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 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 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 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 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 subvs(vis='',
outputvis='',
timerange='',
spw='',
timoffset=4,
windowlen=5,
windowtype='hamming',
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.
windowlen -- Specify the width of window for smoothing
windowtype --The type of window from 'flat', 'hanning', 'hamming', 'bartlett', 'blackman'
flat window will produce a moving average smoothing.
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
"""
# Get the time and frequency axis of the input ms
# Open the ms and plot dynamic spectrum
print 'using window length: ', windowlen
print 'using window type: ', windowtype
ms.open(vis, nomodify=True)
# ms.selectinit(datadescid=0)
timfreq = ms.getdata(['time', 'axis_info'], ifraxis=True)
tim = timfreq['time']
# check timerange input; default: entire timerange
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.'
else:
casalog.post('Selected timerange: ' + timerange +
' as the time for UV subtraction.')
else:
casalog.post(
'Output timerange not specified, using the entire timerange')
timerange = str(qa.time(qa.quantity(
tim[0], 's'), prec=8)[0]) + '~' + str(
qa.time(qa.quantity(tim[-1], 's'), prec=8)[0])
print 'Output timerange not specified, using the entire timerange', timerange
# check spectral window input; default: entire channels of spectral window 0
if spw and (type(spw) == str):
[spwid, chanran] = spw.split(':')
[bchan, echan] = chanran.split('~')
nchan = int(echan) - int(bchan) + 1
else:
casalog.post('spw not specified, use all frequency channels')
freq = timfreq['axis_info']['freq_axis']['chan_freq'].flatten()
nchan = len(freq)
spwid = '0'
bchan = '0'
echan = str(nchan - 1)
print 'spw not specified, use all frequency channels', spwid + ':' + bchan + '~' + str(
nchan - 1)
ntimergn = len(timerange)
# To avoid memory error, split the channel into smaller segements for smoothing
cellstep = 2
chancell = int(nchan / cellstep)
l = range(nchan)
chunks = [l[x:x + cellstep] for x in xrange(0, len(l), cellstep)]
#spwrange='0:0~'+str(chancell)
ms.close()
if not (timoffset and (type(timoffset) == int)):
timoffset = int(4)
for i in range(len(chunks)):
spwrange = spwid + ':' + str(int(bchan) + min(chunks[i])) + '~' + str(
int(bchan) + max(chunks[i]))
print 'Subtracting visibility from spectral range: ', spwrange
result2 = task_subvs_lv1.subvs(vis, outputvis, timerange, spwrange,
timoffset, windowlen, windowtype,
splitsel, False, True)
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 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 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 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 svplot(vis, timerange=None, spw='', workdir='./', specfile=None, bl=None, uvrange=None,
stokes='RR,LL', dmin=None, dmax=None,
goestime=None, reftime=None,
xycen=None, fov=[500.,500.], xyrange=None, restoringbeam=[''], robust=0.0,
niter=500, imsize=[512], cell=['5.0arcsec'],interactive=False,
usemsphacenter=True, imagefile=None, fitsfile=None, plotaia=True,
aiawave=171, aiafits=None, savefig=False, mkmovie=False, overwrite=True, ncpu=10, twidth=1, verbose=True):
'''
Required inputs:
vis: calibrated CASA measurement set
Important optional inputs:
timerange: timerange for clean. Standard CASA time selection format.
If not provided, use the entire range (*BE CAREFUL, COULD BE VERY SLOW*)
spw: spectral window selection following the CASA syntax.
Examples: spw='1:2~60' (spw id 1, channel range 2-60); spw='*:1.2~1.3GHz' (selects all channels within 1.2-1.3 GHz; note the *)
specfile: supply dynamic spectrum save file (from suncasa.utils.dspec2.get_dspec()). Otherwise
generate a median dynamic spectrum on the fly
Optional inputs:
bl: baseline to generate dynamic spectrum
uvrange: uvrange to select baselines for generating dynamic spectrum
stokes: polarization of the clean image, can be 'RR,LL' or 'I,V'
dmin,dmax: color bar parameter
goestime: goes plot time, example ['2016/02/18 18:00:00','2016/02/18 23:00:00']
rhessisav: rhessi savefile
reftime: reftime for the image
xycen: center of the image in helioprojective coordinates (HPLN/HPLT), in arcseconds. Example: [900, -150.]
fov: field of view in arcsecs. Example: [500., 500.]
xyrange: field of view in solar XY coordinates. Format: [[x1,x2],[y1,y2]]. Example: [[900., 1200.],[0,300]]
***NOTE: THIS PARAMETER OVERWRITES XYCEN AND FOV***
aiawave: wave length of aia file in a
imagefile: if imagefile provided, use it. Otherwise do clean and generate a new one.
fitsfile: if fitsfile provided, use it. Otherwise generate a new one
savefig: whether to save the figure
Example:
'''
if xycen:
xc, yc = xycen
xlen, ylen = fov
if parse_version(sunpy.__version__)>parse_version('0.8.0'):
xyrange = [[xc - xlen / 2.0, yc - ylen / 2.0], [xc + xlen / 2.0, yc + ylen / 2.0]]
else:
xyrange = [[xc - xlen / 2.0, xc + xlen / 2.0], [yc - ylen / 2.0, yc + ylen / 2.0]]
stokes_allowed = ['RR,LL', 'I,V', 'RRLL', 'IV']
if not stokes in stokes_allowed:
print 'wrong stokes parameter ' + str(stokes) + '. Allowed values are ' + ', '.join(stokes_allowed)
return -1
if stokes == 'RRLL':
stokes = 'RR,LL'
if stokes == 'IV':
stokes = 'I,V'
if vis[-1] == '/':
vis = vis[:-1]
if not os.path.exists(vis):
print 'input measurement not exist'
return -1
if aiafits is None:
aiafits = ''
# split the data
# generating dynamic spectrum
if not os.path.exists(workdir):
os.makedirs(workdir)
if specfile:
try:
specdata = np.load(specfile)
except:
print('Provided dynamic spectrum file not numpy npz. Generating one from the visibility data')
specfile = os.path.join(workdir, os.path.basename(vis) + '.dspec.npz')
dspec_external(vis, workdir=workdir, specfile=specfile)
specdata = np.load(specfile) # specdata = ds.get_dspec(vis, domedian=True, verbose=True)
else:
print('Dynamic spectrum file not provided; Generating one from the visibility data')
# specdata = ds.get_dspec(vis, domedian=True, verbose=True)
specfile = os.path.join(workdir, os.path.basename(vis) + '.dspec.npz')
dspec_external(vis, workdir=workdir, specfile=specfile)
specdata = np.load(specfile)
tb.open(vis)
starttim = Time(tb.getcell('TIME', 0) / 24. / 3600., format='mjd')
endtim = Time(tb.getcell('TIME', tb.nrows() - 1) / 24. / 3600., format='mjd')
tb.close()
datstr = starttim.iso[:10]
if timerange is None or timerange == '':
starttim1 = starttim
endtim1 = endtim
timerange = '{0}~{1}'.format(starttim.iso.replace('-', '/').replace(' ', '/'), endtim.iso.replace('-', '/').replace(' ', '/'))
else:
try:
(tstart, tend) = timerange.split('~')
if tstart[2] == ':':
starttim1 = Time(datstr + 'T' + tstart)
endtim1 = Time(datstr + 'T' + tend)
timerange = '{0}/{1}~{0}/{2}'.format(datstr.replace('-', '/'), tstart, tend)
else:
starttim1 = Time(qa.quantity(tstart, 'd')['value'], format='mjd')
endtim1 = Time(qa.quantity(tend, 'd')['value'], format='mjd')
except ValueError:
print "keyword 'timerange' in wrong format"
midtime_mjd = (starttim1.mjd + endtim1.mjd) / 2.
if vis.endswith('/'):
vis = vis[:-1]
visname = os.path.basename(vis)
bt = starttim1.plot_date
et = endtim1.plot_date
# find out min and max frequency for plotting in dynamic spectrum
ms.open(vis)
metadata = ms.metadata()
observatory = metadata.observatorynames()[0]
spwInfo = ms.getspectralwindowinfo()
nspw = len(spwInfo)
if not spw:
spw = '0~' + str(nspw - 1)
staql = {'timerange': timerange, 'spw': spw}
if ms.msselect(staql, onlyparse=True):
ndx = ms.msselectedindices()
chan_sel = ndx['channel']
nspw = chan_sel.shape[0]
bspw = chan_sel[0, 0]
bchan = chan_sel[0, 1]
espw = chan_sel[-1, 0]
echan = chan_sel[-1, 2]
bfreq = spwInfo[str(bspw)]['Chan1Freq'] + spwInfo[str(bspw)]['ChanWidth'] * bchan
efreq = spwInfo[str(espw)]['Chan1Freq'] + spwInfo[str(espw)]['ChanWidth'] * echan
bfreqghz = bfreq / 1e9
efreqghz = efreq / 1e9
if verbose:
print 'selected timerange {}'.format(timerange)
print 'selected frequency range {0:6.3f} to {1:6.3f} GHz'.format(bfreqghz, efreqghz)
else:
print "spw or timerange selection failed. Aborting..."
ms.close()
return -1
ms.close()
if observatory == 'EOVSA':
print 'Provide stokes: ' + str(stokes) + '. However EOVSA has linear feeds. Force stokes to be IV'
stokes = 'I,V'
if mkmovie:
plt.ioff()
# fig = plt.figure(figsize=(12, 7.5), dpi=100)
if fitsfile:
pass
else:
if not imagefile:
# from ptclean_cli import ptclean_cli as ptclean
eph = hf.read_horizons(t0=Time(midtime_mjd, format='mjd'))
if observatory == 'EOVSA' or (not usemsphacenter):
phasecenter = ''
else:
phasecenter = 'J2000 ' + str(eph['ra'][0])[:15] + 'rad ' + str(eph['dec'][0])[:15] + 'rad'
print 'use phasecenter: ' + phasecenter
qlookfitsdir = os.path.join(workdir, 'qlookfits/')
qlookfigdir = os.path.join(workdir, 'qlookimgs/')
imresfile = os.path.join(qlookfitsdir, '{}.imres.npz'.format(os.path.basename(vis)))
if overwrite:
imres = mk_qlook_image(vis, twidth=twidth, ncpu=ncpu, imagedir=qlookfitsdir, phasecenter=phasecenter, stokes=stokes,
c_external=True)
else:
if os.path.exists(imresfile):
imres = np.load(imresfile)
imres = imres['imres'].item()
else:
print('Image results file not found; Creating new images.')
imres = mk_qlook_image(vis, twidth=twidth, ncpu=ncpu, imagedir=qlookfitsdir, phasecenter=phasecenter, stokes=stokes,
c_external=True)
if not os.path.exists(qlookfigdir):
os.makedirs(qlookfigdir)
plt_qlook_image(imres, figdir=qlookfigdir, specdata=specdata, verbose=True, stokes=stokes, fov=xyrange)
else:
spec = specdata['spec']
(npol, nbl, nfreq, ntim) = spec.shape
tidx = range(ntim)
fidx = range(nfreq)
tim = specdata['tim']
freq = specdata['freq']
freqghz = freq / 1e9
spec_tim = Time(specdata['tim'] / 3600. / 24., format='mjd')
timstrr = spec_tim.plot_date
plt.ion()
fig = plt.figure(figsize=(12, 7), dpi=100)
gs1 = gridspec.GridSpec(3, 1)
gs1.update(left=0.08, right=0.32, wspace=0.05)
gs2 = gridspec.GridSpec(2, 2)
gs2.update(left=0.38, right=0.98, hspace=0.02, wspace=0.02)
spec_1 = np.absolute(spec[0, 0, :, :])
spec_2 = np.absolute(spec[1, 0, :, :])
if observatory == 'EVLA':
# circular feeds
polstr = ['RR', 'LL']
if observatory == 'EOVSA' or observatory == 'ALMA':
# linear feeds
polstr = ['XX', 'YY']
print 'plot the dynamic spectrum in pol ' + ' & '.join(polstr)
ax1 = plt.subplot(gs1[0])
ax1.pcolormesh(timstrr, freqghz, spec_1, cmap='jet', vmin=dmin, vmax=dmax)
ax1.set_xlim(timstrr[tidx[0]], timstrr[tidx[-1]])
ax1.xaxis_date()
ax1.xaxis.set_major_formatter(DateFormatter("%H:%M:%S"))
# ax1.set_xticklabels(['']*10)
ax1.set_ylim(freqghz[fidx[0]], freqghz[fidx[-1]])
ax1.set_ylabel('Frequency (GHz)', fontsize=10)
ax1.set_title(observatory + ' ' + datstr + ' ' + polstr[0] + ' & ' + polstr[1], fontsize=12)
ax1.set_autoscale_on(False)
ax1.add_patch(patches.Rectangle((bt, bfreqghz), et - bt, efreqghz - bfreqghz, ec='w', fill=False))
ax1.plot([(bt + et) / 2.], [(bfreqghz + efreqghz) / 2.], '*w', ms=12)
for tick in ax1.get_xticklabels():
tick.set_fontsize(8)
for tick in ax1.get_yticklabels():
tick.set_fontsize(8)
ax2 = plt.subplot(gs1[1])
ax2.pcolormesh(timstrr, freqghz, spec_2, cmap='jet', vmin=dmin, vmax=dmax)
ax2.set_xlim(timstrr[tidx[0]], timstrr[tidx[-1]])
ax2.xaxis_date()
ax2.xaxis.set_major_formatter(DateFormatter("%H:%M:%S"))
ax2.set_ylim(freqghz[fidx[0]], freqghz[fidx[-1]])
ax2.set_ylabel('Frequency (GHz)', fontsize=10)
for tick in ax2.get_xticklabels():
tick.set_fontsize(8)
for tick in ax2.get_yticklabels():
tick.set_fontsize(8)
ax2.set_autoscale_on(False)
ax2.add_patch(patches.Rectangle((bt, bfreqghz), et - bt, efreqghz - bfreqghz, ec='w', fill=False))
ax2.plot([(bt + et) / 2.], [(bfreqghz + efreqghz) / 2.], '*w', ms=12)
# Second part: GOES plot
if goestime:
btgoes = goestime[0]
etgoes = goestime[1]
else:
datstrg = datstr.replace('-', '/')
btgoes = datstrg + ' ' + qa.time(qa.quantity(tim[0] - 1800, 's'), form='clean', prec=9)[0]
etgoes = datstrg + ' ' + qa.time(qa.quantity(tim[tidx[-1] - 1] + 1800, 's'), form='clean', prec=9)[0]
if verbose:
print 'Acquire GOES soft X-ray data in from ' + btgoes + ' to ' + etgoes
ax3 = plt.subplot(gs1[2])
try:
from sunpy import lightcurve as lc
from sunpy.time import TimeRange
goest = lc.GOESLightCurve.create(TimeRange(btgoes, etgoes))
except:
goesscript = os.path.join(workdir, 'goes.py')
goesdatafile = os.path.join(workdir, 'goes.dat')
os.system('rm -rf {}'.format(goesscript))
fi = open(goesscript, 'wb')
fi.write('import os \n')
fi.write('from sunpy.time import TimeRange \n')
fi.write('from sunpy import lightcurve as lc \n')
fi.write('import pickle \n')
fi.write('goesplottim = TimeRange("{0}", "{1}") \n'.format(btgoes, etgoes))
fi.write('goes = lc.GOESLightCurve.create(goesplottim) \n')
fi.write('fi2 = open("{}", "wb") \n'.format(goesdatafile))
fi.write('pickle.dump(goes, fi2) \n')
fi.write('fi2.close()')
fi.close()
try:
os.system('python {}'.format(goesscript))
os.system('rm -rf {}'.format(goesscript))
except NameError:
print "Bad input names"
except ValueError:
print "Bad input values"
except:
print "Unexpected error:", sys.exc_info()[0]
print "Error in generating GOES light curves. Proceed without GOES..."
if os.path.exists(goesdatafile):
fi1 = file(goesdatafile, 'rb')
goest = pickle.load(fi1)
fi1.close()
try:
dates = mpl.dates.date2num(parse_time(goest.data.index))
goesdif = np.diff(goest.data['xrsb'])
gmax = np.nanmax(goesdif)
gmin = np.nanmin(goesdif)
ran = gmax - gmin
db = 2.8 / ran
goesdifp = goesdif * db + gmin + (-6)
ax3.plot_date(dates, np.log10(goest.data['xrsb']), '-', label='1.0--8.0 $\AA$', color='red', lw=2)
ax3.plot_date(dates[0:-1], goesdifp, '-', label='derivate', color='blue', lw=0.4)
ax3.set_ylim([-7, -3])
ax3.set_yticks([-7, -6, -5, -4, -3])
ax3.set_yticklabels([r'$10^{-7}$', r'$10^{-6}$', r'$10^{-5}$', r'$10^{-4}$', r'$10^{-3}$'])
ax3.set_title('Goes Soft X-ray', fontsize=12)
ax3.set_ylabel('Watts m$^{-2}$')
ax3.set_xlabel(datetime.datetime.isoformat(goest.data.index[0])[0:10])
ax3.axvspan(dates[899], dates[dates.size - 899], alpha=0.2)
ax2 = ax3.twinx()
# ax2.set_yscale("log")
ax2.set_ylim([-7, -3])
ax2.set_yticks([-7, -6, -5, -4, -3])
ax2.set_yticklabels(['B', 'C', 'M', 'X', ''])
ax3.yaxis.grid(True, 'major')
ax3.xaxis.grid(False, 'major')
ax3.legend(prop={'size': 6})
formatter = mpl.dates.DateFormatter('%H:%M')
ax3.xaxis.set_major_formatter(formatter)
ax3.fmt_xdata = mpl.dates.DateFormatter('%H:%M')
except:
print 'Error in downloading GOES soft X-ray data. Proceeding with out soft X-ray plot.'
# third part
# start to download the fits files
if plotaia:
if not aiafits:
newlist = []
items = glob.glob('*.fits')
for names in items:
str1 = starttim1.iso[:4] + '_' + starttim1.iso[5:7] + '_' + starttim1.iso[8:10] + 't' + starttim1.iso[
11:13] + '_' + starttim1.iso[14:16]
str2 = str(aiawave)
if names.endswith(".fits"):
if names.find(str1) != -1 and names.find(str2) != -1:
newlist.append(names)
newlist.append('0')
if newlist and os.path.exists(newlist[0]):
aiafits = newlist[0]
else:
print 'downloading the aiafits file'
wave1 = aiawave - 3
wave2 = aiawave + 3
t1 = Time(starttim1.mjd - 0.02 / 24., format='mjd')
t2 = Time(endtim1.mjd + 0.02 / 24., format='mjd')
try:
from sunpy.net import vso
client = vso.VSOClient()
qr = client.query(vso.attrs.Time(t1.iso, t2.iso), vso.attrs.Instrument('aia'), vso.attrs.Wave(wave1 * u.AA, wave2 * u.AA))
res = client.get(qr, path='{file}')
except:
SdoDownloadscript = os.path.join(workdir, 'SdoDownload.py')
os.system('rm -rf {}'.format(SdoDownloadscript))
fi = open(SdoDownloadscript, 'wb')
fi.write('from sunpy.net import vso \n')
fi.write('from astropy import units as u \n')
fi.write('client = vso.VSOClient() \n')
fi.write(
"qr = client.query(vso.attrs.Time('{0}', '{1}'), vso.attrs.Instrument('aia'), vso.attrs.Wave({2} * u.AA, {3} * u.AA)) \n".format(
t1.iso, t2.iso, wave1, wave2))
fi.write("res = client.get(qr, path='{file}') \n")
fi.close()
try:
os.system('python {}'.format(SdoDownloadscript))
except NameError:
print "Bad input names"
except ValueError:
print "Bad input values"
except:
print "Unexpected error:", sys.exc_info()[0]
print "Error in Downloading AIA fits files. Proceed without AIA..."
# Here something is needed to check whether it has finished downloading the fits files or not
if not aiafits:
newlist = []
items = glob.glob('*.fits')
for nm in items:
str1 = starttim1.iso[:4] + '_' + starttim1.iso[5:7] + '_' + starttim1.iso[8:10] + 't' + starttim1.iso[
11:13] + '_' + starttim1.iso[14:16]
str2 = str(aiawave)
if nm.find(str1) != -1 and nm.find(str2) != -1:
newlist.append(nm)
if newlist:
aiafits = newlist[0]
print 'AIA fits ' + aiafits + ' selected'
else:
print 'no AIA fits files found. Proceed without AIA'
try:
aiamap = smap.Map(aiafits)
except:
print 'error in reading aiafits. Proceed without AIA'
# RCP or I
ax4 = plt.subplot(gs2[0, 0])
ax5 = plt.subplot(gs2[1, 0])
# LCP or V
ax6 = plt.subplot(gs2[0, 1])
ax7 = plt.subplot(gs2[1, 1])
if fitsfile:
pass
else:
if not imagefile:
eph = hf.read_horizons(t0=Time(midtime_mjd, format='mjd'))
if observatory == 'EOVSA' or (not usemsphacenter):
print 'This is EOVSA data'
# use RA and DEC from FIELD ID 0
tb.open(vis+'/FIELD')
phadir = tb.getcol('PHASE_DIR').flatten()
tb.close()
ra0 = phadir[0]
dec0 = phadir[1]
if stokes == 'RRLL' or stokes == 'RR,LL':
print 'Provide stokes: ' + str(stokes) + '. However EOVSA has linear feeds. Force stokes to be IV'
stokes = 'I,V'
else:
ra0 = eph['ra'][0]
dec0 = eph['dec'][0]
if not xycen:
# use solar disk center as default
phasecenter = 'J2000 ' + str(ra0) + 'rad ' + str(dec0) + 'rad'
else:
x0 = np.radians(xycen[0]/3600.)
y0 = np.radians(xycen[1]/3600.)
p0 = np.radians(eph['p0'][0]) # p angle in radians
raoff = -((x0) * np.cos(p0) - y0 * np.sin(p0))/np.cos(eph['dec'][0])
decoff = (x0) * np.sin(p0) + y0 * np.cos(p0)
newra = ra0 + raoff
newdec = dec0 + decoff
phasecenter = 'J2000 ' + str(newra) + 'rad ' + str(newdec) + 'rad'
imagename = os.path.join(workdir, visname + '.outim')
if os.path.exists(imagename + '.image') or os.path.exists(imagename + '.flux'):
os.system('rm -rf ' + imagename + '.*')
sto = stokes.replace(',', '')
print 'do clean for ' + timerange + ' in spw ' + spw + ' stokes ' + sto
print 'Original phasecenter: '+ str(ra0) + str(dec0)
print 'use phasecenter: ' + phasecenter
clean(vis=vis, imagename=imagename, selectdata=True, spw=spw, timerange=timerange, stokes=sto,
niter=niter, interactive=interactive, npercycle=50, imsize=imsize, cell=cell, restoringbeam=restoringbeam,
weighting='briggs', robust=robust, phasecenter=phasecenter)
os.system('rm -rf ' + imagename + '.psf')
os.system('rm -rf ' + imagename + '.flux')
os.system('rm -rf ' + imagename + '.model')
os.system('rm -rf ' + imagename + '.mask')
os.system('rm -rf ' + imagename + '.residual')
imagefile = imagename + '.image'
fitsfile = imagefile + '.fits'
hf.imreg(vis=vis, ephem=eph, imagefile=imagefile, timerange=timerange, reftime=reftime, fitsfile=fitsfile, verbose=True, overwrite=True)
print 'fits file ' + fitsfile + ' selected'
ax4.cla()
ax5.cla()
ax6.cla()
ax7.cla()
rfits = fitsfile
try:
hdulist = fits.open(rfits)
hdu = hdulist[0]
(npol, nf, nx, ny) = hdu.data.shape
rmap = smap.Map(hdu.data[0, 0, :, :], hdu.header)
except:
print 'radio fits file not recognized by sunpy.map. Aborting...'
return -1
if npol > 1:
rmap1 = smap.Map(hdu.data[0, 0, :, :], hdu.header)
rmap2 = smap.Map(hdu.data[1, 0, :, :], hdu.header)
XX, YY = np.meshgrid(np.arange(rmap.data.shape[1]), np.arange(rmap.data.shape[0]))
try:
rmapx, rmapy = rmap.pixel_to_data(XX * u.pix, YY * u.pix)
except:
rmapxy = rmap.pixel_to_data(XX * u.pix, YY * u.pix)
rmapx = rmapxy.Tx
rmapy = rmapxy.Ty
if not xyrange:
if xycen:
x0 = xycen[0] * u.arcsec
y0 = xycen[1] * u.arcsec
if not xycen:
row, col = rmap1.data.shape
positon = np.nanargmax(rmap1.data)
m, n = divmod(positon, col)
x0 = rmap1.xrange[0] + rmap1.scale[1] * (n + 0.5) * u.pix
y0 = rmap1.yrange[0] + rmap1.scale[0] * (m + 0.5) * u.pix
if len(fov) == 1:
fov=[fov]*2
sz_x = fov[0] * u.arcsec
sz_y = fov[1] * u.arcsec
x1 = x0 - sz_x/2.
x2 = x0 + sz_x/2.
y1 = y0 - sz_y/2.
y2 = y0 + sz_y/2.
xyrange = [[x1.value, x2.value], [y1.value, y2.value]]
else:
sz_x = xyrange[0][1] - xyrange[0][0]
sz_y = xyrange[1][1] - xyrange[1][0]
clevels1 = np.linspace(0.2, 0.9, 5)
if stokes.split(',')[1] == 'V':
clevels2 = np.array([0.8, -0.6, -0.4, -0.2, 0.2, 0.4, 0.6, 0.8])
else:
clevels2 = np.linspace(0.2, 0.9, 5)
if 'aiamap' in vars():
aiamap.plot_settings['cmap'] = plt.get_cmap('binary')
if rmap:
title = 'AIA {0:.0f} + {1} {2:6.3f} GHz'.format(aiamap.wavelength.value, observatory, (bfreqghz + efreqghz) / 2.0)
else:
title = 'AIA {0:.0f}'.format(aiamap.wavelength.value)
aiamap.plot(axes=ax4)
ax4.set_title(title + ' ' + stokes.split(',')[0], fontsize=12)
aiamap.draw_limb()
aiamap.draw_grid()
aiamap.draw_rectangle((xyrange[0][0], xyrange[1][0]) * u.arcsec, sz_x, sz_y)
aiamap.plot(axes=ax6)
ax6.set_title(title + ' ' + stokes.split(',')[1], fontsize=12)
aiamap.draw_limb()
aiamap.draw_grid()
aiamap.draw_rectangle((xyrange[0][0], xyrange[1][0]) * u.arcsec, sz_x, sz_y)
if rmap:
ax4.contour(rmapx.value, rmapy.value, rmap1.data, levels=clevels1 * np.nanmax(rmap1.data), cmap=cm.jet)
ax6.contour(rmapx.value, rmapy.value, rmap2.data, levels=clevels2 * np.nanmax(rmap2.data), cmap=cm.RdBu)
ax4.text(0.02, 0.02, 'AIA {0:.0f} '.format(aiamap.wavelength.value) + aiamap.date.strftime('%H:%M:%S'),
verticalalignment='bottom', horizontalalignment='left', transform=ax4.transAxes, color='k',
fontsize=10)
ax6.text(0.02, 0.02, 'AIA {0:.0f} '.format(aiamap.wavelength.value) + aiamap.date.strftime('%H:%M:%S'),
verticalalignment='bottom', horizontalalignment='left', transform=ax6.transAxes, color='k',
fontsize=10)
else:
title = '{0} {1:6.3f} GHz'.format(observatory, (bfreqghz + efreqghz) / 2.0)
rmap1.plot(axes=ax4, cmap=cm.jet)
ax4.set_title(title + ' ' + stokes.split(',')[0], fontsize=12)
rmap1.draw_limb()
rmap1.draw_grid()
rmap1.draw_rectangle((xyrange[0][0], xyrange[1][0]) * u.arcsec, sz_x, sz_y)
rmap2.plot(axes=ax6, cmap=cm.RdBu)
ax6.set_title(title + ' ' + stokes.split(',')[1], fontsize=12)
rmap2.draw_limb()
rmap2.draw_grid()
# ax4.contour(rmapx.value, rmapy.value, rmap1.data, levels=np.linspace(0.2, 0.9, 5) * np.nanmax(rmap1.data),
# cmap=cm.gray)
# ax6.contour(rmapx.value, rmapy.value, rmap2.data, levels=np.linspace(0.2, 0.9, 5) * np.nanmax(rmap2.data),
# cmap=cm.gray)
rmap2.draw_rectangle((xyrange[0][0], xyrange[1][0]) * u.arcsec, sz_x, sz_y)
ax4.set_xlim(-1200, 1200)
ax4.set_ylim(-1200, 1200)
ax6.set_xlim(-1200, 1200)
ax6.set_ylim(-1200, 1200)
try:
subrmap1 = rmap1.submap(xyrange[0] * u.arcsec, xyrange[1] * u.arcsec)
subrmap2 = rmap2.submap(xyrange[0] * u.arcsec, xyrange[1] * u.arcsec)
except:
bl = SkyCoord(xyrange[0][0] * u.arcsec, xyrange[1][0] * u.arcsec, frame=rmap1.coordinate_frame)
tr = SkyCoord(xyrange[0][1] * u.arcsec, xyrange[1][1] * u.arcsec, frame=rmap1.coordinate_frame)
subrmap1 = rmap1.submap(bl, tr)
subrmap2 = rmap2.submap(bl, tr)
XX, YY = np.meshgrid(np.arange(subrmap1.data.shape[1]), np.arange(subrmap1.data.shape[0]))
try:
subrmapx, subrmapy = subrmap1.pixel_to_data(XX * u.pix, YY * u.pix)
except:
subrmapxy = subrmap1.pixel_to_data(XX * u.pix, YY * u.pix)
subrmapx = subrmapxy.Tx
subrmapy = subrmapxy.Ty
if 'aiamap' in vars():
try:
subaiamap = aiamap.submap(xyrange[0] * u.arcsec, xyrange[1] * u.arcsec)
except:
bl = SkyCoord(xyrange[0][0] * u.arcsec, xyrange[1][0] * u.arcsec, frame=aiamap.coordinate_frame)
tr = SkyCoord(xyrange[0][1] * u.arcsec, xyrange[1][1] * u.arcsec, frame=aiamap.coordinate_frame)
subaiamap = aiamap.submap(bl, tr)
subaiamap.plot(axes=ax5, title='')
subaiamap.draw_limb()
subaiamap.draw_grid()
subaiamap.plot(axes=ax7, title='')
subaiamap.draw_limb()
subaiamap.draw_grid()
ax5.contour(subrmapx.value, subrmapy.value, subrmap1.data, levels=clevels1 * np.nanmax(subrmap1.data), cmap=cm.jet)
ax7.contour(subrmapx.value, subrmapy.value, subrmap2.data, levels=clevels2 * np.nanmax(subrmap2.data),
cmap=cm.RdBu) # subaiamap.draw_rectangle((fov[0][0], fov[1][0]) * u.arcsec, 400 * u.arcsec, 400 * u.arcsec)
else:
subrmap1.plot(axes=ax5, cmap=cm.jet, title='')
subrmap1.draw_limb()
subrmap1.draw_grid()
subrmap2.plot(axes=ax7, cmap=cm.RdBu, title='')
subrmap2.draw_limb()
subrmap2.draw_grid() # ax5.contour(subrmapx.value, subrmapy.value, subrmap1.data, # levels=clevels1 * np.nanmax(subrmap1.data), cmap=cm.gray) # ax7.contour(subrmapx.value, subrmapy.value, subrmap2.data, # levels=clevels2 * np.nanmax(subrmap2.data), cmap=cm.gray) # subrmap1.draw_rectangle((fov[0][0], fov[1][0]) * u.arcsec, 400 * u.arcsec, 400 * u.arcsec) # subrmap2.draw_rectangle((fov[0][0], fov[1][0]) * u.arcsec, 400 * u.arcsec, 400 * u.arcsec)
ax5.set_xlim(xyrange[0])
ax5.set_ylim(xyrange[1])
ax5.text(0.02, 0.02, observatory + ' ' + rmap.date.strftime('%H:%M:%S.%f')[:-3], verticalalignment='bottom',
horizontalalignment='left', transform=ax5.transAxes, color='k', fontsize=10)
ax7.set_xlim(xyrange[0])
ax7.set_ylim(xyrange[1])
ax7.text(0.02, 0.02, observatory + ' ' + rmap.date.strftime('%H:%M:%S.%f')[:-3], verticalalignment='bottom',
horizontalalignment='left', transform=ax7.transAxes, color='k', fontsize=10)
fig.show()
def plotcomp(compdict, showplot=True, wantdict=False, symb=',',
include0amp=False, include0bl=False, blunit='', bl0flux=0.0):
"""
Given a dict including
{'clist': component list,
'objname': objname,
'epoch': epoch,
'shape': component shape dict, including direction.
'freqs (GHz)': pl.array of frequencies,
'antennalist': An array configuration file as used by simdata,
'savedfig': False or, if specified, the filename to save the plot to,
'standard': setjy fluxstandard type},
and symb: One of matplotlib's codes for plot symbols: .:,o^v<>s+xDd234hH|_
default: ',': The smallest points I could find,
make a plot of visibility amplitude vs. baseline length for clist at epoch.
If antennalist is not found as is, it will look for antennalist in
os.getenv('CASAPATH').split(' ')[0] + '/data/alma/simmos/'.
showplot: Whether or not to show the plot on screen.
If wantdict is True, it returns a dictionary with the amplitudes and
baselines on success. Otherwise, it returns True or False as its estimated
success value.
include0amp: Force the lower limit of the amplitude axis to 0.
include0bl: Force the lower limit of the baseline length axis to 0.
blunit: unit of the baseline length (='' used the unit in the data or klambda)
bl0flux: Zero baseline flux
"""
def failval():
"""
Returns an appropriate failure value.
Note that mydict.update(plotcomp(wantdict=True, ...)) would give a
confusing error message if plotcomp returned False.
"""
retval = False
if wantdict:
retval = {}
return retval
retval = failval() # Default
try:
clist = compdict['clist']
objname = compdict['objname']
epoch = compdict['epoch']
epstr = mepoch_to_str(epoch)
antennalist = compdict['antennalist']
# Read the configuration info.
if not antennalist:
print "compdict['antennalist'] must be set!"
print "Try something in", os.getenv("CASAPATH").split(' ')[0] + "/data/alma/simmos/"
return failval()
# Try repodir if raw antennalist doesn't work.
if not os.path.exists(antennalist):
repodir = os.getenv("CASAPATH").split(' ')[0] + "/data/alma/simmos/"
antennalist = repodir + antennalist
su = simutil("")
stnx, stny, stnz, diam, padnames, nant, telescopename = su.readantenna(antennalist)
#print "telescopename:", telescopename
# Check that the source is up.
myme = metool()
posobs = myme.observatory(telescopename)
#print "posobs:", posobs
myme.doframe(epoch)
myme.doframe(posobs)
azel = myme.measure(compdict['shape']['direction'], 'azel')
azeldegs = tuple([qa.convert(azel[m], 'deg')['value'] for m in ('m0', 'm1')])
casalog.post("(az, el): (%.2f, %.2f) degrees" % azeldegs)
# riseset blabs to the logger, so introduce it now.
casalog.post('Rise and set times of ' + objname + " from " + telescopename + ':')
approx = ''
if 'JPL' in compdict.get('standard', 'JPL'):
# The object is in the Solar System or not known to be extragalactic.
approx = "APPROXIMATE. The times do not account for the apparent motion of "\
+ objname + "."
casalog.post(" (" + approx + ")")
riset = myme.riseset(compdict['shape']['direction'])
msg = ''
if riset['rise'] == 'above':
msg = objname + " is circumpolar"
elif riset['rise'] == 'below':
msg = objname + ' is not visible from ' + telescopename
if msg:
if approx:
msg += ' around ' + mepoch_to_str(epoch)
casalog.post(msg)
else:
for t in riset:
riset[t]['str'] = mepoch_to_str(riset[t]['utc'])
casalog.post(objname + " rises at %s and sets at %s." % (riset['rise']['str'],
riset['set']['str']))
tmeridian=(riset['rise']['utc']['m0']['value']+riset['set']['utc']['m0']['value'])/2.
casalog.post(objname + ': meridian passage at ' + qa.time(str(tmeridian)+'d')[0])
if approx:
riset['NOTE'] = approx
if not azel['m1']['value'] > 0.0:
casalog.post(objname + " is not visible from " + telescopename + " at " + epstr,
'SEVERE')
if wantdict:
return riset
else:
return False
# Start a temp MS.
workingdir = os.path.abspath(os.path.dirname(clist.rstrip('/')))
tempms = tempfile.mkdtemp(prefix=objname, dir=workingdir)
mysm = smtool()
mysm.open(tempms)
su.setcfg(mysm, telescopename, stnx, stny, stnz, diam,
padnames, posobs)
#print "cfg set"
# Only 1 polarization is wanted for now.
stokes, feeds = su.polsettings(telescopename, 'RR')
casalog.post("stokes, feeds: %s, %s" % (stokes, feeds))
fband = su.bandname(compdict['freqs (GHz)'][0])
chaninc = 1.0
nchan = len(compdict['freqs (GHz)'])
if nchan > 1:
chaninc = (compdict['freqs (GHz)'][-1] - compdict['freqs (GHz)'][0]) / (nchan - 1)
mysm.setspwindow(spwname=fband,
freq=str(compdict['freqs (GHz)'][0]) + 'GHz',
deltafreq=str(chaninc) + 'GHz',
freqresolution='1Hz',
nchannels=nchan, refcode="LSRK",
stokes=stokes)
mysm.setfeed(mode=feeds, pol=[''])
mysm.setlimits(shadowlimit=0.01, elevationlimit='10deg')
mysm.setauto(0.0)
mysm.setfield(sourcename=objname,
sourcedirection=compdict['shape']['direction'],
calcode="OBJ", distance='0m')
mysm.settimes(integrationtime="1s", usehourangle=False,
referencetime=epoch)
# this only creates blank uv entries
mysm.observe(sourcename=objname, spwname=fband,
starttime="-0.5s", stoptime="0.5s", project=objname)
mysm.setdata(fieldid=[0])
mysm.setvp()
casalog.post("done setting up simulation parameters")
mysm.predict(complist=clist) # do actual calculation of visibilities:
mysm.close()
casalog.post("Simulation finished.")
mytb = tbtool()
mytb.open(tempms)
data = mytb.getcol('DATA')[0] # Again, only 1 polarization for now.
data = abs(data)
baselines = mytb.getcol('UVW')[:2,:] # Drop w.
datablunit = mytb.getcolkeywords('UVW')['QuantumUnits']
mytb.close()
#print "Got the data and baselines"
shutil.rmtree(tempms)
if datablunit[1] != datablunit[0]:
casalog.post('The baseline units are mismatched!: %s' % datablunit,
'SEVERE')
return failval()
datablunit = datablunit[0]
# uv dist unit in klambda or m
if datablunit == 'm' and blunit=='klambda':
kl = qa.constants('C')['value']/(compdict['freqs (GHz)'][0]*1e6)
blunit = 'k$\lambda$'
else:
blunit = datablunit
kl = 1.0
pl.ioff()
#baselines = pl.hypot(baselines[0]/kl, baselines[1]/kl)
baselines = pl.hypot(baselines[0], baselines[1])
#if not showplot:
# casalog.post('Sorry, not showing the plot is not yet implemented',
# 'WARN')
if showplot:
pl.ion()
pl.clf()
pl.ioff()
nfreqs = len(compdict['freqs (GHz)'])
for freqnum in xrange(nfreqs):
freq = compdict['freqs (GHz)'][freqnum]
casalog.post("Plotting " + str(freq) + " GHz.")
pl.plot(baselines/kl, data[freqnum], symb, label="%.3g GHz" % freq)
#pl.plot(baselines, data[freqnum], symb, label="%.3g GHz" % freq)
pl.xlabel("Baseline length (" + blunit + ")")
pl.ylabel("Visibility amplitude (Jy)")
if include0amp:
pl.ylim(ymin=0.0)
if include0bl:
pl.xlim(xmin=0.0)
pl.suptitle(objname + " (predicted by %s)" % compdict['standard'], fontsize=14)
#pl.suptitle(objname + " (predicted)", fontsize=14)
# Unlike compdict['antennalist'], antennalist might have had repodir
# prefixed to it.
pl.title('at ' + epstr + ' for ' + os.path.basename(compdict['antennalist']), fontsize=10)
titletxt='($%.0f^\circ$ az, $%.0f^\circ$ el)' % azeldegs
# for comparison of old and new models - omit azeldegs as all in az~0
if bl0flux > 0.0:
if len(compdict['freqs (GHz)']) == 1:
titletxt+='\n bl0 flux:%.3f Jy' % bl0flux
else:
titletxt+='\n bl0 flux:%.3f Jy @ %s GHz' % (bl0flux, compdict['freqs (GHz)'][0])
pl.legend(loc='best', title=titletxt)
#pl.legend(loc='best', title='($%.0f^\circ$ az, $%.0f^\circ$ el)' % azeldegs)
y_formatter=matplotlib.ticker.ScalarFormatter(useOffset=False)
pl.axes().yaxis.set_major_formatter(y_formatter)
if showplot:
pl.ion()
pl.draw()
if compdict.get('savedfig'):
pl.savefig(compdict.get('savedfig'))
casalog.post("Saved plot to " + str(compdict.get('savedfig')))
if wantdict:
retval = {'amps': data,
'antennalist': antennalist, # Absolute path, now.
'azel': azel,
'baselines': baselines,
'blunit': blunit,
'riseset': riset,
'savedfig': compdict.get('savedfig')}
else:
retval = True
except Exception, instance:
casalog.post(str(instance), 'SEVERE')
if os.path.isdir(tempms):
shutil.rmtree(tempms)
def draw_goes(goestime=None, ax=None):
if goestime:
btgoes = goestime[0]
etgoes = goestime[1]
else:
datstrg = datstr.replace('-', '/')
btgoes = datstrg + ' ' + qa.time(
qa.quantity(tim[0] - 1800, 's'), form='clean', prec=9)[0]
etgoes = datstrg + ' ' + qa.time(
qa.quantity(tim[tidx[-1] - 1] + 1800,
's'), form='clean', prec=9)[0]
#if verbose:
# print 'Acquire GOES soft X-ray data in from ' + btgoes + ' to ' + etgoes
#ax3 = plt.subplot(gs1[2])
goesscript = os.path.join(workdir, 'goes.py')
goesdatafile = os.path.join(workdir, 'goes.dat')
os.system('rm -rf {}'.format(goesscript))
fi = open(goesscript, 'wb')
fi.write('import os \n')
fi.write('from sunpy.time import TimeRange \n')
fi.write('from sunpy import lightcurve as lc \n')
fi.write('import pickle \n')
fi.write('goesplottim = TimeRange("{0}", "{1}") \n'.format(btgoes, etgoes))
fi.write('goes = lc.GOESLightCurve.create(goesplottim) \n')
fi.write('fi2 = open("{}", "wb") \n'.format(goesdatafile))
fi.write('pickle.dump(goes, fi2) \n')
fi.write('fi2.close()')
fi.close()
try:
os.system('python {}'.format(goesscript))
except NameError:
print "Bad input names"
except ValueError:
print "Bad input values"
except:
print "Unexpected error:", sys.exc_info()[0]
print "Error in generating GOES light curves. Proceed without GOES..."
if os.path.exists(goesdatafile):
fi1 = file(goesdatafile, 'rb')
goest = pickle.load(fi1)
fi1.close()
dates = mpl.dates.date2num(parse_time(goest.data.index))
goesdif = np.diff(goest.data['xrsb'])
gmax = np.nanmax(goesdif)
gmin = np.nanmin(goesdif)
ran = gmax - gmin
db = 2.8 / ran
goesdifp = goesdif * db + gmin + (-6)
ax.plot_date(dates,
np.log10(goest.data['xrsb']),
'-',
label='1.0--8.0 $\AA$',
color='red',
lw=2)
ax.plot_date(dates[0:-1],
goesdifp,
'-',
label='derivate',
color='blue',
lw=0.4)
ax.set_ylim([-7, -3])
ax.set_yticks([-7, -6, -5, -4, -3])
ax.set_yticklabels([
r'$10^{-7}$', r'$10^{-6}$', r'$10^{-5}$', r'$10^{-4}$',
r'$10^{-3}$'
])
ax.set_title('Goes Soft X-ray', fontsize=12)
ax.set_ylabel('Watts m$^{-2}$')
ax.set_xlabel(datetime.datetime.isoformat(goest.data.index[0])[0:10])
ax.axvspan(dates[899], dates[dates.size - 899], alpha=0.2)
ax.yaxis.grid(True, 'major')
ax.xaxis.grid(False, 'major')
ax.legend(prop={'size': 6})
formatter = mpl.dates.DateFormatter('%H:%M')
ax.xaxis.set_major_formatter(formatter)
ax.fmt_xdata = mpl.dates.DateFormatter('%H:%M')
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 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
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 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 plotcomp(compdict, showplot=True, wantdict=False, symb=',',
include0amp=False, include0bl=False, blunit='', bl0flux=0.0):
"""
Given a dict including
{'clist': component list,
'objname': objname,
'epoch': epoch,
'shape': component shape dict, including direction.
'freqs (GHz)': pl.array of frequencies,
'antennalist': An array configuration file as used by simdata,
'savedfig': False or, if specified, the filename to save the plot to,
'standard': setjy fluxstandard type},
and symb: One of matplotlib's codes for plot symbols: .:,o^v<>s+xDd234hH|_
default: ',': The smallest points I could find,
make a plot of visibility amplitude vs. baseline length for clist at epoch.
If antennalist is not found as is, it will look for antennalist in
os.getenv('CASAPATH').split(' ')[0] + '/data/alma/simmos/'.
showplot: Whether or not to show the plot on screen.
If wantdict is True, it returns a dictionary with the amplitudes and
baselines on success. Otherwise, it returns True or False as its estimated
success value.
include0amp: Force the lower limit of the amplitude axis to 0.
include0bl: Force the lower limit of the baseline length axis to 0.
blunit: unit of the baseline length (='' used the unit in the data or klambda)
bl0flux: Zero baseline flux
"""
def failval():
"""
Returns an appropriate failure value.
Note that mydict.update(plotcomp(wantdict=True, ...)) would give a
confusing error message if plotcomp returned False.
"""
retval = False
if wantdict:
retval = {}
return retval
retval = failval() # Default
try:
clist = compdict['clist']
objname = compdict['objname']
epoch = compdict['epoch']
epstr = mepoch_to_str(epoch)
antennalist = compdict['antennalist']
# Read the configuration info.
if not antennalist:
print "compdict['antennalist'] must be set!"
print "Try something in", os.getenv("CASAPATH").split(' ')[0] + "/data/alma/simmos/"
return failval()
# Try repodir if raw antennalist doesn't work.
if not os.path.exists(antennalist):
repodir = os.getenv("CASAPATH").split(' ')[0] + "/data/alma/simmos/"
antennalist = repodir + antennalist
su = simutil("")
stnx, stny, stnz, diam, padnames, telescopename, obsmeas = su.readantenna(antennalist)
#print "telescopename:", telescopename
# Check that the source is up.
myme = metool()
posobs = myme.observatory(telescopename)
#print "posobs:", posobs
myme.doframe(epoch)
myme.doframe(posobs)
azel = myme.measure(compdict['shape']['direction'], 'azel')
azeldegs = tuple([qa.convert(azel[m], 'deg')['value'] for m in ('m0', 'm1')])
casalog.post("(az, el): (%.2f, %.2f) degrees" % azeldegs)
# riseset blabs to the logger, so introduce it now.
casalog.post('Rise and set times of ' + objname + " from " + telescopename + ':')
approx = ''
if 'JPL' in compdict.get('standard', 'JPL'):
# The object is in the Solar System or not known to be extragalactic.
approx = "APPROXIMATE. The times do not account for the apparent motion of "\
+ objname + "."
casalog.post(" (" + approx + ")")
riset = myme.riseset(compdict['shape']['direction'])
msg = ''
if riset['rise'] == 'above':
msg = objname + " is circumpolar"
elif riset['rise'] == 'below':
msg = objname + ' is not visible from ' + telescopename
if msg:
if approx:
msg += ' around ' + mepoch_to_str(epoch)
casalog.post(msg)
else:
for t in riset:
riset[t]['str'] = mepoch_to_str(riset[t]['utc'])
casalog.post(objname + " rises at %s and sets at %s." % (riset['rise']['str'],
riset['set']['str']))
tmeridian=(riset['rise']['utc']['m0']['value']+riset['set']['utc']['m0']['value'])/2.
casalog.post(objname + ': meridian passage at ' + qa.time(str(tmeridian)+'d')[0])
if approx:
riset['NOTE'] = approx
if not azel['m1']['value'] > 0.0:
casalog.post(objname + " is not visible from " + telescopename + " at " + epstr,
'SEVERE')
if wantdict:
return riset
else:
return False
# Start a temp MS.
workingdir = os.path.abspath(os.path.dirname(clist.rstrip('/')))
tempms = tempfile.mkdtemp(prefix=objname, dir=workingdir)
mysm = smtool()
mysm.open(tempms)
su.setcfg(mysm, telescopename, stnx, stny, stnz, diam,
padnames, posobs)
#print "cfg set"
# Only 1 polarization is wanted for now.
stokes, feeds = su.polsettings(telescopename, 'RR')
casalog.post("stokes, feeds: %s, %s" % (stokes, feeds))
fband = su.bandname(compdict['freqs (GHz)'][0])
chaninc = 1.0
nchan = len(compdict['freqs (GHz)'])
if nchan > 1:
chaninc = (compdict['freqs (GHz)'][-1] - compdict['freqs (GHz)'][0]) / (nchan - 1)
mysm.setspwindow(spwname=fband,
freq=str(compdict['freqs (GHz)'][0]) + 'GHz',
deltafreq=str(chaninc) + 'GHz',
freqresolution='1Hz',
nchannels=nchan, refcode="LSRK",
stokes=stokes)
mysm.setfeed(mode=feeds, pol=[''])
mysm.setlimits(shadowlimit=0.01, elevationlimit='10deg')
mysm.setauto(0.0)
mysm.setfield(sourcename=objname,
sourcedirection=compdict['shape']['direction'],
calcode="OBJ", distance='0m')
mysm.settimes(integrationtime="1s", usehourangle=False,
referencetime=epoch)
# this only creates blank uv entries
mysm.observe(sourcename=objname, spwname=fband,
starttime="-0.5s", stoptime="0.5s", project=objname)
mysm.setdata(fieldid=[0])
mysm.setvp()
casalog.post("done setting up simulation parameters")
mysm.predict(complist=clist) # do actual calculation of visibilities:
mysm.close()
casalog.post("Simulation finished.")
mytb = tbtool()
mytb.open(tempms)
data = mytb.getcol('DATA')[0] # Again, only 1 polarization for now.
data = abs(data)
baselines = mytb.getcol('UVW')[:2,:] # Drop w.
datablunit = mytb.getcolkeywords('UVW')['QuantumUnits']
mytb.close()
#print "Got the data and baselines"
shutil.rmtree(tempms)
if datablunit[1] != datablunit[0]:
casalog.post('The baseline units are mismatched!: %s' % datablunit,
'SEVERE')
return failval()
datablunit = datablunit[0]
# uv dist unit in klambda or m
if datablunit == 'm' and blunit=='klambda':
kl = qa.constants('C')['value']/(compdict['freqs (GHz)'][0]*1e6)
blunit = 'k$\lambda$'
else:
blunit = datablunit
kl = 1.0
pl.ioff()
#baselines = pl.hypot(baselines[0]/kl, baselines[1]/kl)
baselines = pl.hypot(baselines[0], baselines[1])
#if not showplot:
# casalog.post('Sorry, not showing the plot is not yet implemented',
# 'WARN')
if showplot:
pl.ion()
pl.clf()
pl.ioff()
nfreqs = len(compdict['freqs (GHz)'])
for freqnum in xrange(nfreqs):
freq = compdict['freqs (GHz)'][freqnum]
casalog.post("Plotting " + str(freq) + " GHz.")
pl.plot(baselines/kl, data[freqnum], symb, label="%.3g GHz" % freq)
#pl.plot(baselines, data[freqnum], symb, label="%.3g GHz" % freq)
pl.xlabel("Baseline length (" + blunit + ")")
pl.ylabel("Visibility amplitude (Jy)")
if include0amp:
pl.ylim(ymin=0.0)
if include0bl:
pl.xlim(xmin=0.0)
pl.suptitle(objname + " (predicted by %s)" % compdict['standard'], fontsize=14)
#pl.suptitle(objname + " (predicted)", fontsize=14)
# Unlike compdict['antennalist'], antennalist might have had repodir
# prefixed to it.
pl.title('at ' + epstr + ' for ' + os.path.basename(compdict['antennalist']), fontsize=10)
titletxt='($%.0f^\circ$ az, $%.0f^\circ$ el)' % azeldegs
# for comparison of old and new models - omit azeldegs as all in az~0
if bl0flux > 0.0:
if len(compdict['freqs (GHz)']) == 1:
titletxt+='\n bl0 flux:%.3f Jy' % bl0flux
else:
titletxt+='\n bl0 flux:%.3f Jy @ %s GHz' % (bl0flux, compdict['freqs (GHz)'][0])
pl.legend(loc='best', title=titletxt)
#pl.legend(loc='best', title='($%.0f^\circ$ az, $%.0f^\circ$ el)' % azeldegs)
y_formatter=matplotlib.ticker.ScalarFormatter(useOffset=False)
pl.axes().yaxis.set_major_formatter(y_formatter)
if showplot:
pl.ion()
pl.draw()
if compdict.get('savedfig'):
pl.savefig(compdict.get('savedfig'))
casalog.post("Saved plot to " + str(compdict.get('savedfig')))
if wantdict:
retval = {'amps': data,
'antennalist': antennalist, # Absolute path, now.
'azel': azel,
'baselines': baselines,
'blunit': blunit,
'riseset': riset,
'savedfig': compdict.get('savedfig')}
else:
retval = True
except Exception, instance:
casalog.post(str(instance), 'SEVERE')
if os.path.isdir(tempms):
shutil.rmtree(tempms)
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 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 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 pltvs(vis='',
outputvis='',
plttimerange='',
pltspw1='',
pltspw2='',
pltspw3='',
timoffset=4,
windowlen=10,
windowtype='hamming',
pol='LL',
bl='19&22'):
ms.open(vis, nomodify=True)
""" This function can do two steps: (1) plot the uv amplitude vs. time
on three selected channel and compare the original and smoothed signals.
You can select appropriate window length and type, and the offset time
to match the peaks and valleys for the three channel curves. (2) Confirm
the use of specified window length, type and offset time and smooth the
data channel by channel. The background-subtracted measurement set is
then generated.
"""
timfreq = ms.getdata(['time', 'axis_info'], ifraxis=True)
tim = timfreq['time']
timerange = str(qa.time(qa.quantity(tim[0], 's'), prec=8)[0]) + '~' + str(
qa.time(qa.quantity(tim[-1], 's'), prec=8)[0])
# check plotting timerange
if plttimerange and (type(plttimerange) == str):
print 'plotting the specified timerange: ', plttimerange
else:
plttimerange = timerange
print 'plotting the entire timerange: ', plttimerange
if pltspw1 and (type(pltspw1) == str):
print 'Using the specified channel 1:', pltspw1
else:
pltspw1 = '0:400'
if pltspw2 and (type(pltspw2) == str):
print 'Using the specified channel 2:', pltspw2
else:
pltspw2 = '0:500'
if pltspw3 and (type(pltspw3) == str):
print 'Using the specified channel 3:', pltspw3
else:
pltspw3 = '0:600'
[spwid1, chan1] = pltspw1.split(':')
[spwid2, chan2] = pltspw2.split(':')
[spwid3, chan3] = pltspw3.split(':')
chanid = [chan1, chan2, chan3]
if not (spwid1 == spwid2 and spwid1 == spwid3):
print 'Please use the same spectral window'
exit()
if not (timoffset and (type(timoffset) == int)):
timoffset = int(4)
# initialize the loop-out status
status = 'n'
while True:
timoffset = int(
raw_input("Please specify the offset after smoothing:"))
windowlen = int(
raw_input("Please specify window width for smoothing:"))
windowtype = str(
raw_input(
"Please specify window type for smoothing: (e.g. 'flat', 'hanning', 'hamming', 'bartlett', 'blackman')"
))
pol = str(raw_input("Please specify polarization: (e.g. RR/LL)"))
bl = str(raw_input("Please specify baseline: (e.g. '19&22')"))
j = 331
for i in range(len(chanid)):
ms.selectinit(datadescid=int(spwid1))
if bl and (type(bl) == str):
ms.msselect({'baseline': bl})
if timerange and (type(timerange) == str):
ms.msselect({'time': timerange})
if chanid[i] and (type(chanid[i]) == str):
ms.selectchannel(1, int(chanid[i]), 1, 1)
specdata = ms.getdata(['data', 'time', 'axis_info'], ifraxis=True)
if pol == 'RR':
spec = specdata['data'][0, 0, 0, :]
if pol == 'LL':
spec = specdata['data'][1, 0, 0, :]
ms.selectinit(datadescid=int(spwid1))
if bl and (type(bl) == str):
ms.msselect({'baseline': bl})
if plttimerange and (type(plttimerange) == str):
ms.msselect({'time': plttimerange})
if chanid[i] and (type(chanid[i]) == str):
ms.selectchannel(1, int(chanid[i]), 1, 1)
specdata_plt = ms.getdata(['data', 'time', 'axis_info'],
ifraxis=True)
if pol == 'RR':
spec_plt = specdata_plt['data'][0, 0, 0, :]
if pol == 'LL':
spec_plt = specdata_plt['data'][1, 0, 0, :]
spec_plt_smooth = task_smooth.smooth(spec_plt, timoffset,
windowlen, windowtype)
spec_smooth = task_smooth.smooth(spec, timoffset, windowlen,
windowtype)
spec_plt_amp = np.absolute(spec_plt)
spec_plt_smooth_amp = np.absolute(spec_plt_smooth)
#spec_plt_amp=sqrt(spec_plt.real**2+spec_plt.imag**2)
#spec_plt_smooth_amp=sqrt(spec_plt_smooth.real**2+spec_plt_smooth.imag**2)
#print len(spec)
#print len(spec_smooth)
#print type(spec)
#print spec[0]
sp1 = fft(spec)
sp2 = fft(spec_smooth)
sp3 = sp1 - sp2
freq1 = fftfreq(len(sp1), d=0.001)
freq2 = fftfreq(len(sp2), d=0.001)
freq3 = fftfreq(len(sp3), d=0.001)
freq1_index = np.argsort(freq1)
freq2_index = np.argsort(freq2)
freq3_index = np.argsort(freq3)
#print min(freq1),max(freq1)
subplot(j)
plot(spec_plt_amp)
plot(spec_plt_smooth_amp)
title("Signal vs Time")
j = j + 1
subplot(j)
plot(freq1[freq1_index], log10(sp1[freq1_index]))
plot(freq2[freq2_index], log10(sp2[freq2_index]))
ylim([0, 6])
title("FFT signal vs Frequency")
j = j + 1
subplot(j)
#plot(subspec)
plot(freq3[freq3_index], log10(sp3[freq3_index]))
ylim([0, 6])
title("FFT smoothed signal vs Frequency")
j = j + 1
#print "number of original data points: ",len(spec)
#print "number of smoothed data points: ",len(spec_smooth)
status = str(
raw_input("Confirm to use current parameters? (y/n/abort) "))
if status == 'y':
flag1 = str(
raw_input("Smooth all the channels and time range? (y/n) "))
if flag1 == 'y':
smtimerange = ''
smspw = ''
splitsel = False
else:
print 'confirm using window width: ', windowlen
print 'confirm using window type: ', windowtype
smtimerange = str(
raw_input(
"Please specify the time range for smoothing (HH:MM:SS) :"
))
smspw = str(
raw_input(
"Please specify spectral window and channel (e.g. 0:0~1032) :"
))
splitsel = True
break
elif status == 'abort':
print 'Abort background subtraction.'
sys.exit()
if not outputvis:
outputvis = str(timoffset) + '_' + str(windowlen) + '_' + str(
windowtype) + '.ms'
print "Generating output: ", outputvis
ms.close()
result1 = subvs(vis, outputvis, smtimerange, smspw, timoffset, windowlen,
windowtype, '', '', '')
