, cyclefactor, cyclespeedup, nterms, reffreq, chaniter,
flatnoise, allowchunk, btidx):
from taskinit import ms
from taskinit import qa
# from __casac__.quanta import quanta as qa
from __main__ import default, inp
from clean import clean
bt = btidx # 0
if bt + twidth < len(tim) - 1:
et = btidx + twidth - 1
else:
et = len(tim) - 1
# tim_d = tim/3600./24.-np.fix(tim/3600./24.)
if bt == 0:
bt_d = tim[bt] - ((tim[bt + 1] - tim[bt]) / 2)
else:
bt_d = tim[bt] - ((tim[bt] - tim[bt - 1]) / 2)
if et == (len(tim) - 1) or et == -1:
et_d = tim[et] + ((tim[et] - tim[et - 1]) / 2)
else:
et_d = tim[et] + ((tim[et + 1] - tim[et]) / 2)
#
# bt_d=tim[bt]
# et_d=tim[et]+0.005
timerange = qa.time(qa.quantity(bt_d, 's'), prec=9)[0] + '~' + \
qa.time(qa.quantity(et_d, 's'), prec=9)[0]
tmid = (bt_d + et_d) / 2.
btstr = qa.time(qa.quantity(bt_d, 's'), prec=9, form='fits')[0]
print 'cleaning timerange: ' + timerange
try:
image0 = btstr.replace(':', '').replace('-', '')
imname = imageprefix + image0
if overwrite or (len(glob.glob(imname + '*')) == 0):
# inp(taskname = 'clean')
os.system('rm -rf {}*'.format(imname))
clean(vis=vis,
imagename=imname,
outlierfile=outlierfile,
field=field,
spw=spw,
selectdata=selectdata,
timerange=timerange,
uvrange=uvrange,
antenna=antenna,
scan=scan,
observation=str(observation),
intent=intent,
mode=mode,
resmooth=resmooth,
gridmode=gridmode,
wprojplanes=wprojplanes,
facets=facets,
cfcache=cfcache,
rotpainc=rotpainc,
painc=painc,
psterm=psterm,
aterm=aterm,
mterm=mterm,
wbawp=wbawp,
conjbeams=conjbeams,
epjtable=epjtable,
interpolation=interpolation,
niter=niter,
gain=gain,
threshold=threshold,
psfmode=psfmode,
imagermode=imagermode,
ftmachine=ftmachine,
mosweight=mosweight,
scaletype=scaletype,
multiscale=multiscale,
negcomponent=negcomponent,
smallscalebias=smallscalebias,
interactive=interactive,
mask=mask,
nchan=nchan,
start=start,
width=width,
outframe=outframe,
veltype=veltype,
imsize=imsize,
cell=cell,
phasecenter=phasecenter,
restfreq=restfreq,
stokes=stokes,
weighting=weighting,
robust=robust,
uvtaper=uvtaper,
outertaper=outertaper,
innertaper=innertaper,
modelimage=modelimage,
restoringbeam=restoringbeam,
pbcor=pbcor,
minpb=minpb,
usescratch=usescratch,
noise=noise,
npixels=npixels,
npercycle=npercycle,
cyclefactor=cyclefactor,
cyclespeedup=cyclespeedup,
nterms=nterms,
reffreq=reffreq,
chaniter=chaniter,
flatnoise=flatnoise,
allowchunk=False)
clnjunks = ['.flux', '.mask', '.model', '.psf', '.residual']
for clnjunk in clnjunks:
if os.path.exists(imname + clnjunk):
shutil.rmtree(imname + clnjunk)
else:
print imname + ' existed. Clean task aborted.'
if doreg and not os.path.isfile(imname + '.fits'):
# check if ephemfile and msinfofile exist
if not ephem:
print("ephemeris info does not exist!")
return
reftime = [timerange]
helio = vla_prep.ephem_to_helio(msinfo=msinfofile,
ephem=ephem,
reftime=reftime)
imagefile = [imname + '.image']
fitsfile = [imname + '.fits']
vla_prep.imreg(imagefile=imagefile,
fitsfile=fitsfile,
helio=helio,
toTb=False,
scl100=True)
if os.path.exists(imname + '.fits'):
return [True, btstr, imname + '.fits']
else:
return [False, btstr, '']
else:
if os.path.exists(imname + '.image'):
return [True, btstr, imname + '.image']
else:
return [False, btstr, '']
except:
print('error in processing image: ' + btstr)
return [False, btstr, '']
def subvs2(vis=None,
outputvis=None,
timerange='',
spw='',
mode=None,
subtime1=None,
subtime2=None,
smoothaxis=None,
smoothtype=None,
smoothwidth=None,
splitsel=None,
reverse=None,
overwrite=None):
"""Perform vector subtraction for visibilities
Keyword arguments:
vis -- Name of input visibility file (MS)
default: none; example: vis='ngc5921.ms'
outputvis -- Name of output uv-subtracted visibility file (MS)
default: none; example: outputvis='ngc5921_src.ms'
timerange -- Time range of performing the UV subtraction:
default='' means all times. examples:
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
timerange = 'hh:mm:ss~hh:mm:ss'
spw -- Select spectral window/channel.
default = '' all the spectral channels. Example: spw='0:1~20'
mode -- operation mode
default 'linear'
mode = 'linear': use a linear fit for the background to be subtracted
mode = 'lowpass': act as a lowpass filter---smooth the data using different
smooth types and window sizes. Can be performed along either time
or frequency axis
mode = 'highpass': act as a highpass filter---smooth the data first, and
subtract the smoothed data from the original. Can be performed along
either time or frequency axis
mode = 'linear' expandable parameters:
subtime1 -- Time range 1 of the background to be subtracted from the data
default='' means all times. format:
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
timerange = 'hh:mm:ss~hh:mm:ss'
subtime2 -- Time range 2 of the backgroud to be subtracted from the data
default='' means all times. examples:
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
timerange = 'hh:mm:ss~hh:mm:ss'
mode = 'lowpass' or 'highpass' expandable parameters:
smoothaxis -- axis of smooth
Default: 'time'
smoothaxis = 'time': smooth is along the time axis
smoothaxis = 'freq': smooth is along the frequency axis
smoothtype -- type of the smooth depending on the convolving kernel
Default: 'flat'
smoothtype = 'flat': convolving kernel is a flat rectangle,
equivalent to a boxcar moving smooth
smoothtype = 'hanning': Hanning smooth kernel. See numpy.hanning
smoothtype = 'hamming': Hamming smooth kernel. See numpy.hamming
smoothtype = 'bartlett': Bartlett smooth kernel. See numpy.bartlett
smoothtype = 'blackman': Blackman smooth kernel. See numpy.blackman
smoothwidth -- width of the smooth kernel
Default: 5
Examples: smoothwidth=5, meaning the width is 5 pixels
splitsel -- True or False. default = False. If splitsel = False, then the entire input
measurement set is copied as the output measurement set (outputvis), with
background subtracted at selected timerange and spectral channels.
If splitsel = True,then only the selected timerange and spectral channels
are copied into the output measurement set (outputvis).
reverse -- True or False. default = False. If reverse = False, then the times indicated
by subtime1 and/or subtime2 are treated as background and subtracted; If reverse
= True, then reverse the sign of the background-subtracted data. The option can
be used for mapping absorptive structure.
overwrite -- True or False. default = False. If overwrite = True and
outputvis already exists, the selected subtime and spw in the
output measurment set will be replaced with background subtracted
visibilities
"""
# check the visbility ms
casalog.post('input parameters:')
casalog.post('vis: ' + vis)
casalog.post('outputvis: ' + outputvis)
casalog.post('smoothaxis: ' + smoothaxis)
casalog.post('smoothtype: ' + smoothtype)
casalog.post('smoothwidth: ' + str(smoothwidth))
if not outputvis or outputvis.isspace():
raise (ValueError, 'Please specify outputvis')
if os.path.exists(outputvis):
if overwrite:
print(
"The already existing output measurement set will be updated.")
else:
raise (ValueError,
"Output MS %s already exists - will not overwrite." %
outputvis)
else:
if not splitsel:
shutil.copytree(vis, outputvis)
else:
ms.open(vis, nomodify=True)
ms.split(outputvis, spw=spw, time=timerange, whichcol='DATA')
ms.close()
if timerange and (type(timerange) == str):
[btimeo, etimeo] = timerange.split('~')
btimeosec = qa.getvalue(qa.convert(qa.totime(btimeo), 's'))
etimeosec = qa.getvalue(qa.convert(qa.totime(etimeo), 's'))
timebinosec = etimeosec - btimeosec
if timebinosec < 0:
raise Exception(
'Negative timebin! Please check the "timerange" parameter.')
casalog.post('Selected timerange: ' + timerange +
' as the time for UV subtraction.')
else:
casalog.post(
'Output timerange not specified, using the entire timerange')
if spw and (type(spw) == str):
spwlist = spw.split(';')
else:
casalog.post('spw not specified, use all frequency channels')
# read the output data
datams = mstool()
datams.open(outputvis, nomodify=False)
datamsmd = msmdtool()
datamsmd.open(outputvis)
spwinfod = datams.getspectralwindowinfo()
spwinfok = spwinfod.keys()
spwinfok.sort(key=int)
spwinfol = [spwinfod[k] for k in spwinfok]
for s, spi in enumerate(spwinfol):
print('processing spectral window {}'.format(spi['SpectralWindowId']))
datams.selectinit(reset=True)
staql = {'time': '', 'spw': ''}
if not splitsel:
# outputvis is identical to input visibility, do the selection
if timerange and (type(timerange == str)):
staql['time'] = timerange
if spw and (type(spw) == str):
staql['spw'] = spwlist[s]
if not spw and not timerange:
# data selection is not made
print('selecting all spws and times')
staql['spw'] = str(spi['SpectralWindowId'])
else:
# outputvis is splitted, selections have already applied, select all the data
print('split the selected spws and times')
staql['spw'] = str(spi['SpectralWindowId'])
datams.msselect(staql)
orec = datams.getdata(['data', 'time', 'axis_info'], ifraxis=True)
npol, nchan, nbl, ntim = orec['data'].shape
print('dimension of output data', orec['data'].shape)
casalog.post('Number of baselines: ' + str(nbl))
casalog.post('Number of spectral channels: ' + str(nchan))
casalog.post('Number of time pixels: ' + str(ntim))
try:
if mode == 'linear':
# define and check the background time ranges
if subtime1 and (type(subtime1) == str):
[bsubtime1, esubtime1] = subtime1.split('~')
bsubtime1sec = qa.getvalue(
qa.convert(qa.totime(bsubtime1), 's'))
esubtime1sec = qa.getvalue(
qa.convert(qa.totime(esubtime1), 's'))
timebin1sec = esubtime1sec - bsubtime1sec
if timebin1sec < 0:
raise Exception(
'Negative timebin! Please check the "subtime1" parameter.'
)
casalog.post('Selected timerange 1: ' + subtime1 +
' as background for uv subtraction.')
else:
raise Exception(
'Please enter at least one timerange as the background'
)
if subtime2 and (type(subtime2) == str):
[bsubtime2, esubtime2] = subtime2.split('~')
bsubtime2sec = qa.getvalue(
qa.convert(qa.totime(bsubtime2), 's'))
esubtime2sec = qa.getvalue(
qa.convert(qa.totime(esubtime2), 's'))
timebin2sec = esubtime2sec - bsubtime2sec
if timebin2sec < 0:
raise Exception(
'Negative timebin! Please check the "subtime2" parameter.'
)
timebin2 = str(timebin2sec) + 's'
casalog.post('Selected timerange 2: ' + subtime2 +
' as background for uv subtraction.')
# plus 1s is to ensure averaging over the entire timerange
else:
casalog.post(
'Timerange 2 not selected, using only timerange 1 as background'
)
# Select the background indicated by subtime1
ms.open(vis, nomodify=True)
# Select the spw id
# ms.msselect({'time': subtime1})
staql0 = {'time': subtime1, 'spw': ''}
if spw and (type(spw) == str):
staql0['spw'] = spwlist[s]
else:
staql0['spw'] = staql['spw']
ms.msselect(staql0)
rec1 = ms.getdata(['data', 'time', 'axis_info'], ifraxis=True)
# print('shape of the frequency matrix ',rec1['axis_info']['freq_axis']['chan_freq'].shape)
sz1 = rec1['data'].shape
print('dimension of selected background 1', rec1['data'].shape)
# the data shape is (n_pol,n_channel,n_baseline,n_time), no need to reshape
# rec1['data']=rec1['data'].reshape(sz1[0],sz1[1],sz1[2],nspw,sz1[3]/nspw,order='F')
# print('reshaped rec1 ', rec1['data'].shape)
rec1avg = np.average(rec1['data'], axis=3)
casalog.post('Averaging the visibilities in subtime1: ' +
subtime1)
ms.close()
if subtime2 and (type(subtime2) == str):
ms.open(vis, nomodify=True)
# Select the spw id
staql0 = {'time': subtime2, 'spw': ''}
if spw and (type(spw) == str):
staql0['spw'] = spwlist[s]
else:
staql0['spw'] = staql['spw']
ms.msselect(staql0)
rec2 = ms.getdata(['data', 'time', 'axis_info'],
ifraxis=True)
sz2 = rec2['data'].shape
print('dimension of selected background 2',
rec2['data'].shape)
# rec2['data']=rec2['data'].reshape(sz2[0],sz2[1],sz2[2],nspw,sz2[3]/nspw,order='F')
# print('reshaped rec1 ', rec2['data'].shape)
rec2avg = np.average(rec2['data'], axis=3)
ms.close()
casalog.post('Averaged the visibilities in subtime2: ' +
subtime2)
if subtime1 and (not subtime2):
casalog.post(
'Only "subtime1" is defined, subtracting background defined in subtime1: '
+ subtime1)
t1 = (np.amax(rec1['time']) + np.amin(rec1['time'])) / 2.
print('t1: ',
qa.time(qa.quantity(t1, 's'), form='ymd', prec=10))
for i in range(ntim):
orec['data'][:, :, :, i] -= rec1avg
if reverse:
orec['data'][:, :, :,
i] = -orec['data'][:, :, :, i]
if subtime1 and subtime2 and (type(subtime2) == str):
casalog.post(
'Both subtime1 and subtime2 are specified, doing linear interpolation between "subtime1" and "subtime2"'
)
t1 = (np.amax(rec1['time']) + np.amin(rec1['time'])) / 2.
t2 = (np.amax(rec2['time']) + np.amin(rec2['time'])) / 2.
touts = orec['time']
print('t1: ',
qa.time(qa.quantity(t1, 's'), form='ymd', prec=10))
print('t2: ',
qa.time(qa.quantity(t2, 's'), form='ymd', prec=10))
for i in range(ntim):
tout = touts[i]
if tout > np.amax([t1, t2]):
tout = np.amax([t1, t2])
elif tout < np.amin([t1, t2]):
tout = np.amin([t1, t2])
orec['data'][:, :, :, i] -= (rec2avg - rec1avg) * (
tout - t1) / (t2 - t1) + rec1avg
if reverse:
orec['data'][:, :, :,
i] = -orec['data'][:, :, :, i]
elif mode == 'highpass':
if smoothtype != 'flat' and smoothtype != 'hanning' and smoothtype != 'hamming' and smoothtype != 'bartlett' and smoothtype != 'blackman':
raise Exception('Unknown smoothtype ' + str(smoothtype))
if smoothaxis == 'time':
if smoothwidth <= 0 or smoothwidth >= ntim:
raise Exception(
'Specified smooth width is <=0 or >= the total number of '
+ smoothaxis)
else:
for i in range(orec['data'].shape[0]):
for j in range(nchan):
for k in range(nbl):
orec['data'][i, j,
k, :] -= signalsmooth.smooth(
orec['data'][i, j, k, :],
smoothwidth, smoothtype)
if smoothaxis == 'freq':
if smoothwidth <= 0 or smoothwidth >= nchan:
raise Exception(
'Specified smooth width is <=0 or >= the total number of '
+ smoothaxis)
else:
for i in range(orec['data'].shape[0]):
for j in range(nbl):
for k in range(ntim):
orec['data'][i, :, j,
k] -= signalsmooth.smooth(
orec['data'][i, :, j, k],
smoothwidth, smoothtype)
elif mode == 'lowpass':
if smoothtype != 'flat' and smoothtype != 'hanning' and smoothtype != 'hamming' and smoothtype != 'bartlett' and smoothtype != 'blackman':
raise Exception('Unknown smoothtype ' + str(smoothtype))
if smoothaxis == 'time':
if smoothwidth <= 0 or smoothwidth >= ntim:
raise Exception(
'Specified smooth width is <=0 or >= the total number of '
+ smoothaxis)
else:
for i in range(orec['data'].shape[0]):
for j in range(nchan):
for k in range(nbl):
orec['data'][i, j,
k, :] = signalsmooth.smooth(
orec['data'][i, j, k, :],
smoothwidth, smoothtype)
if smoothaxis == 'freq':
if smoothwidth <= 0 or smoothwidth >= nchan:
raise Exception(
'Specified smooth width is <=0 or >= the total number of '
+ smoothaxis)
else:
for i in range(orec['data'].shape[0]):
for j in range(nbl):
for k in range(ntim):
orec['data'][i, :, j,
k] = signalsmooth.smooth(
orec['data'][i, :, j, k],
smoothwidth, smoothtype)
else:
raise Exception('Unknown mode' + str(mode))
except Exception as instance:
print('*** Error ***', instance)
# orec['data']=orec['data'].reshape(szo[0],szo[1],szo[2],szo[3],order='F')
# put the modified data back into the output visibility set
del orec['time']
del orec['axis_info']
# ms.open(outputvis,nomodify=False)
# if not splitsel:
# outputvis is identical to input visibility, do the selection
# if timerange and (type(timerange==str)):
# datams.msselect({'time':timerange})
# if spw and (type(spw)==str):
# datams.selectinit(datadescid=int(spwid))
# nchan=int(echan)-int(bchan)+1
# datams.selectchannel(nchan,int(bchan),1,1)
# if not spw and not timerange:
# data selection is not made
# datams.selectinit(datadescid=0)
# else:
# outputvis is splitted, selections have already applied, select all the data
# datams.selectinit(datadescid=0)
datams.putdata(orec)
datams.close()
datamsmd.done()
def ksc_sim_gauss(projname='sim_7m_array_1GHz_gaus',
antennalist='ksc-7m.cfg',
dishdiam=7,
imagename=None,
indirection='J2000 14h26m46.0s -14d31m22.0s',
incell='1arcsec',
frequency='1.0GHz',
inwidth='1MHz',
radec_offset=[100., 100.],
flux=50.,
majoraxis='40arcsec',
minoraxis='27arcsec',
positionangle='45.0deg',
imsize=[512, 512]):
"""
Simulate observation of an input Gaussian model
:param projname: project name for simobserve
:param antennalist: cfg file of the array configuration
:param dishdiam: diameter of each dish, in meters
:param imagename: name (and path) for output clean image, psf, etc.
:param indirection: phase center of the observation
:param incell: pixel scale of the model/simulated image
:param frequency: central frequency
:param inwidth: frequency bandwidth
:param radec_offset: offset of the Gaussian source from the phasecenter, in arcsec
:param flux: total flux of the Gaussian source, in solar flux unit (sfu)
:param majoraxis: FWHM size of the Gaussian source along the major axis
:param minoraxis: FWHM size of the Gaussian source along the minor axis
:param positionangle: position angle of the Gaussian source
:param imsize: size of the model/simulated image, in pixels (x and y)
:return:
"""
# set voltage patterns and primary beams for KSC 7 m. This is a placeholder for now (but required for PB correction)
vp = vptool()
if len(vp.getvp(telescope='KSC').keys()) == 0:
vprec = vp.setpbairy(telescope='KSC',
dishdiam='{0:.1f}m'.format(dishdiam),
blockagediam='0.75m',
maxrad='1.784deg',
reffreq='1.0GHz',
dopb=True)
# make a Gaussian source
cl = cltool()
ia = iatool()
cl.addcomponent(dir=indirection,
flux=flux * 1e4,
fluxunit='Jy',
freq=frequency,
shape="Gaussian",
majoraxis=majoraxis,
minoraxis=minoraxis,
positionangle=positionangle)
ia.fromshape("Gaussian.im", imsize + [1, 1], overwrite=True)
cs = ia.coordsys()
cs.setunits(['rad', 'rad', '', 'Hz'])
cell_rad = qa.convert(qa.quantity(incell), "rad")['value']
cs.setincrement([-cell_rad, cell_rad], 'direction')
ra_ref = qa.toangle(indirection.split(' ')[1])
dec_ref = qa.toangle(indirection.split(' ')[2])
ra = ra_ref['value'] - radec_offset[0] / 3600.
dec = dec_ref['value'] - radec_offset[1] / 3600.
cs.setreferencevalue([
qa.convert('{0:.4f}deg'.format(ra), 'rad')['value'],
qa.convert('{0:.4f}deg'.format(dec), 'rad')['value']
],
type="direction")
cs.setreferencevalue("1.0GHz", 'spectral')
cs.setincrement('10MHz', 'spectral')
ia.setcoordsys(cs.torecord())
ia.setbrightnessunit("Jy/pixel")
ia.modify(cl.torecord(), subtract=False)
ia.close()
simobserve(project=projname,
skymodel='Gaussian.im',
indirection=indirection,
incell=incell,
incenter=frequency,
inwidth=inwidth,
hourangle='transit',
refdate='2014/11/01',
totaltime='120s',
antennalist=antennalist,
obsmode='int',
overwrite=True)
if not imagename:
imagename = projname + '/tst'
tclean(vis=projname + '/' + projname + '.' + antennalist.split('.')[0] +
'.ms',
imagename=imagename,
imsize=imsize,
cell=incell,
phasecenter=indirection,
niter=200,
interactive=False)
viewer(projname + '/' + projname + '.' + antennalist.split('.')[0] +
'.skymodel')
viewer(imagename + '.psf')
viewer(imagename + '.image')
def ptclean3(vis, imageprefix, imagesuffix, ncpu, twidth, doreg, usephacenter,
reftime, toTb, overwrite, selectdata, field, spw, timerange,
uvrange, antenna, scan, observation, intent, datacolumn, imsize,
cell, phasecenter, stokes, projection, startmodel, specmode,
reffreq, nchan, start, width, outframe, veltype, restfreq,
interpolation, gridder, facets, chanchunks, wprojplanes, vptable,
usepointing, mosweight, aterm, psterm, wbawp, conjbeams, cfcache,
computepastep, rotatepastep, pblimit, normtype, deconvolver,
scales, nterms, smallscalebias, restoration, restoringbeam, pbcor,
outlierfile, weighting, robust, npixels, uvtaper, niter, gain,
threshold, nsigma, cycleniter, cyclefactor, minpsffraction,
maxpsffraction, interactive, usemask, mask, pbmask,
sidelobethreshold, noisethreshold, lownoisethreshold,
negativethreshold, smoothfactor, minbeamfrac, cutthreshold,
growiterations, dogrowprune, minpercentchange, verbose, restart,
savemodel, calcres, calcpsf, parallel, subregion):
if not (type(ncpu) is int):
casalog.post('ncpu should be an integer')
ncpu = 8
if doreg:
# check if ephem and msinfo exist. If not, generate one on the fly
try:
ephem = hf.read_horizons(vis=vis)
except ValueError:
print("error in obtaining ephemeris")
try:
msinfo = hf.read_msinfo(vis)
except ValueError:
print("error in getting ms info")
else:
ephem = None
msinfo = None
if imageprefix:
workdir = os.path.dirname(imageprefix)
else:
workdir = './'
tmpdir = workdir + '/tmp/'
if not os.path.exists(tmpdir):
os.makedirs(tmpdir)
# get number of time pixels
ms.open(vis)
ms.selectinit()
timfreq = ms.getdata(['time', 'axis_info'], ifraxis=True)
tim = timfreq['time']
ms.close()
if twidth < 1:
casalog.post('twidth less than 1. Change to 1')
twidth = 1
if twidth > len(tim):
casalog.post(
'twidth greater than # of time pixels in the dataset. Change to the timerange of the entire dateset'
)
twidth = len(tim)
# find out the start and end time index according to the parameter timerange
# if not defined (empty string), use start and end from the entire time of the ms
if not timerange:
btidx = 0
etidx = len(tim) - 1
else:
try:
(tstart, tend) = timerange.split('~')
bt_s = qa.convert(qa.quantity(tstart, 's'), 's')['value']
et_s = qa.convert(qa.quantity(tend, 's'), 's')['value']
# only time is given but not date, add the date (at 0 UT) from the first record
if bt_s < 86400. or et_s < 86400.:
bt_s += np.fix(
qa.convert(qa.quantity(tim[0], 's'),
'd')['value']) * 86400.
et_s += np.fix(
qa.convert(qa.quantity(tim[0], 's'),
'd')['value']) * 86400.
btidx = np.argmin(np.abs(tim - bt_s))
etidx = np.argmin(np.abs(tim - et_s))
# make the indice back to those bracket by the timerange
if tim[btidx] < bt_s:
btidx += 1
if tim[etidx] > et_s:
etidx -= 1
if etidx <= btidx:
print("ending time must be greater than starting time")
print("reinitiating to the entire time range")
btidx = 0
etidx = len(tim) - 1
except ValueError:
print("keyword 'timerange' has a wrong format")
btstr = qa.time(qa.quantity(tim[btidx], 's'), prec=9, form='fits')[0]
etstr = qa.time(qa.quantity(tim[etidx], 's'), prec=9, form='fits')[0]
iterable = range(btidx, etidx + 1, twidth)
print('First time pixel: ' + btstr)
print('Last time pixel: ' + etstr)
print(str(len(iterable)) + ' images to clean...')
res = []
# partition
clnpart = partial(
clean_iter, tim, vis, imageprefix, imagesuffix, twidth, doreg,
usephacenter, reftime, ephem, msinfo, toTb, overwrite, selectdata,
field, spw, uvrange, antenna, scan, observation, intent, datacolumn,
imsize, cell, phasecenter, stokes, projection, startmodel, specmode,
reffreq, nchan, start, width, outframe, veltype, restfreq,
interpolation, gridder, facets, chanchunks, wprojplanes, vptable,
usepointing, mosweight, aterm, psterm, wbawp, conjbeams, cfcache,
computepastep, rotatepastep, pblimit, normtype, deconvolver, scales,
nterms, smallscalebias, restoration, restoringbeam, pbcor, outlierfile,
weighting, robust, npixels, uvtaper, niter, gain, threshold, nsigma,
cycleniter, cyclefactor, minpsffraction, maxpsffraction, interactive,
usemask, mask, pbmask, sidelobethreshold, noisethreshold,
lownoisethreshold, negativethreshold, smoothfactor, minbeamfrac,
cutthreshold, growiterations, dogrowprune, minpercentchange, verbose,
restart, savemodel, calcres, calcpsf, parallel, subregion, tmpdir)
timelapse = 0
t0 = time()
# parallelization
if ncpu > 1:
import multiprocessing as mprocs
casalog.post('Perform clean in parallel ...')
print('Perform clean in parallel ...')
pool = mprocs.Pool(ncpu)
res = pool.map(clnpart, iterable)
pool.close()
pool.join()
else:
casalog.post('Perform clean in single process ...')
print('Perform clean in single process ...')
for i in iterable:
res.append(clnpart(i))
t1 = time()
timelapse = t1 - t0
print('It took %f secs to complete' % timelapse)
# repackage this into a single dictionary
results = {
'Succeeded': [],
'BeginTime': [],
'EndTime': [],
'ImageName': []
}
for r in res:
results['Succeeded'].append(r[0])
results['BeginTime'].append(r[1])
results['EndTime'].append(r[2])
results['ImageName'].append(r[3])
if os.path.exists(tmpdir):
os.system('rm -rf ' + tmpdir)
return results
def predictcomp(objname=None, standard=None, epoch=None,
minfreq=None, maxfreq=None, nfreqs=None, prefix=None,
antennalist=None, showplot=None, savefig=None, symb=None,
include0amp=None, include0bl=None, blunit=None, bl0flux=None):
"""
Writes a component list named clist to disk and returns a dict of
{'clist': clist,
'objname': objname,
'angdiam': angular diameter in radians (if used in clist),
'standard': standard,
'epoch': epoch,
'freqs': pl.array of frequencies, in GHz,
'uvrange': pl.array of baseline lengths, in m,
'amps': pl.array of predicted visibility amplitudes, in Jy,
'savedfig': False or, if made, the filename of a plot.}
or False on error.
objname: An object supported by standard.
standard: A standard for calculating flux densities, as in setjy.
Default: 'Butler-JPL-Horizons 2010'
epoch: The epoch to use for the calculations. Irrelevant for
extrasolar standards.
minfreq: The minimum frequency to use.
Example: '342.0GHz'
maxfreq: The maximum frequency to use.
Default: minfreq
Example: '346.0GHz'
Example: '', anything <= 0, or None: use minfreq.
nfreqs: The number of frequencies to use.
Default: 1 if minfreq == maxfreq,
2 otherwise.
prefix: The component list will be saved to
prefix + 'spw0_<objname>_<minfreq><epoch>.cl'
Default: ''
antennalist: An array configuration file as used by simdata.
If given, a plot of S vs. |u| will be made.
Default: '' (None, just make clist.)
showplot: Whether or not to show the plot on screen.
Subparameter of antennalist.
Default: Necessarily False if antennalist is not specified.
True otherwise.
savefig: Filename for saving a plot of S vs. |u|.
Subparameter of antennalist.
Default: False (necessarily if antennalist is not specified)
Examples: True (save to prefix + '.png')
'myplot.png' (save to myplot.png)
symb: One of matplotlib's codes for plot symbols: .:,o^v<>s+xDd234hH|_
default: '.'
include0amp: Force the lower limit of the amplitude axis to 0.
Default: False
include0bl: Force the lower limit of the baseline length axis to 0.
blunit: Unit of the baseline length
bl0flux: show zero baseline flux
"""
retval = False
try:
casalog.origin('predictcomp')
# some parameter minimally required
if objname=='':
raise Exception, "Error, objname is undefined"
if minfreq=='':
raise Exception, "Error, minfreq is undefined"
minfreqq = qa.quantity(minfreq)
minfreqHz = qa.convert(minfreqq, 'Hz')['value']
try:
maxfreqq = qa.quantity(maxfreq)
except Exception, instance:
maxfreqq = minfreqq
frequnit = maxfreqq['unit']
maxfreqHz = qa.convert(maxfreqq, 'Hz')['value']
if maxfreqHz <= 0.0:
maxfreqq = minfreqq
maxfreqHz = minfreqHz
if minfreqHz != maxfreqHz:
if nfreqs < 2:
nfreqs = 2
else:
nfreqs = 1
freqs = pl.linspace(minfreqHz, maxfreqHz, nfreqs)
myme = metool()
mepoch = myme.epoch('UTC', epoch)
#if not prefix:
## meanfreq = {'value': 0.5 * (minfreqHz + maxfreqHz),
## 'unit': frequnit}
## prefix = "%s%s_%.7g" % (objname, epoch.replace('/', '-'),
## minfreqq['value'])
## if minfreqHz != maxfreqHz:
## prefix += "to" + maxfreq
## else:
## prefix += minfreqq['unit']
## prefix += "_"
# prefix = ''
#
if not prefix:
if not os.access("./",os.W_OK):
casalog.post("No write access in the current directory, trying to write cl to /tmp...","WARN")
prefix="/tmp/"
if not os.access(prefix, os.W_OK):
casalog.post("No write access to /tmp to write cl file", "SEVERE")
return False
else:
prefixdir=os.path.dirname(prefix)
if not os.path.exists(prefixdir):
prefixdirs = prefixdir.split('/')
if prefixdirs[0]=="":
rootdir = "/" + prefixdirs[1]
else:
rootdir = "./"
if os.access(rootdir,os.W_OK):
os.makedirs(prefixdir)
else:
casalog.post("No write access to "+rootdir+" to write cl file", "SEVERE")
return False
# Get clist
myim = imtool()
if hasattr(myim, 'predictcomp'):
casalog.post('local im instance created', 'DEBUG1')
else:
casalog.post('Error creating a local im instance.', 'SEVERE')
return False
#print "FREQS=",freqs
if standard=='Butler-JPL-Horizons 2012':
clist = predictSolarObjectCompList(objname, mepoch, freqs.tolist(), prefix)
else:
clist = myim.predictcomp(objname, standard, mepoch, freqs.tolist(), prefix)
#print "created componentlist =",clist
if os.path.isdir(clist):
# The spw0 is useless here, but it is added by FluxStandard for the sake of setjy.
casalog.post('The component list was saved to ' + clist)
retval = {'clist': clist,
'objname': objname,
'standard': standard,
'epoch': mepoch,
'freqs (GHz)': 1.0e-9 * freqs,
'antennalist': antennalist}
mycl = cltool()
mycl.open(clist)
comp = mycl.getcomponent(0)
zeroblf=comp['flux']['value']
if standard=='Butler-JPL-Horizons 2012':
f0=comp['spectrum']['frequency']['m0']['value']
else:
f0=retval['freqs (GHz)'][0]
casalog.post("Zero baseline flux %s @ %sGHz " % (zeroblf, f0),'INFO')
mycl.close(False) # False prevents the stupid warning.
for k in ('shape', 'spectrum'):
retval[k] = comp[k]
if antennalist:
retval['spectrum']['bl0flux']={}
retval['spectrum']['bl0flux']['value']=zeroblf[0]
retval['spectrum']['bl0flux']['unit']='Jy'
retval['savedfig'] = savefig
if not bl0flux:
zeroblf=[0.0]
retval.update(plotcomp(retval, showplot, wantdict=True, symb=symb,
include0amp=include0amp, include0bl=include0bl, blunit=blunit, bl0flux=zeroblf[0]))
else:
retval['savedfig'] = None
else:
casalog.post("There was an error in making the component list.",
'SEVERE')
if nspw > 1:
casalog.post('Separate MS into %s spws'%nspw)
config['nspw'] = nspw
config['interpolation'] = interpolation
if restfreq != '':
config['restfreq'] = restfreq
if outframe != '':
config['outframe'] = outframe
if phasecenter != '':
config['phasecenter'] = phasecenter
config['veltype'] = veltype
config['preaverage'] = preaverage
# Only parse timeaverage parameters when timebin > 0s
if timeaverage:
tb = qa.convert(qa.quantity(timebin), 's')['value']
if not tb > 0:
raise Exception, "Parameter timebin must be > '0s' to do time averaging"
if timeaverage:
casalog.post('Parse time averaging parameters')
config['timeaverage'] = True
config['timebin'] = timebin
config['timespan'] = timespan
config['maxuvwdistance'] = maxuvwdistance
if docallib:
casalog.post('Parse docallib parameters')
mycallib = callibrary()
mycallib.read(callib)
config['calibration'] = True
def read_msinfo(vis=None, msinfofile=None, use_scan_time=True):
import glob
# read MS information #
msinfo = dict.fromkeys([
'vis', 'scans', 'fieldids', 'btimes', 'btimestr', 'inttimes', 'ras',
'decs', 'observatory'
])
ms.open(vis)
metadata = ms.metadata()
observatory = metadata.observatorynames()[0]
scans = ms.getscansummary()
scanids = sorted(scans.keys(), key=lambda x: int(x))
nscanid = len(scanids)
btimes = []
btimestr = []
etimes = []
fieldids = []
inttimes = []
dirs = []
ras = []
decs = []
ephem_file = glob.glob(vis + '/FIELD/EPHEM*SUN.tab')
if ephem_file:
print('Loading ephemeris info from {}'.format(ephem_file[0]))
tb.open(ephem_file[0])
col_ra = tb.getcol('RA')
col_dec = tb.getcol('DEC')
col_mjd = tb.getcol('MJD')
if use_scan_time:
from scipy.interpolate import interp1d
f_ra = interp1d(col_mjd, col_ra)
f_dec = interp1d(col_mjd, col_dec)
for idx, scanid in enumerate(scanids):
btimes.append(scans[scanid]['0']['BeginTime'])
etimes.append(scans[scanid]['0']['EndTime'])
fieldid = scans[scanid]['0']['FieldId']
fieldids.append(fieldid)
inttimes.append(scans[scanid]['0']['IntegrationTime'])
ras = f_ra(np.array(btimes))
decs = f_dec(np.array(btimes))
ras = qa.convert(qa.quantity(ras, 'deg'), 'rad')
decs = qa.convert(qa.quantity(decs, 'deg'), 'rad')
else:
ras = qa.convert(qa.quantity(col_ra, 'deg'), 'rad')
decs = qa.convert(qa.quantity(col_dec, 'deg'), 'rad')
else:
for idx, scanid in enumerate(scanids):
btimes.append(scans[scanid]['0']['BeginTime'])
etimes.append(scans[scanid]['0']['EndTime'])
fieldid = scans[scanid]['0']['FieldId']
fieldids.append(fieldid)
inttimes.append(scans[scanid]['0']['IntegrationTime'])
dir = ms.getfielddirmeas('PHASE_DIR', fieldid)
dirs.append(dir)
ras.append(dir['m0'])
decs.append(dir['m1'])
ms.close()
btimestr = [
qa.time(qa.quantity(btimes[idx], 'd'), form='fits', prec=10)[0]
for idx in range(nscanid)
]
msinfo['vis'] = vis
msinfo['scans'] = scans
msinfo['fieldids'] = fieldids
msinfo['btimes'] = btimes
msinfo['btimestr'] = btimestr
msinfo['inttimes'] = inttimes
msinfo['ras'] = ras
msinfo['decs'] = decs
msinfo['observatory'] = observatory
if msinfofile:
np.savez(msinfofile,
vis=vis,
scans=scans,
fieldids=fieldids,
btimes=btimes,
btimestr=btimestr,
inttimes=inttimes,
ras=ras,
decs=decs,
observatory=observatory)
return msinfo
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 imreg(vis=None,
ephem=None,
msinfo=None,
imagefile=None,
timerange=None,
reftime=None,
fitsfile=None,
beamfile=None,
offsetfile=None,
toTb=None,
sclfactor=1.0,
verbose=False,
p_ang=False,
overwrite=True,
usephacenter=True,
deletehistory=False,
subregion=[],
docompress=False):
'''
main routine to register CASA images
Required Inputs:
vis: STRING. CASA measurement set from which the image is derived
imagefile: STRING or LIST. name of the input CASA image
timerange: STRING or LIST. timerange used to generate the CASA image, must have the same length as the input images.
Each element should be in CASA standard time format, e.g., '2012/03/03/12:00:00~2012/03/03/13:00:00'
Optional Inputs:
msinfo: DICTIONARY. CASA MS information, output from read_msinfo. If not provided, generate one from the supplied vis
ephem: DICTIONARY. solar ephem, output from read_horizons.
If not provided, query JPL Horizons based on time info of the vis (internet connection required)
fitsfile: STRING or LIST. name of the output registered fits files
reftime: STRING or LIST. Each element should be in CASA standard time format, e.g., '2012/03/03/12:00:00'
offsetfile: optionally provide an offset with a series of solar x and y offsets with timestamps
toTb: Bool. Convert the default Jy/beam to brightness temperature?
sclfactor: scale the image values up by its value (to compensate VLA 20 dB attenuator)
verbose: Bool. Show more diagnostic info if True.
usephacenter: Bool -- if True, correct for the RA and DEC in the ms file based on solar empheris.
Otherwise assume the phasecenter is correctly pointed to the solar disk center
(EOVSA case)
subregion: Region selection. See 'help par.region' for details.
Usage:
>>> from suncasa.utils import helioimage2fits as hf
>>> hf.imreg(vis='mydata.ms', imagefile='myimage.image', fitsfile='myimage.fits',
timerange='2017/08/21/20:21:10~2017/08/21/20:21:18')
The output fits file is 'myimage.fits'
History:
BC (sometime in 2014): function was first wrote, followed by a number of edits by BC and SY
BC (2019-07-16): Added checks for stokes parameter. Verified that for converting from Jy/beam to brightness temperature,
the convention of 2*k_b*T should always be used. I.e., for unpolarized source, stokes I, RR, LL, XX, YY,
etc. in the output CASA images from (t)clean should all have same values of radio intensity
(in Jy/beam) and brightness temperature (in K).
'''
if deletehistory:
ms_clearhistory(vis)
if not imagefile:
raise ValueError('Please specify input image')
if not timerange:
raise ValueError('Please specify timerange of the input image')
if type(imagefile) == str:
imagefile = [imagefile]
if type(timerange) == str:
timerange = [timerange]
if not fitsfile:
fitsfile = [img + '.fits' for img in imagefile]
if type(fitsfile) == str:
fitsfile = [fitsfile]
nimg = len(imagefile)
if len(timerange) != nimg:
raise ValueError(
'Number of input images does not equal to number of timeranges!')
if len(fitsfile) != nimg:
raise ValueError(
'Number of input images does not equal to number of output fits files!'
)
nimg = len(imagefile)
if verbose:
print(str(nimg) + ' images to process...')
if reftime: # use as reference time to find solar disk RA and DEC to register the image, but not the actual timerange associated with the image
if type(reftime) == str:
reftime = [reftime] * nimg
if len(reftime) != nimg:
raise ValueError(
'Number of reference times does not match that of input images!'
)
helio = ephem_to_helio(vis,
ephem=ephem,
msinfo=msinfo,
reftime=reftime,
usephacenter=usephacenter)
else:
# use the supplied timerange to register the image
helio = ephem_to_helio(vis,
ephem=ephem,
msinfo=msinfo,
reftime=timerange,
usephacenter=usephacenter)
if toTb:
(bmajs, bmins, bpas, beamunits,
bpaunits) = getbeam(imagefile=imagefile, beamfile=beamfile)
for n, img in enumerate(imagefile):
if verbose:
print('processing image #' + str(n) + ' ' + img)
fitsf = fitsfile[n]
timeran = timerange[n]
# obtain duration of the image as FITS header exptime
try:
[tbg0, tend0] = timeran.split('~')
tbg_d = qa.getvalue(qa.convert(qa.totime(tbg0), 'd'))[0]
tend_d = qa.getvalue(qa.convert(qa.totime(tend0), 'd'))[0]
tdur_s = (tend_d - tbg_d) * 3600. * 24.
dateobs = qa.time(qa.quantity(tbg_d, 'd'), form='fits', prec=10)[0]
except:
print('Error in converting the input timerange: ' + str(timeran) +
'. Proceeding to the next image...')
continue
hel = helio[n]
if not os.path.exists(img):
warnings.warn('{} does not existed!'.format(img))
else:
if os.path.exists(fitsf) and not overwrite:
raise ValueError(
'Specified fits file already exists and overwrite is set to False. Aborting...'
)
else:
p0 = hel['p0']
tb.open(img + '/logtable', nomodify=False)
nobs = tb.nrows()
tb.removerows([i + 1 for i in range(nobs - 1)])
tb.close()
ia.open(img)
imr = ia.rotate(pa=str(-p0) + 'deg')
if subregion is not []:
imr = imr.subimage(region=subregion)
imr.tofits(fitsf, history=False, overwrite=overwrite)
imr.close()
imsum = ia.summary()
ia.close()
ia.done()
# construct the standard fits header
# RA and DEC of the reference pixel crpix1 and crpix2
(imra, imdec) = (imsum['refval'][0], imsum['refval'][1])
# find out the difference of the image center to the CASA phase center
# RA and DEC difference in arcseconds
ddec = degrees((imdec - hel['dec_fld'])) * 3600.
dra = degrees((imra - hel['ra_fld']) * cos(hel['dec_fld'])) * 3600.
# Convert into image heliocentric offsets
prad = -radians(hel['p0'])
dx = (-dra) * cos(prad) - ddec * sin(prad)
dy = (-dra) * sin(prad) + ddec * cos(prad)
if offsetfile:
try:
offset = np.load(offsetfile)
except:
raise ValueError(
'The specified offsetfile does not exist!')
reftimes_d = offset['reftimes_d']
xoffs = offset['xoffs']
yoffs = offset['yoffs']
timg_d = hel['reftime']
ind = bisect.bisect_left(reftimes_d, timg_d)
xoff = xoffs[ind - 1]
yoff = yoffs[ind - 1]
else:
xoff = hel['refx']
yoff = hel['refy']
if verbose:
print(
'offset of image phase center to visibility phase center (arcsec): dx={0:.2f}, dy={1:.2f}'
.format(dx, dy))
print(
'offset of visibility phase center to solar disk center (arcsec): dx={0:.2f}, dy={1:.2f}'
.format(xoff, yoff))
(crval1, crval2) = (xoff + dx, yoff + dy)
# update the fits header to heliocentric coordinates
hdu = pyfits.open(fitsf, mode='update')
hdu[0].verify('fix')
header = hdu[0].header
dshape = hdu[0].data.shape
ndim = hdu[0].data.ndim
(cdelt1,
cdelt2) = (-header['cdelt1'] * 3600., header['cdelt2'] * 3600.
) # Original CDELT1, 2 are for RA and DEC in degrees
header['cdelt1'] = cdelt1
header['cdelt2'] = cdelt2
header['cunit1'] = 'arcsec'
header['cunit2'] = 'arcsec'
header['crval1'] = crval1
header['crval2'] = crval2
header['ctype1'] = 'HPLN-TAN'
header['ctype2'] = 'HPLT-TAN'
header['date-obs'] = dateobs # begin time of the image
if not p_ang:
hel['p0'] = 0
try:
# this works for pyfits version of CASA 4.7.0 but not CASA 4.6.0
if tdur_s:
header.set('exptime', tdur_s)
else:
header.set('exptime', 1.)
header.set('p_angle', hel['p0'])
header.set('hgln_obs', 0.)
header.set('rsun_ref', sun.constants.radius.value)
if sunpyver <= 1:
header.set(
'dsun_obs',
sun.sunearth_distance(Time(dateobs)).to(u.meter).value)
header.set(
'rsun_obs',
sun.solar_semidiameter_angular_size(
Time(dateobs)).value)
header.set(
'hglt_obs',
sun.heliographic_solar_center(Time(dateobs))[1].value)
else:
header.set(
'dsun_obs',
sun.earth_distance(Time(dateobs)).to(u.meter).value)
header.set('rsun_obs',
sun.angular_radius(Time(dateobs)).value)
header.set('hglt_obs', sun.L0(Time(dateobs)).value)
except:
# this works for astropy.io.fits
if tdur_s:
header.append(('exptime', tdur_s))
else:
header.append(('exptime', 1.))
header.append(('p_angle', hel['p0']))
header.append(('hgln_obs', 0.))
header.append(('rsun_ref', sun.constants.radius.value))
if sunpyver <= 1:
header.append(
('dsun_obs', sun.sunearth_distance(Time(dateobs)).to(
u.meter).value))
header.append(('rsun_obs',
sun.solar_semidiameter_angular_size(
Time(dateobs)).value))
header.append(('hglt_obs',
sun.heliographic_solar_center(
Time(dateobs))[1].value))
else:
header.append(
('dsun_obs',
sun.earth_distance(Time(dateobs)).to(u.meter).value))
header.append(
('rsun_obs', sun.angular_radius(Time(dateobs)).value))
header.append(('hglt_obs', sun.L0(Time(dateobs)).value))
# check if stokes parameter exist
exist_stokes = False
stokes_mapper = {
'I': 1,
'Q': 2,
'U': 3,
'V': 4,
'RR': -1,
'LL': -2,
'RL': -3,
'LR': -4,
'XX': -5,
'YY': -6,
'XY': -7,
'YX': -8
}
if 'CRVAL3' in header.keys():
if header['CTYPE3'] == 'STOKES':
stokenum = header['CRVAL3']
exist_stokes = True
if 'CRVAL4' in header.keys():
if header['CTYPE4'] == 'STOKES':
stokenum = header['CRVAL4']
exist_stokes = True
if exist_stokes:
if stokenum in stokes_mapper.values():
stokesstr = list(stokes_mapper.keys())[list(
stokes_mapper.values()).index(stokenum)]
else:
print('Stokes parameter {0:d} not recognized'.format(
stokenum))
if verbose:
print('This image is in Stokes ' + stokesstr)
else:
print(
'STOKES Information does not seem to exist! Assuming Stokes I'
)
stokenum = 1
# intensity units to brightness temperature
if toTb:
# get restoring beam info
bmaj = bmajs[n]
bmin = bmins[n]
beamunit = beamunits[n]
data = hdu[
0].data # remember the data order is reversed due to the FITS convension
keys = list(header.keys())
values = list(header.values())
# which axis is frequency?
faxis = keys[values.index('FREQ')][-1]
faxis_ind = ndim - int(faxis)
# find out the polarization of this image
k_b = qa.constants('k')['value']
c_l = qa.constants('c')['value']
# Always use 2*kb for all polarizations
const = 2. * k_b / c_l**2
if header['BUNIT'].lower() == 'jy/beam':
header['BUNIT'] = 'K'
header['BTYPE'] = 'Brightness Temperature'
for i in range(dshape[faxis_ind]):
nu = header['CRVAL' +
faxis] + header['CDELT' + faxis] * (
i + 1 - header['CRPIX' + faxis])
if header['CUNIT' + faxis] == 'KHz':
nu *= 1e3
if header['CUNIT' + faxis] == 'MHz':
nu *= 1e6
if header['CUNIT' + faxis] == 'GHz':
nu *= 1e9
if len(bmaj) > 1: # multiple (per-plane) beams
bmajtmp = bmaj[i]
bmintmp = bmin[i]
else: # one single beam
bmajtmp = bmaj[0]
bmintmp = bmin[0]
if beamunit == 'arcsec':
bmaj0 = np.radians(bmajtmp / 3600.)
bmin0 = np.radians(bmintmp / 3600.)
if beamunit == 'arcmin':
bmaj0 = np.radians(bmajtmp / 60.)
bmin0 = np.radians(bmintmp / 60.)
if beamunit == 'deg':
bmaj0 = np.radians(bmajtmp)
bmin0 = np.radians(bmintmp)
if beamunit == 'rad':
bmaj0 = bmajtmp
bmin0 = bmintmp
beam_area = bmaj0 * bmin0 * np.pi / (4. * log(2.))
factor = const * nu**2 # SI unit
jy_to_si = 1e-26
# print(nu/1e9, beam_area, factor)
factor2 = sclfactor
# if sclfactor:
# factor2 = 100.
if faxis == '3':
data[:,
i, :, :] *= jy_to_si / beam_area / factor * factor2
if faxis == '4':
data[
i, :, :, :] *= jy_to_si / beam_area / factor * factor2
header = fu.headerfix(header)
hdu.flush()
hdu.close()
if ndim - np.count_nonzero(np.array(dshape) == 1) > 3:
docompress = False
'''
Caveat: only 1D, 2D, or 3D images are currently supported by
the astropy fits compression. If a n-dimensional image data array
does not have at least n-3 single-dimensional entries,
force docompress to be False
'''
print(
'warning: The fits data contains more than 3 non squeezable dimensions. Skipping fits compression..'
)
if docompress:
fitsftmp = fitsf + ".tmp.fits"
os.system("mv {} {}".format(fitsf, fitsftmp))
hdu = pyfits.open(fitsftmp)
hdu[0].verify('fix')
header = hdu[0].header
data = hdu[0].data
fu.write_compressed_image_fits(fitsf,
data,
header,
compression_type='RICE_1',
quantize_level=4.0)
os.system("rm -rf {}".format(fitsftmp))
if deletehistory:
ms_restorehistory(vis)
return fitsfile
