mrgx functions

Functions
Rcpp::Environment	mrgx::get_envir (const databox &self)
	Return the model environment.
double	mrgx::rnorm (const double mean, const double sd, const double lower, const double upper)
double	mrgx::rlognorm (const double mean, const double sd, const double lower, const double upper)
template<typename _T___>
_T___	mrgx::get (const std::string name, const databox &self)
template<typename _T___>
void	mrgx::assign (const std::string x, const _T___ &value, const databox &self)
template<typename _T___>
_T___	mrgx::get (const std::string name)
template<typename _T___>
_T___	mrgx::get (const std::string package, const std::string name)
template<typename _T___>
_T___	mrgx::readRDS (const std::string filename)
Rcpp::Function	mrgx::mt_fun ()

Detailed Description

Extra C++ functions provided by mrgsolve. To use these functions, use $PLUGIN mrgx in your model file. Using mrgx will also invoke the Rcpp plugin.

Function Documentation

assign()

template<typename _T___>

void mrgx::assign	(	const std::string	x,
		const _T___ &	value,
		const databox &	self )

Assign an object to the model environment.

Example:

$PLUGIN mrgx
 
$GLOBAL Rcpp::NumericVector ans(100);
 
$PREAMBLE
for(R_xlen_t i = 0; i < ans.size(); ++i) {
  ans[i] = R::rnorm(0,1);
}
 
$PK
if(FINAL_ROW) {
  mrgx::assign("vec", ans, self);
}

Parameters

x	a variable name to be assigned in the model evironment.
value	a value to be assigned to x in the model environment.
self	the model object; the assignment happens in self.envir.

get() [1/3]

template<typename _T___>

_T___ mrgx::get

(

const std::string

name

)

Get an R object from the global environment.

Example:

Rcpp::NumericVector x = mrgx::get<Rcpp::NumericVector>("x");

Note: for this to work, x must be a numeric vector in .GlobalEnv.

Parameters

name	name of the R object to get

Returns

an object from the global environment

get() [2/3]

template<typename _T___>

_T___ mrgx::get	(	const std::string	name,
		const databox &	self )

Get an R object from the model environment.

Example:

$PLUGIN mrgx
 
$GLOBAL
Rcpp::NumericMatrix mat;
 
$PREAMBLE
mat = mrgx::get<Rcpp::NumericMatrix>("mymatrix", self); 
 
$ENV
mat <- dmat(1,2,3)

Note: for this to work, you must define a numeric matrix called mat in $ENV.

Parameters

name	name of the R object to get
self	the model data object

Returns

an object from the model environment

get() [3/3]

template<typename _T___>

_T___ mrgx::get	(	const std::string	package,
		const std::string	name )

Get an R object from a package namespace. This is typically used to get a function from a specific package.

Example:

To get a function, use this code:

$PLUGIN mrgx
 
$GLOBAL 
Rcpp::Function Rnorm = mrgx::get<Rcpp::Function>("stats", "rnorm"); 
Rcpp::Function Seq = mrgx::get<Rcpp::Function>("base", "seq");
 
$ERROR 
if(FINAL_ROW) {
  mrgx::assign("double", Rnorm(10), self); 
  mrgx::assign("int", seq(10), self);
}

Parameters

package	name of the package
name	name of the object to get

Returns

an object from the package namespace

get_envir()

Rcpp::Environment mrgx::get_envir

(

const databox &

self

)

Return the model environment.

With each mrgsolve model object, there is an R environment that can be used to maintain arbitrary R objects, potentially for use in the model.

Parameters

self	the model databox object

Returns

the model environment

mt_fun()

Rcpp::Function mrgx::mt_fun

(

)

An empty R function. This is typically used as a placeholder when declaring an Rcpp::Function object in $GLOBAL. This pattern of declaring in $GLOBAL and (re)defining in $PREAMBLE could be used for efficiency when the function must be called many times.

$PLUGIN mrgx
 
$ENV
NORM <- function(n, mu, sd) rnorm(n, mu, sd)
 
$GLOBAL 
Rcpp::Function fun = mrgx::mt_fun(); 
 
$PREAMBLE 
fun = mrgx::get<Rcpp::Function>("NORM");
 
$MAIN
Rcpp::NumericVector ans = fun(1000, 33, 3);
 
if(FINAL_ROW) {
  mrgx::assign("vec", ans, self);
}

Returns

the function mt_fun from the mrgsolve namespace.

readRDS()

template<typename _T___>

_T___ mrgx::readRDS

(

const std::string

filename

)

Read an RDS file.

$PLUGIN mrgx
 
$ENV 
file <- file.path(tempdir(), "file-read-rds.RDS")
x <- list(a = 1.23, b = c(1,2,3,99))
saveRDS(object = x, file = file)
 
$PREAMBLE
std::string file = mrgx::get<std::string>("file", self);
 
Rcpp::List y = mrgx::readRDS<Rcpp::List>(file);
 
capture a = y["a"];
capture b = Rcpp::as<Rcpp::NumericVector>(y["b"])[3];

Parameters

filename

the name of the RDS file to read.

Returns

an object saved in the RDS file

rlognorm()

double mrgx::rlognorm	(	const double	mean,
		const double	sd,
		const double	lower,
		const double	upper )

Simulate random lognormal variate between lower and upper boundaries. An error is generated if a variate between lower and upper bounds cannot be generated in 50 tries.

Example:

$MAIN
double WT = mrgx::rlnorm(log(80),1,40,140);

Parameters

mean	normal distribution mean
sd	normal distribution standard deviation
lower	lower bound for variates
upper	upper bound for variates

Returns

the simulated variate

rnorm()

double mrgx::rnorm	(	const double	mean,
		const double	sd,
		const double	lower,
		const double	upper )

Simulate random normal variate between lower and upper boundaries. An error is generated if a variate between lower and upper bounds cannot be generated in 50 tries.

Example:

$MAIN
double WT = mrgx::rnorm(80,40,40,140);

Parameters

mean	normal distribution mean
sd	normal distribution standard deviation
lower	lower bound for variates
upper	upper bound for variates

Returns

the simulated variate