def plt_eovsa_image(eofiles, figoutdir='./'):
import matplotlib.pyplot as plt
import matplotlib.colors as colors
from astropy.visualization.stretch import AsinhStretch, LinearStretch, SqrtStretch
from astropy.visualization import ImageNormalize
from suncasa.utils import plot_mapX as pmX
from sunpy import map as smap
import astropy.units as u
from mpl_toolkits.axes_grid1 import make_axes_locatable
import matplotlib.colorbar as colorbar
# It is expected that nfiles will be either 4 (for older 34-band data) or 6 (for newer 52-band data)
nfiles = len(eofiles)
plt.ioff()
fig = plt.figure(figsize=(5 * nfiles // 2, 9))
axs = []
cmap = 'gist_heat'
for idx, eofile in enumerate(eofiles):
ax = fig.add_subplot(2, nfiles // 2, idx + 1)
axs.append(ax)
# ax = axs[idx]
eomap = smap.Map(eofile)
tb_disk = eomap.meta['TBDISK']
vmaxs = [70.0e4, 30e4, 18e4, 13e4, 8e4, 6e4]
vmins = [-18.0e3, -8e3, -4.8e3, -3.4e3, -2.1e3, -1.6e3]
# norm = colors.Normalize(vmin=vmins[idx], vmax=vmaxs[idx])
stretch = AsinhStretch(a=0.15)
norm = ImageNormalize(vmin=vmins[idx], vmax=vmaxs[idx], stretch=stretch)
# norm = colors.Normalize(vmin=tb_disk * (-0.2), vmax=0.5*np.nanmax(eomap.data))
eomap_ = pmX.Sunmap(eomap)
eomap_.imshow(axes=ax, cmap=cmap, norm=norm)
eomap_.draw_limb(axes=ax, lw=0.5, alpha=0.5)
eomap_.draw_grid(axes=ax, grid_spacing=10. * u.deg, lw=0.5)
divider = make_axes_locatable(ax)
cax = divider.append_axes('right', size='2.0%', pad=0.08)
cax.tick_params(direction='in')
clb = colorbar.ColorbarBase(cax, cmap=cmap, norm=norm)
clb.set_label(r'T$_b$ [$\times$10$^3$K]')
if idx != nfiles / 2:
ax.set_xlabel('')
ax.set_ylabel('')
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.tick_params(direction="out")
ax.text(0.02, 0.98,
'EOVSA {:.1f} GHz {}'.format(eomap.meta['CRVAL3'] / 1e9, eomap.date.strftime('%d-%b-%Y 20:00 UT')),
transform=ax.transAxes, color='w', ha='left', va='top', fontsize=8, fontweight='bold')
ax.text(0.02, 0.02, 'Max Tb {:.0f} K'.format(np.nanmax(eomap.data)),
transform=ax.transAxes, color='w', ha='left', va='bottom', fontsize=8, fontweight='bold')
ax.set_xlim(-1200, 1200)
ax.set_ylim(-1200, 1200)
fig.tight_layout()
figname = os.path.join(figoutdir, 'eovsa_qlimg_{}.png'.format(eomap.date.strftime('%Y%m%d')))
fig.savefig(figname, dpi=150)
plt.close(fig)
plt.ion()
return figname
def pltEovsaQlookImage(timobj, spws, vmaxs, vmins, dpis_dict, fig=None, ax=None, overwrite=False, verbose=False):
plt.ioff()
dateobj = timobj.to_datetime()
datestrdir = dateobj.strftime("%Y/%m/%d/")
imgindir = imgfitsdir + datestrdir
# if not os.path.exists(imgindir):
# os.makedirs(imgindir)
cmap = cm_smap.get_cmap('sdoaia304')
if fig is None or ax is None:
mkfig = True
else:
mkfig = False
if mkfig:
fig, ax = plt.subplots(figsize=(8, 8))
fig.subplots_adjust(bottom=0.0, top=1.0, left=0.0, right=1.0)
if verbose: print('Processing EOVSA images for date {}'.format(dateobj.strftime('%Y-%m-%d')))
for s, sp in enumerate(spws):
fexists = []
for l, dpi in dpis_dict.items():
figname = os.path.join(movieoutdir, '{}_eovsa_bd{:02d}.jpg'.format(l, s + 1))
fexists.append(os.path.exists(figname))
if overwrite or (False in fexists):
ax.cla()
spwstr = '-'.join(['{:02d}'.format(int(sp_)) for sp_ in sp.split('~')])
eofile = imgindir + 'eovsa_{}.spw{}.tb.disk.fits'.format(dateobj.strftime('%Y%m%d'), spwstr)
if not os.path.exists(eofile): continue
if not os.path.exists(movieoutdir): os.makedirs(movieoutdir)
eomap = smap.Map(eofile)
norm = colors.Normalize(vmin=vmins[s], vmax=vmaxs[s])
eomap_ = pmX.Sunmap(eomap)
eomap_.imshow(axes=ax, cmap=cmap, norm=norm)
eomap_.draw_limb(axes=ax, lw=0.5, alpha=0.5)
eomap_.draw_grid(axes=ax, grid_spacing=10. * u.deg, lw=0.5)
ax.set_xlabel('')
ax.set_ylabel('')
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.text(0.02, 0.02,
'EOVSA {:.1f} GHz {}'.format(eomap.meta['CRVAL3'] / 1e9, eomap.date.strftime('%d-%b-%Y 20:00 UT')),
transform=ax.transAxes, color='w', ha='left', va='bottom', fontsize=9)
ax.text(0.98, 0.02, 'Max Tb {:.0f} K'.format(np.nanmax(eomap.data)),
transform=ax.transAxes, color='w', ha='right', va='bottom', fontsize=9)
ax.set_xlim(-1227, 1227)
ax.set_ylim(-1227, 1227)
for l, dpi in dpis_dict.items():
figname = os.path.join(movieoutdir, '{}_eovsa_bd{:02d}.jpg'.format(l, s + 1))
fig.savefig(figname, dpi=np.int(dpi), quality=85)
if mkfig:
pass
else:
plt.close(fig)
return
def pltEmptyImage(datestr, spws, vmaxs, vmins, dpis_dict={'t': 32.0}):
plt.ioff()
dateobj = datetime.strptime(datestr, "%Y-%m-%d")
datastrdir = dateobj.strftime("%Y/%m/%d/")
imgindir = imgfitsdir + datastrdir
imgoutdir = './nodata/'
cmap = cm.get_cmap('sdoaia304')
fig, ax = plt.subplots(figsize=(8, 8))
fig.subplots_adjust(bottom=0.0, top=1.0, left=0.0, right=1.0)
rect = patches.Rectangle((-1227, -300),
1227 * 2,
300 * 2,
linewidth=0,
edgecolor='none',
facecolor='k',
alpha=0.5)
for s, sp in enumerate(spws):
ax.cla()
spwstr = '-'.join(['{:02d}'.format(int(sp_)) for sp_ in sp.split('~')])
eofile = imgindir + 'eovsa_{}.spw{}.tb.disk.fits'.format(
dateobj.strftime('%Y%m%d'), spwstr)
if not os.path.exists(eofile): continue
if not os.path.exists(imgoutdir): os.makedirs(imgoutdir)
eomap = smap.Map(eofile)
norm = colors.Normalize(vmin=vmins[s], vmax=vmaxs[s])
eomap_ = pmX.Sunmap(eomap)
eomap_.imshow(axes=ax, cmap=cmap, norm=norm, alpha=0.75)
eomap_.draw_limb(axes=ax, lw=0.5, alpha=0.5)
eomap_.draw_grid(axes=ax, grid_spacing=10. * u.deg, lw=0.5)
ax.set_xlabel('')
ax.set_ylabel('')
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.text(0.5,
0.5,
'No Data',
transform=ax.transAxes,
color='w',
ha='center',
va='center',
fontsize=120)
ax.add_patch(rect)
ax.set_xlim(-1227, 1227)
ax.set_ylim(-1227, 1227)
for l, dpi in dpis_dict.items():
figname = os.path.join(imgoutdir,
'{}_eovsa_bd{:02d}.jpg'.format(l, s + 1))
fig.savefig(figname, dpi=np.int(dpi), quality=85)
return
def pltBbsoQlookImage(datestr, dpis_dict, fig=None, ax=None, overwrite=False, verbose=False, clearcache=False):
from astropy.io import fits
from html.parser import HTMLParser
class MyHTMLParser(HTMLParser):
def __init__(self, prefix='bbso_halph_fr_', suffix='.fts'):
HTMLParser.__init__(self)
self.prefix = prefix
self.suffix = suffix
def handle_starttag(self, tag, attrs):
if tag != 'a':
return
for name, value in attrs:
if name == "href":
if value.startswith(self.prefix) and value.endswith(self.suffix):
self.links.append(value)
def extract(url, prefix='bbso_halph_fr_', suffix='.fts'):
import urllib.request
with urllib.request.urlopen(url) as response:
f = response.read()
parser = MyHTMLParser(prefix, suffix)
parser.links = []
parser.feed(str(f))
return parser.links
bbsodir = 'http://www.bbso.njit.edu/pub/archive/'
plt.ioff()
dateobj = datetime.strptime(datestr, "%Y-%m-%d")
datestrdir = dateobj.strftime("%Y/%m/%d/")
imgindir = os.path.join(imgfitstmpdir, datestr)
imgoutdir = pltfigdir + datestrdir
if not os.path.exists(imgindir):
os.makedirs(imgindir)
bbsoDataSource = {"_Halph_fr": ["bbso_halph_fr_", ".fts"]}
if fig is None or ax is None:
mkfig = True
else:
mkfig = False
if mkfig:
fig, ax = plt.subplots(figsize=(8, 8))
fig.subplots_adjust(bottom=0.0, top=1.0, left=0.0, right=1.0)
if verbose: print('Processing BBSO images for date {}'.format(dateobj.strftime('%Y-%m-%d')))
for key, sourceid in bbsoDataSource.items():
fexists = []
for l, dpi in dpis_dict.items():
figname = os.path.join(imgoutdir, '{}{}.jpg'.format(l, key))
fexists.append(os.path.exists(figname))
if overwrite or (False in fexists):
bbsosite = os.path.join(bbsodir, datestrdir)
filelist = extract(bbsosite, sourceid[0], sourceid[1])
if filelist:
tfilelist = Time(
[datetime.strptime(tf.replace(sourceid[0], '').replace(sourceid[1], ''), "%Y%m%d_%H%M%S") for tf in
filelist])
bbsourl = os.path.join(bbsosite, filelist[
np.nanargmin(np.abs(np.array(tfilelist.mjd - (Time(dateobj).mjd + 20. / 24.))))])
bbsofile = os.path.join(imgindir, key + '.fits')
if not os.path.exists(bbsofile):
try:
urllib.request.urlretrieve(bbsourl, bbsofile)
except:
print('The connection with {} has timed out. Skipped!'.format(bbsourl))
ax.cla()
if not os.path.exists(bbsofile): continue
if not os.path.exists(imgoutdir): os.makedirs(imgoutdir)
try:
hdu = fits.open(bbsofile)[0]
header = hdu.header
header['WAVELNTH'] = 6562.8
header['WAVEUNIT'] = 'angstrom'
header['WAVE_STR'] = 'Halph'
header['CTYPE1'] = 'HPLN-TAN'
header['CUNIT1'] = 'arcsec'
header['CTYPE2'] = 'HPLT-TAN'
header['CUNIT2'] = 'arcsec'
header['DATE-OBS'] = header['DATE_OBS']
for k in ['CONTRAST', 'WAVE ERR']:
try:
header.remove(k)
except:
pass
bbsomap = smap.Map(hdu.data, header)
med = np.nanmean(bbsomap.data)
norm = colors.Normalize(vmin=med - 1500, vmax=med + 1500)
bbsomap_ = pmX.Sunmap(bbsomap)
cmap = cm_smap.get_cmap('sdoaia304')
bbsomap_.imshow(axes=ax, cmap=cmap, norm=norm)
bbsomap_.draw_limb(axes=ax, lw=0.5, alpha=0.5)
bbsomap_.draw_grid(axes=ax, grid_spacing=10. * u.deg, lw=0.5)
ax.set_xlabel('')
ax.set_ylabel('')
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.text(0.02, 0.02,
'{} {}'.format(bbsomap.instrument, bbsomap.date.strftime('%d-%b-%Y %H:%M UT')),
transform=ax.transAxes, color='w', ha='left', va='bottom', fontsize=9)
ax.set_xlim(-1227, 1227)
ax.set_ylim(-1227, 1227)
ax.set_facecolor('k')
for l, dpi in dpis_dict.items():
figname = os.path.join(imgoutdir, '{}{}.jpg'.format(l, key))
fig.savefig(figname, dpi=np.int(dpi), quality=85)
except Exception as err:
print('Fail to plot {}'.format(bbsofile))
print(err)
if clearcache:
os.system('rm -rf ' + imgindir)
if mkfig:
pass
else:
plt.close(fig)
return
def pltSdoQlookImage(datestr, dpis_dict, fig=None, ax=None, overwrite=False, verbose=False, clearcache=False):
plt.ioff()
dateobj = datetime.strptime(datestr, "%Y-%m-%d")
datestrdir = dateobj.strftime("%Y/%m/%d/")
imgindir = os.path.join(imgfitstmpdir, datestr)
imgoutdir = pltfigdir + datestrdir
if not os.path.exists(imgindir):
os.makedirs(imgindir)
aiaDataSource = {"0094": 8,
"0193": 11,
"0335": 14,
# "4500": 17,
"0171": 10,
"0304": 13,
"0131": 9,
"1700": 16,
"0211": 12,
# "1600": 15,
"_HMIcont": 18,
"_HMImag": 19}
if fig is None or ax is None:
mkfig = True
else:
mkfig = False
if mkfig:
fig, ax = plt.subplots(figsize=(8, 8))
fig.subplots_adjust(bottom=0.0, top=1.0, left=0.0, right=1.0)
if verbose: print('Processing SDO images for date {}'.format(dateobj.strftime('%Y-%m-%d')))
for key, sourceid in aiaDataSource.items():
fexists = []
for l, dpi in dpis_dict.items():
figname = os.path.join(imgoutdir, '{}{}.jpg'.format(l, key))
fexists.append(os.path.exists(figname))
if overwrite or (False in fexists):
sdourl = 'https://api.helioviewer.org/v2/getJP2Image/?date={}T20:00:00Z&sourceId={}'.format(datestr,
sourceid)
sdofile = os.path.join(imgindir, key + '.jp2')
if overwrite and os.path.exists(sdofile):
os.system('rm -rf {}'.format(sdofile))
if not os.path.exists(sdofile):
try:
urllib.request.urlretrieve(sdourl, sdofile)
except:
print('The connection with {} has timed out. Skipped!'.format(sdourl))
ax.cla()
if not os.path.exists(sdofile): continue
if not os.path.exists(imgoutdir): os.makedirs(imgoutdir)
try:
sdomap = smap.Map(sdofile)
norm = colors.Normalize()
sdomap_ = pmX.Sunmap(sdomap)
if "HMI" in key:
cmap = plt.get_cmap('gray')
else:
cmap = cm_smap.get_cmap('sdoaia' + key.lstrip('0'))
sdomap_.imshow(axes=ax, cmap=cmap, norm=norm)
sdomap_.draw_limb(axes=ax, lw=0.5, alpha=0.5)
sdomap_.draw_grid(axes=ax, grid_spacing=10. * u.deg, lw=0.5)
ax.set_xlabel('')
ax.set_ylabel('')
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.text(0.02, 0.02,
'{}/{} {} {}'.format(sdomap.observatory, sdomap.instrument.split(' ')[0], sdomap.measurement,
sdomap.date.strftime('%d-%b-%Y %H:%M UT')),
transform=ax.transAxes, color='w', ha='left', va='bottom', fontsize=9)
ax.set_xlim(-1227, 1227)
ax.set_ylim(-1227, 1227)
for l, dpi in dpis_dict.items():
figname = os.path.join(imgoutdir, '{}{}.jpg'.format(l, key))
fig.savefig(figname, dpi=np.int(dpi), quality=85)
except Exception as err:
print('Fail to plot {}'.format(sdofile))
print(err)
if clearcache:
os.system('rm -rf ' + imgindir)
if mkfig:
pass
else:
plt.close(fig)
return
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)
plt_ax = True
for tidx in tqdm(range(len(imres['ImageName']))):
fsfile = imres['ImageName'][tidx]
if os.path.exists(fsfile):
hdu = fits.open(fsfile)
else:
data = np.zeros(imsize)
for s, sp in enumerate(spws):
cfreq = imres['FreqGHz'][s]
ax = axs[s]
if os.path.exists(fsfile):
data = hdu[0].data[0, s, :, :].reshape(imsize)
data[np.isnan(data)] = 0.0
eomap = smap.Map(data, hdu[0].header)
if tidx == 0 or plt_ax:
eomap_ = pmX.Sunmap(eomap)
im.append(
eomap_.imshow(axes=ax, vmax=dmaxs[s],
vmin=dmaxs[s] * 0.05))
eomap_.draw_limb(axes=ax)
eomap_.draw_grid(axes=ax, grid_spacing=grid_spacing)
else:
im[s].set_array(data)
if tidx == 0:
ax.text(0.95,
0.95,
'{0:.1f} GHz'.format(cfreq),
transform=ax.transAxes,
ha='right',
va='top',
color='w',
def image_adddisk(eofile, diskinfo, edgeconvmode='frommergeddisk', caltbonly=False):
'''
:param eofile:
:param diskxmlfile:
:param edgeconvmode: available mode: frommergeddisk,frombeam
:return:
'''
from sunpy import map as smap
from suncasa.utils import plot_mapX as pmX
from scipy import constants
import astropy.units as u
from sunpy import io as sio
dsize = diskinfo['disk_size']
fdens = diskinfo['flux_dens']
freqs = diskinfo['freq']
eomap = smap.Map(eofile)
eomap_ = pmX.Sunmap(eomap)
header = eomap.meta
bmaj = header['bmaj'] * 3600 * u.arcsec
bmin = header['bmin'] * 3600 * u.arcsec
cell = (header['cdelt1'] * u.Unit(header['cunit1']) + header['cdelt2'] * u.Unit(header['cunit2'])) / 2.0
bmsize = (bmaj + bmin) / 2.0
data = eomap.data # remember the data order is reversed due to the FITS convension
keys = header.keys()
values = header.values()
mapx, mapy = eomap_.map2wcsgrids(cell=False)
mapx = mapx[:-1, :-1]
mapy = mapy[:-1, :-1]
rdisk = np.sqrt(mapx ** 2 + mapy ** 2)
k_b = constants.k
c_l = constants.c
const = 2. * k_b / c_l ** 2
pix_area = (cell.to(u.rad).value) ** 2
jy_to_si = 1e-26
factor2 = 1.
faxis = keys[values.index('FREQ')][-1]
if caltbonly:
edgeconvmode = ''
if edgeconvmode == 'frommergeddisk':
nul = header['CRVAL' + faxis] + header['CDELT' + faxis] * (1 - header['CRPIX' + faxis])
nuh = header['CRVAL' + faxis] + header['CDELT' + faxis] * (header['NAXIS' + faxis] - header['CRPIX' + faxis])
## get the frequency range of the image
nu_bound = (np.array([nul, nuh]) + 0.5 * np.array([-1, 1]) * header['CDELT' + faxis]) * u.Unit(
header['cunit' + faxis])
nu_bound = nu_bound.to(u.GHz)
## get the frequencies of the disk models
fidxs = np.logical_and(freqs > nu_bound[0], freqs < nu_bound[1])
ny, nx = rdisk.shape
freqs_ = freqs[fidxs]
fdens_ = fdens[fidxs] / 2.0 # divide by 2 because fdens is 2x solar flux density
dsize_ = dsize[fidxs]
fdisk_ = np.empty((len(freqs_), ny, nx))
fdisk_[:] = np.nan
for fidx, freq in enumerate(freqs_):
fdisk_[fidx, ...][rdisk <= dsize_[fidx].value] = 1.0
# nu = header['CRVAL' + faxis] + header['CDELT' + faxis] * (1 - header['CRPIX' + faxis])
factor = const * freq.to(u.Hz).value ** 2 # SI unit
jy2tb = jy_to_si / pix_area / factor * factor2
fdisk_[fidx, ...] = fdisk_[fidx, ...] / np.nansum(fdisk_[fidx, ...]) * fdens_[fidx].value
fdisk_[fidx, ...] = fdisk_[fidx, ...] * jy2tb
# # fdisk_[np.isnan(fdisk_)] = 0.0
tbdisk = np.nanmean(fdisk_, axis=0)
tbdisk[np.isnan(tbdisk)] = 0.0
sig2fwhm = 2.0 * np.sqrt(2 * np.log(2))
x0, y0 = 0, 0
sigx, sigy = bmaj.value / sig2fwhm, bmin.value / sig2fwhm
theta = -(90.0 - header['bpa']) * u.deg
x = (np.arange(31) - 15) * cell.value
y = (np.arange(31) - 15) * cell.value
x, y = np.meshgrid(x, y)
kernel = gaussian2d(x, y, 1.0, x0, y0, sigx, sigy, theta.to(u.radian).value)
kernel = kernel / np.nansum(kernel)
from scipy import signal
tbdisk = signal.fftconvolve(tbdisk, kernel, mode='same')
else:
nu = header['CRVAL' + faxis] + header['CDELT' + faxis] * (1 - header['CRPIX' + faxis])
freqghz = nu / 1.0e9
factor = const * nu ** 2 # SI unit
jy2tb = jy_to_si / pix_area / factor * factor2
p_dsize = np.poly1d(np.polyfit(freqs.value, dsize.value, 15))
p_fdens = np.poly1d(
np.polyfit(freqs.value, fdens.value, 15)) / 2. # divide by 2 because fdens is 2x solar flux density
if edgeconvmode == 'frombeam':
from scipy.special import erfc
factor_erfc = 2.0 ## erfc function ranges from 0 to 2
fdisk = erfc((rdisk - p_dsize(freqghz)) / bmsize.value) / factor_erfc
else:
fdisk = np.zeros_like(rdisk)
fdisk[rdisk <= p_dsize(freqghz)] = 1.0
fdisk = fdisk / np.nansum(fdisk) * p_fdens(freqghz)
tbdisk = fdisk * jy2tb
tb_disk = np.nanmax(tbdisk)
if caltbonly:
return tb_disk
else:
datanew = data + tbdisk
# datanew[np.isnan(data)] = 0.0
header['TBDISK'] = tb_disk
header['TBUNIT'] = 'K'
eomap_disk = smap.Map(datanew, header)
nametmp = eofile.split('.')
nametmp.insert(-1, 'disk')
outfits = '.'.join(nametmp)
datanew = datanew.astype(np.float32)
if os.path.exists(outfits):
os.system('rm -rf {}'.format(outfits))
sio.write_file(outfits, datanew, header)
return eomap_disk, tb_disk, outfits