Step Arguments

The adaptive_trace_model step has the following step-specific arguments:

--fit_threshold (float, default=10.0)

Signal threshold value for attempting a spline fit, specified as the number of standard deviations from the overall mean for the image. This parameter controls whether a spline fit is attempted for a given spectral region (slit or slice). Higher values will create spline models for fewer slices; lower values will attempt to fit more slices. If set to 0, all slices will be fit.

--oversample (float, default=1.0)

Use the trace model to oversample the data by this factor. If the value is 1.0, the only change to the datamodel is to attach a spectral trace image, in the trace_model attribute. If any other value is specified, the input flux, error, and variance images are replaced with interpolated data oversampled onto a new pixel grid.

--slope_limit (float, default=0.1)

Slope limit for using the spline model to compute the trace. This parameter is used to distinguish between bright, compact sources for which the spline model is appropriate and faint, diffuse sources for which it is not. For compact sources (high slope), the spline models are saved in the output trace model and are used to compute the oversampled flux if oversampling is performed. For diffuse sources (low slope), a linear interpolation is used in oversampling. Set the slope limit to lower values to use the spline model for fainter sources. If set to zero, the spline model will always be used.

--psf_optimal boolean(default=False)

If set to True, the values for fit_threshold and slope_limit are ignored and the spline models are fit and used for all data. Also, residual differences from the spline model are not interpolated and added to the spline fits in oversampling. This option is generally only appropriate for simple, isolated point sources.

--save_intermediate_results boolean(default=False)

If set to True, additional image models are saved to disk for inspection, containing the full spline model, the spline model as used for compact sources, the linearly interpolated data, and the residual flux model. The saved files will have suffix spline_full, spline_used, linear_interp, and spline_residual, respectively. The linear interpolation and residual flux files are saved only if oversampling was performed.

--maximum_cores: The number of available cores that will be

used for multi-processing in this step. The default value is ‘none’, which does not use multi-processing. The other options are either an integer, ‘quarter’, ‘half’, or ‘all’. Note that these fractions refer to the total available cores and on most CPUs these include physical and virtual cores. Note that only the spline fitting portion of the code will use multiprocessing. The oversampling portion is not affected by this flag. Thus the speed up will be less than linear with the number of cores, since only a portion of the code is affected. The relative fractional speedup will be largest for cases in which the fit_threshold and slope_limit parameter values, and/or the psf_optimal flag, result in a larger fraction of the image having the spline fit performed.