PIOutputMapping

Establishes connections between simulated quantities and corresponding observed data sets. Utilized within ParameterIdentification instances to align and compare simulation outputs with empirical data.

Active bindings

observedDataSets

A named list containing DataSet objects for comparison with simulation outcomes.

dataTransformations

A named list of factors and offsets.

dataWeights

A named list of y-value weights.

quantity

Simulation quantities to be aligned with observed data values.

simId

Identifier of the simulation associated with the mapped quantity.

scaling

Specifies scaling for output mapping: linear (default) or logarithmic.

transformResultsFunction

A function to preprocess simulated results (time and observation values) before residual calculation. It takes numeric vectors xVals and yVals, and returns a named list with keys xVals and yVals.

Methods

Public methods

• PIOutputMapping$new()

• PIOutputMapping$addObservedDataSets()

• PIOutputMapping$removeObservedDataSet()

• PIOutputMapping$setDataTransformations()

• PIOutputMapping$setDataWeights()

• PIOutputMapping$print()

• PIOutputMapping$clone()

---

Method new()

Initialize a new instance of the class.

Usage

PIOutputMapping$new(quantity)

Arguments

quantity

An object of the type Quantity.

Returns

A new PIOutputMapping object. Adds or updates observed data using DataSet objects.

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Method addObservedDataSets()

Usage

PIOutputMapping$addObservedDataSets(data, weights = NULL)

Arguments

data

A DataSet object or a list thereof, matching the simulation quantity dimensions.

weights

A named list of numeric values or numeric vectors. The names must match the names of the observed datasets.

Details

Replaces any existing dataset with the same label.

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Method removeObservedDataSet()

Removes specified observed data series.

Usage

PIOutputMapping$removeObservedDataSet(label)

Arguments

label

The label of the observed data series to remove.

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Method setDataTransformations()

Configures transformations for datasets.

Usage

PIOutputMapping$setDataTransformations(
  labels = NULL,
  xOffsets = 0,
  yOffsets = 0,
  xFactors = 1,
  yFactors = 1
)

Arguments

labels

List of dataset labels for targeted transformations. Absence of labels applies transformations globally.

xOffsets

Numeric list/value for X-offset adjustments.

yOffsets

Numeric list/value for Y-offset adjustments.

xFactors

Numeric list/value for X-scaling factors.

yFactors

Numeric list/value for Y-scaling factors.

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Method setDataWeights()

Assigns weights to observed data sets for residual weighting during parameter identification.

Usage

PIOutputMapping$setDataWeights(weights)

Arguments

weights

A named list of numeric values or numeric vectors. The names must match the names of the observed datasets.

Each element in the list can be:

• a scalar, which will be broadcast to all y-values of the corresponding dataset,

• or a numeric vector matching the number of y-values for that dataset.

To apply both dataset-level and point-level weights, multiply them beforehand and provide the combined result as a single numeric vector per dataset.

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Method print()

Prints a summary of the PIOutputMapping.

Usage

PIOutputMapping$print()

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Method clone()

The objects of this class are cloneable with this method.

Usage

PIOutputMapping$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.