Package 'piamValidation'

Validation Tools for PIK-PIAM

Description

The piamValidation package provides validation tools for the Potsdam Integrated Assessment Modelling environment.

Author(s)

Maintainer: Pascal Weigmann [email protected]

Authors:

• Oliver Richters

See Also

Useful links:

• https://github.com/pik-piam/piamValidation

---

construct tooltips for interactive plots

Description

construct tooltips for interactive plots

Usage

appendTooltips(df)

Arguments

df	data.frame as returned from 'validateScenarios()'

---

Check variable consistency

Description

Test whether unit of on row of config and data for this variable match.

Usage

checkUnits(data, cfgRow)

Arguments

data	scenario or reference data for one variable
cfgRow	one row of a config file containing the same variable as the data object

---

Combine scenario and reference data with thresholds

Description

for one row of cfg: filter and merge relevant scenario data with cfg results in one df that contains scenario data, reference data and thresholds

Usage

combineData(scenData, cfgRow, histData = NULL)

Arguments

scenData	scenario data
cfgRow	one row of a config file
histData	reference data

---

performs the validation checks from a config on a scenario data set

Description

performs the validation checks from a config on a scenario data set

Usage

validateScenarios(dataPath, config, outputFile = NULL, extraColors = TRUE)

Arguments

dataPath	one or multiple path(s) to scenario data in .mif or .csv format, in case of historic comparison, also path to reference data
config	select config from inst/config or give a full path to a config file on your computer
outputFile	give name of output file in case results should be exported; include file extension
extraColors	if TRUE, use cyan and blue for violation of min thresholds instead of using the same colors as for max thresholds (yel and red)

---

takes the output of "validateScenarios()" and plots heatmaps per variable

Description

takes the output of "validateScenarios()" and plots heatmaps per variable

takes the output of "validateScenarios()" and plots heatmaps per variable

Usage

validationHeatmap(
  df,
  var,
  met,
  historical = TRUE,
  interactive = TRUE,
  x_plot = "region",
  y_plot = "period",
  x_facet = "model",
  y_facet = "scenario"
)

validationHeatmap(
  df,
  var,
  met,
  historical = TRUE,
  interactive = TRUE,
  x_plot = "region",
  y_plot = "period",
  x_facet = "model",
  y_facet = "scenario"
)

Arguments

df	data.frame as returned by “validateScenarios()“ and “appendTooltips()“
var	variable to be plotted
met	choose metric from "relative", "difference", "absolute" or "growthrate"
historical	should this be a plot comparing to historical data
interactive	return plots as interactive plotly plots by default
x_plot	choose dimension to display on x-axis of plot, default: region
y_plot	choose dimension to display on y-axis of plot, default: period
x_facet	choose dimension to display on x-dim of facets, default: model
y_facet	choose dimension to display on x-dim of facets, default: scenario

---

returns information on whether scenarios passed critical validation checks

Description

returns information on whether scenarios passed critical validation checks

Usage

validationPass(data, yellowFail = FALSE)

Arguments

data	data.frame as returned from “validateScenarios()“
yellowFail	if set to TRUE a yellow check result of a critical variable will lead to the scenario not passing as validated

---

perform validateScenarios and create an .html report using .Rmd templates

Description

perform validateScenarios and create an .html report using .Rmd templates

Usage

validationReport(
  dataPath,
  config,
  report = "default",
  outputDir = "output",
  extraColors = TRUE
)

Arguments

dataPath	one or multiple path(s) to scenario data in .mif or .csv format
config	name a config from inst/config ("validationConfig_<name>.csv") or give a full path to a separate configuration file
report	name a .Rmd from inst/markdown ("validationReport_<name>.Rmd") to be rendered or give a full path to a separate .Rmd file
outputDir	choose a directory to save validation reports to
extraColors	if TRUE, use cyan and blue for violation of min thresholds instead of using the same colors as for max thresholds (yel and red)

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