# No method matching zero

**URL:** <https://discourse.pumas.ai/t/no-method-matching-zero/949>\
**Category:** Simulation\
**Created:** [October 15, 2023, 10:13pm UTC](https://discourse.pumas.ai/t/no-method-matching-zero/949 "2023-10-15T22:13:37Z")\
**Posts on this page:** 11\
**Page:** 1

<div class="post-metadata">

**Author:** ![MathangiCTM](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/mathangictm/32/142_2.png) [@MathangiCTM](https://discourse.pumas.ai/u/MathangiCTM)\
**Post date:** [October 15, 2023, 10:13pm UTC](https://discourse.pumas.ai/t/no-method-matching-zero/949/1 "2023-10-15T22:13:37Z")

</div>

Hi,  
I am running a simulation using resampled individual parameter sets from a two-stage estimation. My model code is below:

```auto
pilot_fast_2cmt_katlag_ehc = @model begin
    @param begin
        σ_prop ∈ RealDomain(lower=0.001)
        σ_add ∈ RealDomain(lower=0.001)
    end

    @covariates iCl iVc iQ iVp iKa iLag iKpb iKgp ik0bile is_bile Form_C

    @pre begin
        Cl = iCl
        Vc = iVc
        Q = iQ 
        Vp = iVp 
        Ka = iKa 
        Kpb = iKpb 
        Kgp = iKgp 
        k0bile = (is_bile == 0) ? 0 : ik0bile
    end

    @dosecontrol begin
        lags = (; Depot = iLag)
    end

    @dynamics begin
    Depot' = - Ka*Depot
    Central' = Ka*Depot - (Cl/Vc)*Central + (Q/Vp)*Peripheral - Kpb*Central + Kgp * Gut
    Peripheral' = (Cl/Vc)*Central - (Q/Vp)*Peripheral
    Bile' = Kpb*Central - k0bile
    Gut' = k0bile - Kgp * Gut
    end

    @derived begin
        cp = @. (Central/Vc)
        Conc ~ @. Normal(cp, sqrt(σ_add^2+(cp*σ_prop)^2))
    end
end

```

And when I run the simulation, I get this error message:

```auto
simobs(
        pilot_fast_2cmt_katlag_ehc,
        pop_fit_df.pop,
        param_2cmt_ehc,
        obstimes=[0.08,0.17,0.25,0.5,1.0,1.5,2.0,3.0,4.0,6.0,8.0,10.0,12.0,16.0,18.0,24.0]
        #rng=rng
    )

```

Error message:

```auto
ERROR: MethodError: no method matching zero(::Type{Array{Float64}})

Closest candidates are:
  zero(::Union{Type{P}, P}) where P<:Period
   @ Dates C:\Pumas-v2.4.1\Julia-1.9.2\share\julia\stdlib\v1.9\Dates\src\periods.jl:51
  zero(::Union{AbstractAlgebra.Generic.LaurentSeriesFieldElem{T}, AbstractAlgebra.Generic.LaurentSeriesRingElem{T}} where T<:AbstractAlgebra.RingElement)
   @ AbstractAlgebra C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\AbstractAlgebra\FcxWh\src\generic\LaurentSeries.jl:466     
  zero(::Union{AbstractAlgebra.Generic.LaurentSeriesFieldElem{T}, AbstractAlgebra.Generic.LaurentSeriesRingElem{T}} where T<:AbstractAlgebra.RingElement, ::String; cached)
   @ AbstractAlgebra C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\AbstractAlgebra\FcxWh\src\generic\LaurentSeries.jl:480     
  ...

Stacktrace:
  [1] zeros(#unused#::Type{Array{Float64}}, dims::Tuple{Int64, Int64})
    @ Base .\array.jl:585
  [2] zeros(::Type{Array{Float64}}, ::Int64, ::Int64)
    @ Base .\array.jl:580
  [3] (::var"#821#831")(_param#2926::NamedTuple{(:σ_add, :σ_prop), Tuple{Float64, Float64}}, _random#2927::NamedTuple{(), Tuple{}}, _subject#2924::Subject{NamedTuple{(:Conc,), Tuple{Vector{Union{Missing, Float64}}}}, Pumas.ConstantCovar{NamedTuple{(:iCl, :iVc, :iQ, :iVp, :iKa, :iLag, :iKpb, :iKgp, :ik0bile, :is_bile, :Form_C), Tuple{Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Int64}, Vector{String15}}}}, Vector{Pumas.Event{Float64, Float64, Float64, Float64, Float64, Float64, Int64}}, Vector{Float64}})
    @ Main C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\Pumas\VyE8h\src\dsl\model_macro.jl:822
  [4] (::Pumas.TimeDispatcher{var"#821#831", var"#822#832"})(param::NamedTuple{(:σ_add, :σ_prop), Tuple{Float64, Float64}}, randeffs::NamedTuple{(), Tuple{}}, subject::Subject{NamedTuple{(:Conc,), Tuple{Vector{Union{Missing, Float64}}}}, Pumas.ConstantCovar{NamedTuple{(:iCl, :iVc, :iQ, :iVp, :iKa, :iLag, :iKpb, :iKgp, :ik0bile, :is_bile, :Form_C), Tuple{Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Int64}, Vector{String15}}}}, Vector{Pumas.Event{Float64, Float64, Float64, Float64, Float64, Float64, Int64}}, Vector{Float64}}, #unused#::Pumas.ConstantCovar{NamedTuple{(:iCl, :iVc, :iQ, :iVp, 
:iKa, :iLag, :iKpb, :iKgp, :ik0bile, :is_bile, :Form_C), Tuple{Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Int64}, Vector{String15}}}})
    @ Pumas C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\Pumas\VyE8h\src\dsl\model_macro.jl:502
  [5] (::Pumas.TimeDispatcher{var"#821#831", var"#822#832"})(param::NamedTuple{(:σ_add, :σ_prop), Tuple{Float64, Float64}}, randeffs::NamedTuple{(), Tuple{}}, subject::Subject{NamedTuple{(:Conc,), Tuple{Vector{Union{Missing, Float64}}}}, Pumas.ConstantCovar{NamedTuple{(:iCl, :iVc, :iQ, :iVp, :iKa, :iLag, :iKpb, :iKgp, :ik0bile, :is_bile, :Form_C), Tuple{Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Int64}, Vector{String15}}}}, Vector{Pumas.Event{Float64, Float64, Float64, Float64, Float64, Float64, Int64}}, Vector{Float64}})
    @ Pumas C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\Pumas\VyE8h\src\dsl\model_macro.jl:499
  [6] pre(model::PumasModel{(σ_prop = 1, σ_add = 1), 0, (:Depot, :Central, :Peripheral, :Bile, :Gut), ParamSet{NamedTuple{(:σ_prop, :σ_add), Tuple{RealDomain{Float64, TransformVariables.Infinity{true}, Float64}, RealDomain{Float64, TransformVariables.Infinity{true}, Float64}}}}, var"#820#830", Pumas.TimeDispatcher{var"#821#831", var"#822#832"}, Pumas.DCPChecker{Pumas.TimeDispatcher{var"#824#834", var"#825#835"}}, var"#827#837", Pumas.LinearODE, var"#828#838", var"#829#839", ModelingToolkit.ODESystem}, subject::Subject{NamedTuple{(:Conc,), Tuple{Vector{Union{Missing, Float64}}}}, Pumas.ConstantCovar{NamedTuple{(:iCl, :iVc, :iQ, :iVp, :iKa, :iLag, :iKpb, :iKgp, :ik0bile, :is_bile, :Form_C), Tuple{Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Int64}, Vector{String15}}}}, Vector{Pumas.Event{Float64, Float64, Float64, Float64, Float64, Float64, Int64}}, Vector{Float64}}, param::NamedTuple{(:σ_add, :σ_prop), Tuple{Float64, Float64}}, randeffs::NamedTuple{(), Tuple{}})
    @ Pumas C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\Pumas\VyE8h\src\models\model_api.jl:2167
  [7] simobs(::PumasModel{(σ_prop = 1, σ_add = 1), 0, (:Depot, :Central, :Peripheral, :Bile, :Gut), ParamSet{NamedTuple{(:σ_prop, :σ_add), Tuple{RealDomain{Float64, TransformVariables.Infinity{true}, Float64}, RealDomain{Float64, TransformVariables.Infinity{true}, Float64}}}}, var"#820#830", Pumas.TimeDispatcher{var"#821#831", var"#822#832"}, Pumas.DCPChecker{Pumas.TimeDispatcher{var"#824#834", var"#825#835"}}, var"#827#837", Pumas.LinearODE, var"#828#838", var"#829#839", ModelingToolkit.ODESystem}, ::Subject{NamedTuple{(:Conc,), Tuple{Vector{Union{Missing, Float64}}}}, Pumas.ConstantCovar{NamedTuple{(:iCl, :iVc, :iQ, :iVp, :iKa, :iLag, :iKpb, :iKgp, :ik0bile, :is_bile, :Form_C), Tuple{Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Int64}, Vector{String15}}}}, Vector{Pumas.Event{Float64, Float64, Float64, Float64, Float64, Float64, Int64}}, Vector{Float64}}, ::NamedTuple{(:σ_add, :σ_prop), Tuple{Float64, Float64}}, ::Nothing; obstimes::Vector{Float64}, ensemblealg::EnsembleSerial, diffeq_options::NamedTuple{(:alg, :callback), Tuple{OrdinaryDiffEq.CompositeAlgorithm{Tuple{OrdinaryDiffEq.Tsit5{typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}, Rosenbrock23{1, true, LinearSolve.LUFactorization{LinearAlgebra.RowMaximum}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, OrdinaryDiffEq.AutoSwitch{OrdinaryDiffEq.Tsit5{typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}, Rosenbrock23{1, true, LinearSolve.LUFactorization{LinearAlgebra.RowMaximum}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}, Rational{Int64}, Int64}}, Nothing}}, rng::TaskLocalRNG, simulate_error::Val{true}, isfor_derived::Val{false}, return_model::Val{true})
    @ Pumas C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\Pumas\VyE8h\src\models\model_api.jl:1532
  [8] #_simobs!#359
    @ C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\Pumas\VyE8h\src\models\model_api.jl:1829 [inlined]
  [9] _simobs!
    @ C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\Pumas\VyE8h\src\models\model_api.jl:1810 [inlined]
 [10] _simobs(::PumasModel{(σ_prop = 1, σ_add = 1), 0, (:Depot, :Central, :Peripheral, :Bile, :Gut), ParamSet{NamedTuple{(:σ_prop, :σ_add), Tuple{RealDomain{Float64, TransformVariables.Infinity{true}, Float64}, RealDomain{Float64, TransformVariables.Infinity{true}, Float64}}}}, var"#820#830", Pumas.TimeDispatcher{var"#821#831", var"#822#832"}, Pumas.DCPChecker{Pumas.TimeDispatcher{var"#824#834", var"#825#835"}}, var"#827#837", Pumas.LinearODE, var"#828#838", var"#829#839", ModelingToolkit.ODESystem}, ::Vector{Subject{NamedTuple{(:Conc,), Tuple{Vector{Union{Missing, Float64}}}}, Pumas.ConstantCovar{NamedTuple{(:iCl, :iVc, :iQ, :iVp, :iKa, :iLag, :iKpb, :iKgp, :ik0bile, :is_bile, :Form_C), Tuple{Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Int64}, Vector{String15}}}}, Vector{Pumas.Event{Float64, Float64, Float64, Float64, Float64, Float64, Int64}}, Vector{Float64}}}, ::StaticArraysCore.SVector{1, NamedTuple{(:σ_add, :σ_prop), Tuple{Float64, Float64}}}, ::Nothing; rng::TaskLocalRNG, diffeq_options::NamedTuple{(), Tuple{}}, isfor_derived::Val{false}, simulate_error::Val{true}, obstimes::Vector{Float64}, ensemblealg::EnsembleSerial)
    @ Pumas C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\Pumas\VyE8h\src\models\model_api.jl:2112
 [11] _simobs
    @ C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\Pumas\VyE8h\src\models\model_api.jl:2023 [inlined]
 [12] #simobs#370
    @ C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\Pumas\VyE8h\src\models\model_api.jl:1991 [inlined]
 [13] simobs
    @ C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\Pumas\VyE8h\src\models\model_api.jl:1966 [inlined]
 [14] top-level scope

```

I am not able to understand what this error means. Any help deciphering it is appreciated. Thanks.

---

<div class="post-metadata">

**Author:** ![vijay](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/vijay/32/96_2.png) [@vijay](https://discourse.pumas.ai/u/vijay)\
**Post date:** [October 16, 2023, 8:39am UTC](https://discourse.pumas.ai/t/no-method-matching-zero/949/2 "2023-10-16T08:39:19Z")

</div>

> [@MathangiCTM](#):
>
> `param_2cmt_ehc`

Can you show this object that you passed into the simobs

---

<div class="post-metadata">

**Author:** ![MathangiCTM](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/mathangictm/32/142_2.png) [@MathangiCTM](https://discourse.pumas.ai/u/MathangiCTM)\
**Post date:** [October 16, 2023, 9:03am UTC](https://discourse.pumas.ai/t/no-method-matching-zero/949/3 "2023-10-16T09:03:36Z")

</div>

@vijay Here it is:

```auto
param_2cmt_ehc = (
        σ_add = 50.0,
        σ_prop = 0.15
        )

```

---

<div class="post-metadata">

**Author:** ![vijay](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/vijay/32/96_2.png) [@vijay](https://discourse.pumas.ai/u/vijay)\
**Post date:** [October 16, 2023, 9:30am UTC](https://discourse.pumas.ai/t/no-method-matching-zero/949/4 "2023-10-16T09:30:29Z")

</div>

Can you try with this please

```auto
simobs(
        pilot_fast_2cmt_katlag_ehc,
        pop_fit_df.pop[1],
        param_2cmt_ehc,
        obstimes=[0.08,0.17,0.25,0.5,1.0,1.5,2.0,3.0,4.0,6.0,8.0,10.0,12.0,16.0,18.0,24.0]
        #rng=rng
    )

```

---

<div class="post-metadata">

**Author:** ![MathangiCTM](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/mathangictm/32/142_2.png) [@MathangiCTM](https://discourse.pumas.ai/u/MathangiCTM)\
**Post date:** [October 16, 2023, 9:49am UTC](https://discourse.pumas.ai/t/no-method-matching-zero/949/5 "2023-10-16T09:49:08Z")

</div>

Still getting the same error.

```auto
ERROR: MethodError: no method matching zero(::Type{Array{Float64}})

Closest candidates are:
  zero(::Union{Type{P}, P}) where P<:Period
   @ Dates C:\Pumas-v2.4.1\Julia-1.9.2\share\julia\stdlib\v1.9\Dates\src\periods.jl:51
  zero(::Union{AbstractAlgebra.Generic.LaurentSeriesFieldElem{T}, AbstractAlgebra.Generic.LaurentSeriesRingElem{T}} where T<:AbstractAlgebra.RingElement)
   @ AbstractAlgebra C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\AbstractAlgebra\FcxWh\src\generic\LaurentSeries.jl:466     
  zero(::Union{AbstractAlgebra.Generic.LaurentSeriesFieldElem{T}, AbstractAlgebra.Generic.LaurentSeriesRingElem{T}} where T<:AbstractAlgebra.RingElement, ::String; cached)
   @ AbstractAlgebra C:\a\PumasSystemImages\PumasSystemImages\julia_depot\packages\AbstractAlgebra\FcxWh\src\generic\LaurentSeries.jl:480     
  ...

```

If you need to see the `pop_fit_df.pop` this is how I have it.

```auto
    pop_fit_df = combine(
        groupby(rep_df, :REP),
        t -> (pop = read_pumas(
            t;
            id = :id,
            observations = [:Conc],
            covariates = [:iCl, :iVc, :iQ, :iVp, :iKa, :iLag, :iKpb, :iKgp, :ik0bile, :is_bile, :Form_C],
            time = :time,
            amt= :amt,
            cmt= :cmt,
            evid = :evid
            ),)
    )

```

Right now, I am running one rep.

```auto
48×2 DataFrame
 Row │ REP pop
     │ Int64 Subject…
─────┼──────────────────────────────────
   1 │ 1 Subject(id = r1fjYN, ...)
   2 │ 1 Subject(id = CzySNV, ...)
   3 │ 1 Subject(id = OMXW3R, ...)
   4 │ 1 Subject(id = sAwVWJ, ...)
   5 │ 1 Subject(id = zy0RbI, ...)
   6 │ 1 Subject(id = SIt6UZ, ...)
  ⋮ │ ⋮ ⋮
  44 │ 1 Subject(id = w7hmQA, ...)
  45 │ 1 Subject(id = vM8N6b, ...)
  46 │ 1 Subject(id = C1YBt0, ...)
  47 │ 1 Subject(id = lTWD0c, ...)
  48 │ 1 Subject(id = BifVDE, ...)
                         37 rows omitted

```

---

<div class="post-metadata">

**Author:** ![andreasnoack](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/andreasnoack/32/22_2.png) [@andreasnoack](https://discourse.pumas.ai/u/andreasnoack)\
**Post date:** [October 16, 2023, 11:27am UTC](https://discourse.pumas.ai/t/no-method-matching-zero/949/6 "2023-10-16T11:27:40Z")

</div>

Could you please share the result of

```julia
pop_fit_df.pop[1].covariates

```

---

<div class="post-metadata">

**Author:** ![MathangiCTM](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/mathangictm/32/142_2.png) [@MathangiCTM](https://discourse.pumas.ai/u/MathangiCTM)\
**Post date:** [October 16, 2023, 11:40am UTC](https://discourse.pumas.ai/t/no-method-matching-zero/949/7 "2023-10-16T11:40:02Z")

</div>

@andreasnoack Here it is.

```auto
Pumas.ConstantCovar{NamedTuple{(:iCl, :iVc, :iQ, :iVp, :iKa, :iLag, :iKpb, :iKgp, :ik0bile, :is_bile, :Form_C), Tuple{Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Float64}, Vector{Int64}, Vector{String15}}}}((iCl = [3605.0619119801404], iVc = [5443.37263296165], iQ = [6011.470769053865], iVp = [20793.580152771443], iKa = [2.0464227778328072], iLag = [0.2941399587159395], iKpb = [1.2750117011351623], iKgp = [0.8679120706896064], ik0bile = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 1.9915461368456517, 1.9915461368456517, 1.9915461368456517, 1.9915461368456517, 0.0, 0.0, 0.0], is_bile = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0 … 0, 0, 0, 1, 1, 1, 1, 0, 0, 0], Form_C = String15["Test"]))

```

FYI - I have the `is_bile` variable which takes a value of `1` for time between `4 to 10 hours` and `0` otherwise.

---

<div class="post-metadata">

**Author:** ![andreasnoack](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/andreasnoack/32/22_2.png) [@andreasnoack](https://discourse.pumas.ai/u/andreasnoack)\
**Post date:** [October 16, 2023, 12:01pm UTC](https://discourse.pumas.ai/t/no-method-matching-zero/949/8 "2023-10-16T12:01:58Z")

</div>

Something is off with the covariates. Could you show us a bit of `rep_df`? What are the columns types of the covariates?

---

<div class="post-metadata">

**Author:** ![MathangiCTM](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/mathangictm/32/142_2.png) [@MathangiCTM](https://discourse.pumas.ai/u/MathangiCTM)\
**Post date:** [October 16, 2023, 12:46pm UTC](https://discourse.pumas.ai/t/no-method-matching-zero/949/9 "2023-10-16T12:46:25Z")

</div>

Here it is:

 ![pumascode](https://canada1.discourse-cdn.com/flex030/uploads/pumas/original/1X/8772be931ef85a01f3d9690ef796c9b03c8a0bb0.png)  
 ![pumascode1](https://canada1.discourse-cdn.com/flex030/uploads/pumas/original/1X/88098165bb07e016b2f0d857964ddfc42860a4c5.png)

---

<div class="post-metadata">

**Author:** ![andreasnoack](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/andreasnoack/32/22_2.png) [@andreasnoack](https://discourse.pumas.ai/u/andreasnoack)\
**Post date:** [October 16, 2023, 12:48pm UTC](https://discourse.pumas.ai/t/no-method-matching-zero/949/10 "2023-10-16T12:48:28Z")

</div>

That is the issue. For some reason, each element in the data frame column is an array. How did you construct this data frame?

---

<div class="post-metadata">

**Author:** ![MathangiCTM](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/mathangictm/32/142_2.png) [@MathangiCTM](https://discourse.pumas.ai/u/MathangiCTM)\
**Post date:** [October 20, 2023, 5:55pm UTC](https://discourse.pumas.ai/t/no-method-matching-zero/949/11 "2023-10-20T17:55:47Z")

</div>

@andreasnoack Thanks for pointing out the error.  
I was able to solve constructing the populations properly with internal help.

Thanks.