There 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
list
You 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 | . ... .
##
## 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
behavior
Note: 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 listNext, we update the base initial condition for A
to 100
Note:
$MAIN
still doesn’t get run because
IFLAG
is 0Now, turn on IFLAG
Note:
$MAIN
gets runA_0
is set to the value of BASE
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
Even when we change RESP_0
in R
, the
calculation in $MAIN
gets the final say
## 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
on
init
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 | . ... .
##
## 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~.)