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further doc improvements
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docs/make.jl

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"Solvers" => [
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"sgfevector.md",
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"modelproblems.md",
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]
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"Adaptivity" => [
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"estimators.md",
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]
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"Plotting" => [

src/coefficients/coefficients.jl

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A stochastic coefficient is assumed to have the Karhunen-Loeve expansion form
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a(x,y) = a_0(x) + ∑_m y_m a_m(x)
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``a(x,y) = a_0(x) + ∑_m y_m a_m(x)``
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with (centered independent) random variables `y_m` and
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basis functions `a_m(x)` that need to be specified (together with their gradients)
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and expectation value `a_0`
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with (centered independent) random variables ``y_m`` and
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basis functions ``a_m(x)`` that need to be specified (together with their gradients)
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and expectation value ``a_0``
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(in general they steam from a spectral analysis of the covariance operator
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of a).
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of ``a``).
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"""

src/modelproblems/logpoisson_dual.jl

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"""
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$(TYPEDEF)
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Dual log-transformed formulation of the Poisson problem with exponential stochastic coefficient.
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Dual log-transformed formulation of the Poisson problem with exponential stochastic coefficient (WIP).
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"""
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abstract type LogTransformedPoissonProblemDual <: AbstractModelProblem end
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src/modelproblems/logpoisson_primal.jl

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"""
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$(TYPEDEF)
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Log-transformed formulation of the Poisson problem with exponential stochastic coefficient.
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Poisson problem with exponential stochastic coefficient ``e^a`` that seeks ``u`` such that
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``-\\mathrm{div}(e^a(y,x) \\nabla u(y,x)) = f(x) \\quad \\text{for } (y,x) \\in \\Gamma \\times D``
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The stochastic Galerkin FEM solves the equivalent transformed problem
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``-\\mathrm{div}(\\nabla u(y,x)) - \\nabla a(y,x) \\cdot \\nabla u(y,x) = e^{-a(y,x)} f(x) \\quad \\text{for } (y,x) \\in \\Gamma \\times D``
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"""
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abstract type LogTransformedPoissonProblemPrimal <: AbstractModelProblem end
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src/modelproblems/poisson_primal.jl

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"""
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$(TYPEDEF)
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Poisson problem with linear stochastic coefficient.
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Poisson problem with linear stochastic coefficient ``a`` that seeks ``u`` such that
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``-\\mathrm{div}(a(y,x) \\nabla u(y,x)) = f(x) \\quad \\text{for } (y,x) \\in \\Gamma \\times D``
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"""
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abstract type PoissonProblemPrimal <: AbstractModelProblem end
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