added simplified histogram (abdfc5f2) · Commits · Johannes Blaschke / FHD.jl

1d_diffusion.ipynb

+29 −18

Original line number	Diff line number	Diff line
		%% Cell type:code id: tags:

		``` julia
		include("src/fp.jl")
		```

		%% Output

		Main.FP

		%% Cell type:code id: tags:

		``` julia
		using .FP
		```

		%% Cell type:code id: tags:

		``` julia
		N = 10
		D = 1.;
		h = 1e-3;
		k = 1.;
		```

		%% Cell type:code id: tags:

		``` julia
		n = zeros(N);
		n = DistributionArray{Float64}(0., 1., N);
		f = FluxArray{Float64}(N);
		```

		%% Cell type:code id: tags:

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

		%% Output

		1
		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);
		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
		0.13816584763737239
		0.0022742765607139948
		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
		0.8618341523626276
		0.997725723439286
		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
		138.1658476373724
		-861.8341523626276
		2.2742765607139948
		-997.725723439286
		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}:
		-0.42054232430683963
		-0.0
		0.0
		-0.8640646960498399
		0.0
		0.9582299402193841
		9.427963410111976
		0.0
		-0.0
		0.3672085709169771
		-2.924360797089483
		0.0
		0.0
		-0.0
		0.6927609681908308
		0.0
		0.3838915655069409

		%% 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
		0.9582299402193841
		9.427963410111976
		0.0
		-0.0
		0.3672085709169771
		-2.924360797089483
		0.0
		0.0
		-0.0
		0.0
		0.0

		%% Cell type:code id: tags:

		``` julia
		```

src/fp.jl

+40 −9

Original line number	Diff line number	Diff line
		module FP

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

		import Base.size
		import Random.rand!
		@@ -10,6 +12,35 @@ 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



		"""
		FluxArrays store flux data as Struct-of-Arrays. These arrays are allocated and
		initialized (to zero) by the constructor (each array has length `n+1` where `n`
		@@ -18,23 +49,23 @@ is the argument of the constructor).
		mutable struct FluxArray{T}

		# Fluxes
		total::Array{T}
		diffusive::Array{T}
		stochastic::Array{T}
		total::Array{T};
		diffusive::Array{T};
		stochastic::Array{T};

		# Left and Right sampling
		fr::Array{T}
		left::Array{T}
		right::Array{T}
		fr::Array{T};
		left::Array{T};
		right::Array{T};

		# Storage for the Dististribution object (used to sample Gaussian random variables)
		distribution
		distribution;

		"""
		Constructor: allocates memory for all fluxes, and intializes the distribution
		object. Note that `n` is the length of the corresponding 1D data array.
		"""
		function FluxArray{T}(n) where T
		function FluxArray{T}(n::Integer) where T
		total::Array{T} = zeros(n + 1);
		diffusive::Array{T} = zeros(n + 1);
		stochastic::Array{T} = zeros(n + 1);