def addQualityTable(image, usedCounts, visCounts):
# Create the table using TaQL.
tab = pt.taql("create table '" + image.name() + "/LOFAR_QUALITY' " +
"QUALITY_MEASURE string, VALUE string, FLAG_ROW bool")
# Get the rms noise of I,Q,U,V as list of tuples.
noises = grn.get_rms_noise(image.name())
for noise in noises:
row = tab.nrows()
tab.addrows(2)
tab.putcell("QUALITY_MEASURE", row, "RMS_NOISE_" + noise[0])
tab.putcell("VALUE", row, str(noise[1]))
tab.putcell("FLAG_ROW", row, False)
perc = 100.
nvis = 1.0 * visCounts.sum()
if nvis > 0:
# Get flagged percentage to 2 decimals.
perc = int(10000. * (1 - usedCounts.sum() / nvis) + 0.5) / 100.
tab.putcell("QUALITY_MEASURE", row + 1, "PERC_FLAGGED_VIS")
tab.putcell("VALUE", row + 1, str(perc)[:5])
tab.putcell("FLAG_ROW", row + 1, False)
tab.flush()
image.putkeyword("ATTRGROUPS." + "LOFAR_QUALITY", tab)
print "Added subtable LOFAR_QUALITY containing", tab.nrows(), "rows"
tab.close()
def addQualityTable (image, usedCounts, visCounts):
# Create the table using TaQL.
tab = pt.taql ("create table '" + image.name() + "/LOFAR_QUALITY' " +
"QUALITY_MEASURE string, VALUE string, FLAG_ROW bool")
# Get the rms noise of I,Q,U,V as list of tuples.
noises = grn.get_rms_noise (image.name())
for noise in noises:
row = tab.nrows()
tab.addrows (2)
tab.putcell ("QUALITY_MEASURE", row, "RMS_NOISE_"+noise[0])
tab.putcell ("VALUE", row, str(noise[1]))
tab.putcell ("FLAG_ROW", row, False)
perc = 100.
nvis = 1.0 * visCounts.sum()
if nvis > 0:
# Get flagged percentage to 2 decimals.
perc = int(10000. * (1 - usedCounts.sum() / nvis) + 0.5) / 100.
tab.putcell ("QUALITY_MEASURE", row+1, "PERC_FLAGGED_VIS")
tab.putcell ("VALUE", row+1, str(perc)[:5])
tab.putcell ("FLAG_ROW", row+1, False)
tab.flush()
image.putkeyword ("ATTRGROUPS." + "LOFAR_QUALITY", tab)
print "Added subtable LOFAR_QUALITY containing", tab.nrows(), "rows"
tab.close()