Light Ray Generator

Light rays are similar to light cones (Light Cone Generator) in how they stack multiple datasets together to span a redshift interval. Unlike light cones, which stack randomly oriented projections from each dataset to create synthetic images, light rays use thin pencil beams to simulate QSO sight lines. A sample script can be found in the cookbook under Light Ray.


A ray segment records the information of all grid cells intersected by the ray as well as the path length, dl, of the ray through the cell. Column densities can be calculated by multiplying physical densities by the path length.

Configuring the Light Ray Generator

Below follows the creation of a light ray from multiple datasets stacked together. However, a light ray can also be made from a single dataset. For an example of this, see Single Dataset Light Ray.

The arguments required to instantiate a LightRay object are the same as those required for a LightCone object: the simulation parameter file, the simulation type, the nearest redshift, and the furthest redshift.

from yt.analysis_modules.cosmological_observation.api import LightRay
lr = LightRay("enzo_tiny_cosmology/32Mpc_32.enzo",
              near_redshift=0.0, far_redshift=0.1)

Additional keyword arguments are:

  • use_minimum_datasets (bool): If True, the minimum number of datasets is used to connect the initial and final redshift. If false, the light ray solution will contain as many entries as possible within the redshift interval. Default: True.
  • deltaz_min (float): Specifies the minimum Delta-z between consecutive datasets in the returned list. Default: 0.0.
  • max_box_fraction (float): In terms of the size of the domain, the maximum length a light ray segment can be in order to span the redshift interval from one dataset to another. If using a zoom-in simulation, this parameter can be set to the length of the high resolution region so as to limit ray segments to that size. If the high resolution region is not cubical, the smallest side should be used. Default: 1.0 (the size of the box)
  • minimum_coherent_box_fraction (float): Use to specify the minimum length of a ray, in terms of the size of the domain, before the trajectory is re-randomized. Set to 0 to have ray trajectory randomized for every dataset. Set to np.inf (infinity) to use a single trajectory for the entire ray. Default: 0.0.
  • time_data (bool): Whether or not to include time outputs when gathering datasets for time series. Default: True.
  • redshift_data (bool): Whether or not to include redshift outputs when gathering datasets for time series. Default: True.

Making Light Ray Data

Once the LightRay object has been instantiated, the make_light_ray() function will trace out the rays in each dataset and collect information for all the fields requested. The output file will be an HDF5 file containing all the cell field values for all the cells that were intersected by the ray. A single LightRay object can be used over and over to make multiple randomizations, simply by changing the value of the random seed with the seed keyword.

                  fields=['temperature', 'density'],

The keyword arguments are:

  • seed (int): Seed for the random number generator. Default: None.
  • periodic (bool): If True, ray trajectories will make use of periodic boundaries. If False, ray trajectories will not be periodic. Default : True.
  • left_edge (iterable of floats or YTArray): The left corner of the region in which rays are to be generated. If None, the left edge will be that of the domain. Default: None.
  • right_edge (iterable of floats or YTArray): The right corner of the region in which rays are to be generated. If None, the right edge will be that of the domain. Default: None.
  • min_level (int): The minimum refinement level of the spatial region in which the ray passes. This can be used with zoom-in simulations where the high resolution region does not keep a constant geometry. Default: None.
  • start_position (list of floats): Used only if creating a light ray from a single dataset. The coordinates of the starting position of the ray. Default: None.
  • end_position (list of floats): Used only if creating a light ray from a single dataset. The coordinates of the ending position of the ray. Default: None.
  • trajectory (list of floats): Used only if creating a light ray from a single dataset. The (r, theta, phi) direction of the light ray. Use either end_position or trajectory, not both. Default: None.
  • fields (list): A list of fields for which to get data. Default: None.
  • solution_filename (string): Path to a text file where the trajectories of each subray is written out. Default: None.
  • data_filename (string): Path to output file for ray data. Default: None.
  • use_peculiar_velocity (bool): If True, the doppler redshift from the peculiar velocity of gas along the ray is calculated and added to the cosmological redshift as the “effective” redshift. Default: True.
  • redshift (float): Used with light rays made from single datasets to specify a starting redshift for the ray. If not used, the starting redshift will be 0 for a non-cosmological dataset and the dataset redshift for a cosmological dataset. Default: None.
  • njobs (int): The number of parallel jobs over which the slices for the halo mask will be split. Choose -1 for one processor per individual slice and 1 to have all processors work together on each projection. Default: 1

Useful Tips for Making LightRays

Below are some tips that may come in handy for creating proper LightRays.

How many snapshots do I need?

The number of snapshots required to traverse some redshift interval depends on the simulation box size and cosmological parameters. Before running an expensive simulation only to find out that you don’t have enough outputs to span the redshift interval you want, have a look at Planning Simulations to use LightCones or LightRays. The functionality described there will allow you to calculate the precise number of snapshots and specific redshifts at which they should be written.

My snapshots are too far apart!

The max_box_fraction keyword, provided when creating the Lightray, allows the user to control how long a ray segment can be for an individual dataset. Be default, the LightRay generator will try to make segments no longer than the size of the box to avoid sampling the same structures more than once. However, this can be increased in the case that the redshift interval between datasets is longer than the box size. Increasing this value should be done with caution as longer ray segments run a greater risk of coming back to somewhere near their original position.

What if I have a zoom-in simulation?

A zoom-in simulation has a high resolution region embedded within a larger, low resolution volume. In this type of simulation, it is likely that you will want the ray segments to stay within the high resolution region. To do this, you must first specify the size of the high resolution region when creating the LightRay using the max_box_fraction keyword. This will make sure that the calculation of the spacing of the segment datasets only takes into account the high resolution region and not the full box size. If your high resolution region is not a perfect cube, specify the smallest side. Then, in the call to make_light_ray(), use the left_edge and right_edge keyword arguments to specify the precise location of the high resolution region.

Technically speaking, the ray segments should no longer be periodic since the high resolution region is only a sub-volume within the larger domain. To make the ray segments non-periodic, set the periodic keyword to False. The LightRay generator will continue to generate randomly oriented segments until it finds one that fits entirely within the high resolution region. If you have a high resolution region that can move and change shape slightly as structure forms, use the min_level keyword to mandate that the ray segment only pass through cells that are refined to at least some minimum level.

If the size of the high resolution region is not large enough to span the required redshift interval, the LightRay generator can be configured to treat the high resolution region as if it were periodic simply by setting the periodic keyword to True. This option should be used with caution as it will lead to the creation of disconnected ray segments within a single dataset.

I want a continous trajectory over the entire ray.

Set the minimum_coherent_box_fraction keyword argument to a very large number, like infinity (numpy.inf).


As of yt-3.0, the functionality for recording properties of the nearest halo to each element of the ray no longer exists. This is still available in yt-2.x. If you would like to use this feature in yt-3.x, help is needed to port it over. Contact the yt-users mailing list if you are interested in doing this.

What Can I do with this?

Once you have created a LightRay, you can use it to generate an Creating Absorption Spectra. In addition, you can use the RayCallback to Overplot the Path of a Ray on your plots.