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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
File size: 4876 byte(s)
new Rd produced by roxygen2
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ChemosensorsClass.R, R/ChemosensorsClassMethods.R, R/SensorArrayClass.R, R/SensorArrayClassMethods.R
\title{Method getSensor.}
getSensor(object, index)

affinity(object, ...)

\S4method{affinity}{ANY}(object, concUnits = "norm", gases = 0,
  type = "inc", n = 300, ...)


\S4method{initialize}{SensorArray}(.Object, type = "character",
  enableSorption = "logical", nsensors = "numeric", num = "numeric",
  gases = "numeric", gnames = "character", concUnits = "character",
  concUnitsInt = "character", concUnitsIntSorption = "character",
  knum = "numeric", model = "character", datasetSensorModel = "character",
  datasetDistr = "character", datasetSensorNoiseModel = "character",
  pck = "character", Conc0, Conc, dat, sndata, coefsd, ...)


Sensor(num = 1, ...)

\S4method{getSensor}{SensorArray}(object, index)
\item{...}{parameters of constructor.}

\item{num}{Type of sensors (or UNIMAN number).}
List of the default parameters.
Method getSensor.

Method affinity.

Class \code{SensorArray} is a extension of the class \code{\link{Sensor}} for many sensor elements.

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

Constructor method of SensorArray Class.

Wrapper function SensorArray.

Wrapper function Sensor
The array aggregates classes \code{\link{ConcNoiseModel}}, \code{\link{SensorNoiseModel}}, 
\code{\link{SorptionModel}}, \code{\link{SensorModel}} and \code{\link{DriftNoiseModel}}.

In comparision to the class \code{\link{Sensor}}, slot \code{num} is a numeric vector, 
and class \code{SensorArray} also inherits class \code{\link{DriftNoiseModel}}.

See \code{\link{Sensor}} and \code{\link{DriftNoiseModel}} for more details.

Slots of the class:
  \code{type} \tab Sensor type (not used). Default value is \code{polymeric}. \cr
  \code{idx} \tab Sensor index (unique ID number). \cr
  \code{enableSorption} \tab Boolean whether \code{\link{SorptionModel}} is enabled. Default value is \code{TRUE}. \cr
  \code{...} \tab Slots inherited from super-classes \code{\link{ConcNoiseModel}}, \code{\link{SensorNoiseModel}}, 
    \code{\link{SorptionModel}}, \code{\link{SensorModel}} and \code{\link{DriftNoiseModel}}. \cr

Methods of the class:
  \code{predict} \tab Predicts a model response to an input concentration matrix. \cr
  \code{coef} \tab Extracts the coefficient matrix from sensors. \cr
  \code{csd} \tab Gets the concentration noise level (inherited from class \code{\link{ConcNoiseModel}}). \cr
  \code{csd<-} \tab Sets the concentration noise level. \cr
  \code{ssd} \tab Gets the sensor noise level (inherited from class \code{\link{SensorNoiseModel}}). \cr
  \code{ssd<-} \tab Sets the sensor noise level. \cr

The \code{plot} method has the only type (parameter \code{y}):
  \code{response} \tab (default) Shows the sensitivity curves per gas in normalized concentration units. \cr

# array: default initialization
sa <- SensorArray()

# get information about the array

print(coef(sa)) # array coefficients


# model: custom parameters
sa <- SensorArray(num=1:17) # 17 UNIMAN virtual sensors
plot(sa, main="17 UNIMAN virtual sensors")

# array with quite linear sensors
sa <- SensorArray(num=15:17, alpha=0.01, model="mvr") 

# add UNIMAN reference data (the models were build from)
p1 <- plotResponse(sa, main="Array of more linear sensors") 
# sensor object: default initialization
s <- Sensor()

# get information about the sensor


# sensor object: custom parameters
s <- Sensor(num=5, enableSorption=FALSE) # sorption model disabled
plot(s, main="Sensor with sorption model disabled")

s <- Sensor(num=5, alpha=0.01) # amost linear sensor
plot(s, main="Almost linear sensor, non-linearity 0.01")

s <- Sensor(num=5, alpha=1) # saturated sensor
plot(s, main="Saturated sensor, non-linearity 1")

s <- Sensor(num=5, csd=0, ssd=0, dsd = 0) # noise level is set to zero
plot(s, "snoise", main="Noise-free sensor")

s <- Sensor(num=5, csd=1, ssd=1, dsd = 0) # maximum reasonable level of noise
plot(s, "snoise", main="Very noisy sensor")

# method plot
#  - plot types 'y': response, noise
s <- Sensor() # default model

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

plot(s, "snoise", main="plot(s, 'snoise')")

\code{\link{Sensor}}, \code{\link{DriftNoiseModel}}

\code{\link{SensorArray}}, \code{\link{SensorModel}}
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