Nothing

```
testNumberOfPools <- function(){
t_start=0
t_end=2
tn=100
tol=.02/tn
print(tol)
timestep=(t_end-t_start)/tn
t=seq(t_start,t_end,timestep)
nr=3
nc=3
# define the transfer functions for the model
# we could compile them to a matrix valued
# Function of C and t since they will be
# applied in a linear way on the output vector.
# but we rather store them in an indexed list (
# as a sparse matrix which also has some
# implementational benefits because the single
# functions are easier to retrieve from the operator
# if needed.
alpha=list()
alpha[["2_to_1"]]=function(C,t){
1/4*1e-16
}
alpha[["3_to_2"]]=function(C,t){
1/3*1e-16
}
alpha[["1_to_2"]]=function(C,t){
1/2#*1e-16
}
k1=-1/2
k2=-2/3
k3=-1
f=function(t,O){
# in this case the Matrix N is actually completely linear
N=matrix(
nrow=nr,
ncol=nc,
c(
k1, 0, 0,
0 , k2, 0,
0, 0, k3
)
)
# so we can write f(O) as a Matrix product
# note however that we could anything we like with the components
# of O here.
# The only thing to take care of is that we release a vector of the same
# size as O
res=N*O
}
c01=3
c02=2
c03=2.5
inputrates=new("TimeMap",t_start,t_end,function(t){return(matrix(
nrow=3,
ncol=1,
c(
1, 2, 3
)
))})
A=new("TransportDecompositionOperator",t_start,Inf,nr,alpha,f)
mod=GeneralNlModel(
t,
A,
c(
c01,
c02,
c03
),
inputrates,
deSolve.lsoda.wrapper
)
# both
checkEquals(3,getNumberOfPools(mod))
checkEquals(3,getNumberOfPools(A))
}
```

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