QPot (version 1.0)

Model2String: Converts equations with parameters to strings with numbers

Description

Function that converts differential equations from function-format to string-format. Specifically, it reads in a function, searches for the differential equations within the function, and returns a list of strings containing the differential equations from the function. Will also replace parameters of those equations with numerical values.

Usage

Model2String(model.function, parms = "NULL", x.lhs.term = "dx",
  y.lhs.term = "dy", supress.print = FALSE)

Arguments

model.function

function containing the differential equations as given to TSTraj()

parms

a named vector of paramters and their respective values for the deterministic equations.

x.lhs.term

string containing the left hand side of the first equation to search for, default is 'dx'

y.lhs.term

string containing the left hand side of the second equation to search for, default is 'dx'

supress.print

Default it FALSE, supress output. TRUE prints out equations from function

Value

• equations a list with two elements, the first is the x equation, the second is the y equation

Examples

#deSolve-style function call:
model.parms <- c(alpha=1.54, beta=10.14, delta=1, kappa=1, gamma=0.476, mu=0.112509)
ModelEquations <- function(t, state, parms) {
	with(as.list(c(state, parms)), {
	dx <- (alpha*x)*(1-(x/beta)) - ((delta*(x^2)*y)/(kappa + (x^2)))
	dy <- ((gamma*(x^2)*y)/(kappa + (x^2))) - mu*(y^2)
	list(c(dx,dy))
	})
}

Model2String(ModelEquations, parms = model.parms, x.lhs.term = 'dx', y.lhs.term = 'dy')


#Second example with individual strings
# Note the use of dx and dy
test.eqn.x = "dx = (alpha*x)*(1-(x/beta)) - ((delta*(x^2)*y)/(kappa + (x^2)))"
test.eqn.y = "dy = ((gamma*(x^2)*y)/(kappa + (x^2))) - mu*(y^2)"
model.parms <- c(alpha=1.54, beta=10.14, delta=1, kappa=1, gamma=0.476, mu=0.112509)
equations.as.strings.x <- Model2String(test.eqn.x, parms = model.parms,
 x.lhs.term = 'dx', y.lhs.term = 'dy')
equations.as.strings.y <- Model2String(test.eqn.y, parms = model.parms,
 x.lhs.term = 'dx', y.lhs.term = 'dy')