FITS Radio Cubes in ytΒΆ

In [1]:
%matplotlib inline
import yt

This notebook demonstrates some of the capabilties of yt on some FITS "position-position-spectrum" cubes of radio data.

Note that it depends on some external dependencies, including astropy, wcsaxes, and pyregion.

M33 VLA Image

The dataset "m33_hi.fits" has NaNs in it, so we'll mask them out by setting nan_mask = 0:

In [2]:
ds = yt.load("radio_fits/m33_hi.fits", nan_mask=0.0, z_axis_decomp=True)
/usr/lib64/python3.4/site-packages/IPython/kernel/ ShimWarning: The `IPython.kernel` package has been deprecated. You should import from ipykernel or jupyter_client instead.
  "You should import from ipykernel or jupyter_client instead.", ShimWarning)
WARNING:yt:Cannot find time
WARNING:yt:No length conversion provided. Assuming 1 = 1 cm.

First, we'll take a slice of the data along the z-axis, which is the velocity axis of the FITS cube:

In [3]:
slc = yt.SlicePlot(ds, "z", ["intensity"], origin="native")