Package 'Slick'

Run the Slick App in the local browser

Description

An online hosted version of the Slick App is available here

Usage

App(...)

Arguments

...	Additional arguments. To load a object directly in the App, use App(slick=myslick) where myslick is your Slick-class() object.

Details

App() runs the Slick Shiny Application

Value

None

---

Methods for Creating, Accessing and Assigning Boxplot objects

Description

The Boxplot function is used both to create and modify an Boxplot-class() object. and to access and assign Boxplot for an object of class Slick-class(). See Details.

Usage

Boxplot(
  Code = "",
  Label = "",
  Description = "",
  Value = array(),
  Preset = list(),
  Defaults = list("overall", "boxplot"),
  Misc = list()
)

Boxplot(Slick) <- value

## S4 method for signature 'missing'
Boxplot()

## S4 method for signature 'character_list'
Boxplot(
  Code = "",
  Label = "",
  Description = "",
  Value = array(),
  Preset = list(),
  Defaults = list("overall", "boxplot"),
  Misc = list()
)

## S4 method for signature 'Slick'
Boxplot(Code)

## S4 replacement method for signature 'Slick'
Boxplot(Slick) <- value

Arguments

Code	A short code for the Performance Indicators for this object. A character string length nPI or a named list for multi-language support. See Details
Label	A short label for the Performance Indicators for this object. Used to label axes on charts. Can be longer than Code but recommended to keep short as possible so it shows clearly in plots and tables. A character string length nPI or a named list for multi-language support. See Details
Description	A description for the Performance Indicators for this object. Can include Markdown, see Examples. A character string length nPI or a named list for multi-language support. See Details
Value	A numeric array with the stochastic performance indicator values for each simulation (sim), operating model (OM), management procedure (MP), and performance indicator (PI). Dimensions: c(nsim, nOM, nMP, and nPI).
Preset	An optional named list for the preset buttons in the App(). The name of the list element will appear as a button in the App().
Defaults	A list object with default selections for the Boxplot
Misc	A named list for additional miscellaneous information.
Slick	A Slick-class() object
value	A Boxplot-class() object

Details

Objects of class Boxplot are created with Boxplot()

Use plotBoxplot() to create the boxplot from the console.

Use the Code(), Label(), Description(), Value(), Preset() functions to access and assign the values for an existing Boxplot object, see Examples

Multi-Language Support

Text with multi-language supported can be provided as a named list. Available languages:

• en: English (default)

• es: Spanish

• fr: French

• pt: Portuguese

Note

Character strings in Code, Label, and Description must all be same length as the number of performance indicators (nPIs) in 'Value

Defaults

Defaults is used to select the plot options that are selected in the Boxplot. It is a list of length 2, with the following requirements for the list elements:

1. A character string. Options: 'overall' (default) or 'byom'

2. A character string. Options: 'boxplot' (default), 'violin', or 'both'

If unrecognized values are entered, the defaults will be used.

Functions

• Boxplot(missing): Create an empty Boxplot object

• Boxplot(character_list): Create a populated Boxplot object

• Boxplot(Slick): Return Boxplot from a Slick-class() object

• Boxplot(Slick) <- value: Assign a Boxplot-class() object to a Slick-class() object

See Also

Code(), Label(), Description(), Metadata(), Value(), Preset(), Defaults(), plotBoxplot()

Examples

# Generate dummy values
nsim <- 10
nOM <- 2
nMP <- 4
nPI <- 3

values <- array(NA, dim=c(nsim, nOM, nMP, nPI))
pi_means <- runif(nPI, 5, 50)
for (om in 1:nOM) {
  for (mp in 1:nMP) {
    for (pi in 1:nPI) {
      values[,om, mp, pi] <- rlnorm(nsim, log(pi_means[pi]), 0.4)
    }
  }
}

# Create and populate Object
boxplot <- Boxplot(Code=c('PI1', 'PI2', 'PI3'),
                   Label=c('Performance Indicator 1',
                           'Performance Indicator 2',
                           'Performance Indicator 3'),
                   Description = c('This is the description for PI 1',
                                   'This is the description for PI 2',
                                   'This is the description for PI 3'),
                   Value=values)

# Check
Check(boxplot)

# Add to `Slick` object
slick <- Slick()
Boxplot(slick) <- boxplot

# Plots
plotBoxplot(slick)

plotBoxplot(slick, type='violin')

plotBoxplot(slick, byOM=TRUE)

plotBoxplot(slick, 2, type='both', byOM=TRUE)

---

Boxplot S4 Object Class

Description

Objects of class Boxplot are used to store information for the Boxplot and Violin plots. Like all S4 objects in Slick, slots in this object can be accessed and assigned using functions corresponding to slot name. See Boxplot() and the the ⁠See Also⁠ section below.

Details

Objects of class Boxplot are created with Boxplot()

Multi-Language Support

Text with multi-language supported can be provided as a named list. Available languages:

• en: English (default)

• es: Spanish

• fr: French

• pt: Portuguese

Note

Character strings in Code, Label, and Description must all be same length as the number of performance indicators (nPIs) in Value

Slots

Code

A short code for the Performance Indicators for this object. A character string length nPI or a named list for multi-language support. See Details

Label

A short label for the Performance Indicators for this object. Used to label axes on charts. Can be longer than Code but recommended to keep short as possible so it shows clearly in plots and tables. A character string length nPI or a named list for multi-language support. See Details

Description

A description for the Performance Indicators for this object. Can include Markdown, see Examples. A character string length nPI or a named list for multi-language support. See Details

Value

A numeric array with the stochastic performance indicator values for each simulation (sim), operating model (OM), management procedure (MP), and performance indicator (PI). Dimensions: c(nsim, nOM, nMP, and nPI).

Preset

An optional named list for the preset buttons in the App(). The name of the list element will appear as a button in the App().

Defaults

A list object with default selections for the Boxplot. See Boxplot()

Misc

A named list for additional miscellaneous information.

See Also

Boxplot(), Code(), Label(), Description(), Metadata(), Value(), Preset()

Examples

# Generate dummy values
nsim <- 10
nOM <- 2
nMP <- 4
nPI <- 3

values <- array(NA, dim=c(nsim, nOM, nMP, nPI))
pi_means <- runif(nPI, 5, 50)
for (om in 1:nOM) {
  for (mp in 1:nMP) {
    for (pi in 1:nPI) {
      values[,om, mp, pi] <- rlnorm(nsim, log(pi_means[pi]), 0.4)
    }
  }
}

# Create and populate Object
boxplot <- Boxplot(Code=c('PI1', 'PI2', 'PI3'),
                   Label=c('Performance Indicator 1',
                           'Performance Indicator 2',
                           'Performance Indicator 3'),
                   Description = c('This is the description for PI 1',
                                   'This is the description for PI 2',
                                   'This is the description for PI 3'),
                   Value=values)

# Check
Check(boxplot)

# Add to `Slick` object
slick <- Slick()
Boxplot(slick) <- boxplot

# Plots
plotBoxplot(slick)

plotBoxplot(slick, type='violin')

plotBoxplot(slick, byOM=TRUE)

plotBoxplot(slick, 2, type='both', byOM=TRUE)

---

Check an object for errors or issues

Description

Checks S4 objects to check for warnings and errors

Usage

Check(object, ...)

## S4 method for signature 'Boxplot'
Check(object, req_dims = c(NA, NA, NA, NA))

## S4 method for signature 'Kobe'
Check(object)

## S4 method for signature 'MPs'
Check(object)

## S4 method for signature 'OMs'
Check(object)

## S4 method for signature 'Quilt'
Check(object)

## S4 method for signature 'Tradeoff'
Check(object)

## S4 method for signature 'Timeseries'
Check(object)

## S4 method for signature 'Spider'
Check(object)

## S4 method for signature 'Slick'
Check(object)

Arguments

object	An object of class: Slick-class(), MPs-class(), OMs-class() or the six chart types: Boxplot-class(), Kobe-class(), Quilt-class(), Spider-class(), Timeseries-class(), and Tradeoff-class().
...	Additional arguments
req_dims	Required dimensions for Value slot. Used internally

Value

Prints messages to the console

Methods (by class)

• Check(Boxplot): Check Boxplot-class() objects for errors

• Check(Kobe): Check Kobe-class() objects for errors

• Check(MPs): Check MPs-class() objects for errors

• Check(OMs): Check OMs-class() objects for errors

• Check(Quilt): Check Quilt-class() objects for errors

• Check(Tradeoff): Check Tradeoff-class() objects for errors

• Check(Timeseries): Check Timeseries-class() objects for errors

• Check(Spider): Check Spider-class() objects for errors

• Check(Slick): Check Slick-class() objects for errors

Examples

slick <- Slick()
Check(slick)

---

Access or assign Code, Label, and Description for a valid object class

Description

Access or assign Code, Label, and Description for a valid object class

Usage

Code(object, lang = "en")

Code(object) <- value

Description(object, lang = "en")

Description(object) <- value

Label(object, lang = "en")

Label(object) <- value

## S4 method for signature 'Boxplot'
Code(object, lang = "en")

## S4 replacement method for signature 'Boxplot'
Code(object) <- value

## S4 method for signature 'Boxplot'
Description(object, lang = "en")

## S4 method for signature 'Boxplot'
Label(object, lang = "en")

## S4 replacement method for signature 'Boxplot'
Label(object) <- value

## S4 replacement method for signature 'Boxplot'
Description(object) <- value

## S4 method for signature 'Boxplot'
Misc(object)

## S4 replacement method for signature 'Boxplot'
Misc(object) <- value

## S4 method for signature 'Kobe'
Code(object, lang = "en")

## S4 replacement method for signature 'Kobe'
Code(object) <- value

## S4 method for signature 'Kobe'
Description(object, lang = "en")

## S4 replacement method for signature 'Kobe'
Description(object) <- value

## S4 method for signature 'Kobe'
Label(object, lang = "en")

## S4 replacement method for signature 'Kobe'
Label(object) <- value

## S4 method for signature 'Kobe'
Misc(object)

## S4 replacement method for signature 'Kobe'
Misc(object) <- value

## S4 method for signature 'MPs'
Code(object, lang = "en")

## S4 replacement method for signature 'MPs'
Code(object) <- value

## S4 method for signature 'MPs'
Label(object, lang = "en")

## S4 replacement method for signature 'MPs'
Label(object) <- value

## S4 method for signature 'MPs'
Description(object, lang = "en")

## S4 replacement method for signature 'MPs'
Description(object) <- value

## S4 method for signature 'Quilt'
Code(object, lang = "en")

## S4 replacement method for signature 'Quilt'
Code(object) <- value

## S4 method for signature 'Quilt'
Description(object, lang = "en")

## S4 replacement method for signature 'Quilt'
Description(object) <- value

## S4 method for signature 'Quilt'
Label(object, lang = "en")

## S4 replacement method for signature 'Quilt'
Label(object) <- value

## S4 method for signature 'Quilt'
Misc(object)

## S4 replacement method for signature 'Quilt'
Misc(object) <- value

## S4 method for signature 'Tradeoff'
Code(object, lang = "en")

## S4 replacement method for signature 'Tradeoff'
Code(object) <- value

## S4 method for signature 'Tradeoff'
Description(object, lang = "en")

## S4 replacement method for signature 'Tradeoff'
Description(object) <- value

## S4 method for signature 'Tradeoff'
Misc(object)

## S4 replacement method for signature 'Tradeoff'
Misc(object) <- value

## S4 method for signature 'Tradeoff'
Label(object, lang = "en")

## S4 replacement method for signature 'Tradeoff'
Label(object) <- value

## S4 method for signature 'Timeseries'
Code(object, lang = "en")

## S4 replacement method for signature 'Timeseries'
Code(object) <- value

## S4 method for signature 'Timeseries'
Description(object, lang = "en")

## S4 replacement method for signature 'Timeseries'
Description(object) <- value

## S4 method for signature 'Timeseries'
Label(object, lang = "en")

## S4 replacement method for signature 'Timeseries'
Label(object) <- value

## S4 method for signature 'Timeseries'
Misc(object)

## S4 replacement method for signature 'Timeseries'
Misc(object) <- value

## S4 method for signature 'Spider'
Code(object, lang = "en")

## S4 replacement method for signature 'Spider'
Code(object) <- value

## S4 method for signature 'Spider'
Description(object, lang = "en")

## S4 replacement method for signature 'Spider'
Description(object) <- value

## S4 method for signature 'Spider'
Label(object, lang = "en")

## S4 replacement method for signature 'Spider'
Label(object) <- value

## S4 method for signature 'Spider'
Misc(object)

## S4 replacement method for signature 'Spider'
Misc(object) <- value

Arguments

object	An object of class MPs-class(), Boxplot-class(), Kobe-class(), Quilt-class(), Spider-class(), Timeseries-class(), or Tradeoff-class()
lang	Optional text string specifying the language (if available). Either 'en', 'es', 'fr', or 'pt' for English, Spanish, French, or Portuguese respectively
value	A character vector or a named list for multi-language support

Details

Code, Label, and Description must all be equal length.

Multi-Language Support

Text with multi-language supported can be provided as a named list. Available languages:

• en: English (default)

• es: Spanish

• fr: French

• pt: Portuguese

Value

Returns character string or named list with the contents of the Code, Label, or Description slot of object

Methods (by class)

• Code(Boxplot): Return Code from a Boxplot-class() object

• Code(Boxplot) <- value: Assign Code to a Boxplot-class() object

• Description(Boxplot): Return Description from a Boxplot-class() object

• Label(Boxplot): Return Label from a Boxplot-class() object

• Label(Boxplot) <- value: Assign Label to a Boxplot-class() object

• Description(Boxplot) <- value: Assign Description to a Boxplot-class() object

• Misc(Boxplot): Return Misc from a Boxplot-class() object

• Misc(Boxplot) <- value: Assign Misc to a Boxplot-class() object

• Code(Kobe): Return Code from a Kobe-class() object

• Code(Kobe) <- value: Assign Code to a Kobe-class() object

• Description(Kobe): Return Description from a Kobe-class() object

• Description(Kobe) <- value: Assign Description to a Kobe-class() object

• Label(Kobe): Return Label from a Kobe-class() object

• Label(Kobe) <- value: Assign Label to a Kobe-class() object

• Misc(Kobe): Return Misc from a Kobe-class() object

• Misc(Kobe) <- value: Assign Misc to a Kobe-class() object

• Code(MPs): Return Code from a MPs-class() object

• Code(MPs) <- value: Assign Code to a MPs-class() object

• Label(MPs): Return Label from a MPs-class() object

• Label(MPs) <- value: Assign Label to a MPs-class() object

• Description(MPs): Return Description from a MPs-class() object

• Description(MPs) <- value: Assign Description to a MPs-class() object

• Code(Quilt): Return Code from a Quilt-class() object

• Code(Quilt) <- value: Assign Code to a Quilt-class() object

• Description(Quilt): Return Description from a Quilt-class() object

• Description(Quilt) <- value: Assign Description to a Quilt-class() object

• Label(Quilt): Return Label from a Quilt-class() object

• Label(Quilt) <- value: Assign Label to a Quilt-class() object

• Misc(Quilt): Return Misc from a Quilt-class() object

• Misc(Quilt) <- value: Assign Misc to a Quilt-class() object

• Code(Tradeoff): Return Code from a Tradeoff-class() object

• Code(Tradeoff) <- value: Assign Code to a Tradeoff-class() object

• Description(Tradeoff): Return Description from a Tradeoff-class() object

• Description(Tradeoff) <- value: Assign Description to a Tradeoff-class() object

• Misc(Tradeoff): Return Misc from a Tradeoff-class() object

• Misc(Tradeoff) <- value: Assign Misc to a Tradeoff-class() object

• Label(Tradeoff): Return Label from a Tradeoff-class() object

• Label(Tradeoff) <- value: Assign Label to a Tradeoff-class() object

• Code(Timeseries): Return Code from a Timeseries-class() object

• Code(Timeseries) <- value: Assign Code to a Timeseries-class() object

• Description(Timeseries): Return Description from a Timeseries-class() object

• Description(Timeseries) <- value: Assign Description to a Timeseries-class() object

• Label(Timeseries): Return Label from a Timeseries-class() object

• Label(Timeseries) <- value: Assign Label to a Timeseries-class() object

• Misc(Timeseries): Return Misc from a Timeseries-class() object

• Misc(Timeseries) <- value: Assign Misc to a Timeseries-class() object

• Code(Spider): Return Code from a Spider-class() object

• Code(Spider) <- value: Assign Code to a Spider-class() object

• Description(Spider): Return Description from a Spider-class() object

• Description(Spider) <- value: Assign Description to a Spider-class() object

• Label(Spider): Return Label from a Spider-class() object

• Label(Spider) <- value: Assign Label to a Spider-class() object

• Misc(Spider): Return Misc from a Spider-class() object

• Misc(Spider) <- value: Assign Misc to a Spider-class() object

See Also

Label(), Description(), MPs-class(), Boxplot-class(), Kobe-class(), Quilt-class(), Spider-class(), Timeseries-class(), Tradeoff-class()

---

Access or assign Color for MPs and Quilt objects

Description

Access or assign Color for MPs and Quilt objects

Usage

Color(object)

Color(object) <- value

## S4 method for signature 'MPs'
Color(object)

## S4 replacement method for signature 'MPs'
Color(object) <- value

## S4 method for signature 'Quilt'
Color(object)

## S4 replacement method for signature 'Quilt'
Color(object) <- value

Arguments

object	An MPs-class() or Quilt-class() object
value	A character vector formatted to match the class of object. See the documentation for corresponding object class for more details.

Value

Returns a character string with the contents of the Color slot of object

Methods (by class)

• Color(MPs): Return Color from a MPs-class() object

• Color(MPs) <- value: Preset Assign Color to a MPs-class() object

• Color(Quilt): Return Color from a Quilt-class() object

• Color(Quilt) <- value: Preset Assign Color to a Quilt-class() object

---

Set Default Colors for the MPs

Description

Requires the colorspace package

Usage

default_mp_colors(nMP)

Arguments

nMP	The number of management procedures

Value

A character vector of length nMP with color hex codes

Examples

cols <- default_mp_colors(4)
cols

---

Access or assign the default selections for the plots in the App()

Description

Access or assign the default selections for the plots in the App()

Usage

Defaults(object)

Defaults(object) <- value

## S4 method for signature 'Boxplot'
Defaults(object)

## S4 replacement method for signature 'Boxplot'
Defaults(object) <- value

## S4 method for signature 'Kobe'
Defaults(object)

## S4 replacement method for signature 'Kobe'
Defaults(object) <- value

Arguments

object	A Boxplot() or Kobe() object
value	A list of default selections for the App()

Value

Returns a list object with default selections from the Defaults slot of Boxplot() and Kobe() objects.

Methods (by class)

• Defaults(Boxplot): Defaults Code from a Boxplot-class() object

• Defaults(Boxplot) <- value: Assign Defaults to a Boxplot-class() object

• Defaults(Kobe): Defaults Code from a Kobe-class() object

• Defaults(Kobe) <- value: Assign Defaults to a Kobe-class() object

---

Return the Design matrix from an OMs object

Description

Return the Design matrix from an OMs object

Usage

Design(object)

Design(object) <- value

## S4 method for signature 'OMs'
Design(object)

## S4 replacement method for signature 'OMs'
Design(object) <- value

## S4 method for signature 'Slick'
Design(object)

## S4 replacement method for signature 'Slick'
Design(object) <- value

Arguments

object	A Slick-class() object
value	A data.frame with the Design matrix

Value

The Design matrix from an OMs object in a Slick object

Methods (by class)

• Design(OMs): Return the operating model Design matrix from a OMs-class() object

• Design(OMs) <- value: Assign the operating model Design matrix to a OMs-class() object

• Design(Slick): Access the operating model Design matrix from a Slick-class() object

• Design(Slick) <- value: Assign the operating model Design matrix to a Slick-class() object

---

Return the Factors matrix from an OMs object

Description

Return the Factors matrix from an OMs object

Usage

Factors(object, lang = "en")

Factors(object) <- value

## S4 method for signature 'OMs'
Factors(object, lang = "en")

## S4 replacement method for signature 'OMs'
Factors(object) <- value

## S4 method for signature 'Slick'
Factors(object, lang = "en")

## S4 replacement method for signature 'Slick'
Factors(object) <- value

Arguments

object	A Slick-class() object
lang	Optional text string specifying the language (if available). Either 'en', 'es', 'fr', or 'pt' for English, Spanish, French, or Portuguese respectively
value	A data.frame with the Factors

Value

The Design matrix from an OMs object in a Slick object

Methods (by class)

• Factors(OMs): Return the operating model Factors table from a OMs-class() object

• Factors(OMs) <- value: Assign the operating model Factors table to a OMs-class() object

• Factors(Slick): Access the operating model Factors table from a Slick-class() object

• Factors(Slick) <- value: Assign the operating model Factors table to a Slick-class() object

---

FilterSlick

Description

Filter a Slick Object

Usage

FilterSlick(slick = NULL, MPs = NULL, OMs = NULL, PIs = NULL, plot = NULL)

Arguments

slick	An object of class Slick
MPs	Numeric values of the MPs to keep. Default NULL keeps all MPs.
OMs	Numeric values of the OMs to keep (rows of OM@Design). Default NULL keeps all OMs.
PIs	Numeric values of the PIs in plot to keep. Default NULL keeps all PIs.
plot	The plot to filter the PIs. One of: Timeseries, Boxplot, Kobe, Quilt, Spider, orTradeoff

Details

Filter a Slick Object by management procedures (MPs), operating models (OMs), and performance indicators (PIs) for a given plot

Value

A filtered Slick Object

Examples

slick <- Slick() # a completed slick object
boxplot_OM_1 <- FilterSlick(slick, OMs=1, plot='boxplot')

---

Get Case Studies from the SlickLibrary GitHub Repo

Description

Get Case Studies from the SlickLibrary GitHub Repo

Usage

get_casestudies()

download_casestudy(
  name,
  case_studies = NULL,
  dir = NULL,
  silent = FALSE,
  object = TRUE,
  delete = object
)

Arguments

name	The name of the case study to download. Name column from get_casestudies()
case_studies	optional. Dataframe returned by get_casestudies()
dir	Optional. Directory to save the file. Defaults to a temporary directory
silent	Logical. Print out messages?
object	Logical. Return the Slick object? Default downloads Slick object to a temporary location, loads and returns the Slick object, and then deletes downloaded file.
delete	Logical. Delete the downloaded file after function finishes? Only useful if object = TRUE

Value

A data.frame for get_casestudies and a Slick object for download_casestudy

The downloaded Slick object if object==TRUE, otherwise nothing.

Functions

• download_casestudy(): download a case study file

Examples

case_studies <- get_casestudies()
slick <- download_casestudy(case_studies$Name[1])

---

Methods for Creating, Accessing and Assigning Kobe objects

Description

The Kobe function is used both to create and modify an Kobe-class() object. and to access and assign Kobe for an object of class Slick-class(). See Details.

Usage

Kobe(
  Code = "",
  Label = "",
  Description = "",
  Time = numeric(),
  TimeLab = "Year",
  Value = array(),
  Preset = list(),
  Target = 1,
  Limit = NULL,
  Defaults = list(),
  TimeTerminal = numeric(),
  Misc = list()
)

Kobe(Slick) <- value

## S4 method for signature 'missing'
Kobe()

## S4 method for signature 'character'
Kobe(
  Code = "",
  Label = "",
  Description = "",
  Time = numeric(),
  TimeLab = "Year",
  Value = array(),
  Preset = list(),
  Target = 1,
  Limit = NULL,
  Defaults = list(),
  TimeTerminal = numeric(),
  Misc = list()
)

## S4 method for signature 'list'
Kobe(
  Code = "",
  Label = "",
  Description = "",
  Time = numeric(),
  TimeLab = "Year",
  Value = array(),
  Preset = list(),
  Target = 1,
  Limit = NULL,
  Defaults = list(),
  TimeTerminal = numeric(),
  Misc = list()
)

## S4 method for signature 'Slick'
Kobe(Code)

## S4 replacement method for signature 'Slick'
Kobe(Slick) <- value

Arguments

Code	A short code for the Performance Indicators for this object. A character string length nPI or a named list for multi-language support. See Details
Label	A short label for the Performance Indicators for this object. Used to label axes on charts. Can be longer than Code but recommended to keep short as possible so it shows clearly in plots and tables. A character string length nPI or a named list for multi-language support. See Details
Description	A description for the Performance Indicators for this object. Can include Markdown, see Examples. A character string length nPI or a named list for multi-language support. See Details
Time	A numeric vector with values for the projection time-steps. Must match length nTS in Value
TimeLab	Character string length 1. Name of the time step (e.g., 'Year'). Will be used as the label in the ⁠Kobe Time⁠ plot. Use a named list for multiple languages.
Value	A numeric array with the stochastic performance indicator values for each simulation (sim), operating model (OM), management procedure (MP), performance indicator (PI), and projection time-steps (nTS). Dimensions: c(nsim, nOM, nMP, nPI, nTS)
Preset	An optional named list for the preset buttons in the App(). The name of the list element will appear as a button in the App().
Target	Numeric vector length nPI with the target value for the PIs. Defines the color quadrants on the Kobe plot. Defaults to c(1,1).
Limit	Numeric vector length nPI with the limit value for the PIs. Shows as red line on Kobe plot. NULL to ignore.
Defaults	A list object with default selections for the Kobe See Kobe()
TimeTerminal	Optional. By default the Kobe plot shows the terminal projection year. TimeTerminal can be used to override this. Use a numeric value indicating the time (must match a value in Time) to use for the Kobe plot
Misc	A named list for additional miscellaneous information.
Slick	A Slick-class() object
value	A Kobe-class() object

Details

Objects of class Kobe are created with Kobe()

The Kobe plot typically shows B/BMSY (or something similar) on the x-axis, and F/FMSY (or something similar) on the y-axis.

Performance Indicators

The first PI will be on the x-axis (usually B/BMSY or something similar) and the second on the y-axis (e.g., F/FMSY)

Multi-Language Support

Text with multi-language supported can be provided as a named list. Available languages:

• en: English (default)

• es: Spanish

• fr: French

• pt: Portuguese

Note

Character strings in Code, Label, and Description must all be same length as the number of performance indicators (nPIs) in Value

Functions

• Kobe(missing): Create an empty Kobe object

• Kobe(character): Create a populated Kobe object

• Kobe(list): Create a populated Kobe object

• Kobe(Slick): Return Kobe from a Slick-class() object

• Kobe(Slick) <- value: Assign a Kobe-class() object to a Slick-class() object

See Also

Code(), Label(), Description(), Time(), [TimeLab(), Value(), Preset(), Target() and Limit()

Examples

# Generate dummy values
nsim <- 10
nOM <- 2
nMP <- 4
nPI <- 2
nTS <- 30

values <- array(NA, dim=c(nsim, nOM, nMP, nPI, nTS))

pi_means <- c(1,1)

for (om in 1:nOM) {
  for (mp in 1:nMP) {
    for (pi in 1:nPI) {
      values[,om, mp, pi,] <- pi_means[pi] *
        matrix(
        cumprod(c(rlnorm(nTS*nsim, 0, 0.05))),
        nrow=nsim)
    }
  }
}

# Create and populate Object
kobe <- Kobe(Code=c('B/BMSY', 'F/FMSY'),
             Label=c('B/BMSY',
                     'F/FMSY'),
             Description = c('This is the description for PI 1',
                             'This is the description for PI 2'),
             Value=values
)

# Add values for projection time steps
Time(kobe) <- seq(2025, by=1, length.out=nTS)

# Check
Check(kobe)

# Add to `Slick` object
slick <- Slick()
Kobe(slick) <- kobe

# Plots
plotKobe(slick)

plotKobe(slick, Time=TRUE)

---

S4 class Kobe

Description

Slots can be accessed and assigned using functions corresponding to slot name. See ⁠See Also⁠ section below.

Details

Objects of class Kobe are created with Kobe()

Performance Indicators

By default, the first PI will be on the x-axis (usually B/BMSY or something similar) and the second on the y-axis (e.g., F/FMSY). The Slick App() provides drop down menus for selecting other PIs.

Multi-Language Support

Text with multi-language supported can be provided as a named list. Available languages:

• en: English (default)

• es: Spanish

• fr: French

• pt: Portuguese

Note

Character strings in Code, Label, and Description must all be same length as the number of performance indicators (nPIs) in Value

Slots

Code

A short code for the Performance Indicators for this object. A character string length nPI or a named list for multi-language support. See Details

Label

A short label for the Performance Indicators for this object. Used to label axes on charts. Can be longer than Code but recommended to keep short as possible so it shows clearly in plots and tables. A character string length nPI or a named list for multi-language support. See Details

Description

A description for the Performance Indicators for this object. Can include Markdown, see Examples. A character string length nPI or a named list for multi-language support. See Details

Time

A numeric vector with values for the projection time-steps. Must match length nTS in Value

TimeLab

Character string length 1. Name of the time step (e.g., 'Year'). Will be used as the label in the ⁠Kobe Time⁠ plot. Use a named list for multiple languages.

Value

A numeric array with the stochastic performance indicator values for each simulation (sim), operating model (OM), management procedure (MP), performance indicator (PI), and projection time-steps (nTS) Dimensions: c(nsim, nOM, nMP, nPI, nTS)

Preset

An optional named list for the preset buttons in the App(). The name of the list element will appear as a button in the App().

Target

Numeric vector length nPI with the target value for the PIs. Defines the color quadrants on the Kobe plot. Defaults to 1.

Limit

Numeric vector length nPI with the limit value for the two PIs. Shows as red line on Kobe plot. NULL to ignore.

Defaults

A list object with default selections for the Kobe See Kobe()

TimeTerminal

Optional. By default the Kobe plot shows the terminal projection year. TimeTerminal can be used to override this. Use a numeric value indicating the time (must match a value in Time) to use for the Kobe plot

Misc

A named list for additional miscellaneous information.

See Also

Kobe(), Code(), Label(), Description(), Value(), Preset()

Examples

# Generate dummy values
nsim <- 10
nOM <- 2
nMP <- 4
nPI <- 2
nTS <- 30

values <- array(NA, dim=c(nsim, nOM, nMP, nPI, nTS))

pi_means <- c(1,1)

for (om in 1:nOM) {
  for (mp in 1:nMP) {
    for (pi in 1:nPI) {
      values[,om, mp, pi,] <- pi_means[pi] *
        matrix(
        cumprod(c(rlnorm(nTS*nsim, 0, 0.05))),
        nrow=nsim)
    }
  }
}

# Create and populate Object
kobe <- Kobe(Code=c('B/BMSY', 'F/FMSY'),
             Label=c('B/BMSY',
                     'F/FMSY'),
             Description = c('This is the description for PI 1',
                             'This is the description for PI 2'),
             Value=values
)

# Add values for projection time steps
Time(kobe) <- seq(2025, by=1, length.out=nTS)

# Check
Check(kobe)

# Add to `Slick` object
slick <- Slick()
Kobe(slick) <- kobe

# Plots
plotKobe(slick)

plotKobe(slick, Time=TRUE)

---

Access or assign Target and Limit for object of class Kobe or Timeseries

Description

Access or assign Target and Limit for object of class Kobe or Timeseries

Usage

Limit(object)

Limit(object) <- value

Target(object)

Target(object) <- value

## S4 method for signature 'Kobe'
Limit(object)

## S4 replacement method for signature 'Kobe'
Limit(object) <- value

## S4 method for signature 'Kobe'
Target(object)

## S4 replacement method for signature 'Kobe'
Target(object) <- value

## S4 method for signature 'Timeseries'
Limit(object)

## S4 replacement method for signature 'Timeseries'
Limit(object) <- value

## S4 method for signature 'Timeseries'
Target(object)

## S4 replacement method for signature 'Timeseries'
Target(object) <- value

Arguments

object	A Kobe-class() or Timeseries() class object
value	Value to assign to Target

Value

Returns a numeric vector with the contents of the Target or Limit slots of Kobe() and Timeseries() objects

Methods (by class)

• Limit(Kobe): Return Limit from a Kobe-class() object

• Limit(Kobe) <- value: Assign Limit to a Kobe-class() object

• Target(Kobe): Return Target from a Kobe-class() object

• Target(Kobe) <- value: Assign Target to a Kobe-class() object

• Limit(Timeseries): Return Limit from a Timeseries-class() object

• Limit(Timeseries) <- value: Assign Limit to a Timeseries-class() object

• Target(Timeseries): Return Target from a Timeseries-class() object

• Target(Timeseries) <- value: Assign Target to a Timeseries-class() object

Functions

• Target(object) <- value: Assign value to object@Target

---

Make an example Slick object

Description

A function that creates an example Slick data object

Usage

Make_Slick(
  name = "Unnamed Slick object",
  OM = NULL,
  MPs = c("DCAC", "AvC", "Fratio", "FMSYref", "FMSYref50", "matlenlim"),
  MP_Desc = NULL,
  PMs = c("AAVE", "AAVY", "LTY", "P10", "P50", "P100", "PNOF", "STY", "Yield"),
  Design = as.data.frame(cbind(rbind(as.matrix(expand.grid(1:2, 1:3, 1:2)), matrix(1,
    nrow = 5, ncol = 3)), c(rep(1, 12), 2:6))),
  SN = list(Factor_Labels = c("Natural Mortality", "Resilience", "Stock Depletion",
    "Robustness"), Labels = list(c("M=0.2", "M=0.3"), c("h=0.5", "h=0.7", "h=0.9"),
    c("Dep=0.1", "Dep=0.3"), c("Ref_Case", "L50=0.5", "Vmaxlen=0.1", "Cobs=0.5",
    "Perr=0.5", "AC=0.95")), Codes = list(c("M2", "M3"), c("h5", "h7", "h9"), c("D1",
    "D3"), c("Ref_case", "mat_low", "dome", "h_Cerr", "h_Perr", "h_AC")), Description =
    list(c("M=0.2", "M=0.3"), c("h=0.5", "h=0.7", "h=0.9"), c("Dep=0.1", "Dep=0.3"),
    c("Reference Case", 
     "L50=0.5", "Vmaxlen=0.1", "Cobs=0.5", "Perr=0.5",
    "AC=0.95"))),
  mods = list(function(OM, lev) {
     if (lev == 1) OM@M <- c(0.2, 0.2)
     if (lev ==
    2) OM@M <- c(0.3, 0.3)
     OM
 }, function(OM, lev) {
     if (lev == 1) OM@h <-
    c(0.5, 0.5)
     if (lev == 2) OM@h = c(0.7, 0.7)
     if (lev == 3) OM@h = c(0.9,
    0.9)
     OM
 }, function(OM, lev) {
     if (lev == 1) OM@D <- c(0.1, 0.1)
     if
    (lev == 2) OM@D <- c(0.3, 0.3)
     OM
 }, function(OM, lev) {
     if (lev == 2)
    OM@L50 <- c(0.5, 0.5)
     if (lev == 3) OM@Vmaxlen = c(0.1, 0.1)
     if (lev == 4)
    OM@Cobs = c(0.5, 0.5)
     if (lev == 5) OM@Perr = c(0.5, 0.5)
     if (lev == 6)
    OM@AC = c(0.9, 0.9)
     OM
 }),
  nsim = 48,
  MSElist = NULL,
  fstYr = NULL,
  returnMSEs = FALSE
)

Arguments

name	Character string that is the object name (abbreviated for use in menus etc)
OM	An operating model object (class 'OM')
MPs	A vector of methods (character string) of class MP
MP_Desc	A vector method descriptions (character string) nMPs long
PMs	A vector of performance metrics of class PM
Design	A design matrix of OM runs
SN	A list of Labels, Codes and Descriptions of the factor levels. Each list item is a factor containing a vector of factor levels.
mods	A nested list of mods
nsim	Integer, the number of simulations
MSElist	An optional list of prerun MSEs
fstYr	An optional numeric value for first projection year. Otherwise current year is used
returnMSEs	Logical, rather than the Slick object should the list of MSEs be returned?

Value

An object of class Slick

Author(s)

T. Carruthers

---

Return Code, Label, Description and other information from an object

Description

Return Code, Label, Description and other information from an object

Usage

Metadata(object, lang = "en")

Metadata(object) <- value

## S4 method for signature 'Boxplot'
Metadata(object, lang = "en")

## S4 replacement method for signature 'Boxplot'
Metadata(object) <- value

## S4 method for signature 'Kobe'
Metadata(object, lang = "en")

## S4 replacement method for signature 'Kobe'
Metadata(object) <- value

## S4 method for signature 'MPs'
Metadata(object, lang = "en")

## S4 replacement method for signature 'MPs'
Metadata(object) <- value

## S4 method for signature 'Quilt'
Metadata(object, lang = "en")

## S4 replacement method for signature 'Quilt'
Metadata(object) <- value

## S4 method for signature 'Tradeoff'
Metadata(object, lang = "en")

## S4 replacement method for signature 'Tradeoff'
Metadata(object) <- value

## S4 method for signature 'Timeseries'
Metadata(object, lang = "en")

## S4 replacement method for signature 'Timeseries'
Metadata(object) <- value

## S4 method for signature 'Spider'
Metadata(object, lang = "en")

## S4 replacement method for signature 'Spider'
Metadata(object) <- value

## S4 method for signature 'Slick'
Metadata(object, lang = "en")

Arguments

object	A Slick-class(), MPs-class(), Boxplot-class(), Kobe-class(), Quilt-class(), Spider-class(), Timeseries-class(), or Tradeoff-class() object
lang	Optional text string specifying the language (if available). Either 'en', 'es', 'fr', or 'pt' for English, Spanish, French, or Portuguese respectively
value	Replacement value for Metadata() in the corresponding object. See help documentation for the relevant object class for details.

Value

⁠A data.frame⁠

A data.frame

Methods (by class)

• Metadata(Boxplot): Return Metadata for Boxplot-class() objects

• Metadata(Boxplot) <- value: Assign Metadata for Boxplot-class() objects

• Metadata(Kobe): Return Metadata for Kobe-class() objects

• Metadata(Kobe) <- value: Assign Metadata for Kobe-class() objects

• Metadata(MPs): Return Metadata for MPs-class() objects

• Metadata(MPs) <- value: Assign Metadata for MPs-class() objects

• Metadata(Quilt): Return Metadata for Quilt-class() objects

• Metadata(Quilt) <- value: Assign Metadata for Quilt-class() objects

• Metadata(Tradeoff): Return Metadata for Tradeoff-class() objects

• Metadata(Tradeoff) <- value: Assign Metadata for Tradeoff-class() objects

• Metadata(Timeseries): Return Metadata for Timeseries-class() objects

• Metadata(Timeseries) <- value: Assign Metadata for Timeseries-class() objects

• Metadata(Spider): Return Metadata for Spider-class() objects

• Metadata(Spider) <- value: Assign Metadata for Spider-class() objects

• Metadata(Slick): Return Author, Email, and Institution from Slick() objects

---

Assign and access MinValue and MaxValue for a Quilt object

Description

Assign and access MinValue and MaxValue for a Quilt object

Usage

MinValue(Quilt)

MinValue(Quilt) <- value

MaxValue(Quilt)

MaxValue(Quilt) <- value

Arguments

Quilt	A Quilt-class() object
value	A numeric vector with minimum or maximum values for the Performance Indicators.

Value

A numeric value

Functions

• MinValue(): Return MinValue from a Quilt-class() object

• MinValue(Quilt) <- value: Assign MinValue to a Quilt-class() object

• MaxValue(): Return MaxValue from a Quilt-class() object

• MaxValue(Quilt) <- value: Assign MaxValue to a Quilt-class() object

See Also

Quilt()

---

Access or assign Misc for a valid object class

Description

Access or assign Misc for a valid object class

Usage

Misc(object)

Misc(object) <- value

Arguments

object	A Slick-class(), MPs-class(), Boxplot-class(), Kobe-class(), Quilt-class(), Spider-class(), Timeseries-class(), or Tradeoff-class() object
value	A named list

---

Methods for Creating, Accessing and Assigning MPs objects

Description

The MPs function is used both to create and modify an MPs-class() object. and to access and assign MPs for an object of class Slick-class(). See Details.

Usage

MPs(Code = "", Label = "", Description = "", Color = "", Preset = list())

MPs(object) <- value

## S4 method for signature 'missing'
MPs()

## S4 method for signature 'character_list'
MPs(Code = "", Label = "", Description = "", Color = "", Preset = list())

## S4 method for signature 'Slick'
MPs(Code)

## S4 replacement method for signature 'Slick'
MPs(object) <- value

Arguments

Code	A short code for the Management Procedures in this Slick object. A character string length nMP or a named list for multi-language support. See Details
Label	A short label for the Management Procedures in this Slick object. Can be longer than Code but recommended to keep short as possible so it shows clearly in plots and tables. A character string length nMP or a named list for multi-language support. See Details
Description	A description for the Management Procedures in this Slick object. Can include Markdown, see Examples. A character string length nMP or a named list for multi-language support. See Details
Color	A character vector of colors for the MPs.
Preset	An optional named list for the preset buttons in the App(). The name of the list element will appear as a button in the App(). Use Code(), Label(), Description(), and Preset() to access and assign the values for an existing MPs object, see Examples.
object	A Slick-class() object
value	A MPs-class() object

Details

Objects of class MPs are created with MPs()

Functions

• MPs(missing): Create an empty MPs object

• MPs(character_list): Create a populated MPs object

• MPs(Slick): Return an MPs-class() object from a Slick() object

• MPs(Slick) <- value: Assign an MPs-class() object to a Slick() object

See Also

Code(), Label(), Description(), Color(), Metadata(), Preset()

Examples

myMPs <- MPs()
Code(myMPs) <- c('MP1', 'MP2', 'MP3')
Label(myMPs) <- c('Management Procedure 1',
                  'Management Procedure 2',
                  'Management Procedure 3')
Description(myMPs) <- c('This is the description for Management Procedure 1',
                        'This is the description for Management Procedure 2',
                        'This is the description for Management Procedure 3')

Preset(myMPs) <- list(All=1:3, FirstTwo=1:2)


myMPs

# Multi-language
Description(myMPs) <- list(en=c('This is the English description for Management Procedure 1',
                             'This is the English description for Management Procedure 2',
                             'This is the English description for Management Procedure 3'),
                           es=c("This is the Spanish description for Management Procedure 1",
                             "This is the Spanish description for Management Procedure 2",
                             "This is the Spanish description for Management Procedure 3"),
                           fr=c("This is the French description for Management Procedure 1",
                             "This is the French description for Management Procedure 2",
                             "This is the French description for Management Procedure 3"),
                           pt=c("This is the Portuguese description for Management Procedure 1",
                                "This is the Portuguese description for Management Procedure 2",
                                "This is the Portuguese description for Management Procedure 3")
                           )

Metadata(myMPs)
Metadata(myMPs, 'es')
Metadata(myMPs, 'fr')
Metadata(myMPs, 'pt')

---

MPs S4 class and functions

Description

An object of class MPs contains information about the management procedures (MPs) in a Slick-class() object. Like all S4 objects in Slick, slots in this object can be accessed and assigned using functions corresponding to slot name. See MPs() and the the ⁠See Also⁠ section below.

Details

Objects of class MPs are created with MPs()

Multi-Language Support

Text with multi-language supported can be provided as a named list. Available languages:

• en: English (default)

• es: Spanish

• fr: French

• pt: Portuguese

Note

Character strings in Code, Label, and Description must all be same length as the number of management procedures (nMPs) in the plot objects Boxplot, Kobe, Quilt, Spider, Timeseries, and Tradeoff.

Slots

Code

A short code for the Management Procedures in this Slick object. A character string length nMP or a named list for multi-language support. See Details Required

Label

A short label for the Management Procedures in this Slick object. Can be longer than Code but recommended to keep short as possible so it shows clearly in plots and tables. A character string length nMP or a named list for multi-language support. See Details Required

Description

A description for the Management Procedures in this Slick object. Can include Markdown, see Examples. A character string length nMP or a named list for multi-language support. See Details

Color

A character vector of colors for the MPs. Defaults will be used if not populated

Preset

An optional named list for the preset buttons in the App(). The name of the list element will appear as a button in the App().

See Also

Code(), Label(), Description(), Preset()

Examples

myMPs <- MPs()
Code(myMPs) <- c('MP1', 'MP2', 'MP3')
Label(myMPs) <- c('Management Procedure 1',
                  'Management Procedure 2',
                  'Management Procedure 3')
Description(myMPs) <- c('This is the description for Management Procedure 1',
                        'This is the description for Management Procedure 2',
                        'This is the description for Management Procedure 3')

Preset(myMPs) <- list(All=1:3, FirstTwo=1:2)


myMPs

# Multi-language
Description(myMPs) <- list(en=c('This is the English description for Management Procedure 1',
                             'This is the English description for Management Procedure 2',
                             'This is the English description for Management Procedure 3'),
                           es=c("This is the Spanish description for Management Procedure 1",
                             "This is the Spanish description for Management Procedure 2",
                             "This is the Spanish description for Management Procedure 3"),
                           fr=c("This is the French description for Management Procedure 1",
                             "This is the French description for Management Procedure 2",
                             "This is the French description for Management Procedure 3"),
                           pt=c("This is the Portuguese description for Management Procedure 1",
                                "This is the Portuguese description for Management Procedure 2",
                                "This is the Portuguese description for Management Procedure 3")
                           )

Metadata(myMPs)
Metadata(myMPs, 'es')
Metadata(myMPs, 'fr')
Metadata(myMPs, 'pt')

---

Creates a blank Slick object

Description

Creates a blank Slick object

Usage

NewSlick(
  name = "Unnamed Slick Object",
  nPerf = list(nD = 5, nS = 6, nP = 7),
  nMPs = 5,
  nsim = 10,
  nProjYr = 50,
  nStateVar = 2,
  nHistYr = 55,
  Design = expand.grid(1:2, 1:2)
)

Arguments

name	Character string that is the object name (shortened for use in menus etc.)
nPerf	An integer vector of the number of deterministic (nD), stochastic (nS) and projected (nP) performance metrics
nMPs	Integer, the number of management options (aka management procedures).
nsim	Integer, the number of simulations (stochastic replicates per state of nature)
nProjYr	Integer, the number of projected years
nStateVar	Integer, the number of state variables
nHistYr	Integer, the number of historical years for state variables
Design	A design matrix of factor levels ⁠SN, factor⁠

Value

An object of class Slick

Author(s)

T. Carruthers

---

Methods for Creating, Accessing and Assigning OMs objects

Description

The OMs function is used both to create and modify an OMs-class() object. and to access and assign OMs for an object of class Slick-class(). See Details.

Usage

OMs(Factors = data.frame(), Design = data.frame(), Preset = list())

OMs(object) <- value

## S4 method for signature 'missing'
OMs()

## S4 method for signature 'dataframe_list'
OMs(Factors = data.frame(), Design = data.frame(), Preset = list())

## S4 method for signature 'Slick'
OMs(Factors)

## S4 replacement method for signature 'Slick'
OMs(object) <- value

Arguments

Factors	A data.frame with column headings Factor, Level, and Description. See Details
Design	A data.frame with nFactor columns (i.e., length(unique(Factors$Factor))), and nOM rows. See Details
Preset	An optional named list for the preset buttons in the App(). The name of the list element will appear as a button in the App().. See Details and 'Examples
object	A Slick-class() object
value	A OMs-class() object

Details

Factors

Factors can be accessed and assigned using Factors(myslick) and Factors(myslick) <- data.frame() respectively.

The Factor column should be character strings with the name of each factor, while the Level column is a numeric or character value with the level for the corresponding factor.

The Description column is a description for each row, i.e., a unique factor and level. See Examples.

Design

The Design matrix is nOM rows and nFactor columns. The values in each column should either be numeric values indicating the levels for the corresponding factor, or the actual level values (i.e., Factors$Level) that correspond to each OM. See Examples.

Preset

For OMs objects, Preset should be a named list, where each list element represents a different preset button to be shown in the app by the name of the list element, and each named list element should be a list of length nFactors, with the list elements for each Factor containing numeric values indicating the levels to include for that factor. See Examples

Use Factors(), Design(), and Preset() to access and assign the values for an existing OMs object, see Examples.

Functions

• OMs(missing): Create an empty OMs object

• OMs(dataframe_list): Create a populated OMs object

• OMs(Slick): Return an OMs-class() object from a Slick() object

• OMs(Slick) <- value: Assign an OMs-class() object to a Slick() object

See Also

OMs-class(), Factors(), Design(), Preset()

Examples

# Create Object
oms <- OMs()

# Specify Factors
Factors(oms) <- data.frame(Factor='M',
                           Level=c('Base', 'Low M', 'High M'),
                           Description=c('Base Case',
                                         'Lower Natural Mortality',
                                         'Higher Natural Mortality')
)

Factors(oms)

# OM Design

Design(oms) <- data.frame(M=c('Base', 'Low M', 'High M'))

# Add names for OMs
rownames(Design(oms)) <- c('Base Case', 'Less Productive', 'More Productive')

Design(oms)

# Preset

Preset(oms) <- list('Base Case'=list(1),
                    'Low M' = list(2),
                    'High M' = list(3),
                    'All'= list(1:3)
)

# Create Slick Object
myslick <- Slick()

# Add OMs to Slick Object
OMs(myslick) <- oms

---

OMs S4 class and functions

Description

An object of class OMs contains information about the operating models (MPs) in the Slick() object. Like all S4 objects in Slick, slots in this object can be accessed and assigned using functions corresponding to slot name. See OMs() and the the ⁠See Also⁠ section below.

Details

Multi-Language Support

Use a named list to use multi-languages in Factors

Factors

Factors can be accessed and assigned using Factors(myslick) and Factors(myslick) <- data.frame() respectively.

The Factor column should be character strings with the name of each factor, while the Level column is a numeric or character value with the level for the corresponding factor.

The Description column is a description for each row, i.e., a unique factor and level. See Examples.

Design

The Design matrix is nOM rows and nFactor columns. The values in each column should either be numeric values indicating the levels for the corresponding factor, or the actual level values (i.e., Factors$Level) that correspond to each OM. See Examples.

Preset

For OMs objects, Preset should be a named list, where each list element represents a different preset button to be shown in the app by the name of the list element, and each named list element should be a list of length nFactors, with the list elements for each Factor containing numeric values indicating the levels to include for that factor. See Examples

Slots

Factors

A data.frame with column headings Factor, Level, and Description. See Details

Design

A data.frame with nFactor columns (i.e., length(unique(Factors$Factor))), and nOM rows. See Details

Preset

An optional named list for the preset buttons in the App(). The name of the list element will appear as a button in the App().. See Details and Examples

See Also

OMs(), Factors(), Design(), Preset()

Examples

# Create Object
oms <- OMs()

# Specify Factors
Factors(oms) <- data.frame(Factor='M',
                           Level=c('Base', 'Low M', 'High M'),
                           Description=c('Base Case',
                                         'Lower Natural Mortality',
                                         'Higher Natural Mortality')
)

Factors(oms)

# OM Design

Design(oms) <- data.frame(M=c('Base', 'Low M', 'High M'))

# Add names for OMs
rownames(Design(oms)) <- c('Base Case', 'Less Productive', 'More Productive')

Design(oms)

# Preset

Preset(oms) <- list('Base Case'=list(1),
                    'Low M' = list(2),
                    'High M' = list(3),
                    'All'= list(1:3)
)

# Create Slick Object
myslick <- Slick()

# Add OMs to Slick Object
OMs(myslick) <- oms

---

Plot Boxplot

Description

Plots boxplot, violin plot, or a combined box+violin plot for information stored in a Boxplot object

Usage

plotBoxplot(
  slick,
  PI = NULL,
  type = c("boxplot", "violin", "both", "all"),
  byOM = FALSE,
  OMs = NA,
  ncol = 4,
  MP_label = "Code",
  PI_label = "Code"
)

Arguments

slick	A Slick-class() object
PI	Numeric value indicating the Performance Indicator(s) to plot from the Boxplot-class object. If NULL, it will facet_wrap all PIs
type	Character string specifying the plot type.
byOM	Logical. Facet the plots by operating model? PI must be a single value
OMs	Integers representing the OMs to include in the plot. Defaults to all.
ncol	Numeric. Number of columns
MP_label	Label to use for the MPs. Either Code or Label. Description works as well, but you probably don't want to do that.
PI_label	Label to use for the PIs. Either Code or Label. Description works as well, but you probably don't want to do that.

Value

A ggplot2 object, or a list of ggplot2 objects

Examples

# Generate dummy values
nsim <- 10
nOM <- 2
nMP <- 4
nPI <- 3

values <- array(NA, dim=c(nsim, nOM, nMP, nPI))
pi_means <- runif(nPI, 5, 50)
for (om in 1:nOM) {
  for (mp in 1:nMP) {
    for (pi in 1:nPI) {
      values[,om, mp, pi] <- rlnorm(nsim, log(pi_means[pi]), 0.4)
    }
  }
}

# Create and populate Object
boxplot <- Boxplot(Code=c('PI1', 'PI2', 'PI3'),
                   Label=c('Performance Indicator 1',
                           'Performance Indicator 2',
                           'Performance Indicator 3'),
                   Description = c('This is the description for PI 1',
                                   'This is the description for PI 2',
                                   'This is the description for PI 3'),
                   Value=values)

# Check
Check(boxplot)

# Add to `Slick` object
slick <- Slick()
Boxplot(slick) <- boxplot

# Plots
plotBoxplot(slick)

plotBoxplot(slick, type='violin')

plotBoxplot(slick, byOM=TRUE)

plotBoxplot(slick, 2, type='both', byOM=TRUE)

---

Plot Kobe

Description

Plots a Kobe plot for a given projection year, or a Kobe Time plot.

Usage

plotKobe(
  slick,
  xPI = 1,
  yPI = 2,
  Time = FALSE,
  OMs = NA,
  BLcol = "#F8DC7A",
  TLcol = "#D8775D",
  TRcol = "#FDBD56",
  BRcol = "#67C18B",
  axis_label = "Code",
  percentile = 0.75,
  axis.text.size = 14,
  axis.title.size = 16,
  strip.text.size = 16,
  strip.text.color = "#D6501C",
  incMP_label = TRUE,
  mp.text.size = 7,
  mp.point.size = 4,
  mp.init.point.size = 2,
  xmax = 2,
  ymax = 2,
  hist_traj = FALSE,
  ncol = 4,
  lang = "en",
  MP_label = "Code"
)

Arguments

slick	A Slick-class() object
xPI	Numeric value specifying the performance indicator for the x-axis
yPI	Numeric value specifying the performance indicator for the y-axis
Time	Logical. Kobe Time plot?
OMs	Integers representing the OMs to include in the plot. Defaults to all.
BLcol	Color for the bottom left quadrant
TLcol	Color for the top left quadrant
TRcol	Color for the top right quadrant
BRcol	Color for the bottom right quadrant
axis_label	Label to use for the axes. Either Code or Label. Description works as well, but you probably don't want to do that.
percentile	Numeric value specifying the percentile for the x and y percentile bars. Use NULL to remove percentile lines.
axis.text.size	Font size for axis text
axis.title.size	Font size for axis title
strip.text.size	Font size for facet strip text
strip.text.color	Color for facet strip text
incMP_label	Logical. Include MP labels?
mp.text.size	Font size for MP labels
mp.point.size	Point size for MP labels
mp.init.point.size	Point size for start of trajectory. If hist_traj==TRUE
xmax	Maximum value for the x-axis. Values greater than xmax will be shown at xmax
ymax	Maximum value for the yx-axis. Values greater than ymax will be shown at ymax
hist_traj	Logical. Plot the historical trajectories?
ncol	Numeric. Number of columns for Kobe Time
lang	Optional. Language (if supported in Slick Object). Either 'en', 'es', 'fr', or 'pt'
MP_label	Label to use for the MPs. Either Code or Label. Description works as well, but you probably don't want to do that.

Details

By default plotKobe shows the terminal projection year. TimeTerminal(Kobe) can be used to override this. Use a numeric value indicating the time (must match a value in Time(Kobe)) to use for the Kobe plot.

Value

A ggplot2 object

See Also

Kobe(), Kobe-class()

Examples

# Generate dummy values
nsim <- 10
nOM <- 2
nMP <- 4
nPI <- 2
nTS <- 30

values <- array(NA, dim=c(nsim, nOM, nMP, nPI, nTS))

pi_means <- c(1,1)

for (om in 1:nOM) {
  for (mp in 1:nMP) {
    for (pi in 1:nPI) {
      values[,om, mp, pi,] <- pi_means[pi] *
        matrix(
        cumprod(c(rlnorm(nTS*nsim, 0, 0.05))),
        nrow=nsim)
    }
  }
}

# Create and populate Object
kobe <- Kobe(Code=c('B/BMSY', 'F/FMSY'),
             Label=c('B/BMSY',
                     'F/FMSY'),
             Description = c('This is the description for PI 1',
                             'This is the description for PI 2'),
             Value=values
)

# Add values for projection time steps
Time(kobe) <- seq(2025, by=1, length.out=nTS)

# Check
Check(kobe)

# Add to `Slick` object
slick <- Slick()
Kobe(slick) <- kobe

# Plots
plotKobe(slick)

plotKobe(slick, Time=TRUE)

---

Plot Quilt

Description

Create a Quilt plot (unless shading==FALSE in which case it's just a table)

Usage

plotQuilt(
  slick,
  MP_label = "Code",
  OMs = NA,
  minmax = FALSE,
  shading = TRUE,
  kable = FALSE,
  signif = 3,
  alpha = 0.5
)

Arguments

slick	A Slick-class() object
MP_label	Label to use for the MPs. Either Code or Label. Description works as well, but you probably don't want to do that.
OMs	Integers representing the OMs to include in the plot. Defaults to all.
minmax	Logical. Color shading from min to max values in each column? If TRUE, ignores MinValue(quilt) and MaxValue(quilt)
shading	Logical. Color shading for the columns?
kable	Logical. Return a kable object?
signif	Numeric Number of significant figures
alpha	Numeric value. Transparency for color shading

Details

The columns are color shaded from light (lowest values) to dark (highest values).

Colors are set in Color(quilt).

The color shading has 10 steps, from MinValue(quilt) to MaxValue(quilt) for each Performance Indicator. If those values are missing (NA) for a given PI, colors are shaded from lowest to highest values. If minmax==TRUE, MinValue(quilt) and MaxValue(quilt) are ignored.

Value

A DT::datatable or a knitr::kable object

See Also

Quilt(), Quilt-class()

Examples

# Generate dummy values
nOM <- 2
nMP <- 4
nPI <- 4

values <- array(NA, dim=c(nOM, nMP, nPI))

pi_means <- runif(nPI, 5, 50)
for (om in 1:nOM) {
  for (mp in 1:nMP) {
    for (pi in 1:nPI) {
      values[om, mp, pi] <- rlnorm(1,log(pi_means[pi]), 0.4)
    }
  }
}

# Create and populate Object
quilt <- Quilt(Code=c('PI1', 'PI2', 'PI3', 'PI4'),
               Label=c('Performance Indicator 1',
                       'Performance Indicator 2',
                       'Performance Indicator 3',
                       'Performance Indicator 4'),
               Description = c('This is the description for PI 1',
                               'This is the description for PI 2',
                               'This is the description for PI 3',
                               'This is the description for PI 4'),
               Value=values)

# Check
Check(quilt)

# Add to `Slick` object
slick <- Slick()
Quilt(slick) <- quilt

# Plots
plotQuilt(slick)


# Alternative - include Simulation dimension

# Generate dummy values
nSim <- 3
nOM <- 2
nMP <- 4
nPI <- 4

values <- array(NA, dim=c(nSim, nOM, nMP, nPI))

pi_means <- runif(nPI, 5, 50)
for (om in 1:nOM) {
  for (mp in 1:nMP) {
    for (pi in 1:nPI) {
      values[, om, mp, pi] <- rlnorm(nSim,log(pi_means[pi]), 0.4)
    }
  }
}

# Create and populate Object
quilt <- Quilt(Code=c('PI1', 'PI2', 'PI3', 'PI4'),
               Label=c('Performance Indicator 1',
                       'Performance Indicator 2',
                       'Performance Indicator 3',
                       'Performance Indicator 4'),
               Description = c('This is the description for PI 1',
                               'This is the description for PI 2',
                               'This is the description for PI 3',
                               'This is the description for PI 4'),
               Value=values)




# Add to `Slick` object
slick <- Slick()
Quilt(slick) <- quilt

# Plots
plotQuilt(slick)
apply(quilt@Value, 3:4, mean) |> round(1)

---

Plot Spider

Description

A Spider or Radar plot

Usage

plotSpider(
  slick,
  byOM = FALSE,
  byMP = FALSE,
  OMs = NA,
  incMean = TRUE,
  incMax = TRUE,
  relScale = FALSE,
  col.om.title = "#D6501C",
  cex.om.title = 2,
  col.Mean = "white",
  bg.Mean = "black",
  grid.fill = "#f2f3f5",
  grid.line = "black",
  fill = byMP | all(byOM),
  inc.grid = TRUE,
  PI.labels = !(byMP | all(byOM)),
  MP_label = "Code",
  mp.lwd = 3,
  alpha = 0.3,
  ncol = 4,
  PI.mean.cex = 2.2,
  incMPtitle = byMP,
  mplab.cex = 2.2,
  max.pt.cex = 2,
  max.pt.col = "darkred"
)

Arguments

slick	A Slick-class() object
byOM	Logical Plot by OM? Otherwise mean over OMs
byMP	Logical. Plot by MP? Otherwise all MPs together on one plot
OMs	Integers representing the OMs to include in the plot. Defaults to all.
incMean	Logical. Include mean PI score in center?
incMax	Logical. Include colored points indicating maximum PI values?
relScale	Logical. Scale PI values between minimum (0) and maximum (1)?
col.om.title	Color of the OM names/labels
cex.om.title	Size of OM names/labels
col.Mean	Color of mean value text
bg.Mean	Background color of mean value text
grid.fill	Color of fill for the spider grid
grid.line	Color of lines for the spider grid
fill	Logical Fill the spider plot?
inc.grid	Logical. Include the grid?
PI.labels	Logical Show PI labels?
MP_label	Label to use for the MPs. Either Code or Label. Description works as well, but you probably don't want to do that.
mp.lwd	Line width
alpha	Alpha value for the fill
ncol	Number of columns
PI.mean.cex	Size of PI mean score text
incMPtitle	Logical. Include MP label?
mplab.cex	MP label size
max.pt.cex	Max value point size
max.pt.col	Max value point color

Value

A ggplot2 object

Examples

# Generate dummy values
nOM <- 2
nMP <- 4
nPI <- 4

values <- array(NA, dim=c(nOM, nMP, nPI))

# Note: PI values must be between 0 and 1, with 1 indicating better performance
pi_means <- runif(nPI, 0, 1)
for (om in 1:nOM) {
  for (mp in 1:nMP) {
    for (pi in 1:nPI) {
      values[om, mp, pi] <- runif(1, pi_means[pi])
    }
  }
}

# Create and populate Object
spider <- Spider(Code=c('PI1', 'PI2', 'PI3', 'PI4'),
               Label=c('Performance Indicator 1',
                       'Performance Indicator 2',
                       'Performance Indicator 3',
                       'Performance Indicator 4'),
               Description = c('This is the description for PI 1',
                               'This is the description for PI 2',
                               'This is the description for PI 3',
                               'This is the description for PI 4'),
               Value=values)

# Check
Check(spider)

# Add to `Slick` object
slick <- Slick()
Spider(slick) <- spider

# Plots
plotSpider(slick)

plotSpider(slick, fill=TRUE)

plotSpider(slick, byMP=TRUE)

plotSpider(slick, byOM=TRUE)

---

Plot Timeseries

Description

Plot the historical and projected values for a performance indicator.

Usage

plotTimeseries(
  slick,
  PI = 1,
  byMP = FALSE,
  byOM = FALSE,
  OMs = NA,
  includeHist = TRUE,
  ncol = 4,
  col_line = "darkgray",
  includeQuants = TRUE,
  includeLabels = TRUE,
  MeanMed = c("mean", "median"),
  fill_ribbon1 = "#ededed",
  col_ribbon1 = "#ededed",
  quants1 = c(0.25, 0.75),
  alpha1 = 0.3,
  fill_ribbon2 = "white",
  col_ribbon2 = "#c9c9c9",
  linetype_ribbon2 = "dashed",
  quants2 = c(0.1, 0.9),
  alpha2 = 0.1,
  MP_label = "Code",
  col_title = "#D6501C",
  size.title = 18,
  size.axis.title = 18,
  size.axis.text = 16,
  size.mp.label = 6,
  linewidth.median.line = 0.5,
  targ_color = "green",
  targ_name = "Target",
  lim_color = "red",
  lim_name = "Limit",
  inc_y_label = TRUE,
  sims = NULL,
  lang = "en"
)

Arguments

slick	A Slick-class() object
PI	A numeric value specifying the performance indicator to plot
byMP	Logical. Facet by MP? Defaults to FALSE, where all MPs are shown on the same plot
byOM	Logical. Facet by OM? Defaults to FALSE where values are calculated as mean across OMs
OMs	Integers representing the OMs to include in the plot. Defaults to all.
includeHist	Logical. Include the historical period in the projections?
ncol	Numeric. Number of columns if faceting by MP or OM
col_line	Color for the median line (historical)
includeQuants	Logical. Include quantile shading for the projections?
includeLabels	Logical. Include MP labels?
MeanMed	Character. Plot the 'mean' (default) or 'median'.
fill_ribbon1	Fill color for the inner ribbon
col_ribbon1	Color of the line for inner ribbon
quants1	Quantiles for the inner ribbon. Numeric length 2
alpha1	Alpha for the colored MPs inner shading
fill_ribbon2	Fill color for the outer ribbon
col_ribbon2	Color of the line for outer ribbon
linetype_ribbon2	Line type for outer ribbon
quants2	Quantiles for the outer ribbon. Numeric length 2.
alpha2	Alpha for the colored MPs outer shading
MP_label	Label to use for the MPs. Either Code or Label. Description works as well, but you probably don't want to do that.
col_title	Color of the MP title (if byMP==TRUE)
size.title	Numeric length 1. Size for plot title
size.axis.title	Numeric length 1. Size for axis title
size.axis.text	Numeric length 1. Size for axis text
size.mp.label	Numeric length 1. Size of MP labels. Set to NULL for no MP labels
linewidth.median.line	Width of the mean/median line
targ_color	Color for the target line (if it exists in Target(Timeseries(slick)))
targ_name	Label for the target line
lim_color	Color for the limit line (if it exists in Limit(Timeseries(slick)))
lim_name	Label for the limit line
inc_y_label	Include the label for the y-axis?
sims	Optional. Numeric values indicating the simulations to include. Defaults to all.
lang	Optional. Language (if supported in Slick Object). Either 'en', 'es', 'fr', or 'pt'

Details

If byOM==FALSE the results are shown as the mean across operating models.

Value

A ggplot2 object

See Also

Timeseries(), Timeseries-class()

Examples

# Generate dummy values
nsim <- 10
nOM <- 2
nMP <- 4
nPI <- 3
nHistTS <- 50
nProjTS <- 30
nTS <- nHistTS + nProjTS

set.seed(101)

values <- array(NA, dim=c(nsim, nOM, nMP, nPI, nTS))

pi_means <- c(1,1, 1000)

for (om in 1:nOM) {
  for (pi in 1:nPI) {
    # PI identical for historical
    histVals <- matrix(
      pi_means[pi] *
        cumprod(c(rlnorm(nHistTS*nsim, 0, 0.05))),
      nrow=nsim, ncol=nHistTS, byrow=TRUE)
    histVals <- replicate(nMP, histVals)
    values[,om, , pi,1:nHistTS] <- aperm(histVals, c(1,3,2))

    for (mp in 1:nMP) {
      values[,om, mp, pi,(nHistTS+1):nTS] <- matrix(
        pi_means[pi] *
          cumprod(c(rlnorm(nProjTS*nsim, 0, 0.05))),
        nrow=nsim, ncol=nProjTS, byrow=FALSE)
    }
  }
}

# Create and populate Object
timeseries <- Timeseries(Code=c('B/BMSY', 'F/FMSY', 'TAC'),
                         Label=c('B/BMSY',
                                 'F/FMSY',
                                 'TAC'),
                         Description = c('This is the description for PI 1',
                                         'This is the description for PI 2',
                                         'This is the description for PI 3'),
                         Value=values
)

# Last historical time step
TimeNow(timeseries) <- 2024

# Add values for time steps
Time(timeseries) <- c(rev(seq(TimeNow(timeseries), by=-1, length.out=nHistTS)),
                      seq(TimeNow(timeseries)+1, by=1, length.out=nProjTS))

# Check
Check(timeseries)

# Add to `Slick` object
slick <- Slick()
Timeseries(slick) <- timeseries

# Plots
plotTimeseries(slick)
plotTimeseries(slick, 2)
plotTimeseries(slick, 3)

plotTimeseries(slick, byMP=TRUE)

plotTimeseries(slick, byOM=TRUE)

# Custom Reference Points
RefPoints(timeseries) <- list(
  list(Name=c('0.5 BMSY', 'BMSY', '1.5 BMSY'),
       Value=c(0.5, 1, 1.5),
       Color=c('red', 'orange', 'green')),
  list(Name=c('0.8 FMSY', 'FMSY'),
       Value=c(0.8,1),
       Color=c('orange', 'red')),
  list(Name='Target Catch',
       Value=1200,
       Color='blue')
)

Timeseries(slick) <- timeseries
plotTimeseries(slick)
plotTimeseries(slick, 2)
plotTimeseries(slick, 3)

---

Plot Tradeoff

Description

Plot Tradeoff

Usage

plotTradeoff(
  slick,
  xPI = NULL,
  yPI = NULL,
  OMs = NA,
  MP_label = "Code",
  lab_size = 6,
  point_size = 2,
  size.axis.title = 14,
  size.axis.text = 12
)

Arguments

slick	A Slick-class() object
xPI	Numeric value indicating the PI to plot on the x-axis. Multiple values are accepted. Recycled if xPI<yPI
yPI	Numeric value indicating the PI to plot on the y-axis. Multiple values are accepted. Recycled if yPI<xPI
OMs	Integers representing the OMs to include in the plot. Defaults to all.
MP_label	Label to use for the MPs. Either Code or Label. Description works as well, but you probably don't want to do that.
lab_size	Size of the MP labels
point_size	Size of the points
size.axis.title	Size of axis title
size.axis.text	Size of axis text

Value

A ggplot2 object

Examples

# Generate dummy values
nOM <- 2
nMP <- 4
nPI <- 4

values <- array(NA, dim=c(nOM, nMP, nPI))

pi_means <- runif(nPI, 5, 50)
for (om in 1:nOM) {
  for (mp in 1:nMP) {
    for (pi in 1:nPI) {
      values[om, mp, pi] <- rlnorm(1,log(pi_means[pi]), 0.4)
    }
  }
}

# Create and populate Object
tradeoff <- Tradeoff(Code=c('PI1', 'PI2', 'PI3', 'PI4'),
               Label=c('Performance Indicator 1',
                       'Performance Indicator 2',
                       'Performance Indicator 3',
                       'Performance Indicator 4'),
               Description = c('This is the description for PI 1',
                               'This is the description for PI 2',
                               'This is the description for PI 3',
                               'This is the description for PI 4'),
               Value=values)

# Check
Check(tradeoff)

# Add to `Slick` object
slick <- Slick()
Tradeoff(slick) <- tradeoff

# Plots
plotTradeoff(slick)

plotTradeoff(slick, c(1,1,2), c(2,3,3))

---

Normalize performance metric values in a Slick object

Description

A function that converts deterministic or stochastic performance metrics to the range 0-100 and optionally inverts these

Usage

PMnorm(obj, det = TRUE, inv = NULL)

Arguments

obj	An object of class 'slick'
det	logical, should the normalization be applied to the deterministic performance metrics (or, if false the stochastic ones)
inv	A logical vector nPM long. If true, the PM will be inverted (100-value).

Value

An object of class Slick

Author(s)

T. Carruthers

---

Assign or access Preset for a valid object class

Description

Assign or access Preset for a valid object class

Usage

Preset(object)

Preset(object) <- value

## S4 method for signature 'Boxplot'
Preset(object)

## S4 replacement method for signature 'Boxplot'
Preset(object) <- value

## S4 method for signature 'Kobe'
Preset(object)

## S4 replacement method for signature 'Kobe'
Preset(object) <- value

## S4 method for signature 'MPs'
Preset(object)

## S4 replacement method for signature 'MPs'
Preset(object) <- value

## S4 method for signature 'OMs'
Preset(object)

## S4 replacement method for signature 'OMs'
Preset(object) <- value

## S4 method for signature 'Quilt'
Preset(object)

## S4 replacement method for signature 'Quilt'
Preset(object) <- value

## S4 method for signature 'Tradeoff'
Preset(object)

## S4 replacement method for signature 'Tradeoff'
Preset(object) <- value

## S4 method for signature 'Timeseries'
Preset(object)

## S4 replacement method for signature 'Timeseries'
Preset(object) <- value

## S4 method for signature 'Spider'
Preset(object)

## S4 replacement method for signature 'Spider'
Preset(object) <- value

Arguments

object	An object of class Boxplot-class(), Kobe-class(), Quilt-class(), Spider-class(), Timeseries-class(), or Tradeoff-class()
value	A list, formatted to match the class of object. See the documentation for corresponding object class for more details.

Value

Returns a list object from the Preset slot in object

Methods (by class)

• Preset(Boxplot): Return Preset from a Boxplot-class() object

• Preset(Boxplot) <- value: Assign Preset slot from a Boxplot-class() object

• Preset(Kobe): Return Preset from a Kobe-class() object

• Preset(Kobe) <- value: Assign Preset to a Kobe-class() object

• Preset(MPs): Return Preset from a MPs-class() object

• Preset(MPs) <- value: Assign Preset to a MPs-class() object

• Preset(OMs): Return Preset from a OMs-class() object

• Preset(OMs) <- value: Assign Preset to an OMs-class() object

• Preset(Quilt): Return Preset from a Quilt-class() object

• Preset(Quilt) <- value: Assign Preset to a Quilt-class() object

• Preset(Tradeoff): Return Preset from a Tradeoff-class() object

• Preset(Tradeoff) <- value: Assign Preset to a Tradeoff-class() object

• Preset(Timeseries): Return Preset from a Timeseries-class() object

• Preset(Timeseries) <- value: Assign Preset to a Timeseries-class() object

• Preset(Spider): Return Preset from a Spider-class() object

• Preset(Spider) <- value: Assign Preset slot from a Spider-class() object

---

Methods for Creating, Accessing and Assigning Quilt objects

Description

The Quilt function is used both to create and modify an Quilt-class() object. and to access and assign Quilt for an object of class Slick-class(). See Details.

Usage

Quilt(
  Code = "",
  Label = "",
  Description = "",
  Value = array(),
  Preset = list(),
  Color = c("darkblue", "lightblue"),
  MinValue = as.numeric(NA),
  MaxValue = as.numeric(NA),
  Misc = list()
)

Quilt(Slick) <- value

## S4 method for signature 'missing'
Quilt()

## S4 method for signature 'character_list'
Quilt(
  Code = "",
  Label = "",
  Description = "",
  Value = array(),
  Preset = list(),
  Color = c("darkblue", "lightblue"),
  MinValue = as.numeric(NA),
  MaxValue = as.numeric(NA),
  Misc = list()
)

## S4 method for signature 'Slick'
Quilt(Code)

## S4 replacement method for signature 'Slick'
Quilt(Slick) <- value

Arguments

Code	A short code for the Performance Indicators for this object. A character string length nPI or a named list for multi-language support. See Details
Label	A short label for the Performance Indicators for this object. Used to label axes on charts. Can be longer than Code but recommended to keep short as possible so it shows clearly in plots and tables. A character string length nPI or a named list for multi-language support. See Details
Description	A description for the Performance Indicators for this object. Can include Markdown, see Examples. A character string length nPI or a named list for multi-language support. See Details
Value	A numeric array with the stochastic performance indicator values for each operating model (OM), management procedure (MP), and performance indicator (PI). Dimensions: c(nOM, nMP, and nPI). Alternatively, to calculate average over both simulations and Operating Models, Value can be a 4-dimensional array with dimensions: c(nSim, nOM, nMP, and nPI).
Preset	An optional named list for the preset buttons in the App(). The name of the list element will appear as a button in the App().
Color	A character vector length 2 of colors for the maximum and minimum values in the chart.
MinValue	Numeric vector length nPI with the minimum possible value for the respective PIs. Defaults to minimum PI value in Value (averaged across OMs in some cases)
MaxValue	Numeric vector length nPI with the maximum possible value (i.e., best performance) for the respective PIs. Defaults to maximum PI value in Value (averaged across OMs in some cases).
Misc	A named list for additional miscellaneous information.
Slick	A Slick-class() object
value	A Quilt-class() object

Details

Objects of class Quilt are created with Quilt()

Use the Code(), Label(), Description(), Value(), Preset(), Color(), MinValue(), and MaxValue() functions to access and assign the values for an existing Quilt object, see Examples

Multi-Language Support

Text with multi-language supported can be provided as a named list. Available languages:

• en: English (default)

• es: Spanish

• fr: French

• pt: Portuguese

Note

Character strings in Code, Label, and Description must all be same length as the number of performance indicators (nPIs) in Value

Functions

• Quilt(missing): Create an empty Quilt object

• Quilt(character_list): Create a populated Quilt object

• Quilt(Slick): Return Quilt from a Slick-class() object

• Quilt(Slick) <- value: Assign a Quilt-class() object to a Slick-class() object

See Also

Code(), Label(), Description(), Color(), Metadata(), Preset(), Color(), MinValue(), MaxValue()

Examples

# Generate dummy values
nOM <- 2
nMP <- 4
nPI <- 4

values <- array(NA, dim=c(nOM, nMP, nPI))

pi_means <- runif(nPI, 5, 50)
for (om in 1:nOM) {
  for (mp in 1:nMP) {
    for (pi in 1:nPI) {
      values[om, mp, pi] <- rlnorm(1,log(pi_means[pi]), 0.4)
    }
  }
}

# Create and populate Object
quilt <- Quilt(Code=c('PI1', 'PI2', 'PI3', 'PI4'),
               Label=c('Performance Indicator 1',
                       'Performance Indicator 2',
                       'Performance Indicator 3',
                       'Performance Indicator 4'),
               Description = c('This is the description for PI 1',
                               'This is the description for PI 2',
                               'This is the description for PI 3',
                               'This is the description for PI 4'),
               Value=values)

# Check
Check(quilt)

# Add to `Slick` object
slick <- Slick()
Quilt(slick) <- quilt

# Plots
plotQuilt(slick)


# Alternative - include Simulation dimension

# Generate dummy values
nSim <- 3
nOM <- 2
nMP <- 4
nPI <- 4

values <- array(NA, dim=c(nSim, nOM, nMP, nPI))

pi_means <- runif(nPI, 5, 50)
for (om in 1:nOM) {
  for (mp in 1:nMP) {
    for (pi in 1:nPI) {
      values[, om, mp, pi] <- rlnorm(nSim,log(pi_means[pi]), 0.4)
    }
  }
}

# Create and populate Object
quilt <- Quilt(Code=c('PI1', 'PI2', 'PI3', 'PI4'),
               Label=c('Performance Indicator 1',
                       'Performance Indicator 2',
                       'Performance Indicator 3',
                       'Performance Indicator 4'),
               Description = c('This is the description for PI 1',
                               'This is the description for PI 2',
                               'This is the description for PI 3',
                               'This is the description for PI 4'),
               Value=values)




# Add to `Slick` object
slick <- Slick()
Quilt(slick) <- quilt

# Plots
plotQuilt(slick)
apply(quilt@Value, 3:4, mean) |> round(1)

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S4 class Quilt

Description

Objects of class Quilt are used to store information for the Quilt chart. Like all S4 objects in Slick, slots in this object can be accessed and assigned using functions corresponding to slot name. See Quilt() and the the ⁠See Also⁠ section below.

Details

Objects of class Quilt are created with Quilt()

Multi-Language Support

Text with multi-language supported can be provided as a named list. Available languages:

• en: English (default)

• es: Spanish

• fr: French

• pt: Portuguese

Note

Character strings in Code, Label, and Description must all be same length as the number of performance indicators (nPIs) in Value

Slots

Code

A short code for the Performance Indicators for this object. A character string length nPI or a named list for multi-language support. See Details

Label

A short label for the Performance Indicators for this object. Used to label axes on charts. Can be longer than Code but recommended to keep short as possible so it shows clearly in plots and tables. A character string length nPI or a named list for multi-language support. See Details

Description

A description for the Performance Indicators for this object. Can include Markdown, see Examples. A character string length nPI or a named list for multi-language support. See Details

Value

A numeric array with the stochastic performance indicator values for each operating model (OM), management procedure (MP), and performance indicator (PI). Dimensions: c(nOM, nMP, and nPI). Alternatively, to calculate average over both simulations and Operating Models, Value can be a 4-dimensional array with dimensions: c(nSim, nOM, nMP, and nPI).

Preset

An optional named list for the preset buttons in the App(). The name of the list element will appear as a button in the App().

Color

A character vector length 2 of colors for the maximum and minimum values in the chart.

MinValue

Numeric vector length nPI with the minimum possible value for the respective PIs. Defaults to minimum PI value in Value (averaged across OMs in some cases)

MaxValue

Numeric vector length nPI with the maximum possible value (i.e., best performance) for the respective PIs. Defaults to maximum PI value in Value (averaged across OMs in some cases).

Misc

A named list for additional miscellaneous information.

See Also

Quilt(), Code(), Label(), Description(), Value(), Preset()

Examples

# Generate dummy values
nOM <- 2
nMP <- 4
nPI <- 4

values <- array(NA, dim=c(nOM, nMP, nPI))

pi_means <- runif(nPI, 5, 50)
for (om in 1:nOM) {
  for (mp in 1:nMP) {
    for (pi in 1:nPI) {
      values[om, mp, pi] <- rlnorm(1,log(pi_means[pi]), 0.4)
    }
  }
}

# Create and populate Object
quilt <- Quilt(Code=c('PI1', 'PI2', 'PI3', 'PI4'),
               Label=c('Performance Indicator 1',
                       'Performance Indicator 2',
                       'Performance Indicator 3',
                       'Performance Indicator 4'),
               Description = c('This is the description for PI 1',
                               'This is the description for PI 2',
                               'This is the description for PI 3',
                               'This is the description for PI 4'),
               Value=values)

# Check
Check(quilt)

# Add to `Slick` object
slick <- Slick()
Quilt(slick) <- quilt

# Plots
plotQuilt(slick)


# Alternative - include Simulation dimension

# Generate dummy values
nSim <- 3
nOM <- 2
nMP <- 4
nPI <- 4

values <- array(NA, dim=c(nSim, nOM, nMP, nPI))

pi_means <- runif(nPI, 5, 50)
for (om in 1:nOM) {
  for (mp in 1:nMP) {
    for (pi in 1:nPI) {
      values[, om, mp, pi] <- rlnorm(nSim,log(pi_means[pi]), 0.4)
    }
  }
}

# Create and populate Object
quilt <- Quilt(Code=c('PI1', 'PI2', 'PI3', 'PI4'),
               Label=c('Performance Indicator 1',
                       'Performance Indicator 2',
                       'Performance Indicator 3',
                       'Performance Indicator 4'),
               Description = c('This is the description for PI 1',
                               'This is the description for PI 2',
                               'This is the description for PI 3',
                               'This is the description for PI 4'),
               Value=values)




# Add to `Slick` object
slick <- Slick()
Quilt(slick) <- quilt

# Plots
plotQuilt(slick)
apply(quilt@Value, 3:4, mean) |> round(1)

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