Create a cube and signal mask corrected for galactic rotation

analysis/rotcurve_correction.py

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+
+'''
+Create a version of the NOEMA data corrected for galactic rotation.
+'''
+
+from spectral_cube import SpectralCube, Projection
+from astropy.io import fits
+import astropy.units as u
+from galaxies import Galaxy
+from astropy.table import Table
+import os
+import numpy as np
+
+from cube_analysis.rotation_curves.curve_fitting import vcirc_brandt
+from cube_analysis.rotation_curves import update_galaxy_params
+from cube_analysis.spectra_shifter import cube_shifter
+
+from paths import noema_co21_file_dict, hi_14B088_data_path, noema_data_path
+
+num_cores = 4
+
+# Set the number of spectra to load in and operate on at once.
+chunk_size = 50000
+
+gal = Galaxy("M33")
+
+# Make sure this version has 840 kpc as the distance
+assert gal.distance == 840 * u.kpc
+
+cube = SpectralCube.read(noema_co21_file_dict['Cube'])
+
+# Create rotation velocities over the cube region
+tab = Table.read(hi_14B088_data_path("diskfit_peakvels_noasymm_noradial_nowarp_output/rad.out.params.csv"))
+
+update_galaxy_params(gal, tab)
+
+hi_model = Projection.from_hdu(fits.open(hi_14B088_data_path("diskfit_peakvels_noasymm_noradial_nowarp_output/rad.fitmod.fits")))
+
+radii = gal.radius(header=cube.header).to(u.kpc)
+pas = gal.position_angles(header=cube.header)
+
+# Convert 3'' pix to kpc
+rmax_kpc = tab['fit_rmax'] * (3 * u.arcsec).to(u.rad).value * \
+    gal.distance.to(u.kpc)
+
+vmax_kms = tab['fit_vmax'] * u.km / u.s
+
+pars = [0.56, 110.0, 12.0]
+
+# vcirc = vcirc_brandt(radii, *[tab['fit_n'], vmax_kms, rmax_kpc]) * \
+#     u.km / u.s
+vcirc = vcirc_brandt(radii.value, *pars) * u.km / u.s
+
+smooth_model = vcirc * np.cos(pas) * np.sin(gal.inclination).value + \
+    tab['Vsys'] * u.km / u.s
+
+# Make sure the model is correct by comparing with the HI fit range
+# spat_mask_0 = np.logical_and(hi_model.spatial_coordinate_map[1] >= cube.longitude_extrema[0],
+#                              hi_model.spatial_coordinate_map[1] <= cube.longitude_extrema[1])
+# spat_mask_1 = np.logical_and(hi_model.spatial_coordinate_map[0] >= cube.latitude_extrema[0],
+#                              hi_model.spatial_coordinate_map[0] <= cube.latitude_extrema[1])
+# spat_mask = np.logical_and(spat_mask_0, spat_mask_1)
+
+# hi_model_noema = hi_model[spat_mask]
+
+# hi_model_reproj = hi_model.reproject(header=cube[0].header)
+
+# Shift with the first moment
+filename = os.path.splitext(noema_co21_file_dict['Cube'])[0]
+
+print("Shifting w/ rotation velocity")
+rotsub_cube_name = "{}.rotation_corrected.fits".format(filename)
+cube_shifter(cube, smooth_model, smooth_model.mean(), save_shifted=True,
+             save_name=noema_data_path(rotsub_cube_name, no_check=True),
+             return_spectra=False, verbose=True, num_cores=num_cores,
+             chunk_size=chunk_size, pad_edges=True)
+
+# Also shift the signal mask to match those shifted here.
+print("Shifting mask w/ rotation velocity")
+mask = SpectralCube.read(noema_co21_file_dict['Source_Mask'])
+
+rotsub_mask_name = "{}_source_mask.rotation_corrected.fits".format(filename)
+cube_shifter(mask, smooth_model, smooth_model.mean(), save_shifted=True,
+             save_name=noema_data_path(rotsub_mask_name, no_check=True),
+             return_spectra=False, verbose=True, num_cores=num_cores,
+             is_mask=True, chunk_size=chunk_size, pad_edges=True)