Run the Slick App in the local browser

Description

An online hosted version of the Slick App is available here

Usage

App(...)

Arguments

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")
)

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")
)

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

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

Arguments

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

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

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()

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

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 '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 '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 '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'
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 '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

Arguments

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

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

• 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

• 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

• 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

• 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

• 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

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

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

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

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

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

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

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')

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()
)

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()
)

## 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()
)

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

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

Arguments

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

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

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

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

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

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

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")
                           )

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

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

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")
                           )

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

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

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

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

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()

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

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

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

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

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

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)
)

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)
)

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

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

Arguments

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

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)

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

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)

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).

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)

Assign or access RefPoints for a valid object class

Description

Assign or access RefPoints for a valid object class

Usage

RefPoints(object)

RefPoints(object) <- value

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

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

Arguments

Value

Returns a list object with the contents of the RefPoints slot of Timeseries() objects

Methods (by class)

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

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

Create a Slick class object

Description

The Slick class is the main object class used in the Slick package. It contains sub-objects for the management procedures MPs(), operating models OMs(), and the six chart types: Boxplot(), Kobe(), Quilt(), Spider(), Timeseries(), and Tradeoff(), as well as metadata information for the Slick object such as Title, Author, and Introduction.

Usage

Slick(
  Title = "",
  Subtitle = "",
  Date = Sys.Date(),
  Author = "",
  Email = "",
  Institution = "",
  Introduction = "",
  MPs = NULL,
  OMs = NULL,
  Boxplot = NULL,
  Kobe = NULL,
  Quilt = NULL,
  Spider = NULL,
  Timeseries = NULL,
  Tradeoff = NULL
)

Title(object, lang = "en", markdown = FALSE)

Title(object) <- value

Subtitle(object, lang = "en", markdown = FALSE)

Subtitle(object) <- value

Date(object)

Date(object) <- value

Author(object, markdown = FALSE)

Author(object) <- value

Email(object, markdown = FALSE)

Email(object) <- value

Institution(object, lang = "en", markdown = FALSE)

Institution(object) <- value

Introduction(object, lang = "en", markdown = FALSE)

Introduction(object) <- value

Arguments

Details

Objects of class Slick are created with Slick().

Like all S4 objects in Slick, slots in this object can be accessed and assigned using functions corresponding to slot name. See Usage and Functions section.

Multi-Language Support

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

• en: English (default)

• es: Spanish

• fr: French

All functions with the exception of Date support Markdown.

Value

A Slick object

Functions

• Slick(): Create a Slick-class() object

• Title(): Access Title, Multi-language support

• Title(object) <- value: Assign Title, Multi-language support

• Subtitle(): Access Subtitle, Multi-language support

• Subtitle(object) <- value: Assign Subtitle, Multi-language support

• Date(): Access Date

• Date(object) <- value: Assign Date

• Author(): Access Author

• Author(object) <- value: Assign Author

• Email(): Access Email

• Email(object) <- value: Assign Email

• Institution(): Access Institution

• Institution(object) <- value: Assign Institution

• Introduction(): Access Introduction

• Introduction(object) <- value: Assign Introduction, can include Markdown. See Examples

Slots

Title

Title for the Slick object. A character string. For multiple languages, use a named list with names: en, es, fr for the three supported languages.

Subtitle

Subtitle for the Slick object. A character string or a named list with languages: en, es, fr

Date

Date the Slick object was created. Text in format 'YYYY-MM-DD' or class Date e.g., Sys.Date()

Author

A character vector with Author(s) names. The length of the vector should equal the number of authors.

Email

A character vector with email addresses for the author(s). Must be same length as Author. Can include Markdown.

Institution

A character vector with institution details for the author(s). Must be same length as Author. Can include Markdown.

Introduction

Introduction text for the Slick object. Supports all markdown formatting. Character string, must be length 1. For multiple languages, use a named list with names: en, es, fr for the three supported languages.

MPs

An object of class MPs-class()

OMs

An object of class OMs-class()

Boxplot

An object of class Boxplot-class()

Kobe

An object of class Kobe-class()

Quilt

An object of class Quilt-class()

Spider

An object of class Spider-class()

Timeseries

An object of class Timeseries-class()

Tradeoff

An object of class Tradeoff-class()

See Also

MPs(), OMs(), Boxplot(), Kobe(), Quilt(), Spider(), Timeseries(), Tradeoff(), Check(), Title(), Subtitle(), Date(), Author(), Email(), Institution(), Introduction()

Examples

# Assign values to a new `Slick` object
slick <- Slick()

Title(slick) <- 'An Example Slick Object'
Subtitle(slick) <- ""
Date(slick) <- Sys.Date()
Author(slick) <- 'Adrian Hordyk'
Email(slick) <-  "[mailto:adrian@bluematterscience.com](mailto:adrian@bluematterscience.com)"
Institution(slick) <- "[Blue Matter Science](bluematterscience.com)"

Introduction(slick) <- "This is the Introduction text"

# Access values from `Slick` object
Title(slick)
Subtitle(slick)
Date(slick)
Author(slick)
Email(slick)
Institution(slick)
Introduction(slick)

Methods for Creating, Accessing and Assigning Spider objects

Description

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

Usage

Spider(
  Code = "",
  Label = "",
  Description = "",
  Value = array(),
  Preset = list()
)

Spider(Slick) <- value

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

## S4 method for signature 'character'
Spider(
  Code = "",
  Label = "",
  Description = "",
  Value = array(),
  Preset = list()
)

## S4 method for signature 'list'
Spider(
  Code = "",
  Label = "",
  Description = "",
  Value = array(),
  Preset = list()
)

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

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

Arguments

Details

Objects of class Spider are created with Spider()

Use the Code(), Label(), Description(), Value(), Preset() functions to access and assign the values for an existing Spider 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

Note

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

Functions

• Spider(missing): Create an empty Spider object

• Spider(character): Create a populated Spider object

• Spider(list): Create a populated Spider object

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

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

See Also

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

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)

S4 class Spider

Description

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

Details

Objects of class Spider are created with Spider()

Multi-Language Support

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

• en: English (default)

• es: Spanish

• fr: French

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). All PI values must range between 0 and 1 or 0 and 100. If all values are <= 1, they will be multiplied by 100 in the plot. Dimensions: c(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().

See Also

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

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)

Access or assign Time for object of class Kobe or Timeseries

Description

Access or assign Time for object of class Kobe or Timeseries

Usage

Time(object)

Time(object) <- value

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

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

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

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

Arguments

Value

Returns a numeric vector with values from the Time slot in Kobe() and Timeseries() objects

Methods (by class)

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

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

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

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

Functions

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

Access or assign TimeLab in a Kobe or Timeseries object

Description

Access or assign TimeLab in a Kobe or Timeseries object

Usage

TimeLab(object, lang = "en")

TimeLab(object) <- value

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

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

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

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

Arguments

Value

Returns a character string from the TimeLab slot in Kobe() and Timeseries() objects

Methods (by class)

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

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

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

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

Access and return TimeNow from a Timeseries-class() object

Description

Access and return TimeNow from a Timeseries-class() object

Usage

TimeNow(Timeseries)

TimeNow(Timeseries) <- value

Arguments

Value

A numeric value

Functions

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

Assign or access TimeTerminal for a valid object class

Description

Assign or access TimeTerminal for a valid object class

Usage

TimeTerminal(object)

TimeTerminal(object) <- value

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

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

Arguments

Value

Returns a numeric values from the TimeTerminal slot in Kobe() objects

Methods (by class)

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

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

Methods for Creating, Accessing and Assigning Timeseries objects

Description

An object of class Timeseries contains information for the Time Series chart. The Timeseries function is used both to create and modify an Timeseries-class() object, and to access and assign Timeseries for an object of class Slick-class(). See Details.

Usage

Timeseries(
  Code = "",
  Label = "",
  Description = "",
  Time = numeric(),
  TimeNow = numeric(),
  TimeLab = "Year",
  Value = array(),
  Preset = list(),
  Target = NULL,
  Limit = NULL,
  RefPoints = list()
)

Timeseries(Slick) <- value

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

## S4 method for signature 'character'
Timeseries(
  Code = "",
  Label = "",
  Description = "",
  Time = numeric(),
  TimeNow = numeric(),
  TimeLab = "Year",
  Value = array(),
  Preset = list(),
  Target = NULL,
  Limit = NULL,
  RefPoints = list()
)

## S4 method for signature 'list'
Timeseries(
  Code = "",
  Label = "",
  Description = "",
  Time = numeric(),
  TimeNow = numeric(),
  TimeLab = "Year",
  Value = array(),
  Preset = list(),
  Target = NULL,
  Limit = NULL,
  RefPoints = list()
)

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

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

Arguments

Details

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

Note

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

Objects of class Timeseries are created with Timeseries()

Multi-Language Support

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

• en: English (default)

• es: Spanish

• fr: French

Custom Reference Points with RefPoints

RefPoints provides more options than the default Target and Limit reference points. It can be used to control the name and color of the reference point lines, or to add additional reference point lines to the Timeseries plot.

Note: If RefPoints is included, Target and Limit are ignored.

RefPoints must be a list of length <= length(Code) (i.e., the number of performance indicators). Each element in RefPoints should be a named list:

• Name character vector with name(s) of reference point(s)

• Value numeric vector length Name with value(s) for the reference point(s)

• Color character vector length Name with color(s) for the reference point(s)

See Examples

Accessing Slots

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

Functions

• Timeseries(missing): Create an empty Timeseries object

• Timeseries(character): Create a populated Timeseries object

• Timeseries(list): Create a populated Timeseries object

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

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

See Also

Timeseries-class(), Code(), Label(), Description(), Metadata(), Value(), Preset(), plotTimeseries()

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

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)

S4 class Timeseries

Description

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

Details

Objects of class Timeseries are created with Timeseries()

Multi-Language Support

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

• en: English (default)

• es: Spanish

• fr: French

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 historical and projection time-steps. Must match length nTS in Value. Can also be class Date, POSIXct or POSIXt

TimeNow

A numeric value matching the last historical timestep in Time

TimeLab

Character string length 1. Name of the time step (e.g., 'Year'). Will be used as the label in the plots. 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 historical + projection timestep (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.

Limit

Numeric vector length nPI with the limit value for the PIs.

RefPoints

List for setting custom Reference Points. Overrides Target and Limit. See Details section in Timeseries().

See Also

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

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)

Methods for Creating, Accessing and Assigning Tradeoff objects

Description

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

Usage

Tradeoff(
  Code = "",
  Label = "",
  Description = "",
  Value = array(),
  Preset = list()
)

Tradeoff(Slick) <- value

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

## S4 method for signature 'character'
Tradeoff(
  Code = "",
  Label = "",
  Description = "",
  Value = array(),
  Preset = list()
)

## S4 method for signature 'list'
Tradeoff(
  Code = "",
  Label = "",
  Description = "",
  Value = array(),
  Preset = list()
)

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

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

Arguments

Details

Objects of class Tradeoff are created with Tradeoff()

Multi-Language Support

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

• en: English (default)

• es: Spanish

• fr: French

Note

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

Functions

• Tradeoff(missing): Create an empty Tradeoff object

• Tradeoff(character): Create a populated Tradeoff object

• Tradeoff(list): Create a populated Tradeoff object

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

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

See Also

Code(), Label(), Description(), Metadata(), 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
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))

S4 class Tradeoff

Description

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

Details

Objects of class Tradeoff are created with Tradeoff()

Multi-Language Support

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

• en: English (default)

• es: Spanish

• fr: French

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 3 dimensional numeric array with the stochastic performance indicator values for operating model (OM), management procedure (MP), and performance indicator (PI). Dimensions: c(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().

See Also

Tradeoff(), 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
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))

Updates an old object of class Slick to new S4 class Slick

Description

Updates an old object of class Slick to new S4 class Slick

Usage

Update(slick)

Arguments

Value

An S4 object of class Slick

Examples

slick <- Slick() # a dummy old Slick object
slick <- Update(slick) # updated to S4 object

Assign or access Value for a valid object class

Description

Assign or access Value for a valid object class

Usage

Value(object)

Value(object) <- value

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

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

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

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

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

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

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

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

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

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

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

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

Arguments

Value

Returns a numeric array with the contents of the Value slot of object

Methods (by class)

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

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

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

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

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

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

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

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

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

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

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

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

Set Default Colors for the MPs

Description

Requires the colorspace package

Usage

default_mp_colors(nMP)

Arguments

Value

A character vector of length nMP with color hex codes

Examples

cols <- default_mp_colors(4)
cols

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

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])

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,
  ncol = 4,
  MP_label = "Code",
  PI_label = "Code"
)

Arguments

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,
  BLcol = "#F8DC7A",
  TLcol = "#D8775D",
  TRcol = "#FDBD56",
  BRcol = "#67C18B",
  axis_label = "Code",
  percentile = 0.9,
  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

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",
  minmax = FALSE,
  shading = TRUE,
  kable = FALSE,
  signif = 2,
  alpha = 0.5
)

Arguments

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)

Plot Spider

Description

A Spider or Radar plot

Usage

plotSpider(
  slick,
  byOM = FALSE,
  byMP = FALSE,
  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

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,
  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

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,
  MP_label = "Code",
  lab_size = 6,
  point_size = 2,
  size.axis.title = 14,
  size.axis.text = 12
)

Arguments

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))

Generic show method

Description

A copy of methods::show()

Usage

show(object)

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

## S4 method for signature 'CheckList'
show(object)

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

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

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

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

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

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

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

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

Arguments

Value

show returns an invisible NULL

Methods (by class)

• show(Boxplot): Print a Boxplot-class() object

• show(CheckList): Print a CheckList object

• show(Kobe): Print a Kobe-class() object

• show(MPs): Print a MPs-class() object

• show(OMs): Print a OMs-class() object

• show(Quilt): Print a Quilt-class() object

• show(Tradeoff): Print a Tradeoff-class() object

• show(Timeseries): Print a Timeseries-class() object

• show(Spider): Print a Spider-class() object

• show(Slick): Print a Slick-class() object