Normalization of given data

Maps the given time-intensity data into a rescaled dataframe where time is scaled to between 0 and 1, and intensity is scaled to be between 0 and 1.

Usage

normalizeData(dataInput, dataInputName = NA)

Arguments

dataInput

A dataframe or a list containing the dataframe. The data frame should be composed of at least two columns. One represents time, and the other represents intensity.

dataInputName

experiment name (Default is 'NA').

Value

Function returns a new dataframe, scaling factors and scaling constants that connects the initial data frame to the new one. The new data frame includes 2 columns: normalized time and normalized intensity. The time and intensity constants and scaling factors are the parameters to transform data from the unnormalized dataframe to normalized data frame.

Examples

# runif() is used here for consistency with previous versions of the sicegar package. However,
# rnorm() will generate symmetric errors, producing less biased numerical parameter estimates.
# We recommend errors generated with rnorm() for any simulation studies on sicegar.
# generateRandomData
time <- seq(3, 48, 0.5)
intensity <- runif(length(time), 3.0, 7.5)
dataInput <- data.frame(time, intensity)

# Normalize Data
dataOutput <- normalizeData(dataInput, dataInputName="sample001")