def stats(imagefile, regionfile):
stats1 = cts.imstat(imagefile, stokes='I')
peakflux = stats1['max'][0]
stats2 = cts.imstat(imagefile, region=regionfile)
rms = stats2['rms'][0]
return rms, peakflux
def checkResidualMaskStats(imagename, outfile='test.csv'):
'''
Purpose: go through each mask and residual image for each major
cycle, calculate the peak residual, and
imagename: root image name
'''
f = open(outfile, 'w')
imageList = glob.glob("*inputres*")
f.write('cycle, imagename, mask, max\n')
for image in imageList:
cycle = int(re.search('inputres(.*)', image).group(1))
mask = image.replace('inputres', 'autothresh')
stats = imstat(imagename=image, mask=mask)
maxresid = max(stats['max'][0], abs(stats['min'])[0])
f.write("{:d}, {:s}, {:s}, {:f}\n".format(cycle, image, mask,
maxresid))
f.close()
def calcResRMS(resname=''):
istat = imstat(resname,axes=[0,1,2]) ### Make this calc within the PB.
rres = istat['rms'] ### for all channels. For first, pick [0]
print("RMS spectrum : "+str(rres))
return rres
def estimate_SNR(imagename, disk_mask, noise_mask, chans=None):
"""
Estimate peak SNR of source
Args:
imagename (string): Image name ending in '.image'
disk_mask: in the CASA region format
noise_mask (string): Annulus to measure image rms, in the CASA region
format, e.g. 'annulus[[500pix, 500pix],["1arcsec", "2arcsec"]]'
"""
headerlist = casatasks.imhead(imagename, mode="list")
beammajor = headerlist["beammajor"]["value"]
beamminor = headerlist["beamminor"]["value"]
beampa = headerlist["beampa"]["value"]
print("# %s" % imagename)
print("# Beam %.3f arcsec x %.3f arcsec (%.2f deg)" %
(beammajor, beamminor, beampa))
if chans is not None:
disk_stats = casatasks.imstat(imagename=imagename,
region=disk_mask,
chans=chans)
else:
disk_stats = casatasks.imstat(imagename=imagename, region=disk_mask)
disk_flux = disk_stats["flux"][0]
print("# Flux inside disk mask: %.3f mJy" % (disk_flux * 1000, ))
peak_intensity = disk_stats["max"][0]
print("# Peak intensity of source: %.3f mJy/beam" %
(peak_intensity * 1000, ))
# print("npoints", disk_stats["npts"])
# print("sum", disk_stats["sum"])
# print("mean", disk_stats["mean"])
# print("sigma", disk_stats["sigma"])
if chans is not None:
rms = casatasks.imstat(imagename=imagename,
region=noise_mask,
chans=chans)["rms"][0]
else:
rms = casatasks.imstat(imagename=imagename,
region=noise_mask)["rms"][0]
print("# rms: %.3e mJy/beam" % (rms * 1000, ))
SNR = peak_intensity / rms
print("# Peak SNR: %.3f" % (SNR, ))
print()
def calcDiffImage(baseImage, testImage, diffImage='test.diff'):
'''
calculate the image difference in two different primary beam ranges.
Date Programmer Changes
----------------------------------------------------------------------
2/22/2020 A.A. Kepley Original Code
'''
import analyzemsimage as ami
if not os.path.exists(diffImage):
# using statistics across cube rather than per channel
stats = imstat(baseImage)
sncut = 7.0 * stats[
'medabsdevmed'] * 1.4286 # 7 sigma. could probably change to lower
immath(
imagename=[baseImage, testImage],
mode='evalexpr',
expr='100*(IM1-IM0)/IM0',
outfile=diffImage, ## shold I flip this for consistency with sims?
mask='\"' + baseImage + '\" >' + str(sncut[0]) + ' && \"' +
testImage + '\" >' + str(sncut[0]))
pbImage = baseImage.replace('.image', '.pb')
if os.path.exists(pbImage):
statspdiff = ami.runImstat(Image=diffImage,
PB=pbImage,
innerAnnulusLevel=1.0,
level=0.5)
outstatspdiff = ami.runImstat(Image=diffImage,
PB=pbImage,
innerAnnulusLevel=0.5,
level=0.2)
else:
print("PB not found. Not calculating stats.")
statspdiff = None
outstatspdiff = None
return statspdiff, outstatspdiff
def get_rms(dirty_image_path, mask_path):
# Estimate the RMS of the un-masked pixels of the dirty image
rms = casatasks.imstat(imagename=dirty_image_path,
mask='"{}" < 1.0'.format(mask_path))["rms"][0]
return rms
def display_image_interact(imprefix=''):
ia.open(imprefix + '.image')
shp = ia.shape()
impix = ia.getchunk()
ia.close()
ia.open(imprefix + '.pb')
shp = ia.shape()
impb = ia.getchunk()
ia.close()
ploc = np.where(impix == impix.max())
imspec = impix[ploc[0][0], ploc[1][0], 0, :]
pbspec = impb[ploc[0][0], ploc[1][0], 0, :]
istat = imstat(imprefix + '.residual')
print('Residual RMS : %3.7f' % (istat['rms']))
pow_slider = widgets.FloatSlider(
value=1.0,
min=0.1,
max=2.0,
step=0.05,
description='Power Scale:',
disabled=False,
continuous_update=False,
orientation='horizontal',
readout=True,
readout_format='.1f',
)
ran_slider = widgets.FloatRangeSlider(
value=[-0.1, 2.0],
min=-0.1,
max=1.0,
step=0.01,
description='Min-Max:',
disabled=False,
continuous_update=False,
orientation='horizontal',
readout=True,
readout_format='.1f',
)
yran_slider = widgets.FloatRangeSlider(
value=[0.6, 1.1],
min=0.0,
max=1.5,
step=0.01,
description='yMin-yMax:',
disabled=False,
continuous_update=False,
orientation='horizontal',
readout=True,
readout_format='.1f',
)
interact(arrplot,
iarr=fixed(impix[:, :, 0, 0].transpose()),
pow=pow_slider,
vran=ran_slider,
pb=fixed(impb[:, :, 0, 0].transpose()),
imspec=fixed(imspec),
pbspec=fixed(pbspec),
yran=yran_slider)
def displayImage(imname='try_ALMA_A_single.image', pbname='', resname=''):
ia.open(imname)
shp = ia.shape()
csys = ia.coordsys()
impix = ia.getchunk()
ia.close()
if pbname != '':
ia.open(pbname)
impb = ia.getchunk()
ia.close()
rad_to_deg = 180 / np.pi
w = WCS(naxis=2)
w.wcs.crpix = csys.referencepixel()['numeric'][0:2]
w.wcs.cdelt = csys.increment()['numeric'][0:2] * rad_to_deg
w.wcs.crval = csys.referencevalue()['numeric'][0:2] * rad_to_deg
w.wcs.ctype = ['RA---SIN', 'DEC--SIN']
#w.wcs.ctype = ['RA','DEC']
pl.figure(figsize=(12, 5))
pl.clf()
pl.subplot(121, projection=w)
p1 = int(shp[0] * 0.25)
p2 = int(shp[0] * 0.75)
pl.imshow(impix[p1:p2, p1:p2, 0, 0].transpose(), origin='lower')
if pbname != '':
pl.contour(impb[p1:p2, p1:p2, 0, 0].transpose(), [0.5],
colors=['magenta'],
origin='lower')
pl.title('Image from channel 0')
pl.xlabel('Right Ascension')
pl.ylabel('Declination')
pk = 0.0
if shp[3] > 1:
pl.subplot(122)
ploc = np.where(impix == impix.max())
pl.plot(impix[ploc[0][0], ploc[1][0], 0, :], 'bo-', label='Im')
if pbname != '':
pl.plot(impb[ploc[0][0], ploc[1][0], 0, :], 'ro-', label='PB')
pl.title('Spectrum at source peak')
pl.xlabel('Channel')
pl.ylim((0.4, 1.1))
pl.legend()
pk = impix[ploc[0][0], ploc[1][0], 0, 0]
print('Peak Intensity (chan0) : %3.7f' % (pk))
if pbname != '':
pbk = impb[ploc[0][0], ploc[1][0], 0, 0]
print('PB at location of Intensity peak (chan0) : %3.7f' % (pbk))
else:
ploc = np.where(impix == impix.max())
print("Image Peak : %3.4f" % (impix[ploc[0][0], ploc[1][0], 0, 0]))
if pbname != '':
print("PB Value : %3.4f" % (impb[ploc[0][0], ploc[1][0], 0, 0]))
pk = impix[ploc[0][0], ploc[1][0], 0, 0]
if resname != '':
istat = imstat(resname) ### Make this calc within the PB.
rres = istat['rms'][0]
print('Residual RMS : %3.7f' % (rres))
else:
rres = None
return pk, rres # Return peak intensity from channnel 0 and rms
def get_selfcal_args(vis, loop, nloops, nterms, deconvolver, discard_nloops,
calmode, outlier_threshold, threshold, step):
visbase = os.path.split(
vis.rstrip('/ '))[1] # Get only vis name, not entire path
#Assume first target will be in the visname later (relevant for writing outliers.txt at beginning of pipeline)
if '.ms' in visbase:
from casatools import msmetadata
msmd = msmetadata()
msmd.open(vis)
basename = visbase.replace(
'.ms', '.{0}'.format(
msmd.namesforfields(msmd.fieldsforintent('TARGET'))[0]))
msmd.done()
else:
basename = visbase.replace('.mms', '')
imbase = basename + '_im_%d' # Images will be produced in $CWD
imagename = imbase % loop
outimage = imagename + '.image'
pixmask = imagename + ".pixmask"
maskfile = imagename + ".islmask"
rmsfile = imagename + ".rms"
caltable = basename + '.gcal%d' % loop
prev_caltables = sorted(glob.glob('*.gcal?'))
cfcache = basename + '.cf'
thresh = 10
if nterms[loop] > 1 and deconvolver[loop] == 'mtmfs':
outimage += '.tt0'
if step not in ['tclean', 'sky'] and not os.path.exists(outimage):
logger.error(
"Image '{0}' doesn't exist, so self-calibration loop {1} failed. Will terminate selfcal process."
.format(outimage, loop))
sys.exit(1)
if step in ['tclean', 'predict']:
pixmask = imbase % (loop - 1) + '.pixmask'
rmsfile = imbase % (loop - 1) + '.rms'
if step in ['tclean', 'predict', 'sky'
] and ((loop == 0 and not os.path.exists(pixmask)) or
(0 < loop < nloops and calmode[loop] == '')):
pixmask = ''
#Check no missing caltables
for i in range(0, loop):
if calmode[i] != '' and not os.path.exists(basename + '.gcal%d' % i):
logger.error(
"Calibration table '{0}' doesn't exist, so self-calibration loop {1} failed. Will terminate selfcal process."
.format(basename + '.gcal%d' % i, i))
sys.exit(1)
for i in range(discard_nloops):
prev_caltables.pop(0)
if outlier_threshold != '' and outlier_threshold != 0: # and (loop > 0 or step in ['sky','bdsf'] and loop == 0):
if step in ['tclean', 'predict', 'sky']:
outlierfile = 'outliers_loop{0}.txt'.format(loop)
else:
outlierfile = 'outliers_loop{0}.txt'.format(loop + 1)
else:
outlierfile = ''
if not (type(threshold[loop]) is str
and 'Jy' in threshold[loop]) and threshold[loop] > 1:
if step in ['tclean', 'predict']:
if os.path.exists(rmsfile):
from casatasks import imstat
stats = imstat(imagename=rmsfile)
threshold[loop] *= stats['min'][0]
else:
logger.error(
"'{0}' doesn't exist. Can't do thresholding at S/N > {1}. Loop 0 must use an absolute threshold value. Check the logs to see why RMS map not created."
.format(rmsfile, threshold[loop]))
sys.exit(1)
elif step == 'bdsf':
thresh = threshold[loop]
return imbase, imagename, outimage, pixmask, rmsfile, caltable, prev_caltables, threshold, outlierfile, cfcache, thresh, maskfile