From c7a66e8ccabb7a57c674ef6b78a0f336b71de643 Mon Sep 17 00:00:00 2001
From: AK <kutkin@gmail.com>
Date: Mon, 9 Aug 2021 13:35:42 +0000
Subject: [PATCH] fixed wrong mask file usage
---
cluster.py | 20 +++++++++++---------
imcal.py | 27 ++++++++++++++-------------
imcal.yml | 14 +++++---------
3 files changed, 30 insertions(+), 31 deletions(-)
diff --git a/cluster.py b/cluster.py
index 67aa4a1..a2c2cbc 100755
--- a/cluster.py
+++ b/cluster.py
@@ -378,12 +378,6 @@ def auto_clustering(fig, ax, df, wcs, resid_data, pix_arcmin_scale, nbright,
small_resid = resid_data[py-boxsize:py+boxsize, px-boxsize:px+boxsize]
ellipse_mean, ecc, amaj, numpix = ellipses_coh(small_resid, amin=20, amax=boxsize-1, dr=1.0)
- # print ellipse_mean, ecc, amaj, numpix
-
-
-
- # if abs(ring_mean/resid_mean) > 1.7e5:
- # if abs(ring_mean/small_resid_mean) > 1e4:
if nclusters=='auto':
if abs(ellipse_mean/rms) > 1.4:
@@ -451,12 +445,20 @@ def auto_clustering(fig, ax, df, wcs, resid_data, pix_arcmin_scale, nbright,
return final_clusters
+# TODO
+def voronoy_clustering():
+ """
+ Use Voronoy clustering instead of fixed radius around sources
+ """
+ pass
+
+
def main(img, resid, model, auto=True, add_manual=False, nclusters=5, boxsize=250,
nbright=80, cluster_radius=5, cluster_overlap=1.6):
- path = os.path.split(os.path.abspath(img))[0]
- output = os.path.splitext(img)[0]+'-clustered.txt'
+ imgbase = os.path.splitext(img)[0]
+ output = imgbase + '-clustered.txt'
df = pd.read_csv(model, skipinitialspace=True)
df['ra'] = df.Ra.apply(ra2deg)
@@ -491,7 +493,7 @@ def main(img, resid, model, auto=True, add_manual=False, nclusters=5, boxsize=25
if clusters:
write_df(df, clusters, output=output)
fig.tight_layout()
- fig.savefig(path+'/clustering.png')
+ fig.savefig(imgbase+'-clustering.png')
return output
diff --git a/imcal.py b/imcal.py
index f7e5236..cd6a1e4 100755
--- a/imcal.py
+++ b/imcal.py
@@ -326,13 +326,13 @@ def main(msin, outbase=None, cfgfile='imcal.yml'):
img1 = outbase + '_1'
img2 = outbase + '_2'
img3 = outbase + '_3'
- img_final = outbase
+ img_final = outbase + '-dical'
img_ddsub = outbase + '-ddsub'
img_ddcal = outbase + '-ddcal'
- mask0 = 'mask0.fits'
- mask1 = 'mask1.fits'
- mask2 = 'mask2.fits'
+ mask0 = outbase + '-mask0.fits'
+ mask1 = outbase + '-mask1.fits'
+ mask2 = outbase + '-mask2.fits'
model1 = outbase + '_model1.sourcedb'
model2 = outbase + '_model2.sourcedb'
@@ -364,45 +364,46 @@ def main(msin, outbase=None, cfgfile='imcal.yml'):
threshold = img_max/cfg['clean0']['max_over_thresh']
wsclean(ms_split, outname=img0, automask=None, save_source_list=False, multifreq=False, mgain=None,
kwstring=f'-threshold {threshold}')
- if not os.path.exists('mask0.fits') :
- create_mask(img0 +'-image.fits', img0 +'-residual.fits', clipval=20, outname='mask0.fits')
+ create_mask(img0 +'-image.fits', img0 +'-residual.fits', clipval=20, outname=mask0)
# clean1
if not os.path.exists(img1 +'-image.fits') and (not os.path.exists(img1 +'-MFS-image.fits')):
- wsclean(ms_split, outname=img1, **cfg['clean1']) # fast shallow clean
+ wsclean(ms_split, fitsmask=mask0, outname=img1, **cfg['clean1']) # fast shallow clean
if not os.path.exists(model1):
makesourcedb(img1+'-sources.txt', out=model1)
-
+# dical1
if not os.path.exists(dical1):
dical1 = dical(ms_split, model1, msout=dical1, h5out=h5_1, **cfg['dical1'])
view_sols(h5_1, outname='dical1')
# clean2
if (not os.path.exists(img2 +'-image.fits')) and (not os.path.exists(img2 +'-MFS-image.fits')):
- wsclean(dical1, outname=img2, **cfg['clean2'])
- create_mask(img2 +'-image.fits', img2 +'-residual.fits', clipval=7, outname='mask1.fits')
+ wsclean(dical1, fitsmask=mask0, outname=img2, **cfg['clean2'])
+ create_mask(img2 +'-image.fits', img2 +'-residual.fits', clipval=7, outname=mask1)
if not os.path.exists(model2):
makesourcedb(img2+'-sources.txt', out=model2)
+# dical2
if not os.path.exists(dical2):
dical2 = dical(dical1, model2, msout=dical2, h5out=h5_2, **cfg['dical2'])
view_sols(h5_2, outname='dical2')
# clean3
if (not os.path.exists(img3 +'-image.fits')) and (not os.path.exists(img3 +'-MFS-image.fits')):
- wsclean(dical2, outname=img3, **cfg['clean3'])
- create_mask(img3 +'-image.fits', img3 +'-residual.fits', clipval=5, outname='mask2.fits')
+ wsclean(dical2, fitsmask=mask1, outname=img3, **cfg['clean3'])
+ create_mask(img3 +'-image.fits', img3 +'-residual.fits', clipval=5, outname=mask2)
if not os.path.exists(model3):
makesourcedb(img3+'-sources.txt', out=model3)
+# dical3
if not os.path.exists(dical3):
dical3 = dical(dical2, model3, msout=dical3, h5out=h5_3, **cfg['dical3'])
view_sols(h5_3, outname='dical3')
# clean4
if (not os.path.exists(img_final +'-image.fits')) and (not os.path.exists(img_final +'-MFS-image.fits')):
- wsclean(dical3, outname=img_final, **cfg['clean4'])
+ wsclean(dical3, fitsmask=mask2, outname=img_final, **cfg['clean4'])
# Cluster
diff --git a/imcal.yml b/imcal.yml
index 6fc2213..997fc12 100644
--- a/imcal.yml
+++ b/imcal.yml
@@ -24,7 +24,6 @@ clean1: # wsclean setup
mgain: 0
automask: 20
autothresh: 5
- fitsmask: 'mask0.fits'
multiscale: False
kwstring: '-use-wgridder -parallel-deconvolution 1400' # use this for additional wsclean options, e.g. '-weight uniform -use-idg'
@@ -32,7 +31,7 @@ dical1: # DPPP setup for direction independent calibration
solint: 20
mode: 'phaseonly'
uvlambdamin: 500 # Ignore baselines / channels with UV < uvlambdamin wavelengths.
-# cal_nchan: 31 # number of chans with the same solutions
+ cal_nchan: 30 # number of chans with the same solutions
clean2:
imagesize: 3072
@@ -40,7 +39,6 @@ clean2:
multifreq: 8
automask: 10
autothresh: 5
- fitsmask: 'mask0.fits'
multiscale: True
kwstring: '-use-wgridder -parallel-deconvolution 1400 -parallel-gridding 8 -deconvolution-channels 3'
@@ -48,7 +46,7 @@ dical2:
solint: 1
mode: 'phaseonly'
uvlambdamin: 500 # Ignore baselines / channels with UV < uvlambdamin wavelengths.
- cal_nchan: 31 # number of chans with the same solutions
+ cal_nchan: 30 # number of chans with the same solutions
clean3:
imagesize: 3072
@@ -56,7 +54,6 @@ clean3:
multifreq: 8
automask: 7
autothresh: 3.5
- fitsmask: 'mask1.fits'
multiscale: True
kwstring: '-use-wgridder -parallel-deconvolution 1400 -parallel-gridding 8 -deconvolution-channels 3'
@@ -64,7 +61,7 @@ dical3:
solint: 800
mode: 'diagonal'
uvlambdamin: 500 # Ignore baselines / channels with UV < uvlambdamin wavelengths.
- cal_nchan: 31 # number of chans with the same solutions
+ cal_nchan: 30 # number of chans with the same solutions.
clean4:
imagesize: 3072
@@ -73,7 +70,6 @@ clean4:
automask: 4.5
autothresh: 0.5
multiscale: True
- fitsmask: 'mask2.fits'
kwstring: '-use-wgridder -parallel-deconvolution 1400 -parallel-gridding 8 -deconvolution-channels 3 -weight briggs 0.0'
####################### CLUSTERING #######################
@@ -88,9 +84,9 @@ cluster:
######################## DD CALIBRATION #######################
ddcal: # see DPPP/DDECal documentation
- solint: 120 # Solution interval in timesteps (1 ~ 30sec for Apertif).
+ solint: 120 # Solution interval in timesteps (1 corresponds to 30 seconds for Apertif).
mode: 'diagonal' # Type of constraint to apply.
- nfreq: 15 # Number of channels in each channel block, for which the solution is assumed to be constant.
+ nfreq: 30 # Number of channels in each channel block, for which the solution is assumed to be constant.
startchan: 0
nchan: 0
uvlambdamin: 500 # Ignore baselines / channels with UV < uvlambdamin wavelengths.
--
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