../../../data/GHE/mpn/deployment/deployments/2021-04-19/vignettes/extra/init.Rmd
init.RmdThere are two commonly-used ways to set initial conditions: in $MAIN and in the initial condition list.
$MAIN
For a compartment called CMT, there is a variable available to you called CMT_0 that you can use to set the initial condition of that compartment in $MAIN. For example:
code <- '
$PARAM KIN = 200, KOUT = 50
$CMT RESP
$MAIN
RESP_0 = KIN/KOUT;
'This is the most commonly-used way to set initial conditions: the initial condition for the RESP compartment is set equal to KIN divided by KOUT. If you had a parameter called BASE, you could also write RESP_0 = BASE;. In these examples, we’re using data items from $PARAM. But the initial condition could be set to any numeric value in the model, including individual parameters derived from parameters, covariates, and random effects. Note that you should never declare RESP_0 (e.g. double RESP_0): it just appears for you to use.
init listYou can also set initial conditions in the initials list. Most commonly, this means declaring compartments with $INIT rather than $CMT. For example
code <- '
$INIT RESP = 4
'This method gets us the same result as the previous example, however the initial condition now is not a derived value, but it is coded as a number. Alternatively, you could declare a compartment via $CMT and update later (see next).
We can update this value later like this
.
. Model initial conditions (N=1):
. name value . name value
. RESP (1) 4 | . ... .
init(mod, RESP=8) %>% init.
. Model initial conditions (N=1):
. name value . name value
. RESP (1) 8 | . ... .
This method is commonly used to set initial conditions in large QSP models where the compartment starts out as some known or assumed steady state value.
The following is from a wiki post I did on the topic. It’s pedantic. But hopefully helpful to learn what mrgsolve is doing for those who want to know.
mrgsolve keeps a base list of compartments and initial conditions that you can update either from R or from inside the model specification
$CMT, the value in that base list is assumed to be 0 for every compartmentmrgsolve will by default use the values in that base list when starting the problem$MAIN to set the initial condition
$MAIN RESP_0 = KIN/KOUT; when KIN and KOUT have some value in $PARAM
$MAIN overwrites the value in the base list for the current ID
$MAIN
init behaviorNote: IFLAG is my invention only for this demo. The demo is always responsible for setting and interpreting the value (it is not reserved in any way and mrgsolve does not control the value).
For this demo
A initial condition defaults to 0A initial condition will get set to BASE only if IFLAG > 0
A always stays at the initial condition (the system doesn’t advance)
code <- '
$PARAM BASE=200, IFLAG = 0
$CMT A
$MAIN
if(IFLAG > 0) A_0 = BASE;
$ODE dxdt_A = 0;
'Check the initial condition
init(mod).
. Model initial conditions (N=1):
. name value . name value
. A (1) 0 | . ... .
Note:
$CMT in the model spec; that implies that the base initial condition for A is set to 0$MAIN doesn’t get run because IFLAG is 0$MAIN the initial condition is as we set it in the base list
mod %>% mrgsim %>% dplot
Next, we update the base initial condition for A to 100
Note:
$MAIN still doesn’t get run because IFLAG is 0
mod %>% init(A = 100) %>% mrgsim %>% dplot
Now, turn on IFLAG
Note:
$MAIN gets runA_0 is set to the value of BASE
mod %>% param(IFLAG=1) %>% mrgsim %>% dplot
mod %>% param(IFLAG=1, BASE=300) %>% mrgsim %>% dplot
Just to be clear, there is no need to set any sort of flag to set the initial condition.
code <- '
$PARAM AUC=0, AUC50 = 75, KIN=200, KOUT=5
$CMT RESP
$MAIN
RESP_0 = KIN/KOUT;
$ODE
dxdt_RESP = KIN*(1-AUC/(AUC50+AUC)) - KOUT*RESP;
'
mod <- mcode("init_long2", code)The initial condition is set to 40 per the values of KIN and KOUT
mod %>% mrgsim %>% plot
Even when we change RESP_0 in R, the calculation in $MAIN gets the final say
mod %>% init(RESP=1E9) %>% mrgsim. Model: init_long2
. Dim: 25 x 3
. Time: 0 to 24
. ID: 1
. ID time RESP
. 1: 1 0 40
. 2: 1 1 40
. 3: 1 2 40
. 4: 1 3 40
. 5: 1 4 40
. 6: 1 5 40
. 7: 1 6 40
. 8: 1 7 40
init will let you check to see what is going oninit first takes the base initial condition list, then calls $MAIN and does any calculation you have in there; so the result is the calculated initials
init(mod).
. Model initial conditions (N=1):
. name value . name value
. RESP (1) 40 | . ... .
mod %>% param(KIN=100) %>% init.
. Model initial conditions (N=1):
. name value . name value
. RESP (1) 20 | . ... .
idata
Go back to house model
.
. Model initial conditions (N=3):
. name value . name value
. CENT (2) 0 | RESP (3) 50
. GUT (1) 0 | . ... .
Notes
idata (only), include a column with CMT_0 (like you’d do in $MAIN).idata value will override the base initial list for that subject.CMT_0 is set in $MAIN, that will override the idata update.
idata <- expand.idata(CENT_0 = seq(0,25,1))
idata %>% head. ID CENT_0
. 1 1 0
. 2 2 1
. 3 3 2
. 4 4 3
. 5 5 4
. 6 6 5
plot(out, CENT~.)