Difference between revisions of "City-level climate policy model"

library(OpasnetUtils)
library(xtable)
library(ggplot2)

test <- 0
issues <- op_baseGetData("opasnet_base", "Op_en5811")
me <- "Urban area"
formula <- function(dependencies, me, ...) {
data <- issues[issues$Topic == me, ]

return(data)
}
ova <- new("ovariable", dependencies = data.frame(Name = "test"),
formula = formula
)
ova
EvalOutput(ova, me = "Transport")

equations <- tidy(op_baseGetData("opasnet_base", "Op_enXXXX"), objname = "equations")

### This formula creates a causal model with linear dependencies between ovariables Policy.target, Action.on, ...
# The dependencies are defined in a data table equations.
formula <- function(dependencies, me, ...) {
	ComputeDependencies(dependencies, ...)

	# Find coefficients of equations that are relevant for this ovariable.
	coefficients <- new("ovariable",
		name = "coefficients",
		data = equations[equations$Equation == equations[equations$Role == "Child" & equations$Step == me, "Equation"], ]
	)
	
	out <- data.frame()
	for(i in dependencies$Name) {
		out <- rbind(out, get(i)@output * coefficients)
	}
	out <- tapply(out$Result, out["Equation"], sum)
	return(out)
}

Policy.targets <- new("ovariable", 
	name = "Policy.targets", 
	data = tidy(issues[issues$Table == "Policy target" , ], objname = "Policy.target")
)

Action.on <- new("ovariable", 
	name = "Action.on", 
	data = tidy(issues[issues$Table == "Action on" , ], objname = "Action.on"),
	dependencies = data.frame(Name = c(
		"equation", 
		"Policy.target"
	)),
	formula = formula
)

Primary.impact.on <- new("ovariable", 
	name = "Primary.impact.on", 
	data = tidy(issues[issues$Table == "Primary impact on" , ], objname = "Primary impact on"),
	dependencies = data.frame(Name = c(
		"equation", 
		"Policy.target", 
		"Action.on"
	)),
	formula = formula
)

End.use.of.energy <- new("ovariable", 
	name = "End.use.of.energy", 
	data = tidy(issues[issues$Table == "End use of energy" , ], objname = "End.use.of.energy"),
	dependencies = data.frame(Name = c(
		"equation", 
		"Policy.target", 
		"Action.on", 
		"Primary.impact.on"
	)),
	formula = formula
)

Emission <- new("ovariable", 
	name = "Emission", 
	data = tidy(issues[issues$Table == "Emission" , ], objname = "Emission"),
	dependencies = data.frame(Name = c(
		"equation", 
		"Policy.target", 
		"Action.on", 
		"Primary.impact.on", 
		"End.use.of.energy"
	)),
	formula = formula
)

Time.budget <- new("ovariable", 
	name = "Time.budget", 
	data = tidy(issues[issues$Table == "Time budget" , ], objname = "Time.budget"),
	dependencies = data.frame(Name = c(
		"equation", 
		"Policy.target", 
		"Action.on", 
		"Primary.impact.on", 
		"End.use.of.energy", 
		"Emission"
	)),
	formula = formula
)

Exposure <- new("ovariable", 
	name = "Exposure", 
	data = tidy(issues[issues$Table == "Exposure" , ], objname = "Exposure"),
	dependencies = data.frame(Name = c(
		"equation", 
		"Policy.target", 
		"Action.on", 
		"Primary.impact.on", 
		"End.use.of.energy", 
		"Emission", 
		"Time.budget"
	)),
	formula = formula
)

Policy.outcome <- new("ovariable", 
	name = "Policy.outcome", 
	data = tidy(issues[issues$Table == "Policy.outcome" , ], objname = "Policy.outcome"),
	dependencies = data.frame(Name = c(
		"equation", 
		"Policy.target", 
		"Action.on", 
		"Primary.impact.on", 
		"End.use.of.energy", 
		"Emission", 
		"Time.budget", 
		"Exposure", 
		"Policy.outcome"
	)),
	formula = formula
)