Trying uv comparison with 30-m data left in Ta*. They suspiciously ma…

…tch... need to find why still

imaging/IRAM_feather_preprocess.py

@@ -33,16 +33,22 @@
 
 # Open each cube and apply the Ta* -> Tmb correction
 
+# NOTE: The uv-overlap ratio matches if this correction is NOT applied.
+# If that is the case, the correction factor may need to be applied to both
+# data sets.
+
 rep_spat_cube = SpectralCube.read(iram_matched_data_path("m33.co21_iram.noema_regrid.spatial.fits"))
-rep_spat_cube.allow_huge_operations=True
-rep_spat_cube /= beam_eff_30m_druard
+# rep_spat_cube.allow_huge_operations = True
+# rep_spat_cube /= beam_eff_30m_druard
 rep_spat_cube.write(iram_matched_data_path("m33.co21_iram.noema_regrid.spatial.fits"),
                     overwrite=True)
 
 del rep_spat_cube
 
 rep_cube = SpectralCube.read(iram_matched_data_path("m33.co21_iram.noema_regrid.fits"))
-rep_cube.allow_huge_operations=True
-rep_cube /= beam_eff_30m_druard
+# rep_cube.allow_huge_operations = True
+# rep_cube /= beam_eff_30m_druard
+rep_cube.write(iram_matched_data_path("m33.co21_iram.noema_regrid.fits"),
+                                      overwrite=True)
 
 del rep_cube

imaging/line_feather.py

@@ -14,19 +14,19 @@
 from cube_analysis.feather_cubes import feather_cube
 
 
-noema_cube = SpectralCube.read(noema_data_path('M33-ARM26.image.pbcor.fits'))
+noema_cube = SpectralCube.read(noema_data_path('M33-ARM05_yclean.tc_final.image.pbcor.K.26regrid.fits'))
 iram_cube = SpectralCube.read(iram_matched_data_path("m33.co21_iram.noema_regrid.spatial.fits"))
 
 # Cut the IRAM cube to the extent of the NOEMA data
 iram_cube = iram_cube.spectral_slab(noema_cube.spectral_extrema[0],
                                     noema_cube.spectral_extrema[1])
 
 # Convert the NOEMA cube to K
-noema_cube = noema_cube.to(u.K)
+# noema_cube = noema_cube.to(u.K)
 
 # Also need the pb map. It is constant across the channels so grab the first
 # channel
-noema_pb = SpectralCube.read(noema_data_path('M33-ARM05.pb.fits'))[0]
+noema_pb = SpectralCube.read(noema_data_path('yclean_05/M33-ARM05_yclean.tc_final.pb.fits'))[0]
 
 # Define a mask that will be used to smoothly taper the IRAM data near the
 # map edges. Otherwise the comparison is dominated by ringing in the Fourier
@@ -38,24 +38,24 @@
 
 feather_cube(noema_cube, iram_cube,
              verbose=True, save_feather=True,
-             save_name=noema_data_path('M33-ARM26.image.pbcor.feather.fits', no_check=True),
+             save_name=noema_data_path('M33-ARM05_yclean.tc_final.image.pbcor.K.26regrid.feather.fits', no_check=True),
              num_cores=1, chunk=100,
              restfreq=co21_freq,
              weights=weight_arr)
 
 
 # Now do the same for the 0.5 km/s data
 
-noema_cube = SpectralCube.read(noema_data_path('M33-ARM05.image.pbcor.fits'))
+noema_cube = SpectralCube.read(noema_data_path('M33-ARM05_yclean.tc_final.image.pbcor.K.fits'))
 iram_cube = SpectralCube.read(iram_matched_data_path("m33.co21_iram.noema_regrid.fits"))
 
 # Convert the NOEMA cube to K
-noema_cube.allow_huge_operations = True
-noema_cube = noema_cube.to(u.K)
+# noema_cube.allow_huge_operations = True
+# noema_cube = noema_cube.to(u.K)
 
 feather_cube(noema_cube, iram_cube,
              verbose=True, save_feather=True,
-             save_name=noema_data_path('M33-ARM05.image.pbcor.feather.fits', no_check=True),
+             save_name=noema_data_path('M33-ARM05_yclean.tc_final.image.pbcor.K.feather.fits', no_check=True),
              num_cores=1, chunk=100,
              restfreq=co21_freq,
              weights=weight_arr)

imaging/uv_overlap_comparison.py

@@ -79,9 +79,11 @@
 plt.close()
 
 print("{0}+/-{1}".format(sfact, sfact_stderr))
-# 0.597+/-0.019
-# There's a large discrepancy between the data sets.
-# The IRAM data appear to have twice the flux of NOEMA in the overlap region.
+# 0.980326306378+/-0.032036255747
+# There's a large discrepancy between the data sets when the Ta* -> Tmb
+# conversion. Is applied to the 30-m data. The discrepancy is suspiciously
+# the same as the Tmb conversion factor.
+# The above ratio and saved plot do NOT have the Tmb conversion factor
 
 # There doesn't appear to be a clear trend with radius, but let's just check