Blank correction

This function is used to remove blank from eems which can help to reduce the effect of scatter bands.

eem_remove_blank(eem, blank = NA)

Arguments

eem	An object of class eemlist.
blank	An object of class eemlist.

Value

An object of class eemlist.

Details

The function will first try to use the provided blank. If the blank is omitted, the function will then try to extract the blank from the eemlist object. This is done by looking for sample names containing one of these complete or partial strings (ignoring case):

1. nano

2. miliq

3. milliq

4. mq

5. blank

Note that if blank is omitted, the function will group the eemlist based on file location and will assumes that there is a blank sample in each folder. In that context, the blank will be used on each sample in the same folder. If more than one blank is found they will be averaged (a message will be printed if this appends).

Consider the following example where there are two folders that could represent scans performed on two different days `scans_day_1` and `scans_day_2`.

scans_day_1
	nano.csv
	sample1.csv
	sample2.csv
	sample3.csv
scans_day_2
	blank.csv
	s1.csv
	s2.csv
	s3.csv

In each folder there are three samples and one blank files. In that context, `eem_remove_blank()` will use the blank `nano.csv` from `sample1.csv`, `sample2.csv` and `sample3.csv`. The same strategy will be used for files in folder `scans_day_2` but with blank named `blank.csv`.

Note that the blanks eem are not returned by the function.

Note that blank correction should be performed before Raman normalization (eem_raman_normalisation()). An error will occur if trying to perform blank correction after Raman normalization.

References

Murphy, K. R., Stedmon, C. a., Graeber, D., & Bro, R. (2013). Fluorescence spectroscopy and multi-way techniques. PARAFAC. Analytical Methods, 5(23), 6557. http://doi.org/10.1039/c3ay41160e

http://xlink.rsc.org/?DOI=c3ay41160e

Examples

## Example 1

# Open the fluorescence eem
file <- system.file("extdata/cary/scans_day_1", "sample1.csv", package = "eemR")
eem <- eem_read(file, import_function = "cary")

plot(eem)

# Open the blank eem
file <- system.file("extdata/cary/scans_day_1", "nano.csv", package = "eemR")
blank <- eem_read(file, import_function = "cary")

plot(blank)

# Remove the blank
eem <- eem_remove_blank(eem, blank)

plot(eem)

## Example 2

# Open the fluorescence eem
folder <- system.file("extdata/cary/scans_day_1", package = "eemR")
eems <- eem_read(folder, import_function = "cary")

plot(eems, which = 3)

# Open the blank eem
file <- system.file("extdata/cary/scans_day_1", "nano.csv", package = "eemR")
blank <- eem_read(file, import_function = "cary")

plot(blank)

# Remove the blank
eems <- eem_remove_blank(eems, blank)

plot(eems, which = 3)

# Automatic correction
folder <- system.file("extdata/cary/", package = "eemR")

# Look at the folder structure
list.files(folder, "*.csv", recursive = TRUE)
#> [1] "scans_day_1/nano.csv"    "scans_day_1/sample1.csv"
#> [3] "scans_day_1/sample2.csv" "scans_day_1/sample3.csv"
#> [5] "scans_day_2/blank.csv"   "scans_day_2/s1.csv"     

eems <- eem_read(folder, recursive = TRUE, import_function = "cary")
res <- eem_remove_blank(eems)
#> A total of 1 blank EEMs will be averaged.
#> A total of 1 blank EEMs will be averaged.