Menu Import

Tutorials

DOE Import and Simulator Configuration
Exploration

Architecture

menuImport.R

UI and Server functions

source("modules/menuImport/importDOE/importDOE.R", local = TRUE) source("modules/menuImport/calibration/defineCalibration.R", local = TRUE) source("modules/menuImport/exploreDOE/exploreDOE.R", local = TRUE)

menuImport.ui(id)

This function adds the menu “Import Data” to the user interface.

Parameters:: id (character) – namespace of the module

Main reactives:

Import DOE: tabPanel in the menu, calls importDOE.ui() with id tabimportDOE
Define Calibration: tabPanel in the menu, calls defineCalibration.ui() with id tabdefineCalib
Preliminary Exploration: tabPanel in the menu, calls exploreDOE.ui() with id tabprelimExplo

menuImport.server(input, output, session, DOEX, Xadd, XaddUQ, XaddSeqOptim, XaddUnconstOptim, XaddConstOptim, settings, import.clicked, prelimexplo.clicked, window.dimension)

This function builds a list-like object named output that contains all of the code needed to update the R objects in the app.

Parameters:

input (list-like-object) – stores the widgets’ values.
output (list-like-object) – stores the instructions to build R objects in the app.
session (object) – environment that can be used to access information and functionality related to the session.
DOEX (list) – stores the input point values and the input DOE information (e.g. bounds…)
Xadd (object) – extra points in the DOE to refine the model
XaddUQ (object) – extra points in the DOE to refine the model in specific zones (low and/or high values)
XaddSeqOptim (object) – extra points in the DOE to refine the model for a sequential optimization
XaddUnconstOptim (object) – extra points in the DOE to confirm unconstrained optimization results
XaddConstOptim (object) – extra points in the DOE to confirm constrained optimization results
settings (list-like-object) – variables specified in settingsDOE.R
import.clicked (logical) – informs if the user selected the import DOE tab
prelimexplo.clicked (logical) – informs whether the user selected the preliminary exploration tab
window.dimension (object) – dimensions of the window

Main reactives:

OutputimportDOE: calls the module importDOE.server() with id importDOE
calibDOE: calls the module defineCalibration.server() with id defineCalibration
ML: calls the module exploreDOE.server() with id exploreDOE
filteredDOE: reactive expression containing the DOE definition with the inputs filtered by the user.

Import DOE

importDOE.R

source("modules/menuImport/importDOE/uploadDOE.R", local = TRUE) source("modules/menuImport/importDOE/confSimulator.R", local = TRUE)

UI and Server functions

importDOE.ui(id)

Displays the panel asking to use a simulator, and the panel to upload a file

Parameters:: id (character) – namespace of the module

importDOE.server(input, output, session, DOEX, Xadd, XaddUQ, XaddSeqOptim, XaddUnconstOptim, XaddConstOptim, settings, import.clicked)

Parameters:

input (list-like-object) – stores the widgets’ values.
output (list-like-object) – stores the instructions to build R objects in the app.
session (object) – environment that can be used to access information and functionality related to the session.
DOEX (list) – stores the input point values and the DOE input information (e.g. bounds…)
Xadd (object) – extra points in the DOE to refine the model
XaddUQ (object) – extra points in the DOE to refine the model in specific zones (low and/or high values)
XaddSeqOptim (object) – extra points in the DOE to refine the model for a sequential optimization
XaddUnconstOptim (object) – extra points in the DOE to confirm unconstrained optimization results
XaddConstOptim (object) – extra points in the DOE to confirm constrained optimization results
settings (list-like-object) – variables specified in settingsDOE.R
import.clicked (logical) – TRUE when the tab import DOE is clicked

Main reactives:

upload_file_bool: checks if the user uploaded a file
use_simulator: checks if the user wants to connect a simulator

Three data import use cases are available, hence the need of upload_file_bool:

Upload a file
Use a simulator and the DOE generated in the prepareDOE tab
Use a simulator and upload a file

dataModal(): creates graphical elements

uploadDOE.R

source("modules/shared/XinfosChange.R", local = TRUE) source("modules/shared/XactiveChange.R", local = TRUE) source("modules/shared/YinfosChange.R", local = TRUE) source("modules/shared/XYnamesChange.R", local = TRUE) source("modules/shared/missingValChange.R", local = TRUE) source("modules/shared/dynamicSelect.R", local = TRUE) source("modules/prepareDOE/evaluateDOE.R", local = TRUE) source("modules/prepareDOE/visualizeDOE.R", local = TRUE) source("modules/menuImport/importDOE/compositeFunction.R", local = TRUE) source("modules/menuImport/importDOE/importDiscretization.R", local = TRUE)

UI and Server functions

uploadDOE.ui(id)

displays graphical components for the upload process

Parameters:: id (character) – namespace of the module

uploadDOE.server(input, output, session, settings)

Parameters:

input (list-like-object) – stores the widgets’ values.
output (list-like-object) – stores the instructions to build R objects in the app.
session (object) – environment that can be used to access information and functionality related to the session.
settings (list-like-object) – variables specified in settingsDOE.R

Main reactives:

output$import.dynui: displays UI by taking into account displayui$mode
displayui$mode: the mode changes along the process to display the right UI
output$tabimport.dynui: displays UI by calling three ids: upload.dynui, sepdec.dynui, preview.dynui
output$upload.dynui: displays import elements
output$sepdec.dynui: displays elements to change the separator and the decimal character
file.data: reads and stores file content
output$preview.dynui: displays a preview of the file to check the loading
output$preview: displays output variables information
output$taboutputs.dynui: displays elements to change output types and shows some output information
DOEfinal: contains the DOE definition and data
output$tabfinish.dynui: displays a summary before import confirmation

Main functions

my.summary(x, ...)

Computes descriptive statistics: mean, standard-deviation, min, max, quantile variation

Parameters:

x (vector) – vector of numeric data
.... (-) – ellipsis

Returns:

computed statistics

Return type:

vector

compute.summary(Y, my.summary, Yinfos)

Computes summary for all variables

Parameters:

Y (data.frame) – data
my.summary (function) – computes descriptive statistics
Yinfos (list) – variable information

Returns:

computed statistics

Return type:

matrix

checkValid.XYData(XY, nX)

Checks the validity of XYData using three conditions:

XY must be not null
XY must be a data.frame
nX must be greater than the number of columns in XY

Parameters:

XY (data.frame) – data
nX (numeric) – number of variables

Returns:

TRUE if valid, FALSE otherwise

Return type:

logical

get.XYdata(XY, nX, header, firstcol, namesvisu, namesmenu)

Forms the data in the right shape for Lagun

Parameters:

XY (data.frame) – experience parameters and outputs
nX (numeric) – number of variables
header (logical) – presence of header
firstcol (logical) – if the first column indicates the observation number
namesvisu (vector) – vector of variable names processed for plots
namesmenu (vector) – vector of variable names processed for menus

Returns:

XYData

Return type:

list

Secondary functions

get.Xinfos.col(ind, XDOE, xnames, xnamesvisu, xnamesmenu, nvalues)

Evaluates whether the variable’s type is numeric, a constant, or categorical

Parameters:

ind (numeric) – index of column to evaluate
XDOE (data.frame) – stores the input point values and the input DOE information (e.g. bounds…)
xnames (vector) – vector of variable names
namesvisu (vector) – vector of variable names processed for plots
namesmenu (vector) – vector of variable names processed for menus
nvalues (numeric) – number of values for the variable

Returns:

Xinfos.col

Return type:

list

get.Yinfos.col(ind, YDOE, nvalues, threshold.var)

Focuses on the target variables. Evaluates its type: status (if not numeric), constant or interest

Parameters:

ind (numeric) – index of column to evaluate
YDOE (object) – stores the output point values and the DOE output information (e.g. bounds…)
nvalues (numeric) – number of values for the variable
threshold.var (numeric) – threshold variation, if the quantile variation is below this threshold, the variable is considered a constant

Returns:

Yinfos.col

Return type:

list

compositeFunction.R

UI and Server functions

compositeFunctionUI(id)

Parameters:: id (character) – namespace of the module

Main reactives:

createCompFunc: button to call the modal modalAddCompFunc that allows to create a composite output
existingCompFunc: displays the existing composite outputs, alongside with a delete button

compositeFunctionServer(id, DOE)

Parameters:

id (character) – namespace of the module
DOE (object) – stores the point values and the DOE information (e.g. bounds…)

Main reactives:

output$existingCompFunc: displays the existing composite outputs, alongside with a delete button
output$modalAddCompFunc: modal that allows to create a composite output
output$latexFormula: displays the formula in latex format
input$addCompFunc: performs a few checks, creates the composite output and updates compositeInfos object

Main functions

latexify(formula, name)

This functions translates the formula in R language into a latex formula

Parameters:

formula (character) – formula entered by the user
name (character) – name of the composite output

getUsedParams(formula, ynames)

Identifies the output(s) used in the formula

Parameters:

formula (character) – formula entered by the user
ynames (list) – list of the output names in the DOE

checkName(name, xnames, ynames)

Performs the following verifications on the name:

It must not be empty
It must be unique
it must only contain letters, numbers, “_”, and “.”

Parameters:

name (character) – name of the composite output (entered by the user)
xnames (list) – list of the input names in the DOE
ynames (list) – list of the output names in the DOE

checkFormula(formula, usedParams, modelMode, type, Y)

Performs the following verifications on the formula:

It must not be empty
It must contain at least one output
It must be a valid expression
It must not trigger an error nor a warning when evaluated
It must only contain numbers if numeric type is selected
It must not contain log or ln if combine mode is selected

Parameters:

formula (character) – formula entered by the user
usedParams (list) – parameters used in formula
modelMode (character) – informs whether a model should be trained or combine the models from the used parameters
type (character) – selected output type (numeric or categorical)
Y (data.frame) – output values of the imported DOE

Secondary functions

findAllFunctions(formula, funcName, nbToFind, res)

Finds recusively all functions to replace in latexify function

Parameters:

formula (character) – formula entered by the user
funcName (character) – add_description
nbToFind (numeric) – number of funcName to find in the formula (default=NULL)
res (list) – each element contains two fields, fullFunc (function name and its content) and content (expression between parentheses)

indicator(expr)

Wrapper for ifelse function, returns ifelse(expr, 1, 0)

Parameters:: expr (expression) – logical expression

pln(y)

\[ \begin{align}\begin{aligned}pln(y) &= \ln(1+ y'), \quad\mbox{if}\quad y' ≥ 0\\pln(y) &= -\ln(1- y'), \quad\mbox{if}\quad y' < 0\end{aligned}\end{align} \]

Parameters:: y (vector) – data

plog(y)

\[ \begin{align}\begin{aligned}plog(y) &= \log(1+ y'), \quad\mbox{if}\quad y' ≥ 0\\plog(y) &= -\log(1- y'), \quad\mbox{if}\quad y' < 0\end{aligned}\end{align} \]

Parameters:: y (vector) – data

Explore DOE

exploreDOE.R

source("modules/menuImport/exploreDOE/qualitativeExploration.R", local = TRUE) source("modules/menuImport/exploreDOE/quantitativeExploration.R", local = TRUE)

UI and Server functions

exploreDOE.ui(id)

This function creates the exploration page with two panels : qualitative exploration and quantitative exploration with Machine Learning tools

Parameters:: id (character) – namespace of the module

Main reactives:

modalViewDOE: calls a modal view to display table of the current DOE
qualitativeExploration: populates the Qualitative Exploration panel
quantitativeExploration: populates the Quantitative Exploration panel

exploreDOE.server(input, output, session, DOE, settings, prelimexplo.clicked, advance.importDOE, use_simulator, window.dimension)

This function builds a list-like object named output that contains all of the code needed to update the R objects in the app.

Parameters:

input (list-like-object) – stores the widgets’ values.
output (list-like-object) – stores the instructions to build R objects in the app.
session (object) – environment that can be used to access information and functionality related to the session.
DOE (object) – stores the point values and the DOE information (e.g. bounds…)
settings (list-like-object) – variables specified in settingsDOE.R
prelimexplo.clicked (logical) – informs whether the user selected the preliminary exploration tab
advance.importDOE (object) – stores the simulation information status (completed/waiting/running) when Lagun is connected to an external simulator
use_simulator (logical) – informs if the user uses a simulator linked to Lagun
window.dimension (object) – dimensions of the window

Main reactives:

currentDOE: reactive expression containing the DOE definition
output$DTcurrentDOE: displays the DOE as a table
qualitativeExploration.server() module called
ML: calls module quantitativeExploration.server()

qualitativeExploration.R

source("modules/shared/dynamicSelect.R", local = TRUE) source("modules/shared/dynamicSelectpicker.R", local = TRUE)

UI and Server functions

qualitativeExploration.ui(id)

Displays the panel with three tabs, each containing an interactive plot.

Parameters:: id (character) – namespace of the module

Main reactives:

Regression plot - One by One
- chooseY: Y axis variable selector
- chooseX: X axis variable selector
- chooseRegColor: color marks by selected variable value
- chooseRegSize: change size marks by selected variable value
- chooseRegMark: change type of mark by selected variable value
- showhist: switch button to display histograms on the axes
- plot.reg: displays regression plot
Parallel coordinate plot
- choose.palette.num: color palette selector for numerical variables
- choose.palette.cat: color palette selector for categorical variables
- downloadpcp: export plot
- chooseXParcoords: input variables selector
- chooseYParcoords: output variables selector
- chooseHistParcoords: variable selection to display histogram
- chooseBoundsParcoords: bound selection for a variable
- parcoords: displays parallel plot
Regression plot - All in One
- plot.allinone: displays regression plots for all variables, pairwise.

qualitativeExploration.server(input, output, session, DOE, window.dimension)

Parameters:

input (list-like-object) – stores the widgets’ values.
output (list-like-object) – stores the instructions to build R objects in the app.
session (object) – environment that can be used to access information and functionality related to the session.
DOE (object) – stores the point values and the DOE information (e.g. bounds…)
window.dimension (object) – dimensions of the window

Returns:

DOE

Return type:

object

Main reactives:

Regression plot - One by One
- choicesX: contains all the variables for the X axis. Inputs come first.
- Xcat: contains the input categorical variables
- Ycat: contains the output categorical variables
- Allcat: contains all the categorical variables
- Allb: contains all the bounds
- choicesY: contains all the variables for the Y axis. Outputs come first.
- choicesRegColor: contains all the variables to apply different colors
- choicesRegSize: contains all the continuous variables to apply different sizes
- choicesRegMark: contains all the categorical variables to apply different mark types
- output$regression: calls plot.regression()
- output$plot.reg: displays the regression plot
Regression plot - All in One
- choicesXallinone: contains all the input variables
- currentview: computes the number of rows and columns in the lattice
- input$goPrevious / goNext / goUp / goDown: navigation in the lattice
- output$plot.allinone: descprition
- output$ui.treillis: displays lattice navigation buttons
- output$plotallinone.treillis: builds the plot
- output$plot.allinone.inside: displays the plot
Parallel coordinate plot
- choicesXParcoords: list of input variables
- selectedXParcoords: selected input variables
- choicesYParcoords: list of output variables
- selectedYParcoords: selected output variables
- choicesHistParcoords: list of all variables for histogram selection
- choicesBoundsParcoords: list of all variables for bounds edition
- output$dynui_bounds: renders UI
- output$parcoords: displays the parallel plot
- choicescluster: contains the variables to use for clustering
- cluster: contains clusters computed with kMeans
- output$downloadpcp: creates a downloadable html parallel plot

Plot functions

plot.regression(df, xname, yname, colorname, sizename, markname, catnames, showhist, xnamevisu, ynamevisu, colnamevisu, adapt.visu)

Displays a plot to observe interactions between variables.

Parameters:

df (data.frame) – data to plot
xname (character) – x name in df
yname (character) – y name in df
colorname (character) – colors to apply
sizename (numeric) – size to apply
markname (character) – mark to use
catnames (list) – categories names
showhist (logical) – informs if a histogram should be displayed on x and y axis
xnamevisu (character) – x axis title
ynamevisu (character) – y axis title
colnamevisu (character) – color bar title
adapt.visu (logical) – adapt margins

Returns:

plot to display

Return type:

plotly plot

quantitativeExploration.R

source("modules/shared/dynamicSelect.R", local = TRUE)

UI and Server functions

quantitativeExploration.ui(id)

Populates the quantitative exploration panel

Parameters:: id (character) – namespace of the module

Main reactives:

ui.cor: tab that displays correlations plot
ui.hsicdcor: tab that displays generalized correlations plot
ui.download: tab that contains buttons to download results

quantitativeExploration.server(input, output, session, DOE, window.dimension, settings)

Parameters:

input (list-like-object) – stores the widgets’ values.
output (list-like-object) – stores the instructions to build R objects in the app.
session (object) – environment that can be used to access information and functionality related to the session.
DOE (object) – stores the point values and the DOE information (e.g. bounds…)
window.dimension (object) – dimensions of the window
settings (list-like-object) – variables specified in settingsDOE.R

Main reactives:

Correlation tab
- choicesXcor: list of the input variables
- choicesYcor: list of the output variables
- output$ui.cor: displays correlation plot
- output$plot.correl: builds correlation plot
- output$scatterplotCOR: builds scatter plot
Generalized Correlation tab
- xnamehsicdcor: list of the input variables
- ynamehsicdcor: list of the output variables
- output$ui.hsicdcor: defines UI layout
- output$plot.hsicdcor: displays correlation plot with computed DCOR
- output$boxplotDCOR: displays boxplot with computed DCOR
Download tab
- output$ui.download: defines UI layout
- output$downloadCOR: download correlations in a CSV file
- output$downloadDCOR: download distance correlations in a CSV file

Main functions

computeHSICDCOR(Y, X, nrepML, callback)

Computes a distance correlation statistics pairwise [1]

Parameters:

Y (vector) – vector data
X (vector) – vector data
nrepML (numeric) – number of repetitions
callback (function) – reports progress

Returns:

computed correlations

Return type:

list

Secondary functions

callback(r)

Reports progress of a task. Calls R Shiny incProgress

Parameters:: r (numeric) – r^th iteration

Define Calibration

defineCalibration.R

source("modules/menuImport/calibration/importExperimentalData.R", local = TRUE) source("modules/menuImport/calibration/defineObjective.R", local = TRUE)

UI and Server functions

defineCalibration.ui(id)

displays graphical components for the calibration process

Parameters:: id (character) – namespace of the module

defineCalibration.server(input, output, session, DOE, settings)

Parameters:

input (list-like-object) – stores the widgets’ values.
output (list-like-object) – stores the instructions to build R objects in the app.
session (object) – environment that can be used to access information and functionality related to the session.
DOE (list) – stores the input point values and the input DOE information (e.g. bounds…)
settings (list-like-object) – variables specified in settingsDOE.R

Main reactives:

calibDOE: contains the calibration definition (experimental data, standard deviations, weigths) and objective function values

defineObjective.R

UI and Server functions

defineObjective.ui(id)

displays graphical components for the definition of data weights

Parameters:: id (character) – namespace of the module

defineObjective.server(input, output, session, DOE, xpData, settings)

Parameters:

input (list-like-object) – stores the widgets’ values.
output (list-like-object) – stores the instructions to build R objects in the app.
session (object) – environment that can be used to access information and functionality related to the session.
DOE (list) – stores the input point values and the input DOE information (e.g. bounds…)
xpData (list) – contains experimental data and standard deviations
settings (list-like-object) – variables specified in settingsDOE.R

Main reactives:

objFunc: contains the calibration definition (weights, normalization type) and objective function values

importDiscretization.R

UI and Server functions

importDiscretization.ui(id)

This function displays a button that calls a modal window in order to import functional outputs discretization

Parameters:: id (character) – namespace of the module

importDiscretization.server(input, output, session, DOE)

Parameters:

input (list-like-object) – stores the widgets’ values.
output (list-like-object) – stores the instructions to build R objects in the app.
session (object) – environment that can be used to access information and functionality related to the session.
DOE (list) – stores the input point values and the input DOE information (e.g. bounds…)

Main reactives:

importDiscF: contains discretization for functional outputs

importExperimentalData.R

UI and Server functions

importExperimentalData.ui(id)

displays graphical components in order to import experimental data and standard deviations

Parameters:: id (character) – namespace of the module

importExperimentalData.server(input, output, session, DOE, settings)

Parameters:

input (list-like-object) – stores the widgets’ values.
output (list-like-object) – stores the instructions to build R objects in the app.
session (object) – environment that can be used to access information and functionality related to the session.
DOE (list) – stores the input point values and the input DOE information (e.g. bounds…)
settings (list-like-object) – variables specified in settingsDOE.R

Main reactives:

xpData: contains experimental data and standard deviations

Main functions

checkXPdata(data, DOE, ynames)

Check validity of imported experimental data

Parameters:

data (data.frame) – contains imported DOE
DOE (list) – contains the input point values and the input DOE information (e.g. bounds…)
ynames (list) – list of the output names in the imported DOE

Returns:

validity information about imported data

Return type:

list

Menu Import

Tutorials

Architecture

menuImport.R

UI and Server functions

Import DOE

importDOE.R

UI and Server functions

uploadDOE.R

UI and Server functions

Main functions

Secondary functions

compositeFunction.R

UI and Server functions

Main functions

Secondary functions

Explore DOE

exploreDOE.R

UI and Server functions

qualitativeExploration.R

UI and Server functions

Plot functions

quantitativeExploration.R

UI and Server functions

Main functions

Secondary functions

Define Calibration

defineCalibration.R

UI and Server functions

defineObjective.R

UI and Server functions

importDiscretization.R

UI and Server functions

importExperimentalData.R

UI and Server functions

Main functions

References