The gap-filling mays crash on longer gradient with optimized parameters, as SLAW can often lead to really sensitive parameters, picking 50000+ (real) features on a long gradient. I am working on it. At the moment a workaround is to use the peakpicking/peaktable_filter to truncate the features, the default is 30000 but if you want to get a rough overview it can be lower.
It is currenty my highest priority to get this bug fixed.
The gap-filling mays crash on longer gradient with optimized parameters, as SLAW can often lead to really sensitive parameters, picking 50000+ (real) features on a long gradient. I am working on it. At the moment a workaround is to use the peakpicking/peaktable_filter to truncate the features, the default is 30000 but if you want to get a rough overview it can be lower.
It is currenty my highest priority to get this bug fixed.