Description Usage Format Details Inheritance Fields Methods See Also Examples

The `R6Class`

object `elementR_sample`

contains the main information needed for the filtration of a single sample replicate.

1 |

An `R6Class`

generator object

As a subclass object, the `elementR_sample`

object already contains the whole fields and methods from the `elementR_data`

. Moreover, it also contains items specifically designed for sample filtration.

The `elementR_sample`

object inherits from the `elementR_data`

`type`

A character string corresponding to the type of replicate (here, "sample")

`dataConc`

A matrix corresponding to the

`dataNorm`

converted in concentration

`dataConcCorr`

A matrix corresponding to the

`dataConc`

corrected (or not) from the machine drift

`setDataConc(bins, plat, calibFile, meanStand, rempl)`

Aim: set

`dataConc`

; Arguments: bins = a numerical value corresponding to the time at which end the blank values, plat = a vector of two numerical values corresponding respectively to the time at which begin and end the plateau, calibFile = a matrix corresponding to the data of the calibration file, meanStand = a vector containing the averaged signal intensity per chemical element for all standard replicates of the running session, rempl = the value replacing data if below the limit of detection

`setDataConcCorr(bins, plat, name, calibFile, meanStand, rankSample, rankStandard, model, correction, rempl, threshold)`

Aim: set

`dataConcCorr`

; Arguments: bins = a numerical value corresponding to the time at which end the blank values, plat = a vector of two numerical values corresponding respectively to the time at which begin and end the plateau, name = a character string corresponding to the name of the sample replicates, calibFile = a matrix corresponding to the the calibration file, meanStand = a vector containing the averaged signal intensity per chemical element for all standard replicates of the running session, rankSample = a vector containing the rank of each sample in ICPMS analysis, rankStandard = a vector containing the rank of each standard in ICPMS analysis, correction = a vector indicating the chemical elements to correct from machine drift, model = a matrix containing the parameters of the linear regression corresponding to the machine drift for all chemical elements, threshold = the R2 threshold to consider that the model does not fit to a linear model

`renderData(curve)`

Aim: render data without proceding to their calculation; Argument: curve = a character string corresponding to the type of data to render ("Blank" for calculate and/or render the

`dataBlank`

, "Raw" for`data`

, "Plateau" for`dataPlateau`

, "Blank removed" for`dataSuppBlank`

, ">LOD" for`dataSupLOD`

, "Normalized" for`dataNorm`

, "Concentration" for`dataConc`

and "Conc. corrected" for`dataConcCorr`

); Output: a matrix of the required data

`getData(curve, bins, plat, name, calibFile, meanStand, rankSample, rankStandard, model, correction)`

Aim: calculate and render the required data ; Arguments: curve = a character string corresponding to the type of data to calculate (for more details, see renderData arguments), bins = a numerical value corresponding to the time at which end the blank values, plat = a vector of two numerical values corresponding respectively to the time at which begin and end the plateau, name = a character string corresponding to the name of the sample replicates, calibFile = a matrix corresponding to the the calibration file, meanStand = a vector containing the averaged signal intensity per chemical element for all standard replicates of the running session, rankSample = a vector containing the rank of each sample in ICPMS analysis, rankStandard = a vector containing the rank of each standard in ICPMS analysis, correction = a vector indicating the chemical elements to correct from machine drift, model = a matrix containing the parameters of the linear regression corresponding to the machine drift for all chemical elements, threshold = the R2 threshold to consider that the model does not fit to a linear model

`elementR_data`

.
`elementR_standard`

.

1 2 3 4 5 6 7 8 9 10 | ```
## create a new elementR_sample object based on the "filePath" from a file containing data
## replicate (accepted format of data: .csv, .ods, .xls, .xlsx)
filePath <- system.file("Example_Session/samples/Sample_1/Sample1_Rep1.csv", package="elementR")
sampleExample <- elementR_sample$new(filePath)
## Display the name of the object
sampleExample$name
``` |

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