Commit 9f597476 authored by Johannes Blaschke's avatar Johannes Blaschke
Browse files

cleanup module hirearchy

parent 1efb2d33

1d_diffusion.ipynb

+27 −17
Original line number Diff line number Diff line 
%% Cell type:code id: tags:



``` julia

include("src/flux_array.jl")

include("src/fhd.jl")

```



%% Output



    Main.ModFluxArray

    Main.FHD



%% Cell type:code id: tags:



``` julia

using .ModFluxArray

using .FHD

```



%% Cell type:code id: tags:



``` julia

N = 10

D = 1.;

h = 1e-3;

k = 1.;

```



%% Cell type:code id: tags:



``` julia

FluxArray{Float64}

```



%% Output



    FluxArray{Float64}



%% Cell type:code id: tags:



``` julia

n = DistributionArray{Float64}(0., 1., N);

f = FluxArray{Float64}(N);

```



%% Cell type:code id: tags:



``` julia

n.p[Integer(size(n)/2)] = 1;

n.p

```



%% Output



    10-element Array{Float64,1}:

     0.0

     0.0

     0.0

     0.0

     1.0

     0.0

     0.0

     0.0

     0.0

     0.0



%% Cell type:code id: tags:



``` julia

fill_fr!(f);

fill_lr!(f, n.p);

```



%% Cell type:code id: tags:



``` julia

f.left

```



%% Output



    10-element Array{Float64,1}:

     0.0

     0.0

     0.0

     0.0

     0.1936697622933632

     0.8892007282354997

     0.0

     0.0

     0.0

     0.0

     0.0



%% Cell type:code id: tags:



``` julia

f.right

```



%% Output



    10-element Array{Float64,1}:

     0.0

     0.0

     0.0

     0.0

     0.8063302377066368

     0.11079927176450033

     0.0

     0.0

     0.0

     0.0

     0.0



%% Cell type:code id: tags:



``` julia

f.left .+ f.right

```



%% Output



    10-element Array{Float64,1}:

     0.0

     0.0

     0.0

     0.0

     1.0

     0.0

     0.0

     0.0

     0.0

     0.0



%% Cell type:code id: tags:



``` julia

fill_df!(f, D, h);

```



%% Cell type:code id: tags:



``` julia

f.diffusive

```



%% Output



    11-element Array{Float64,1}:

        0.0

        0.0

        0.0

        0.0

      193.6697622933632

     -806.3302377066368

      122.48749433947626

     -877.5125056605237

        0.0

        0.0

        0.0

        0.0

        0.0



%% Cell type:code id: tags:



``` julia

fill_sf!(f, D, h, k);

```



%% Cell type:code id: tags:



``` julia

f.stochastic

```



%% Output



    11-element Array{Float64,1}:

      1.662956306086986

      0.0

      0.769796229343863

     -0.0

     -0.0

      4.240011808025856

      2.710972258785979

     -0.0

      0.0

     -4.0441835514004545

     -2.5447437949849974

     -0.0

     -0.0

     -0.0

     -0.0

     -0.3416384648516665

      0.36347271419150995



%% Cell type:code id: tags:



``` julia

apply_bc!(f);

```



%% Cell type:code id: tags:



``` julia

f.stochastic

```



%% Output



    11-element Array{Float64,1}:

      0.0

      0.0

     -0.0

     -0.0

      4.240011808025856

      2.710972258785979

     -0.0

      0.0

     -4.0441835514004545

     -2.5447437949849974

     -0.0

     -0.0

     -0.0

     -0.0

      0.0



%% Cell type:code id: tags:



``` julia

```

src/distribution_array.jl

0 → 100644
+32 −0
Original line number Diff line number Diff line 
#module DistributionArrayModule



# export DistributionArray, size



"""

DistributionArrays store the distribution (probablity) `p` data, together with

the cell-center `xc` and face-center `xf` coodrdinates. This is essentially a

cheap histogram.

"""

mutable struct DistributionArray{T}



    xc::Array{T};

    xf::Array{T};

    p::Array{T};



    function DistributionArray{T}(xlo::T, xhi::T, n::Integer) where T

        p::Array{T} = zeros(n);



        xf::Array{T} = collect(range(xlo, stop = xhi, length = n+1));

        

        dx::T = (xhi-xlo)/n;

        xc::Array{T} = xf[1:n] .+ dx/2;

        

        new{T}(xc, xf, p)

    end

end



function size(d::DistributionArray{T}) where T

    return size(d.p, 1)

end



# end
 
 No newline at end of file

src/fhd.jl

0 → 100644
+18 −0
Original line number Diff line number Diff line 
module FHD



include("flux_array.jl")

#import  .FluxArrayModule



include("distribution_array.jl")

#import .DistributionArrayModule



include("sample.jl")

#import  .SampleModule



export FluxArray, DistributionArray

export size, reset!, fill_fr!, fill_lr!, fill_df!, fill_sf!, apply_bc!



#size(d::FluxArray{T}) where T = FluxArrayModule.size(d)

#size(d::DistributionArray{T}) where T = DistributionArrayModule.size(d)



end
 
 No newline at end of file

src/flux_array.jl

+5 −39
Original line number Diff line number Diff line 
module StochFluxArray

# module FluxArrayModule



export DistributionArray

export size

export FluxArray, reset!, fill_fr!, fill_lr!, fill_df!, fill_sf!, apply_bc!

# export FluxArray, size, reset!, fill_fr!, fill_lr!, fill_df!, fill_sf!, apply_bc!



import Base.size

import Random.rand!

import Distributions.Normal



include("sample.jl")

import .Sample





"""

DistributionArrays store the distribution (probablity) `p` data, together with

the cell-center `xc` and face-center `xf` coodrdinates. This is essentially a

cheap histogram.

"""

mutable struct DistributionArray{T}



    xc::Array{T};

    xf::Array{T};

    p::Array{T};



    function DistributionArray{T}(xlo::T, xhi::T, n::Integer) where T

        p::Array{T} = zeros(n);



        xf::Array{T} = collect(range(xlo, stop = xhi, length = n+1));

        

        dx::T = (xhi-xlo)/n;

        xc::Array{T} = xf[1:n] .+ dx/2;

        

        new{T}(xc, xf, p)

    end

end



function size(d::DistributionArray{T}) where T

    return size(d.p, 1)

end



#include("sample.jl")

#import .SampleModule





"""
@@ -181,7 +150,4 @@ function fill_ft!(flx::FluxArray{T}, h::T, k::T) where T 
    end

end









end
 
 No newline at end of file
 
# end
 
 No newline at end of file

src/sample.jl

+3 −3
Original line number Diff line number Diff line 
module Sample

# module SampleModule



export Proposal, rejection_sample

# export Proposal, rejection_sample



import Random.rand
@@ -39,4 +39,4 @@ function rejection_sample(x::Array{T}, p::Array{T}, P::T, trials::Integer=1000) 
    return Proposal(T(0), false);

end



end
 
 No newline at end of file
 
# end
 
 No newline at end of file