The single laser shots of 20 of the measurements of forageLIBS: 8 shots per measurement, in two wavelength windows, to study the shot-to-shot variability and the rejection of outlying shots.
Format
A tibble with 160 rows (shots) and 844 columns:
- Measurement
Measurement identifier, as in forageLIBS.
- Sample
Sample identifier, as in forageLIBS.
- shot
Shot number in the measurement (1 to 8), in firing order.
- Ca, K
Calcium and potassium contents, in percent.
- 380.011254, ..., 779.977295
Emission intensity (counts) at each wavelength, in nm.
Source
Laboratory LIBS measurements provided by Christian L. Goueguel.
The script data-raw/forageShots.R in the package source builds the
data set from the shot-level export.
Details
forageLIBS holds the mean of the 8 shots of each measurement; these are
the shots themselves, raw detector counts, in the order in which they
were fired. To keep the package small, only two windows are kept:
380 to 430 nm (Ca II 393.37 and 396.85 nm, Ca I 422.67 nm, Al I 394.40
and 396.15 nm, the CN band at 388 nm) and 760 to 780 nm (K I 766.49 and
769.90 nm, O I 777 nm). The strongest lines reach the saturation of the
detector (65535 counts) in most shots (132 of the 160); the wavelength
argument of reject_shots() can leave them out.
The 20 measurements are those of the 368 with a shot rejected by
reject_shots() in these windows (7), and 13 others drawn at random:
their outlying shots are weak or strong plasmas (total intensity 0.7 or
1.3 times that of the other shots) with spectra of a different shape.
Examples
data(forageShots)
dim(forageShots)
#> [1] 160 844
# the shot-to-shot variability of the total intensity, per measurement
total <- rowSums(forageShots[-(1:5)])
round(tapply(total, forageShots$Measurement, function(v) 100 * sd(v) / mean(v)), 1)
#> 121022 121041 121080 121089 121117 121138 121140 121144 121163 121238 121306
#> 4.7 6.1 9.3 7.7 7.2 10.9 5.0 11.3 12.3 15.7 12.7
#> 121318 121319 121322 121323 121367 121382 121440 121618 121645
#> 4.8 6.6 5.7 7.7 9.3 11.8 6.6 8.6 12.1