Replace data from bad pixels with interpolated values, replace data from saturated and nearby pixels withs NAs, apply linearization function if data is not already linearized, optionally use a range of pixels as dark reference, convert the raw counts for each integration time used into counts-per-second, if data from bracketed intergartion times is available, splice the different spectra.
Usage
raw2corr_cps(x, ref.pixs.range, ...)
# Default S3 method
raw2corr_cps(x, ref.pixs.range = NULL, ...)
# S3 method for class 'raw_spct'
raw2corr_cps(
x,
ref.pixs.range = c(1, 100),
despike = FALSE,
hdr.tolerance = getOption("ooacquire.hdr.tolerance", default = 0.05),
...
)
# S3 method for class 'raw_mspct'
raw2corr_cps(x, ref.pixs.range = c(1, 100), despike = FALSE, ...)
Arguments
- x
raw_spct object.
- ref.pixs.range
integer vector of length 2.
- ...
passed to
photobiology::despike
.- despike
logical flag, if TRUE despiking will be attempted.
- hdr.tolerance
numeric Passed as tolerance argument to merge_cps().
Methods (by class)
raw2corr_cps(default)
: Default methodraw2corr_cps(raw_spct)
: raw_spct methodraw2corr_cps(raw_mspct)
: raw_spct method
See also
Other functions for conversion of raw-counts data:
raw2cps()
,
s_fraction_corrected()
,
s_irrad_corrected()