def randomCoords(imagenames, ncoords=10):
import random
from taskinit import ia, qa
xmin, xmax = [], []
ymin, ymax = [], []
for image in imagenames:
ia.open(image)
print image, ia.boundingbox()
trc = ia.boundingbox()['trcf'].split(', ')
blc = ia.boundingbox()['blcf'].split(', ')
xmin.append(qa.convert(qa.quantity(trc[0]), 'rad')['value'])
xmax.append(qa.convert(qa.quantity(blc[0]), 'rad')['value'])
ymin.append(qa.convert(qa.quantity(blc[1]), 'rad')['value'])
ymax.append(qa.convert(qa.quantity(trc[1]), 'rad')['value'])
ia.done()
randomcoords = CoordList(imagenames)
for i in range(ncoords):
imageid = random.randint(0, len(imagenames) - 1)
x = random.uniform(xmin[imageid], xmax[imageid])
y = random.uniform(ymin[imageid], ymax[imageid])
c = Coord(x, y, 1.0)
randomcoords.append(c)
return randomcoords
def __axis(self, idx, unit):
refpix = self.coordsys.referencepixel()['numeric'][idx]
refval = self.coordsys.referencevalue()['numeric'][idx]
increment = self.coordsys.increment()['numeric'][idx]
_unit = self.units[idx]
if _unit != unit:
refval = qa.convert(qa.quantity(refval,_unit),unit)['value']
increment = qa.convert(qa.quantity(increment,_unit),unit)['value']
#return numpy.array([refval+increment*(i-refpix) for i in xrange(self.nchan)])
return (refpix, refval, increment)
def to_velocity(self, frequency, freq_unit='GHz', restfreq=None):
rest_frequency = self.coordsys.restfrequency()
# user-defined rest frequency takes priority
if restfreq is not None:
vrf = qa.convert(qa.quantity(restfreq), freq_unit)['value']
elif rest_frequency['unit'] != freq_unit:
vrf = qa.convert(rest_frequency, freq_unit)['value']
else:
vrf = rest_frequency['value']
return (1.0 - (frequency / vrf)) * LightSpeed
def to_velocity(self, frequency, freq_unit='GHz', restfreq=None):
rest_frequency = self.coordsys.restfrequency()
# user-defined rest frequency takes priority
if restfreq is not None:
vrf = qa.convert(qa.quantity(restfreq), freq_unit)['value']
elif rest_frequency['unit'] != freq_unit:
vrf = qa.convert(rest_frequency, freq_unit)['value']
else:
vrf = rest_frequency['value']
return (1.0 - (frequency / vrf)) * LightSpeed
def __axis(self, idx, unit):
refpix = self.coordsys.referencepixel()['numeric'][idx]
refval = self.coordsys.referencevalue()['numeric'][idx]
increment = self.coordsys.increment()['numeric'][idx]
_unit = self.units[idx]
if _unit != unit:
refval = qa.convert(qa.quantity(refval,_unit),unit)['value']
increment = qa.convert(qa.quantity(increment,_unit),unit)['value']
#return numpy.array([refval+increment*(i-refpix) for i in xrange(self.nchan)])
return (refpix, refval, increment)
def _calculate_sigma_weights(coords, maxmaskradius=None):
import numpy as np
from taskinit import ia
global stampsize
if coords.physical and coords.imagenames[0]:
ia.open(coords.imagenames[0])
# beam = qa.convert(ia.restoringbeam()['major'], 'rad')['value']
if ia.restoringbeam() == {}:
masksize = 10
else:
masksize = 2*np.abs(qa.convert(ia.restoringbeam()['major'],'rad')['value']/ ia.coordsys().increment()['numeric'][0])
ia.done()
X = np.arange(0, stampsize)-stampsize/2
Y = np.arange(0, stampsize)-stampsize/2
X,Y = np.meshgrid(X,Y)
for i,coord in enumerate(coords):
tmpdata = data[i,:,:,:,:]
for j in range(tmpdata.shape[2]):
for k in range(tmpdata.shape[3]):
tmpdata[:,:,j,k] = (tmpdata[:,:,j,k]*np.double( np.sqrt(X**2+Y**2)>masksize))
sigma = np.std(tmpdata)
if sigma == 0:
coord.weight = 0.
else:
coord.weight = 1/sigma
if maxmaskradius and maxmaskradius < masksize:
masksize = maxmaskradius
return coords
def to_velocity(self, frequency, freq_unit='GHz'):
rest_frequency = self.coordsys.restfrequency()
if rest_frequency['unit'] != freq_unit:
vrf = qa.convert(rest_frequency, freq_unit)['value']
else:
vrf = rest_frequency['value']
return (1.0 - (frequency / vrf)) * LightSpeed
def noise(coords,
vis,
weighting='sigma2',
imagenames=[],
beam=None,
nrand=50,
stampsize=32,
maskradius=None):
""" Calculate noise using a Monte Carlo method, can be time consuming. """
import stacker
import stacker.image
from math import pi
if beam is None:
try:
from taskinit import ia, qa
ia.open(imagenames[0])
beam = qa.convert(ia.restoringbeam()['major'], 'rad')['value']
ia.done()
except ImportError:
beam = 1 / 3600. / 180. * pi
dist = []
for i in range(nrand):
random_coords = stacker.randomizeCoords(coords, beam=beam)
if weighting == 'sigma2':
random_coords = stacker.image.calculate_sigma2_weights(
random_coords, imagenames, stampsize, maskradius)
dist.append(stack(random_coords, vis))
return np.std(np.real(np.array(dist)))
def mean_radius_with_known_theta(retdict):
"""
Return the average apparent mean radius of an ellipsoid with semiaxes
a >= b >= c (= retdict['radii']['value']).
"average" means average over a rotation period, and "apparent mean radius"
means the radius of a circle with the same area as the apparent disk.
"""
a = retdict['radii']['value'][0]
b2 = retdict['radii']['value'][1]**2
c2 = retdict['radii']['value'][2]**2
onemboa2 = 1.0 - b2 / a**2
units = {}
values = {}
for c in ['RA', 'DEC', 'NP_RA', 'NP_DEC']:
units[c] = retdict['data'][c]['data']['unit']
values[c] = retdict['data'][c]['data']['value']
av = 0.0
nrows = len(retdict['data']['RA']['data']['value'])
for i in xrange(nrows):
radec = me.direction('app', {'unit': units['RA'], 'value': values['RA'][i]},
{'unit': units['DEC'], 'value': values['DEC'][i]})
np = me.direction('j2000', {'unit': units['NP_RA'], 'value': values['NP_RA'][i]},
{'unit': units['NP_DEC'], 'value': values['NP_DEC'][i]})
szeta2 = scipy.sin(qa.convert(me.separation(radec, np), 'rad')['value'])**2
csinz2 = c2 * szeta2
bcosz2 = b2 * (1.0 - szeta2)
bcz2pcsz2 = bcosz2 + csinz2
m = csinz2 * onemboa2 / bcz2pcsz2
av += (scipy.sqrt(bcz2pcsz2) * scipy.special.ellipe(m) - av) / (i + 1.0)
return scipy.sqrt(2.0 * a * av / scipy.pi)
def to_frequency(self, velocity, freq_unit='km/s'):
rest_frequency = self.coordsys.restfrequency()
if rest_frequency['unit'] != freq_unit:
vrf = qa.convert(rest_frequency, freq_unit)['value']
else:
vrf = rest_frequency['value']
return (1.0 - velocity / LightSpeed) * vrf
def noise(coords, vis, weighting='sigma2', imagenames=[], beam=None, nrand=50,
stampsize=32, maskradius=None):
""" Calculate noise using a Monte Carlo method, can be time consuming. """
import stacker
import stacker.image
from math import pi
if beam is None:
try:
from taskinit import ia, qa
ia.open(imagenames[0])
beam = qa.convert(ia.restoringbeam()['major'], 'rad')['value']
ia.done()
except ImportError:
beam = 1/3600./180.*pi
dist = []
for i in range(nrand):
random_coords = stacker.randomizeCoords(coords, beam=beam)
if weighting == 'sigma2':
random_coords = stacker.image.calculate_sigma2_weights(
random_coords, imagenames, stampsize, maskradius)
dist.append(stack(random_coords, vis))
return np.std(np.real(np.array(dist)))
def mean_radius_with_known_theta(retdict):
"""
Return the average apparent mean radius of an ellipsoid with semiaxes
a >= b >= c (= retdict['radii']['value']).
"average" means average over a rotation period, and "apparent mean radius"
means the radius of a circle with the same area as the apparent disk.
"""
a = retdict["radii"]["value"][0]
b2 = retdict["radii"]["value"][1] ** 2
c2 = retdict["radii"]["value"][2] ** 2
onemboa2 = 1.0 - b2 / a ** 2
units = {}
values = {}
for c in ["RA", "DEC", "NP_RA", "NP_DEC"]:
units[c] = retdict["data"][c]["data"]["unit"]
values[c] = retdict["data"][c]["data"]["value"]
av = 0.0
nrows = len(retdict["data"]["RA"]["data"]["value"])
for i in xrange(nrows):
radec = me.direction(
"app", {"unit": units["RA"], "value": values["RA"][i]}, {"unit": units["DEC"], "value": values["DEC"][i]}
)
np = me.direction(
"j2000",
{"unit": units["NP_RA"], "value": values["NP_RA"][i]},
{"unit": units["NP_DEC"], "value": values["NP_DEC"][i]},
)
szeta2 = scipy.sin(qa.convert(me.separation(radec, np), "rad")["value"]) ** 2
csinz2 = c2 * szeta2
bcosz2 = b2 * (1.0 - szeta2)
bcz2pcsz2 = bcosz2 + csinz2
m = csinz2 * onemboa2 / bcz2pcsz2
av += (scipy.sqrt(bcz2pcsz2) * scipy.special.ellipe(m) - av) / (i + 1.0)
return scipy.sqrt(2.0 * a * av / scipy.pi)
def to_frequency(self, velocity, freq_unit='km/s'):
rest_frequency = self.coordsys.restfrequency()
if rest_frequency['unit'] != freq_unit:
vrf = qa.convert(rest_frequency, freq_unit)['value']
else:
vrf = rest_frequency['value']
return (1.0 - velocity / LightSpeed) * vrf
def noise(coords, nrandom = 50, imagenames=[], stampsize=32,
method = 'mean', weighting = 'simga2', maskradius=None,
psfmode = 'point'):
import stacker
import numpy as np
from taskinit import ia, qa
ia.open(imagenames[0])
beam = qa.convert(ia.restoringbeam()['major'], 'rad')['value']
ia.done()
# if coords.coord_type == 'physical':
# coords = stacker.getPixelCoords(coords, imagenames)
_allocate_buffers(imagenames, stampsize, len(coords)*len(imagenames))
dist = []
for i in range(nrandom):
random_coords = stacker.randomizeCoords(coords, beam=beam)
random_coords = stacker.getPixelCoords(random_coords, imagenames)
_load_stack(random_coords, psfmode)
if method == 'mean' and weighting == 'sigma2':
random_coords = _calculate_sigma2_weights(random_coords, maskradius)
elif method == 'mean' and weighting == 'sigma':
random_coords = _calculate_sigma_weights(random_coords, maskradius)
stacked_im = _stack_stack(method, random_coords)
dist.append(stacked_im[int(stampsize/2+0.5), int(stampsize/2+0.5),0,0])
return np.std(dist)
def parse_figsize(figsize):
"""
return figsize in inches
"""
casalog.post('parse_figsize input: {input}'.format(input=figsize), priority='DEBUG')
parsed = None
if figsize is not None and isinstance(figsize, str) and len(figsize) > 0:
size_list = figsize.split(',')
size_inch_list = [x / 25.4 for s in size_list for x in qa.getvalue(qa.convert(qa.quantity(s),outunit='mm'))]
if len(size_inch_list) == 1:
s = size_inch_list[0]
parsed = (s, s)
else:
parsed = tuple(size_inch_list[:2])
casalog.post('parse_figsize output: {output}'.format(output=parsed), priority='DEBUG')
return parsed
def parse_figsize(figsize):
"""
return figsize in inches
"""
casalog.post('parse_figsize input: {input}'.format(input=figsize), priority='DEBUG')
parsed = None
if figsize is not None and isinstance(figsize, str) and len(figsize) > 0:
size_list = figsize.split(',')
size_inch_list = [x / 25.4 for s in size_list for x in qa.getvalue(qa.convert(qa.quantity(s),outunit='mm'))]
if len(size_inch_list) == 1:
s = size_inch_list[0]
parsed = (s, s)
else:
parsed = tuple(size_inch_list[:2])
casalog.post('parse_figsize output: {output}'.format(output=parsed), priority='DEBUG')
return parsed
def __call__(self, dx, dy, nu=None):
"""
Returns primary beam correction for translation (dx, dy) from center.
Keyword arguments:
dx -- Projected separation in x direction in radians
dy -- Projected separation in y direction in radians
nu -- Frequency, either self.nu0 or nu must be set.
"""
from scipy.constants import c
from taskinit import qa
if nu is None:
if self.nu0 is None:
return 0.
nu = self.nu0
dishdia = qa.convert(self.dishdia, 'm')['value']
vp_fwhm = 1.22 * c / nu / dishdia
return np.exp(-4. * np.log(2) * (dx**2 + dy**2) / vp_fwhm**2)
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 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)
if nspw > 1:
casalog.post('Separate MS into %s spws'%nspw)
config['nspw'] = nspw
config['interpolation'] = interpolation
if restfreq != '':
config['restfreq'] = restfreq
if outframe != '':
config['outframe'] = outframe
if phasecenter != '':
config['phasecenter'] = phasecenter
config['veltype'] = veltype
config['preaverage'] = preaverage
# Only parse timeaverage parameters when timebin > 0s
if timeaverage:
tb = qa.convert(qa.quantity(timebin), 's')['value']
if not tb > 0:
raise Exception, "Parameter timebin must be > '0s' to do time averaging"
if timeaverage:
casalog.post('Parse time averaging parameters')
config['timeaverage'] = True
config['timebin'] = timebin
config['timespan'] = timespan
config['maxuvwdistance'] = maxuvwdistance
if docallib:
casalog.post('Parse docallib parameters')
mycallib = callibrary()
mycallib.read(callib)
config['calibration'] = True
retdict[hk] = {
'unit': headers[hk]['unit'],
'value': float(retdict[hk])
}
except Exception, e:
print "Error converting header", hk, "to a Quantity."
print "retdict[hk] =", retdict[hk]
raise e
elif hk == 'GeoLong':
long_lat_alt = retdict[hk].split(',')
retdict['GeoLong'] = float(long_lat_alt[0])
retdict['GeoLat'] = float(long_lat_alt[1])
retdict['GeoDist'] = float(long_lat_alt[2])
elif hk == 'dMJD':
retdict[hk] = qa.convert(
qa.totime(retdict[hk].replace('minutes', 'min')),
'd')['value']
elif hk == 'orb_per':
unit = 'h'
retrograde = False
if 'd' in retdict[hk].lower():
unit = 'd' # Actually this is most common.
if 'r' in retdict[hk].lower():
retrograde = True
value = get_num_from_str(retdict[hk], 'orbital period')
if value != False:
if retrograde and value > 0.0:
value = -value
retdict[hk] = {'unit': unit, 'value': value}
else:
del retdict[hk]
def flagdata(
vis,
mode,
autocorr, # mode manual parameter
inpfile, # mode list parameters
reason,
tbuff,
spw, # data selection parameters
field,
antenna,
uvrange,
timerange,
correlation,
scan,
intent,
array,
observation,
feed,
clipminmax, # mode clip parameters
datacolumn,
clipoutside,
channelavg,
chanbin,
timeavg,
timebin,
clipzeros,
quackinterval, # mode quack parameters
quackmode,
quackincrement,
tolerance, # mode shadow parameter
addantenna,
lowerlimit, # mode elevation parameters
upperlimit,
ntime, # mode tfcrop
combinescans,
timecutoff,
freqcutoff,
timefit,
freqfit,
maxnpieces,
flagdimension,
usewindowstats,
halfwin,
extendflags,
winsize, # rflag parameters
timedev,
freqdev,
timedevscale,
freqdevscale,
spectralmax,
spectralmin,
antint_ref_antenna, # mode antint
minchanfrac,
verbose,
extendpols, # mode extend
growtime,
growfreq,
growaround,
flagneartime,
flagnearfreq,
minrel, # mode summary
maxrel,
minabs,
maxabs,
spwchan,
spwcorr,
basecnt,
fieldcnt,
name,
action, # run or not the tool
display,
flagbackup,
savepars, # save the current parameters to FLAG_CMD or to a file
cmdreason, # reason to save to flag cmd
outfile, # output file to save flag commands
overwrite, # overwrite the outfile file
writeflags # HIDDEN parameter
):
#
# Task flagdata
# Flags data from an MS or calibration table based on data selection in various ways
casalog.origin('flagdata')
if (action == 'none' or action == '' or action == 'calculate'):
flagbackup = False
# SMC: moved the flagbackup to before initializing the cluster.
# Note that with this change, a flag backup will be created even if
# an error happens that prevents the flagger tool from running.
if (mode != 'summary' and flagbackup):
casalog.post('Backup original flags before applying new flags')
fh.backupFlags(aflocal=None, msfile=vis, prename='flagdata')
# Set flagbackup to False because only the controller
# should create a backup
flagbackup = False
# Initialize the helper class
orig_locals = copy.deepcopy(locals())
FHelper = FlagHelper()
# Check if vis is a MS, MMS or cal table:
# typevis = 1 --> cal table
# typevis = 0 --> MS
# typevis = 2 --> MMS
iscal = False
typevis = fh.isCalTable(vis)
if typevis == 1:
iscal = True
# ***************** Input is MMS -- Parallel Processing ***********************
if FHelper.isMPIEnabled(
) and typevis == 2 and action != '' and action != 'none':
# Create a temporary input file with .tmp extension.
# Use this file for all the processing from now on.
if (isinstance(inpfile,str) and inpfile != '') or \
(isinstance(inpfile, list) and os.path.isfile(inpfile[0])):
inpfile = FHelper.setupInputFile(inpfile)
if inpfile != None:
orig_locals['inpfile'] = inpfile
if outfile != '':
outfile = os.path.abspath(outfile)
orig_locals['outfile'] = outfile
if isinstance(addantenna, str) and addantenna != '':
addantenna = os.path.abspath(addantenna)
orig_locals['addantenna'] = addantenna
if isinstance(timedev, str) and timedev != '':
timedev = os.path.abspath(timedev)
orig_locals['timedev'] = timedev
if isinstance(freqdev, str) and freqdev != '':
freqdev = os.path.abspath(freqdev)
orig_locals['freqdev'] = freqdev
FHelper.__init__(orig_locals)
# For tests only
# FHelper.bypassParallelProcessing(1)
FHelper.setupCluster('flagdata')
# (CAS-4119): Override summary minabs,maxabs,minrel,maxrel
# so that it is done after consolidating the summaries
# By-pass options to filter summary
filterSummary = False
if ((mode == 'summary') and ((minrel != 0.0) or (maxrel != 1.0) or
(minabs != 0) or (maxabs != -1))):
filterSummary = True
myms = mstool()
myms.open(vis)
subMS_list = myms.getreferencedtables()
myms.close()
if (minrel != 0.0):
minreal_dict = create_arg_dict(subMS_list, 0.0)
FHelper.override_arg('minrel', minreal_dict)
if (maxrel != 1.0):
maxrel_dict = create_arg_dict(subMS_list, 1.0)
FHelper.override_arg('maxrel', maxrel_dict)
if (minabs != 0):
minabs_dict = create_arg_dict(subMS_list, 0)
FHelper.override_arg('minabs', minabs_dict)
if (maxabs != -1):
maxabs_dict = create_arg_dict(subMS_list, -1)
FHelper.override_arg('maxabs', maxabs_dict)
# By-pass options to filter summary
if savepars:
myms = mstool()
myms.open(vis)
subMS_list = myms.getreferencedtables()
myms.close()
savepars_dict = create_arg_dict(subMS_list, False)
FHelper.override_arg('savepars', savepars_dict)
# Execute the parallel engines
retVar = FHelper.go()
# Save overall RFlag values into timedev/freqdev files once the subMS results have
# been consolidated, if needed for RFlag (introduced in CAS-11850)
opts_dict = {
'writeflags': writeflags,
'timedev': timedev,
'freqdev': freqdev
}
fh.save_rflag_consolidated_files(mode, action, retVar, opts_dict,
inpfile)
# In async mode return the job ids
if ParallelTaskHelper.getAsyncMode():
return retVar
else:
# Filter summary at MMS level
if (mode == 'summary'):
if filterSummary:
retVar = filter_summary(retVar, minrel, maxrel, minabs,
maxabs)
return retVar
# Save parameters at MMS level
elif savepars:
action = 'none'
else:
return retVar
summary_stats = {}
# ***************** Input is a normal MS/cal table ****************
# Create local tools
# aflocal = casac.agentflagger()
aflocal = aftool()
mslocal = mstool()
try:
# Verify the ntime value
newtime = 0.0
if type(ntime) == float or type(ntime) == int:
if ntime <= 0:
raise Exception, 'Parameter ntime cannot be < = 0'
else:
# units are seconds
newtime = float(ntime)
elif type(ntime) == str:
if ntime == 'scan':
# iteration time step is a scan
newtime = 0.0
else:
# read the units from the string
qtime = qa.quantity(ntime)
if qtime['unit'] == 'min':
# convert to seconds
qtime = qa.convert(qtime, 's')
elif qtime['unit'] == '':
qtime['unit'] = 's'
# check units
if qtime['unit'] == 's':
newtime = qtime['value']
else:
casalog.post(
'Cannot convert units of ntime. Will use default 0.0s',
'WARN')
casalog.post(
"New ntime is of type %s and value %s" % (type(newtime), newtime),
'DEBUG')
# Open the MS and attach it to the tool
if ((type(vis) == str) & (os.path.exists(vis))):
aflocal.open(vis, newtime)
else:
raise Exception, 'Visibility data set not found - please verify the name'
# Get the parameters for the mode
agent_pars = {}
# By default, write flags to the MS
writeflags = True
# Only the apply action writes to the MS
# action=apply --> write to the MS
# action=calculate --> do not write to the MS
# action='' --> do not run the tool and do not write to the MS
if action != 'apply':
writeflags = False
# Default mode
if mode == '' or mode == 'manualflag':
mode = 'manual'
# Read in the list of commands
# Make a dictionary of the input commands. Select by reason if requested
flagcmd = {}
if mode == 'list':
casalog.post('List mode is active')
doPadding = True
try:
# If tbuff is requested, read and Parse
if tbuff == 0.0 or tbuff == [] or tbuff == None:
doPadding = False
if doPadding:
casalog.post('Will apply time buffer padding')
# inpfile is a file
if isinstance(inpfile, str):
inpfile = [inpfile]
# read in the list and do a simple parsing to apply tbuff
flaglist = fh.readAndParse(inpfile, tbuff)
else:
flaglist = fh.get_flag_cmd_list(inpfile)
# Parse and create a dictionary
flagcmd = fh.parseDictionary(flaglist, reason)
# Validate the dictionary.
# IMPORTANT: if any parameter changes its type, the following
# function needs to be updated. The same if any new parameter is
# added or removed from the task
fh.evaluateFlagParameters(flagcmd, orig_locals)
# List of flag commands in dictionary
vrows = flagcmd.keys()
casalog.post('%s' % flagcmd, 'DEBUG1')
except Exception, instance:
casalog.post('%s' % instance, 'ERROR')
raise Exception, 'Error reading the input list. Make sure the syntax used in the list '\
'follows the rules given in the inline help of the task.'
casalog.post('Selected ' + str(vrows.__len__()) +
' commands from combined input list(s) ')
elif mode == 'manual':
agent_pars['autocorr'] = autocorr
casalog.post('Manual mode is active')
def predictcomp(objname=None, standard=None, epoch=None,
minfreq=None, maxfreq=None, nfreqs=None, prefix=None,
antennalist=None, showplot=None, savefig=None, symb=None,
include0amp=None, include0bl=None, blunit=None, bl0flux=None):
"""
Writes a component list named clist to disk and returns a dict of
{'clist': clist,
'objname': objname,
'angdiam': angular diameter in radians (if used in clist),
'standard': standard,
'epoch': epoch,
'freqs': pl.array of frequencies, in GHz,
'uvrange': pl.array of baseline lengths, in m,
'amps': pl.array of predicted visibility amplitudes, in Jy,
'savedfig': False or, if made, the filename of a plot.}
or False on error.
objname: An object supported by standard.
standard: A standard for calculating flux densities, as in setjy.
Default: 'Butler-JPL-Horizons 2010'
epoch: The epoch to use for the calculations. Irrelevant for
extrasolar standards.
minfreq: The minimum frequency to use.
Example: '342.0GHz'
maxfreq: The maximum frequency to use.
Default: minfreq
Example: '346.0GHz'
Example: '', anything <= 0, or None: use minfreq.
nfreqs: The number of frequencies to use.
Default: 1 if minfreq == maxfreq,
2 otherwise.
prefix: The component list will be saved to
prefix + 'spw0_<objname>_<minfreq><epoch>.cl'
Default: ''
antennalist: An array configuration file as used by simdata.
If given, a plot of S vs. |u| will be made.
Default: '' (None, just make clist.)
showplot: Whether or not to show the plot on screen.
Subparameter of antennalist.
Default: Necessarily False if antennalist is not specified.
True otherwise.
savefig: Filename for saving a plot of S vs. |u|.
Subparameter of antennalist.
Default: False (necessarily if antennalist is not specified)
Examples: True (save to prefix + '.png')
'myplot.png' (save to myplot.png)
symb: One of matplotlib's codes for plot symbols: .:,o^v<>s+xDd234hH|_
default: '.'
include0amp: Force the lower limit of the amplitude axis to 0.
Default: False
include0bl: Force the lower limit of the baseline length axis to 0.
blunit: Unit of the baseline length
bl0flux: show zero baseline flux
"""
retval = False
try:
casalog.origin('predictcomp')
# some parameter minimally required
if objname=='':
raise Exception, "Error, objname is undefined"
if minfreq=='':
raise Exception, "Error, minfreq is undefined"
minfreqq = qa.quantity(minfreq)
minfreqHz = qa.convert(minfreqq, 'Hz')['value']
try:
maxfreqq = qa.quantity(maxfreq)
except Exception, instance:
maxfreqq = minfreqq
frequnit = maxfreqq['unit']
maxfreqHz = qa.convert(maxfreqq, 'Hz')['value']
if maxfreqHz <= 0.0:
maxfreqq = minfreqq
maxfreqHz = minfreqHz
if minfreqHz != maxfreqHz:
if nfreqs < 2:
nfreqs = 2
else:
nfreqs = 1
freqs = pl.linspace(minfreqHz, maxfreqHz, nfreqs)
myme = metool()
mepoch = myme.epoch('UTC', epoch)
#if not prefix:
## meanfreq = {'value': 0.5 * (minfreqHz + maxfreqHz),
## 'unit': frequnit}
## prefix = "%s%s_%.7g" % (objname, epoch.replace('/', '-'),
## minfreqq['value'])
## if minfreqHz != maxfreqHz:
## prefix += "to" + maxfreq
## else:
## prefix += minfreqq['unit']
## prefix += "_"
# prefix = ''
#
if not prefix:
if not os.access("./",os.W_OK):
casalog.post("No write access in the current directory, trying to write cl to /tmp...","WARN")
prefix="/tmp/"
if not os.access(prefix, os.W_OK):
casalog.post("No write access to /tmp to write cl file", "SEVERE")
return False
else:
prefixdir=os.path.dirname(prefix)
if not os.path.exists(prefixdir):
prefixdirs = prefixdir.split('/')
if prefixdirs[0]=="":
rootdir = "/" + prefixdirs[1]
else:
rootdir = "./"
if os.access(rootdir,os.W_OK):
os.makedirs(prefixdir)
else:
casalog.post("No write access to "+rootdir+" to write cl file", "SEVERE")
return False
# Get clist
myim = imtool()
if hasattr(myim, 'predictcomp'):
casalog.post('local im instance created', 'DEBUG1')
else:
casalog.post('Error creating a local im instance.', 'SEVERE')
return False
#print "FREQS=",freqs
if standard=='Butler-JPL-Horizons 2012':
clist = predictSolarObjectCompList(objname, mepoch, freqs.tolist(), prefix)
else:
clist = myim.predictcomp(objname, standard, mepoch, freqs.tolist(), prefix)
#print "created componentlist =",clist
if os.path.isdir(clist):
# The spw0 is useless here, but it is added by FluxStandard for the sake of setjy.
casalog.post('The component list was saved to ' + clist)
retval = {'clist': clist,
'objname': objname,
'standard': standard,
'epoch': mepoch,
'freqs (GHz)': 1.0e-9 * freqs,
'antennalist': antennalist}
mycl = cltool()
mycl.open(clist)
comp = mycl.getcomponent(0)
zeroblf=comp['flux']['value']
if standard=='Butler-JPL-Horizons 2012':
f0=comp['spectrum']['frequency']['m0']['value']
else:
f0=retval['freqs (GHz)'][0]
casalog.post("Zero baseline flux %s @ %sGHz " % (zeroblf, f0),'INFO')
mycl.close(False) # False prevents the stupid warning.
for k in ('shape', 'spectrum'):
retval[k] = comp[k]
if antennalist:
retval['spectrum']['bl0flux']={}
retval['spectrum']['bl0flux']['value']=zeroblf[0]
retval['spectrum']['bl0flux']['unit']='Jy'
retval['savedfig'] = savefig
if not bl0flux:
zeroblf=[0.0]
retval.update(plotcomp(retval, showplot, wantdict=True, symb=symb,
include0amp=include0amp, include0bl=include0bl, blunit=blunit, bl0flux=zeroblf[0]))
else:
retval['savedfig'] = None
else:
casalog.post("There was an error in making the component list.",
'SEVERE')
def predictcomp(objname=None,
standard=None,
epoch=None,
minfreq=None,
maxfreq=None,
nfreqs=None,
prefix=None,
antennalist=None,
showplot=None,
savefig=None,
symb=None,
include0amp=None,
include0bl=None,
blunit=None,
bl0flux=None):
"""
Writes a component list named clist to disk and returns a dict of
{'clist': clist,
'objname': objname,
'angdiam': angular diameter in radians (if used in clist),
'standard': standard,
'epoch': epoch,
'freqs': pl.array of frequencies, in GHz,
'uvrange': pl.array of baseline lengths, in m,
'amps': pl.array of predicted visibility amplitudes, in Jy,
'savedfig': False or, if made, the filename of a plot.}
or False on error.
objname: An object supported by standard.
standard: A standard for calculating flux densities, as in setjy.
Default: 'Butler-JPL-Horizons 2010'
epoch: The epoch to use for the calculations. Irrelevant for
extrasolar standards.
minfreq: The minimum frequency to use.
Example: '342.0GHz'
maxfreq: The maximum frequency to use.
Default: minfreq
Example: '346.0GHz'
Example: '', anything <= 0, or None: use minfreq.
nfreqs: The number of frequencies to use.
Default: 1 if minfreq == maxfreq,
2 otherwise.
prefix: The component list will be saved to
prefix + '<objname>_spw0_<minfreq><epoch>.cl'
Default: ''
antennalist: An array configuration file as used by simdata.
If given, a plot of S vs. |u| will be made.
Default: '' (None, just make clist.)
showplot: Whether or not to show the plot on screen.
Subparameter of antennalist.
Default: Necessarily False if antennalist is not specified.
True otherwise.
savefig: Filename for saving a plot of S vs. |u|.
Subparameter of antennalist.
Default: False (necessarily if antennalist is not specified)
Examples: True (save to prefix + '.png')
'myplot.png' (save to myplot.png)
symb: One of matplotlib's codes for plot symbols: .:,o^v<>s+xDd234hH|_
default: '.'
include0amp: Force the lower limit of the amplitude axis to 0.
Default: False
include0bl: Force the lower limit of the baseline length axis to 0.
blunit: Unit of the baseline length
bl0flux: show zero baseline flux
"""
retval = False
try:
casalog.origin('predictcomp')
# some parameter minimally required
if objname == '':
raise Exception, "Error, objname is undefined"
if minfreq == '':
raise Exception, "Error, minfreq is undefined"
minfreqq = qa.quantity(minfreq)
minfreqHz = qa.convert(minfreqq, 'Hz')['value']
try:
maxfreqq = qa.quantity(maxfreq)
except Exception, instance:
maxfreqq = minfreqq
frequnit = maxfreqq['unit']
maxfreqHz = qa.convert(maxfreqq, 'Hz')['value']
if maxfreqHz <= 0.0:
maxfreqq = minfreqq
maxfreqHz = minfreqHz
if minfreqHz != maxfreqHz:
if nfreqs < 2:
nfreqs = 2
else:
nfreqs = 1
freqs = pl.linspace(minfreqHz, maxfreqHz, nfreqs)
myme = metool()
mepoch = myme.epoch('UTC', epoch)
#if not prefix:
## meanfreq = {'value': 0.5 * (minfreqHz + maxfreqHz),
## 'unit': frequnit}
## prefix = "%s%s_%.7g" % (objname, epoch.replace('/', '-'),
## minfreqq['value'])
## if minfreqHz != maxfreqHz:
## prefix += "to" + maxfreq
## else:
## prefix += minfreqq['unit']
## prefix += "_"
# prefix = ''
#
if not prefix:
if not os.access("./", os.W_OK):
casalog.post(
"No write access in the current directory, trying to write cl to /tmp...",
"WARN")
prefix = "/tmp/"
if not os.access(prefix, os.W_OK):
casalog.post("No write access to /tmp to write cl file",
"SEVERE")
return False
else:
prefixdir = os.path.dirname(prefix)
if prefixdir == '/' and len(prefix) > 1:
prefix = prefix + '/'
prefixdir = os.path.dirname(prefix)
if not os.path.exists(prefixdir):
prefixdirs = prefixdir.split('/')
if prefixdirs[0] == "" and len(prefixdirs) > 1:
rootdir = "/" + prefixdirs[1]
else:
rootdir = "./"
if os.access(rootdir, os.W_OK):
if prefixdir != '':
os.makedirs(prefixdir)
else:
casalog.post(
"No write access to " + rootdir + " to write cl file",
"SEVERE")
return False
# Get clist
myim = imtool()
if hasattr(myim, 'predictcomp'):
casalog.post('local im instance created', 'DEBUG1')
else:
casalog.post('Error creating a local im instance.', 'SEVERE')
return False
#print "FREQS=",freqs
# output CL file name is fixed : prefix+"spw0_"+minfreq+mepoch.cl
minfreqGHz = qa.convert(qa.quantity(minfreq), 'GHz')['value']
decimalfreq = minfreqGHz - int(minfreqGHz)
decimalepoch = mepoch['m0']['value'] - int(mepoch['m0']['value'])
if decimalfreq == 0.0:
minfreqGHzStr = str(int(minfreqGHz)) + 'GHz'
else:
minfreqGHzStr = str(minfreqGHz) + 'GHz'
if decimalepoch == 0.0:
epochStr = str(int(mepoch['m0']['value'])) + 'd'
else:
epochStr = str(mepoch['m0']['value']) + 'd'
outfilename = "spw0_" + objname + "_" + minfreqGHzStr + epochStr + '.cl'
outfilename = prefix + outfilename
if (os.path.exists(outfilename) and os.path.isdir(outfilename)):
shutil.rmtree(outfilename)
casalog.post("Removing the existing componentlist, " + outfilename)
if standard == 'Butler-JPL-Horizons 2012':
clist = predictSolarObjectCompList(objname, mepoch, freqs.tolist(),
prefix)
else:
clist = myim.predictcomp(objname, standard, mepoch, freqs.tolist(),
prefix)
#print "created componentlist =",clist
if os.path.isdir(clist):
# The spw0 is useless here, but it is added by FluxStandard for the sake of setjy.
casalog.post('The component list was saved to ' + clist)
retval = {
'clist': clist,
'objname': objname,
'standard': standard,
'epoch': mepoch,
'freqs (GHz)': 1.0e-9 * freqs,
'antennalist': antennalist
}
mycl = cltool()
mycl.open(clist)
comp = mycl.getcomponent(0)
zeroblf = comp['flux']['value']
if standard == 'Butler-JPL-Horizons 2012':
f0 = comp['spectrum']['frequency']['m0']['value']
else:
f0 = retval['freqs (GHz)'][0]
casalog.post("Zero baseline flux %s @ %sGHz " % (zeroblf, f0),
'INFO')
mycl.close(False) # False prevents the stupid warning.
for k in ('shape', 'spectrum'):
retval[k] = comp[k]
if antennalist:
retval['spectrum']['bl0flux'] = {}
retval['spectrum']['bl0flux']['value'] = zeroblf[0]
retval['spectrum']['bl0flux']['unit'] = 'Jy'
retval['savedfig'] = savefig
if not bl0flux:
zeroblf = [0.0]
retval.update(
plotcomp(retval,
showplot,
wantdict=True,
symb=symb,
include0amp=include0amp,
include0bl=include0bl,
blunit=blunit,
bl0flux=zeroblf[0]))
else:
retval['savedfig'] = None
else:
casalog.post("There was an error in making the component list.",
'SEVERE')
def 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 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 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 mk_diskmodel(outname='disk', bdwidth='325MHz', direction='J2000 10h00m00.0s 20d00m00.0s',
reffreq='2.8GHz', flux=660000.0, eqradius='16.166arcmin', polradius='16.166arcmin',
pangle='21.1deg', index=None, cell='2.0arcsec', overwrite=True):
''' Create a blank solar disk model image (or optionally a data cube)
outname String to use for part of the image and fits file names (default 'disk')
direction String specifying the position of the Sun in RA and Dec. Default
means use the standard string "J2000 10h00m00.0s 20d00m00.0s"
reffreq The reference frequency to use for the disk model (the frequency at which
the flux level applies). Default is '2.8GHz'.
flux The flux density, in Jy, for the entire disk. Default is 66 sfu.
eqradius The equatorial radius of the disk. Default is
16 arcmin + 10" (for typical extension of the radio limb)
polradius The polar radius of the disk. Default is
16 arcmin + 10" (for typical extension of the radio limb)
pangle The solar P-angle (geographic position of the N-pole of the Sun) in
degrees E of N. This only matters if eqradius != polradius
index The spectral index to use at other frequencies. Default None means
use a constant flux density for all frequencies.
cell The cell size (assumed square) to use for the image. The image size
is determined from a standard radius of 960" for the Sun, divided by
cell size, increased to nearest power of 512 pixels. The default is '2.0arcsec',
which results in an image size of 1024 x 1024.
Note that the frequency increment used is '325MHz', which is the width of EOVSA bands
(not the width of individual science channels)
'''
diskim = outname + reffreq + '.im'
if os.path.exists(diskim):
if overwrite:
os.system('rm -rf {}'.format(diskim))
else:
return diskim
ia = iatool()
cl = cltool()
cl.done()
ia.done()
try:
aspect = 1.01 # Enlarge the equatorial disk by 1%
eqradius = qa.quantity(eqradius)
diamajor = qa.quantity(2 * aspect * eqradius['value'], eqradius['unit'])
polradius = qa.quantity(polradius)
diaminor = qa.quantity(2 * polradius['value'], polradius['unit'])
solrad = qa.convert(polradius, 'arcsec')
except:
print('Radius', eqradius, polradius,
'does not have the expected format, number + unit where unit is arcmin or arcsec')
return
try:
cell = qa.convert(qa.quantity(cell), 'arcsec')
cellsize = float(cell['value'])
diskpix = solrad['value'] * 2 / cellsize
cell_rad = qa.convert(cell, 'rad')
except:
print('Cell size', cell, 'does not have the expected format, number + unit where unit is arcmin or arcsec')
return
# Add 90 degrees to pangle, due to angle definition in addcomponent() -- it puts the majoraxis vertical
pangle = qa.add(qa.quantity(pangle), qa.quantity('90deg'))
mapsize = ((int(diskpix) / 512) + 1) * 512
# Flux density is doubled because it is split between XX and YY
cl.addcomponent(dir=direction, flux=flux * 2, fluxunit='Jy', freq=reffreq, shape='disk',
majoraxis=diamajor, minoraxis=diaminor, positionangle=pangle)
cl.setrefdirframe(0, 'J2000')
ia.fromshape(diskim, [mapsize, mapsize, 1, 1], overwrite=True)
cs = ia.coordsys()
cs.setunits(['rad', 'rad', '', 'Hz'])
cell_rad_val = cell_rad['value']
cs.setincrement([-cell_rad_val, cell_rad_val], 'direction')
epoch, ra, dec = direction.split()
cs.setreferencevalue([qa.convert(ra, 'rad')['value'], qa.convert(dec, 'rad')['value']], type="direction")
cs.setreferencevalue(reffreq, 'spectral')
cs.setincrement(bdwidth, 'spectral')
ia.setcoordsys(cs.torecord())
ia.setbrightnessunit("Jy/pixel")
ia.modify(cl.torecord(), subtract=False)
ia.close()
ia.done()
# cl.close()
cl.done()
return diskim
def ksc_sim_gauss(projname='sim_7m_array_1GHz_gaus',
antennalist='ksc-7m.cfg',
dishdiam=7,
imagename=None,
indirection='J2000 14h26m46.0s -14d31m22.0s',
incell='1arcsec',
frequency='1.0GHz',
inwidth='1MHz',
radec_offset=[100., 100.],
flux=50.,
majoraxis='40arcsec',
minoraxis='27arcsec',
positionangle='45.0deg',
imsize=[512, 512]):
"""
Simulate observation of an input Gaussian model
:param projname: project name for simobserve
:param antennalist: cfg file of the array configuration
:param dishdiam: diameter of each dish, in meters
:param imagename: name (and path) for output clean image, psf, etc.
:param indirection: phase center of the observation
:param incell: pixel scale of the model/simulated image
:param frequency: central frequency
:param inwidth: frequency bandwidth
:param radec_offset: offset of the Gaussian source from the phasecenter, in arcsec
:param flux: total flux of the Gaussian source, in solar flux unit (sfu)
:param majoraxis: FWHM size of the Gaussian source along the major axis
:param minoraxis: FWHM size of the Gaussian source along the minor axis
:param positionangle: position angle of the Gaussian source
:param imsize: size of the model/simulated image, in pixels (x and y)
:return:
"""
# set voltage patterns and primary beams for KSC 7 m. This is a placeholder for now (but required for PB correction)
vp = vptool()
if len(vp.getvp(telescope='KSC').keys()) == 0:
vprec = vp.setpbairy(telescope='KSC',
dishdiam='{0:.1f}m'.format(dishdiam),
blockagediam='0.75m',
maxrad='1.784deg',
reffreq='1.0GHz',
dopb=True)
# make a Gaussian source
cl = cltool()
ia = iatool()
cl.addcomponent(dir=indirection,
flux=flux * 1e4,
fluxunit='Jy',
freq=frequency,
shape="Gaussian",
majoraxis=majoraxis,
minoraxis=minoraxis,
positionangle=positionangle)
ia.fromshape("Gaussian.im", imsize + [1, 1], overwrite=True)
cs = ia.coordsys()
cs.setunits(['rad', 'rad', '', 'Hz'])
cell_rad = qa.convert(qa.quantity(incell), "rad")['value']
cs.setincrement([-cell_rad, cell_rad], 'direction')
ra_ref = qa.toangle(indirection.split(' ')[1])
dec_ref = qa.toangle(indirection.split(' ')[2])
ra = ra_ref['value'] - radec_offset[0] / 3600.
dec = dec_ref['value'] - radec_offset[1] / 3600.
cs.setreferencevalue([
qa.convert('{0:.4f}deg'.format(ra), 'rad')['value'],
qa.convert('{0:.4f}deg'.format(dec), 'rad')['value']
],
type="direction")
cs.setreferencevalue("1.0GHz", 'spectral')
cs.setincrement('10MHz', 'spectral')
ia.setcoordsys(cs.torecord())
ia.setbrightnessunit("Jy/pixel")
ia.modify(cl.torecord(), subtract=False)
ia.close()
simobserve(project=projname,
skymodel='Gaussian.im',
indirection=indirection,
incell=incell,
incenter=frequency,
inwidth=inwidth,
hourangle='transit',
refdate='2014/11/01',
totaltime='120s',
antennalist=antennalist,
obsmode='int',
overwrite=True)
if not imagename:
imagename = projname + '/tst'
tclean(vis=projname + '/' + projname + '.' + antennalist.split('.')[0] +
'.ms',
imagename=imagename,
imsize=imsize,
cell=incell,
phasecenter=indirection,
niter=200,
interactive=False)
viewer(projname + '/' + projname + '.' + antennalist.split('.')[0] +
'.skymodel')
viewer(imagename + '.psf')
viewer(imagename + '.image')
plot_profile_map(image, figfile, pol, spectralaxis, restfreq, title, linecolor, linestyle, linewidth,
separatepanel, plotmasked, maskedcolor,
showaxislabel, showtick, showticklabel, parsed_size,
nx, ny, transparent, plotrange)
except Exception, e:
casalog.post('Error: %s'%(str(e)), priority='SEVERE')
import traceback
casalog.post(traceback.format_exc(), priority='DEBUG')
raise e
finally:
pass
NoData = -32767.0
NoDataThreshold = NoData + 10000.0
LightSpeedQuantity = qa.constants('c')
LightSpeed = qa.convert(LightSpeedQuantity, 'km/s')['value'] # speed of light in km/s
DPIDetail = 130
dsyb = '$^\circ$'
hsyb = ':'
msyb = ':'
def Deg2HMS(x, arrowance):
# Transform degree to HHMMSS.sss format
xx = x % 360 + arrowance
h = int(xx / 15)
m = int((xx % 15) * 4)
s = ((xx % 15) * 4 - m) * 60.0
return (h, m, s)
def HHMMSSss(x, pos):
else:
try:
# meanrad might already have been converted.
if type(retdict[hk]) != dict:
retdict[hk] = {"unit": headers[hk]["unit"], "value": float(retdict[hk])}
except Exception, e:
print "Error converting header", hk, "to a Quantity."
print "retdict[hk] =", retdict[hk]
raise e
elif hk == "GeoLong":
long_lat_alt = retdict[hk].split(",")
retdict["GeoLong"] = float(long_lat_alt[0])
retdict["GeoLat"] = float(long_lat_alt[1])
retdict["GeoDist"] = float(long_lat_alt[2])
elif hk == "dMJD":
retdict[hk] = qa.convert(qa.totime(retdict[hk].replace("minutes", "min")), "d")["value"]
elif hk == "orb_per":
unit = "h"
retrograde = False
if "d" in retdict[hk].lower():
unit = "d" # Actually this is most common.
if "r" in retdict[hk].lower():
retrograde = True
value = get_num_from_str(retdict[hk], "orbital period")
if value != False:
if retrograde and value > 0.0:
value = -value
retdict[hk] = {"unit": unit, "value": value}
else:
del retdict[hk]
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()
try:
# meanrad might already have been converted.
if type(retdict[hk]) != dict:
retdict[hk] = {'unit': headers[hk]['unit'],
'value': float(retdict[hk])}
except Exception, e:
print "Error converting header", hk, "to a Quantity."
print "retdict[hk] =", retdict[hk]
raise e
elif hk == 'GeoLong':
long_lat_alt = retdict[hk].split(',')
retdict['GeoLong'] = float(long_lat_alt[0])
retdict['GeoLat'] = float(long_lat_alt[1])
retdict['GeoDist'] = float(long_lat_alt[2])
elif hk == 'dMJD':
retdict[hk] = qa.convert(qa.totime(retdict[hk].replace('minutes', 'min')),
'd')['value']
elif hk == 'orb_per':
unit = 'h'
retrograde = False
if 'd' in retdict[hk].lower():
unit = 'd' # Actually this is most common.
if 'r' in retdict[hk].lower():
retrograde = True
value = get_num_from_str(retdict[hk], 'orbital period')
if value != False:
if retrograde and value > 0.0:
value = -value
retdict[hk] = {'unit': unit, 'value': value}
else:
del retdict[hk]
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 subvs(vis=None,
outputvis=None,
timerange=None,
spw=None,
timoffset=4,
windowlen=10,
windowtype='flat',
splitsel=True,
reverse=False,
overwrite=False):
"""Vector-subtraction in UV using selected time ranges and spectral channels as background
subvs is a function to do UV vector-subtraction. By selecting gliding averaging window,
only the low-frequency signals corresponding to the background continuum emission remain.
As a result, a uv subtraction of original dynamic spectrum from the background can improve
fine stucture such as fibers. Subvs can be used to subtract the background
continuum emission to separate the time-dependent emission, e.g. solar
coherent radio bursts.
Keyword arguments:
vis -- Name of input visibility file
default: none; example: vis='sun_type3.ms'
outputvis -- Name of output visibility file
default: none; example: outputvis='sun_type3.sub.ms'
timerange -- Select the time range in the data to be subtracted from.
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
Note: if YYYY/MM/DD is missing date, timerange defaults to the
first day in the dataset
timerange='09:14:0~09:54:0' picks 40 min on first day
timerange='25:00:00~27:30:00' picks 1 hr to 3 hr 30min
on next day
spw -- Select spectral window/channel.
default = '' all the spectral channels. Example: spw='0:1~20'
timoffset -- After the convolution, each single channel of smoothed uv vectors
in time series are misaligned from original data. Setting the
timoffset allow you to shift by the specifed amount of data points.
windowlen -- Choose the width the gliding window for smoothing.
windowtype -- Choose the type o gliding window. Options available are 'flat',
'hanning', 'hamming', 'bartlett', 'blackman'
splitsel -- True of 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 already existing
output measurement set will be replaced with 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()
# check and specify time range and channel
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('~')
nchan = int(echan) - int(bchan) + 1
else:
casalog.post('spw not specified, use all frequency channels')
#select data range to be smoothed
ms.open(vis, nomodify=True)
#Select the spw id
ms.msselect({'time': timerange})
ms.selectinit(datadescid=int(spwid))
ms.selectchannel(nchan, int(bchan), 1, 1)
rec = ms.getdata(['data', 'time', 'axis_info'], ifraxis=True)
#print 'shape of the frequency matrix ',rec1['axis_info']['freq_axis']['chan_freq'].shape
sz = rec['data'].shape
print 'dimension of selected background for smoothing', rec['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
if not (timoffset and (type(timoffset) == int)):
timoffset = int(4)
for i in range(rec['data'].shape[0]):
for j in range(rec['data'].shape[1]):
for k in range(rec['data'].shape[2]):
rec['data'][i, j,
k, :] = task_smooth.smooth(rec['data'][i, j, k, :],
timoffset, windowlen,
windowtype)
casalog.post('Smoothing the visibilities in timerange: ' + timerange)
ms.close()
#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))
casalog.post('Subtracting background defined in timerange: ' + timerange)
for i in range(t_rows):
orec['data'][:, :, :, i] -= rec['data'][:, :, :, i]
if reverse:
orec['data'][:, :, :, i] = -orec['data'][:, :, :, i]
del orec['time']
del orec['axis_info']
ms.putdata(orec)
ms.close()
plotmasked, maskedcolor, showaxislabel, showtick,
showticklabel, parsed_size, nx, ny, transparent,
plotrange)
except Exception, e:
casalog.post('Error: %s' % (str(e)), priority='SEVERE')
import traceback
casalog.post(traceback.format_exc(), priority='DEBUG')
raise e
finally:
pass
NoData = -32767.0
NoDataThreshold = NoData + 10000.0
LightSpeedQuantity = qa.constants('c')
LightSpeed = qa.convert(LightSpeedQuantity,
'km/s')['value'] # speed of light in km/s
DPIDetail = 130
dsyb = '$^\circ$'
hsyb = ':'
msyb = ':'
def Deg2HMS(x, arrowance):
# Transform degree to HHMMSS.sss format
xx = x % 360 + arrowance
h = int(xx / 15)
m = int((xx % 15) * 4)
s = ((xx % 15) * 4 - m) * 60.0
return (h, m, s)
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 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 split_core(vis, outputvis, datacolumn, field, spw, width, antenna,
timebin, timerange, scan, intent, array, uvrange,
correlation, observation, combine, keepflags):
retval = True
if not outputvis or outputvis.isspace():
raise ValueError, 'Please specify outputvis'
myms = mstool()
mytb = None
if ((type(vis)==str) & (os.path.exists(vis))):
myms.open(vis, nomodify=True)
else:
raise ValueError, 'Visibility data set not found - please verify the name'
if os.path.exists(outputvis):
myms.close()
raise ValueError, "Output MS %s already exists - will not overwrite." % outputvis
if (os.path.exists(outputvis+".flagversions")):
myms.close()
raise ValueError, "The flagversions \"%s.flagversions\" for the output MS already exist. Please delete." % outputvis
# No longer needed. When did it get put in? Note that the default
# spw='*' in myms.split ends up as '' since the default type for a variant
# is BOOLVEC. (Of course!) Therefore both split and myms.split must
# work properly when spw=''.
#if(spw == ''):
# spw = '*'
if(type(antenna) == list):
antenna = ', '.join([str(ant) for ant in antenna])
## Accept digits without units ...assume seconds
timebin = qa.convert(qa.quantity(timebin), 's')['value']
timebin = str(timebin) + 's'
if timebin == '0s':
timebin = '-1s'
# MSStateGram is picky ('CALIBRATE_WVR.REFERENCE, OBSERVE_TARGET_ON_SOURCE'
# doesn't work, but 'CALIBRATE_WVR.REFERENCE,OBSERVE_TARGET_ON_SOURCE'
# does), and I don't want to mess with bison now. A .upper() might be a
# good idea too, but the MS def'n v.2 does not say whether OBS_MODE should
# be case-insensitive.
intent = intent.replace(', ', ',')
if '^' in spw:
casalog.post("The interpretation of ^n in split's spw strings has changed from 'average n' to 'skip n' channels!", 'WARN')
casalog.post("Watch for Slicer errors", 'WARN')
if type(width) == str:
try:
if(width.isdigit()):
width=[string.atoi(width)]
elif(width.count('[') == 1 and width.count(']') == 1):
width = width.replace('[', '')
width = width.replace(']', '')
splitwidth = width.split(',')
width = []
for ws in splitwidth:
if(ws.isdigit()):
width.append(string.atoi(ws))
else:
width = [1]
except:
raise TypeError, 'parameter width is invalid...using 1'
if type(correlation) == list:
correlation = ', '.join(correlation)
correlation = correlation.upper()
if hasattr(combine, '__iter__'):
combine = ', '.join(combine)
if type(spw) == list:
spw = ','.join([str(s) for s in spw])
elif type(spw) == int:
spw = str(spw)
do_chan_mod = spw.find('^') > -1 # '0:2~11^1' would be pointless.
if not do_chan_mod: # ...look in width.
if type(width) == int and width > 1:
do_chan_mod = True
elif hasattr(width, '__iter__'):
for w in width:
if w > 1:
do_chan_mod = True
break
do_both_chan_and_time_mod = (do_chan_mod and
string.atof(timebin[:-1]) > 0.0)
if do_both_chan_and_time_mod:
# Do channel averaging first because it might be included in the spw
# string.
import tempfile
# We want the directory outputvis is in, not /tmp, because /tmp
# might not have enough space.
# outputvis is itself a directory, so strip off a trailing slash if
# it is present.
# I don't know if giving tempfile an absolute directory is necessary -
# dir='' is effectively '.' in Ubuntu.
workingdir = os.path.abspath(os.path.dirname(outputvis.rstrip('/')))
cavms = tempfile.mkdtemp(suffix=outputvis, dir=workingdir)
casalog.post('Channel averaging to ' + cavms)
if not myms.split(outputms=cavms, field=field,
spw=spw, step=width,
baseline=antenna, subarray=array,
timebin='', time=timerange,
whichcol=datacolumn,
scan=scan, uvrange=uvrange,
combine=combine,
correlation=correlation, intent=intent,
obs=str(observation)):
myms.close()
if os.path.isdir(cavms):
import shutil
shutil.rmtree(cavms)
return False
# The selection was already made, so blank them before time averaging.
field = ''
spw = ''
width = [1]
antenna = ''
array = ''
timerange = ''
datacolumn = 'all'
scan = ''
intent = ''
uvrange = ''
observation = ''
myms.close()
myms.open(cavms)
casalog.post('Starting time averaging')
if keepflags:
taqlstr = ''
else:
taqlstr = 'NOT (FLAG_ROW OR ALL(FLAG))'
if not myms.split(outputms=outputvis, field=field,
spw=spw, step=width,
baseline=antenna, subarray=array,
timebin=timebin, time=timerange,
whichcol=datacolumn,
scan=scan, uvrange=uvrange,
combine=combine,
correlation=correlation,
taql=taqlstr, intent=intent,
obs=str(observation)):
myms.close()
return False
myms.close()
if do_both_chan_and_time_mod:
import shutil
shutil.rmtree(cavms)
# Write history to output MS, not the input ms.
try:
param_names = split_core.func_code.co_varnames[:split_core.func_code.co_argcount]
param_vals = [eval(p) for p in param_names]
retval &= write_history(myms, outputvis, 'oldsplit', param_names, param_vals,
casalog)
except Exception, instance:
casalog.post("*** Error \'%s\' updating HISTORY" % (instance),
'WARN')
def 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=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: {0:s}'.format(msinfo0['vis']))
scans = msinfo0['scans']
fieldids = msinfo0['fieldids']
btimes = msinfo0['btimes']
inttimes = msinfo0['inttimes']
ras = msinfo0['ras']
decs = msinfo0['decs']
if 'observatory' in msinfo0.keys():
if msinfo0['observatory'] == 'EOVSA':
usephacenter = False
if type(ras) is list:
ra_rads = [ra['value'] for ra in ras]
elif type(ras) is dict:
ra_rads = ras['value']
else:
print('Type of msinfo0["ras"] unrecognized.')
return 0
if type(decs) is list:
dec_rads = [dec['value'] for dec in decs]
elif type(decs) is dict:
dec_rads = decs['value']
else:
print('Type of msinfo0["decs"] unrecognized.')
# 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
try:
[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.
except:
print('Error in converting the input reftime: ' +
str(reftime0) + '. Aborting...')
else:
# if reftime0 is specified as a single value
try:
tref_d = qa.getvalue(qa.convert(qa.totime(reftime0), 'd'))[0]
# 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)
# if msinfo0['etimes']:
# tdur_s = inttimes[ind - 1]
# else:
# tdur_s = np.mean(inttimes)
tdur_s = 1.
except:
print('Error in converting the input reftime: ' +
str(reftime0) + '. Aborting...')
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
inttime = np.nanmean(inttimes)
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) = (ra_rads[ind - 1], ra_rads[ind])
(dec_b, dec_e) = (dec_rads[ind - 1], dec_rads[ind])
if ind >= len(btimes):
scanlen = btimes[ind - 1] - btimes[ind - 2]
(ra_b, ra_e) = (ra_rads[ind - 2], ra_rads[ind - 1])
(dec_b, dec_e) = (dec_rads[ind - 2], dec_rads[ind - 1])
if ind == 1: # only one scan exists (e.g., imported from AIPS)
ra_b = ra_rads[ind - 1]
ra_e = ra_b
dec_b = dec_rads[ind - 1]
dec_e = dec_b
scanlen = 10. # radom value
dt = 0.
if ind < 1:
if np.abs((tref_d - btimes[0]) * 24 * 3600) < inttime / 2.0:
ind = 1
ra_b = ra_rads[ind - 1]
ra_e = ra_b
dec_b = dec_rads[ind - 1]
dec_e = dec_b
scanlen = 10. # radom value
dt = 0.
else:
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']
if len(time0) > 1:
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
else:
try:
ra0 = ra0[0]
dec0 = dec0[0]
p0 = p0[0]
delta0 = delta0[0]
except:
print("Error in retrieving info from ephemeris!")
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 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 readJPLephem(fmfile, version=''):
"""
Reads a JPL Horizons text file (see
http://ssd.jpl.nasa.gov/horizons.cgi#top ) for a solar system object and
returns various quantities in a dictionary. The dict will be blank ({}) if
there is a failure.
"""
retdict = {}
casalog.origin('readJPLephem')
# Try opening fmfile now, because otherwise there's no point continuing.
try:
ephem = open(fmfile, 'rb')
print("opened the file=", fmfile)
lines = ephem.readlines()
# skip this, handle by rstrip later
#crCount=0
#newlines=''
#newln=''
#for ln in lines:
# n = ln.count('\r')
# if n > 0:
# newln=ln.replace('\r','\n')
# crCount+=n
# newlines += newln
#if crCount > 0:
# print("The input file appears to contains the carriage return code, \'^M\', will replace it with \'\\n\'...")
# raw_input('pause0')
# ephem.close()
# ephem = open('temp_ephem_data.txt','w+')
# ephem.write(newlines)
ephem.seek(0)
except IOError:
casalog.post("Could not open ephemeris file " + fmfile,
priority="SEVERE")
return {}
# reset to default search pattern for MJD
cols['MJD']['pat'] = r'(?P<MJD>\d+-\w+-\d+ \d+:\d+)'
# Setup the regexps.
# Headers (one time only things)
# Dictionary of quantity label: regexp pattern pairs that will be searched
# for once. The matching quantity will go in retdict[label]. Only a
# single quantity (group) will be retrieved per line.
headers = {
'NAME': {
'pat': r'^[>\s]*Target body name:\s+\d*\s*(\w+)'
}, # object name, w.o. number
'ephtype': {
'pat': r'\?s_type=1#top>\]\s*:\s+\*(\w+)'
}, # e.g. OBSERVER
'obsloc': {
'pat': r'^[>\s]*Center-site name:\s+(\w+)'
}, # e.g. GEOCENTRIC
# Catch either an explicit mean radius or a solitary target radius.
'meanrad': {
'pat':
r'(?:Mean radius \(km\)\s*=|^Target radii\s*:)\s*([0-9.]+)(?:\s*km)?\s*$',
'unit': 'km'
},
# Triaxial target radii
#'radii': {'pat': r'Target radii\s*:\s*([0-9.]+\s*x\s*[0-9.]+\s*x\s*[0-9.]+)\s*km.*Equator, meridian, pole',
'radii': {
'pat':
r'Target radii\s*:\s*([0-9.]+\s*x\s*[0-9.]+\s*x\s*[0-9.]+)\s*km.*Equator, meridian, pole|Target radii\s*:\s*([0-9.]+)\s*km\s*',
'unit': 'km'
},
'T_mean': {
'pat': r'Mean Temperature \(K\)\s*=\s*([0-9.]+)',
'unit': 'K'
},
# Figure out the units later.
'rot_per': {
'pat':
r'(?i)(?<!Inferred )\b(rot(ation(al)?|\.)?\s*per.*=\s*([-0-9.]+\s*[dhr]*|Synchronous))'
},
'orb_per': {
'pat':
r'Orbital period((, days)?\s*=\s*[-0-9.]+\s*[dhr](\s*\(?R\)?)?)'
},
# MeasComet does not read units for these! E-lon(deg), Lat(deg), Alt(km)
'GeoLong': {
'pat':
r'^[>\s]*Center geodetic\s*: ([-+0-9.]+,\s*[-+0-9.]+,\s*[-+0-9.]+)'
},
'dMJD': {
'pat': r'^[>\s]*Step-size\s*:\s*(.+)'
},
# request method v wday mth mday hh mm ss yyyy
'VS_CREATE': {
'pat':
r'^[>\s]*Ephemeris / \w+ \w+ (\w+\s+\d+\s+\d+:\d+:\d+\s+\d+)'
}
}
for hk in headers:
headers[hk]['pat'] = re.compile(headers[hk]['pat'])
# Data ("the rows of the table")
# need date, r (heliocentric distance), delta (geocentric distance), and phang (phase angle).
# (Could use the "dot" time derivatives for Doppler shifting, but it's
# likely unnecessary.)
#datapat = r'^[>\s]*'
datapat = r'^\s*'
stoppat = r'[>\s]*\$\$EOE$' # Signifies the end of data.
# Read fmfile into retdict.
num_cols = 0
in_data = False
comp_mismatches = []
print_datapat = False
# define interpretation of invalid values ('n.a.')
invalid = -999.
for origline in ephem:
line = origline.rstrip('\r\n')
if in_data:
if re.match(stoppat, line):
break
matchobj = re.search(datapat, line)
if matchobj:
#print("matchobj!")
gdict = matchobj.groupdict()
#print("gdict=",gdict)
for col in gdict:
if gdict[col] == 'n.a.':
gdict[col] = invalid
# print("cols.key=",cols.keys())
if not cols[col].get('unwanted'):
retdict['data'][col]['data'].append(gdict[col])
if len(gdict) < num_cols:
print("Partially mismatching line:")
print(line)
print("Found:")
print(gdict)
print_datapat = True
raw_input("pause0")
else:
print_datapat = True
# Chomp trailing whitespace.
comp_mismatches.append(re.sub(r'\s*$', '', line))
elif re.match(
r'^[>\s]*' + cols['MJD']['header'] + r'\s+' +
cols['RA']['header'], line):
# need to modify regex to search for the header name for MJD containing second digits
if re.match(r'^[>\s]*Date__\(UT\)__HR:MN:SC.fff', line):
cols['MJD']['pat'] = r'(?P<MJD>\d+-\w+-\d+ \d+:\d+:\d+.\d+)'
# See what columns are present, and finish setting up datapat and
# retdict.
havecols = []
# extract coordinate ref info
m = re.match(r'(^[>\s]*)(\S+)(\s+)(' + cols['RA']['header'] + ')',
line)
coordref = m.group(4).split('(')[-1]
cols['RA']['comment'] += '(' + coordref + ')'
cols['DEC']['comment'] += '(' + coordref + ')'
#print("cols['RA']['comment']=", cols['RA']['comment'])
# Chomp trailing whitespace.
myline = re.sub(r'\s*$', '', line)
titleline = myline
remaining_cols = cols.keys()
found_col = True
# This loop will terminate one way or another.
while myline and remaining_cols and found_col:
found_col = False
#print("myline = '%s'" % myline)
#print("remaining_cols =", ', '.join(remaining_cols))
for col in remaining_cols:
if re.match(r'^[>\s]*' + cols[col]['header'], myline):
#print("Found", col)
havecols.append(col)
remaining_cols.remove(col)
myline = re.sub(r'^[>\s]*' + cols[col]['header'], '',
myline)
found_col = True
break
datapat += r'\s+'.join([cols[col]['pat'] for col in havecols])
sdatapat = datapat
casalog.post("Found columns: " + ', '.join(havecols))
datapat = re.compile(datapat)
retdict['data'] = {}
for col in havecols:
if not cols[col].get('unwanted'):
retdict['data'][col] = {
'comment': cols[col]['comment'],
'data': []
}
num_cols = len(retdict['data'])
#elif re.match(r'^\$\$SOE\s*$', line): # Start of ephemeris
elif re.match(r'^[>\s]*\$\$SOE\s*$', line): # Start of ephemeris
casalog.post("Starting to read data.", priority='INFO2')
in_data = True
else:
#print("line =", line)
#print("looking for",)
for hk in headers:
#print("hk=",hk)
if not retdict.has_key(hk):
matchobj = re.search(headers[hk]['pat'], line)
if matchobj:
if hk == 'radii':
mobjs = matchobj.groups()
for gp in mobjs:
if gp != None:
retdict[hk] = gp
break
break
else:
retdict[hk] = matchobj.group(
1) # 0 is the whole line
break
ephem.close()
# clean up the temp file if exists
#if os.path.exists('temp_ephem_data.txt'):
# os.remove('temp_ephem_data.txt')
# If there were errors, provide debugging info.
if comp_mismatches:
print("Completely mismatching lines:")
#print("\n".join(comp_mismatches))
if print_datapat:
print("The apparent title line is:")
print(titleline)
print("datapat = r'%s'" % sdatapat)
# Convert numerical strings into actual numbers.
try:
retdict['earliest'] = datestr_to_epoch(
retdict['data']['MJD']['data'][0])
retdict['latest'] = datestr_to_epoch(
retdict['data']['MJD']['data'][-1])
except Exception as e:
print("Error!")
if retdict.has_key('data'):
if retdict['data'].has_key('MJD'):
if retdict['data']['MJD'].has_key('data'):
#print("retdict['data']['MJD']['data'] =", retdict['data']['MJD']['data'])
print("retdict['data'] =", retdict['data'])
else:
print("retdict['data']['MJD'] has no 'data' key.")
print("retdict['data']['MJD'].keys() =",
retdict['data']['MJD'].keys())
else:
print("retdict['data'] has no 'MJD' key.")
print("retdict['data'].keys() =", retdict['data'].keys())
else:
print("retdict has no 'data' key.")
raise e
for hk in headers:
if retdict.has_key(hk):
if headers[hk].has_key('unit'):
if hk == 'radii':
radii = retdict[hk].split('x')
if len(radii) == 1:
a = float(radii[0])
retdict[hk] = {
'unit': headers[hk]['unit'],
'value': (a, a, a)
}
retdict['meanrad'] = {
'unit': headers[hk]['unit'],
'value': a
}
else:
a, b, c = [float(r) for r in radii]
retdict[hk] = {
'unit': headers[hk]['unit'],
'value': (a, b, c)
}
retdict['meanrad'] = {
'unit': headers[hk]['unit'],
'value': mean_radius(a, b, c)
}
else:
try:
# meanrad might already have been converted.
if type(retdict[hk]) != dict:
retdict[hk] = {
'unit': headers[hk]['unit'],
'value': float(retdict[hk])
}
except Exception as e:
print("Error converting header", hk, "to a Quantity.")
print("retdict[hk] =", retdict[hk])
raise e
elif hk == 'GeoLong':
long_lat_alt = retdict[hk].split(',')
retdict['GeoLong'] = float(long_lat_alt[0])
retdict['GeoLat'] = float(long_lat_alt[1])
retdict['GeoDist'] = float(long_lat_alt[2])
elif hk == 'dMJD':
retdict[hk] = qa.convert(
qa.totime(retdict[hk].replace('minutes', 'min')),
'd')['value']
elif hk == 'orb_per':
unit = 'h'
retrograde = False
if 'd' in retdict[hk].lower():
unit = 'd' # Actually this is most common.
if 'r' in retdict[hk].lower():
retrograde = True
value = get_num_from_str(retdict[hk], 'orbital period')
if value != False:
if retrograde and value > 0.0:
value = -value
retdict[hk] = {'unit': unit, 'value': value}
else:
del retdict[hk]
# The rotation period might depend on the orbital period ("Synchronous"),
# so handle it after all the other headers have been done.
if 'rot_per' in retdict:
rpstr = retdict['rot_per']
if 'ROTPER' in rpstr: # Asteroid
retdict['rot_per'] = {
'unit': 'h', # Always seems to be for asteroids.
'value': get_num_from_str(rpstr, 'rotation period')
}
elif 'Synchronous' in rpstr:
retdict['rot_per'] = retdict['orb_per']
else: # Most likely a planet.
match = re.search(r'(\d+)h\s*(\d+)m\s*([0-9.]+)s', rpstr)
if match:
hms = [float(match.group(i)) for i in range(1, 4)]
retdict['rot_per'] = {
'unit': 'h',
'value': hms[0] + (hms[1] + hms[2] / 60.0) / 60.0
}
else:
# DON'T include the optional r in hr! qa.totime can't handle it.
try:
match = re.search(r'([-0-9.]+)(?:\s*\+-[0-9.]+)?\s*([dh])',
rpstr)
if match:
retdict['rot_per'] = {
'unit': match.group(2),
'value': float(match.group(1))
}
except:
print("Error parsing the rotation period from")
print(rpstr)
if retdict['data'].has_key('ang_sep'):
retdict['data']['obs_code'] = {'comment': 'Obscuration code'}
for dk in retdict['data']:
if dk == 'obs_code':
continue
if cols[dk].has_key('unit'):
retdict['data'][dk]['data'] = {
'unit':
cols[dk]['unit'],
'value':
scipy.array([float(s) for s in retdict['data'][dk]['data']])
}
if dk == 'RadVel':
# Convert from km/s to AU/d. Blame MeasComet, not me.
retdict['data'][dk]['data']['unit'] = 'AU/d'
kmps_to_AUpd = qa.convert('1km/s', 'AU/d')['value']
retdict['data'][dk]['data']['value'] *= kmps_to_AUpd
if re.match(r'.*(RA|DEC)$', dk):
retdict['data'][dk] = convert_radec(retdict['data'][dk])
elif dk == 'MJD':
retdict['data']['MJD'] = datestrs_to_MJDs(retdict['data']['MJD'])
elif dk == 'ang_sep':
angseps = []
obscodes = []
for asoc in retdict['data'][dk]['data']:
angsep, obscode = asoc.split('/')
angseps.append(float(angsep))
obscodes.append(obscode)
retdict['data'][dk]['data'] = {
'unit': 'arcseconds',
'value': angseps
}
retdict['data']['obs_code']['data'] = obscodes
if len(retdict.get('radii', {'value': []})['value']) == 3 \
and retdict['data'].has_key('NP_RA') and retdict['data'].has_key('NP_DEC'):
# Do a better mean radius estimate using the actual theta.
retdict['meanrad']['value'] = mean_radius_with_known_theta(retdict)
# To be eventually usable as a MeasComet table, a few more keywords are needed.
retdict['VS_TYPE'] = 'Table of comet/planetary positions'
if version == '':
version = '0003.0001'
#retdict['VS_VERSION'] = '0003.0001'
retdict['VS_VERSION'] = version
if retdict.has_key('VS_CREATE'):
dt = time.strptime(retdict['VS_CREATE'], "%b %d %H:%M:%S %Y")
else:
casalog.post(
"The ephemeris creation date was not found. Using the current time.",
priority="WARN")
dt = time.gmtime()
retdict['VS_CREATE'] = time.strftime('%Y/%m/%d/%H:%M', dt)
# VS_DATE is required by MeasComet, but it doesn't seem to be actually used.
retdict['VS_DATE'] = time.strftime('%Y/%m/%d/%H:%M', time.gmtime())
if retdict['data'].has_key('MJD'):
#casalog.post("retdict.keys=%s" % retdict.keys())
retdict['MJD0'] = retdict['data']['MJD']['value'][0] - retdict['dMJD']
else:
print(
"The table will not be usable with me.framecomet because it lacks MJD."
)
# adding posrefsys keyword
if cols['RA']['comment'].count('J2000'):
retdict['posrefsys'] = 'ICRF/J2000.0'
if cols['RA']['comment'].count('B1950'):
retdict['posrefsys'] = 'FK4/B1950.0'
return retdict
