BPP = short for batchpreprocessing.
well the thing is, a dark frame contains the bias signal as well as the dark signal. so if you subtract a dark (in camera or with some other software) and then subtract a bias using ImageCalibration or BPP, you subtracted the bias twice.
however, that might not be the whole reason that the images were destroyed by the 2nd bias subtraction - in general mixing calibrated frames (your TSX-dark subtracted lights) with uncalibrated frames (the bias frames) in another application (PI) usually does not work. it boils down to what format TSX wrote the images out in. if they were not i16, then there's a good chance that things went wrong as whatever floating point format TSX used to write the lights is not necessarily the same as how PI employs floating point numbers. for proper results you should do all the reduction in a single program. so if you can convince TSX to also flatten your images, then just bring in the fully calibrated images into PI. but if not, you should just use raw lights, darks, bias and flats (meaning i16, just as they came off the camera) and put all that into BPP and let PI do it's thing.
anyway, most likely there's nothing wrong with the bias or with the camera... i have only used TSX in passing but PI's calibration routines are pretty top notch, so most folks here would probably say to just let PI handle calibration.
rob
