The path (relative or absolute) to the folder you wish to
process.
ch1
A natural number. The index of the first channel to use.
ch2
A natural number. The index of the second channel to use.
thresh
Do you want to apply an intensity threshold prior to
calculating cross-correlated number (via
autothresholdr::mean_stack_thresh())? If so, set your thresholding method
here. If this is a single value, that same threshold will be applied to
both channels. If this is a length-2 vector or list, then these two
thresholds will be applied to channels 1 and 2 respectively. A value of
NA for either channel gives no thresholding for that channel.
detrend
Detrend your data with detrendr::img_detrend_rh(). This is
the best known detrending method for brightness analysis. For more
fine-grained control over your detrending, use the detrendr package. To
detrend one channel and not the other, specify this as a length 2 vector.
quick
FALSE repeats the detrending procedure (which has some inherent
randomness) a few times to hone in on the best detrend. TRUE is quicker,
performing the routine only once. FALSE is better.
filt
Do you want to smooth (filt = 'smooth') or median (filt = 'median') filter the cross-correlated number image using smooth_filter()
or median_filter() respectively? If selected, these are invoked here with
a filter radius of 1 and with the option na_count = TRUE. A value of NA
for either channel gives no thresholding for that channel. If you want to
smooth/median filter the cross-correlated number image in a different way,
first calculate the cross-correlated numbers without filtering (filt = NULL) using this function and then perform your desired filtering routine
on the result.
parallel
Would you like to use multiple cores to speed up this
function? If so, set the number of cores here, or to use all available
cores, use parallel = TRUE.