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Revision 55 - (download) (as text) (annotate)
Wed Mar 2 14:48:07 2016 UTC (2 years, 11 months ago) by variani
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new Rd produced by roxygen2
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ChemosensorsClass.R, R/SensorNoiseModelClass.R, R/SensorNoiseModelClassMethods.R
\docType{class}
\name{SensorNoiseModel-class}
\alias{SensorNoiseModel}
\alias{SensorNoiseModel-class}
\alias{defaultSensorNoiseModel}
\alias{noisef,SensorNoiseModel-method}
\title{Method noisef.}
\usage{
noisef(x)

\S4method{noisef}{SensorNoiseModel}(x)

defaultSensorNoiseModel()

\S4method{initialize}{SensorNoiseModel}(.Object, num = "numeric",
  gases = "numeric", gnames = "character", concUnits = "character",
  concUnitsInt = "character", datasetSensorNoiseModel = "character",
  pck = "character", ssd = "numeric", sntype = "character",
  snf = "numeric", sndata, nsd = "numeric", ...)

SensorNoiseModel(...)
}
\arguments{
\item{...}{parameters of constructor.}
}
\value{
List of the default parameters.
}
\description{
Method noisef.

Class \code{SensorNoiseModel} simulates a degradation in the performance of an individual sensor 
by generating noise in the sensitivity coefficients. This class is a super-class of the class \code{Sensor}.

Function to get default constructor parameters of class \code{\link{SensorNoiseModel}}.

Constructor method of SensorNoiseModel Class.

Wrapper function SensorNoiseModel.
}
\details{
Slots of the class:
\tabular{rl}{
  \code{num} \tab Sensor number (\code{1:17}), which noise profile is used. The default value is \code{1}. \cr
  \code{gases} \tab Gas indices. \cr
  \code{ngases} \tab The number of gases. \cr
  \code{gnames} \tab Names of gases. \cr
  \code{concUnits} \tab Concentration units external to the model. \cr
  \code{concUnitsInt} \tab Concentration units internal for the model, values used to evaluate the statistics on coefficients. \cr
  \code{ssd} \tab Parameter of standard deviation used to generate the noise. The deault value is 0.1. \cr
  \code{sntype} \tab Noise type (\code{randomWalk}). \cr
  \code{snf} \tab Scaling factor for the amplitude to generate the noise. The default value is \code{c(1, 1, 0.2)}. \cr
  \code{sndata} \tab The reference data of standard deviation values from UNIMAN dataset (see \code{\link{UNIMANsnoise}}). \cr
}

Methods of the class:
\tabular{rl}{
  \code{predict} \tab Generates noise vectors of a given length. \cr
  \code{ssd} \tab Gets the noise level. \cr
  \code{ssd<-} \tab Sets the noise level. \cr
  \code{ncoef} \tab Gets the number of coefficients. \cr
}

The \code{plot} method has three types (parameter \code{y}):
\tabular{rl}{
  \code{barplot} \tab (default) Shows distribution of sd values stored in slot \code{sndata}. \cr
  \code{noise} \tab Depicts the noise vectors generated by the model. \cr
  \code{walk} \tab  Shows the random walk on a scatterplot for two given coefficients. \cr
}
}
\examples{
# model: default initialization
sn <- SensorNoiseModel()

# get information about the model
show(sn)
print(sn)

plot(sn)  

# model: custom parameters
# - many sensors
sn <- SensorNoiseModel(ssd=0.5, num=1:17, gases=c(1, 2, 3))

print(sn)

plot(sn)

# method plot
#  - plot types 'y': barplot, noise, walk
sn <- SensorNoiseModel() # default model

plot(sn, "barplot", main="plot(sn, 'barplot')") 
# default plot type, i.e. 'plot(sn)' does the same plotting

plot(sn, "noise", main="plot(sn, 'noise')")

set.seed(6) # make results reproducible
plot(sn, "walk", n=100, k=5, main="plot(sn, 'walk', n=100, k=5)")
  
}
\seealso{
\code{\link{UNIMANsnoise}}, \code{\link{Sensor}}
}


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