Visualization¶
Spectral-cube is not primarily a visualization package, but it has several tools for visualizing subsets of the data.
All lower-dimensional subsets,
OneDSpectrum
, and
Projection
, have their own
quicklook
methods
(quicklook
and
quicklook
,
respectively). These methods will plot the data with somewhat properly labeled
axes.
The two-dimensional viewers default to using aplpy.
Because of quirks of how aplpy sets up its plotting window, these methods will
create their own figures. If use_aplpy
is set to False
, and similarly
if you use the OneDSpectrum
quicklook, the data will be overplotted in the
latest used plot window.
In principle, one can also simply plot the data. For example, if you have a cube, you could do:
>>> plt.plot(cube[:,0,0])
to plot a spectrum sliced out of the cube or:
>>> plt.imshow(cube[0,:,:])
to plot an image slice.
Warning
There are known incompatibilities with the above plotting approach:
matplotlib versions <2.1
will crash, and you will have to clear the plot
window to reset it.
Other Visualization Tools¶
To visualize the cubes directly, you can use some of the other tools we provide for pushing cube data into external viewers.
See Visualizing spectral cubes with yt for using yt as a visualization tool.
The spectral_cube.SpectralCube.to_glue
and
spectral_cube.SpectralCube.to_ds9
methods will send the whole cube to glue
and ds9. This approach generally requires loading the whole cube into memory.