%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
NaNs in it, so we'll mask them out by setting
nan_mask = 0:
ds = yt.load("radio_fits/m33_hi.fits", nan_mask=0.0, z_axis_decomp=True)
/usr/lib64/python3.4/site-packages/IPython/kernel/__init__.py:13: 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:
slc = yt.SlicePlot(ds, "z", ["intensity"], origin="native") slc.show()