| reliability.minSNR | float | ≥ 0.0 | 3.0 | Lower signal-to-noise limit for reliable sources. Detections that fall below this threshold will be deemed unreliable and assigned a reliability of 0. The value denotes the integrated signal-to-noise ratio, SNR = F_sum / \[RMS * sqrt(N * Ω)\], of the source, where Ω is the solid angle (in pixels) of the point spread function of the data, N is the number of spatial and spectral pixels of the source, F_sum is the summed flux density and RMS is the local RMS noise level (assumed to be constant). Note that the spectral resolution is assumed to be equal to the channel width. |
| reliability.parameters | list | peak, sum, mean, chan, pix, fill, std, skew, kurt | peak, sum, mean | Parameter space to be used in deriving the reliability of detections. This must be a list of parameters the number of which defines the dimensionality of the parameter space. Possible values are `peak` for the peak flux density, `sum` for the summed flux density, `mean` for mean flux density, `chan` for the number of spectral channels, `pix` for the total number of spatial and spectral pixels, `fill` for the filling factor, `std` for the standard deviation, `skew` for the skewness and `kurt` for the kurtosis across the source mask. Flux densities will be divided by the global RMS noise level. `peak`, `sum`, `mean`, `pix` and `fill` will be logarithmic, all other parameters linear. |
| reliability.plot | bool | true, false | true | If set to `true`, diagnostic plots (in EPS format) will be created to allow the quality of the reliability estimation to be assessed. It is advisable to generate and inspect these plots to ensure that the outcome of the reliability filtering procedure is satisfactory. |
| reliability.plotExtra | bool | true, false | false | If set to `true` then additional diagnostic lines of SNR = 2, 4 and 8 as well as a line of the current `reliability.minPixels` settings will be included in the reliability plot, if possible. |
| reliability.scaleKernel | float | | 0.4 | When estimating the density of positive and negative detections in parameter space, the size of the Gaussian kernel used in this process is determined from the covariance of the distribution of negative detections in parameter space. This parameter setting can be used to scale that kernel by a constant factor. |
| reliability.threshold | float | 0.0...1.0 | 0.9 | Reliability threshold in the range of 0 to 1. Sources with a reliability below this threshold will be discarded. |
| reliability.tolerance | float | | 0.05 | Convergence tolerance for the reliability kernel auto-scaling algorithm. Convergence is achieved when the absolute value of the median of the Skellam distribution drops below this tolerance. |
