Setting the ssn.zero_snr parameter will prevent samples contributing to the SSN model if they fall within map pixels that have SNR values greater than ssn.zero_snr. A ssn.zero_snr value of zero means no SNR mask is used. See also parameter "ssn.zero_snr_ffclean" .

Note, the SNR values are only available once a map has been created, and so using this parameter results in no SSN masking on the first iteration. Consequently the map at the end of the first iteration may have noticable straight lines aligned with azimuth that pass through bright sources, since no SSN masking was done. Normally, these lines would polute the AST model derived from the map, and thus polute the residuals on the next iteration, resulting in the lines remaining in later maps. To avoid this, parameter "ast.skip" can be set to a positive value. This causes the AST model to be skipped (i.e. no AST signal is subtracted from the residuals) for the first " ast.skip" iterations. This means that a good SSN mask can be formed from these initial iterations before any AST model is calculated and used. [0.0]

MAKEMAP, CALCQU