Visualizing spectral cubes with yt¶
Extracting yt objects¶
SpectralCube class includes a
to_yt() method that makes is easy to return
an object that can be used by yt to make volume
renderings or other visualizations of the data. One common issue with volume
rendering of spectral cubes is that you may not want pixels along the
spectral axis to be given the same ‘3-d’ size as positional pixels, so the
to_yt() method includes a
spectral_factor argument that can be used to compress or expand the
to_yt() method is used as follows:
>>> ytcube = cube.to_yt(spectral_factor=0.5) >>> ds = ytcube.dataset
The API change in https://github.com/radio-astro-tools/spectral-cube/pull/129 affects the interpretation of the 0-pixel. There may be a 1-pixel offset between the yt cube and the SpectralCube
ds object is then a yt object that can be used for rendering! By
default the dataset is defined in pixel coordinates, going from
n+0.5, as would be the case in ds9, for example. Along the spectral axis,
this range will be modified if
spectral_factor does not equal unity.
When working with datasets in yt, it may be useful to convert world coordinates
to pixel coordinates, so that whenever you may have to input a position in yt
(e.g., for slicing or volume rendering) you can get the pixel coordinate that
corresponds to the desired world coordinate. For this purpose, the method
world2yt() is provided:
>>> import astropy.units as u >>> pix_coord = ytcube.world2yt([51.424522, ... 30.723611, ... 5205.18071], # units of deg, deg, m/s ... )
There is also a reverse method provided,
>>> world_coord = ytcube.yt2world([ds.domain_center])
which in this case would return the world coordinates of the center of the dataset in yt.
This section shows an example of a rendering script that can be used to
produce a 3-d isocontour visualization using an object returned by
import numpy as np from spectral_cube import SpectralCube from yt.mods import ColorTransferFunction, write_bitmap import astropy.units as u # Read in spectral cube cube = SpectralCube.read('L1448_13CO.fits', format='fits') # Extract the yt object from the SpectralCube instance ytcube = cube.to_yt(spectral_factor=0.75) ds = ytcube.dataset # Set the number of levels, the minimum and maximum level and the width # of the isocontours n_v = 10 vmin = 0.05 vmax = 4.0 dv = 0.02 # Set up color transfer function transfer = ColorTransferFunction((vmin, vmax)) transfer.add_layers(n_v, dv, colormap='RdBu_r') # Set up the camera parameters # Derive the pixel coordinate of the desired center # from the corresponding world coordinate center = ytcube.world2yt([51.424522, 30.723611, 5205.18071]) direction = np.array([1.0, 0.0, 0.0]) width = 100. # pixels size = 1024 camera = ds.camera(center, direction, width, size, transfer, fields=['flux']) # Take a snapshot and save to a file snapshot = camera.snapshot() write_bitmap(snapshot, 'cube_rendering.png', transpose=True)
You can move the camera around; see the yt camera docs.
There is a simple utility for quick movie making. The default movie is a rotation of the cube around one of the spatial axes, going from PP -> PV space and back.:
>>> cube = read('cube.fits', format='fits') >>> ytcube = cube.to_yt() >>> images = ytcube.quick_render_movie('outdir')
The movie only does rotation, but it is a useful stepping-stone if you wish to learn how to use yt’s rendering system.
SketchFab Isosurface Contours¶
For data exploration, making movies can be tedious - it is difficult to control the camera and expensive to generate new renderings. Instead, creating a ‘model’ from the data and exporting that to SketchFab can be very useful. Only grayscale figures will be created with the quicklook code.
You need an account on sketchfab.com for this to work.:
>>> ytcube.quick_isocontour(title='GRS l=49 13CO 1 K contours', level=1.0)
Here’s an example:
You can also export locally to .ply and .obj files, which can be read by many programs (sketchfab, meshlab, blender). See the yt page for details.:
>>> ytcube.quick_isocontour(export_to='ply', filename='meshes.ply', level=1.0) >>> ytcube.quick_isocontour(export_to='obj', filename='meshes', level=1.0)