Search Parameters#

Search parameters are set extensively via the SearchConfiguration object. We use a custom object, instead of a standard dictionary, to both add helper functions, such as I/O and validity checking, and also to set defaults. All of the standard parameters are given default values (shown in the Table below) unless explicitly set.

Creating a SearchConfiguration#

There are several methods for setting these parameters.

First, parameters can be set one-by-one from a default SearchConfiguration object using the set() method:

config = SearchConfiguration()
config.set("cluster_eps", 10.0)

Second, you can provide a YAML file of the parameters using the config_file parameter:

config = SearchConfiguration.from_file(file_path)

Third, you can pass in a dictionary mapping parameter name to parameter value:

config = SearchConfiguration.from_dict(param_dict)

The dictionary values take precedence over all other settings, allowing you to use KBMOD as part of an internal loop over parameters.

In addition SearchConfiguration objects are automatically saved and loaded within a WorkUnit.

Configuration Parameters#

Parameter	Default Value	Interpretation
`chunk_size`	500000	The batch size to use when processing the results of the on-GPU search.
`clip_negative`	False	An option used with sigmaG filtering, remove all negative values prior to computing the percentiles.
`cluster_eps`	20.0	The threshold to use for clustering similar results.
`cluster_type`	all	Types of predicted values to use when determining trajectories to clustered together, including position and velocities (if do_clustering = True). Options include: `all`, `position`, `mid_position`, and `start_end_position`
`cluster_v_scale`	1.0	The weight of differences in velocity relative to differences in distances during clustering.
`coadds`	[]	A list of additional coadds to create. These are not used in filtering, but saved to columns for analysis. Can include: “sum”, “mean”, “median”, and “weighted”. The filtering coadd is controlled by the `stamp_type` parameter.
`debug`	False	Display debugging output.
`do_clustering`	True	Cluster the resulting trajectories to remove duplicates and known objects. See Clustering for more.
`do_mask`	True	Apply the mask to the raw pixels.
`encode_num_bytes`	-1	The number of bytes to use to encode `psi` and `phi` images on GPU. By default a `float` encoding is used. When either `1` or `2`, the images are compressed into `unsigned int`.
`gpu_filter`	False	Perform the filtering on the GPU. Only `filter_type=clipped_sigmaG` filtering is supported on GPU.
`generator_config`	None	The configuration dictionary for the trajectory generator that will create the search candidates.
`lh_level`	10.0	The minimum computed likelihood for an object to be accepted.
`max_lh`	1000.0	A maximum likelihood threshold to apply to detected objects. Objects with a computed likelihood above this threshold are rejected.
`num_obs`	10	The minimum number of non-masked observations for the object to be accepted.
`psf_val`	1.4	The value for the standard deviation of the point spread function (PSF) in pixels
`result_filename`	None	Full filename and path for a single tabular result saves as ecsv.
`results_per_pixel`	8	The maximum number of results to to return for each pixel search.
`save_all_stamps`	True	Save the individual stamps for each result and timestep.
`sigmaG_lims`	[25, 75]	The percentiles to use in sigmaG filtering, if `filter_type= clipped_sigmaG`.
`stamp_radius`	10	Half the size of a side of a box cut around the predicted position when creating a stamp for stamp filtering (in pixels).
`stamp_type`	sum	The type of coadd to use as the main stamp: * `sum` - (default) Per pixel sum * `median` - Per pixel median * `mean` - Per pixel mean * `weighted` - Per pixel mean weighted by 1.0 / variance.
`track_filtered`	False	A Boolean indicating whether to track the filtered trajectories. Warning can use a lot of memory.
`x_pixel_bounds`	None	A length two list giving the starting and ending x pixels to use for the search. None uses the image bounds.
`x_pixel_buffer`	None	An integer length of pixels outside the image bounds to use for starting coordinates. If `x_bounds` is provided that takes precedence. `None` uses the image bounds.
`y_pixel_bounds`	None	A length two list giving the starting and ending y pixels to use for the search. None uses the image bounds.
`y_pixel_buffer`	None	An integer length of pixels outside the image bounds to use for starting coordinates. If `y_bounds` is provided that takes precedence. `None` uses the image bounds.