def reflectance_correction(rad_arr, lons, lats):
'''Make satpy "reflectances" consistent with usual definition
Reflectance is normally defined as outgoing radiation/incoming radiation.
In satpy, the denominator is set to a fixed value - the incoming radiation
for a solar zenith angle of 0 and earth-sun distance of one. This function
corrects this using the actual earth-sun distance and the solar zenith
angle appropriate for the observation time. See discussion at
https://github.com/pytroll/satpy/issues/536 for further details.
Args:
rad_arr (Xarray): Xarray for one of the two visible channels (0.6, 0.8) from satpy scene
lons (ndarray, shape(nlat,nlon)): Array of longitude values
lats (ndarray, shape(nlat,nlon)): Array of longitude values
Returns:
rad_arr (Xarray): Input array, with reflectance corrected to account for
solar zenith angle and earth-sun distance.
'''
from astropy.units import AU # Requires virtual environment
from sunpy.sun import sunearth_distance # Requires virtual environment
from pyorbital.astronomy import sun_zenith_angle
nx = rad_arr.sizes['x']
ny = rad_arr.sizes['y']
mu0 = np.ma.zeros((ny,nx))
dist_sun_earth = np.ma.zeros(ny)
Tacq = rad_arr.attrs["end_time"] - rad_arr.attrs["start_time"]
for j in range(ny) :
tacq = rad_arr.attrs["start_time"] + datetime.timedelta( seconds=(j/float(ny))*Tacq.seconds )
mu0[j,:] = np.ma.masked_outside( np.pi*sun_zenith_angle( tacq, lons[j,:], lats[j,:])/180.,0.035, 1, copy=False) # in degrees
dist_sun_earth[j] = float(sunearth_distance(tacq) / AU)
rad_arr.values *= ((dist_sun_earth[:,None]**2) / np.cos(mu0)) # sun earth distance in AU.
return rad_arr
def test_sunearth_distance():
assert_array_almost_equal(sun.sunearth_distance("2010/02/04"), 0.9858, decimal=4)
assert_array_almost_equal(sun.sunearth_distance("2009/04/13"), 1.003, decimal=4)
assert_array_almost_equal(sun.sunearth_distance("2008/06/20"), 1.016, decimal=4)
assert_array_almost_equal(sun.sunearth_distance("2007/08/15"), 1.013, decimal=4)
assert_array_almost_equal(sun.sunearth_distance("2007/10/02"), 1.001, decimal=4)
assert_array_almost_equal(sun.sunearth_distance("2006/12/27"), 0.9834, decimal=4)
def test():
"""
Print out a summary of Solar ephemeris
A correct answer set to compare to
Solar Ephemeris for 1-JAN-01 00:00:00
Distance (AU) = 0.98330468
Semidiameter (arc sec) = 975.92336
True (long, lat) in degrees = (280.64366, 0.00000)
Apparent (long, lat) in degrees = (280.63336, 0.00000)
True (RA, Dec) in hrs, deg = (18.771741, -23.012449)
Apparent (RA, Dec) in hrs, deg = (18.770994, -23.012593)
Heliographic long. and lat. of disk center in deg = (217.31269, -3.0416292)
Position angle of north pole in deg = 2.0102649
Carrington Rotation Number = 1971.4091 check!
"""
t = '2001-01-01T00:00:00'
swpy_jd = swdt.julian_day(t)
sunpy_jd = sunt.julian_day(t)
print "SWPY JD: {}, SUNPY JD: {}".format(swpy_jd,sunpy_jd)
print "Sun-earth distance: {}, {}".format(
sun.sunearth_distance(t),
ssun.sunearth_distance(t))
print "Solar semidiameter angular size: {}, {}".format(
sun.solar_semidiameter_angular_size(t),
sun.solar_semidiameter_angular_size(t))
print "True longitude: {}, {}".format(sun.true_longitude(t),
ssun.true_longitude(t))
print "Apparent Longitude: {}, {}".format(sun.apparent_longitude(t),
ssun.apparent_longitude(t))
print "True R.A.: {}, {}".format(
sun.true_rightascension(t),
ssun.true_rightascension(t))
print "True Dec.: {}, {}".format(sun.true_declination(t),
ssun.true_declination(t))
print "Apparent R.A.: {}, {}".format(
sun.apparent_rightascension(t),
ssun.apparent_rightascension(t))
print "Apparent Dec.: {}, {}".format(sun.apparent_declination(t),
ssun.apparent_declination(t))
print "Heliographic center: {}, {}".format(sun.heliographic_solar_center(t),
ssun.heliographic_solar_center(t))
print "Position angle of north pole [deg]: {}, {}".format(sun.solar_north(t),
ssun.solar_north(t))
print "Carrington rotation number: {}, {}".format(sun.carrington_rotation_number(t),
ssun.carrington_rotation_number(t))
def plt_qlook_image(imres, figdir=None, verbose=True, synoptic=False):
from matplotlib import pyplot as plt
from sunpy import map as smap
from sunpy import sun
from matplotlib import colors
import astropy.units as u
from suncasa.utils import plot_mapX as pmX
# from matplotlib import gridspec as gridspec
if not figdir:
figdir = './'
nspw = len(set(imres['Spw']))
plttimes = list(set(imres['BeginTime']))
ntime = len(plttimes)
# sort the imres according to time
images = np.array(imres['ImageName'])
btimes = Time(imres['BeginTime'])
etimes = Time(imres['EndTime'])
spws = np.array(imres['Spw'])
suc = np.array(imres['Succeeded'])
inds = btimes.argsort()
images_sort = images[inds].reshape(ntime, nspw)
btimes_sort = btimes[inds].reshape(ntime, nspw)
suc_sort = suc[inds].reshape(ntime, nspw)
if verbose:
print('{0:d} figures to plot'.format(ntime))
plt.ioff()
fig = plt.figure(figsize=(8, 8))
plt.subplots_adjust(left=0, bottom=0, right=1, top=1, wspace=0, hspace=0)
axs = []
ims = []
pltst = 0
for i in range(ntime):
plt.ioff()
plttime = btimes_sort[i, 0]
tofd = plttime.mjd - np.fix(plttime.mjd)
suci = suc_sort[i]
if not synoptic:
if tofd < 16. / 24. or sum(
suci
) < nspw - 2: # if time of the day is before 16 UT (and 24 UT), skip plotting (because the old antennas are not tracking)
continue
else:
if pltst == 0:
i0 = i
pltst = 1
else:
if pltst == 0:
i0 = i
pltst = 1
if i == i0:
if synoptic:
timetext = fig.text(0.01,
0.98,
plttime.iso[:10],
color='w',
fontweight='bold',
fontsize=12,
ha='left')
else:
timetext = fig.text(0.01,
0.98,
plttime.iso[:19],
color='w',
fontweight='bold',
fontsize=12,
ha='left')
else:
if synoptic:
timetext.set_text(plttime.iso[:10])
else:
timetext.set_text(plttime.iso[:19])
if verbose:
print('Plotting image at: ', plttime.iso)
for n in range(nspw):
plt.ioff()
if i == i0:
if nspw == 1:
ax = fig.add_subplot(111)
else:
ax = fig.add_subplot(nspw / 2, 2, n + 1)
axs.append(ax)
else:
ax = axs[n]
image = images_sort[i, n]
if suci[n] or os.path.exists(image):
try:
eomap = smap.Map(image)
except:
continue
data = eomap.data
sz = data.shape
if len(sz) == 4:
data = data.reshape((sz[2], sz[3]))
data[np.isnan(data)] = 0.0
# add a basin flux to the image to avoid negative values
data = data + 0.8e5
data[data < 0] = 0.0
data = np.sqrt(data)
eomap = smap.Map(data, eomap.meta)
# resample the image for plotting
dim = u.Quantity([256, 256], u.pixel)
eomap = eomap.resample(dim)
else:
# make an empty map
data = np.zeros((256, 256))
header = {
"DATE-OBS": plttime.isot,
"EXPTIME": 0.,
"CDELT1": 10.,
"NAXIS1": 256,
"CRVAL1": 0.,
"CRPIX1": 128.5,
"CUNIT1": "arcsec",
"CTYPE1": "HPLN-TAN",
"CDELT2": 10.,
"NAXIS2": 256,
"CRVAL2": 0.,
"CRPIX2": 128.5,
"CUNIT2": "arcsec",
"CTYPE2": "HPLT-TAN",
"HGLT_OBS":
sun.heliographic_solar_center(plttime)[1].value,
"HGLN_OBS": 0.,
"RSUN_OBS":
sun.solar_semidiameter_angular_size(plttime).value,
"RSUN_REF": sun.constants.radius.value,
"DSUN_OBS":
sun.sunearth_distance(plttime).to(u.meter).value,
}
eomap = smap.Map(data, header)
if i == i0:
eomap_ = pmX.Sunmap(eomap)
# im = eomap_.imshow(axes=ax, cmap='jet', norm=colors.LogNorm(vmin=0.1, vmax=1e8))
im = eomap_.imshow(axes=ax,
cmap='jet',
norm=colors.Normalize(vmin=150, vmax=700))
ims.append(im)
if not synoptic:
eomap_.draw_limb(axes=ax)
eomap_.draw_grid(axes=ax)
ax.set_xlim([-1080, 1080])
ax.set_ylim([-1080, 1080])
try:
cfreq = eomap.meta['crval3'] / 1.0e9
bdwid = eomap.meta['cdelt3'] / 1.0e9
ax.text(0.98,
0.01,
'{0:.1f} - {1:.1f} GHz'.format(
cfreq - bdwid / 2.0, cfreq + bdwid / 2.0),
color='w',
transform=ax.transAxes,
fontweight='bold',
ha='right')
except:
pass
ax.set_title(' ')
ax.set_xlabel('')
ax.set_ylabel('')
ax.set_xticklabels([''])
ax.set_yticklabels([''])
else:
ims[n].set_data(eomap.data)
fig_tdt = plttime.to_datetime()
if synoptic:
fig_subdir = fig_tdt.strftime("%Y/")
figname = 'eovsa_qlimg_' + plttime.iso[:10].replace('-',
'') + '.png'
else:
fig_subdir = fig_tdt.strftime("%Y/%m/%d/")
figname = 'eovsa_qlimg_' + plttime.isot.replace(':', '').replace(
'-', '')[:15] + '.png'
figdir_ = figdir + fig_subdir
if not os.path.exists(figdir_):
os.makedirs(figdir_)
if verbose:
print('Saving plot to :' + figdir_ + figname)
plt.savefig(figdir_ + figname)
plt.close(fig)
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_qlook_image(imres, figdir=None, verbose=True, synoptic=False):
from matplotlib import pyplot as plt
from sunpy import map as smap
from sunpy import sun
from matplotlib import colors
import astropy.units as u
if not figdir:
figdir = './'
nspw = len(set(imres['Spw']))
plttimes = list(set(imres['BeginTime']))
ntime = len(plttimes)
# sort the imres according to time
images = np.array(imres['ImageName'])
btimes = Time(imres['BeginTime'])
etimes = Time(imres['EndTime'])
spws = np.array(imres['Spw'])
suc = np.array(imres['Succeeded'])
inds = btimes.argsort()
images_sort = images[inds].reshape(ntime, nspw)
btimes_sort = btimes[inds].reshape(ntime, nspw)
suc_sort = suc[inds].reshape(ntime, nspw)
spws_sort = spws[inds].reshape(ntime, nspw)
if verbose:
print '{0:d} figures to plot'.format(ntime)
plt.ioff()
fig = plt.figure(figsize=(8, 8))
plt.subplots_adjust(left=0, bottom=0, right=1, top=1, wspace=0, hspace=0)
for i in range(ntime):
plt.ioff()
plt.clf()
plttime = btimes_sort[i, 0]
tofd = plttime.mjd - np.fix(plttime.mjd)
suci = suc_sort[i]
if not synoptic:
if tofd < 16. / 24. or sum(
suci
) < nspw - 2: # if time of the day is before 16 UT (and 24 UT), skip plotting (because the old antennas are not tracking)
continue
#fig=plt.figure(figsize=(9,6))
#fig.suptitle('EOVSA @ '+plttime.iso[:19])
if synoptic:
fig.text(0.01,
0.98,
plttime.iso[:10],
color='w',
fontweight='bold',
fontsize=12,
ha='left')
else:
fig.text(0.01,
0.98,
plttime.iso[:19],
color='w',
fontweight='bold',
fontsize=12,
ha='left')
if verbose:
print 'Plotting image at: ', plttime.iso
for n in range(nspw):
plt.ioff()
image = images_sort[i, n]
#fig.add_subplot(nspw/3, 3, n+1)
fig.add_subplot(nspw / 2, 2, n + 1)
if suci[n]:
try:
eomap = smap.Map(image)
except:
continue
sz = eomap.data.shape
if len(sz) == 4:
eomap.data = eomap.data.reshape((sz[2], sz[3]))
eomap.data[np.isnan(eomap.data)] = 0.0
#resample the image for plotting
dim = u.Quantity([256, 256], u.pixel)
eomap = eomap.resample(dim)
eomap.plot_settings['cmap'] = plt.get_cmap('jet')
eomap.plot_settings['norm'] = colors.Normalize(vmin=-1e5,
vmax=1e6)
eomap.plot()
if not synoptic:
eomap.draw_limb()
eomap.draw_grid()
ax = plt.gca()
ax.set_xlim([-1080, 1080])
ax.set_ylim([-1080, 1080])
spwran = spws_sort[i, n]
freqran = [int(s) * 0.5 + 2.9 for s in spwran.split('~')]
ax.text(0.98,
0.01,
'{0:.1f} - {1:.1f} GHz'.format(freqran[0], freqran[1]),
color='w',
transform=ax.transAxes,
fontweight='bold',
ha='right')
ax.set_title(' ')
#ax.set_title('spw '+spws_sort[i,n])
#ax.text(0.01,0.02, plttime.isot,transform=ax.transAxes,color='white')
ax.set_xlabel('')
ax.set_ylabel('')
ax.set_xticklabels([''])
ax.set_yticklabels([''])
else:
#make an empty map
data = np.zeros((512, 512))
header = {
"DATE-OBS": plttime.isot,
"EXPTIME": 0.,
"CDELT1": 5.,
"NAXIS1": 512,
"CRVAL1": 0.,
"CRPIX1": 257,
"CUNIT1": "arcsec",
"CTYPE1": "HPLN-TAN",
"CDELT2": 5.,
"NAXIS2": 512,
"CRVAL2": 0.,
"CRPIX2": 257,
"CUNIT2": "arcsec",
"CTYPE2": "HPLT-TAN",
"HGLT_OBS":
sun.heliographic_solar_center(plttime)[1].value,
"HGLN_OBS": 0.,
"RSUN_OBS":
sun.solar_semidiameter_angular_size(plttime).value,
"RSUN_REF": sun.constants.radius.value,
"DSUN_OBS":
sun.sunearth_distance(plttime).to(u.meter).value,
}
eomap = smap.Map(data, header)
eomap.plot_settings['cmap'] = plt.get_cmap('jet')
eomap.plot_settings['norm'] = colors.Normalize(vmin=-1e5,
vmax=1e6)
eomap.plot()
if not synoptic:
eomap.draw_limb()
eomap.draw_grid()
ax = plt.gca()
ax.set_xlim([-1080, 1080])
ax.set_ylim([-1080, 1080])
#ax.set_title('spw '+spwran+'( )'))
spwran = spws_sort[i, n]
freqran = [int(s) * 0.5 + 2.9 for s in spwran.split('~')]
spwran = spws_sort[i, n]
#ax.set_title('{0:.1f} - {1:.1f} GHz'.format(freqran[0],freqran[1]))
ax.text(0.98,
0.01,
'{0:.1f} - {1:.1f} GHz'.format(freqran[0], freqran[1]),
color='w',
transform=ax.transAxes,
fontweight='bold',
ha='right')
ax.set_title(' ')
#ax.text(0.01,0.02, plttime.isot,transform=ax.transAxes,color='white')
ax.set_xlabel('')
ax.set_ylabel('')
ax.set_xticklabels([''])
ax.set_yticklabels([''])
fig_tdt = plttime.to_datetime()
if synoptic:
fig_subdir = fig_tdt.strftime("%Y/")
figname = 'eovsa_qlimg_' + plttime.iso[:10].replace('-',
'') + '.png'
else:
fig_subdir = fig_tdt.strftime("%Y/%m/%d/")
figname = 'eovsa_qlimg_' + plttime.isot.replace(':', '').replace(
'-', '')[:15] + '.png'
figdir_ = figdir + fig_subdir
if not os.path.exists(figdir_):
os.makedirs(figdir_)
if verbose:
print 'Saving plot to :' + figdir_ + figname
plt.savefig(figdir_ + figname)
plt.close(fig)
def imreg(vis=None, ephem=None, msinfo=None, reftime=None, imagefile=None, fitsfile=None, beamfile=None, \
offsetfile=None, toTb=None, scl100=None, verbose=False, p_ang = False, overwrite = True, usephacenter=False):
ia = iatool()
if not imagefile:
raise ValueError, 'Please specify input image'
if not reftime:
raise ValueError, 'Please specify reference time corresponding to the input image'
if not fitsfile:
fitsfile = [img + '.fits' for img in imagefile]
if len(imagefile) != len(reftime):
raise ValueError, 'Number of input images does not equal to number of helio coord headers!'
if len(imagefile) != len(fitsfile):
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...'
helio = ephem_to_helio(vis,
ephem=ephem,
msinfo=msinfo,
reftime=reftime,
usephacenter=usephacenter)
for n, img in enumerate(imagefile):
if verbose:
print 'processing image #' + str(n)
fitsf = fitsfile[n]
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()
sum = ia.summary()
ia.close()
# construct the standard fits header
# RA and DEC of the reference pixel crpix1 and crpix2
(imra, imdec) = (sum['refval'][0], sum['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
hdu = pyfits.open(fitsf, mode='update')
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'] = hel['date-obs'] #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
header.update('exptime', hel['exptime'])
header.update('p_angle', hel['p0'])
header.update(
'dsun_obs',
sun.sunearth_distance(Time(hel['date-obs'])).to(u.meter).value)
header.update(
'rsun_obs',
sun.solar_semidiameter_angular_size(Time(
hel['date-obs'])).value)
header.update('rsun_ref', sun.constants.radius.value)
header.update('hgln_obs', 0.)
header.update(
'hglt_obs',
sun.heliographic_solar_center(Time(hel['date-obs']))[1].value)
except:
# this works for astropy.io.fits
header.append(('exptime', hel['exptime']))
header.append(('p_angle', hel['p0']))
header.append(
('dsun_obs', sun.sunearth_distance(Time(hel['date-obs'])).to(
u.meter).value))
header.append(('rsun_obs',
sun.solar_semidiameter_angular_size(
Time(hel['date-obs'])).value))
header.append(('rsun_ref', sun.constants.radius.value))
header.append(('hgln_obs', 0.))
header.append(('hglt_obs',
sun.heliographic_solar_center(Time(
hel['date-obs']))[1].value))
# header.update('comment', 'Fits header updated to heliocentric coordinates by Bin Chen')
# 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'
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
hdu.flush()
hdu.close()
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 plt_qlook_image(imres, figdir=None, specdata=None, verbose=True, stokes='I,V', fov=None):
from matplotlib import pyplot as plt
from sunpy import map as smap
from sunpy import sun
import astropy.units as u
if not figdir:
figdir = './'
observatory = 'EOVSA'
polmap = {'RR': 0, 'LL': 1, 'I': 0, 'V': 1}
pols = stokes.split(',')
npols = len(pols)
# SRL = set(['RR', 'LL'])
# SXY = set(['XX', 'YY', 'XY', 'YX'])
Spw = sorted(list(set(imres['Spw'])))
nspw = len(Spw)
# Freq = set(imres['Freq']) ## list is an unhashable type
Freq = sorted(uniq(imres['Freq']))
plttimes = list(set(imres['BeginTime']))
ntime = len(plttimes)
# sort the imres according to time
images = np.array(imres['ImageName'])
btimes = Time(imres['BeginTime'])
etimes = Time(imres['EndTime'])
spws = np.array(imres['Spw'])
suc = np.array(imres['Succeeded'])
inds = btimes.argsort()
images_sort = images[inds].reshape(ntime, nspw)
btimes_sort = btimes[inds].reshape(ntime, nspw)
suc_sort = suc[inds].reshape(ntime, nspw)
spws_sort = spws[inds].reshape(ntime, nspw)
if verbose:
print '{0:d} figures to plot'.format(ntime)
plt.ioff()
import matplotlib.gridspec as gridspec
spec = specdata['spec']
(npol, nbl, nfreq, ntim) = spec.shape
tidx = range(ntim)
fidx = range(nfreq)
tim = specdata['tim']
freq = specdata['freq']
freqghz = freq / 1e9
pol = ''.join(pols)
spec_tim = Time(specdata['tim'] / 3600. / 24., format='mjd')
timstrr = spec_tim.plot_date
if npols == 1:
if pol == 'RR':
spec_plt = spec[0, 0, :, :]
elif pol == 'LL':
spec_plt = spec[1, 0, :, :]
elif pol == 'I':
spec_plt = (spec[0, 0, :, :] + spec[1, 0, :, :]) / 2.
elif pol == 'V':
spec_plt = (spec[0, 0, :, :] - spec[1, 0, :, :]) / 2.
spec_plt = [spec_plt]
print 'plot the dynamic spectrum in pol ' + pol # ax1 = fig.add_subplot(211)
hnspw = nspw / 2
ncols = hnspw
nrows = 2 + 2 # 1 image: 1x1, 1 dspec:2x4
fig = plt.figure(figsize=(8, 8))
gs = gridspec.GridSpec(nrows, ncols)
axs = [plt.subplot(gs[0, 0])]
for ll in range(1, nspw):
axs.append(plt.subplot(gs[ll / hnspw, ll % hnspw], sharex=axs[0], sharey=axs[0]))
for ll in range(nspw):
axs.append(plt.subplot(gs[ll / hnspw + 2, ll % hnspw], sharex=axs[0], sharey=axs[0]))
axs_dspec = [plt.subplot(gs[2:, :])]
cmaps = ['jet']
elif npols == 2:
R_plot = np.absolute(spec[0, 0, :, :])
L_plot = np.absolute(spec[1, 0, :, :])
if pol == 'RRLL':
spec_plt = [R_plot, L_plot]
polstr = ['RR', 'LL']
cmaps = ['jet'] * 2
if pol == 'IV':
I_plot = (R_plot + L_plot) / 2.
V_plot = (R_plot - L_plot) / 2.
spec_plt = [I_plot, V_plot]
polstr = ['I', 'V']
cmaps = ['jet', 'RdBu']
print 'plot the dynamic spectrum in pol ' + pol
hnspw = nspw / 2
ncols = hnspw + 2 # 1 image: 1x1, 1 dspec:2x2
nrows = 2 + 2
fig = plt.figure(figsize=(12, 8))
gs = gridspec.GridSpec(nrows, ncols)
axs = [plt.subplot(gs[0, 0])]
for ll in range(1, nspw):
axs.append(plt.subplot(gs[ll / hnspw, ll % hnspw], sharex=axs[0], sharey=axs[0]))
for ll in range(nspw):
axs.append(plt.subplot(gs[ll / hnspw + 2, ll % hnspw], sharex=axs[0], sharey=axs[0]))
axs_dspec = [plt.subplot(gs[:2, hnspw:])]
axs_dspec.append(plt.subplot(gs[2:, hnspw:], sharex=axs_dspec[0], sharey=axs_dspec[0]))
fig.subplots_adjust(left=0, bottom=0, right=1, top=1, wspace=0, hspace=0)
timetext = fig.text(0.01, 0.98, '', color='w', fontweight='bold', fontsize=12, ha='left', va='top')
for i in range(ntime):
plt.ioff()
# plt.clf()
for ax in axs:
ax.cla()
plttime = btimes_sort[i, 0]
# tofd = plttime.mjd - np.fix(plttime.mjd)
suci = suc_sort[i]
# if tofd < 16. / 24. or sum(
# suci) < nspw - 2: # if time of the day is before 16 UT (and 24 UT), skip plotting (because the old antennas are not tracking)
# continue
# fig=plt.figure(figsize=(9,6))
# fig.suptitle('EOVSA @ '+plttime.iso[:19])
timetext.set_text(plttime.iso[:19])
if verbose:
print 'Plotting image at: ', plttime.iso
if i == 0:
dspecvspans = []
for pol in range(npols):
ax = axs_dspec[pol]
ax.pcolormesh(timstrr, freqghz, spec_plt[pol], cmap=cmaps[pol])
ax.xaxis_date()
ax.xaxis.set_major_formatter(DateFormatter("%H:%M:%S"))
# plt.xticks(rotation=45)
ax.set_xlim(timstrr[tidx[0]], timstrr[tidx[-1]])
ax.set_ylim(freqghz[fidx[0]], freqghz[fidx[-1]])
ax.set_xlabel('Time [UT]')
ax.set_ylabel('Frequency [GHz]')
for idx, freq in enumerate(Freq):
ax.axhspan(freq[0], freq[1], linestyle='dotted', edgecolor='w', alpha=0.7, facecolor='none')
xtext, ytext = ax.transAxes.inverted().transform(ax.transData.transform([timstrr[tidx[0]], np.mean(freq)]))
ax.text(xtext + 0.01, ytext, 'spw ' + Spw[idx], color='w', transform=ax.transAxes, fontweight='bold', ha='left', va='center',
fontsize=8, alpha=0.5)
ax.text(0.01, 0.98, 'Stokes ' + pols[pol], color='w', transform=ax.transAxes, fontweight='bold', ha='left', va='top')
dspecvspans.append(ax.axvspan(btimes[i].plot_date, etimes[i].plot_date, color='w', alpha=0.4))
ax_pos = ax.get_position().extents
x0, y0, x1, y1 = ax_pos
h, v = x1 - x0, y1 - y0
x0_new = x0 + 0.15 * h
y0_new = y0 + 0.15 * v
x1_new = x1 - 0.05 * h
y1_new = y1 - 0.05 * v
ax.set_position(mpl.transforms.Bbox([[x0_new, y0_new], [x1_new, y1_new]]))
else:
for pol in range(npols):
xy = dspecvspans[pol].get_xy()
xy[:, 0][np.array([0, 1, 4])] = btimes[i].plot_date
xy[:, 0][np.array([2, 3])] = etimes[i].plot_date
dspecvspans[pol].set_xy(xy)
for n in range(nspw):
image = images_sort[i, n]
# fig.add_subplot(nspw/3, 3, n+1)
# fig.add_subplot(2, nspw / 2, n + 1)
for pol in range(npols):
if suci[n]:
try:
eomap = smap.Map(image)
except:
continue
sz = eomap.data.shape
if len(sz) == 4:
eomap.data = eomap.data[min(polmap[pols[pol]], eomap.meta['naxis4'] - 1), 0, :, :].reshape((sz[2], sz[3]))
# resample the image for plotting
if fov is not None:
fov = [np.array(ll) for ll in fov]
pad = max(np.diff(fov[0])[0], np.diff(fov[1])[0])
eomap = eomap.submap((fov[0] + np.array([-1.0, 1.0]) * pad) * u.arcsec, (fov[1] + np.array([-1.0, 1.0]) * pad) * u.arcsec)
else:
dim = u.Quantity([256, 256], u.pixel)
eomap = eomap.resample(dim)
eomap.plot_settings['cmap'] = plt.get_cmap(cmaps[pol])
# import pdb
# pdb.set_trace()
eomap.plot(axes=axs[n + nspw * pol])
eomap.draw_limb()
eomap.draw_grid()
ax = plt.gca()
ax.set_autoscale_on(False)
if fov:
# pass
ax.set_xlim(fov[0])
ax.set_ylim(fov[1])
else:
ax.set_xlim([-1080, 1080])
ax.set_ylim([-1080, 1080])
spwran = spws_sort[i, n]
# freqran = [int(s) * 0.5 + 2.9 for s in spwran.split('~')]
# if len(freqran) == 1:
# ax.text(0.98, 0.01, '{0:.1f} GHz'.format(freqran[0]), color='w',
# transform=ax.transAxes, fontweight='bold', ha='right')
# else:
# ax.text(0.98, 0.01, '{0:.1f} - {1:.1f} GHz'.format(freqran[0], freqran[1]), color='w',
# transform=ax.transAxes, fontweight='bold', ha='right')
ax.text(0.98, 0.01, 'Stokes {1} @ {0:.3f} GHz'.format(eomap.meta['crval3'] / 1e9, pols[pol]), color='w', transform=ax.transAxes,
fontweight='bold', ha='right')
ax.set_title(' ')
# ax.set_title('spw '+spws_sort[i,n])
# ax.text(0.01,0.02, plttime.isot,transform=ax.transAxes,color='white')
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
else:
# make an empty map
data = np.zeros((512, 512))
header = {"DATE-OBS": plttime.isot, "EXPTIME": 0., "CDELT1": 5., "NAXIS1": 512, "CRVAL1": 0., "CRPIX1": 257, "CUNIT1": "arcsec",
"CTYPE1": "HPLN-TAN", "CDELT2": 5., "NAXIS2": 512, "CRVAL2": 0., "CRPIX2": 257, "CUNIT2": "arcsec",
"CTYPE2": "HPLT-TAN", "HGLT_OBS": sun.heliographic_solar_center(plttime)[1].value, "HGLN_OBS": 0.,
"RSUN_OBS": sun.solar_semidiameter_angular_size(plttime).value, "RSUN_REF": sun.constants.radius.value,
"DSUN_OBS": sun.sunearth_distance(plttime).to(u.meter).value, }
eomap = smap.Map(data, header)
# resample the image for plotting
if fov:
fov = [np.array(ll) for ll in fov]
pad = max(np.diff(fov[0])[0], np.diff(fov[1])[0])
try:
eomap = eomap.submap((fov[0] + np.array([-1.0, 1.0]) * pad) * u.arcsec, (fov[1] + np.array([-1.0, 1.0]) * pad) * u.arcsec)
except:
x0, x1 = fov[0] + np.array([-1.0, 1.0]) * pad
y0, y1 = fov[1] + np.array([-1.0, 1.0]) * pad
bl = SkyCoord(x0 * u.arcsec, y0 * u.arcsec, frame=eomap.coordinate_frame)
tr = SkyCoord(x1 * u.arcsec, y1 * u.arcsec, frame=eomap.coordinate_frame)
eomap = eomap.submap(bl, tr)
else:
dim = u.Quantity([256, 256], u.pixel)
eomap = eomap.resample(dim)
eomap.plot_settings['cmap'] = plt.get_cmap(cmaps[pol])
eomap.plot(axes=axs[n + nspw * pol])
eomap.draw_limb()
eomap.draw_grid()
ax = plt.gca()
ax.set_autoscale_on(False)
if fov:
# pass
ax.set_xlim(fov[0])
ax.set_ylim(fov[1])
else:
ax.set_xlim([-1080, 1080])
ax.set_ylim([-1080, 1080])
# ax.set_title('spw '+spwran+'( )'))
spwran = spws_sort[i, n]
freqran = [int(s) * 0.5 + 2.9 for s in spwran.split('~')]
spwran = spws_sort[i, n]
# ax.set_title('{0:.1f} - {1:.1f} GHz'.format(freqran[0],freqran[1]))
# ax.text(0.98, 0.01, '{0:.1f} - {1:.1f} GHz'.format(freqran[0], freqran[1]), color='w',
# transform=ax.transAxes, fontweight='bold', ha='right')
ax.text(0.98, 0.01, 'Stokes {1} @ {0:.3f} GHz'.format(0., pols[pol]), color='w', transform=ax.transAxes, fontweight='bold',
ha='right')
ax.set_title(' ')
# ax.text(0.01,0.02, plttime.isot,transform=ax.transAxes,color='white')
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
figname = observatory + '_qlimg_' + plttime.isot.replace(':', '').replace('-', '')[:19] + '.png'
fig_tdt = plttime.to_datetime()
# fig_subdir = fig_tdt.strftime("%Y/%m/%d/")
figdir_ = figdir # + fig_subdir
if not os.path.exists(figdir_):
os.makedirs(figdir_)
if verbose:
print 'Saving plot to: ' + os.path.join(figdir_, figname)
plt.savefig(os.path.join(figdir_, figname))
plt.close(fig)
DButil.img2html_movie(figdir_)
def plt_qlook_image(imres, figdir=None, verbose=True):
from matplotlib import pyplot as plt
from sunpy import map as smap
from sunpy import sun
import astropy.units as u
if not figdir:
figdir = './'
nspw = len(set(imres['Spw']))
plttimes = list(set(imres['BeginTime']))
ntime = len(plttimes)
# sort the imres according to time
images = np.array(imres['ImageName'])
btimes = Time(imres['BeginTime'])
etimes = Time(imres['EndTime'])
spws = np.array(imres['Spw'])
suc = np.array(imres['Succeeded'])
inds = btimes.argsort()
images_sort = images[inds].reshape(ntime, nspw)
btimes_sort = btimes[inds].reshape(ntime, nspw)
suc_sort = suc[inds].reshape(ntime, nspw)
spws_sort = spws[inds].reshape(ntime, nspw)
if verbose:
print '{0:d} figures to plot'.format(ntime)
for i in range(ntime):
#for i in range(1):
plt.ioff()
fig = plt.figure(figsize=(11, 6))
plttime = btimes_sort[i, 0]
fig.suptitle('EOVSA @ ' + plttime.iso[:19])
if verbose:
print 'Plotting image at: ', plttime.iso
suci = suc_sort[i]
for n in range(nspw):
plt.ioff()
image = images_sort[i, n]
fig.add_subplot(nspw / 3, 3, n + 1)
if suci[n]:
try:
eomap = smap.Map(image)
except:
continue
sz = eomap.data.shape
if len(sz) == 4:
eomap.data = eomap.data.reshape((sz[2], sz[3]))
eomap.plot_settings['cmap'] = plt.get_cmap('jet')
eomap.plot()
eomap.draw_limb()
eomap.draw_grid()
ax = plt.gca()
ax.set_xlim([-1050, 1050])
ax.set_ylim([-1050, 1050])
ax.set_title('spw ' + spws_sort[i, n])
#ax.text(0.01,0.02, plttime.isot,transform=ax.transAxes,color='white')
if n != nspw - 3:
ax.set_xlabel('')
ax.set_ylabel('')
ax.set_xticklabels([''])
ax.set_yticklabels([''])
else:
#make an empty map
data = np.zeros((512, 512))
header = {
"DATE-OBS": plttime.isot,
"EXPTIME": 0.,
"CDELT1": 5.,
"NAXIS1": 512,
"CRVAL1": 0.,
"CRPIX1": 257,
"CUNIT1": "arcsec",
"CTYPE1": "HPLN-TAN",
"CDELT2": 5.,
"NAXIS2": 512,
"CRVAL2": 0.,
"CRPIX2": 257,
"CUNIT2": "arcsec",
"CTYPE2": "HPLT-TAN",
"HGLT_OBS":
sun.heliographic_solar_center(plttime)[1].value,
"HGLN_OBS": 0.,
"RSUN_OBS":
sun.solar_semidiameter_angular_size(plttime).value,
"RSUN_REF": sun.constants.radius.value,
"DSUN_OBS":
sun.sunearth_distance(plttime).to(u.meter).value,
}
eomap = smap.Map(data, header)
eomap.plot_settings['cmap'] = plt.get_cmap('jet')
eomap.plot()
eomap.draw_limb()
eomap.draw_grid()
ax = plt.gca()
ax.set_xlim([-1050, 1050])
ax.set_ylim([-1050, 1050])
ax.set_title('spw ' + spws_sort[i, n])
#ax.text(0.01,0.02, plttime.isot,transform=ax.transAxes,color='white')
if n != 6:
ax.set_xlabel('')
ax.set_ylabel('')
ax.set_xticklabels([''])
ax.set_yticklabels([''])
figname = 'eovsa_qlimg_' + plttime.isot.replace(':', '').replace(
'-', '')[:15] + '.png'
fig_tdt = plttime.to_datetime()
fig_subdir = fig_tdt.strftime("%Y/%m/%d/")
figdir_ = figdir + fig_subdir
if not os.path.exists(figdir_):
os.makedirs(figdir_)
if verbose:
print 'Saving plot to :' + figdir_ + figname
plt.savefig(figdir_ + figname)
plt.close(fig)