From 88ec7cd24680c85adfc3ec12385bead9f8090577 Mon Sep 17 00:00:00 2001 From: Cmurilochem Date: Thu, 19 Sep 2024 14:26:54 +0200 Subject: [PATCH 01/14] Add initial structure with Literate --- docs/Project.toml | 1 + docs/make.jl | 13 +++++++++++++ docs/poisson_tutorial.jl | 15 +++++++++++++++ docs/src/tutorials/poisson_tutorial.md | 23 +++++++++++++++++++++++ 4 files changed, 52 insertions(+) create mode 100644 docs/poisson_tutorial.jl create mode 100644 docs/src/tutorials/poisson_tutorial.md diff --git a/docs/Project.toml b/docs/Project.toml index 0d0ac5d1..22f0f6e2 100644 --- a/docs/Project.toml +++ b/docs/Project.toml @@ -1,3 +1,4 @@ [deps] Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4" GalerkinToolkit = "5e3ba9c4-dd81-444d-b69a-0e7bd7bf60a4" +Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306" diff --git a/docs/make.jl b/docs/make.jl index 144b9bbd..ba304a92 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -1,8 +1,18 @@ using GalerkinToolkit +using Literate using Documenter DocMeta.setdocmeta!(GalerkinToolkit, :DocTestSetup, :(using GalerkinToolkit); recursive=true) +src_dir = joinpath(@__DIR__, "src") +tutorials_dir = joinpath(@__DIR__, "src/tutorials") + +tutorials = ["poisson_tutorial.jl"] +for tutorial in tutorials + tutorial_jl = joinpath(@__DIR__, tutorial) + Literate.markdown(tutorial_jl, tutorials_dir) +end + makedocs(; modules=[GalerkinToolkit], authors="Francesc Verdugo and contributors", @@ -14,6 +24,9 @@ makedocs(; ), pages=[ "Home" => "index.md", + "Tutorials" =>[ + "Poisson equation" => "tutorials/poisson_tutorial.md", + ], "Reference" =>[ "Geometry" => "reference/geometry.md", "Integration" => "reference/integration.md", diff --git a/docs/poisson_tutorial.jl b/docs/poisson_tutorial.jl new file mode 100644 index 00000000..f95f66a6 --- /dev/null +++ b/docs/poisson_tutorial.jl @@ -0,0 +1,15 @@ +# In this tutorial, we will learn +# +# - How to solve a simple PDE in Julia with Gridap +# - How to load a discrete model (aka a FE mesh) from a file +# - How to build a conforming Lagrangian FE space +# - How to define the different terms in a weak form +# - How to impose Dirichlet and Neumann boundary conditions +# - How to visualize results +# +# +# ## Problem statement +# +# In this first tutorial, we provide an overview of a complete simulation pipeline in Gridap: from the construction of the FE mesh to the visualization of the computed results. To this end, we consider a simple model problem: the Poisson equation. +# We want to solve the Poisson equation on the 3D domain depicted in next figure with Dirichlet and Neumann boundary conditions. Dirichlet boundary conditions are applied on $\Gamma_{\rm D}$, being the outer sides of the prism (marked in red). Non-homogeneous Neumann conditions are applied to the internal boundaries $\Gamma_{\rm G}$, $\Gamma_{\rm Y}$, and $\Gamma_{\rm B}$ (marked in green, yellow and blue respectively). And homogeneous Neumann boundary conditions are applied in $\Gamma_{\rm W}$, the remaining portion of the boundary (marked in white). +# \ No newline at end of file diff --git a/docs/src/tutorials/poisson_tutorial.md b/docs/src/tutorials/poisson_tutorial.md new file mode 100644 index 00000000..773b3432 --- /dev/null +++ b/docs/src/tutorials/poisson_tutorial.md @@ -0,0 +1,23 @@ +```@meta +EditURL = "../../poisson_tutorial.jl" +``` + +In this tutorial, we will learn + + - How to solve a simple PDE in Julia with Gridap + - How to load a discrete model (aka a FE mesh) from a file + - How to build a conforming Lagrangian FE space + - How to define the different terms in a weak form + - How to impose Dirichlet and Neumann boundary conditions + - How to visualize results + + +## Problem statement + +In this first tutorial, we provide an overview of a complete simulation pipeline in Gridap: from the construction of the FE mesh to the visualization of the computed results. To this end, we consider a simple model problem: the Poisson equation. + We want to solve the Poisson equation on the 3D domain depicted in next figure with Dirichlet and Neumann boundary conditions. Dirichlet boundary conditions are applied on $\Gamma_{\rm D}$, being the outer sides of the prism (marked in red). Non-homogeneous Neumann conditions are applied to the internal boundaries $\Gamma_{\rm G}$, $\Gamma_{\rm Y}$, and $\Gamma_{\rm B}$ (marked in green, yellow and blue respectively). And homogeneous Neumann boundary conditions are applied in $\Gamma_{\rm W}$, the remaining portion of the boundary (marked in white). + +--- + +*This page was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).* + From 5d14fd9ed94a511b157974dc3e25f94d3512208b Mon Sep 17 00:00:00 2001 From: Cmurilochem Date: Thu, 19 Sep 2024 15:46:29 +0200 Subject: [PATCH 02/14] Add tutorial assets --- docs/poisson_tutorial.jl | 34 ++++++++++++++++- .../assets/poisson/fig_faces_on_circle.png | Bin 0 -> 193345 bytes docs/src/assets/poisson/fig_uh.png | Bin 0 -> 54343 bytes .../assets/poisson/fig_vertices_on_sides.png | Bin 0 -> 107689 bytes docs/src/assets/poisson/model-r1-2.png | Bin 0 -> 11516 bytes docs/src/tutorials/poisson_tutorial.md | 35 ++++++++++++++++++ 6 files changed, 68 insertions(+), 1 deletion(-) create mode 100644 docs/src/assets/poisson/fig_faces_on_circle.png create mode 100644 docs/src/assets/poisson/fig_uh.png create mode 100644 docs/src/assets/poisson/fig_vertices_on_sides.png create mode 100644 docs/src/assets/poisson/model-r1-2.png diff --git a/docs/poisson_tutorial.jl b/docs/poisson_tutorial.jl index f95f66a6..11fff88b 100644 --- a/docs/poisson_tutorial.jl +++ b/docs/poisson_tutorial.jl @@ -1,3 +1,5 @@ +# # Poisson equation +# # In this tutorial, we will learn # # - How to solve a simple PDE in Julia with Gridap @@ -12,4 +14,34 @@ # # In this first tutorial, we provide an overview of a complete simulation pipeline in Gridap: from the construction of the FE mesh to the visualization of the computed results. To this end, we consider a simple model problem: the Poisson equation. # We want to solve the Poisson equation on the 3D domain depicted in next figure with Dirichlet and Neumann boundary conditions. Dirichlet boundary conditions are applied on $\Gamma_{\rm D}$, being the outer sides of the prism (marked in red). Non-homogeneous Neumann conditions are applied to the internal boundaries $\Gamma_{\rm G}$, $\Gamma_{\rm Y}$, and $\Gamma_{\rm B}$ (marked in green, yellow and blue respectively). And homogeneous Neumann boundary conditions are applied in $\Gamma_{\rm W}$, the remaining portion of the boundary (marked in white). -# \ No newline at end of file +# +# ![](../assets/poisson/model-r1-2.png) +# +# Formally, the problem to solve is: find the scalar field $u$ such that +# +# ```math +# \left\lbrace +# \begin{aligned} +# -\Delta u = f \ &\text{in} \ \Omega,\\ +# u = g \ &\text{on}\ \Gamma_{\rm D},\\ +# \nabla u\cdot n = h \ &\text{on}\ \Gamma_{\rm N},\\ +# \end{aligned} +# \right. +# ``` +# being $n$ the outwards unit normal vector to the Neumann boundary $\Gamma_{\rm N} \doteq \Gamma_{\rm G}\cup\Gamma_{\rm Y}\cup\Gamma_{\rm B}\cup\Gamma_{\rm W}$. In this example, we chose $f(x) = 1$, $g(x) = 2$, and $h(x)=3$ on $\Gamma_{\rm G}\cup\Gamma_{\rm Y}\cup\Gamma_{\rm B}$ and $h(x)=0$ on $\Gamma_{\rm W}$. The variable $x$ is the position vector $x=(x_1,x_2,x_3)$. +# +# ## Numerical scheme +# +# To solve this PDE, we use a conventional Galerkin finite element (FE) method with conforming Lagrangian FE spaces (see, e.g., [1] for specific details on this formulation). The weak form associated with this formulation is: find $u\in U_g$ such that $ a(u,v) = b(v) $ for all $v\in V_0$, where $U_g$ and $V_0$ are the subset of functions in $H^1(\Omega)$ that fulfill the Dirichlet boundary condition $g$ and $0$ respectively. The bilinear and linear forms for this problems are +# ```math +# a(u,v) \doteq \int_{\Omega} \nabla v \cdot \nabla u \ {\rm d}\Omega, \quad b(v) \doteq \int_{\Omega} v\ f \ {\rm d}\Omega + \int_{\Gamma_{\rm N}} v\ h \ {\rm d}\Gamma_{\rm N}. +# ``` +# The problem is solved numerically by approximating the spaces $U_g$ and $V_0$ by their discrete counterparts associated with a FE mesh of the computational domain $\Omega$. As we have anticipated, we consider standard conforming Lagrangian FE spaces for this purpose. +# +# The implementation of this numerical scheme in GalerkinToolkit is done in a user-friendly way thanks to the abstractions provided by the library. As it will be seen below, all the mathematical objects involved in the definition of the discrete weak problem have a correspondent representation in the code. +# +# ## Setup +# +# The step number 0 in order to solve the problem is to load the GalerkinToolkit library in the code. 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To this end, we consider a simple model problem: the Poisson equation. We want to solve the Poisson equation on the 3D domain depicted in next figure with Dirichlet and Neumann boundary conditions. Dirichlet boundary conditions are applied on $\Gamma_{\rm D}$, being the outer sides of the prism (marked in red). Non-homogeneous Neumann conditions are applied to the internal boundaries $\Gamma_{\rm G}$, $\Gamma_{\rm Y}$, and $\Gamma_{\rm B}$ (marked in green, yellow and blue respectively). And homogeneous Neumann boundary conditions are applied in $\Gamma_{\rm W}$, the remaining portion of the boundary (marked in white). +![](../assets/poisson/model-r1-2.png) + + Formally, the problem to solve is: find the scalar field $u$ such that + +```math +\left\lbrace +\begin{aligned} +-\Delta u = f \ &\text{in} \ \Omega,\\ +u = g \ &\text{on}\ \Gamma_{\rm D},\\ +\nabla u\cdot n = h \ &\text{on}\ \Gamma_{\rm N},\\ +\end{aligned} +\right. +``` + being $n$ the outwards unit normal vector to the Neumann boundary $\Gamma_{\rm N} \doteq \Gamma_{\rm G}\cup\Gamma_{\rm Y}\cup\Gamma_{\rm B}\cup\Gamma_{\rm W}$. In this example, we chose $f(x) = 1$, $g(x) = 2$, and $h(x)=3$ on $\Gamma_{\rm G}\cup\Gamma_{\rm Y}\cup\Gamma_{\rm B}$ and $h(x)=0$ on $\Gamma_{\rm W}$. The variable $x$ is the position vector $x=(x_1,x_2,x_3)$. + + ## Numerical scheme + + To solve this PDE, we use a conventional Galerkin finite element (FE) method with conforming Lagrangian FE spaces (see, e.g., [1] for specific details on this formulation). The weak form associated with this formulation is: find $u\in U_g$ such that $ a(u,v) = b(v) $ for all $v\in V_0$, where $U_g$ and $V_0$ are the subset of functions in $H^1(\Omega)$ that fulfill the Dirichlet boundary condition $g$ and $0$ respectively. The bilinear and linear forms for this problems are +```math + a(u,v) \doteq \int_{\Omega} \nabla v \cdot \nabla u \ {\rm d}\Omega, \quad b(v) \doteq \int_{\Omega} v\ f \ {\rm d}\Omega + \int_{\Gamma_{\rm N}} v\ h \ {\rm d}\Gamma_{\rm N}. +``` +The problem is solved numerically by approximating the spaces $U_g$ and $V_0$ by their discrete counterparts associated with a FE mesh of the computational domain $\Omega$. As we have anticipated, we consider standard conforming Lagrangian FE spaces for this purpose. + +The implementation of this numerical scheme in GalerkinToolkit is done in a user-friendly way thanks to the abstractions provided by the library. As it will be seen below, all the mathematical objects involved in the definition of the discrete weak problem have a correspondent representation in the code. + + ## Setup + + The step number 0 in order to solve the problem is to load the GalerkinToolkit library in the code. If you have configured your Julia environment properly, it is simply done with the line: + +````@example poisson_tutorial +import GalerkinToolkit as GT +```` + --- *This page was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).* From 35fa464bc8d28386ca2f8dc612516c166b2d9ba6 Mon Sep 17 00:00:00 2001 From: Cmurilochem Date: Tue, 24 Sep 2024 20:21:45 +0200 Subject: [PATCH 03/14] Fix typo --- docs/poisson_tutorial.jl | 2 +- docs/src/tutorials/poisson_tutorial.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/poisson_tutorial.jl b/docs/poisson_tutorial.jl index 11fff88b..e213896f 100644 --- a/docs/poisson_tutorial.jl +++ b/docs/poisson_tutorial.jl @@ -2,7 +2,7 @@ # # In this tutorial, we will learn # -# - How to solve a simple PDE in Julia with Gridap +# - How to solve a simple PDE in Julia with GalerkinToolkit # - How to load a discrete model (aka a FE mesh) from a file # - How to build a conforming Lagrangian FE space # - How to define the different terms in a weak form diff --git a/docs/src/tutorials/poisson_tutorial.md b/docs/src/tutorials/poisson_tutorial.md index 945c6549..dd819645 100644 --- a/docs/src/tutorials/poisson_tutorial.md +++ b/docs/src/tutorials/poisson_tutorial.md @@ -6,7 +6,7 @@ EditURL = "../../poisson_tutorial.jl" In this tutorial, we will learn - - How to solve a simple PDE in Julia with Gridap + - How to solve a simple PDE in Julia with GalerkinToolkit - How to load a discrete model (aka a FE mesh) from a file - How to build a conforming Lagrangian FE space - How to define the different terms in a weak form From a97f25bf5aa29fc6f9b44495c3fa3cd2159b155c Mon Sep 17 00:00:00 2001 From: Cmurilochem Date: Tue, 24 Sep 2024 20:22:32 +0200 Subject: [PATCH 04/14] Update Francesc email --- docs/make.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/make.jl b/docs/make.jl index ba304a92..f7d55a54 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -15,7 +15,7 @@ end makedocs(; modules=[GalerkinToolkit], - authors="Francesc Verdugo and contributors", + authors="Francesc Verdugo and contributors", sitename="GalerkinToolkit.jl", format=Documenter.HTML(; prettyurls=get(ENV, "CI", "false") == "true", From fb71b2caf2fba61332e0a21fed88df4f9dda0c8f Mon Sep 17 00:00:00 2001 From: Cmurilochem Date: Wed, 25 Sep 2024 11:43:46 +0200 Subject: [PATCH 05/14] Untrack autogenerated tutorials md files and docs/Manifest --- .gitignore | 2 + docs/src/tutorials/poisson_tutorial.md | 58 -------------------------- 2 files changed, 2 insertions(+), 58 deletions(-) delete mode 100644 docs/src/tutorials/poisson_tutorial.md diff --git a/.gitignore b/.gitignore index 3188e47e..7bb7c458 100644 --- a/.gitignore +++ b/.gitignore @@ -7,6 +7,8 @@ /output /Manifest.toml /docs/build/ +/docs/src/tutorials/ +/docs/Manifest.toml .vscode GalerkinToolkitExamples_output/ GalerkinToolkitExamples/Manifest.toml diff --git a/docs/src/tutorials/poisson_tutorial.md b/docs/src/tutorials/poisson_tutorial.md deleted file mode 100644 index dd819645..00000000 --- a/docs/src/tutorials/poisson_tutorial.md +++ /dev/null @@ -1,58 +0,0 @@ -```@meta -EditURL = "../../poisson_tutorial.jl" -``` - -# Poisson equation - -In this tutorial, we will learn - - - How to solve a simple PDE in Julia with GalerkinToolkit - - How to load a discrete model (aka a FE mesh) from a file - - How to build a conforming Lagrangian FE space - - How to define the different terms in a weak form - - How to impose Dirichlet and Neumann boundary conditions - - How to visualize results - - -## Problem statement - -In this first tutorial, we provide an overview of a complete simulation pipeline in Gridap: from the construction of the FE mesh to the visualization of the computed results. To this end, we consider a simple model problem: the Poisson equation. - We want to solve the Poisson equation on the 3D domain depicted in next figure with Dirichlet and Neumann boundary conditions. Dirichlet boundary conditions are applied on $\Gamma_{\rm D}$, being the outer sides of the prism (marked in red). Non-homogeneous Neumann conditions are applied to the internal boundaries $\Gamma_{\rm G}$, $\Gamma_{\rm Y}$, and $\Gamma_{\rm B}$ (marked in green, yellow and blue respectively). And homogeneous Neumann boundary conditions are applied in $\Gamma_{\rm W}$, the remaining portion of the boundary (marked in white). - -![](../assets/poisson/model-r1-2.png) - - Formally, the problem to solve is: find the scalar field $u$ such that - -```math -\left\lbrace -\begin{aligned} --\Delta u = f \ &\text{in} \ \Omega,\\ -u = g \ &\text{on}\ \Gamma_{\rm D},\\ -\nabla u\cdot n = h \ &\text{on}\ \Gamma_{\rm N},\\ -\end{aligned} -\right. -``` - being $n$ the outwards unit normal vector to the Neumann boundary $\Gamma_{\rm N} \doteq \Gamma_{\rm G}\cup\Gamma_{\rm Y}\cup\Gamma_{\rm B}\cup\Gamma_{\rm W}$. In this example, we chose $f(x) = 1$, $g(x) = 2$, and $h(x)=3$ on $\Gamma_{\rm G}\cup\Gamma_{\rm Y}\cup\Gamma_{\rm B}$ and $h(x)=0$ on $\Gamma_{\rm W}$. The variable $x$ is the position vector $x=(x_1,x_2,x_3)$. - - ## Numerical scheme - - To solve this PDE, we use a conventional Galerkin finite element (FE) method with conforming Lagrangian FE spaces (see, e.g., [1] for specific details on this formulation). The weak form associated with this formulation is: find $u\in U_g$ such that $ a(u,v) = b(v) $ for all $v\in V_0$, where $U_g$ and $V_0$ are the subset of functions in $H^1(\Omega)$ that fulfill the Dirichlet boundary condition $g$ and $0$ respectively. The bilinear and linear forms for this problems are -```math - a(u,v) \doteq \int_{\Omega} \nabla v \cdot \nabla u \ {\rm d}\Omega, \quad b(v) \doteq \int_{\Omega} v\ f \ {\rm d}\Omega + \int_{\Gamma_{\rm N}} v\ h \ {\rm d}\Gamma_{\rm N}. -``` -The problem is solved numerically by approximating the spaces $U_g$ and $V_0$ by their discrete counterparts associated with a FE mesh of the computational domain $\Omega$. As we have anticipated, we consider standard conforming Lagrangian FE spaces for this purpose. - -The implementation of this numerical scheme in GalerkinToolkit is done in a user-friendly way thanks to the abstractions provided by the library. As it will be seen below, all the mathematical objects involved in the definition of the discrete weak problem have a correspondent representation in the code. - - ## Setup - - The step number 0 in order to solve the problem is to load the GalerkinToolkit library in the code. If you have configured your Julia environment properly, it is simply done with the line: - -````@example poisson_tutorial -import GalerkinToolkit as GT -```` - ---- - -*This page was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).* - From fbb86e4af63852f998a5dc0282fa1404a3331699 Mon Sep 17 00:00:00 2001 From: Cmurilochem Date: Wed, 25 Sep 2024 11:56:46 +0200 Subject: [PATCH 06/14] Removed untracted Manifest from repo --- docs/Manifest.toml | 371 +++++++++++++++++++++++++++------------------ 1 file changed, 220 insertions(+), 151 deletions(-) diff --git a/docs/Manifest.toml b/docs/Manifest.toml index 1ab8ac2d..83e8bf43 100644 --- a/docs/Manifest.toml +++ b/docs/Manifest.toml @@ -1,8 +1,8 @@ # This file is machine-generated - editing it directly is not advised -julia_version = "1.10.0" +julia_version = "1.10.5" manifest_format = "2.0" -project_hash = "06b9521c1b5466285e95a69a2724b3212ddd7990" +project_hash = "317e1433522a009fbd6e7a758dc88bf0bc3514f3" [[deps.ANSIColoredPrinters]] git-tree-sha1 = "574baf8110975760d391c710b6341da1afa48d8c" @@ -10,20 +10,48 @@ uuid = "a4c015fc-c6ff-483c-b24f-f7ea428134e9" version = "0.0.1" [[deps.AbstractTrees]] -git-tree-sha1 = "faa260e4cb5aba097a73fab382dd4b5819d8ec8c" +git-tree-sha1 = "2d9c9a55f9c93e8887ad391fbae72f8ef55e1177" uuid = "1520ce14-60c1-5f80-bbc7-55ef81b5835c" -version = "0.4.4" +version = "0.4.5" [[deps.ArgTools]] uuid = "0dad84c5-d112-42e6-8d28-ef12dabb789f" version = "1.1.1" +[[deps.ArrayLayouts]] +deps = ["FillArrays", "LinearAlgebra"] +git-tree-sha1 = "0dd7edaff278e346eb0ca07a7e75c9438408a3ce" +uuid = "4c555306-a7a7-4459-81d9-ec55ddd5c99a" +version = "1.10.3" +weakdeps = ["SparseArrays"] + + [deps.ArrayLayouts.extensions] + ArrayLayoutsSparseArraysExt = "SparseArrays" + [[deps.Artifacts]] uuid = "56f22d72-fd6d-98f1-02f0-08ddc0907c33" +[[deps.AutoHashEquals]] +deps = ["Pkg"] +git-tree-sha1 = "daaeb6f7f77b88c072a83a2451801818acb5c63b" +uuid = "15f4f7f2-30c1-5605-9d31-71845cf9641f" +version = "2.1.0" + [[deps.Base64]] uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f" +[[deps.BlockArrays]] +deps = ["ArrayLayouts", "FillArrays", "LinearAlgebra"] +git-tree-sha1 = "d434647f798823bcae510aee0bc0401927f64391" +uuid = "8e7c35d0-a365-5155-bbbb-fb81a777f24e" +version = "1.1.1" + + [deps.BlockArrays.extensions] + BlockArraysBandedMatricesExt = "BandedMatrices" + + [deps.BlockArrays.weakdeps] + BandedMatrices = "aae01518-5342-5314-be14-df237901396f" + [[deps.Bzip2_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] git-tree-sha1 = "9e2a6b69137e6969bab0152632dcb3bc108c8bdd" @@ -31,27 +59,27 @@ uuid = "6e34b625-4abd-537c-b88f-471c36dfa7a0" version = "1.0.8+1" [[deps.CEnum]] -git-tree-sha1 = "eb4cb44a499229b3b8426dcfb5dd85333951ff90" +git-tree-sha1 = "389ad5c84de1ae7cf0e28e381131c98ea87d54fc" uuid = "fa961155-64e5-5f13-b03f-caf6b980ea82" -version = "0.4.2" +version = "0.5.0" [[deps.Cairo_jll]] -deps = ["Artifacts", "Bzip2_jll", "CompilerSupportLibraries_jll", "Fontconfig_jll", "FreeType2_jll", "Glib_jll", "JLLWrappers", "LZO_jll", "Libdl", "Pixman_jll", "Pkg", "Xorg_libXext_jll", "Xorg_libXrender_jll", "Zlib_jll", "libpng_jll"] -git-tree-sha1 = "4b859a208b2397a7a623a03449e4636bdb17bcf2" +deps = ["Artifacts", "Bzip2_jll", "CompilerSupportLibraries_jll", "Fontconfig_jll", "FreeType2_jll", "Glib_jll", "JLLWrappers", "LZO_jll", "Libdl", "Pixman_jll", "Xorg_libXext_jll", "Xorg_libXrender_jll", "Zlib_jll", "libpng_jll"] +git-tree-sha1 = "a2f1c8c668c8e3cb4cca4e57a8efdb09067bb3fd" uuid = "83423d85-b0ee-5818-9007-b63ccbeb887a" -version = "1.16.1+1" +version = "1.18.0+2" [[deps.CircularArrays]] deps = ["OffsetArrays"] -git-tree-sha1 = "3f7b8a37359ae592cfa7aca7f811da045deff222" +git-tree-sha1 = "e24a6f390e5563583bb4315c73035b5b3f3e7ab4" uuid = "7a955b69-7140-5f4e-a0ed-f168c5e2e749" -version = "1.3.3" +version = "1.4.0" [[deps.CodecZlib]] deps = ["TranscodingStreams", "Zlib_jll"] -git-tree-sha1 = "cd67fc487743b2f0fd4380d4cbd3a24660d0eec8" +git-tree-sha1 = "bce6804e5e6044c6daab27bb533d1295e4a2e759" uuid = "944b1d66-785c-5afd-91f1-9de20f533193" -version = "0.7.3" +version = "0.7.6" [[deps.Combinatorics]] git-tree-sha1 = "08c8b6831dc00bfea825826be0bc8336fc369860" @@ -59,15 +87,31 @@ uuid = "861a8166-3701-5b0c-9a16-15d98fcdc6aa" version = "1.0.2" [[deps.CommonSubexpressions]] -deps = ["MacroTools", "Test"] -git-tree-sha1 = "7b8a93dba8af7e3b42fecabf646260105ac373f7" +deps = ["MacroTools"] +git-tree-sha1 = "cda2cfaebb4be89c9084adaca7dd7333369715c5" uuid = "bbf7d656-a473-5ed7-a52c-81e309532950" -version = "0.3.0" +version = "0.3.1" + +[[deps.Compat]] +deps = ["TOML", "UUIDs"] +git-tree-sha1 = "8ae8d32e09f0dcf42a36b90d4e17f5dd2e4c4215" +uuid = "34da2185-b29b-5c13-b0c7-acf172513d20" +version = "4.16.0" +weakdeps = ["Dates", "LinearAlgebra"] + + [deps.Compat.extensions] + CompatLinearAlgebraExt = "LinearAlgebra" [[deps.CompilerSupportLibraries_jll]] deps = ["Artifacts", "Libdl"] uuid = "e66e0078-7015-5450-92f7-15fbd957f2ae" -version = "1.0.5+1" +version = "1.1.1+0" + +[[deps.DataStructures]] +deps = ["Compat", "InteractiveUtils", "OrderedCollections"] +git-tree-sha1 = "1d0a14036acb104d9e89698bd408f63ab58cdc82" +uuid = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8" +version = "0.18.20" [[deps.Dates]] deps = ["Printf"] @@ -110,10 +154,10 @@ uuid = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae" version = "0.9.3" [[deps.Documenter]] -deps = ["ANSIColoredPrinters", "AbstractTrees", "Base64", "Dates", "DocStringExtensions", "Downloads", "Git", "IOCapture", "InteractiveUtils", "JSON", "LibGit2", "Logging", "Markdown", "MarkdownAST", "Pkg", "PrecompileTools", "REPL", "RegistryInstances", "SHA", "Test", "Unicode"] -git-tree-sha1 = "2613dbec8f4748273bbe30ba71fd5cb369966bac" +deps = ["ANSIColoredPrinters", "AbstractTrees", "Base64", "CodecZlib", "Dates", "DocStringExtensions", "Downloads", "Git", "IOCapture", "InteractiveUtils", "JSON", "LibGit2", "Logging", "Markdown", "MarkdownAST", "Pkg", "PrecompileTools", "REPL", "RegistryInstances", "SHA", "TOML", "Test", "Unicode"] +git-tree-sha1 = "5a1ee886566f2fa9318df1273d8b778b9d42712d" uuid = "e30172f5-a6a5-5a46-863b-614d45cd2de4" -version = "1.2.1" +version = "1.7.0" [[deps.Downloads]] deps = ["ArgTools", "FileWatching", "LibCURL", "NetworkOptions"] @@ -122,9 +166,14 @@ version = "1.6.0" [[deps.Expat_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "4558ab818dcceaab612d1bb8c19cee87eda2b83c" +git-tree-sha1 = "1c6317308b9dc757616f0b5cb379db10494443a7" uuid = "2e619515-83b5-522b-bb60-26c02a35a201" -version = "2.5.0+0" +version = "2.6.2+0" + +[[deps.ExprTools]] +git-tree-sha1 = "27415f162e6028e81c72b82ef756bf321213b6ec" +uuid = "e2ba6199-217a-4e67-a87a-7c52f15ade04" +version = "0.1.10" [[deps.FLTK_jll]] deps = ["Artifacts", "Fontconfig_jll", "FreeType2_jll", "JLLWrappers", "JpegTurbo_jll", "Libdl", "Libglvnd_jll", "Pkg", "Xorg_libX11_jll", "Xorg_libXext_jll", "Xorg_libXfixes_jll", "Xorg_libXft_jll", "Xorg_libXinerama_jll", "Xorg_libXrender_jll", "Zlib_jll", "libpng_jll"] @@ -142,10 +191,10 @@ version = "1.0.2" uuid = "7b1f6079-737a-58dc-b8bc-7a2ca5c1b5ee" [[deps.FillArrays]] -deps = ["LinearAlgebra", "Random"] -git-tree-sha1 = "5b93957f6dcd33fc343044af3d48c215be2562f1" +deps = ["LinearAlgebra"] +git-tree-sha1 = "6a70198746448456524cb442b8af316927ff3e1a" uuid = "1a297f60-69ca-5386-bcde-b61e274b549b" -version = "1.9.3" +version = "1.13.0" [deps.FillArrays.extensions] FillArraysPDMatsExt = "PDMats" @@ -158,10 +207,10 @@ version = "1.9.3" Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2" [[deps.Fontconfig_jll]] -deps = ["Artifacts", "Bzip2_jll", "Expat_jll", "FreeType2_jll", "JLLWrappers", "Libdl", "Libuuid_jll", "Pkg", "Zlib_jll"] -git-tree-sha1 = "21efd19106a55620a188615da6d3d06cd7f6ee03" +deps = ["Artifacts", "Bzip2_jll", "Expat_jll", "FreeType2_jll", "JLLWrappers", "Libdl", "Libuuid_jll", "Zlib_jll"] +git-tree-sha1 = "db16beca600632c95fc8aca29890d83788dd8b23" uuid = "a3f928ae-7b40-5064-980b-68af3947d34b" -version = "2.13.93+0" +version = "2.13.96+0" [[deps.ForwardDiff]] deps = ["CommonSubexpressions", "DiffResults", "DiffRules", "LinearAlgebra", "LogExpFunctions", "NaNMath", "Preferences", "Printf", "Random", "SpecialFunctions"] @@ -175,9 +224,9 @@ weakdeps = ["StaticArrays"] [[deps.FreeType2_jll]] deps = ["Artifacts", "Bzip2_jll", "JLLWrappers", "Libdl", "Zlib_jll"] -git-tree-sha1 = "d8db6a5a2fe1381c1ea4ef2cab7c69c2de7f9ea0" +git-tree-sha1 = "5c1d8ae0efc6c2e7b1fc502cbe25def8f661b7bc" uuid = "d7e528f0-a631-5988-bf34-fe36492bcfd7" -version = "2.13.1+0" +version = "2.13.2+0" [[deps.GLU_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Libglvnd_jll", "Pkg"] @@ -191,7 +240,7 @@ uuid = "781609d7-10c4-51f6-84f2-b8444358ff6d" version = "6.2.1+6" [[deps.GalerkinToolkit]] -deps = ["Combinatorics", "FastGaussQuadrature", "ForwardDiff", "Gmsh", "IterativeSolvers", "LinearAlgebra", "MPI", "Metis", "PartitionedArrays", "SparseArrays", "StaticArrays", "WriteVTK"] +deps = ["BlockArrays", "Combinatorics", "FastGaussQuadrature", "FillArrays", "ForwardDiff", "Gmsh", "IterativeSolvers", "LinearAlgebra", "MPI", "Metatheory", "Metis", "PartitionedArrays", "SparseArrays", "StaticArrays", "WriteVTK"] path = ".." uuid = "5e3ba9c4-dd81-444d-b69a-0e7bd7bf60a4" version = "0.1.0" @@ -204,45 +253,45 @@ version = "0.21.0+0" [[deps.Git]] deps = ["Git_jll"] -git-tree-sha1 = "51764e6c2e84c37055e846c516e9015b4a291c7d" +git-tree-sha1 = "04eff47b1354d702c3a85e8ab23d539bb7d5957e" uuid = "d7ba0133-e1db-5d97-8f8c-041e4b3a1eb2" -version = "1.3.0" +version = "1.3.1" [[deps.Git_jll]] deps = ["Artifacts", "Expat_jll", "JLLWrappers", "LibCURL_jll", "Libdl", "Libiconv_jll", "OpenSSL_jll", "PCRE2_jll", "Zlib_jll"] -git-tree-sha1 = "d8be4aab0f4e043cc40984e9097417307cce4c03" +git-tree-sha1 = "ea372033d09e4552a04fd38361cd019f9003f4f4" uuid = "f8c6e375-362e-5223-8a59-34ff63f689eb" -version = "2.36.1+2" +version = "2.46.2+0" [[deps.Glib_jll]] deps = ["Artifacts", "Gettext_jll", "JLLWrappers", "Libdl", "Libffi_jll", "Libiconv_jll", "Libmount_jll", "PCRE2_jll", "Zlib_jll"] -git-tree-sha1 = "e94c92c7bf4819685eb80186d51c43e71d4afa17" +git-tree-sha1 = "7c82e6a6cd34e9d935e9aa4051b66c6ff3af59ba" uuid = "7746bdde-850d-59dc-9ae8-88ece973131d" -version = "2.76.5+0" +version = "2.80.2+0" [[deps.Gmsh]] deps = ["gmsh_jll"] -git-tree-sha1 = "00228b1b4697f060d39ef883e7b4929d0a537453" +git-tree-sha1 = "6d815101e62722f4e323514c9fc704007d4da2e3" uuid = "705231aa-382f-11e9-3f0c-b7cb4346fdeb" -version = "0.3.0" +version = "0.3.1" [[deps.HDF5_jll]] -deps = ["Artifacts", "JLLWrappers", "LibCURL_jll", "Libdl", "OpenSSL_jll", "Pkg", "Zlib_jll"] -git-tree-sha1 = "4cc2bb72df6ff40b055295fdef6d92955f9dede8" +deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "LazyArtifacts", "LibCURL_jll", "Libdl", "MPICH_jll", "MPIPreferences", "MPItrampoline_jll", "MicrosoftMPI_jll", "OpenMPI_jll", "OpenSSL_jll", "TOML", "Zlib_jll", "libaec_jll"] +git-tree-sha1 = "82a471768b513dc39e471540fdadc84ff80ff997" uuid = "0234f1f7-429e-5d53-9886-15a909be8d59" -version = "1.12.2+2" +version = "1.14.3+3" [[deps.Hwloc_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "ca0f6bf568b4bfc807e7537f081c81e35ceca114" +git-tree-sha1 = "5e19e1e4fa3e71b774ce746274364aef0234634e" uuid = "e33a78d0-f292-5ffc-b300-72abe9b543c8" -version = "2.10.0+0" +version = "2.11.1+0" [[deps.IOCapture]] deps = ["Logging", "Random"] -git-tree-sha1 = "8b72179abc660bfab5e28472e019392b97d0985c" +git-tree-sha1 = "b6d6bfdd7ce25b0f9b2f6b3dd56b2673a66c8770" uuid = "b5f81e59-6552-4d32-b1f0-c071b021bf89" -version = "0.2.4" +version = "0.2.5" [[deps.InteractiveUtils]] deps = ["Markdown"] @@ -255,15 +304,15 @@ version = "0.2.2" [[deps.IterativeSolvers]] deps = ["LinearAlgebra", "Printf", "Random", "RecipesBase", "SparseArrays"] -git-tree-sha1 = "b435d190ef8369cf4d79cc9dd5fba88ba0165307" +git-tree-sha1 = "59545b0a2b27208b0650df0a46b8e3019f85055b" uuid = "42fd0dbc-a981-5370-80f2-aaf504508153" -version = "0.9.3" +version = "0.9.4" [[deps.JLLWrappers]] deps = ["Artifacts", "Preferences"] -git-tree-sha1 = "7e5d6779a1e09a36db2a7b6cff50942a0a7d0fca" +git-tree-sha1 = "f389674c99bfcde17dc57454011aa44d5a260a40" uuid = "692b3bcd-3c85-4b1f-b108-f13ce0eb3210" -version = "1.5.0" +version = "1.6.0" [[deps.JSON]] deps = ["Dates", "Mmap", "Parsers", "Unicode"] @@ -273,21 +322,21 @@ version = "0.21.4" [[deps.JpegTurbo_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "60b1194df0a3298f460063de985eae7b01bc011a" +git-tree-sha1 = "c84a835e1a09b289ffcd2271bf2a337bbdda6637" uuid = "aacddb02-875f-59d6-b918-886e6ef4fbf8" -version = "3.0.1+0" +version = "3.0.3+0" [[deps.LLVMOpenMP_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "d986ce2d884d49126836ea94ed5bfb0f12679713" +git-tree-sha1 = "78211fb6cbc872f77cad3fc0b6cf647d923f4929" uuid = "1d63c593-3942-5779-bab2-d838dc0a180e" -version = "15.0.7+0" +version = "18.1.7+0" [[deps.LZO_jll]] -deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] -git-tree-sha1 = "e5b909bcf985c5e2605737d2ce278ed791b89be6" +deps = ["Artifacts", "JLLWrappers", "Libdl"] +git-tree-sha1 = "70c5da094887fd2cae843b8db33920bac4b6f07d" uuid = "dd4b983a-f0e5-5f8d-a1b7-129d4a5fb1ac" -version = "2.10.1+0" +version = "2.10.2+0" [[deps.LazilyInitializedFields]] git-tree-sha1 = "8f7f3cabab0fd1800699663533b6d5cb3fc0e612" @@ -332,10 +381,10 @@ uuid = "e9f186c6-92d2-5b65-8a66-fee21dc1b490" version = "3.2.2+1" [[deps.Libgcrypt_jll]] -deps = ["Artifacts", "JLLWrappers", "Libdl", "Libgpg_error_jll", "Pkg"] -git-tree-sha1 = "64613c82a59c120435c067c2b809fc61cf5166ae" +deps = ["Artifacts", "JLLWrappers", "Libdl", "Libgpg_error_jll"] +git-tree-sha1 = "9fd170c4bbfd8b935fdc5f8b7aa33532c991a673" uuid = "d4300ac3-e22c-5743-9152-c294e39db1e4" -version = "1.8.7+0" +version = "1.8.11+0" [[deps.Libglvnd_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libX11_jll", "Xorg_libXext_jll"] @@ -344,10 +393,10 @@ uuid = "7e76a0d4-f3c7-5321-8279-8d96eeed0f29" version = "1.6.0+0" [[deps.Libgpg_error_jll]] -deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] -git-tree-sha1 = "c333716e46366857753e273ce6a69ee0945a6db9" +deps = ["Artifacts", "JLLWrappers", "Libdl"] +git-tree-sha1 = "fbb1f2bef882392312feb1ede3615ddc1e9b99ed" uuid = "7add5ba3-2f88-524e-9cd5-f83b8a55f7b8" -version = "1.42.0+0" +version = "1.49.0+0" [[deps.Libiconv_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] @@ -356,16 +405,16 @@ uuid = "94ce4f54-9a6c-5748-9c1c-f9c7231a4531" version = "1.17.0+0" [[deps.Libmount_jll]] -deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] -git-tree-sha1 = "9c30530bf0effd46e15e0fdcf2b8636e78cbbd73" +deps = ["Artifacts", "JLLWrappers", "Libdl"] +git-tree-sha1 = "0c4f9c4f1a50d8f35048fa0532dabbadf702f81e" uuid = "4b2f31a3-9ecc-558c-b454-b3730dcb73e9" -version = "2.35.0+0" +version = "2.40.1+0" [[deps.Libuuid_jll]] -deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] -git-tree-sha1 = "7f3efec06033682db852f8b3bc3c1d2b0a0ab066" +deps = ["Artifacts", "JLLWrappers", "Libdl"] +git-tree-sha1 = "5ee6203157c120d79034c748a2acba45b82b8807" uuid = "38a345b3-de98-5d2b-a5d3-14cd9215e700" -version = "2.36.0+0" +version = "2.40.1+0" [[deps.LightXML]] deps = ["Libdl", "XML2_jll"] @@ -383,11 +432,17 @@ git-tree-sha1 = "71e8ee0f9fe0e86a8f8c7f28361e5118eab2f93f" uuid = "18c40d15-f7cd-5a6d-bc92-87468d86c5db" version = "5.0.0+0" +[[deps.Literate]] +deps = ["Base64", "IOCapture", "JSON", "REPL"] +git-tree-sha1 = "b9b38448af801760a608b7a7f895f7dcf166f4a5" +uuid = "98b081ad-f1c9-55d3-8b20-4c87d4299306" +version = "2.19.1" + [[deps.LogExpFunctions]] deps = ["DocStringExtensions", "IrrationalConstants", "LinearAlgebra"] -git-tree-sha1 = "7d6dd4e9212aebaeed356de34ccf262a3cd415aa" +git-tree-sha1 = "a2d09619db4e765091ee5c6ffe8872849de0feea" uuid = "2ab3a3ac-af41-5b50-aa03-7779005ae688" -version = "0.3.26" +version = "0.3.28" [deps.LogExpFunctions.extensions] LogExpFunctionsChainRulesCoreExt = "ChainRulesCore" @@ -416,9 +471,9 @@ version = "5.6.0+0" [[deps.MPI]] deps = ["Distributed", "DocStringExtensions", "Libdl", "MPICH_jll", "MPIPreferences", "MPItrampoline_jll", "MicrosoftMPI_jll", "OpenMPI_jll", "PkgVersion", "PrecompileTools", "Requires", "Serialization", "Sockets"] -git-tree-sha1 = "b4d8707e42b693720b54f0b3434abee6dd4d947a" +git-tree-sha1 = "892676019c58f34e38743bc989b0eca5bce5edc5" uuid = "da04e1cc-30fd-572f-bb4f-1f8673147195" -version = "0.20.16" +version = "0.20.22" [deps.MPI.extensions] AMDGPUExt = "AMDGPU" @@ -429,22 +484,22 @@ version = "0.20.16" CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba" [[deps.MPICH_jll]] -deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "MPIPreferences", "TOML"] -git-tree-sha1 = "2ee75365ca243c1a39d467e35ffd3d4d32eef11e" +deps = ["Artifacts", "CompilerSupportLibraries_jll", "Hwloc_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "MPIPreferences", "TOML"] +git-tree-sha1 = "19d4bd098928a3263693991500d05d74dbdc2004" uuid = "7cb0a576-ebde-5e09-9194-50597f1243b4" -version = "4.1.2+1" +version = "4.2.2+0" [[deps.MPIPreferences]] deps = ["Libdl", "Preferences"] -git-tree-sha1 = "8f6af051b9e8ec597fa09d8885ed79fd582f33c9" +git-tree-sha1 = "c105fe467859e7f6e9a852cb15cb4301126fac07" uuid = "3da0fdf6-3ccc-4f1b-acd9-58baa6c99267" -version = "0.1.10" +version = "0.1.11" [[deps.MPItrampoline_jll]] deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "MPIPreferences", "TOML"] -git-tree-sha1 = "8eeb3c73bbc0ca203d0dc8dad4008350bbe5797b" +git-tree-sha1 = "8c35d5420193841b2f367e658540e8d9e0601ed0" uuid = "f1f71cc9-e9ae-5b93-9b94-4fe0e1ad3748" -version = "5.3.1+1" +version = "5.4.0+0" [[deps.MacroTools]] deps = ["Markdown", "Random"] @@ -467,11 +522,17 @@ deps = ["Artifacts", "Libdl"] uuid = "c8ffd9c3-330d-5841-b78e-0817d7145fa1" version = "2.28.2+1" +[[deps.Metatheory]] +deps = ["AutoHashEquals", "DataStructures", "DocStringExtensions", "Reexport", "TermInterface", "TimerOutputs"] +git-tree-sha1 = "2cdcf1d7c4ae2d81cc015fae603df5c1b4b8f422" +uuid = "e9d8d322-4543-424a-9be4-0cc815abe26c" +version = "2.0.2" + [[deps.Metis]] deps = ["CEnum", "LinearAlgebra", "METIS_jll", "SparseArrays"] -git-tree-sha1 = "66a4f74edb3ac5f28c74de60f9acc2a541fbbe28" +git-tree-sha1 = "54aca4fd53d39dcd2c3f1bef367b6921e8178628" uuid = "2679e427-3c69-5b7f-982b-ece356f1e94b" -version = "1.4.0" +version = "1.5.0" [deps.Metis.extensions] MetisGraphs = "Graphs" @@ -485,9 +546,9 @@ version = "1.4.0" [[deps.MicrosoftMPI_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] -git-tree-sha1 = "b01beb91d20b0d1312a9471a36017b5b339d26de" +git-tree-sha1 = "f12a29c4400ba812841c6ace3f4efbb6dbb3ba01" uuid = "9237b28f-5490-5468-be7b-bb81f5f5e6cf" -version = "10.1.4+1" +version = "10.1.4+2" [[deps.Mmap]] uuid = "a63ad114-7e13-5084-954f-fe012c677804" @@ -507,15 +568,15 @@ uuid = "ca575930-c2e3-43a9-ace4-1e988b2c1908" version = "1.2.0" [[deps.OCCT_jll]] -deps = ["Artifacts", "FreeType2_jll", "JLLWrappers", "Libdl", "Libglvnd_jll", "Pkg", "Xorg_libX11_jll", "Xorg_libXext_jll", "Xorg_libXfixes_jll", "Xorg_libXft_jll", "Xorg_libXinerama_jll", "Xorg_libXrender_jll"] -git-tree-sha1 = "acc8099ae8ed10226dc8424fb256ec9fe367a1f0" +deps = ["Artifacts", "FreeType2_jll", "JLLWrappers", "Libdl", "Libglvnd_jll", "Xorg_libX11_jll", "Xorg_libXext_jll", "Xorg_libXfixes_jll", "Xorg_libXft_jll", "Xorg_libXinerama_jll", "Xorg_libXrender_jll"] +git-tree-sha1 = "bef34b68c20cc34475c5cb464ab48555e74f4c61" uuid = "baad4e97-8daa-5946-aac2-2edac59d34e1" -version = "7.6.2+2" +version = "7.7.2+0" [[deps.OffsetArrays]] -git-tree-sha1 = "6a731f2b5c03157418a20c12195eb4b74c8f8621" +git-tree-sha1 = "1a27764e945a152f7ca7efa04de513d473e9542e" uuid = "6fe1bfb0-de20-5000-8ca7-80f57d26f881" -version = "1.13.0" +version = "1.14.1" [deps.OffsetArrays.extensions] OffsetArraysAdaptExt = "Adapt" @@ -526,7 +587,7 @@ version = "1.13.0" [[deps.OpenBLAS_jll]] deps = ["Artifacts", "CompilerSupportLibraries_jll", "Libdl"] uuid = "4536629a-c528-5b80-bd46-f80d51c5b363" -version = "0.3.23+2" +version = "0.3.23+4" [[deps.OpenLibm_jll]] deps = ["Artifacts", "Libdl"] @@ -534,16 +595,16 @@ uuid = "05823500-19ac-5b8b-9628-191a04bc5112" version = "0.8.1+2" [[deps.OpenMPI_jll]] -deps = ["Artifacts", "CompilerSupportLibraries_jll", "Hwloc_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "MPIPreferences", "PMIx_jll", "TOML", "Zlib_jll", "libevent_jll", "prrte_jll"] -git-tree-sha1 = "1d1421618bab0e820bdc7ae1a2b46ce576981273" +deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "MPIPreferences", "TOML"] +git-tree-sha1 = "e25c1778a98e34219a00455d6e4384e017ea9762" uuid = "fe0851c0-eecd-5654-98d4-656369965a5c" -version = "5.0.1+0" +version = "4.1.6+0" [[deps.OpenSSL_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "a12e56c72edee3ce6b96667745e6cbbe5498f200" +git-tree-sha1 = "7493f61f55a6cce7325f197443aa80d32554ba10" uuid = "458c3c95-2e84-50aa-8efc-19380b2a3a95" -version = "1.1.23+0" +version = "3.0.15+1" [[deps.OpenSpecFun_jll]] deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl", "Pkg"] @@ -551,17 +612,16 @@ git-tree-sha1 = "13652491f6856acfd2db29360e1bbcd4565d04f1" uuid = "efe28fd5-8261-553b-a9e1-b2916fc3738e" version = "0.5.5+0" +[[deps.OrderedCollections]] +git-tree-sha1 = "dfdf5519f235516220579f949664f1bf44e741c5" +uuid = "bac558e1-5e72-5ebc-8fee-abe8a469f55d" +version = "1.6.3" + [[deps.PCRE2_jll]] deps = ["Artifacts", "Libdl"] uuid = "efcefdf7-47ab-520b-bdef-62a2eaa19f15" version = "10.42.0+1" -[[deps.PMIx_jll]] -deps = ["Artifacts", "Hwloc_jll", "JLLWrappers", "Libdl", "Zlib_jll", "libevent_jll"] -git-tree-sha1 = "8b3b19351fa24791f94d7ae85faf845ca1362541" -uuid = "32165bc3-0280-59bc-8c0b-c33b6203efab" -version = "4.2.7+0" - [[deps.Parsers]] deps = ["Dates", "PrecompileTools", "UUIDs"] git-tree-sha1 = "8489905bcdbcfac64d1daa51ca07c0d8f0283821" @@ -569,16 +629,16 @@ uuid = "69de0a69-1ddd-5017-9359-2bf0b02dc9f0" version = "2.8.1" [[deps.PartitionedArrays]] -deps = ["CircularArrays", "Distances", "FillArrays", "IterativeSolvers", "LinearAlgebra", "MPI", "Printf", "Random", "SparseArrays", "SparseMatricesCSR"] -git-tree-sha1 = "ef8689c008317753472f0dc4a8160265619b23c4" +deps = ["BlockArrays", "CircularArrays", "Distances", "FillArrays", "IterativeSolvers", "LinearAlgebra", "MPI", "Printf", "Random", "SparseArrays", "SparseMatricesCSR", "StaticArrays"] +git-tree-sha1 = "912e48995e001f7b24d425fb1eebbb97e8c3cb09" uuid = "5a9dfac6-5c52-46f7-8278-5e2210713be9" -version = "0.4.0" +version = "0.5.4" [[deps.Pixman_jll]] deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "LLVMOpenMP_jll", "Libdl"] -git-tree-sha1 = "64779bc4c9784fee475689a1752ef4d5747c5e87" +git-tree-sha1 = "35621f10a7531bc8fa58f74610b1bfb70a3cfc6b" uuid = "30392449-352a-5448-841d-b1acce4e97dc" -version = "0.42.2+0" +version = "0.43.4+0" [[deps.Pkg]] deps = ["Artifacts", "Dates", "Downloads", "FileWatching", "LibGit2", "Libdl", "Logging", "Markdown", "Printf", "REPL", "Random", "SHA", "Serialization", "TOML", "Tar", "UUIDs", "p7zip_jll"] @@ -593,15 +653,15 @@ version = "0.3.3" [[deps.PrecompileTools]] deps = ["Preferences"] -git-tree-sha1 = "03b4c25b43cb84cee5c90aa9b5ea0a78fd848d2f" +git-tree-sha1 = "5aa36f7049a63a1528fe8f7c3f2113413ffd4e1f" uuid = "aea7be01-6a6a-4083-8856-8a6e6704d82a" -version = "1.2.0" +version = "1.2.1" [[deps.Preferences]] deps = ["TOML"] -git-tree-sha1 = "00805cd429dcb4870060ff49ef443486c262e38e" +git-tree-sha1 = "9306f6085165d270f7e3db02af26a400d580f5c6" uuid = "21216c6a-2e73-6563-6e65-726566657250" -version = "1.4.1" +version = "1.4.3" [[deps.Printf]] deps = ["Unicode"] @@ -621,6 +681,11 @@ git-tree-sha1 = "5c3d09cc4f31f5fc6af001c250bf1278733100ff" uuid = "3cdcf5f2-1ef4-517c-9805-6587b60abb01" version = "1.3.4" +[[deps.Reexport]] +git-tree-sha1 = "45e428421666073eab6f2da5c9d310d99bb12f9b" +uuid = "189a3867-3050-52da-a836-e630ba90ab69" +version = "1.2.2" + [[deps.RegistryInstances]] deps = ["LazilyInitializedFields", "Pkg", "TOML", "Tar"] git-tree-sha1 = "ffd19052caf598b8653b99404058fce14828be51" @@ -662,9 +727,9 @@ version = "0.6.7" [[deps.SpecialFunctions]] deps = ["IrrationalConstants", "LogExpFunctions", "OpenLibm_jll", "OpenSpecFun_jll"] -git-tree-sha1 = "e2cfc4012a19088254b3950b85c3c1d8882d864d" +git-tree-sha1 = "2f5d4697f21388cbe1ff299430dd169ef97d7e14" uuid = "276daf66-3868-5448-9aa4-cd146d93841b" -version = "2.3.1" +version = "2.4.0" [deps.SpecialFunctions.extensions] SpecialFunctionsChainRulesCoreExt = "ChainRulesCore" @@ -674,9 +739,9 @@ version = "2.3.1" [[deps.StaticArrays]] deps = ["LinearAlgebra", "PrecompileTools", "Random", "StaticArraysCore"] -git-tree-sha1 = "f68dd04d131d9a8a8eb836173ee8f105c360b0c5" +git-tree-sha1 = "eeafab08ae20c62c44c8399ccb9354a04b80db50" uuid = "90137ffa-7385-5640-81b9-e52037218182" -version = "1.9.1" +version = "1.9.7" [deps.StaticArrays.extensions] StaticArraysChainRulesCoreExt = "ChainRulesCore" @@ -687,9 +752,9 @@ version = "1.9.1" Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2" [[deps.StaticArraysCore]] -git-tree-sha1 = "36b3d696ce6366023a0ea192b4cd442268995a0d" +git-tree-sha1 = "192954ef1208c7019899fbf8049e717f92959682" uuid = "1e83bf80-4336-4d27-bf5d-d5a4f845583c" -version = "1.4.2" +version = "1.4.3" [[deps.Statistics]] deps = ["LinearAlgebra", "SparseArrays"] @@ -721,15 +786,25 @@ deps = ["ArgTools", "SHA"] uuid = "a4e569a6-e804-4fa4-b0f3-eef7a1d5b13e" version = "1.10.0" +[[deps.TermInterface]] +git-tree-sha1 = "3939db0ce564b5fda6e9f9edcb4dabe0a1a0cc5f" +uuid = "8ea1fca8-c5ef-4a55-8b96-4e9afe9c9a3c" +version = "0.3.3" + [[deps.Test]] deps = ["InteractiveUtils", "Logging", "Random", "Serialization"] uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40" +[[deps.TimerOutputs]] +deps = ["ExprTools", "Printf"] +git-tree-sha1 = "5a13ae8a41237cff5ecf34f73eb1b8f42fff6531" +uuid = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f" +version = "0.5.24" + [[deps.TranscodingStreams]] -deps = ["Random", "Test"] -git-tree-sha1 = "9a6ae7ed916312b41236fcef7e0af564ef934769" +git-tree-sha1 = "e84b3a11b9bece70d14cce63406bbc79ed3464d2" uuid = "3bb67fe8-82b1-5028-8e26-92a6c54297fa" -version = "0.9.13" +version = "0.11.2" [[deps.UUIDs]] deps = ["Random", "SHA"] @@ -745,21 +820,21 @@ version = "1.0.1" [[deps.WriteVTK]] deps = ["Base64", "CodecZlib", "FillArrays", "LightXML", "TranscodingStreams", "VTKBase"] -git-tree-sha1 = "41f0dc2a8f6fd860c266b91fd5cdf4fead65ae69" +git-tree-sha1 = "93fd3a6bbeb33c18929b7d8b4f4dbd2024395f70" uuid = "64499a7a-5c06-52f2-abe2-ccb03c286192" -version = "1.18.1" +version = "1.20.0" [[deps.XML2_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Libiconv_jll", "Zlib_jll"] -git-tree-sha1 = "801cbe47eae69adc50f36c3caec4758d2650741b" +git-tree-sha1 = "1165b0443d0eca63ac1e32b8c0eb69ed2f4f8127" uuid = "02c8fc9c-b97f-50b9-bbe4-9be30ff0a78a" -version = "2.12.2+0" +version = "2.13.3+0" [[deps.XSLT_jll]] -deps = ["Artifacts", "JLLWrappers", "Libdl", "Libgcrypt_jll", "Libgpg_error_jll", "Libiconv_jll", "Pkg", "XML2_jll", "Zlib_jll"] -git-tree-sha1 = "91844873c4085240b95e795f692c4cec4d805f8a" +deps = ["Artifacts", "JLLWrappers", "Libdl", "Libgcrypt_jll", "Libgpg_error_jll", "Libiconv_jll", "XML2_jll", "Zlib_jll"] +git-tree-sha1 = "a54ee957f4c86b526460a720dbc882fa5edcbefc" uuid = "aed1982a-8fda-507f-9586-7b0439959a61" -version = "1.1.34+0" +version = "1.1.41+0" [[deps.Xorg_libX11_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libxcb_jll", "Xorg_xtrans_jll"] @@ -780,10 +855,10 @@ uuid = "a3789734-cfe1-5b06-b2d0-1dd0d9d62d05" version = "1.1.4+0" [[deps.Xorg_libXext_jll]] -deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libX11_jll"] -git-tree-sha1 = "b7c0aa8c376b31e4852b360222848637f481f8c3" +deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libX11_jll"] +git-tree-sha1 = "d2d1a5c49fae4ba39983f63de6afcbea47194e85" uuid = "1082639a-0dae-5f34-9b06-72781eeb8cb3" -version = "1.3.4+4" +version = "1.3.6+0" [[deps.Xorg_libXfixes_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libX11_jll"] @@ -804,10 +879,10 @@ uuid = "d1454406-59df-5ea1-beac-c340f2130bc3" version = "1.1.4+4" [[deps.Xorg_libXrender_jll]] -deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libX11_jll"] -git-tree-sha1 = "19560f30fd49f4d4efbe7002a1037f8c43d43b96" +deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libX11_jll"] +git-tree-sha1 = "47e45cd78224c53109495b3e324df0c37bb61fbe" uuid = "ea2f1a96-1ddc-540d-b46f-429655e07cfa" -version = "0.9.10+4" +version = "0.9.11+0" [[deps.Xorg_libpthread_stubs_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] @@ -817,9 +892,9 @@ version = "0.1.1+0" [[deps.Xorg_libxcb_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "XSLT_jll", "Xorg_libXau_jll", "Xorg_libXdmcp_jll", "Xorg_libpthread_stubs_jll"] -git-tree-sha1 = "b4bfde5d5b652e22b9c790ad00af08b6d042b97d" +git-tree-sha1 = "bcd466676fef0878338c61e655629fa7bbc69d8e" uuid = "c7cfdc94-dc32-55de-ac96-5a1b8d977c5b" -version = "1.15.0+0" +version = "1.17.0+0" [[deps.Xorg_xtrans_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] @@ -834,26 +909,26 @@ version = "1.2.13+1" [[deps.gmsh_jll]] deps = ["Artifacts", "Cairo_jll", "CompilerSupportLibraries_jll", "FLTK_jll", "FreeType2_jll", "GLU_jll", "GMP_jll", "HDF5_jll", "JLLWrappers", "JpegTurbo_jll", "LLVMOpenMP_jll", "Libdl", "Libglvnd_jll", "METIS_jll", "MMG_jll", "OCCT_jll", "Xorg_libX11_jll", "Xorg_libXext_jll", "Xorg_libXfixes_jll", "Xorg_libXft_jll", "Xorg_libXinerama_jll", "Xorg_libXrender_jll", "Zlib_jll", "libpng_jll"] -git-tree-sha1 = "d15409a4b9f1d14f1e1f9e910cd00f7d6695c261" +git-tree-sha1 = "1e7fe5c8dbe0e911931a18cdfbd2c7a1e01b68ef" uuid = "630162c2-fc9b-58b3-9910-8442a8a132e6" -version = "4.11.1+0" +version = "4.13.1+0" + +[[deps.libaec_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl"] +git-tree-sha1 = "46bf7be2917b59b761247be3f317ddf75e50e997" +uuid = "477f73a3-ac25-53e9-8cc3-50b2fa2566f0" +version = "1.1.2+0" [[deps.libblastrampoline_jll]] deps = ["Artifacts", "Libdl"] uuid = "8e850b90-86db-534c-a0d3-1478176c7d93" -version = "5.8.0+1" - -[[deps.libevent_jll]] -deps = ["Artifacts", "JLLWrappers", "Libdl", "OpenSSL_jll", "Pkg"] -git-tree-sha1 = "31bceb8a838f2e1e6d7e0311f2bea22e3a3fdae3" -uuid = "1080aeaf-3a6a-583e-a51c-c537b09f60ec" -version = "2.1.12+0" +version = "5.11.0+0" [[deps.libpng_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Zlib_jll"] -git-tree-sha1 = "93284c28274d9e75218a416c65ec49d0e0fcdf3d" +git-tree-sha1 = "d7015d2e18a5fd9a4f47de711837e980519781a4" uuid = "b53b4c65-9356-5827-b1ea-8c7a1a84506f" -version = "1.6.40+0" +version = "1.6.43+1" [[deps.nghttp2_jll]] deps = ["Artifacts", "Libdl"] @@ -864,9 +939,3 @@ version = "1.52.0+1" deps = ["Artifacts", "Libdl"] uuid = "3f19e933-33d8-53b3-aaab-bd5110c3b7a0" version = "17.4.0+2" - -[[deps.prrte_jll]] -deps = ["Artifacts", "Hwloc_jll", "JLLWrappers", "Libdl", "PMIx_jll", "libevent_jll"] -git-tree-sha1 = "5adb2d7a18a30280feb66cad6f1a1dfdca2dc7b0" -uuid = "eb928a42-fffd-568d-ab9c-3f5d54fc65b9" -version = "3.0.2+0" From 5450ed2f5273492a17dc03b836e19e46458b3341 Mon Sep 17 00:00:00 2001 From: Cmurilochem Date: Wed, 25 Sep 2024 13:26:18 +0200 Subject: [PATCH 07/14] Add vtu files to gitignore --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index 7bb7c458..2a59dd8c 100644 --- a/.gitignore +++ b/.gitignore @@ -4,6 +4,7 @@ *.swp *.swn *.swo +*.vtu /output /Manifest.toml /docs/build/ From 19c1ed27c776f33133d0d904750f38fc8d783bd5 Mon Sep 17 00:00:00 2001 From: Cmurilochem Date: Thu, 26 Sep 2024 17:21:33 +0200 Subject: [PATCH 08/14] Add notebooks folder --- assets/model.geo | 114 + assets/model.msh | 55594 ++++++++++++++++ .../poisson/fig_faces_on_circle.png | Bin .../src/assets => assets}/poisson/fig_uh.png | Bin .../poisson/fig_vertices_on_sides.png | Bin .../assets => assets}/poisson/model-r1-2.png | Bin .../t001_poisson-checkpoint.ipynb | 738 + notebooks/t001_poisson.ipynb | 781 + 8 files changed, 57227 insertions(+) create mode 100644 assets/model.geo create mode 100644 assets/model.msh rename {docs/src/assets => assets}/poisson/fig_faces_on_circle.png (100%) rename {docs/src/assets => assets}/poisson/fig_uh.png (100%) rename {docs/src/assets => assets}/poisson/fig_vertices_on_sides.png (100%) rename {docs/src/assets => assets}/poisson/model-r1-2.png (100%) create mode 100644 notebooks/.ipynb_checkpoints/t001_poisson-checkpoint.ipynb create mode 100644 notebooks/t001_poisson.ipynb diff --git a/assets/model.geo b/assets/model.geo new file mode 100644 index 00000000..1625d8fe --- /dev/null +++ b/assets/model.geo @@ -0,0 +1,114 @@ +//+ +Point(1) = {0, 0, 0, 1.0}; +//+ +Point(2) = {1.5, 0, 0, 1.0}; +//+ +Point(3) = {1.5, 1, 0, 1.0}; +//+ +Point(4) = {0, 1, 0, 1.0}; +//+ +Point(5) = {0.095, 0.2, 0, 1.0}; +//+ +Point(6) = {0.63, 0.2, 0, 1.0}; +//+ +Point(7) = {0.3625, 0.675, 0, 1.0}; +//+ +Point(8) = {0.58, 0.5, 0, 1.0}; +//+ +Point(9) = {0.94, 0.5, 0, 1.0}; +//+ +Point(10) = {0.94, 0.86, 0, 1.0}; +//+ +Point(11) = {0.58, 0.86, 0, 1.0}; +//+ +Point(12) = {1, 0.39, 0, 1.0}; +//+ +Point(13) = {1.19, 0.39, 0, 1.0}; +//+ +Point(14) = {1.38, 0.39, 0, 1.0}; +//+ +Point(15) = {1.19, 0.2, 0, 1.0}; +//+ +Point(16) = {1.19, 0.58, 0, 1.0}; +//+ +Line(1) = {1, 2}; +//+ +Line(2) = {2, 3}; +//+ +Line(3) = {3, 4}; +//+ +Line(4) = {4, 1}; +//+ +Line(5) = {5, 7}; +//+ +Line(6) = {7, 6}; +//+ +Line(7) = {6, 5}; +//+ +Line(8) = {8, 11}; +//+ +Line(9) = {11, 10}; +//+ +Line(10) = {10, 9}; +//+ +Line(11) = {9, 8}; +//+ +Circle(12) = {12, 13, 16}; +//+ +Circle(13) = {16, 13, 14}; +//+ +Circle(14) = {14, 13, 15}; +//+ +Circle(15) = {15, 13, 12}; +//+ +Curve Loop(1) = {3, 4, 1, 2}; +//+ +Curve Loop(2) = {5, 6, 7}; +//+ +Curve Loop(3) = {9, 10, 11, 8}; +//+ +Curve Loop(4) = {13, 14, 15, 12}; +//+ +Plane Surface(1) = {1,2,3,4}; +//+ +Extrude {0, 0, 0.15} { + Surface{1}; +} +//+ +Physical Volume("volume") = {1}; +//+ +Physical Surface("triangle") = {55, 59, 51}; +//+ +Physical Surface("square") = {75, 63, 67, 71}; +//+ +Physical Surface("circle") = {79, 91, 83, 87}; +//+ +Physical Surface("sides") = {43, 39, 35, 47}; +//+ +Physical Surface("top") = {92}; +//+ +Physical Surface("bottom") = {1}; +//+ +Physical Curve("triangle") = {49, 50, 54}; +//+ +Physical Curve("square") = {61, 62, 66, 70}; +//+ +Physical Curve("circle") = {77, 82, 78, 86}; +//+ +Physical Curve("sides") = {38, 34, 33, 42}; +//+ +Physical Curve("triangle_c") = {23, 21, 22, 7, 5, 6}; +//+ +Physical Curve("square_c") = {24, 27, 26, 25, 8, 9, 10, 11}; +//+ +Physical Curve("circle_c") = {28, 31, 29, 30, 12, 13, 14, 15}; +//+ +Physical Curve("sides_c") = {18, 17, 20, 19, 4, 3, 2, 1}; +//+ +Physical Point("sides_c") = {18, 17, 4, 3, 26, 2, 22, 1}; +//+ +Physical Point("triangle_c") = {38, 7, 34, 6, 33, 5}; +//+ +Physical Point("square_c") = {45, 54, 10, 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6788 +$EndElements diff --git a/docs/src/assets/poisson/fig_faces_on_circle.png b/assets/poisson/fig_faces_on_circle.png similarity index 100% rename from docs/src/assets/poisson/fig_faces_on_circle.png rename to assets/poisson/fig_faces_on_circle.png diff --git a/docs/src/assets/poisson/fig_uh.png b/assets/poisson/fig_uh.png similarity index 100% rename from docs/src/assets/poisson/fig_uh.png rename to assets/poisson/fig_uh.png diff --git a/docs/src/assets/poisson/fig_vertices_on_sides.png b/assets/poisson/fig_vertices_on_sides.png similarity index 100% rename from docs/src/assets/poisson/fig_vertices_on_sides.png rename to assets/poisson/fig_vertices_on_sides.png diff --git a/docs/src/assets/poisson/model-r1-2.png b/assets/poisson/model-r1-2.png similarity index 100% rename from docs/src/assets/poisson/model-r1-2.png rename to assets/poisson/model-r1-2.png diff --git a/notebooks/.ipynb_checkpoints/t001_poisson-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/t001_poisson-checkpoint.ipynb new file mode 100644 index 00000000..d54dca05 --- /dev/null +++ b/notebooks/.ipynb_checkpoints/t001_poisson-checkpoint.ipynb @@ -0,0 +1,738 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Tutorial 1: Poisson equation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this tutorial, we will learn\n", + "\n", + " - How to solve a simple PDE in Julia with GalerkinToolkit\n", + " - How to load a discrete model (aka a FE mesh) from a file\n", + " - How to build a conforming Lagrangian FE space\n", + " - How to define the different terms in a weak form\n", + " - How to impose Dirichlet and Neumann boundary conditions\n", + " - How to visualize results\n", + "\n", + "\n", + "## Problem statement\n", + "\n", + "In this first tutorial, we provide an overview of a complete simulation pipeline in GalerkinToolkit: from the construction of the FE mesh to the visualization of the computed results. To this end, we consider a simple model problem: the Poisson equation.\n", + " We want to solve the Poisson equation on the 3D domain depicted in next figure with Dirichlet and Neumann boundary conditions. Dirichlet boundary conditions are applied on $\\Gamma_{\\rm D}$, being the outer sides of the prism (marked in red). Non-homogeneous Neumann conditions are applied to the internal boundaries $\\Gamma_{\\rm G}$, $\\Gamma_{\\rm Y}$, and $\\Gamma_{\\rm B}$ (marked in green, yellow and blue respectively). And homogeneous Neumann boundary conditions are applied in $\\Gamma_{\\rm W}$, the remaining portion of the boundary (marked in white).\n", + "\n", + "![](../assets/poisson/model-r1-2.png)\n", + "\n", + " Formally, the problem to solve is: find the scalar field $u$ such that\n", + "\n", + "$$\n", + "\\left\\lbrace\n", + "\\begin{aligned}\n", + "-\\Delta u = f \\ &\\text{in} \\ \\Omega,\\\\\n", + "u = g \\ &\\text{on}\\ \\Gamma_{\\rm D},\\\\\n", + "\\nabla u\\cdot n = h \\ &\\text{on}\\ \\Gamma_{\\rm N},\\\\\n", + "\\end{aligned}\n", + "\\right.\n", + "$$\n", + " being $n$ the outwards unit normal vector to the Neumann boundary $\\Gamma_{\\rm N} \\doteq \\Gamma_{\\rm G}\\cup\\Gamma_{\\rm Y}\\cup\\Gamma_{\\rm B}\\cup\\Gamma_{\\rm W}$. In this example, we chose $f(x) = 1$, $g(x) = 2$, and $h(x)=3$ on $\\Gamma_{\\rm G}\\cup\\Gamma_{\\rm Y}\\cup\\Gamma_{\\rm B}$ and $h(x)=0$ on $\\Gamma_{\\rm W}$. The variable $x$ is the position vector $x=(x_1,x_2,x_3)$.\n", + "\n", + " ## Numerical scheme\n", + "\n", + " To solve this PDE, we use a conventional Galerkin finite element (FE) method with conforming Lagrangian FE spaces (see, e.g., [1] for specific details on this formulation). The weak form associated with this formulation is: find $u\\in U_g$ such that $ a(u,v) = b(v) $ for all $v\\in V_0$, where $U_g$ and $V_0$ are the subset of functions in $H^1(\\Omega)$ that fulfill the Dirichlet boundary condition $g$ and $0$ respectively. The bilinear and linear forms for this problems are\n", + "$$\n", + " a(u,v) \\doteq \\int_{\\Omega} \\nabla v \\cdot \\nabla u \\ {\\rm d}\\Omega, \\quad b(v) \\doteq \\int_{\\Omega} v\\ f \\ {\\rm d}\\Omega + \\int_{\\Gamma_{\\rm N}} v\\ h \\ {\\rm d}\\Gamma_{\\rm N}.\n", + "$$\n", + "The problem is solved numerically by approximating the spaces $U_g$ and $V_0$ by their discrete counterparts associated with a FE mesh of the computational domain $\\Omega$. As we have anticipated, we consider standard conforming Lagrangian FE spaces for this purpose.\n", + "\n", + "The implementation of this numerical scheme in GalerkinToolkit is done in a user-friendly way thanks to the abstractions provided by the library. As it will be seen below, all the mathematical objects involved in the definition of the discrete weak problem have a correspondent representation in the code.\n", + "\n", + " ## Setup\n", + "\n", + " The step number 0 in order to solve the problem is to load the GalerkinToolkit library in the code. If you have configured your Julia environment properly, it is simply done with the line:" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[36m\u001b[1mProject\u001b[22m\u001b[39m GalerkinToolkit v0.1.0\n", + "\u001b[32m\u001b[1mStatus\u001b[22m\u001b[39m `~/Library/CloudStorage/OneDrive-NetherlandseScienceCenter/Documents/NLeSC_Projects/HP2SIM/GalerkinToolkit.jl/Project.toml`\n", + " \u001b[90m[8e7c35d0] \u001b[39mBlockArrays v1.1.1\n", + " \u001b[90m[861a8166] \u001b[39mCombinatorics v1.0.2\n", + " \u001b[90m[442a2c76] \u001b[39mFastGaussQuadrature v1.0.2\n", + " \u001b[90m[1a297f60] \u001b[39mFillArrays v1.13.0\n", + " \u001b[90m[f6369f11] \u001b[39mForwardDiff v0.10.36\n", + " \u001b[90m[705231aa] \u001b[39mGmsh v0.3.1\n", + " \u001b[90m[42fd0dbc] \u001b[39mIterativeSolvers v0.9.4\n", + "\u001b[32m⌃\u001b[39m \u001b[90m[da04e1cc] \u001b[39mMPI v0.20.21\n", + " \u001b[90m[e9d8d322] \u001b[39mMetatheory v2.0.2\n", + "\u001b[32m⌃\u001b[39m \u001b[90m[2679e427] \u001b[39mMetis v1.4.1\n", + " \u001b[90m[5a9dfac6] \u001b[39mPartitionedArrays v0.5.4\n", + " \u001b[90m[90137ffa] \u001b[39mStaticArrays v1.9.7\n", + "\u001b[32m⌃\u001b[39m \u001b[90m[64499a7a] \u001b[39mWriteVTK v1.19.2\n", + " \u001b[90m[37e2e46d] \u001b[39mLinearAlgebra\n", + " \u001b[90m[2f01184e] \u001b[39mSparseArrays v1.10.0\n", + "\u001b[36m\u001b[1mInfo\u001b[22m\u001b[39m Packages marked with \u001b[32m⌃\u001b[39m have new versions available and may be upgradable.\n" + ] + } + ], + "source": [ + "using Pkg\n", + "Pkg.status()" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import GalerkinToolkit as GT" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Computational mesh\n", + "\n", + "As in any FE simulation, we need a discretization of the computational domain (i.e., a FE mesh). All geometrical data needed for solving a FE problem is provided in GalerkinToolkit by types inheriting from the abstract type `GenericMesh`. In the following line, we build an instance of `GenericMesh` by loading a `msh` file." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Info : Reading '../assets/model.msh'...\n", + "Info : 95 entities\n", + "Info : 7475 nodes\n", + "Info : 40330 elements\n", + "Info : Done reading '../assets/model.msh'\n" + ] + }, + { + "data": { + "text/plain": [ + "GalerkinToolkit.GenericMesh(…)" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mesh = GT.mesh_from_gmsh(\"../assets/model.msh\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The file `\"model.msh\"` (which contains a FE mesh and information about user-defined physical boundaries) was generated by using the [GMSH](http://gmsh.info/) mesh generator. See the documentation of [GMSH](http://gmsh.info/#Documentation).\n", + "\n", + "You can easily inspect the generated discrete model in [Paraview](https://www.paraview.org/) by writing it in `vtk` format." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1-element Vector{String}:\n", + " \"mesh.vtu\"" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# writevtk(model,\"model\")\n", + "# TODO\n", + "# GT.plot_vtk(\"mesh\",mesh)\n", + "using WriteVTK\n", + "vtk_grid(\"mesh\",GT.vtk_args(mesh)...) do vtk\n", + " GT.vtk_physical_faces!(vtk, mesh)\n", + "end" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Dict{String, Vector{Int32}} with 6 entries:\n", + " \"triangle\" => [5401, 5402, 5403, 5404, 5405, 5406, 5407, 5408, 5409, 5410 … …\n", + " \"bottom\" => [1, 2, 3, 4, 5, 6, 7, 8, 9, 10 … 3385, 3386, 3387, 3388, 3389…\n", + " \"circle\" => [6609, 6610, 6611, 6612, 6613, 6614, 6615, 6616, 6617, 6618 … …\n", + " \"top\" => [7053, 7054, 7055, 7056, 7057, 7058, 7059, 7060, 7061, 7062 … …\n", + " \"square\" => [6053, 6054, 6055, 6056, 6057, 6058, 6059, 6060, 6061, 6062 … …\n", + " \"sides\" => [3395, 3396, 3397, 3398, 3399, 3400, 3401, 3402, 3403, 3404 … …" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "GT.physical_faces(mesh,2)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Dict{String, Vector{Int32}} with 1 entry:\n", + " \"volume\" => [1, 2, 3, 4, 5, 6, 7, 8, 9, 10 … 29151, 29152, 29153, 29154, 29…" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "GT.physical_faces(mesh,3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Computational domains" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.PhysicalDomain(…)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Ω = GT.interior(mesh;physical_names=[\"volume\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "GT.vtk_plot(\"Ω\",Ω) do plt end # TODO Maybe remove do plt end\n", + "# GT.vtk_plot(\"Ω\",Ω)\n", + "# TODO move this to domain.jl\n", + "GT.vtk_plot(name::AbstractString,domain::GT.AbstractDomain;kwargs...) = GT.vtk_plot(identity,name,domain;kwargs...)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1-element Vector{String}:\n", + " \"Ω.vtu\"" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "GT.vtk_plot(\"Ω\",Ω)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.PhysicalDomain(…)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Γd = GT.boundary(mesh;physical_names=[\"sides\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1-element Vector{String}:\n", + " \"Γd.vtu\"" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "GT.vtk_plot(\"Γd\",Γd) do plt end # TODO Maybe remove do plt end" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.PhysicalDomain(…)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Γ = GT.boundary(mesh;physical_names=[\"circle\", \"triangle\", \"square\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1-element Vector{String}:\n", + " \"Γ.vtu\"" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "GT.vtk_plot(\"Γ\",Γ) do plt end # TODO Maybe remove do plt end" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The previous line generates four different files `model_0.vtu`, `model_1.vtu`, `model_2.vtu`, and `model_3.vtu` containing the vertices, edges, faces, and cells present in the discrete model. Moreover, you can easily inspect which boundaries are defined within the model.\n", + "\n", + "For instance, if you want to see which faces of the model are on the boundary $\\Gamma_{\\rm B}$ (i.e., the walls of the circular perforation), open the file `model_2.vtu` and chose coloring by the element field \"circle\". You should see that only the faces on the circular hole have a value different from zero (see next figure).\n", + "\n", + "![](../assets/poisson/fig_faces_on_circle.png)\n", + "\n", + "It is also possible to see which vertices are on the Dirichlet boundary $\\Gamma_{\\rm D}$. To do so, open the file `model_0.vtu` and chose coloring by the field \"sides\" (see next figure).\n", + "\n", + "![](../assets/poisson/fig_vertices_on_sides.png)\n", + "\n", + "That is, the boundary $\\Gamma_{\\rm B}$ (i.e., the walls of the circular hole) is called \"circle\" and the Dirichlet boundary $\\Gamma_{\\rm D}$ is called \"sides\" in the model. In addition, the walls of the triangular hole $\\Gamma_{\\rm G}$ and the walls of the square hole $\\Gamma_{\\rm Y}$ are identified in the model with the names \"triangle\" and \"square\" respectively. You can easily check this by opening the corresponding file in Paraview.\n", + "\n", + "\n", + "## FE spaces\n", + "\n", + " Once we have a discretization of the computational domain, the next step is to generate a discrete approximation of the finite element spaces $V_0$ and $U_g$ (i.e. the test and trial FE spaces) of the problem. To do so, first, we are going to build a discretization of $V_0$ as the standard Conforming Lagrangian FE space (with zero boundary conditions) associated with the discretization of the computational domain. The approximation of the FE space $V_0$ is built as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.LagrangeSpace(…)" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "order = 1\n", + "V = GT.lagrange_space(Ω,order;dirichlet_boundary=Γd)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here, we have used the `TestFESpace` constructor, which constructs a particular FE space (to be used as a test space) from a set of options described as positional and key-word arguments. The first positional argument is the model on top of which we want to build the space. The second positional argument contains information about the type of FE interpolation (the reference FE in this case). With `ReferenceFE(lagrangian,Float64,order)` We select a scalar-valued Lagrangian reference FE of order 1, where the value of the shape functions will be represented with 64-bit floating point numbers. With the key-word argument `conformity` we define the regularity of the interpolation at the boundaries of the cells in the mesh. Here, we use `conformity=:H1`, which means that the resulting interpolation space is a subset of $H^1(\\Omega)$ (i.e., continuous shape functions). On the other hand, we pass the identifiers of the Dirichlet boundary via the `dirichlet_tags` argument. In this case, we mark as Dirichlet all objects of the discrete model identified with the `\"sides\"` tag. Since this is a test space, the corresponding shape functions vanishes at the Dirichlet boundary.\n", + "\n", + "Once the space $V_0$ is discretized in the code, we proceed with the approximation of the trial space $U_g$." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.DiscreteField(…)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "uhd = GT.dirichlet_field(Float64,V)\n", + "g = GT.analytical_field(Ω) do x\n", + " 2.0\n", + "end\n", + "GT.interpolate_dirichlet!(g,uhd)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1-element Vector{String}:\n", + " \"Γd.vtu\"" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "GT.vtk_plot(\"Γd\",Γd) do plt\n", + " GT.plot!(plt,g;label=\"g\")\n", + "end" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1-element Vector{String}:\n", + " \"Ω.vtu\"" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "GT.vtk_plot(\"Ω\",Ω) do plt\n", + " GT.plot!(plt,uhd;label=\"uhd\")\n", + "end" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To this end, we have used the `TrialFESpace` constructors. Note that we have passed a function representing the value of the Dirichlet boundary condition, when building the trial space.\n", + "\n", + "\n", + "## Numerical integration\n", + "\n", + "Once we have built the interpolation spaces, the next step is to set up the machinery to perform the integrals in the weak form numerically. Here, we need to compute integrals on the interior of the domain $\\Omega$ and on the Neumann boundary $\\Gamma_{\\rm N}$. In both cases, we need two main ingredients. We need to define an integration mesh (i.e. a triangulation of the integration domain), plus a Gauss-like quadrature in each of the cells in the triangulation. In Gridap, integration meshes are represented by types inheriting from the abstract type `Triangulation`. For integrating on the domain $\\Omega$, we build the following triangulation and the corresponding Lebesgue measure, which will allow to write down integrals in a syntax similar to the usual mathematical notation." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.Measure(…)" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "degree = 2*order\n", + "dΩ = GT.measure(Ω,degree) # TODO fix pretty printing in GalerkinToolkit.Measure" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here, we build a triangulation from the cells of the model and build (an approximation of) the Lebesgue measure using a quadrature rule of degree 2 in the cells of this triangulation. This is enough for integrating the corresponding terms of the weak form exactly for an interpolation of order 1.\n", + "\n", + "On the other hand, we need a special type of triangulation, represented by the type `BoundaryTriangulation`, to integrate on the boundary. Essentially, a `BoundaryTriangulation` is a particular type of `Triangulation` that is aware of which cells in the model are touched by faces on the boundary. We build an instance of this type from the discrete model and the names used to identify the Neumann boundary as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.Measure(…)" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dΓ = GT.measure(Γ,degree)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Differential operators" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "∇ (generic function with 1 method)" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "using ForwardDiff\n", + "gradient(u) = x->ForwardDiff.gradient(u,x)\n", + "∇(u,x) = GT.call(gradient,u)(x)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In addition, we have created a quadrature of degree 2 on top of the cells in the triangulation for the Neumann boundary.\n", + "\n", + "## Weak form\n", + "\n", + "With all the ingredients presented so far, we are ready to define the weak form. This is done by defining functions representing the bi-linear and linear forms:" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "l (generic function with 1 method)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "using LinearAlgebra\n", + "f = GT.analytical_field(Ω) do x\n", + " 1.0\n", + "end\n", + "h = GT.analytical_field(Ω) do x\n", + " 3.0\n", + "end\n", + "a(u,v) = GT.∫( x->∇(u,x)⋅∇(v,x), dΩ)\n", + "l(v) = GT.∫( x->v(x)*f(x), dΩ) + GT.∫( x->v(x)*h(x),dΓ)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that by using the integral function `∫`, the Lebesgue measures `dΩ`, `dΓ`, and the gradient function `∇`, the weak form is written with an obvious relation with the corresponding mathematical notation." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " ## FE Problem\n", + "\n", + " At this point, we can build the FE problem that, once solved, will provide the numerical solution we are looking for. A FE problem is represented in Gridap by types inheriting from the abstract type `FEOperator` (both for linear and nonlinear cases). Since we want to solve a linear problem, we use the concrete type `AffineFEOperator`, i.e., a problem represented by a matrix and a right hand side vector." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "x,A,b = GT.linear_problem(uhd,a,l)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that the `AffineFEOperator` object representing our FE problem is built from the function `a` and `b` representing the weak form and test and trial FE spaces `V0` and `Ug`.\n", + "\n", + " ## Solver phase\n", + "\n", + " We have constructed a FE problem, the last step is to solve it. In Gridap, FE problems are solved with types inheriting from the abstract type `FESolver`. Since this is a linear problem, we use a `LinearFESolver`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "x .= A\\b" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " `LinearFESolver` objects are built from a given algebraic linear solver. In this case, we use a LU factorization. Now we are ready to solve the FE problem with the FE solver as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "uh = GT.solution_field(uhd,x)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `solve` function returns the computed numerical solution `uh`. This object is an instance of `FEFunction`, the type used to represent a function in a FE space. We can inspect the result by writing it into a `vtk` file:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "GT.vtk_plot(\"Ω\",Ω) do plt\n", + " GT.plot!(plt,uhd;label=\"uhd\")\n", + " GT.plot!(plt,uh;label=\"uh\")\n", + "end" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " which will generate a file named `results.vtu` having a nodal field named `\"uh\"` containing the solution of our problem (see next figure).\n", + "\n", + "![](../assets/poisson/fig_uh.png)\n", + "\n", + "## References\n", + "\n", + "[1] C. Johnson. *Numerical Solution of Partial Differential Equations by the Finite Element Method*. Dover Publications, 2009." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "*This notebook was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).*" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Julia 1.10.5", + "language": "julia", + "name": "julia-1.10" + }, + "language_info": { + "file_extension": ".jl", + "mimetype": "application/julia", + "name": "julia", + "version": "1.10.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/notebooks/t001_poisson.ipynb b/notebooks/t001_poisson.ipynb new file mode 100644 index 00000000..369baf1a --- /dev/null +++ b/notebooks/t001_poisson.ipynb @@ -0,0 +1,781 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Tutorial 1: Poisson equation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this tutorial, we will learn\n", + "\n", + " - How to solve a simple PDE in Julia with GalerkinToolkit\n", + " - How to load a discrete model (aka a FE mesh) from a file\n", + " - How to build a conforming Lagrangian FE space\n", + " - How to define the different terms in a weak form\n", + " - How to impose Dirichlet and Neumann boundary conditions\n", + " - How to visualize results\n", + "\n", + "\n", + "## Problem statement\n", + "\n", + "In this first tutorial, we provide an overview of a complete simulation pipeline in GalerkinToolkit: from the construction of the FE mesh to the visualization of the computed results. To this end, we consider a simple model problem: the Poisson equation.\n", + " We want to solve the Poisson equation on the 3D domain depicted in next figure with Dirichlet and Neumann boundary conditions. Dirichlet boundary conditions are applied on $\\Gamma_{\\rm D}$, being the outer sides of the prism (marked in red). Non-homogeneous Neumann conditions are applied to the internal boundaries $\\Gamma_{\\rm G}$, $\\Gamma_{\\rm Y}$, and $\\Gamma_{\\rm B}$ (marked in green, yellow and blue respectively). And homogeneous Neumann boundary conditions are applied in $\\Gamma_{\\rm W}$, the remaining portion of the boundary (marked in white).\n", + "\n", + "![](../assets/poisson/model-r1-2.png)\n", + "\n", + " Formally, the problem to solve is: find the scalar field $u$ such that\n", + "\n", + "$$\n", + "\\left\\lbrace\n", + "\\begin{aligned}\n", + "-\\Delta u = f \\ &\\text{in} \\ \\Omega,\\\\\n", + "u = g \\ &\\text{on}\\ \\Gamma_{\\rm D},\\\\\n", + "\\nabla u\\cdot n = h \\ &\\text{on}\\ \\Gamma_{\\rm N},\\\\\n", + "\\end{aligned}\n", + "\\right.\n", + "$$\n", + " being $n$ the outwards unit normal vector to the Neumann boundary $\\Gamma_{\\rm N} \\doteq \\Gamma_{\\rm G}\\cup\\Gamma_{\\rm Y}\\cup\\Gamma_{\\rm B}\\cup\\Gamma_{\\rm W}$. In this example, we chose $f(x) = 1$, $g(x) = 2$, and $h(x)=3$ on $\\Gamma_{\\rm G}\\cup\\Gamma_{\\rm Y}\\cup\\Gamma_{\\rm B}$ and $h(x)=0$ on $\\Gamma_{\\rm W}$. The variable $x$ is the position vector $x=(x_1,x_2,x_3)$.\n", + "\n", + " ## Numerical scheme\n", + "\n", + " To solve this PDE, we use a conventional Galerkin finite element (FE) method with conforming Lagrangian FE spaces (see, e.g., [1] for specific details on this formulation). The weak form associated with this formulation is: find $u\\in U_g$ such that $ a(u,v) = b(v) $ for all $v\\in V_0$, where $U_g$ and $V_0$ are the subset of functions in $H^1(\\Omega)$ that fulfill the Dirichlet boundary condition $g$ and $0$ respectively. The bilinear and linear forms for this problems are\n", + "$$\n", + " a(u,v) \\doteq \\int_{\\Omega} \\nabla v \\cdot \\nabla u \\ {\\rm d}\\Omega, \\quad b(v) \\doteq \\int_{\\Omega} v\\ f \\ {\\rm d}\\Omega + \\int_{\\Gamma_{\\rm N}} v\\ h \\ {\\rm d}\\Gamma_{\\rm N}.\n", + "$$\n", + "The problem is solved numerically by approximating the spaces $U_g$ and $V_0$ by their discrete counterparts associated with a FE mesh of the computational domain $\\Omega$. As we have anticipated, we consider standard conforming Lagrangian FE spaces for this purpose.\n", + "\n", + "The implementation of this numerical scheme in GalerkinToolkit is done in a user-friendly way thanks to the abstractions provided by the library. As it will be seen below, all the mathematical objects involved in the definition of the discrete weak problem have a correspondent representation in the code.\n", + "\n", + " ## Setup\n", + "\n", + " The step number 0 in order to solve the problem is to load the GalerkinToolkit library in the code. If you have configured your Julia environment properly, it is simply done with the line:" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[36m\u001b[1mProject\u001b[22m\u001b[39m GalerkinToolkit v0.1.0\n", + "\u001b[32m\u001b[1mStatus\u001b[22m\u001b[39m `~/Library/CloudStorage/OneDrive-NetherlandseScienceCenter/Documents/NLeSC_Projects/HP2SIM/GalerkinToolkit.jl/Project.toml`\n", + " \u001b[90m[8e7c35d0] \u001b[39mBlockArrays v1.1.1\n", + " \u001b[90m[861a8166] \u001b[39mCombinatorics v1.0.2\n", + " \u001b[90m[442a2c76] \u001b[39mFastGaussQuadrature v1.0.2\n", + " \u001b[90m[1a297f60] \u001b[39mFillArrays v1.13.0\n", + " \u001b[90m[f6369f11] \u001b[39mForwardDiff v0.10.36\n", + " \u001b[90m[705231aa] \u001b[39mGmsh v0.3.1\n", + " \u001b[90m[42fd0dbc] \u001b[39mIterativeSolvers v0.9.4\n", + "\u001b[32m⌃\u001b[39m \u001b[90m[da04e1cc] \u001b[39mMPI v0.20.21\n", + " \u001b[90m[e9d8d322] \u001b[39mMetatheory v2.0.2\n", + "\u001b[32m⌃\u001b[39m \u001b[90m[2679e427] \u001b[39mMetis v1.4.1\n", + " \u001b[90m[5a9dfac6] \u001b[39mPartitionedArrays v0.5.4\n", + " \u001b[90m[90137ffa] \u001b[39mStaticArrays v1.9.7\n", + "\u001b[32m⌃\u001b[39m \u001b[90m[64499a7a] \u001b[39mWriteVTK v1.19.2\n", + " \u001b[90m[37e2e46d] \u001b[39mLinearAlgebra\n", + " \u001b[90m[2f01184e] \u001b[39mSparseArrays v1.10.0\n", + "\u001b[36m\u001b[1mInfo\u001b[22m\u001b[39m Packages marked with \u001b[32m⌃\u001b[39m have new versions available and may be upgradable.\n" + ] + } + ], + "source": [ + "using Pkg\n", + "Pkg.status()" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import GalerkinToolkit as GT" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Computational mesh\n", + "\n", + "As in any FE simulation, we need a discretization of the computational domain (i.e., a FE mesh). All geometrical data needed for solving a FE problem is provided in GalerkinToolkit by types inheriting from the abstract type `GenericMesh`. In the following line, we build an instance of `GenericMesh` by loading a `msh` file." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Info : Reading '../assets/model.msh'...\n", + "Info : 95 entities\n", + "Info : 7475 nodes\n", + "Info : 40330 elements\n", + "Info : Done reading '../assets/model.msh'\n" + ] + }, + { + "data": { + "text/plain": [ + "GalerkinToolkit.GenericMesh(…)" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mesh = GT.mesh_from_gmsh(\"../assets/model.msh\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The file `\"model.msh\"` (which contains a FE mesh and information about user-defined physical boundaries) was generated by using the [GMSH](http://gmsh.info/) mesh generator. See the documentation of [GMSH](http://gmsh.info/#Documentation).\n", + "\n", + "You can easily inspect the generated discrete model in [Paraview](https://www.paraview.org/) by writing it in `vtk` format." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1-element Vector{String}:\n", + " \"mesh.vtu\"" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# writevtk(model,\"model\")\n", + "# TODO\n", + "# GT.plot_vtk(\"mesh\",mesh)\n", + "using WriteVTK\n", + "vtk_grid(\"mesh\",GT.vtk_args(mesh)...) do vtk\n", + " GT.vtk_physical_faces!(vtk, mesh)\n", + "end" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Dict{String, Vector{Int32}} with 6 entries:\n", + " \"triangle\" => [5401, 5402, 5403, 5404, 5405, 5406, 5407, 5408, 5409, 5410 … …\n", + " \"bottom\" => [1, 2, 3, 4, 5, 6, 7, 8, 9, 10 … 3385, 3386, 3387, 3388, 3389…\n", + " \"circle\" => [6609, 6610, 6611, 6612, 6613, 6614, 6615, 6616, 6617, 6618 … …\n", + " \"top\" => [7053, 7054, 7055, 7056, 7057, 7058, 7059, 7060, 7061, 7062 … …\n", + " \"square\" => [6053, 6054, 6055, 6056, 6057, 6058, 6059, 6060, 6061, 6062 … …\n", + " \"sides\" => [3395, 3396, 3397, 3398, 3399, 3400, 3401, 3402, 3403, 3404 … …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "GT.physical_faces(mesh,2)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Dict{String, Vector{Int32}} with 1 entry:\n", + " \"volume\" => [1, 2, 3, 4, 5, 6, 7, 8, 9, 10 … 29151, 29152, 29153, 29154, 29…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "GT.physical_faces(mesh,3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Computational domains" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.PhysicalDomain(…)" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "Ω = GT.interior(mesh;physical_names=[\"volume\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "GT.vtk_plot(\"Ω\",Ω) do plt end # TODO Maybe remove do plt end\n", + "# GT.vtk_plot(\"Ω\",Ω)\n", + "# TODO move this to domain.jl\n", + "GT.vtk_plot(name::AbstractString,domain::GT.AbstractDomain;kwargs...) = GT.vtk_plot(identity,name,domain;kwargs...)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1-element Vector{String}:\n", + " \"Ω.vtu\"" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "GT.vtk_plot(\"Ω\",Ω)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.PhysicalDomain(…)" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "Γd = GT.boundary(mesh;physical_names=[\"sides\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1-element Vector{String}:\n", + " \"Γd.vtu\"" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "GT.vtk_plot(\"Γd\",Γd) do plt end # TODO Maybe remove do plt end" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.PhysicalDomain(…)" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "Γ = GT.boundary(mesh;physical_names=[\"circle\", \"triangle\", \"square\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1-element Vector{String}:\n", + " \"Γ.vtu\"" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "GT.vtk_plot(\"Γ\",Γ) do plt end # TODO Maybe remove do plt end" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The previous line generates four different files `model_0.vtu`, `model_1.vtu`, `model_2.vtu`, and `model_3.vtu` containing the vertices, edges, faces, and cells present in the discrete model. Moreover, you can easily inspect which boundaries are defined within the model.\n", + "\n", + "For instance, if you want to see which faces of the model are on the boundary $\\Gamma_{\\rm B}$ (i.e., the walls of the circular perforation), open the file `model_2.vtu` and chose coloring by the element field \"circle\". You should see that only the faces on the circular hole have a value different from zero (see next figure).\n", + "\n", + "![](../assets/poisson/fig_faces_on_circle.png)\n", + "\n", + "It is also possible to see which vertices are on the Dirichlet boundary $\\Gamma_{\\rm D}$. To do so, open the file `model_0.vtu` and chose coloring by the field \"sides\" (see next figure).\n", + "\n", + "![](../assets/poisson/fig_vertices_on_sides.png)\n", + "\n", + "That is, the boundary $\\Gamma_{\\rm B}$ (i.e., the walls of the circular hole) is called \"circle\" and the Dirichlet boundary $\\Gamma_{\\rm D}$ is called \"sides\" in the model. In addition, the walls of the triangular hole $\\Gamma_{\\rm G}$ and the walls of the square hole $\\Gamma_{\\rm Y}$ are identified in the model with the names \"triangle\" and \"square\" respectively. You can easily check this by opening the corresponding file in Paraview.\n", + "\n", + "\n", + "## FE spaces\n", + "\n", + " Once we have a discretization of the computational domain, the next step is to generate a discrete approximation of the finite element spaces $V_0$ and $U_g$ (i.e. the test and trial FE spaces) of the problem. To do so, first, we are going to build a discretization of $V_0$ as the standard Conforming Lagrangian FE space (with zero boundary conditions) associated with the discretization of the computational domain. The approximation of the FE space $V_0$ is built as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.LagrangeSpace(…)" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "order = 1\n", + "V = GT.lagrange_space(Ω,order;dirichlet_boundary=Γd)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here, we have used the `TestFESpace` constructor, which constructs a particular FE space (to be used as a test space) from a set of options described as positional and key-word arguments. The first positional argument is the model on top of which we want to build the space. The second positional argument contains information about the type of FE interpolation (the reference FE in this case). With `ReferenceFE(lagrangian,Float64,order)` We select a scalar-valued Lagrangian reference FE of order 1, where the value of the shape functions will be represented with 64-bit floating point numbers. With the key-word argument `conformity` we define the regularity of the interpolation at the boundaries of the cells in the mesh. Here, we use `conformity=:H1`, which means that the resulting interpolation space is a subset of $H^1(\\Omega)$ (i.e., continuous shape functions). On the other hand, we pass the identifiers of the Dirichlet boundary via the `dirichlet_tags` argument. In this case, we mark as Dirichlet all objects of the discrete model identified with the `\"sides\"` tag. Since this is a test space, the corresponding shape functions vanishes at the Dirichlet boundary.\n", + "\n", + "Once the space $V_0$ is discretized in the code, we proceed with the approximation of the trial space $U_g$." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.DiscreteField(…)" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "uhd = GT.dirichlet_field(Float64,V)\n", + "g = GT.analytical_field(Ω) do x\n", + " 2.0\n", + "end\n", + "GT.interpolate_dirichlet!(g,uhd)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1-element Vector{String}:\n", + " \"Γd.vtu\"" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "GT.vtk_plot(\"Γd\",Γd) do plt\n", + " GT.plot!(plt,g;label=\"g\")\n", + "end" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1-element Vector{String}:\n", + " \"Ω.vtu\"" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "GT.vtk_plot(\"Ω\",Ω) do plt\n", + " GT.plot!(plt,uhd;label=\"uhd\")\n", + "end" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To this end, we have used the `TrialFESpace` constructors. Note that we have passed a function representing the value of the Dirichlet boundary condition, when building the trial space.\n", + "\n", + "\n", + "## Numerical integration\n", + "\n", + "Once we have built the interpolation spaces, the next step is to set up the machinery to perform the integrals in the weak form numerically. Here, we need to compute integrals on the interior of the domain $\\Omega$ and on the Neumann boundary $\\Gamma_{\\rm N}$. In both cases, we need two main ingredients. We need to define an integration mesh (i.e. a triangulation of the integration domain), plus a Gauss-like quadrature in each of the cells in the triangulation. In Gridap, integration meshes are represented by types inheriting from the abstract type `Triangulation`. For integrating on the domain $\\Omega$, we build the following triangulation and the corresponding Lebesgue measure, which will allow to write down integrals in a syntax similar to the usual mathematical notation." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.Measure(…)" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "degree = 2*order\n", + "dΩ = GT.measure(Ω,degree) # TODO fix pretty printing in GalerkinToolkit.Measure" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here, we build a triangulation from the cells of the model and build (an approximation of) the Lebesgue measure using a quadrature rule of degree 2 in the cells of this triangulation. This is enough for integrating the corresponding terms of the weak form exactly for an interpolation of order 1.\n", + "\n", + "On the other hand, we need a special type of triangulation, represented by the type `BoundaryTriangulation`, to integrate on the boundary. Essentially, a `BoundaryTriangulation` is a particular type of `Triangulation` that is aware of which cells in the model are touched by faces on the boundary. We build an instance of this type from the discrete model and the names used to identify the Neumann boundary as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.Measure(…)" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dΓ = GT.measure(Γ,degree)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Differential operators" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "∇ (generic function with 1 method)" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "using ForwardDiff\n", + "gradient(u) = x->ForwardDiff.gradient(u,x)\n", + "∇(u,x) = GT.call(gradient,u)(x)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In addition, we have created a quadrature of degree 2 on top of the cells in the triangulation for the Neumann boundary.\n", + "\n", + "## Weak form\n", + "\n", + "With all the ingredients presented so far, we are ready to define the weak form. This is done by defining functions representing the bi-linear and linear forms:" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "l (generic function with 1 method)" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "using LinearAlgebra\n", + "f = GT.analytical_field(Ω) do x\n", + " 1.0\n", + "end\n", + "h = GT.analytical_field(Ω) do x\n", + " 3.0\n", + "end\n", + "a(u,v) = GT.∫( x->∇(u,x)⋅∇(v,x), dΩ)\n", + "l(v) = GT.∫( x->v(x)*f(x), dΩ) + GT.∫( x->v(x)*h(x),dΓ)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that by using the integral function `∫`, the Lebesgue measures `dΩ`, `dΓ`, and the gradient function `∇`, the weak form is written with an obvious relation with the corresponding mathematical notation." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " ## FE Problem\n", + "\n", + " At this point, we can build the FE problem that, once solved, will provide the numerical solution we are looking for. A FE problem is represented in Gridap by types inheriting from the abstract type `FEOperator` (both for linear and nonlinear cases). Since we want to solve a linear problem, we use the concrete type `AffineFEOperator`, i.e., a problem represented by a matrix and a right hand side vector." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "([5.7289883855e-314, 5.376498709e-314, 5.376498709e-314, 4.0e-323, 4.243991582e-314, 9.54898106e-314, 7.4e-323, 2.1219958226e-314, 0.0, 8.4879831955e-314 … 5.3765235783e-314, 2.121995795e-314, 2.121995791e-314, 5.729202794e-314, 0.0, NaN, 5.7290710723e-314, 0.0, 0.0, 0.0], sparse([1, 22, 74, 289, 337, 338, 339, 340, 341, 1872 … 6303, 335, 465, 467, 468, 1806, 6201, 6224, 6232, 6304], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 6303, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304], [0.06443080405538211, -0.0011816946972152084, -0.0019141180663583925, -0.03255921926190384, -0.013954244941888471, -0.009620087896820673, -0.0021278804315064915, -0.004654033162377993, -0.005173786773138719, 0.003329780400807812 … 0.21999530084991323, -0.015615599976174236, 0.003972555304119093, -0.009088995023018824, -0.00030902681072076353, -0.013784861561036393, -0.014076977113079436, -0.024457375688586837, -0.013734513123868308, 0.17287503833373258], 6304, 6304), [0.001567735161920194, 0.0015207565876126676, 0.0015232957017090138, 0.0016182302571138272, 0.0013414312146763385, 0.0014776038723584638, 0.001306589310230424, 0.0014160610368619702, 0.0014136920830547547, 0.001413925912088446 … 0.09466909943634595, 3.837716427462897e-5, 4.067983156302628e-5, 3.407470822273103e-5, 3.41027317460599e-5, 0.08456444214161216, 0.07001671663821094, 3.708312001443067e-5, 3.516169468651288e-5, 0.17159606501883534])" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "x,A,b = GT.linear_problem(uhd,a,l)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that the `AffineFEOperator` object representing our FE problem is built from the function `a` and `b` representing the weak form and test and trial FE spaces `V0` and `Ug`.\n", + "\n", + " ## Solver phase\n", + "\n", + " We have constructed a FE problem, the last step is to solve it. In Gridap, FE problems are solved with types inheriting from the abstract type `FESolver`. Since this is a linear problem, we use a `LinearFESolver`:" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "6304-element Vector{Float64}:\n", + " 2.288817650800605\n", + " 3.191214461559075\n", + " 3.243769827996373\n", + " 4.513021960049178\n", + " 4.137978510723658\n", + " 2.6511832145611978\n", + " 3.9985286410715637\n", + " 2.3676403246611577\n", + " 2.6253865316943625\n", + " 3.1924629585377917\n", + " ⋮\n", + " 2.3980575528123094\n", + " 3.9912082231886825\n", + " 3.6282800936694914\n", + " 3.817091127051113\n", + " 2.0771951682489314\n", + " 2.0995109886643184\n", + " 2.4363879401098405\n", + " 4.398698443572705\n", + " 2.0089547066118425" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "x .= A\\b" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " `LinearFESolver` objects are built from a given algebraic linear solver. In this case, we use a LU factorization. Now we are ready to solve the FE problem with the FE solver as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.DiscreteField(…)" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "uh = GT.solution_field(uhd,x)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `solve` function returns the computed numerical solution `uh`. This object is an instance of `FEFunction`, the type used to represent a function in a FE space. We can inspect the result by writing it into a `vtk` file:" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1-element Vector{String}:\n", + " \"Ω.vtu\"" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "GT.vtk_plot(\"Ω\",Ω) do plt\n", + " GT.plot!(plt,uhd;label=\"uhd\")\n", + " GT.plot!(plt,uh;label=\"uh\")\n", + "end" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " which will generate a file named `results.vtu` having a nodal field named `\"uh\"` containing the solution of our problem (see next figure).\n", + "\n", + "![](../assets/poisson/fig_uh.png)\n", + "\n", + "## References\n", + "\n", + "[1] C. Johnson. *Numerical Solution of Partial Differential Equations by the Finite Element Method*. Dover Publications, 2009." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "*This notebook was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).*" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Julia 1.10.5", + "language": "julia", + "name": "julia-1.10" + }, + "language_info": { + "file_extension": ".jl", + "mimetype": "application/julia", + "name": "julia", + "version": "1.10.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From 9367829db46ca9d58d8ca9d64f5526ca82daf9a2 Mon Sep 17 00:00:00 2001 From: Cmurilochem Date: Fri, 27 Sep 2024 14:21:03 +0200 Subject: [PATCH 09/14] Fix in docs and folder location --- {assets => docs/src/assets}/model.geo | 0 {assets => docs/src/assets}/model.msh | 0 .../assets}/poisson/fig_faces_on_circle.png | Bin .../src/assets}/poisson/fig_uh.png | Bin .../assets}/poisson/fig_vertices_on_sides.png | Bin .../src/assets}/poisson/model-r1-2.png | Bin .../t001_poisson-checkpoint.ipynb | 101 +++++++++++++++--- notebooks/t001_poisson.ipynb | 88 +++++++++------ 8 files changed, 144 insertions(+), 45 deletions(-) rename {assets => docs/src/assets}/model.geo (100%) rename {assets => docs/src/assets}/model.msh (100%) rename {assets => docs/src/assets}/poisson/fig_faces_on_circle.png (100%) rename {assets => docs/src/assets}/poisson/fig_uh.png (100%) rename {assets => docs/src/assets}/poisson/fig_vertices_on_sides.png (100%) rename {assets => docs/src/assets}/poisson/model-r1-2.png (100%) diff --git a/assets/model.geo b/docs/src/assets/model.geo similarity index 100% rename from assets/model.geo rename to docs/src/assets/model.geo diff --git a/assets/model.msh b/docs/src/assets/model.msh similarity index 100% rename from assets/model.msh rename to docs/src/assets/model.msh diff --git a/assets/poisson/fig_faces_on_circle.png b/docs/src/assets/poisson/fig_faces_on_circle.png similarity index 100% rename from assets/poisson/fig_faces_on_circle.png rename to docs/src/assets/poisson/fig_faces_on_circle.png diff --git a/assets/poisson/fig_uh.png b/docs/src/assets/poisson/fig_uh.png similarity index 100% rename from assets/poisson/fig_uh.png rename to docs/src/assets/poisson/fig_uh.png diff --git a/assets/poisson/fig_vertices_on_sides.png b/docs/src/assets/poisson/fig_vertices_on_sides.png similarity index 100% rename from assets/poisson/fig_vertices_on_sides.png rename to docs/src/assets/poisson/fig_vertices_on_sides.png diff --git a/assets/poisson/model-r1-2.png b/docs/src/assets/poisson/model-r1-2.png similarity index 100% rename from assets/poisson/model-r1-2.png rename to docs/src/assets/poisson/model-r1-2.png diff --git a/notebooks/.ipynb_checkpoints/t001_poisson-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/t001_poisson-checkpoint.ipynb index d54dca05..308cd536 100644 --- a/notebooks/.ipynb_checkpoints/t001_poisson-checkpoint.ipynb +++ b/notebooks/.ipynb_checkpoints/t001_poisson-checkpoint.ipynb @@ -26,7 +26,7 @@ "In this first tutorial, we provide an overview of a complete simulation pipeline in GalerkinToolkit: from the construction of the FE mesh to the visualization of the computed results. To this end, we consider a simple model problem: the Poisson equation.\n", " We want to solve the Poisson equation on the 3D domain depicted in next figure with Dirichlet and Neumann boundary conditions. Dirichlet boundary conditions are applied on $\\Gamma_{\\rm D}$, being the outer sides of the prism (marked in red). Non-homogeneous Neumann conditions are applied to the internal boundaries $\\Gamma_{\\rm G}$, $\\Gamma_{\\rm Y}$, and $\\Gamma_{\\rm B}$ (marked in green, yellow and blue respectively). And homogeneous Neumann boundary conditions are applied in $\\Gamma_{\\rm W}$, the remaining portion of the boundary (marked in white).\n", "\n", - "![](../assets/poisson/model-r1-2.png)\n", + "![](../docs/src/assets/poisson/model-r1-2.png)\n", "\n", " Formally, the problem to solve is: find the scalar field $u$ such that\n", "\n", @@ -118,11 +118,11 @@ "name": "stdout", "output_type": "stream", "text": [ - "Info : Reading '../assets/model.msh'...\n", + "Info : Reading '../docs/src/assets/model.msh'...\n", "Info : 95 entities\n", "Info : 7475 nodes\n", "Info : 40330 elements\n", - "Info : Done reading '../assets/model.msh'\n" + "Info : Done reading '../docs/src/assets/model.msh'\n" ] }, { @@ -137,7 +137,7 @@ } ], "source": [ - "mesh = GT.mesh_from_gmsh(\"../assets/model.msh\")" + "mesh = GT.mesh_from_gmsh(\"../docs/src/assets/model.msh\")" ] }, { @@ -373,11 +373,11 @@ "\n", "For instance, if you want to see which faces of the model are on the boundary $\\Gamma_{\\rm B}$ (i.e., the walls of the circular perforation), open the file `model_2.vtu` and chose coloring by the element field \"circle\". You should see that only the faces on the circular hole have a value different from zero (see next figure).\n", "\n", - "![](../assets/poisson/fig_faces_on_circle.png)\n", + "![](../docs/src/assets/poisson/fig_faces_on_circle.png)\n", "\n", "It is also possible to see which vertices are on the Dirichlet boundary $\\Gamma_{\\rm D}$. To do so, open the file `model_0.vtu` and chose coloring by the field \"sides\" (see next figure).\n", "\n", - "![](../assets/poisson/fig_vertices_on_sides.png)\n", + "![](../docs/src/assets/poisson/fig_vertices_on_sides.png)\n", "\n", "That is, the boundary $\\Gamma_{\\rm B}$ (i.e., the walls of the circular hole) is called \"circle\" and the Dirichlet boundary $\\Gamma_{\\rm D}$ is called \"sides\" in the model. In addition, the walls of the triangular hole $\\Gamma_{\\rm G}$ and the walls of the square hole $\\Gamma_{\\rm Y}$ are identified in the model with the names \"triangle\" and \"square\" respectively. You can easily check this by opening the corresponding file in Paraview.\n", "\n", @@ -635,9 +635,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "([5.2150170844097e-310, 2.787823149e-314, 2.787823149e-314, 8.487983168e-314, 2.121995792e-314, 5.2150256584581e-310, NaN, NaN, 5.2150170844097e-310, 2.121995791e-314 … NaN, NaN, NaN, 2.8843385805e-314, NaN, 3.141768011e-314, NaN, 2.8834005396e-314, NaN, 2.8843373987e-314], sparse([1, 22, 74, 289, 337, 338, 339, 340, 341, 1872 … 6303, 335, 465, 467, 468, 1806, 6201, 6224, 6232, 6304], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 6303, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304], [0.06443080405538211, -0.0011816946972152084, -0.0019141180663583925, -0.03255921926190384, -0.013954244941888471, -0.009620087896820673, -0.0021278804315064915, -0.004654033162377993, -0.005173786773138719, 0.003329780400807812 … 0.21999530084991323, -0.015615599976174236, 0.003972555304119093, -0.009088995023018824, -0.00030902681072076353, -0.013784861561036393, -0.014076977113079436, -0.024457375688586837, -0.013734513123868308, 0.17287503833373258], 6304, 6304), [0.001567735161920194, 0.0015207565876126676, 0.0015232957017090138, 0.0016182302571138272, 0.0013414312146763385, 0.0014776038723584638, 0.001306589310230424, 0.0014160610368619702, 0.0014136920830547547, 0.001413925912088446 … 0.09466909943634595, 3.837716427462897e-5, 4.067983156302628e-5, 3.407470822273103e-5, 3.41027317460599e-5, 0.08456444214161216, 0.07001671663821094, 3.708312001443067e-5, 3.516169468651288e-5, 0.17159606501883534])" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x,A,b = GT.linear_problem(uhd,a,l)" ] @@ -655,9 +666,46 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "6304-element Vector{Float64}:\n", + " 2.288817650800605\n", + " 3.191214461559075\n", + " 3.243769827996373\n", + " 4.513021960049178\n", + " 4.137978510723658\n", + " 2.6511832145611978\n", + " 3.9985286410715637\n", + " 2.3676403246611577\n", + " 2.6253865316943625\n", + " 3.1924629585377917\n", + " 2.2896951265865444\n", + " 3.1863629312428015\n", + " 3.2445741024920083\n", + " ⋮\n", + " 4.285487712910332\n", + " 2.9668852150686487\n", + " 2.020241401823711\n", + " 2.3980575528123094\n", + " 3.9912082231886825\n", + " 3.6282800936694914\n", + " 3.817091127051113\n", + " 2.0771951682489314\n", + " 2.0995109886643184\n", + " 2.4363879401098405\n", + " 4.398698443572705\n", + " 2.0089547066118425" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x .= A\\b" ] @@ -671,9 +719,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "GalerkinToolkit.DiscreteField(…)" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "uh = GT.solution_field(uhd,x)" ] @@ -687,9 +746,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "1-element Vector{String}:\n", + " \"Ω.vtu\"" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "GT.vtk_plot(\"Ω\",Ω) do plt\n", " GT.plot!(plt,uhd;label=\"uhd\")\n", @@ -703,7 +774,7 @@ "source": [ " which will generate a file named `results.vtu` having a nodal field named `\"uh\"` containing the solution of our problem (see next figure).\n", "\n", - "![](../assets/poisson/fig_uh.png)\n", + "![](../docs/src/assets/poisson/fig_uh.png)\n", "\n", "## References\n", "\n", diff --git a/notebooks/t001_poisson.ipynb b/notebooks/t001_poisson.ipynb index 369baf1a..308cd536 100644 --- a/notebooks/t001_poisson.ipynb +++ b/notebooks/t001_poisson.ipynb @@ -26,7 +26,7 @@ "In this first tutorial, we provide an overview of a complete simulation pipeline in GalerkinToolkit: from the construction of the FE mesh to the visualization of the computed results. To this end, we consider a simple model problem: the Poisson equation.\n", " We want to solve the Poisson equation on the 3D domain depicted in next figure with Dirichlet and Neumann boundary conditions. Dirichlet boundary conditions are applied on $\\Gamma_{\\rm D}$, being the outer sides of the prism (marked in red). Non-homogeneous Neumann conditions are applied to the internal boundaries $\\Gamma_{\\rm G}$, $\\Gamma_{\\rm Y}$, and $\\Gamma_{\\rm B}$ (marked in green, yellow and blue respectively). And homogeneous Neumann boundary conditions are applied in $\\Gamma_{\\rm W}$, the remaining portion of the boundary (marked in white).\n", "\n", - "![](../assets/poisson/model-r1-2.png)\n", + "![](../docs/src/assets/poisson/model-r1-2.png)\n", "\n", " Formally, the problem to solve is: find the scalar field $u$ such that\n", "\n", @@ -118,11 +118,11 @@ "name": "stdout", "output_type": "stream", "text": [ - "Info : Reading '../assets/model.msh'...\n", + "Info : Reading '../docs/src/assets/model.msh'...\n", "Info : 95 entities\n", "Info : 7475 nodes\n", "Info : 40330 elements\n", - "Info : Done reading '../assets/model.msh'\n" + "Info : Done reading '../docs/src/assets/model.msh'\n" ] }, { @@ -131,12 +131,13 @@ "GalerkinToolkit.GenericMesh(…)" ] }, + "execution_count": 3, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "mesh = GT.mesh_from_gmsh(\"../assets/model.msh\")" + "mesh = GT.mesh_from_gmsh(\"../docs/src/assets/model.msh\")" ] }, { @@ -160,8 +161,9 @@ " \"mesh.vtu\"" ] }, + "execution_count": 4, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -191,8 +193,9 @@ " \"sides\" => [3395, 3396, 3397, 3398, 3399, 3400, 3401, 3402, 3403, 3404 … …" ] }, + "execution_count": 5, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -211,8 +214,9 @@ " \"volume\" => [1, 2, 3, 4, 5, 6, 7, 8, 9, 10 … 29151, 29152, 29153, 29154, 29…" ] }, + "execution_count": 6, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -237,8 +241,9 @@ "GalerkinToolkit.PhysicalDomain(…)" ] }, + "execution_count": 7, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -269,8 +274,9 @@ " \"Ω.vtu\"" ] }, + "execution_count": 9, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -288,8 +294,9 @@ "GalerkinToolkit.PhysicalDomain(…)" ] }, + "execution_count": 10, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -308,8 +315,9 @@ " \"Γd.vtu\"" ] }, + "execution_count": 11, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -327,8 +335,9 @@ "GalerkinToolkit.PhysicalDomain(…)" ] }, + "execution_count": 12, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -347,8 +356,9 @@ " \"Γ.vtu\"" ] }, + "execution_count": 13, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -363,11 +373,11 @@ "\n", "For instance, if you want to see which faces of the model are on the boundary $\\Gamma_{\\rm B}$ (i.e., the walls of the circular perforation), open the file `model_2.vtu` and chose coloring by the element field \"circle\". You should see that only the faces on the circular hole have a value different from zero (see next figure).\n", "\n", - "![](../assets/poisson/fig_faces_on_circle.png)\n", + "![](../docs/src/assets/poisson/fig_faces_on_circle.png)\n", "\n", "It is also possible to see which vertices are on the Dirichlet boundary $\\Gamma_{\\rm D}$. To do so, open the file `model_0.vtu` and chose coloring by the field \"sides\" (see next figure).\n", "\n", - "![](../assets/poisson/fig_vertices_on_sides.png)\n", + "![](../docs/src/assets/poisson/fig_vertices_on_sides.png)\n", "\n", "That is, the boundary $\\Gamma_{\\rm B}$ (i.e., the walls of the circular hole) is called \"circle\" and the Dirichlet boundary $\\Gamma_{\\rm D}$ is called \"sides\" in the model. In addition, the walls of the triangular hole $\\Gamma_{\\rm G}$ and the walls of the square hole $\\Gamma_{\\rm Y}$ are identified in the model with the names \"triangle\" and \"square\" respectively. You can easily check this by opening the corresponding file in Paraview.\n", "\n", @@ -388,8 +398,9 @@ "GalerkinToolkit.LagrangeSpace(…)" ] }, + "execution_count": 14, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -417,8 +428,9 @@ "GalerkinToolkit.DiscreteField(…)" ] }, + "execution_count": 15, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -441,8 +453,9 @@ " \"Γd.vtu\"" ] }, + "execution_count": 16, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -463,8 +476,9 @@ " \"Ω.vtu\"" ] }, + "execution_count": 17, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -496,8 +510,9 @@ "GalerkinToolkit.Measure(…)" ] }, + "execution_count": 18, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -525,8 +540,9 @@ "GalerkinToolkit.Measure(…)" ] }, + "execution_count": 19, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -551,8 +567,9 @@ "∇ (generic function with 1 method)" ] }, + "execution_count": 20, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -583,8 +600,9 @@ "l (generic function with 1 method)" ] }, + "execution_count": 21, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -623,11 +641,12 @@ { "data": { "text/plain": [ - "([5.7289883855e-314, 5.376498709e-314, 5.376498709e-314, 4.0e-323, 4.243991582e-314, 9.54898106e-314, 7.4e-323, 2.1219958226e-314, 0.0, 8.4879831955e-314 … 5.3765235783e-314, 2.121995795e-314, 2.121995791e-314, 5.729202794e-314, 0.0, NaN, 5.7290710723e-314, 0.0, 0.0, 0.0], sparse([1, 22, 74, 289, 337, 338, 339, 340, 341, 1872 … 6303, 335, 465, 467, 468, 1806, 6201, 6224, 6232, 6304], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 6303, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304], [0.06443080405538211, -0.0011816946972152084, -0.0019141180663583925, -0.03255921926190384, -0.013954244941888471, -0.009620087896820673, -0.0021278804315064915, -0.004654033162377993, -0.005173786773138719, 0.003329780400807812 … 0.21999530084991323, -0.015615599976174236, 0.003972555304119093, -0.009088995023018824, -0.00030902681072076353, -0.013784861561036393, -0.014076977113079436, -0.024457375688586837, -0.013734513123868308, 0.17287503833373258], 6304, 6304), [0.001567735161920194, 0.0015207565876126676, 0.0015232957017090138, 0.0016182302571138272, 0.0013414312146763385, 0.0014776038723584638, 0.001306589310230424, 0.0014160610368619702, 0.0014136920830547547, 0.001413925912088446 … 0.09466909943634595, 3.837716427462897e-5, 4.067983156302628e-5, 3.407470822273103e-5, 3.41027317460599e-5, 0.08456444214161216, 0.07001671663821094, 3.708312001443067e-5, 3.516169468651288e-5, 0.17159606501883534])" + "([5.2150170844097e-310, 2.787823149e-314, 2.787823149e-314, 8.487983168e-314, 2.121995792e-314, 5.2150256584581e-310, NaN, NaN, 5.2150170844097e-310, 2.121995791e-314 … NaN, NaN, NaN, 2.8843385805e-314, NaN, 3.141768011e-314, NaN, 2.8834005396e-314, NaN, 2.8843373987e-314], sparse([1, 22, 74, 289, 337, 338, 339, 340, 341, 1872 … 6303, 335, 465, 467, 468, 1806, 6201, 6224, 6232, 6304], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 6303, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304], [0.06443080405538211, -0.0011816946972152084, -0.0019141180663583925, -0.03255921926190384, -0.013954244941888471, -0.009620087896820673, -0.0021278804315064915, -0.004654033162377993, -0.005173786773138719, 0.003329780400807812 … 0.21999530084991323, -0.015615599976174236, 0.003972555304119093, -0.009088995023018824, -0.00030902681072076353, -0.013784861561036393, -0.014076977113079436, -0.024457375688586837, -0.013734513123868308, 0.17287503833373258], 6304, 6304), [0.001567735161920194, 0.0015207565876126676, 0.0015232957017090138, 0.0016182302571138272, 0.0013414312146763385, 0.0014776038723584638, 0.001306589310230424, 0.0014160610368619702, 0.0014136920830547547, 0.001413925912088446 … 0.09466909943634595, 3.837716427462897e-5, 4.067983156302628e-5, 3.407470822273103e-5, 3.41027317460599e-5, 0.08456444214161216, 0.07001671663821094, 3.708312001443067e-5, 3.516169468651288e-5, 0.17159606501883534])" ] }, + "execution_count": 22, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -664,7 +683,13 @@ " 2.3676403246611577\n", " 2.6253865316943625\n", " 3.1924629585377917\n", + " 2.2896951265865444\n", + " 3.1863629312428015\n", + " 3.2445741024920083\n", " ⋮\n", + " 4.285487712910332\n", + " 2.9668852150686487\n", + " 2.020241401823711\n", " 2.3980575528123094\n", " 3.9912082231886825\n", " 3.6282800936694914\n", @@ -676,8 +701,9 @@ " 2.0089547066118425" ] }, + "execution_count": 23, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -702,8 +728,9 @@ "GalerkinToolkit.DiscreteField(…)" ] }, + "execution_count": 24, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -729,8 +756,9 @@ " \"Ω.vtu\"" ] }, + "execution_count": 25, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -746,7 +774,7 @@ "source": [ " which will generate a file named `results.vtu` having a nodal field named `\"uh\"` containing the solution of our problem (see next figure).\n", "\n", - "![](../assets/poisson/fig_uh.png)\n", + "![](../docs/src/assets/poisson/fig_uh.png)\n", "\n", "## References\n", "\n", From b51c254bd0b52b06e98540da00a0d9565d528df3 Mon Sep 17 00:00:00 2001 From: Cmurilochem Date: Thu, 10 Oct 2024 15:08:37 +0200 Subject: [PATCH 10/14] Replace some vtk plots by makie plots --- notebooks/t001_poisson.ipynb | 264 +++++++++++++++++++++-------------- 1 file changed, 156 insertions(+), 108 deletions(-) diff --git a/notebooks/t001_poisson.ipynb b/notebooks/t001_poisson.ipynb index 308cd536..3768e16a 100644 --- a/notebooks/t001_poisson.ipynb +++ b/notebooks/t001_poisson.ipynb @@ -58,7 +58,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -74,32 +74,24 @@ " \u001b[90m[f6369f11] \u001b[39mForwardDiff v0.10.36\n", " \u001b[90m[705231aa] \u001b[39mGmsh v0.3.1\n", " \u001b[90m[42fd0dbc] \u001b[39mIterativeSolvers v0.9.4\n", - "\u001b[32m⌃\u001b[39m \u001b[90m[da04e1cc] \u001b[39mMPI v0.20.21\n", + " \u001b[90m[da04e1cc] \u001b[39mMPI v0.20.22\n", " \u001b[90m[e9d8d322] \u001b[39mMetatheory v2.0.2\n", - "\u001b[32m⌃\u001b[39m \u001b[90m[2679e427] \u001b[39mMetis v1.4.1\n", - " \u001b[90m[5a9dfac6] \u001b[39mPartitionedArrays v0.5.4\n", + " \u001b[90m[2679e427] \u001b[39mMetis v1.5.0\n", + " \u001b[90m[5a9dfac6] \u001b[39mPartitionedArrays v0.5.5\n", " \u001b[90m[90137ffa] \u001b[39mStaticArrays v1.9.7\n", - "\u001b[32m⌃\u001b[39m \u001b[90m[64499a7a] \u001b[39mWriteVTK v1.19.2\n", - " \u001b[90m[37e2e46d] \u001b[39mLinearAlgebra\n", - " \u001b[90m[2f01184e] \u001b[39mSparseArrays v1.10.0\n", - "\u001b[36m\u001b[1mInfo\u001b[22m\u001b[39m Packages marked with \u001b[32m⌃\u001b[39m have new versions available and may be upgradable.\n" + " \u001b[90m[64499a7a] \u001b[39mWriteVTK v1.21.0\n", + " \u001b[90m[37e2e46d] \u001b[39mLinearAlgebra v1.11.0\n", + " \u001b[90m[2f01184e] \u001b[39mSparseArrays v1.11.0\n" ] } ], "source": [ + "import GalerkinToolkit as GT\n", + "\n", "using Pkg\n", "Pkg.status()" ] }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "import GalerkinToolkit as GT" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -111,7 +103,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 30, "metadata": {}, "outputs": [ { @@ -131,9 +123,8 @@ "GalerkinToolkit.GenericMesh(…)" ] }, - "execution_count": 3, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ @@ -146,12 +137,43 @@ "source": [ "The file `\"model.msh\"` (which contains a FE mesh and information about user-defined physical boundaries) was generated by using the [GMSH](http://gmsh.info/) mesh generator. See the documentation of [GMSH](http://gmsh.info/#Documentation).\n", "\n", - "You can easily inspect the generated discrete model in [Paraview](https://www.paraview.org/) by writing it in `vtk` format." + "You can easily inspect the generated discrete model using [Makie](https://docs.makie.org/) and the [GLMakie](https://docs.makie.org/stable/explanations/backends/glmakie#GLMakie) backend. " + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/html": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "using GLMakie\n", + "Makie.inline!(true)\n", + "\n", + "plt = GT.plot(mesh)\n", + "Makie.plot(plt;shading=Makie.NoShading,color=:blue)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Alternatively, the generated discrete model can also be viewed using [Paraview](https://www.paraview.org/) by writing it in [WriteVTK](https://github.com/JuliaVTK/WriteVTK.jl) format." ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 74, "metadata": {}, "outputs": [ { @@ -161,24 +183,27 @@ " \"mesh.vtu\"" ] }, - "execution_count": 4, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "# writevtk(model,\"model\")\n", - "# TODO\n", - "# GT.plot_vtk(\"mesh\",mesh)\n", "using WriteVTK\n", - "vtk_grid(\"mesh\",GT.vtk_args(mesh)...) do vtk\n", - " GT.vtk_physical_faces!(vtk, mesh)\n", - "end" + "\n", + "plt = GT.plot(mesh)\n", + "WriteVTK.vtk_grid(\"mesh\", plt) |> close" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Apart from visualizations, users can additionally inspect general mesh attributes by resorting to several GalerkinToolkit's built-in functions, *e.g*, `num_dims`, `num_nodes`, `num_faces`, `node_coordinates`, `node_coordinates`, `physical_faces`, etc." ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 75, "metadata": {}, "outputs": [ { @@ -193,9 +218,8 @@ " \"sides\" => [3395, 3396, 3397, 3398, 3399, 3400, 3401, 3402, 3403, 3404 … …" ] }, - "execution_count": 5, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ @@ -204,7 +228,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 76, "metadata": {}, "outputs": [ { @@ -214,9 +238,8 @@ " \"volume\" => [1, 2, 3, 4, 5, 6, 7, 8, 9, 10 … 29151, 29152, 29153, 29154, 29…" ] }, - "execution_count": 6, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ @@ -232,7 +255,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 77, "metadata": {}, "outputs": [ { @@ -241,9 +264,8 @@ "GalerkinToolkit.PhysicalDomain(…)" ] }, - "execution_count": 7, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ @@ -252,40 +274,38 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "GT.vtk_plot(\"Ω\",Ω) do plt end # TODO Maybe remove do plt end\n", - "# GT.vtk_plot(\"Ω\",Ω)\n", - "# TODO move this to domain.jl\n", - "GT.vtk_plot(name::AbstractString,domain::GT.AbstractDomain;kwargs...) = GT.vtk_plot(identity,name,domain;kwargs...)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, + "execution_count": 78, "metadata": {}, "outputs": [ + { + "data": { + "image/png": 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oPB5rmoYpxpg1tb29HYZho9EAIITI5/PpdBqEvJ04CCGvZjAYeJ4XBEE+n19YWDBNE7uYTCbdbrfVag0GAyHE8vKyrutSol5HrYYzZxBFkBK3NCkhJXNd9r73qaur+JM/CR94wMxkOK7CORdTg8HA9/3nnnvOMAwhRC6XS6VSo9GIc46XS6fT5XJ5Zmam1+v5vt9sNi3LEkKYpskYAyFvAw5CyFU8z+t2uwsLC91u1/O8wWAghFheXtZ1HbvY2dlpt9utViuOYyHE/Py8qqpSol5HrQbXhZTYY6REvY7jx+0jRya/8zv+8eMZx8moKq5mTJXL5Xa7vbm52Wg0hBCDwSCfz+NaGGPW1Pb2dhiGjUYDgBDCtm1N00DIW4qDEHKVOI7DMByNRnEcFwqFhYUFzjl2IaUMgsDzPM55sVi0bZsxJiXqddRqcF1IiT1MSpw6pbiu0HX83M/hc5/r3X+/kU4zXEVV1WKxWCgUer1eEATnz5+vVCrpdNo0TcYYriWdTpfL5ZmZmV6v5/t+s9nM5/OO45imyRgDIW8FDkLIFaIoCoLg4sWLURQdOHDAsizGGHYRRZE/lc1m5+bmcrmcoihS4nvfQ60G14WUSIjxGL0e6nU8/LB55Agef7z9yCMZy9JUFa+gKEoulzNNs9PpmKbZaDQURXEcx7ZtTdNwLYwxayqKojAMG42GoiiO49i2rWkagDAMNU0zDAOEvH4chJCpXq/n+34YhrZtz8/Pdzod27axi36/73leGIaO4ywuLhqGAUBKuC5qNbgupEQySYlTp3D6dF7XsbKCL3xheN99GVXFK8RxDGB2dlZV1W63GwRBs9m0bVsIkc1mFUXBtei6XqlUSqVSt9sNgqDZbObzecdxgiDI5XKGYYCQ14+DkGSL47jT6fi+PxwOhRDLy8u6rvd6vTAMcZU4jrvdrud5w+FQCHH48OF0Oi0lul2cOIG1NbgupASRElKiXsf73pdZXcVnPtN54IGsrqfwop2dnclkkkqlGGP5qSiKgiC4cOGCqqqO49i2zTnHtTDG8lNRFIVheOnSpY2NjYMHD1qWpWkaCHmdOAhJqvF4HIah53kACoXCwsIC5xxTjLHJZBLHMWMMUzs7O2EYep4Xx3GhUFhYWOCcS4l6HbUazpxBFEFKkFeQEvU6PvAB68iRySc+ER4/rtu2rqoYj8epVIoxhhfpuj47O1sqlTqdju/7zWbTmTIMA7vQdb1SqRQKhW63K6X80Y9+ZNu24zjZbJYxBkJeGw5CkieKIt/3gyDIZDLlctmyLMYYrsAYi+MYU6PRKAgCz/M0TZuZmcnn84wxKVGvo1aD60JKkOuTEqdOKadP27qOlRX81/86uPNOqaoqYwwvl0qlnKnBYOD7/rlz53RdF0JYlpVKpXAtk8nEMIzFxcXxeByG4cWLF1OplD2laRoIeTUchCRJr9fzfT8MQ9u2Dxw4kM1mcS2MsclkMhgM2u12EASmac7Pz5umqSiKlPje91CrwXUhJchrJyWkRL2Of/fvjLvv3vnIR4L/8B/GpslVFVczpiqVShiGW1tbGxsbzpSu63i50WjEOU+lUpzzSqVSKpU6nU4QBM1m07Ztx3Gy2SxjDITsgoOQBIjjuNPpeJ63vb0thDh8+HA6ncbu+v3+1tbWeDwuFouLi4uGYQCQEq6LWg2uCylB3jAp8f3vp37wg/3/5b8oKytYW4vuvVdXVVyNc14sFguFQr/f933/7NmzlmU5jpPL5RhjmBqNRpqmKYqCKcaYPRVFURiGFy9eTKVSjuPk83lN00DIVTgI2dOklGEYep7HGBNC2LbNOccu4jjudDqe5w0GA8750tKSaZpSotvFiRNYW4PrQkqQt8R4rHS7qNfx0EP66io+97nu/fdn02mGqyiKYk5VKpUwDJvN5sbGhhDCtm1N00ajUTqdxlV0Xa9UKqVSqdPpBEHQbDbz+bwQIpvNKooCQl7EQcgeFUWRP2UYxuzsbC6XY4xhF+PxOAxD3/fjOC4Wi/v27XvmmWcAtV5HrYYzZxBFkBLk7SAl6nU8/HDuyBE8/nj7kUcylqWpKq6maVqpVCoWi71ez/f9ZrNp2/ZgMBBCYBeMMXsqiqIwDJ9//vlUKuU4Tj6f1zQNhAAchOw5vV7P87x2u+04zuLiomEY2N1oNPKnNE0rlUqWZTHGtrfjH/4w+/GPaz/4AaQEeQdIiVOncPp0XtexsoIvfGF4330ZVcXVGGPWVBRFYRg+++yzURQxxvL5vKqq2IWu65VKpVQqdTod3/ebzWY+nxdCZLNZRVFAEoyDkL0ijuN2u+153mg0EkLcfvvtmqZhd8Ph0PO8IAhyudzCwoJpmgCkxPe+h09+krnugfFYAXlnSQkpUa/jfe/LrK7iM5/p3H+/kclwXIuu66VSqdVqFYvFTqfTbDZt2xZCGIaBXTDG7KkoioIguHDhAudcCGFZlqZpmBqPx5xzkMTgIOTWJ6UMgsD3fcZYoVDI5/Occ+yu1+u1Wq1ut+s4ztLSUiaTASAlXBe1GlwXUgJQQG4cKVGv4wMfsI4cmXziE+Hx47pt66qKVxiPx3EcF4tFzvlwOPR9/7nnntN1XQhhWRbnHLvQdX12drZUKnW7Xd/3NzY28vm8ECKbzTYaDV3XS6USSDJwEHIri6LInzIMo1qtmqbJGMMu4jjudDqtVms0GgkhqtWqpmlSotvFiRNYW4PrQkqQm4eUOHVKOX3a1nWsrODzn+/fd18mnWZ4kZRS07RUKgUgk8nMzc2Vy+V2u+37frPZtG1bCKHrOnaRSqXsqSiKgiC4cOEC57zT6Rw4cAAkMTgIuQVNJpNer+d5XrfbdRxncXHRMAzsbjweh2HoeZ6iKEII27Y551KiXkethjNnEEWQEuTmJCWkRL2O978/e+QInnii88gjhmlyVcVoNNI0TVEUvIhzXigUhBD9fj8IgmeeecY0TSFELpdjjGEXuq7Pzs6WSqUwDC9evHjhwoXhcOg4TjabVRQFZE/jIOSWEsdxGIa+749GIyFEtVrVNA27G41G/lQ6nS6Xy5ZlMcakRL2OWg2uCymRHKoKXUcUQUrciqTEqVM4fdrSdaysYG0tOnRopGkarqIoijlVLpfDMGw2mxsbG47j2LadTqexi1Qqlc1my+Xy/v37O53OhQsXOOdCiHw+r6oqyB7FQcgtYjQahWHo+z5jrFgs5vP5VCqF3Q0GA38qn88vLCyYpglASnzve6jV4LqQEsmhqjhyZPLUU8ptt8lvfav38Y87UuIWJSWkRL2Ohx7S77wz9cd/fHlmJk6nGa5F07RSqVQsFnu9nu/7ly9fzufzQohsNssYw1WiKEqn0+ZUuVzudru+7zebzXw+7zhONptVFAVkb+Eg5KY3HA49zwvD0DTNarWay+UURcEuJpNJr9fzPK/X6zmOs7y8rOs6ACnhuqjV4LqQEsmhqjhyBE89hbvu2ul2/Y2Nrfe8J/tzP2f84Adp3OKkhOuqjz46t7qqPP54+5FHMpalqSquxhizpqIoCsPw4sWLqVRKCJHP51VVxRWiKNJ1HVOpVMqeGg6HQRBcuHBBVVXHcfL5vKqqIHsFByE3q8lk0u12fd/vdruO4ywuLhqGgd3FcdzpdFqt1mg0KhQK1WpV0zQAUsJ1UavBdSElkkNVceQInnoK99wTd7v+uXObuq7v37/fNM1vfhNHj+LSJewB47Fy6hROn87rOlZW8IUvDO+7L6OquCZd1yuVSqlU6nQ6vu83m03bth3HyWazmIqiyDRNvFxmqlQqdbvdIAiazaY9lc1mFUUBucVxEHLz2dnZabfbnueNx2MhRLVa1TQNuxuPx2EYtlotxlihUMjn85xzKdHt4sQJrK3BdSElkkNVsbqKJ5/EPffE/X547twm53zfvn2WZWFqbg7r63jgAUiJvUFKSIl6He97X2Z1FU880Tt+XDdNrqq4GmPMnhoOh0EQnD9/Pp1OCyFyuVwURcViEdfCOXemBoNBGIYXLlxQVdVxnHw+r6oqyC2Lg5CbyWg0CoLA933OeaFQyOfzqVQKu9ve3g6CwPO8TCYzOztrWZaiKFKiXkethjNnEEWQEokyN4f1dRw5MhkM2j/96SaASqWSz+cVRcEVVlexuop6HXuMlKjX4bqmrmNlBX/6p6P3vEdTVVxTZqpUKnU6Hd/3L168GIZhtVrFdRlTpVKp0+kEQdBsNm3bdhwnm82C3II4CLk5DIdDz/OCIMjlcvv27TNNU1EU7G4wGHieFwSBbdv79+83TROAlHBd1GpwXUiJpFFV3H33zv/8n6lcrnPhwuZ4PC6VSrZtM8ZwFVXF+jqOHsWlS9h7pISUqNfx3vdqq6v4/Of7992XSacZroVzLqZarVan0zl//rxpmkIIy7IYY9gF51xMDQaDMAx/+tOfappmT3HOQW4dHITcUJPJpNvtep7X7/cdx1laWspkMtjdZDLpdrue5/X7fSHE8vKyrusApITrolaD60JKJI2q4p574i9+kS0vD4Ngs92OZmZmhBCpVAq7m5tDvY6jR3HpEvYqKVGv4/3vzx45giee6Bw/nsnlVFXFNTHGqtXqvn37Op3O5ubmxsaG4zi2beu6jt0ZU6VSqdPpBEHQbDZt23YcJ5vN4kWTyURRFJCbEgchN8h4PO50Oq1WK45jIcS+fftUVcXu4jgOw9D3fSlloVCYm5vTNA2AlHBd1GpwXUiJpFFV3HNP/MUvsttvj4Jg89Kl3szMzMLCAuccr8HcHNbX8cADkBJ7mJQ4dQqnT1u6jpUVrK1F996rqypeIYoiXdc1TSsWi0KIXq8XBMHZs2ctyxJCmKbJGMMuOOdiajAYhGF4/vz5dDrtOE4+n+ecX7hwwTCMmZkZkJsPByHvuNFo5Pt+EASqqhaLRdu2GWPY3Xg89qcYY8ViMZ/Pp1IpKdHt4sQJrK3BdSElkkZVcc89ky9+UVlZGYXh1oULYbFYrFarmqbh9Vhdxeoq6nXseVJCStTreOghfXUVn/tc9/77s+k0w4uiKLJtG1OMMWtqe3s7DMNGo6EoihAin89rmobdGVOlUqnT6QRBsLGxYdt2EASFQgHkpsRByNssjmPGGKYGg4Hv+0EQ5HK5+fn5bDarKAp2F0WRP2UYRrVaNU2TMSYlvv991Go4cwZRBCmRNKqKI0cmTz2l3HGHDMOtc+c8IcTy8nI6ncbrp6pYX8fRo7h0CQkhJep1PPxw7sgRPP54+MgjhmVpnE+iKNJ1HS+XTqfL5fLMzEyn0/F9v9ls2rbtOE42m1UUBbvgnIupwWCwubm5sbGRyWRmZmYsy+Kcg9xMOAh5OzUaDQCVSqXX67VarcFgIIS47bbbdF3HdQ0Gg1arFYahbdsHDx7MZrMApMT3vodaDa4LKZFAqoojRyZPPaXceee40/HOnWtZlrW8vKzrOt6EuTmsr+OBByAlkkNKnDqF06dtXcfKCj7zmW6hsKNpGq6FMWZPRVEUBMGFCxc0TXMcJ5/Pc86xO8MwhBAHDx6cmZnxfb/RaNi2LYQwDAPk5sBByNuJc95sNnu9XhzHhUJhfn5eVVXsbjKZdLvdVqs1GAyEEMvLy7quA5ASrotaDa4LKZFAqoojR/DUU7jrrp1u1z93biubzS4uLhqGgbfC6ipWV1GvI2mkhJSo1/GBD1i3337oP/2n4SOPZEyTqyquSdf12dnZmZmZTqfj+36z2XQcx7ZtwzCwi8FgYJqmmBoMBkEQnDt3Lp1OCyEsy+Kcg9xQHIS8Pba3t4MguHjx4mAwuOuuuyzLYoxhdzs7O+122/O8nZ0dIcT8/LyqqgCkhOuiVoPrQkok1q/9Gh57bKIo4Q9/eFnX9X379juOibeOqmJ9HUeP4tIlJJOU+Nd/NX7rt6DrWFnBn/7p6D3v0VQV18Q5F1ODwcD3/eeee84wDCFELpdLpVJ4ucFgYNs2poypcrnc6XR83280Gs6UYRggNwgHIW+1wWDgeV4QBPl8/sCBA5ubm5ZlMcawCyllEAS+76dSqUKhYNs2YwyAlHBd1GpwXUiJhPvqV/G3f6tMJvZkkp+Z2XnwQdx7L/bvxwuOHcMn2neIAAAgAElEQVTP6DpUFW/Y3BzW1/HAA5ASiSUlpES9jve+V1tdxec/37/vvkw6zbALY6pcLrfb7c3NzUajIYSwbVvXdUzFcTwcDmdnZ3EFzrmYGgwGvu8/99xzuq4LISzL4pyDvLM4CHmLxHHc7XY9zxsMBkKI5eVlXdfH43Gj0djZ2WGM4SpRFPlT2Wy2Wq3mcjlFUaREv48TJ7C2BteFlCAvkBJSAlAApd9nTz+NL38Zuo6XHDuG/fvx7ndj/3684Ngx/IyuQ1XxGq2uYnUV9TqIlKjX8f73Z48cwe/+buf4cd2yNFXFNamqWiwWC4VCv9/3ff/s2bOWZQkhTNPc3t4GkE6ncS3GVKVS6XQ6vu9vbGzYtu04jmEYIO8UDkLetPF4HIah7/txHBcKhYWFBc45phhjnPPxeKyqKq7Q7/c9zwvD0HGcxcVFwzAASAnXRa2GM2cQRZAS5DqkhJR4ybe/jRc8/TR0HS85dgz79+Pd78b+/XjBsWP4GV2HquJqqor1dfzbf4tGA+QFUuLUKZw+bek6Vlawthbde6+uqrgmRVHMqUqlEoZho9EAkEqlVFVljGF3nHMxNRgMfN8HeWdxEPImbG9v+74fBEE6nS6VSpZlMcZwBcaYpmlSykwmA2AymXS73VarNRwOhRDLy8u6rgOQEq6LWg2uCylB3jApISVe8u1v4wVPPw1dx0uOHcP+/Xj3u6EoWFjAsWP4GV2HqmJuDl/72s6DD6akBPkZKSEl6nU89JC+uorf+73e8eOZbDalqrgmTdNKpVKxWOx2u2fPno2iSNd1IUQ2m1UUBbszpkDeWRyEvCH9ft/zvDAMbdteWFgwTRO7UFV1NBrt7Oy02+1WqxXHcaFQWFhY4JwDkBKui1oNrgspQd4OUkJKvOTb38YLnn4auo6XHDuG/fvx8Y/H1Wr7X/6lN5nsAxSQl5MS9Tpc19R1rKzgr/96dPCghl0wxvJT+/fv39nZuXDhgqqqjuPYts05B7lpcBDyesRx3Ol0fN8fDoeO4ywvL+u6jutSFKXZbG5tbamqOjMzk8/nGWMApITrolaD60JKkHeYlJASL/n2t/GCp59m6bQdRfZ4rIDsQkpIiXodf/zHo89+9nKp5GSzWUVRcJXxeBxFkW3bmqaVSqVOp+P7frPZtG1bCGEYBshNgIOQ12Y8Hodh6HkegEKhsLCwwDnHdUVR5Pv+pUuXFEVZWVnJ5XKKokiJfh8nTmBtDa4LKUFuHlJCSgXktfnudzNx3L9w4YKqqkKIfD7POccVoijSNE1VVQCpVMqZGgwGvu+fO3dO13UhhGVZqVQK5MbhIOTVRFHk+34QBJlMplwuW5bFGMN19Xo93/fDMBRCHDp0KAxDy7KkhOuiVsOZM4giSAlCbmmtVqpcLhtGsd1u+77fbDadqUwmg6nhcJjJZBRFwRWMqUqlEoZhq9Xa2NhwpnRdB7kROAjZXa/X830/DEPbtg8cOJDNZnFdcRx3Oh3f94fDYaFQOHz4cDqdjqJoY6P13e/Gv//7zHUhJQjZGyoVvCCVSompfr8fBMGzzz5rmqYQIpfLDQYDwzBwLZzzYrFYKBT6/b7v+2fPnrUsy3GcXC7HGAN5B3EQcpU4jjudjud529vbQojDhw+n02lc13g8brfbnufFcVwsFhcWFjjnAKSE66qPP37w//5fJiUI2UsefBC6jpdkp0qlUhiGzWZzY2Oj3W4fPnwYu1MUxZyqVCphGA6Hw3w+D/LO4iDkClLKMAw9z2OMCSFs2+ac47pGo1EQBJ7naZpWKpUsy2KMAZASrotaDa6bkjIDQvYWVcW73w1VxStomlYqlYrFoud5jUbj/PnzxWLRcZxsNovdaZpWKpXiOAZ5x3EQMhVFkT9lGMbs7Gwul2OM4bqGw6HneWEYmqY5Pz+fy+UwJSVcF7UaXBdSgpA9SdfxC78QAwzXwhjTNG1+fn5ubi4Mw/Pnz6fT6UKhYFlWKpXCLhhjIO84DpJ4vV7P87x2u+04zuLiomEYeDW9Xq/VanW7XcdxDh06lMlkAEiJKMKJE1hbg+tCShCyh8VxfP78eSFytm2rqoqrDIfDTCZjTJVKpXa7vbW1tbGxIYSwbVvXdZCbAwdJqjiO2+2253mj0UgIcfvtt2uahuuK47jT6Xiet729LYSoVquapgGQEq6LWg1nziCKICUI2fOKxZ1yedLtdi9fvmzbthDCMAxcYTAY2LaNKc55oVAQQvT7fd/3z549m8/nhRCmaSqKAnJDcZDkkVIGQeD7PmOsUCjk83nOOa5rPB6HYeh5HoBCoWDbNuccgJRwXdRqcF1ICUKSo9X6/371Vz/56KO/8qEPfQjAc889ZxhGoVCwLEtRlDiOh8NhtVrFFRRFMafK5XIQBBcvXkylUkII27Y55yA3CAdJkiiK/CnDMKrVqmmajDFc12g08qc0TSuXy5ZlMcYASAnXRa0G14WUICRROJ/8x/8422qt/tmf/dmf//mfHz9+/Nd//dfvvPPOjY2NZrNZKBQ0TVMURdM0XEs6na5UKjMzM51Ox/f9ZrMphLBt2zAMkHccB0mAyWTS6/U8z+t2u47jLC4uGoaBVzMYDHzfD4Igl8stLCyYpokpKeG6qNXgupAShCRQJqP83u/dsbT0l//yL//y13/911/72te+8pWv3H///R/96EcffPDBTqezubnJGNve3s5kMthFKpVypgaDge/7uq6D3AgcZE+L4zgMQ9/3R6OREKJarWqahlfT7XY9z+t2u47jLC0tZTIZAFIiinDiBNbW4LqQEoQknKIod0998pOf/MY3vvHlL3/5t3/7tw8fPvzoo4/ed999MzMzP/nJT7LZbKFQME2TMYZdGFMgNwgH2aNGo1EYhr7vM8aKxaJlWZxzXFccx51Op9VqjUYjIUS1WtU0DYCUcF3UajhzBlEEKUFIwlUqqFTwkmq1+sQTT/zmb/7miRMnvvSlLz311FPf+ta37r777kcfffRd73pXo9FgjAkhbNvmnIPcZDjInjMcDn3fD4LANM1qtZrL5RRFwXWNx+MwDFutFmOsUCjk83nOOQAp4bqo1eC6kBKEkJ+54w7oOl7BMIwPfvCDv/ALv/AP//APJ0+e/OY3v/kXf/EXDz744G/8xm888MADnU6n2WwKIRzHyWQyIDcNDrJXTCaTbrfr+36323UcZ3Fx0TAMvJrt7e0gCHzf13W9UqlYlsUYAyAlXBe1GlwXUoIQ8hJVxcMPQ1XxCnEcX7582fO8Bx988Fd+5Vc+9alPra+v/9Vf/dXHPvaxO++887HHHvvgBz8Yx/Gzzz6by+WEEKZpMsZAbjQOcuvb2dlpt9ue543HYyFEtVrVNA2vZjAY+FO2bS8sLJimiSkp4bqo1eC6kBKEkFfQdTz4IF4hiqJLly4BWFpa0nUdwMLCwqc+9anf+q3f+ru/+7svfelLn/3sZ7/4xS/+8i//8mOPPVYsFhuNBmNMCGHbNucc5MbhILey0WgUBIHv+5zzQqGQz+dTqRSuazKZdLtd3/d7vZ4QYnl5Wdd1AFIiinDiBNbW4LqQEoSQ18j3/UajUSgUyuUyYwxXyOVyv/qrv/qhD32oXq9/+ctf/sY3vvH000//4i/+4kc/+tFjx4612+1msymEqFarIDcIB7k1DQYD3/eDIMjlcvv27TNNU1EUXFccx+122/O80WhULBar1aqmaQCkhOuiVsOZM4giSAlCyHVUKqhU8DPj8bjZbHY6nfn5+Xw+j12kUql7p/7gD/7ga1/72le+8pXHHntsdXX1Ix/5yC/90i85jgNy43CQW8pkMul2u57n9ft9x3GWlpYymQxezXg8DoLA8zzGWLFYzOfzqVQKgJRwXdRqcF1ICULIa3HHHdB1vKDf71+6dEnTtKWlJU3T8BocOnToD//wDz/xiU9861vf+tKXvvRHf/RH//2///e///u/P3z4MMgNwkFuEePxuNPptFqtOI6FEHNzc5qm4dVsb2/7U5lMZnZ2NpfLMcYASAnXRa0G14WUIIS8RqqKT38aqoqtra2NjY1KpTIzM6MoCl4P27Y/8pGP/Nqv/do//dM//eVf/uXhw4dBbhwOctMbjUa+7wdBoKpqsVi0bZsxhlczGAw8zwuCwLbtAwcOZLNZTEkJ10WtBteFlCCEvHacT44d699xh/bTn25EUbS4uGiaJt4ozvn/MwVyQ3GQm9hgMPCnLMuan5/PZrOKouC6JpNJt9v1PK/f7wshlpeXdV3HlJRwXdRqcF1ICULI6zI3h7W1n9x5p3zmmW0hxKFDhzjnILc+DnLzieO41+u1Wq3BYOA4zvLysq7reDVxHIdh6HneeDwuFAr79u1TVRWAlIginDiBtTW4LqQEIeT1qlYn3/nOZDLRLlxoqqoqpez1epZlMcZAbnEc5Ebr9XqDwaBUKgEYj8ftdtvzvDiOhRDz8/OqquLVSCmDIPB9P5VKFQqFfD6fSqUASAnXRa2GM2cQRZAShJDXS1Vx113jr351R8pLcRz//M//vKqqYRhevnx5c3NTCGHbNucc5JbFQW40xlir1crlcu122/d9TdNKpZJlWYwxvJooivwpwzCq1Woul1MUBYCUcF3UanBdSAmytykKJhOQt0O1ir/5Gxw82N3aajiOU6lUGGMAisWiEKLT6bRarc3NTTGlaRrILYiD3Gg7OzutVmswGMzMzCwsLJimideg3+97nheGoW3bi4uLhmFgSkq4Lmo1uC6kBNnbVBWrq/jYx/C5z+HSJZC3VrU6+ed/3uH8cqvVnpubs20bV2CM2VO9Xq/Vav34xz92HEcIYRgGyC2Fg9wgcRx3u13P8waDQSaTmZubm52dxauJ47jX67VareFw6DjO8vKyruuYkhKui1oNrgspQfY2VcXqKj79aRw/DlXFBz+ID38YrgspQd48VcWdd47/x/+Q29vPx7F66NChdDqNXZhTw+HQ87znnnvONM1CoWCapqIoILcCDvKOG4/HYRj6vh/HcaFQWFhY8DxvNBrhunZ2dtrtdqvViuNYCLGwsMA5ByAloggnTmBtDa4LKUH2vLk5rK9jdRWqip+Zm8PJk3Bd1GpwXUgJ8oZVq/ibv8HCQri11ahUKjMzM4qi4NVkMpl9+/aVSqUgCJ5//nlN0wqFQj6fZ4yB3Nw4yDsoiqJgKp1Ol0oly7IYYwAMwwiCYDKZKIqCq4xGozAMPc9TVbVYLNq2zRgDICVcF7UazpxBFEFKkD1PVbG6ivV1zM3hFVQVR4/i5Em4Lmo1uC6kBHldVBV3373zta/FjG2024PFxUXTNPF6aJpWLpcLhUK73d7a2ppMJkIIkJsbB3lH9Pt9z/PCMLRte2FhwTRNXCGTyYxGIymlpmm4QhRF/lQ2m52bm8vlcoqiAJASrotaDa4LKUGSQFWxuoonn8TqKlQVu1FVHD2KkyfhuqjV4LqQEuS1mJvD+jpuu22wuXnJMIylpSXOOd4QznmhUHAcZzKZgNz0OMjbKY7jTqfj+/5wOHQcZ3l5Wdd1XIVzbhjGYDDQNA1TvV7P9/0wDB3HWVxcNAwDU1LCdVGrwXUhJUgSqCpWV/Hkk1hdharitVBVHD2KkyfhuqjV4LqQEuQ6qtXJd74z0bStS5c2Z2dni8Ui3jTGGK7QbDaz2azneQcOHAC5mXCQt8d4PA7D0PM8AIVCYWFhgXOO3RmGMRgMLMvqdrue5w2HQyHE4cOH0+k0pqSE66JWg+tCSpCEmJvD+jpWV6GqeL1UFUeP4uRJuC4+/GFcugRyNVXFXXftfPWrYykvbW/Hhw4dMgwDb4OdnZ1z58612+2NjY0777zTNE2QmwMHeatFUeT7fhAEmUymXC5blsUYw6vRdf38+fO9Xi+O42KxuLCwwDnHlJRwXdRqcF1ICZIQqorVVayvY24Ob4aq4uhRfOc78SOPjM6c0aUEecncHNbXsbjY3dpq2LZdLpdTqRTeHnNTZ86c2b9/fzabBblpcJC3Tq/X830/DEPbtg8cOJDNZvEaSCl93798+bLv+/Pz84VCgTGGF0mJD30I3/42pARJCFXF6iqefBKrq1BVvHm9Xm80uvxXfxU3m9U/+qOs60JKJJyq4p574q9/fcL55a2tsFqt2raNt9/KygrITYaDvGlxHHc6Hc/ztre3hRCHDx9Op9N4DaIo8jwvCALTNA8cOKBpmq7rjDG8XKsFKUESYm4O6+tYXYWq4s2TUm5tbXmeVy6XDx4srqywkyfhuqjV4LqQEsk0N4f1ddx+e7S11RiP2eLioq7rIEnFQd4EKWUYhp7nMcYKhUI+n+ec4zXo9Xqe57XbbSHE4uKiYRgA2u12v9/P5XK4gqri05/Go49CSpC9TVWxuor1dczN4S3h+36z2TQM47bbbtN1HVOqiqNHcfIkXBe1GlwXUiJRqlXU69B178KFxszMTKlUYoyBJBgHeaMajYbv+4ZhzM7O5nI5xhheTRzHnU7H87zt7W0hxO23365pGl6UzWbDMMRVbrttW9fTUoLsVaqK1VU8+SRWV6GqePMGg0Gz2RyNRtVq1bZtXEVVcfQoTp6E66JWg+tCSux5qoq77975+tcnOzuNra3B/v37LcsCSTwO8kaZpmnbtmEYeA3G43EYhr7vTyaTQqFg2zbnHC9nGEaj0djZ2UmlUpgaDAatVqvb7cTxCsBA9hxVxeoqnnwSq6tQVbx54/G41Wptbm6WSqWFhQXOOXanqjh6FCdPwnXx4Q/j0iXsYXNzWF/H8vLw8uWLhmEcOnRIVVUQAnCQN8qyLLwGo9HIn9I0rVQqWZbFGMO1aJrGGNve3jYMo9PpeJ7X7/eFEHfcsfTe907+9m9B9pi5OayvY3UVqoq3RBiGzWZT07SlpSXDMPDaqCqOHkW9jg9/GK4LKbH3VKuT734Xmrb1/PPNarVaLBZByIs4yHUNh8NMJoM3ZDgcep4XBEEul1tYWDBNE9fFGMtkMs1mM47j0WhULBb37dunqiqA48fxv/83pATZM1QV6+s4ehRviSiKLl++3O/3K5WK4ziKouB1mpvDyZNwXdRqcF1Iib1BVXHXXTtf/3os5cXBQC4tLRmGAUKuwEF2cfHiRQCWZWUyGbxOvV6v1Wp1u13HcZaWljKZDF7NeDxut9utViuKone96122bXPO8aIHH4SuQ0oknKpC13F9UQQpcUtotSAl/v/24Da2jfy+E/iXw/8Mh6MhORzxcYakJZKWd727Xol3WblOHATNpUDyJrhyk+aSQxCkfdUCORQFLmhRFAUuwCHtmxropS2SoNcgi0uQUE3vNtkiyTYtnLWXQaPzZh+zlmRb5AzJ4YMoSqJIDjW8PRcNkma9lm3ZJsXf58PzuBeO4zQaDcuygsHgyZMneZ7H3eJ5LC/j4kWsriKfh2Fg0uk6CgWk0zv1uun3+5PJJGMMhPwiBvJLBoPBzs7O5uamKIo+nw+H5jhOp9NpNBqDwUBVVU3TBEHA7di2vbW11Ww2eZ7Xdb3dbquqynEcph5jI49n5HJxLhdiMbzvfVhYgKLgLaqKxx6DpuFfmCZefRWtFt7SbuPNN/GP/4hqFf9ifx/DIcaNbeM//kfkcrhwAbkceB53odPpVKtVjuPm5uZkWcZR4HmcPo3//J/x+c9jcvE8FhedQgFud7VWa+m6HgwGQcjbYSC/pNvtNhoNxlgoFGKM4RCGw2G73W42my6XS1VVRVEYY7idfr/fbDa3trYkSdJ13efzOY7TarUGg4Eoivg5sRhiMezs4NjjeXg8o7e8+929c+e2Mhn25JP+uTkvAFEEz+NtnTqFU6fwM7aNXg9vqVaxtnbw6qs7X/+67/XXXf2+azh0YWzYNopFnD+PXA6FAnQdhzcYDGq12vb2diwWU1WV4zgcEcNAPo/VVUwuXUehgEcf7VuWwXFcNpsVRRGE3AID+SWiKAZuisViuJ3BYNC6yePxRKNRv9/PcRxup9vttm5SFGV+fl6SJNzkdrslSep2u6Io4ud4PKPHHnNdvYpjjOdx5szw93+fSyTaHGcpihiPh2RZxp3jefA83uLz4eRJ9wc/qPzmb+5ev14tFn1f+ILv2jVvv++ybYwJ20axiOVlFArI5cDzeGeO47RarVqt5vf7FxYWBEHAEbFtrK4in4dhYHJpGopFeL2tzU0zFApFIhGO40DIrTGQXyKKYiwWw+F0Op1+v59KpWRZxiHs7u42Go3d3d1gMLiwsCCKIn6RJEndbldVVdzkOE6n02k0Gr/6q+Kzz+rDoQvHC89DFLGwMPzzP+fm5rbb7TrP8+Gw5vf7cXSCQTkQSMfj1lNPrQcC0ZdeCv/3/+689JLbtjEmDAPnzyOXw4ULyOXA83hbu7u71WrVcZxkMun3+3F0DAP5PFZXYduYUDyPJ588+OY3R45TqdV2U6mU3+8HIbfDQO6NoiihUAi34zjOzs5Oo9Ho9/uqqmqaJggC3o4kSZVKZXRTu91uNBqj0SgYDCrKuiDEh0M3jgueRy6Hz34W73//qNfbabfrnQ5isVggEHC5XDhqHMfFYjG/32+a5hNPbH/3u/E335Q/85nR//2/LtvGOLBtFIs4fx65HAoF6Dp+3nA4tCyr2WxGo9FQKMRxHI6IbWN1Ffk8DAOTS9dRKGBhYb9eNwVByGQygiCAkENgIPeGMYZ35DhOu91uNBqO44RCIUVRGGO4Na/Xu7+/X61Wt7e33W63oij//M///OUvf/m55y7u728AMiYfzyOXw4ULyOWwv9+xLOvg4CAcDgeDQZfLhftJkqRMJlOv18vla8nk7D/+Y+QnP2H5PAwDY8K2USxieRmFAnI58Dze0mq1qtWqJEknT54URRFHxzCQz2N1FbaNyaVpoxdfhCDUS6VqPB4Ph8Mg5NAYyO2Uy+VoNMrzPO7QcDhs3eR2u0OhkKIoHMfhHdm23Wq1ms0mx3HRaPSHP/zhl770peeffz6dTv/BH/ze//pf5muvLWCS8TxyOVy4gFwO/f7u5mZtMBiEw2FVVTmOwwPhcrkikYjf769UKjdurD36qFYs+p96amSaLowNw8D588jl8PnP9zStenDQ0zRNURQcHdvG6iryeRgGJhfP48knD77xDWc4NLrdQSaTmZmZASF3goHcWqPRcByn1WpJkqSqKg5tMBi0Wq1ms+n1ejVN8/l8LpcL72gwGDRvmpmZCYVCly5d+trXvnbx4sUnnnjiT//0Tz/2sY9F/z/8zu/AtjGhdB2FAnI5DAZ7hlHf29sLh8OqqjLG8MCJojg/P99qtUqlUiAQeOaZ2V/7Na9tY3zYNopFfOAD4mOPxb/1LbeiMBwR28bqKv7Lf8HqKmwbk0vXUSggm92r1cp+vz+ZTLrdbhByhxjILQyHw5/+9Kcul4sx5vF4hsMhYwy3s7+/32w2t7a2/H7/iRMnZFnG7fR6vUajsbW1FQgEFEX5zne+88wzz9Tr9dnZ2b/8y7/M5/OqquKm970PogjbxiTStFGx6FLV/Uql3ul0QqGQrus8z+OhUlVVFMU333zzpZdKo9FZwIUxY9u4csVz7hxWVpDLgedxjwwD+TxWV2HbmFw8j8VFp1AAY7VKpalpmqqqIOSuMJBb6HQ6Pp8vFAr1er2ZmRnczu7ubqvVarfbqqpms1mv14vb6Xa7jUaj3W6rqurz+VZWVv76r//61Vdffe973/u7v/u7i4uLp06d8vv9mHA8j8cfH3zzm6PRqH71amt2dnZhYUEQBDxso9Foa2vLsqz9/eB/+2+PDIcujCvTxPnzyOVw4QJyOfA87oJtY3UV+TwMAxNN11Eo4PTpgWUZgwGy2awoiiDkbjGQW/D7/adOnfJ4PDgE0zS3trZmZ2cfeeQRQRBwO7u7u41GY3d3V1VVr9f7la985W/+5m+uXbv2gQ984I//+I8/+MEPiqLYarWuX7+uaVooFMJNsRhiMezsYILEYs43vnGQTDa2txuqqi4sLIiiiDGwu7tbrVb7fada1T/xCW+zyTDebBvFIs6fRy6HQgG6jjtiGMjnsboK28ZE0zQUi/B6WzdumLOzs9FolOM4EHIPGMgtsJtwOKqqRiIRxhje0Wg02tnZaTQavV5PVdVut/uFL3zhq1/9qmVZH/rQhy5cuPD+97+f53ncpKqqIAjlcrnX62maxnGcKOLxx3H1KiZFJDJ87rkWYxbgy2azkiRhDPR6PcuydnZ2hsPoJz8pv/66aNuYFLaNYhHLyygUkMuB53Fbto3VVeTzMAxMNJ7Hk0863/ymMxpVq9VOKpXy+/0g5J4xkKMgiiLekeM4nU6n0WjYtj07O7u9vf35z3/+61//+t7e3oc//OHf+q3fes973sNxHH6RLMvpdLpcLl+/fj2RSAiC8NnP4tlnYdsYf9Ho8Gtf2wgE+HB4TpZljIHhcFi/ye+f3dpa+OhH3ZUKhwlkGDh/HrkcLlxALgeex60YBvJ5rK7CtjHRdB2FAk6d2rcsQxCEbDYrCAIIOQoM5NC63a4kSbhDjuO02+1GozEajWZnZ9fW1v7sz/6sUCgAePrppz/96U+/613vcrlcuAVBEObm5kzT3NjYSCaTudxMLodiEePvd35nK5eL+f1+jAHHcVqtlmVZgiBtbS186lPcK6/wto3JZdsoFnH+PHI5XLiAXA48j59n21hdRT4Pw8Ck07RRsegShPrmZiUWi4XDYZfLBUKOCAM5BMMw3G63KIqSJOHQhsNhu91uNBput3t2dvbll1/+3Oc+93d/93eyLH/yk5/81Kc+debMGRwCx3GJRKJer29sbCQSiUIh+O/+3bBWYxhv/+N/BH/t11guB57Hw9XpdGq1mm2jWj3xe7/HXn3VY9s4HmwbxSLOn0cuh0IBuo5/YRjI57G6CtvGRGNs9Nhj/W99y23bxt7eIJ1Oy7IMQo4UA3lHtm1vbW2Vy+X9/f1IJDIzM8PzPG7Htu1Wq9VsNj0eT7rE+lgAACAASURBVDgc/tGPfvTlL3/5O9/5TiQS+cxnPvPJT35yYWEBdygcDguCsLm5yfO1r33N/YlPnDRNjLNajZ0/j1wOFy4glwPP48HrdruWZXU6+9Vq/L/+V/G110TbxvFj2ygWsbyMQgGnT+O115DPwzAw6XQdn//8+tLSqNPZDwaD6XSaMQZCjhoDeUd7e3umaY5Go0Qi4ff7eZ7HO+r3+61Wq9lsyrIciUQuXrz4xS9+8fvf/346nf7DP/zDT3ziEydOnMBdGQ6Hg8HAcRzLsiKR0Asv2O9+NzNNF8aYbaNYxPnzyOVw4QJyOfA8HozBYFCpNEyz9frr+oUL0ddf99o2jjfDwPnzEEX0erBtTDSex+KiUyhgNBKuXbsmCEI4HHYcB4TcBwzkHSmKcvr06VqtlkwmcTvlcrnVaimKEg6Hv//973/pS1+6ePHi448//id/8icf+9jHYrEY7spwOGy1Wo1Gw+PxzM/Pi6JomuZweOPixeR73iNUKi6MN9tGsYjz55HL4bOfxX/4DxBF8Dzuk37fMc3W//k/3f/5P2Nvvhnr97nhEFPCtmHbmHS6jkIBp08P6nXTcZynnnpqNBpZlnX16tVwOKyqKmMMhBwdhqn34x//OJFIRKNR3IIgCMlkEoegKArHcd/+9re//OUv/+hHP3rqqaf+4i/+Ip/Pq6qKuzIcDlutVqPREEUxkUj4/X7clEqlarXa1tb6D36Q/PjHvS+/zGwbY862USziN34DoojTp/Gbv4n3vQ9vicUgiuB53DXbRq+HahVvee657jPPSK+9NtvrzQ6HLpBJo2koFiFJWzduGKqqxmIxjuMAzM3N7e7uWpbVbDbD4bCqqhzHgZCjwDDd6vX6888//653vatSqSwuLuLevPnmm5/+9Kdffvnl9773vV/5ylc+/OEP+3w+3BXbtlutVrPZFEUxmUz6fD78HI7j4vG4x+Mpl689+6y2uRnK52EYGH+2DdtGsYjVVYgi3hKL4fHHce4cFAVvUVW8JZnEzzzyCN7yxhv4mVIJb2m18JZ2G5cu4ZVXUK3iLb2eZNsAXCCThuexuOh84xvOaFStVDqJREJRFPwc+aZOp2NZVrPZjEQigUCA4zgQcm8Yplu/3z9z5oyiKPF4HPcsd9Mf/dEffehDHxJFEXdlMBhsbW01Gg1JklKplCzLuAVVVQVBKJVKyeTg8uXY2bMu03RhQtg2bBtv2dnB1at49lmIIu5CrwfbBpl0uo5CAY880qvVyjzPZzIZj8eDt+P3+2VZ3t7etiyr2WxGIhG/3w9C7gHDdEskEoyxWCyGw7EsS1EUQRBwC3/1V3/F8zzuymAwaLVajUZDluUTJ07IsozbkWU5nU6Xy2WOu/HCC4l3v5uZpgsTyLZh2yDTSdNQLMLjaWxuVqLRaDgcdrlcuDWO44LBYCAQaLVahmE0Go1IJCLLMgi5KwxTLxaL4RBqtRqAn/70p7Isnz59WhRFvB2e53HnBoNB8yZZlufn52dmZnBoHo9nbm6uUqns7W380z+lPvYx4Sc/cds2CBl/PI8nnzz4xjecg4NKo9Gdn5+XZRmHw3FcKBRSFKXVat24cWNmZiYSiUiSBELuEAM5hF6vV6/Xt7a2Zmdnw+GwKIo4IoPBoNFotFotn8+XTqclScKdc7vdiUTC+v/Wn3susbGh5PMwDBAyznQdhQKy2b163ZQkKZvNMsZwhxhjkUhEUZRms7m+vq4oSjQaFQQBhBwaAzkEURQXFhaq1WoqlcIR6ff7zZsCgUA6nZYkCfcmEokIglAul+fm+sVi9KmnYJogZAzxPBYXnUIBPG+ZZl3TtNnZWdwDQRDi8biqqu12WxAEEHInGMjhCIKQSqVwFHq9XvMmRVEymYwkSTgiiqJ4PJ5SqSSK/UuXtHPn3KbpAiHjRNdRKOD06UG9bvb7TiaTkSQJR8Hj8USjURByhxjIA9Tr9RqNRqvVCgaDJ0+e9Hq9OGper3d+ft4wjOHw+sWLyfPnBdN0gZDxoOsoFjEz0y6VTEVRotGo2+3GfVOv12VZrtfrqVQKhNwCA3kger1eo9FotVqqqi4sLIiiiPuG5/lUKlWtVtvt9X/4h9THPy6+/DKzbRDyEPE8Fhedb35z5HLVTLOtaZqiKLifer3eYDC4dOmSKIocxymKIssyCPklDOSBEEURwMLCgiiKuP84jtM0zePxGMbGs89qm5uhfB6GAUIeCl1HoYBHHunV6+ZwyKXTaVEUcZ+Joqjr+t7eniRJoijKsgxC3g4DeVASiQQerNnZWY/Hs7m5mUwOLl+OnT3LmSYIeZB4HktLo5UVlyg2NzfNSCQSDoc5jsODsrCwAELeEQM51mRZTqfThmG43ZsvvKD/yq9w1aobhDwQuo5CAWfOHNTrZr3enZub8/l8IGTMMJAj1ev1RFHEOBFFcW5uzjTNnZ2rf/u3vt/+7egrrwi2DULuK11HsYhAYPfGjbIkSZlMhud5EDJ+GMgRaTabV69ezWQyjuNIkoRxMhqNPB5PqVTq9ap/+7fualXL52EYIOR+4HksLo5WVsDz9Y2NqqZpoVAIhIwrBnLPer1e9Sa/399ut8PhMMaG4zitVqvRaPA8/8QTTxwcHJTL5fl59uKL4bNnXYYBQo6WrqNQwGOPDep1s9u1s9msJEkgZIwxkHsmimI0GpUkKRKJYGw4jrO9vV2v110uVzweDwQCuEkQhFKpJEn9S5e0X/kVzjRdIOSI6DqKRcjy9uamEQgEkskkYwyEjDcGchS8N2FsbG9vW5blOE44HFYUheM4/CtJkubn5w3DODi49sMfpt7zHt40XSDk3vA8FhedQgEuV7VUaum6HgwGQcgkYCDHy87OTr1eHwwGoVBIVVWO4/BLBEE4ceJEtVrd3l7/wQ9SH/+45yc/YbYNQu6OrqNQwKOP9i3L4Dgum82KoghCJgQDOS729vbq9Xq32w2FQqqqMsZwaxzHaZomCIJprn/724nr19V8HoYBQu4Iz2NpabSy4vJ6W5ubZigUikQiHMeBkMnBQCZft9ttNBqdTicUCiUSCcYYDicUCgmCUC6Xk8ne5cuxs2c50wQhh6TrKBRw5sxBo1GxrL1UKuX3+zEGrl27BmB+fh6EHAIDmWS9Xq/RaLRarVAotLCwIAgC7pDf70+n0+VymbHNS5cS5865TdMFQm5H11EsIhDY3dw0RFFMp9OCIGAMvPHGG4yxb33rW+duAiG3w0Am02AwaNykqurCwoIoirhboijOzc2ZptnrbfzTPyX/038SXnrJbdsg5G3xPBYXRysr4Pn6xkY1Ho+Hw2GMjUceeeTll19+4okn5ufnQcghMJBJMxwOGzf5/f5sNitJEu4ZYyyZTFqWVa+vP/dccn09kM/DMEDIv6HrKBTw+ON2vW52u4NMJjMzM4Mx88RNIORwGMjkGA6HrVar0WhIkjQ/Pz8zM4Oj43K5otGox+Mpl0vz8/1iMbK8DMMAIT+j6ygWIcvbN24Yfr8/kUgwxkDIhGMgk8BxnFar1Wg0BEFIJpM+nw/3h6IoPM+XSiVZHly+rJ096zJNF8jU43ksLjqFAjiuVio1NU1TVRWEHAsMZLw5jtNut+v1utvtjsfjgUAA99nMzEw6nS6Xy8D1F15IfuQj3EsvuW0bZGrpOgoFnD49sCxjMEA2mxVFEYQcFwxkvHEc1+/3I5FIIBDgOA4PhCAIc3NzlUplZ2f9u99NvPmmnM/DMECmDc9jaWm0suLyels3bpizs7PRaJTjOBByjDCQsReNRjmOw4PFcZyu641Go1TaOHkyUSyqy8swDJDpoesoFHDmzEGzWa1WO6lUyu/3g5Bjh4GMPY7j8JCEQiFBEMrlsqoOXnwxurwM03SBTAFdR7EIRdkrlQxBELLZrCAIIOQ4YiDkHfn9/nQ6XSqVBKH/wgva8jIsiwc5vngei4ujlRUIQmN9vRKLxcLhsMvlAiHHFAMZA3t7ewcHB36/H2NJFMX5+fm1tTXLuvzMM+Hf//2Fl15y2zbI8aPrKBTw+ON2o1HZ2uqn02lZlkHIscZAHqpKpbK1tbW7u+v1eufn52VZxvjp9XqWZQ2Hw1AodHAw/Pu/31tb8+fzMAyQ40TXUSzC5+tsbhqyLKfTacYYCDnuGMjDs7+/z/O8ZVmapi0sLGD8DIfDRqNRr9eDweDCwoIgCK1WyzBupNOxYjG8vAzDADkGeB6Li06hALfb2txsaJqmqioImQ4M5OHxer1ut/vcuXOCIGDMOI7TbrdrtZooiplMRpIk3KSqqiAI5XJZlvuXL2tnz7pM0wUyyXQdhQJOnx7U62a/72QyGa/XC0KmBgN5qARBwPjpdDqWZTmOE4/HFUXBL5JlOZ1Ol8tl4PoLLyQ/8hHupZfctg0ycXgeS0ujlRWXJG3duGHMzs5Go1GO40DINGEg5Ofs7+9blrW3txeJRFRV5TgOb0cQhLm5OdM0d3fXv/vdxJtvyvk8DANkgug6CgWcOXPQbFYrlU4ikVAUBYRMHwZCbrJtu9Fo1Ov1UCiUzWYFQcA74jgukUjU6/Vy+drJk3qxqC4vwzBAJoKuo1hEMNgtlcqCIGSzWUEQQMhUYiBTz3GcVqtlWZYkSSdPnvR6vTi0cDjs8XhKpdLs7ODFF6PLyy7TBBlnPI+lpdHKisvjaaytmbFYLBwOu1wuEDKtGMh0297ertVqHMclEgm/34875/f70+l0qVQSxcGlS9q5c27TdIGMpUhk+L//N3viiWGjUWk0uul0WpZlEDLdGMi06na7tVptf38/Go0Gg0GO43C3vF5vOp02DGMwuHbxYuo3foO99JLbtkHGiq7jq1/dCAScjY2h3+/PZrOMMRAy9RjI9BkMBpZltVqtSCSSTCYZY7hnjLFUKlWr1Vqt9b//+8Tamj+fh2GAjAOex+KiUyjA5ZLW1tZEUYzH44wxEEIABjJNDg4Oms2mZVl+v39hYUEURRwdl8sVi8UEQSiXr2cyWrEYWl6GYYA8XLqOQgGnTw/qddNxnKeeemo4HJqmubOzE4vFRFEEIdONgUyH0Wi0vb1drVZ5np+bm5NlGfeHqqqCIJTLZZ+vf/ly/OxZl2m6QB4GnsfS0mhlxTUz097cNILBYDQadbvdACRJsizr6tWrsVhsdnaW4zgQMq0YyBTY3d21LGswGEQikWAw6HK5cD/JspxOp8vlMnD9hReSH/mI+6WXONsGeZB0HYUCnnzSabVqptnWdV1RFPwrxpimaX6/v1KpdDqdeDwuSRIImUoM5FgbDoeVSmV7ezsSiaiqyhjDAyEIwtzcnGmau7vr3/te8qc/ncnnYRggD4auo1hEMNgtl02O49LptCiK+CWyLGcymXq9vra2FrmJ4zgQMmUYyLHGGJMkKRqNCoKAB4vjuEQiYVlWuXzt1KlEsagsL8MwQO4rnsfS0mhlxeXxNNbXK5FIJBwOcxyHW+A4LhqN+ny+arW6tramaZosyyBkmjCQ4252dhYPTyQS8Xg8pVIpHO6/+GJkedllmiD3ia6jUMCZMwf1utlodOfm5nw+Hw5BkqS5ublWq3X9+nVVVSORCGMMhEwHBkLus0AgwPN8uVwWxf6lS9q5c27TdIEcKZ7H0hJWVhAI7N64UZYkKZPJ8DyPQ+M4LhQKybJcrVbX1tbi8XggEAAhU4CBkPtPkqR0Ol0ul4fD6xcvJj/84eEbb0jDoQvkKOg6CgUsLjrb241r12rxeDwUCuGuiKI4NzfXarUMw+h0OtFoVBAEEHKsMZDJNxgMDg4OvF4vxhhjLJVKVavVUunKF7/ILEv/7d+OGQbIPdJ1FIsIhfqmaQ6Hw0wmI0kS7o2qqrIsV6vVtbW1WCymqioIOb4YyCTb2tryeDyrq6uPP/642+0WBAFjbP8mxthwODx3jhWLWF6GYYDcHZ7H0hJWVjAz015fNwOBQCqVcrvdOAqCIKRSqXa7HQgEQMixxkAmlm3b9Xrdsqx0Ot1utxVFwbgaDoeWZTWbzUgkMj8/3+12S6VSIDC4fDl29qzLNF0gd0jXUShgcdFpNquGsaVpWjAYxFFTFAWEHHcMZGLxPH/ixAlVVUOhEMbY1tZWtVr1er0nT54URRGALMvpdLpUKrndN154IfHRj7qvXOFsG+SQdB3FIoLBbqlkchyXyWREUcSDMhwOGWMg5LhgIJPMcxPG1f7+frVa7ff78XhcURT8HI/HMz8/b5pmt7vxve8l33hDyudhGCDvjOextDRaWXF5va2NDTMUCkUiEY7j8EAMBoNer3ft2rUTJ04oigJCjgUGQu6Dg4ODer1uWVY4HE4mk4wx/BK3251MJi3LKpU2Tp1KFIvK8jIMA+RWdB2FAs6cOWg0Kpa1l0ql/H4/HqBut9vpdHZ2dizLmpmZcblcjDEQMuEYCDlq29vb1WqV5/lsNitJEt5RJBIRBKFcLkcig2IxsrwMwwD5N3geuRwKBQQCu5ubhiiK6XRaEAQ8WMpNjDFFUXZ2dlRVBSGTj4GMtzfeeGMwGJw5cwaToNfrWZa1u7sbi8WCwaDL5cIhKIoiCEK5XPZ6+5cuaU8/7bpyhbNtkH+h6ygUsLQ0arfrGxtVTdNCoRAeHk3TAEiSBEKOBQYyriqVymuvvXb16tVf//Vfx9hzHKfRaFiWpSjKyZMneZ7HnZAkaX5+3jCM4fDa888nXntNzOdhGCC6jmIR4fDANM3BYJDJZGZmZkAIOToMZFzF43FJkobD4dbWViQSwRjb2dmpVqsul2tubk6WZdwVnudTqVS1Wi2VNk6fThaLvuVlGAamFs9jaQkrK5Dl7bU1w+/3JxIJxhgIIUeKgYyxQCCwvLysKArG1WAwsCyr3W7HYjFVVTmOwz3gOE7TNEEQrl27put6sTi7vAzDwBTSdRQKWFx0Wq1aqdTUNE1VVRBC7gMGMt4URcFYGo1GzWbTsixZlk+ePOnxeHBEQqGQx+MplUqK0r98OXb2LGeamCq6jmIRs7O9ctkAkM1mRVEEIeT+YCDkzu3t7VWr1YODg0Qi4ff7cdR8Pl86nS6Xy4xtvvCC/tGPuq9c4Wwbxx7PY2lptLLi8npba2tmKBSKRCIcx4EQct8wEHInhsOhZVmNRiMajYbDYY7jcH+Iojg3N2eaZq937XvfS7zxhpTPwzBwjOk6CgWcOXPQbFar1U4qlfL7/SCE3GcMhBza1tZWtVr1er0LCwuiKOI+Y4ylUqlarVYqbZw6lSgWleVlGAaOH55HLodCAYHAbqlkCoKQzWYFQQAh5P5jIOQQ9vf3q9Vqv9+Px+OKouABikajHo+nXC5HIoNiMbK8DMPAcaLrKBSwtDTa3m5sbFRisVg4HHa5XCCEPBAMhByCZVmiKCaTScYYHjhFUQRB2NzclOXBpUvxp5/mrlxx2TaOAV1HsYhweGCa5mAwSKfTsiyDEPIAMRByCLFYzOPx4OGRJCmdThuG4TjX/+EfEq++6snnYRiYXDyPpSWsrMDn66yvGz6fL5FIMMZACHmwGAg5BI/Hg4dNEIQTJ05Uq9VSaeOxx5LFory8DMPAJNJ1FApYXHS2tqzNzYamaaqqghDyMDAQMjk4jtM0TRCEjY2NRCJRLKrLyzAMTBZdR7GI2dmeYZiO42QyGa/XC0LIQ8JAyKQJhUKCIJTL5WCwf/ly9N//+wPL4jEJeB5LS6OVFZckba2tGaqqxmIxjuNACHl4GAi5aTgcMsYwIfx+fzqdvn79+u6u8cwzM3/wB6euXOFsG+NM11Eo4MyZg2azWql0EomEoigghDxsDGTqdTqdvb29drut67okSYwxTIJ+v39wcOA4jqaNvv/9/uuve/N5GAbGEM8jl0OhgGCwWyqVBUHIZrOCIIAQMgYYyBQbDocA1tfXd3d3k8lkt9v1+/0Ye8PhsFqtbm9vx+NxRVEsyyqVNh55JFEsBpaXYRgYK7qOQgG5HLa3G2trZiwWC4fDLpcLhJDxwECmGGMMwKlTp3Z3dyORCCbB9vZ2pVLxer0nT54UBAFALBbzeDybm5uxWKxYDC8vwzAwJnQdxSLC4UGlUu12u+l0WpZlEELGCQOZetJNGHu2bddqtU6nE4/Hg8Egfk4wGBQEoVQqyXL/8mUtn3ddueKybTxEPI+lJayswOfrbGyYkiRls1nGGAghY4aBkEnQbrer1aokSdlsVhAE/JKZmZl0Ol0ul4HrP/hB4pVXhHwehoGHQtdRKGBx0dnasm7cqGuaNjs7C0LIWGIgZLzZtl2r1TqdTiwWU1UVtyYIwtzcnGmapdLGY48likV5eRmGgQdM11EsYna2Zxim4ziZTEaSJBBCxhUDIWOs3W5XKpWZmZlsNisIAm6H47hEItFoNDY2NhKJRLGoLi/DMPBg8DyWlkYrK66Zmfb6uqEoSiwWc7vdIISMMQZCxpJt27VardPpxGIxVVVxJ0KhkCAIpVJpdnbw4ovR5WWXaeJ+03UUCnjySafVqplmW9d1RVFACBl7DISMn3a7XalUZmZmstmsIAi4c36/P5PJbG5uejz9S5f0j3yEu3KFs23cDzyPXA6FAoLBbqlkuN3uTCbj8XhACJkEDISME9u2q9Xqzs5OPB4PBoO4B6IoptNpwzAGg2vPP5987TUxn4dh4GjpOgoF5HLY3m6sr1cikUg4HOY4DoSQCcFAyNhot9uVSmVmZiabzQqCgHvGGEulUrVarVTaePTRRLHoX16GYeCo6DqKRUQidqVS6Xa7c3NzPp8PhJCJwkDIGBgMBrVabWdnJx6PB4NBHB2XyxWLxQRBuH79uqZpxWJoeRmGgXvE81hawsoKAoHd9fWyJEmZTIbneRBCJg0DIQ9bu902TVOW5Ww2KwgC7gNVVQVBKJfLPl//8uV4Pu+6csVl27g7uo5CAYuLzvZ2Y2OjqmlaKBQCIWQyMRDy8AwGg2q1uru7G4/Hg8Eg7idZltPpdLlcBq7/4AeJV14R8nkYBu4IzyOXQ6GAUKhvmuZwOMxms5IkgRAysRgIeUja7bZpmj6fL5vNCoKA+08QhLm5OdM0S6WNxx9PFoszy8swDBySrqNQQC6Hvb32+roZCARSqZTb7QYhZJIxEPLADQaDarW6u7uraZqiKHiAOI5LJBKWZW1sbCQSiWIxuLwMw8Bt6TqKRcTjTrVa3dra0jQtGAyCEDL5GAh5sNrttmmasixns1lBEPAwRCIRj8dTKpVCof6LL0bPnnUZBm6F55HLoVBAMNjd2DA5jstkMqIoghByLDAQ8mB5PB5N0xRFwUMVCAR4ni+Xy6I4uHRJf/pp15UrnG3j39B1FArI5bCz09rYMEOhUDQadblcIIQcFwyEPFjemzAGJElKp9Plcnk4vPb884nXXhPzeRgGfkbXUSwiGh1WKpW9vb1UKuX3+0EIOV4YCJlijLFUKlWr1UqljUcfTRSL/uVlGAZ4HrkcCgUEArvr64Yoiul0WhAEEEKOHQZCphvHcfF43OPxXL9+XdO0YjH0uc+NPvUp19LSqN2ub2xUNU0LhUIghBxTDIQQQFVVQRBKpVIgMPjzP48dHNimaQ4Gg0wmMzMzA0LI8cVAyFFzHIfjOEwaWZbT6XS5XH799ddGo1EwGEwkEowxEEKONQZCjs7+/v5gMNjc3Ewmk4qiYNLwPC+KomEYMzMzqqoyxkAIOe4YCDkijuM0m03LsrrdbjwedxyH4zhMjl6vVy6XXS7Xu971rp2dnY2NjUQioSgKCCHHGgMhR6Tb7cqy3O12E4lEKBTCRGm1WqZphkKhSCTCcZzX6xUEoVwu9/v9aDQKQsjxxUDIEZFl2XEcv9/PcRwmx3A4rFarnU4nlUr5/X78K0VRBEEol8v9fl/TNMYYCCHHEQMhR4fjOEyU3d1d0zQFQchms4Ig4BdJkjQ/P28YxvXr1xOJhCiKIIQcOwyETKXRaNRoNCqVSiwWC4fDLpcLb4fn+RMnTlQqlY2NjWQy6fP5QAg5XhgImT6DwcA0zcFgkE6nZVnGO3K5XJqmeTyea9eu6bo+OzsLQsgxwkDIlOl0OoZh+Hy+RCLBGMPhzM7OCoJQKpX6/X4sFuM4DoSQY4GBkKnhOI5lWY1GQ9M0VVVxh3w+XzqdLpfLm5ubuq7zPA9CyORjIGQ69Ho90zQdx8lkMl6vF3dFFMW5uTnTNK9du5ZIJCRJAiFkwjEQMgW2trYMw1BVNRaLcRyHe8AYS6VStVptY2MjkUgoigJCyCRjIORYGw6H1Wq10+kkEglFUXBEotGox+Mpl8uDwSASiYAQMrEYCDm+ut1uuVwWBCGbzQqCgCOlKIogCKVSSRRFv98PQshkYiDkmGo0GqZpxmKxcDjscrlwH0iSND8/LwgCCCETi4GQY2cwGFSr1f39/XQ6Lcsy7idBEEAImWQMhBwvnU7HNE1JkjKZDGMMhBDyjhgIOS4cx7Esq16va5o2OzuLh6TT6fh8vp2dHb/fD0LI2GMg5Fjo9XqmaTqOk8lkJEnCQzIajQRB+PGPf3z69Ont7e1AIABCyHhjIGTytdttwzCCwWA0GnW73Xh4dnZ2+jdtbm5qmmbbNs/zIISMMQZCJp8oirquK4qCh83v95umeerUKVEUAfA8D0LIeGMgZPKJN2E8aJoGQsjkYCCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQsbe7u7uzMzM3t6eLMsghJAjxUDIeOv1evV6vVwuJ5NJEELIUWMgZLyVSiWO47rdbr/fn5mZASGEHCkGQsZYp9PJZDKWZQWDQVVVQQghR42BkDHm9/sBxGIxEELI/cFACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliZ7GwGAAAAWVJREFUDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVPs/wGOL6frCyl7JgAAAABJRU5ErkJggg==", + "text/html": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "data": { "text/plain": [ - "1-element Vector{String}:\n", - " \"Ω.vtu\"" + "GLMakie.Screen(...)" ] }, - "execution_count": 9, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "GT.vtk_plot(\"Ω\",Ω)" + "plt = GT.plot(Ω)\n", + "fig = Makie.plot(plt;shading=Makie.NoShading,color=:blue)\n", + "display(fig)" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 79, "metadata": {}, "outputs": [ { @@ -294,9 +314,8 @@ "GalerkinToolkit.PhysicalDomain(…)" ] }, - "execution_count": 10, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ @@ -305,28 +324,38 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 80, "metadata": {}, "outputs": [ + { + "data": { + "image/png": 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", + "text/html": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "data": { "text/plain": [ - "1-element Vector{String}:\n", - " \"Γd.vtu\"" + "GLMakie.Screen(...)" ] }, - "execution_count": 11, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "GT.vtk_plot(\"Γd\",Γd) do plt end # TODO Maybe remove do plt end" + "plt = GT.plot(Γd)\n", + "fig = Makie.plot(plt;shading=Makie.NoShading,color=:blue)\n", + "display(fig)" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 81, "metadata": {}, "outputs": [ { @@ -335,9 +364,8 @@ "GalerkinToolkit.PhysicalDomain(…)" ] }, - "execution_count": 12, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ @@ -346,23 +374,33 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 82, "metadata": {}, "outputs": [ + { + "data": { + "image/png": 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", + "text/html": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "data": { "text/plain": [ - "1-element Vector{String}:\n", - " \"Γ.vtu\"" + "GLMakie.Screen(...)" ] }, - "execution_count": 13, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "GT.vtk_plot(\"Γ\",Γ) do plt end # TODO Maybe remove do plt end" + "plt = GT.plot(Γ)\n", + "fig = Makie.plot(plt;shading=Makie.NoShading,color=:blue)\n", + "display(fig)" ] }, { @@ -389,7 +427,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 86, "metadata": {}, "outputs": [ { @@ -398,9 +436,8 @@ "GalerkinToolkit.LagrangeSpace(…)" ] }, - "execution_count": 14, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ @@ -419,7 +456,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 85, "metadata": {}, "outputs": [ { @@ -428,9 +465,8 @@ "GalerkinToolkit.DiscreteField(…)" ] }, - "execution_count": 15, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ @@ -443,48 +479,60 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 96, "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "1-element Vector{String}:\n", - " \"Γd.vtu\"" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" + "ename": "UndefVarError", + "evalue": "UndefVarError: `vtk_plot` not defined in `WriteVTK`\nSuggestion: check for spelling errors or missing imports.", + "output_type": "error", + "traceback": [ + "UndefVarError: `vtk_plot` not defined in `WriteVTK`\n", + "Suggestion: check for spelling errors or missing imports.\n", + "\n", + "Stacktrace:\n", + " [1] getproperty(x::Module, f::Symbol)\n", + " @ Base ./Base.jl:42\n", + " [2] top-level scope\n", + " @ ~/Library/CloudStorage/OneDrive-NetherlandseScienceCenter/Documents/NLeSC_Projects/HP2SIM/GalerkinToolkit.jl/notebooks/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X30sZmlsZQ==.jl:1" + ] } ], "source": [ - "GT.vtk_plot(\"Γd\",Γd) do plt\n", + "WriteVTK.vtk_plot(\"Γd\",Γd) do plt\n", " GT.plot!(plt,g;label=\"g\")\n", - "end" + "end\n", + "#GT.plot!(plt,g;label=\"g\")\n", + "#Makie.plot(plt,color=GT.NodeData(\"g\"))" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 95, "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "1-element Vector{String}:\n", - " \"Ω.vtu\"" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" + "ename": "UndefVarError", + "evalue": "UndefVarError: `vtk_plot` not defined in `GalerkinToolkit`\nSuggestion: check for spelling errors or missing imports.", + "output_type": "error", + "traceback": [ + "UndefVarError: `vtk_plot` not defined in `GalerkinToolkit`\n", + "Suggestion: check for spelling errors or missing imports.\n", + "\n", + "Stacktrace:\n", + " [1] getproperty(x::Module, f::Symbol)\n", + " @ Base ./Base.jl:42\n", + " [2] top-level scope\n", + " @ ~/Library/CloudStorage/OneDrive-NetherlandseScienceCenter/Documents/NLeSC_Projects/HP2SIM/GalerkinToolkit.jl/notebooks/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X31sZmlsZQ==.jl:1" + ] } ], "source": [ - "GT.vtk_plot(\"Ω\",Ω) do plt\n", + "WriteVTK.vtk_plot(\"Ω\",Ω) do plt\n", " GT.plot!(plt,uhd;label=\"uhd\")\n", - "end" + "end\n", + "#GT.plot!(plt,uhd;label=\"uhd\")\n", + "#Makie.plot(plt,color=GT.NodeData(\"uhd\"))" ] }, { @@ -793,15 +841,15 @@ ], "metadata": { "kernelspec": { - "display_name": "Julia 1.10.5", + "display_name": "Julia 1.11.0", "language": "julia", - "name": "julia-1.10" + "name": "julia-1.11" }, "language_info": { "file_extension": ".jl", "mimetype": "application/julia", "name": "julia", - "version": "1.10.5" + "version": "1.11.0" } }, "nbformat": 4, From 6a7dc3a7f5e7108f5ed42520cca9beb20d5609d3 Mon Sep 17 00:00:00 2001 From: Cmurilochem Date: Wed, 16 Oct 2024 16:16:26 +0200 Subject: [PATCH 11/14] Add Project.toml to notebooks --- .gitignore | 1 + notebooks/Project.toml | 4 ++++ 2 files changed, 5 insertions(+) create mode 100644 notebooks/Project.toml diff --git a/.gitignore b/.gitignore index b0ea1d57..5eeba2d0 100644 --- a/.gitignore +++ b/.gitignore @@ -12,6 +12,7 @@ /docs/build/ /docs/src/tutorials/ /docs/Manifest.toml +/notebooks/Manifest.toml .vscode GalerkinToolkitExamples_output/ GalerkinToolkitExamples/Manifest.toml diff --git a/notebooks/Project.toml b/notebooks/Project.toml new file mode 100644 index 00000000..5efcdebd --- /dev/null +++ b/notebooks/Project.toml @@ -0,0 +1,4 @@ +[deps] +GLMakie = "e9467ef8-e4e7-5192-8a1a-b1aee30e663a" +GalerkinToolkit = "5e3ba9c4-dd81-444d-b69a-0e7bd7bf60a4" +WriteVTK = "64499a7a-5c06-52f2-abe2-ccb03c286192" From eceea0cef6c83494802e8de8a3ae28d85c3153f7 Mon Sep 17 00:00:00 2001 From: Cmurilochem Date: Thu, 17 Oct 2024 10:06:47 +0200 Subject: [PATCH 12/14] Improve notebook --- .gitignore | 1 + .../t001_poisson-checkpoint.ipynb | 809 ------------------ notebooks/Project.toml | 1 + notebooks/t001_poisson.ipynb | 523 ++++++----- 4 files changed, 311 insertions(+), 1023 deletions(-) delete mode 100644 notebooks/.ipynb_checkpoints/t001_poisson-checkpoint.ipynb diff --git a/.gitignore b/.gitignore index 5eeba2d0..915f1898 100644 --- a/.gitignore +++ b/.gitignore @@ -7,6 +7,7 @@ *.pvd *.pvtu *.vtu +*.ipynb* /output /Manifest.toml /docs/build/ diff --git a/notebooks/.ipynb_checkpoints/t001_poisson-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/t001_poisson-checkpoint.ipynb deleted file mode 100644 index 308cd536..00000000 --- a/notebooks/.ipynb_checkpoints/t001_poisson-checkpoint.ipynb +++ /dev/null @@ -1,809 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Tutorial 1: Poisson equation" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this tutorial, we will learn\n", - "\n", - " - How to solve a simple PDE in Julia with GalerkinToolkit\n", - " - How to load a discrete model (aka a FE mesh) from a file\n", - " - How to build a conforming Lagrangian FE space\n", - " - How to define the different terms in a weak form\n", - " - How to impose Dirichlet and Neumann boundary conditions\n", - " - How to visualize results\n", - "\n", - "\n", - "## Problem statement\n", - "\n", - "In this first tutorial, we provide an overview of a complete simulation pipeline in GalerkinToolkit: from the construction of the FE mesh to the visualization of the computed results. To this end, we consider a simple model problem: the Poisson equation.\n", - " We want to solve the Poisson equation on the 3D domain depicted in next figure with Dirichlet and Neumann boundary conditions. Dirichlet boundary conditions are applied on $\\Gamma_{\\rm D}$, being the outer sides of the prism (marked in red). Non-homogeneous Neumann conditions are applied to the internal boundaries $\\Gamma_{\\rm G}$, $\\Gamma_{\\rm Y}$, and $\\Gamma_{\\rm B}$ (marked in green, yellow and blue respectively). And homogeneous Neumann boundary conditions are applied in $\\Gamma_{\\rm W}$, the remaining portion of the boundary (marked in white).\n", - "\n", - "![](../docs/src/assets/poisson/model-r1-2.png)\n", - "\n", - " Formally, the problem to solve is: find the scalar field $u$ such that\n", - "\n", - "$$\n", - "\\left\\lbrace\n", - "\\begin{aligned}\n", - "-\\Delta u = f \\ &\\text{in} \\ \\Omega,\\\\\n", - "u = g \\ &\\text{on}\\ \\Gamma_{\\rm D},\\\\\n", - "\\nabla u\\cdot n = h \\ &\\text{on}\\ \\Gamma_{\\rm N},\\\\\n", - "\\end{aligned}\n", - "\\right.\n", - "$$\n", - " being $n$ the outwards unit normal vector to the Neumann boundary $\\Gamma_{\\rm N} \\doteq \\Gamma_{\\rm G}\\cup\\Gamma_{\\rm Y}\\cup\\Gamma_{\\rm B}\\cup\\Gamma_{\\rm W}$. In this example, we chose $f(x) = 1$, $g(x) = 2$, and $h(x)=3$ on $\\Gamma_{\\rm G}\\cup\\Gamma_{\\rm Y}\\cup\\Gamma_{\\rm B}$ and $h(x)=0$ on $\\Gamma_{\\rm W}$. The variable $x$ is the position vector $x=(x_1,x_2,x_3)$.\n", - "\n", - " ## Numerical scheme\n", - "\n", - " To solve this PDE, we use a conventional Galerkin finite element (FE) method with conforming Lagrangian FE spaces (see, e.g., [1] for specific details on this formulation). The weak form associated with this formulation is: find $u\\in U_g$ such that $ a(u,v) = b(v) $ for all $v\\in V_0$, where $U_g$ and $V_0$ are the subset of functions in $H^1(\\Omega)$ that fulfill the Dirichlet boundary condition $g$ and $0$ respectively. The bilinear and linear forms for this problems are\n", - "$$\n", - " a(u,v) \\doteq \\int_{\\Omega} \\nabla v \\cdot \\nabla u \\ {\\rm d}\\Omega, \\quad b(v) \\doteq \\int_{\\Omega} v\\ f \\ {\\rm d}\\Omega + \\int_{\\Gamma_{\\rm N}} v\\ h \\ {\\rm d}\\Gamma_{\\rm N}.\n", - "$$\n", - "The problem is solved numerically by approximating the spaces $U_g$ and $V_0$ by their discrete counterparts associated with a FE mesh of the computational domain $\\Omega$. As we have anticipated, we consider standard conforming Lagrangian FE spaces for this purpose.\n", - "\n", - "The implementation of this numerical scheme in GalerkinToolkit is done in a user-friendly way thanks to the abstractions provided by the library. As it will be seen below, all the mathematical objects involved in the definition of the discrete weak problem have a correspondent representation in the code.\n", - "\n", - " ## Setup\n", - "\n", - " The step number 0 in order to solve the problem is to load the GalerkinToolkit library in the code. If you have configured your Julia environment properly, it is simply done with the line:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[36m\u001b[1mProject\u001b[22m\u001b[39m GalerkinToolkit v0.1.0\n", - "\u001b[32m\u001b[1mStatus\u001b[22m\u001b[39m `~/Library/CloudStorage/OneDrive-NetherlandseScienceCenter/Documents/NLeSC_Projects/HP2SIM/GalerkinToolkit.jl/Project.toml`\n", - " \u001b[90m[8e7c35d0] \u001b[39mBlockArrays v1.1.1\n", - " \u001b[90m[861a8166] \u001b[39mCombinatorics v1.0.2\n", - " \u001b[90m[442a2c76] \u001b[39mFastGaussQuadrature v1.0.2\n", - " \u001b[90m[1a297f60] \u001b[39mFillArrays v1.13.0\n", - " \u001b[90m[f6369f11] \u001b[39mForwardDiff v0.10.36\n", - " \u001b[90m[705231aa] \u001b[39mGmsh v0.3.1\n", - " \u001b[90m[42fd0dbc] \u001b[39mIterativeSolvers v0.9.4\n", - "\u001b[32m⌃\u001b[39m \u001b[90m[da04e1cc] \u001b[39mMPI v0.20.21\n", - " \u001b[90m[e9d8d322] \u001b[39mMetatheory v2.0.2\n", - "\u001b[32m⌃\u001b[39m \u001b[90m[2679e427] \u001b[39mMetis v1.4.1\n", - " \u001b[90m[5a9dfac6] \u001b[39mPartitionedArrays v0.5.4\n", - " \u001b[90m[90137ffa] \u001b[39mStaticArrays v1.9.7\n", - "\u001b[32m⌃\u001b[39m \u001b[90m[64499a7a] \u001b[39mWriteVTK v1.19.2\n", - " \u001b[90m[37e2e46d] \u001b[39mLinearAlgebra\n", - " \u001b[90m[2f01184e] \u001b[39mSparseArrays v1.10.0\n", - "\u001b[36m\u001b[1mInfo\u001b[22m\u001b[39m Packages marked with \u001b[32m⌃\u001b[39m have new versions available and may be upgradable.\n" - ] - } - ], - "source": [ - "using Pkg\n", - "Pkg.status()" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "import GalerkinToolkit as GT" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Computational mesh\n", - "\n", - "As in any FE simulation, we need a discretization of the computational domain (i.e., a FE mesh). All geometrical data needed for solving a FE problem is provided in GalerkinToolkit by types inheriting from the abstract type `GenericMesh`. In the following line, we build an instance of `GenericMesh` by loading a `msh` file." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Info : Reading '../docs/src/assets/model.msh'...\n", - "Info : 95 entities\n", - "Info : 7475 nodes\n", - "Info : 40330 elements\n", - "Info : Done reading '../docs/src/assets/model.msh'\n" - ] - }, - { - "data": { - "text/plain": [ - "GalerkinToolkit.GenericMesh(…)" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "mesh = GT.mesh_from_gmsh(\"../docs/src/assets/model.msh\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The file `\"model.msh\"` (which contains a FE mesh and information about user-defined physical boundaries) was generated by using the [GMSH](http://gmsh.info/) mesh generator. See the documentation of [GMSH](http://gmsh.info/#Documentation).\n", - "\n", - "You can easily inspect the generated discrete model in [Paraview](https://www.paraview.org/) by writing it in `vtk` format." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1-element Vector{String}:\n", - " \"mesh.vtu\"" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# writevtk(model,\"model\")\n", - "# TODO\n", - "# GT.plot_vtk(\"mesh\",mesh)\n", - "using WriteVTK\n", - "vtk_grid(\"mesh\",GT.vtk_args(mesh)...) do vtk\n", - " GT.vtk_physical_faces!(vtk, mesh)\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dict{String, Vector{Int32}} with 6 entries:\n", - " \"triangle\" => [5401, 5402, 5403, 5404, 5405, 5406, 5407, 5408, 5409, 5410 … …\n", - " \"bottom\" => [1, 2, 3, 4, 5, 6, 7, 8, 9, 10 … 3385, 3386, 3387, 3388, 3389…\n", - " \"circle\" => [6609, 6610, 6611, 6612, 6613, 6614, 6615, 6616, 6617, 6618 … …\n", - " \"top\" => [7053, 7054, 7055, 7056, 7057, 7058, 7059, 7060, 7061, 7062 … …\n", - " \"square\" => [6053, 6054, 6055, 6056, 6057, 6058, 6059, 6060, 6061, 6062 … …\n", - " \"sides\" => [3395, 3396, 3397, 3398, 3399, 3400, 3401, 3402, 3403, 3404 … …" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "GT.physical_faces(mesh,2)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dict{String, Vector{Int32}} with 1 entry:\n", - " \"volume\" => [1, 2, 3, 4, 5, 6, 7, 8, 9, 10 … 29151, 29152, 29153, 29154, 29…" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "GT.physical_faces(mesh,3)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Computational domains" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "GalerkinToolkit.PhysicalDomain(…)" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Ω = GT.interior(mesh;physical_names=[\"volume\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "GT.vtk_plot(\"Ω\",Ω) do plt end # TODO Maybe remove do plt end\n", - "# GT.vtk_plot(\"Ω\",Ω)\n", - "# TODO move this to domain.jl\n", - "GT.vtk_plot(name::AbstractString,domain::GT.AbstractDomain;kwargs...) = GT.vtk_plot(identity,name,domain;kwargs...)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1-element Vector{String}:\n", - " \"Ω.vtu\"" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "GT.vtk_plot(\"Ω\",Ω)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "GalerkinToolkit.PhysicalDomain(…)" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Γd = GT.boundary(mesh;physical_names=[\"sides\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1-element Vector{String}:\n", - " \"Γd.vtu\"" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "GT.vtk_plot(\"Γd\",Γd) do plt end # TODO Maybe remove do plt end" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "GalerkinToolkit.PhysicalDomain(…)" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Γ = GT.boundary(mesh;physical_names=[\"circle\", \"triangle\", \"square\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1-element Vector{String}:\n", - " \"Γ.vtu\"" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "GT.vtk_plot(\"Γ\",Γ) do plt end # TODO Maybe remove do plt end" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The previous line generates four different files `model_0.vtu`, `model_1.vtu`, `model_2.vtu`, and `model_3.vtu` containing the vertices, edges, faces, and cells present in the discrete model. Moreover, you can easily inspect which boundaries are defined within the model.\n", - "\n", - "For instance, if you want to see which faces of the model are on the boundary $\\Gamma_{\\rm B}$ (i.e., the walls of the circular perforation), open the file `model_2.vtu` and chose coloring by the element field \"circle\". You should see that only the faces on the circular hole have a value different from zero (see next figure).\n", - "\n", - "![](../docs/src/assets/poisson/fig_faces_on_circle.png)\n", - "\n", - "It is also possible to see which vertices are on the Dirichlet boundary $\\Gamma_{\\rm D}$. To do so, open the file `model_0.vtu` and chose coloring by the field \"sides\" (see next figure).\n", - "\n", - "![](../docs/src/assets/poisson/fig_vertices_on_sides.png)\n", - "\n", - "That is, the boundary $\\Gamma_{\\rm B}$ (i.e., the walls of the circular hole) is called \"circle\" and the Dirichlet boundary $\\Gamma_{\\rm D}$ is called \"sides\" in the model. In addition, the walls of the triangular hole $\\Gamma_{\\rm G}$ and the walls of the square hole $\\Gamma_{\\rm Y}$ are identified in the model with the names \"triangle\" and \"square\" respectively. You can easily check this by opening the corresponding file in Paraview.\n", - "\n", - "\n", - "## FE spaces\n", - "\n", - " Once we have a discretization of the computational domain, the next step is to generate a discrete approximation of the finite element spaces $V_0$ and $U_g$ (i.e. the test and trial FE spaces) of the problem. To do so, first, we are going to build a discretization of $V_0$ as the standard Conforming Lagrangian FE space (with zero boundary conditions) associated with the discretization of the computational domain. The approximation of the FE space $V_0$ is built as follows:" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "GalerkinToolkit.LagrangeSpace(…)" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "order = 1\n", - "V = GT.lagrange_space(Ω,order;dirichlet_boundary=Γd)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Here, we have used the `TestFESpace` constructor, which constructs a particular FE space (to be used as a test space) from a set of options described as positional and key-word arguments. The first positional argument is the model on top of which we want to build the space. The second positional argument contains information about the type of FE interpolation (the reference FE in this case). With `ReferenceFE(lagrangian,Float64,order)` We select a scalar-valued Lagrangian reference FE of order 1, where the value of the shape functions will be represented with 64-bit floating point numbers. With the key-word argument `conformity` we define the regularity of the interpolation at the boundaries of the cells in the mesh. Here, we use `conformity=:H1`, which means that the resulting interpolation space is a subset of $H^1(\\Omega)$ (i.e., continuous shape functions). On the other hand, we pass the identifiers of the Dirichlet boundary via the `dirichlet_tags` argument. In this case, we mark as Dirichlet all objects of the discrete model identified with the `\"sides\"` tag. Since this is a test space, the corresponding shape functions vanishes at the Dirichlet boundary.\n", - "\n", - "Once the space $V_0$ is discretized in the code, we proceed with the approximation of the trial space $U_g$." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "GalerkinToolkit.DiscreteField(…)" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "uhd = GT.dirichlet_field(Float64,V)\n", - "g = GT.analytical_field(Ω) do x\n", - " 2.0\n", - "end\n", - "GT.interpolate_dirichlet!(g,uhd)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1-element Vector{String}:\n", - " \"Γd.vtu\"" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "GT.vtk_plot(\"Γd\",Γd) do plt\n", - " GT.plot!(plt,g;label=\"g\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1-element Vector{String}:\n", - " \"Ω.vtu\"" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "GT.vtk_plot(\"Ω\",Ω) do plt\n", - " GT.plot!(plt,uhd;label=\"uhd\")\n", - "end" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "To this end, we have used the `TrialFESpace` constructors. Note that we have passed a function representing the value of the Dirichlet boundary condition, when building the trial space.\n", - "\n", - "\n", - "## Numerical integration\n", - "\n", - "Once we have built the interpolation spaces, the next step is to set up the machinery to perform the integrals in the weak form numerically. Here, we need to compute integrals on the interior of the domain $\\Omega$ and on the Neumann boundary $\\Gamma_{\\rm N}$. In both cases, we need two main ingredients. We need to define an integration mesh (i.e. a triangulation of the integration domain), plus a Gauss-like quadrature in each of the cells in the triangulation. In Gridap, integration meshes are represented by types inheriting from the abstract type `Triangulation`. For integrating on the domain $\\Omega$, we build the following triangulation and the corresponding Lebesgue measure, which will allow to write down integrals in a syntax similar to the usual mathematical notation." - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "GalerkinToolkit.Measure(…)" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "degree = 2*order\n", - "dΩ = GT.measure(Ω,degree) # TODO fix pretty printing in GalerkinToolkit.Measure" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Here, we build a triangulation from the cells of the model and build (an approximation of) the Lebesgue measure using a quadrature rule of degree 2 in the cells of this triangulation. This is enough for integrating the corresponding terms of the weak form exactly for an interpolation of order 1.\n", - "\n", - "On the other hand, we need a special type of triangulation, represented by the type `BoundaryTriangulation`, to integrate on the boundary. Essentially, a `BoundaryTriangulation` is a particular type of `Triangulation` that is aware of which cells in the model are touched by faces on the boundary. We build an instance of this type from the discrete model and the names used to identify the Neumann boundary as follows:" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "GalerkinToolkit.Measure(…)" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dΓ = GT.measure(Γ,degree)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Differential operators" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "∇ (generic function with 1 method)" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "using ForwardDiff\n", - "gradient(u) = x->ForwardDiff.gradient(u,x)\n", - "∇(u,x) = GT.call(gradient,u)(x)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In addition, we have created a quadrature of degree 2 on top of the cells in the triangulation for the Neumann boundary.\n", - "\n", - "## Weak form\n", - "\n", - "With all the ingredients presented so far, we are ready to define the weak form. This is done by defining functions representing the bi-linear and linear forms:" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "l (generic function with 1 method)" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "using LinearAlgebra\n", - "f = GT.analytical_field(Ω) do x\n", - " 1.0\n", - "end\n", - "h = GT.analytical_field(Ω) do x\n", - " 3.0\n", - "end\n", - "a(u,v) = GT.∫( x->∇(u,x)⋅∇(v,x), dΩ)\n", - "l(v) = GT.∫( x->v(x)*f(x), dΩ) + GT.∫( x->v(x)*h(x),dΓ)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Note that by using the integral function `∫`, the Lebesgue measures `dΩ`, `dΓ`, and the gradient function `∇`, the weak form is written with an obvious relation with the corresponding mathematical notation." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " ## FE Problem\n", - "\n", - " At this point, we can build the FE problem that, once solved, will provide the numerical solution we are looking for. A FE problem is represented in Gridap by types inheriting from the abstract type `FEOperator` (both for linear and nonlinear cases). Since we want to solve a linear problem, we use the concrete type `AffineFEOperator`, i.e., a problem represented by a matrix and a right hand side vector." - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "([5.2150170844097e-310, 2.787823149e-314, 2.787823149e-314, 8.487983168e-314, 2.121995792e-314, 5.2150256584581e-310, NaN, NaN, 5.2150170844097e-310, 2.121995791e-314 … NaN, NaN, NaN, 2.8843385805e-314, NaN, 3.141768011e-314, NaN, 2.8834005396e-314, NaN, 2.8843373987e-314], sparse([1, 22, 74, 289, 337, 338, 339, 340, 341, 1872 … 6303, 335, 465, 467, 468, 1806, 6201, 6224, 6232, 6304], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 6303, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304], [0.06443080405538211, -0.0011816946972152084, -0.0019141180663583925, -0.03255921926190384, -0.013954244941888471, -0.009620087896820673, -0.0021278804315064915, -0.004654033162377993, -0.005173786773138719, 0.003329780400807812 … 0.21999530084991323, -0.015615599976174236, 0.003972555304119093, -0.009088995023018824, -0.00030902681072076353, -0.013784861561036393, -0.014076977113079436, -0.024457375688586837, -0.013734513123868308, 0.17287503833373258], 6304, 6304), [0.001567735161920194, 0.0015207565876126676, 0.0015232957017090138, 0.0016182302571138272, 0.0013414312146763385, 0.0014776038723584638, 0.001306589310230424, 0.0014160610368619702, 0.0014136920830547547, 0.001413925912088446 … 0.09466909943634595, 3.837716427462897e-5, 4.067983156302628e-5, 3.407470822273103e-5, 3.41027317460599e-5, 0.08456444214161216, 0.07001671663821094, 3.708312001443067e-5, 3.516169468651288e-5, 0.17159606501883534])" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "x,A,b = GT.linear_problem(uhd,a,l)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Note that the `AffineFEOperator` object representing our FE problem is built from the function `a` and `b` representing the weak form and test and trial FE spaces `V0` and `Ug`.\n", - "\n", - " ## Solver phase\n", - "\n", - " We have constructed a FE problem, the last step is to solve it. In Gridap, FE problems are solved with types inheriting from the abstract type `FESolver`. Since this is a linear problem, we use a `LinearFESolver`:" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "6304-element Vector{Float64}:\n", - " 2.288817650800605\n", - " 3.191214461559075\n", - " 3.243769827996373\n", - " 4.513021960049178\n", - " 4.137978510723658\n", - " 2.6511832145611978\n", - " 3.9985286410715637\n", - " 2.3676403246611577\n", - " 2.6253865316943625\n", - " 3.1924629585377917\n", - " 2.2896951265865444\n", - " 3.1863629312428015\n", - " 3.2445741024920083\n", - " ⋮\n", - " 4.285487712910332\n", - " 2.9668852150686487\n", - " 2.020241401823711\n", - " 2.3980575528123094\n", - " 3.9912082231886825\n", - " 3.6282800936694914\n", - " 3.817091127051113\n", - " 2.0771951682489314\n", - " 2.0995109886643184\n", - " 2.4363879401098405\n", - " 4.398698443572705\n", - " 2.0089547066118425" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "x .= A\\b" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " `LinearFESolver` objects are built from a given algebraic linear solver. In this case, we use a LU factorization. Now we are ready to solve the FE problem with the FE solver as follows:" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "GalerkinToolkit.DiscreteField(…)" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "uh = GT.solution_field(uhd,x)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The `solve` function returns the computed numerical solution `uh`. This object is an instance of `FEFunction`, the type used to represent a function in a FE space. We can inspect the result by writing it into a `vtk` file:" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1-element Vector{String}:\n", - " \"Ω.vtu\"" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "GT.vtk_plot(\"Ω\",Ω) do plt\n", - " GT.plot!(plt,uhd;label=\"uhd\")\n", - " GT.plot!(plt,uh;label=\"uh\")\n", - "end" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " which will generate a file named `results.vtu` having a nodal field named `\"uh\"` containing the solution of our problem (see next figure).\n", - "\n", - "![](../docs/src/assets/poisson/fig_uh.png)\n", - "\n", - "## References\n", - "\n", - "[1] C. Johnson. *Numerical Solution of Partial Differential Equations by the Finite Element Method*. Dover Publications, 2009." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---\n", - "\n", - "*This notebook was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).*" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia 1.10.5", - "language": "julia", - "name": "julia-1.10" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.10.5" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/notebooks/Project.toml b/notebooks/Project.toml index 5efcdebd..c155d6e1 100644 --- a/notebooks/Project.toml +++ b/notebooks/Project.toml @@ -1,4 +1,5 @@ [deps] +ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210" GLMakie = "e9467ef8-e4e7-5192-8a1a-b1aee30e663a" GalerkinToolkit = "5e3ba9c4-dd81-444d-b69a-0e7bd7bf60a4" WriteVTK = "64499a7a-5c06-52f2-abe2-ccb03c286192" diff --git a/notebooks/t001_poisson.ipynb b/notebooks/t001_poisson.ipynb index 3768e16a..bf80bc4e 100644 --- a/notebooks/t001_poisson.ipynb +++ b/notebooks/t001_poisson.ipynb @@ -58,38 +58,11 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 1, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[36m\u001b[1mProject\u001b[22m\u001b[39m GalerkinToolkit v0.1.0\n", - "\u001b[32m\u001b[1mStatus\u001b[22m\u001b[39m `~/Library/CloudStorage/OneDrive-NetherlandseScienceCenter/Documents/NLeSC_Projects/HP2SIM/GalerkinToolkit.jl/Project.toml`\n", - " \u001b[90m[8e7c35d0] \u001b[39mBlockArrays v1.1.1\n", - " \u001b[90m[861a8166] \u001b[39mCombinatorics v1.0.2\n", - " \u001b[90m[442a2c76] \u001b[39mFastGaussQuadrature v1.0.2\n", - " \u001b[90m[1a297f60] \u001b[39mFillArrays v1.13.0\n", - " \u001b[90m[f6369f11] \u001b[39mForwardDiff v0.10.36\n", - " \u001b[90m[705231aa] \u001b[39mGmsh v0.3.1\n", - " \u001b[90m[42fd0dbc] \u001b[39mIterativeSolvers v0.9.4\n", - " \u001b[90m[da04e1cc] \u001b[39mMPI v0.20.22\n", - " \u001b[90m[e9d8d322] \u001b[39mMetatheory v2.0.2\n", - " \u001b[90m[2679e427] \u001b[39mMetis v1.5.0\n", - " \u001b[90m[5a9dfac6] \u001b[39mPartitionedArrays v0.5.5\n", - " \u001b[90m[90137ffa] \u001b[39mStaticArrays v1.9.7\n", - " \u001b[90m[64499a7a] \u001b[39mWriteVTK v1.21.0\n", - " \u001b[90m[37e2e46d] \u001b[39mLinearAlgebra v1.11.0\n", - " \u001b[90m[2f01184e] \u001b[39mSparseArrays v1.11.0\n" - ] - } - ], + "outputs": [], "source": [ - "import GalerkinToolkit as GT\n", - "\n", - "using Pkg\n", - "Pkg.status()" + "import GalerkinToolkit as GT" ] }, { @@ -103,7 +76,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -123,8 +96,9 @@ "GalerkinToolkit.GenericMesh(…)" ] }, + "execution_count": 2, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -137,31 +111,36 @@ "source": [ "The file `\"model.msh\"` (which contains a FE mesh and information about user-defined physical boundaries) was generated by using the [GMSH](http://gmsh.info/) mesh generator. See the documentation of [GMSH](http://gmsh.info/#Documentation).\n", "\n", - "You can easily inspect the generated discrete model using [Makie](https://docs.makie.org/) and the [GLMakie](https://docs.makie.org/stable/explanations/backends/glmakie#GLMakie) backend. " + "You can easily inspect the generated discrete model using [Makie](https://docs.makie.org/) and [GLMakie](https://docs.makie.org/stable/explanations/backends/glmakie#GLMakie) backend, like so:" ] }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 16, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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"text/html": [ - "" + "" ] }, + "execution_count": 16, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ "using GLMakie\n", - "Makie.inline!(true)\n", "\n", - "plt = GT.plot(mesh)\n", - "Makie.plot(plt;shading=Makie.NoShading,color=:blue)" + "# for a larger figure\n", + "#f = Figure(; size = (600, 400))\n", + "#lscene = LScene(f[1, 1])\n", + "#GLMakie.plot!(lscene, mesh;shading=Makie.NoShading,color=:blue)\n", + "#f\n", + "\n", + "GLMakie.plot(mesh;shading=Makie.NoShading,color=:blue)" ] }, { @@ -173,7 +152,7 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": 46, "metadata": {}, "outputs": [ { @@ -183,129 +162,197 @@ " \"mesh.vtu\"" ] }, + "execution_count": 46, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ "using WriteVTK\n", "\n", - "plt = GT.plot(mesh)\n", - "WriteVTK.vtk_grid(\"mesh\", plt) |> close" + "WriteVTK.vtk_grid(\"mesh\", mesh) |> close" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Apart from visualizations, users can additionally inspect general mesh attributes by resorting to several GalerkinToolkit's built-in functions, *e.g*, `num_dims`, `num_nodes`, `num_faces`, `node_coordinates`, `node_coordinates`, `physical_faces`, etc." + "Apart from visualizations, users can additionally inspect general mesh attributes by resorting to several GalerkinToolkit's built-in functions, *e.g*, `num_dims`, `num_nodes`, `num_faces`, `node_coordinates`, `physical_faces`, etc. For example, you can check the total number of nodes and faces in your loaded mesh:" ] }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Dict{String, Vector{Int32}} with 6 entries:\n", - " \"triangle\" => [5401, 5402, 5403, 5404, 5405, 5406, 5407, 5408, 5409, 5410 … …\n", - " \"bottom\" => [1, 2, 3, 4, 5, 6, 7, 8, 9, 10 … 3385, 3386, 3387, 3388, 3389…\n", - " \"circle\" => [6609, 6610, 6611, 6612, 6613, 6614, 6615, 6616, 6617, 6618 … …\n", - " \"top\" => [7053, 7054, 7055, 7056, 7057, 7058, 7059, 7060, 7061, 7062 … …\n", - " \"square\" => [6053, 6054, 6055, 6056, 6057, 6058, 6059, 6060, 6061, 6062 … …\n", - " \"sides\" => [3395, 3396, 3397, 3398, 3399, 3400, 3401, 3402, 3403, 3404 … …" + "(7475, [7475, 41858, 63541, 29160])" ] }, + "execution_count": 17, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "GT.physical_faces(mesh,2)" + "GT.num_nodes(mesh), GT.num_faces(mesh)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "where the latter array output by `num_faces` gathers information on the number of $0D$ (nodes), $1D$ (lines), $2D$ (triangles?), and $3D$ (tetrahedral?) faces. \n", + "\n", + "If you want, you can also access the position vectors $x_{i}=(x_1,x_2,x_3)$ of each node $i$ in the mesh:" ] }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Dict{String, Vector{Int32}} with 1 entry:\n", - " \"volume\" => [1, 2, 3, 4, 5, 6, 7, 8, 9, 10 … 29151, 29152, 29153, 29154, 29…" + "7475-element Vector{StaticArraysCore.SVector{3, Float64}}:\n", + " [0.0, 0.0, 0.0]\n", + " [1.5, 0.0, 0.0]\n", + " [1.5, 1.0, 0.0]\n", + " [0.0, 1.0, 0.0]\n", + " [0.095, 0.2, 0.0]\n", + " [0.63, 0.2, 0.0]\n", + " [0.3625, 0.675, 0.0]\n", + " [0.58, 0.5, 0.0]\n", + " [0.94, 0.5, 0.0]\n", + " [0.94, 0.86, 0.0]\n", + " [0.58, 0.86, 0.0]\n", + " [1.0, 0.39, 0.0]\n", + " [1.38, 0.39, 0.0]\n", + " ⋮\n", + " [0.6139875445382094, 0.4291099956974653, 0.07620766137880404]\n", + " [1.018820603903195, 0.5835488719740961, 0.1178301433344384]\n", + " [1.468372621304459, 0.3167189270535148, 0.08909060159961962]\n", + " [0.1806463128669575, 0.05567344069086867, 0.121587118230767]\n", + " [0.7265068184253736, 0.06797205524672663, 0.1232031560754262]\n", + " [1.470041808060199, 0.7146914675810988, 0.06742882101485732]\n", + " [0.4065025834426161, 0.8576895536696636, 0.08533633828561348]\n", + " [0.4430988134021598, 0.6529389841406555, 0.1232060341691886]\n", + " [0.9322295533397462, 0.9286533831291607, 0.1210197504572378]\n", + " [1.049623143250591, 0.829259829515705, 0.1242986642343036]\n", + " [0.3580932193740206, 0.02808866532662774, 0.04155394970851191]\n", + " [0.2251334943566448, 0.5163151069021665, 0.02626007329870325]" ] }, + "execution_count": 18, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "GT.physical_faces(mesh,3)" + "GT.node_coordinates(mesh)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Computational domains" + "Or, even access the node composition (in terms of node indexes) of all $3D$ faces:" ] }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "GalerkinToolkit.PhysicalDomain(…)" + "29160-element PartitionedArrays.JaggedArray{Int32, Int32}:\n", + " [776, 1429, 5550, 6016]\n", + " [1329, 5691, 5657, 6088]\n", + " [4756, 3588, 5682, 7070]\n", + " [4332, 5605, 5615, 5919]\n", + " [5656, 5912, 2862, 6808]\n", + " [5891, 5965, 1212, 6969]\n", + " [4866, 5702, 5607, 6073]\n", + " [1621, 1953, 1165, 5618]\n", + " [5414, 5887, 5340, 6945]\n", + " [5350, 5310, 5682, 6309]\n", + " [5249, 6207, 5864, 6509]\n", + " [1244, 5678, 5946, 6190]\n", + " [884, 5537, 6213, 7003]\n", + " ⋮\n", + " [6986, 3691, 4068, 4615]\n", + " [5061, 543, 3293, 4317]\n", + " [3293, 543, 5061, 3291]\n", + " [3293, 6072, 5061, 4317]\n", + " [5061, 6072, 3293, 3291]\n", + " [7130, 6683, 7038, 5486]\n", + " [7130, 2906, 6683, 2904]\n", + " [6683, 2906, 7130, 7038]\n", + " [7426, 6735, 6535, 4507]\n", + " [7426, 6535, 6735, 5858]\n", + " [5805, 4024, 4535, 5125]\n", + " [5805, 4535, 4024, 6788]" ] }, + "execution_count": 21, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "Ω = GT.interior(mesh;physical_names=[\"volume\"])" + "GT.face_nodes(mesh,3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finally, we can also check the node composition of each physical $2D$ faces of the problem:" ] }, { "cell_type": "code", - "execution_count": 78, + "execution_count": 6, "metadata": {}, "outputs": [ - { - "data": { - "image/png": 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", - "text/html": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, { "data": { "text/plain": [ - "GLMakie.Screen(...)" + "Dict{String, Vector{Int32}} with 6 entries:\n", + " \"triangle\" => [5401, 5402, 5403, 5404, 5405, 5406, 5407, 5408, 5409, 5410 … …\n", + " \"bottom\" => [1, 2, 3, 4, 5, 6, 7, 8, 9, 10 … 3385, 3386, 3387, 3388, 3389…\n", + " \"circle\" => [6609, 6610, 6611, 6612, 6613, 6614, 6615, 6616, 6617, 6618 … …\n", + " \"top\" => [7053, 7054, 7055, 7056, 7057, 7058, 7059, 7060, 7061, 7062 … …\n", + " \"square\" => [6053, 6054, 6055, 6056, 6057, 6058, 6059, 6060, 6061, 6062 … …\n", + " \"sides\" => [3395, 3396, 3397, 3398, 3399, 3400, 3401, 3402, 3403, 3404 … …" ] }, + "execution_count": 6, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "plt = GT.plot(Ω)\n", - "fig = Makie.plot(plt;shading=Makie.NoShading,color=:blue)\n", - "display(fig)" + "GT.physical_faces(mesh,2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Computational domains\n", + "\n", + "The discretization of the computational domain. Instantiation of `PhysicalDomain`." ] }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 36, "metadata": {}, "outputs": [ { @@ -314,120 +361,144 @@ "GalerkinToolkit.PhysicalDomain(…)" ] }, + "execution_count": 36, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "Γd = GT.boundary(mesh;physical_names=[\"sides\"])" + "Ω = GT.interior(mesh;physical_names=[\"volume\"])" ] }, { "cell_type": "code", - "execution_count": 80, + "execution_count": 37, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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"text/html": [ - "" + "" ] }, + "execution_count": 37, "metadata": {}, - "output_type": "display_data" - }, + "output_type": "execute_result" + } + ], + "source": [ + "GLMakie.plot(Ω;shading=Makie.NoShading,color=:blue)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Definition and visualization of the Dirichlet boundary $\\Gamma_{\\rm D}$. This corresponds to the \"sides\" of the model." + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ { "data": { "text/plain": [ - "GLMakie.Screen(...)" + "GalerkinToolkit.PhysicalDomain(…)" ] }, + "execution_count": 38, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "plt = GT.plot(Γd)\n", - "fig = Makie.plot(plt;shading=Makie.NoShading,color=:blue)\n", - "display(fig)" + "Γd = GT.boundary(mesh;physical_names=[\"sides\"])" ] }, { "cell_type": "code", - "execution_count": 81, + "execution_count": 39, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "GalerkinToolkit.PhysicalDomain(…)" + "image/png": 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", + "text/html": [ + "" ] }, + "execution_count": 39, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "Γ = GT.boundary(mesh;physical_names=[\"circle\", \"triangle\", \"square\"])" + "GLMakie.plot(Γd;shading=Makie.NoShading,color=:blue)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Definition and visualization of Neumann boundary $\\Gamma_{\\rm N}$. This defines the walls of the circular ($\\Gamma_{\\rm B}$ boundary), triangular ($\\Gamma_{\\rm G}$ boundary), and square ($\\Gamma_{\\rm Y}$ boundary) holes, identified in the model with the names \"circle\", \"triangle\" and \"square\" respectively." ] }, { "cell_type": "code", - "execution_count": 82, + "execution_count": 40, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", - "text/html": [ - "" + "text/plain": [ + "GalerkinToolkit.PhysicalDomain(…)" ] }, + "execution_count": 40, "metadata": {}, - "output_type": "display_data" - }, + "output_type": "execute_result" + } + ], + "source": [ + "Γn = GT.boundary(mesh;physical_names=[\"circle\", \"triangle\", \"square\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ { "data": { - "text/plain": [ - "GLMakie.Screen(...)" + "image/png": 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+ "text/html": [ + "" ] }, + "execution_count": 41, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "plt = GT.plot(Γ)\n", - "fig = Makie.plot(plt;shading=Makie.NoShading,color=:blue)\n", - "display(fig)" + "GLMakie.plot(Γn;shading=Makie.NoShading,color=:blue)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The previous line generates four different files `model_0.vtu`, `model_1.vtu`, `model_2.vtu`, and `model_3.vtu` containing the vertices, edges, faces, and cells present in the discrete model. Moreover, you can easily inspect which boundaries are defined within the model.\n", - "\n", - "For instance, if you want to see which faces of the model are on the boundary $\\Gamma_{\\rm B}$ (i.e., the walls of the circular perforation), open the file `model_2.vtu` and chose coloring by the element field \"circle\". You should see that only the faces on the circular hole have a value different from zero (see next figure).\n", - "\n", - "![](../docs/src/assets/poisson/fig_faces_on_circle.png)\n", - "\n", - "It is also possible to see which vertices are on the Dirichlet boundary $\\Gamma_{\\rm D}$. To do so, open the file `model_0.vtu` and chose coloring by the field \"sides\" (see next figure).\n", - "\n", - "![](../docs/src/assets/poisson/fig_vertices_on_sides.png)\n", - "\n", - "That is, the boundary $\\Gamma_{\\rm B}$ (i.e., the walls of the circular hole) is called \"circle\" and the Dirichlet boundary $\\Gamma_{\\rm D}$ is called \"sides\" in the model. In addition, the walls of the triangular hole $\\Gamma_{\\rm G}$ and the walls of the square hole $\\Gamma_{\\rm Y}$ are identified in the model with the names \"triangle\" and \"square\" respectively. You can easily check this by opening the corresponding file in Paraview.\n", - "\n", - "\n", "## FE spaces\n", "\n", - " Once we have a discretization of the computational domain, the next step is to generate a discrete approximation of the finite element spaces $V_0$ and $U_g$ (i.e. the test and trial FE spaces) of the problem. To do so, first, we are going to build a discretization of $V_0$ as the standard Conforming Lagrangian FE space (with zero boundary conditions) associated with the discretization of the computational domain. The approximation of the FE space $V_0$ is built as follows:" + "Once we have a discretization of the computational domain, the next step is to generate a discrete approximation of the finite element spaces $V_0$ and $U_g$ (i.e. the test and trial FE spaces) of the problem. To do so, first, we are going to build a discretization of $V_0$ as the standard Conforming Lagrangian FE space (with zero boundary conditions) associated with the discretization of the computational domain. The approximation of the FE space $V_0$ is built as follows:" ] }, { "cell_type": "code", - "execution_count": 86, + "execution_count": 43, "metadata": {}, "outputs": [ { @@ -436,8 +507,9 @@ "GalerkinToolkit.LagrangeSpace(…)" ] }, + "execution_count": 43, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -449,24 +521,31 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Here, we have used the `TestFESpace` constructor, which constructs a particular FE space (to be used as a test space) from a set of options described as positional and key-word arguments. The first positional argument is the model on top of which we want to build the space. The second positional argument contains information about the type of FE interpolation (the reference FE in this case). With `ReferenceFE(lagrangian,Float64,order)` We select a scalar-valued Lagrangian reference FE of order 1, where the value of the shape functions will be represented with 64-bit floating point numbers. With the key-word argument `conformity` we define the regularity of the interpolation at the boundaries of the cells in the mesh. Here, we use `conformity=:H1`, which means that the resulting interpolation space is a subset of $H^1(\\Omega)$ (i.e., continuous shape functions). On the other hand, we pass the identifiers of the Dirichlet boundary via the `dirichlet_tags` argument. In this case, we mark as Dirichlet all objects of the discrete model identified with the `\"sides\"` tag. Since this is a test space, the corresponding shape functions vanishes at the Dirichlet boundary.\n", + "### TO BE EDITED...\n", + "\n", + "Here, we have used the `lagrange_space` constructor, which constructs a particular FE space (to be used as a test space) from a set of options described as positional and key-word arguments. The first positional argument is the model on top of which we want to build the space. The second positional argument contains information about the type of FE interpolation (the reference FE in this case). Here, we select a scalar-valued Lagrangian FE of order 1.\n", + "\n", + "\n", + "where the value of the shape functions will be represented with 64-bit floating point numbers. With the key-word argument `conformity` we define the regularity of the interpolation at the boundaries of the cells in the mesh. Here, we use `conformity=:H1`, which means that the resulting interpolation space is a subset of $H^1(\\Omega)$ (i.e., continuous shape functions). On the other hand, we pass the identifiers of the Dirichlet boundary via the `dirichlet_tags` argument. In this case, we mark as Dirichlet all objects of the discrete model identified with the `\"sides\"` tag. Since this is a test space, the corresponding shape functions vanishes at the Dirichlet boundary.\n", + "\n", "\n", "Once the space $V_0$ is discretized in the code, we proceed with the approximation of the trial space $U_g$." ] }, { "cell_type": "code", - "execution_count": 85, + "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "GalerkinToolkit.DiscreteField(…)" + "(GalerkinToolkit.Quantity(…), GalerkinToolkit.DiscreteField(…))" ] }, + "execution_count": 44, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ @@ -474,82 +553,90 @@ "g = GT.analytical_field(Ω) do x\n", " 2.0\n", "end\n", - "GT.interpolate_dirichlet!(g,uhd)" + "GT.interpolate_dirichlet!(g,uhd)\n", + "\n", + "g, uhd" ] }, { "cell_type": "code", - "execution_count": 96, + "execution_count": 37, "metadata": {}, "outputs": [ { - "ename": "UndefVarError", - "evalue": "UndefVarError: `vtk_plot` not defined in `WriteVTK`\nSuggestion: check for spelling errors or missing imports.", - "output_type": "error", - "traceback": [ - "UndefVarError: `vtk_plot` not defined in `WriteVTK`\n", - "Suggestion: check for spelling errors or missing imports.\n", - "\n", - "Stacktrace:\n", - " [1] getproperty(x::Module, f::Symbol)\n", - " @ Base ./Base.jl:42\n", - " [2] top-level scope\n", - " @ ~/Library/CloudStorage/OneDrive-NetherlandseScienceCenter/Documents/NLeSC_Projects/HP2SIM/GalerkinToolkit.jl/notebooks/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X30sZmlsZQ==.jl:1" - ] + "data": { + "image/png": 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+ "text/html": [ + "" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "WriteVTK.vtk_plot(\"Γd\",Γd) do plt\n", + "WriteVTK.vtk_grid(\"Γd\",Γd) do plt\n", " GT.plot!(plt,g;label=\"g\")\n", "end\n", - "#GT.plot!(plt,g;label=\"g\")\n", - "#Makie.plot(plt,color=GT.NodeData(\"g\"))" + "\n", + "# Plot `Quantity <: AbstractQuantity` instances with Makie\n", + "plt = GT.plot(Γd)\n", + "GT.plot!(plt,g;label=\"g\")\n", + "GLMakie.plot(plt,color=GT.NodeData(\"g\"))" ] }, { "cell_type": "code", - "execution_count": 95, + "execution_count": 47, "metadata": {}, "outputs": [ { - "ename": "UndefVarError", - "evalue": "UndefVarError: `vtk_plot` not defined in `GalerkinToolkit`\nSuggestion: check for spelling errors or missing imports.", - "output_type": "error", - "traceback": [ - "UndefVarError: `vtk_plot` not defined in `GalerkinToolkit`\n", - "Suggestion: check for spelling errors or missing imports.\n", - "\n", - "Stacktrace:\n", - " [1] getproperty(x::Module, f::Symbol)\n", - " @ Base ./Base.jl:42\n", - " [2] top-level scope\n", - " @ ~/Library/CloudStorage/OneDrive-NetherlandseScienceCenter/Documents/NLeSC_Projects/HP2SIM/GalerkinToolkit.jl/notebooks/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X31sZmlsZQ==.jl:1" - ] + "data": { + "image/png": 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+ "text/html": [ + "" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "WriteVTK.vtk_plot(\"Ω\",Ω) do plt\n", + "WriteVTK.vtk_grid(\"Ω\",Ω) do plt\n", " GT.plot!(plt,uhd;label=\"uhd\")\n", "end\n", - "#GT.plot!(plt,uhd;label=\"uhd\")\n", - "#Makie.plot(plt,color=GT.NodeData(\"uhd\"))" + "\n", + "# Plot `DiscreteField <: AbstractQuantity` instances using Makie\n", + "plt = GT.plot(Ω)\n", + "GT.plot!(plt,g;label=\"uhd\")\n", + "GLMakie.plot(plt,color=GT.NodeData(\"uhd\"))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "To this end, we have used the `TrialFESpace` constructors. Note that we have passed a function representing the value of the Dirichlet boundary condition, when building the trial space.\n", + "## Numerical integration\n", "\n", + "Once we have built the interpolation spaces, the next step is to set up the machinery to perform the integrals in the weak form numerically. Here, we need to compute integrals on the interior of the domain $\\Omega$ and on the Neumann boundary $\\Gamma_{\\rm N}$. In both cases, we need two main ingredients. We need to define an integration mesh (i.e. a triangulation of the integration domain), plus a Gauss-like quadrature in each of the cells in the triangulation. \n", "\n", - "## Numerical integration\n", + "### TO BE EDITED...\n", "\n", - "Once we have built the interpolation spaces, the next step is to set up the machinery to perform the integrals in the weak form numerically. Here, we need to compute integrals on the interior of the domain $\\Omega$ and on the Neumann boundary $\\Gamma_{\\rm N}$. In both cases, we need two main ingredients. We need to define an integration mesh (i.e. a triangulation of the integration domain), plus a Gauss-like quadrature in each of the cells in the triangulation. In Gridap, integration meshes are represented by types inheriting from the abstract type `Triangulation`. For integrating on the domain $\\Omega$, we build the following triangulation and the corresponding Lebesgue measure, which will allow to write down integrals in a syntax similar to the usual mathematical notation." + "In Gridap, integration meshes are represented by types inheriting from the abstract type `Triangulation`. For integrating on the domain $\\Omega$, we build the following triangulation and the corresponding Lebesgue measure, which will allow to write down integrals in a syntax similar to the usual mathematical notation." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Compute $\\Omega$ integration domain" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 48, "metadata": {}, "outputs": [ { @@ -558,28 +645,37 @@ "GalerkinToolkit.Measure(…)" ] }, - "execution_count": 18, + "execution_count": 48, "metadata": {}, "output_type": "execute_result" } ], "source": [ "degree = 2*order\n", - "dΩ = GT.measure(Ω,degree) # TODO fix pretty printing in GalerkinToolkit.Measure" + "dΩ = GT.measure(Ω,degree)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ + "### TO BE EDITED...\n", + "\n", "Here, we build a triangulation from the cells of the model and build (an approximation of) the Lebesgue measure using a quadrature rule of degree 2 in the cells of this triangulation. This is enough for integrating the corresponding terms of the weak form exactly for an interpolation of order 1.\n", "\n", "On the other hand, we need a special type of triangulation, represented by the type `BoundaryTriangulation`, to integrate on the boundary. Essentially, a `BoundaryTriangulation` is a particular type of `Triangulation` that is aware of which cells in the model are touched by faces on the boundary. We build an instance of this type from the discrete model and the names used to identify the Neumann boundary as follows:" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Compute $\\Gamma_{\\rm N}$ integration domain" + ] + }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 49, "metadata": {}, "outputs": [ { @@ -588,13 +684,13 @@ "GalerkinToolkit.Measure(…)" ] }, - "execution_count": 19, + "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "dΓ = GT.measure(Γ,degree)" + "dΓn = GT.measure(Γn,degree)" ] }, { @@ -606,7 +702,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 50, "metadata": {}, "outputs": [ { @@ -615,13 +711,14 @@ "∇ (generic function with 1 method)" ] }, - "execution_count": 20, + "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "using ForwardDiff\n", + "\n", "gradient(u) = x->ForwardDiff.gradient(u,x)\n", "∇(u,x) = GT.call(gradient,u)(x)" ] @@ -630,8 +727,6 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "In addition, we have created a quadrature of degree 2 on top of the cells in the triangulation for the Neumann boundary.\n", - "\n", "## Weak form\n", "\n", "With all the ingredients presented so far, we are ready to define the weak form. This is done by defining functions representing the bi-linear and linear forms:" @@ -639,7 +734,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 51, "metadata": {}, "outputs": [ { @@ -648,7 +743,7 @@ "l (generic function with 1 method)" ] }, - "execution_count": 21, + "execution_count": 51, "metadata": {}, "output_type": "execute_result" } @@ -662,7 +757,7 @@ " 3.0\n", "end\n", "a(u,v) = GT.∫( x->∇(u,x)⋅∇(v,x), dΩ)\n", - "l(v) = GT.∫( x->v(x)*f(x), dΩ) + GT.∫( x->v(x)*h(x),dΓ)" + "l(v) = GT.∫( x->v(x)*f(x), dΩ) + GT.∫( x->v(x)*h(x),dΓn)" ] }, { @@ -678,21 +773,22 @@ "source": [ " ## FE Problem\n", "\n", + "### TO BE EDITED...\n", " At this point, we can build the FE problem that, once solved, will provide the numerical solution we are looking for. A FE problem is represented in Gridap by types inheriting from the abstract type `FEOperator` (both for linear and nonlinear cases). Since we want to solve a linear problem, we use the concrete type `AffineFEOperator`, i.e., a problem represented by a matrix and a right hand side vector." ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 52, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "([5.2150170844097e-310, 2.787823149e-314, 2.787823149e-314, 8.487983168e-314, 2.121995792e-314, 5.2150256584581e-310, NaN, NaN, 5.2150170844097e-310, 2.121995791e-314 … NaN, NaN, NaN, 2.8843385805e-314, NaN, 3.141768011e-314, NaN, 2.8834005396e-314, NaN, 2.8843373987e-314], sparse([1, 22, 74, 289, 337, 338, 339, 340, 341, 1872 … 6303, 335, 465, 467, 468, 1806, 6201, 6224, 6232, 6304], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 6303, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304], [0.06443080405538211, -0.0011816946972152084, -0.0019141180663583925, -0.03255921926190384, -0.013954244941888471, -0.009620087896820673, -0.0021278804315064915, -0.004654033162377993, -0.005173786773138719, 0.003329780400807812 … 0.21999530084991323, -0.015615599976174236, 0.003972555304119093, -0.009088995023018824, -0.00030902681072076353, -0.013784861561036393, -0.014076977113079436, -0.024457375688586837, -0.013734513123868308, 0.17287503833373258], 6304, 6304), [0.001567735161920194, 0.0015207565876126676, 0.0015232957017090138, 0.0016182302571138272, 0.0013414312146763385, 0.0014776038723584638, 0.001306589310230424, 0.0014160610368619702, 0.0014136920830547547, 0.001413925912088446 … 0.09466909943634595, 3.837716427462897e-5, 4.067983156302628e-5, 3.407470822273103e-5, 3.41027317460599e-5, 0.08456444214161216, 0.07001671663821094, 3.708312001443067e-5, 3.516169468651288e-5, 0.17159606501883534])" + "([7.291212384108405e-304, 2.121995791e-314, 2.834986376732e-311, 4.0474e-320, 2.529418982843e-311, 0.0, 0.0, 0.0, 7.71e-321, 6.76e-321 … 5.439857071e-314, 2.121995795e-314, 2.121995791e-314, 5.21501990224866e-310, 2.6300848696e-314, NaN, 0.0, 2.794628673e-314, 0.0, 5.21501729013624e-310], sparse([1, 22, 74, 289, 337, 338, 339, 340, 341, 1872 … 6303, 335, 465, 467, 468, 1806, 6201, 6224, 6232, 6304], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 6303, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304], [0.06443080405538211, -0.0011816946972152084, -0.0019141180663583925, -0.03255921926190384, -0.013954244941888471, -0.009620087896820673, -0.0021278804315064915, -0.004654033162377993, -0.005173786773138719, 0.003329780400807812 … 0.21999530084991323, -0.015615599976174236, 0.003972555304119093, -0.009088995023018824, -0.00030902681072076353, -0.013784861561036393, -0.014076977113079436, -0.024457375688586837, -0.013734513123868308, 0.17287503833373258], 6304, 6304), [0.0015677351619201938, 0.0015207565876126684, 0.0015232957017090134, 0.0016182302571138272, 0.0013414312146763385, 0.0014776038723584638, 0.001306589310230424, 0.0014160610368619696, 0.0014136920830547547, 0.0014139259120884476 … 0.09466909943634595, 3.837716427462898e-5, 4.067983156302676e-5, 3.40747082227309e-5, 3.410273174605993e-5, 0.08456444214161216, 0.07001671663821094, 3.7083120014430675e-5, 3.516169468651288e-5, 0.17159606501883534])" ] }, - "execution_count": 22, + "execution_count": 52, "metadata": {}, "output_type": "execute_result" } @@ -705,16 +801,17 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Note that the `AffineFEOperator` object representing our FE problem is built from the function `a` and `b` representing the weak form and test and trial FE spaces `V0` and `Ug`.\n", - "\n", - " ## Solver phase\n", + "## Solver phase\n", "\n", - " We have constructed a FE problem, the last step is to solve it. In Gridap, FE problems are solved with types inheriting from the abstract type `FESolver`. Since this is a linear problem, we use a `LinearFESolver`:" + " We have constructed a FE problem, the last step is to solve it. \n", + " \n", + "### TO BE EDITED...\n", + "In Gridap, FE problems are solved with types inheriting from the abstract type `FESolver`. Since this is a linear problem, we use a `LinearFESolver`:" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 32, "metadata": {}, "outputs": [ { @@ -722,34 +819,34 @@ "text/plain": [ "6304-element Vector{Float64}:\n", " 2.288817650800605\n", - " 3.191214461559075\n", - " 3.243769827996373\n", - " 4.513021960049178\n", - " 4.137978510723658\n", - " 2.6511832145611978\n", + " 3.191214461559076\n", + " 3.2437698279963745\n", + " 4.51302196004918\n", + " 4.137978510723659\n", + " 2.651183214561197\n", " 3.9985286410715637\n", " 2.3676403246611577\n", " 2.6253865316943625\n", " 3.1924629585377917\n", " 2.2896951265865444\n", - " 3.1863629312428015\n", - " 3.2445741024920083\n", + " 3.1863629312428032\n", + " 3.244574102492009\n", " ⋮\n", - " 4.285487712910332\n", + " 4.285487712910334\n", " 2.9668852150686487\n", " 2.020241401823711\n", - " 2.3980575528123094\n", - " 3.9912082231886825\n", + " 2.3980575528123103\n", + " 3.991208223188683\n", " 3.6282800936694914\n", - " 3.817091127051113\n", + " 3.817091127051114\n", " 2.0771951682489314\n", " 2.0995109886643184\n", - " 2.4363879401098405\n", - " 4.398698443572705\n", + " 2.4363879401098414\n", + " 4.398698443572706\n", " 2.0089547066118425" ] }, - "execution_count": 23, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -762,12 +859,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - " `LinearFESolver` objects are built from a given algebraic linear solver. In this case, we use a LU factorization. Now we are ready to solve the FE problem with the FE solver as follows:" + "### TO BE EDITED...\n", + "\n", + "`LinearFESolver` objects are built from a given algebraic linear solver. In this case, we use a LU factorization. Now we are ready to solve the FE problem with the FE solver as follows:" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 53, "metadata": {}, "outputs": [ { @@ -776,7 +875,7 @@ "GalerkinToolkit.DiscreteField(…)" ] }, - "execution_count": 24, + "execution_count": 53, "metadata": {}, "output_type": "execute_result" } @@ -794,7 +893,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 55, "metadata": {}, "outputs": [ { @@ -804,13 +903,13 @@ " \"Ω.vtu\"" ] }, - "execution_count": 25, + "execution_count": 55, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "GT.vtk_plot(\"Ω\",Ω) do plt\n", + "WriteVTK.vtk_grid(\"Ω\",Ω) do plt\n", " GT.plot!(plt,uhd;label=\"uhd\")\n", " GT.plot!(plt,uh;label=\"uh\")\n", "end" @@ -820,10 +919,6 @@ "cell_type": "markdown", "metadata": {}, "source": [ - " which will generate a file named `results.vtu` having a nodal field named `\"uh\"` containing the solution of our problem (see next figure).\n", - "\n", - "![](../docs/src/assets/poisson/fig_uh.png)\n", - "\n", "## References\n", "\n", "[1] C. Johnson. *Numerical Solution of Partial Differential Equations by the Finite Element Method*. Dover Publications, 2009." From 16e461f9caa2408ba9b097e700835c037e7e39fb Mon Sep 17 00:00:00 2001 From: Cmurilochem Date: Fri, 18 Oct 2024 08:19:56 +0200 Subject: [PATCH 13/14] Add Makie plots of DiscreteField --- notebooks/t001_poisson.ipynb | 140 ++++++++++++++++++----------------- 1 file changed, 71 insertions(+), 69 deletions(-) diff --git a/notebooks/t001_poisson.ipynb b/notebooks/t001_poisson.ipynb index bf80bc4e..667f9c20 100644 --- a/notebooks/t001_poisson.ipynb +++ b/notebooks/t001_poisson.ipynb @@ -116,17 +116,17 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { - "image/png": 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1PGPUOj09XS6XWZZVVXV1dbVYLCaTSRzHvu/3er26rkWk1+vJS+r3+9PpNEmS9Xqd5/lyuVy1BoNB2BqNRkopAQB80hgBAAAvoGma9XqdZVlRFNZapdRkMonjOAxDY4z8Jk1L3lvTNKvVarFYlGV5PB57vV4URdPpdDwea63lXXa7XdM0IuJ5nlJK3qXf70+n0ziO1+t1nufFOzzPi6KoaRoR0VrLnSilxq2zs7PlcpllWVVVV1dX19fXk8kkiqIgCPr9vgAAPjmMAACA91XXdVmWaZqWZVnXda/Xi6IoSZLJZKK1lvfVNI1SSt7leDwul8vFYlFVVdM0/X4/juMkSUajkby37XYrLdd15b1prSet09PToijyPN9sNr/61a+22+16vfY8r65rrbXcVb/fn06nSZKs1+s8z5fLZdkaDAZhazQaKaUEAPCxZwQAALyHw+GQ53mappvNpmmafr8/nU6TJBkOh/LClFJaa3nHfr8viiJN081mIyKu60ZRFMex67ryPGtlt5Nfc13p9+XXdrudtDzPkxcwGAxOT09PTk7Ksszz/Be/+MV6vX769KnWOo7jMAwdx5G7UkqNW6enp2VZZllWVdXV1dXNzc14PI6iKAxDY4w843A4aK1VSwAAHwNGAADAu+x2u6x1e3srIp7nxS3HceSF1XXdNI1SSlq73S5r3d7eishoNIrjOIqifr8vz7BWdjt54w35r/9V/vqv5df+6I/k3/07efRIttuttFzXlRemtQ5bSqnD4TAYDNaty8vLMAyjKBqPx0opuSvHcabTaZIk6/U6y7Llclm2Li8vwzCMomg0GknrcDi8/fbbxpg/+IM/0FoLAOB3zQgAAHhGVVVpmhZFcTgclFKTySRJkiAIjDHy8pqmUUqt1+vlclkUhbVWKeX7fpIkYRhqreUZ1sp8Lufn8tZbstuJtfL3/s//kf/23+TRI/nSlwKRvoj1PE9enjEmCILPfOYzruvmeb5arW5ubhaLxXg8juM4CIJ+vy93pZQat/b7fVmWWZZVVXV1dXVzczOZTKIoCoKgruv9ft/r9ZRSAgD4GDACAABE6rouy3KxWJRl2TRNr9eL4zhJkvF4rLWWO6nrerPZbLdba62I9Hq9OI6TJJlMJkopeYa1Mp/L+bnM52KtvJu1cnEh/+N//L8inw+C/8+YyFrp9+Wl1HUtIo7jxHEcRdF2u82yrCiKVWswGIRhGMex53lKKbkrx3Gm02mSJOv1Osuy5TsGg4HjOLe3t+PxWCklAICPASMAAHSbtTbP8yzLNptN0zSO40RRFMfxcDiUuzocDsvl8vLy8vr6utfrJe8YDofyPGtlPpfzc5nPxVp5f8ejFvl/lstH/+W/1P/9v8v3v1+9+upwMNDyYo7Ho4horUVEKTVsnZ6eLpfLLMuqqrq6ulosFuPxOI5j3/eNMXJXSqlxa7/fL5fLPM+rqsrzPE3Tw+GQJEkQBMYYAQD8ThkBAKCrdrtd1rq9vRURz/PiluM4clf7/T7P8zRNt9uttdYYE0XRF77wBc/z5HnWynwu5+cyn4u18jL6+71cXMjXvz5++FD+43/Mv/KV0WjkyAc5Ho8iorWWZ/T7/el0miTJer3OsqwoimXL87wwDKMo8jxP7sFxnJOTk+l0ul6vf/KTn+R5vt1uf/rTnw4Gg6g1HA4FAPA7YgQAgI5pmma9Xi8Wi+VyeTgclFK+7ydJEgRBr9eTu9rtdmma5nl+e3urlBqNRuPx2BgzHA4Hg4G8w1rZ7eSNN+T112U+F2vlzqyVJ0/kn/7T6I//uPnX/3rx+PEwjof9vryXuq5FRGst76KUGrfOzs6KosiybLPZPH369Pr62vf9OI5939day10ppcbj8Ww22+12w+HQcZyqqi4vL6+vryeTSRzHvu8bYwQA8NEyAgBAZ9R1XRRFlmVlWTZN0+v1kiSJ43gymSil5E6aplmv12maFkVxOByUUkEQJEkSBMFut7u+vpZ3WCvzuZyfy1tvyW4n1spvhbXyox+pN99M/uzP5ItflO99r/zKV0au25N3qetaKaW1lvfmOM5sNptOp1VVZVm2XC7zPC+KYjgcRlEUhuFgMJC7OhwOvV5vOp3OZrP1ep3neVEUy9ZgMAjDMI7j4XAoAICPihEAADpgv98XRZFl2Xq9FhHHcaIoiuN4OBzKXdV1XZZlmqZlWdZ13ev1kiSJ43gymSil5B1a68NBvfmmnJ/LfC7WyofhcFBVJRcX8o1v+A8fNt/6VvHaa24Yuv2+/L26JSJaa/kgWmu/tdvtiqLIsmzdurq6CoIgiqLxeKy1lpd0OBxExBijtZ60zs7OilZVVVdXV4vFYjwex3Hs+74xRgAAHzIjAAB8qm232yzL8jy/vb0VkeFwmCRJGIaO48hdHQ6HoiiyLKuqqmmafr9/cnISx/FwOJRnNE1zOKj/9b/cf/Ev1Hwu1spHwFp58kS9+WbouvLggfzgB+tXXx06jhKRuq51S16Y67pnZ2cnJydlWWZZtlqtFotFmqbj8TiKoiAIHMeRF3Y8HkXEGCPvcBxnNptNp9P1ep3neVEUy5brumEYRlE0HA4FAPChMQIAwKdR0zRVVaVpWhTF8XhUSgVBEMdxEAS9Xk/uar/fZ63tdisinufFcRxF0WAwkOdZKz/6kf63//YP/vf/Hh4O8hGzVqyViwv52tdGjx7Jd79bfOlLbtM0IqK1lpfU6/Wi1mazyVur1mAwCMMwiqLRaCQfpGma4/GolDLGyPO01pPW2dlZURR5nq/X68vLy5ubm/F4HMex7/vGGAEA/LYZAQDg0+V4PC6XyzRNq6qq67rX6yWt8XislJK72m63aZrmeb7f75VSo9FoOp2GYWiMkedZK/O5nJ/LfO5ZK79b1srFhbz2WvjHf1w/fqz+0T9qjkctdzVsnZ6eFkWR5/lqtbq6urq5uZlMJnEc+75vjJH30DTN4XBQSmmt5T04jjObzabTaVVVeZ4v3+G6bhRFYRh6nqeUEgDAb4kRAAA+Lfb7fZ7nWZZtNhsRGQwGURTFcex5ntxDVVVpmuZ5fjwelVJBEEynU9/3tdbyDGtlt5M33pDXX5f5XKyVjw9r5Uc/0m+++UXHqf/oj/QPfrB69dXRYKDlTowx0+k0SZL1ep1l2fIdrutGLc/z5F2apqnrWinV6/XkfWmt/dZ+vy+KIs/z9Xr99OnT6+vryWQSRZHv+8YYAQDcmxEAAD75NptNlmV5nu/3exEZjUZxHIdh6DiO3FVd12VZLhaLsiybpun1eklrMpnI86yV+VzOz+Wtt2S3E2vl4+lwUIdD78kT+frXJw8fyre/vXz82PN9p9+XO1BKjVv7/b4oijzP1+v106dPr6+vfd+P49j3fa21vON4PNZ1rbXu9XryYhzHmc1m0+m0qqo8z5fLZdHyPC9sDYdDAQDcgxEAAD6xmqZZrVZZlhVFcTwetdZBECRJEgSB1lru6nA4FEWRpul6vW6axnGcKIriOB4Oh/I8a2U+l/Nzmc/FWvmksFaePJE33wxcVx48kB/+cPvKK16/L3fjOM5sNptOp1VVZVlWlmWe50VReJ4XtQaDgYjULWOM1lpehtbab+33+6IosizbbDZPnz69vr6eTCZRFPm+b4wRAMDLMwIAwCfQ8XhcLpeLxaKqqqZpjDFJkkyn0/F4LPew3++z1na7FRHP8+KW4zjyPGtlPpfzc5nPxVr5JLJWrJWLC/nqV71Hj+R73ytffXXoeUbuRGvtt3a7XVEUeZ5vt9vNZnN9fR0EQRRFWuu6ro0xSim5E8dxZrPZdDqtqirLsrIsi5bneWFrOBwKAOBlGAEA4BNlv99nre12KyKDwSBuua4r97DZbLKWtVYpNR6PkyQJw9AYI8+zVuZzOT+X+VyslU8Ba+XiQr7xDf/hw+ab38wfP/bC0O335W5c1z07Ozs5OVmtVlmWlWW5WCzSNNVal2XpeZ5SSu5Ba+23bm9vl8tllmWbzebp06fX19e+70dRNJlMjDECAHgBRgAA+ITYbDZZluV5vt/vlVKj0SiO4yiK+v2+3FXTNFVVpWlaFMXxeNRah2GYJInv+1preYa1stvJG2/I66/LfC7WyqeMtfLkiZrPo+98Rx48kB/8YP3KK95goOVOer1e2NpsNkVR5HmepmmWZcfjcTweR1E0Go2UUnIPg8FgNptNp9OqqrIsK8syb3meF7aGw6EAAN6XEQAAPt6aplmtVovFoizL4/GotQ6CYDqd+r6vtZa7qut6uVymaVqWZdM0vV4vSZLpdDoej+V51sp8Lufn8tZbstuJtfIpdjjIaiUXF/K1r40ePpTvfa949dXRcNiXuxq2ZrPZT3/60/V63TTN9fX1zc2N7/tRFAVBYIyRe9Ba+63b29uiKPI832w2T58+vb6+9n0/iqLJZGKMkefVda21FgDoPCMAAHxcHQ6H5XKZpmlVVU3T9Pv9KIqSJBmPx3IPh8OhKIrFYrHZbJqmGQwGYRgmSeJ5njzPWpnP5fxc5nOxVjrFWnnyRF57LXz4sPlX/yp9/NiL42G/L3djjBmPxycnJ2EYDgaDoiiWrcFgELWGw6Hcz2AwOD09PTk5qaoqy7KyLPOW53lhGEZR5HmevOOnP/3p4XCYTqdxHAsAdJgRAAA+fvb7fdbabrciMhgM4pbrunIPt7e3WWu324mI53lJkkRR5DiOPM9amc/l/Fzmc7FWOstaefJEzefJn/2ZfPGL8v3vr159dTQYaHl5h8NBKTWZTE5by+Uyz/Oqqi4vL29ubnzfj+N4Mpn0ej25B62139rtdsvlMs/zzWbz9OnT6+tr3/fjOJ5MJr1e73A4rFars7MzAYBuMwIAwMfJZrNJ0zTPc2utUmo0GiVJEkWRMUbuYbPZpGma57m1Vik1mUySJAmCwBgjz7NW5nM5P5f5XKwV/NrhIFUlFxfy9a9PHj6Ub3+7ePx46PtOvy8v7nA4iEiv1xMRx3FOTk6SJKmqKsuy5XKZtzzPi+M4DEPXdeV+3NbJyclqtcrzvCzLvOV5XhAEm81GKdXv9wUAus0IAAAfA3Vdr1arNE3Lsjwej1rrMAyTJPF9X2std9U0TVVVi8ViuVwej0etdRRFcRz7vq+1lmdYK7udvPGGvP66zOdireDdrJUnT+TNN0PXlQcP5Ic/3L7yitfvy4s4HA4iYoyRd2it/dbt7W1RFHmebzabX/7yl1dXV0EQxHE8Ho+11nIPWuugtdvtlstlnuebzaaqquvra9d1V6uV4zi9Xk8AoKuMAADwO3U4HIqiyLKsqqqmafr9ftwaj8dyD3VdF0WRZVlZlk3TGGNOTk7iOB6Px/I8a2U+l/Nzeest2e3EWsH7s1aslYsL+epXvUeP5HvfK199deh5Rt5b0zTH41EpZYyRdxkMBqenpycnJ2VZZllWlmWaplmWDYfDOI7DMHQcR+7HbZ2cnKxWq6urq8vLy+12+/Of/3yxWEQt13UFALrHCAAAvyO3t7d5nmdZtt1uRcR13TiOoyhyXVfu4XA4ZK31ei0ig8EgbrmuK8+zVuZzOT+X+VysFbwsa+XiQr7xDf/hw+ab38wePx6Godvvy7s1TXM8HkVEay3vQWsdtrbbbZ7nRVGsW5eXl2EYxnE8Go2UUnIPWusgCHq9Xp7nTdOMRqPtdvurX/3q6urK9/04jieTSa/XEwDoDCMAAHzk1ut1mqZFUVhrlVLj8ThJkjAMjTFyD7vdLs/zNE1vb29FZDgcJkkShqHjOPI8a2U+l/Nzmc/FWsF9WCtPnqj5PP7Od+TBA/nBD9avvOINBlqeUbe01sYY+SBeazablWWZZdlqtbq5uVksFuPxOI7jMAyNMXIPh8PBGBOG4ec///myLIuiWC6XeZ4XReG6bhzHYRi6risA0AFGAAD4qNR1XZZllmVlWR6Px16vF0VRHMe+72ut5R42m81isSiKwlqrlJpMJtPpNAiCXq8nz7NW5nM5P5f5XKwV/LYcDrJaycWFfO1ro4cP5d/8m/LxY28y6ff78mt1XR+PR92SF2OMiVvr9TrP86IoVq3Ly8uoNRwO5U72+72I9Pt9rXWcfGU/AAAgAElEQVTY2u12RVHkeb7dbn/5y19eXl76vh/Hse/7WmsBgE8vIwAAfPgOh0NRFGmartfrpmn6/X4cx0mSDIdDpZTcVdM0q9VqsViUZXk8Hnu9XhRF0+l0PB5rreV51sp8LufnMp+LtYIPibXy5Im8+abvuvLggbz++u5LXxrULcdxtNbykkat09PT5XKZZVlVVZeXl9fX177vR1EUBEGv15OXcTgcRKTf78s7XNc9OzubzWZlWeZ5XpZlnudFUXieF0VRGIau6woAfBoZAQDgw7Tb7fI8z7Jst9uJiOd5cRxHUTQYDOQejsfjcrlM03S1WjVN0+/34zhOkmQ0GsnzrJXdTt54Q15/XeZzsVbwEbBWrJWLC/mTP3EfPZL/8B+qJKk9r6eUkjvp9/vT6TRJkqqq8jwv3uF5XtRyXVdezH6/F5F+vy/P01qHrd1uVxRFnufb7Xaz2VxdXfm+H0WR7/taawGATxEjAAB8OKqqyrKsKAprrVJqMpnEcRyGoTFG7sFam+d5lmXr9VpEBoNB3HJdV55nrczncn4ub70lu51YK/joWSsXF/Knfzr9h//Q++f//Ff/8l/ug2DQ78vdKKUmrbOzs7y12Wx+9atfXV9f+74fx/FkMtFay/uy1opIv9+X9+C67tnZ2Ww2K8syy7KyLLMsy/Pc87woisIwdF1XAOBTwQgAAL9VdV2XZZmmaVmWdV33er0oipIkmUwmWmu5h91ul7Vub29FZDQaxXEcRVG/35fnWSvzuZyfy3wu1gp+5w4H+eu/Hv37f//7f/7n6sED+eEPt1/+sus4Su7KcZzT09OTk5OyLPM8Xy6XWZbleT4cDuM4DsPQcRz5TZqmORwOSql+vy/vS2sdtna7XVEUWZZtWldXV77vR1Hk+77WWgDgk8wIAAC/JYfDIc/zNE03m03TNP1+fzqdxnE8Go3kftbrdZqmRVFYa5VSvu8nSRIEQa/Xk+dZK/O5nJ/LfC7WCj5WDge1WsnFhXz1q96jR/Ld7y6/8pWR5xm5K6112NrtdlmWFUWxbl1eXoZhGEXReDxWSskzji2ttTFGXozrumdnZycnJ6vVKsuysiyzLMvzfDgchi3XdQUAPpmMAABwb7vdLmvd3t6KiOd5cctxHLmHpmlWq9VisSjL8ng89nq9KIqm0+lkMlFKyfOslflczs9lPhdrBR9n1srFhbz2WvDwYfPNb2aPHw/D0O335c5c1/3sZz87m83KssyyrKqqm5ubxWIxHo/jOA6CoN/vS6uu68Ph0Ov1tNbyMnq9Xtja7XZ5a7PZrNfrq6urIAiiKJpMJlprAYBPFCMAALyYxWJR17XneZPJRN5RVVWapkVRHA4HpdRkMkmSJAgCY4zcw/F4XC6Xi8Wiqqqmafr9fhzH0+l0OBzK86yV3U7eeENef13mc7FW8ElhrTx5oubz+DvfkQcP5Ac/WL/yijcYaLkrY0wcx1EUbbfbLMuKoli1BoNBGIZxHA+Hw8PhUNf1YDDQWsuduK77mc98ZjabrVarLMvKskzTNMuy4XAYtlzXFQD4hDACAMCLKYpiuVz+/u//vojUdV2W5WKxWK1WdV33er04jpMkGY/HWmu5h/1+XxRFmqabzUZEBoNB3HJdV55nrczncn4ub70lu51YK/gkOhxktZKLC/na10YPH8q3v718/Njzfaffl7tRSg1bZ2dnRVFkWbZer6+urm5ubiaTSb/fPx6P/X5fay330Ov1wtZut8tb69bV1VUQBFEUTSYTrbUAwMebEQAAXozWWkRub2+vr6+zLNtsNk3TOI4TRVEcx8PhUO5nt9tlrdvbWxEZjUZxyxgjz7NW5nM5P5f5XKwVfDpYK0+eyJtvBq4rDx7I66/vvvxlt9+XOzPGTKfTJEnW63WWZUVRLJfLqqrKstRab7dbz/Pk3lzX/cxnPjObzVarVZZlZVmmaZpl2XA4DFuu6woAfFwZAQDgxRwOh6IorLX9fl9EPM+LW47jyP1UVZVlWZ7nh8NBKRUEQRzHYRhqreV51sp8LufnMp+LtYJPH2vFWrm4kD/5E/fRI/nzP1+9+urQdXtyV0qpcevs7Kwoip/85CfW2qIofvzjH/u+H8ex7/taa7mfXq8XtrbbbZ7nRVGsW9fX177vx3E8Ho+11gIAHzNGAAD4IFVVLRaLv/u7v1sul8aYOI6n02kQBL1eT+6hruuyLLMsWy6XdV33er04jpMkmUwmSil5nrUyn8v5ucznYq3gU89aubiQf/JPJg8fNt/6VvH4sRcEg35f7sxxnNlsttlsDofDaDRSSuV5XhTFcDiMoigMw8FgIPfmtU5PT8uyzPO8LMs0TbMsGw6HURSFYTgYDAQAPjaMAADwHuq6Xi6XaZqWZdk0jVJqPB5/7nOf+73f+z2llNzD4XBYLpdpmlZV1TRNv9+fTqdJkgyHQ3kXa2U+l/Nzmc/FWkGnWCtPnqg33wzPz+XBA/nhD7df/rLrOEru6ng8ep73+c9/3nXdoiiyLFu3rq6ugiCIomgymSil5H56vV7U2m63eZ4XRbFuXV1d+b4fx/F4PNZayztub2/TNB0MBkEQGGMEAD4qRgAAeJf9fl8URZZl6/VaRBzHiaIojuMsyzzPU0rJXe33+zzP0zTdbrci4rpukiRRFA0GA3metbLbyRtvyOuvy3wu1go6y1qxVi4u5Ktf9R49ku9+t/jKV8aeZ+TlWWuVUsYY13XPzs5OTk7KssyybLVaLRaLNE3H43EURUEQOI4j9+a1ZrPZarXK87wsyzRNsywbDodRFIVhOBgMRMRae3l5ORwO4zgWAPgIGQEA4Bnb7TbLsjzPb29vRWQ4HCZJEoah4ziXl5ciUte13Ml2u03TNM/z/X6vlBqNRtPpNAxDY4w8z1qZz+X8XN56S3Y7sVaAv2etXFzIa6+FDx823/xm9tprXhR5/b68oLquj8ej1toYI61erxdFURiG2+02b61ag8EgDMMoikajkdybMSaKojAMd7tdnudFUaxbV1dXvu/Hcbzf75umcRxHKSUA8BEyAgCASNM0VVWlaVoUxfF4VEr5vp8kSRAEvV5PWlprEanrWl5SVVWLxaIoiuPxqJQKgiBJkiAItNbyPGtlPpfzc5nPxVoBfiNr5ckTNZ/Hritf/KJ8//vVq68OBwMtH+TQ0lobY+QZSqlh6/T0tCiKPM9Xq9XV1dXNzc1kMonj2Pd9Y4zcj1LKa81ms7Is8zxfrVZpmmZZtt/vd7tdkiQCAB8tIwCAbjsej8vlMsuysiybpun1eklrPB4rpeQZWmsRqetaXkxd12VZpmlalmVd171eL2mNx2OllDzPWpnP5fxc5nOxVoAPdDhIVcnFhXz96+OHD+Xb314+fuz5vtPvy3s5tlzX1VrLb2KMmU6nSZKs1+ssy5bvcF03iqIwDIfDodybMSaO4yiKtttt0VosFlVV9ft9pVQURZPJRCklAPDhMwIA6Kr9fl8URZqmm81GRAaDQRRFcRx7nie/Sa/XE5G6ruWDHA6HoijSNF2v103TOI4TRVEcx8PhUN7FWpnP5fxc5nOxVoCXZa08eSJvvhm4rjx4ID/84faVV7x+X97NWisixhillLw3pdS4td/vi6LI83y9Xj99+vT6+tr3/TiOfd/XWsv9KKWGrdlsttvt6rrWWi8WizRNh8NhHMdhGDqOIwDwYTICAOiezWaTZVme5/v9XkRGo1Ecx2EYOo4j701rLSJ1Xct72+/3WWu73YqI53lxy3EceZ61stvJG2/I66/LfC7WCnAf1oq1cnEhX/2q9+iRfO975Ve+MnLdnjzjcDg0TWOMUUrJC3AcZzabTafTqqqyLCvLMs/zoig8z4uiKAxD13Xl3rTWg8FgNpv9g3/wD3a7XZ7n69bl5WUQBFEUjcdjrbUAwIfACACgM5qmWa1WWZYVRXE8HpVSQRAkSRIEgdZaPohq1XUtv8lms8myLM/z/X6vlBqPx0mShGFojJHnWSvzuZyfy1tvyW4n1grwW2StXFzIN77hP3zYfOtbxWuvuWHo9vvya9ZaEXEcR16G1tpv7Xa7oijyPN9ut5vN5vr62vf9OI7H47HWWu7qcDhYa40xvu/HcTybzcqyzPN8tVotFos0TUejURRFYRg6jiMA8FtlBADQAcfjcblcLhaLqqqapjHGJEkynU5Ho5FSSl6M1lpE6rqW561WqzRNi6I4Ho9KqSAIptOp7/taa3metTKfy/m5zOdirQAfHmvlyRP15puh68qDB/Kf/tPmlVc8a62IGGPkTlzXPTs7m81mZVlmWVaWZZqmWZaNRqMoisIwdBxHXt5+v6/r2nXdXq8nIsaYuLXZbPI8L4qial1eXoat8XistRYA+G0wAgD4VNvv91lru92KyGAwiFuu68pL0lqLSN3SWtd1XZblYrEoy7Jpml6vlyTJdDodj8fyLtbKfC7n5zKfi7UCfDSsFWvl4kL+8T8ePnok/+yfHR4+FKUcuQetddjabrd5q2pdXV2FYRhF0Wg0UkrJC9vv903TOI6jlJJnDFunp6dlWWZZVlXVzc3NYrEYjUZRFIVh6DiOAMD9GAEAfEptNpssy/I83+/3SqnRaBTHcRRF/X5f7kRrrZRqmuZwOJRluVgsNptN0zSO40RRlCSJ53nyLtbKfC7n5zKfi7UC/E5YKxcX8j//5//tOP/XH/5h85//8+7LX3b7fbkPrzWbzcqyzLJstVpdX1/f3NxMJpM4joMgMMbIC9jv9yLiOI78JsaYuLXZbPJW1bq8vAzDMIqi0WiktRYAuBMjAIBPl7quq6pK03S5XB6PR611EATT6dT3fa213IPW+ng85nn+N3/zN7e3tyLieV7cchxH/n/24DdWjvO+D/13Zp75uzv/ntmzZyXaJoL8MczrBuCmKk3RKpw6UiRUbGAkQNIkvgWaoIgtF5sURfOyaAO5phUEl2/yIq8EpE5SBAd+U6CoQqDBRYGbJZIhkBRs4OLm1o4pnrO788yfnZ2d3Wd35xJjSJByKJnUObJInt/n825Soq5x4wauXUMcQ0oQ8pHbbJTNRvuLv8Dzz7PhEK++Ov/sZzumqeIEGGO8VZZlmqZZlhUt0zTDMOScW5alKAre22q1AmAYBt6X09rf3y+KQghRluV0Op3NZt1uN2gZhgFCCHlIDIQQQp4Um80mz/MkScqybJqGMdbr9aIo6na7OLGqqiaTyeHh4W63M03T933OeRAEjDG8m5SIY4xGuH0bdQ0pQcijRkqMx3jpJffiRXzpS/nVq7bnGbqOk+i29vf38zxP07Qsy8PDw+l06nke59x1XU3TcD9SSgCGYeABMMZ4q6oqIUSWZfPW4eFhEARhGHY6HVVVQQghD4aBEELI42+9XovWcrkEYJomb1mWhZNpmmY+nwshsixbr9dN01iW9UM/9EOcc1VV8W5SIo4xGiGOISUIecRJiZs3ceuWb1m4cAFf+9ryyhVb13EShmHs7e1FUVSWpRCiKIq0Zds25zwIAsuy8A673W69XiuKYhgGHobTGgwGeZ6naTqfz6fT6Ww263a7YRj6vm8YBggh5PthIIQQ8jirqipJkjRNpZSKonQ6nSiKwjBkjOFkdrtdnudJkhRF0TQNY2xvb09VVcaY67qqquIdpEQcYzRCHENKEPIYkRJSYjzGCy/YwyF+67eKz37WsW2GE1BV1WutVqs0TbMsq6rqzp07R0dHvu9zzrvdrqqqADYtxpiu63h4jLGotVgs0jTNsmzeMgzD933OeafTURQFhBDyHhgIIYQ8hna73Xw+T5KkKIrtdquqahAEURR5nqeqKk5ms9mkaZokSVVVTdOYphmGYRRFhmEsl8u6rne7Hd4iJeIYoxHiGFKCkMeXlBiP8Y//sXfxYvNrv5a9/LIVBJau4yRM0xwMBv1+vygKIURRFEmSCCE6nU4YhkEQbFqWZWmahhPotAaDQZ7naZrO5/PpdDqbzbrdbhiGvu8bhgFCCDmGgRBCyGNls9lkWSaEKMuyaRpd13mr2+3ixFarlWjVdQ3Atu0oisIwNAwDQNM0qqoCaJoGgJSIY4xGiGNICUKeDFLi5k3l1q3AsnDhAr761cWVK7ZpqjgBVVWD1nK5TNM0y7KydXh4yBir69rzPFVVcWKMsai1WCzSNM2ybN4yDMP3fc55p9NRFAWEEPIWBkIIIY+J1WqVpqkQYrlcArAsi7dM08SJVVWVJEmaplJKRVFc142iKAgCTdPwFkVRVFXdbJSiaP7rf8W1a4hjSAlCnjxSQkqMx3jxxc7Fi3jlleLqVafbZbqOk7Bb/X6/KAohxHw+F0JkWQYgaDHGcBo6rcFgkLXm8/l0Op3NZt1ul3PueZ5hGCCEEICBEELII2+xWCRJkmWZlFJRlG63G0VREASMMZxM0zTz+TxJkjzPt9utqqphGEZR5Lquqqp4Nynxl39p/7t/d+5//29ntYKUIOSJJyVu3sStW55l4cIFXLtWP/uspes4CcYYby0Wi7/+678uimK9Xn/7298+PDwMgoBz7jgOTgNjrNdaLBZpmmZZNm8ZhuH7Pue80+koigJCyBnGQAgh5FG12+3m83mSJEVRbLdbTdPCMOSce56nqipOZrfbZVmWJMl8Pm+aRtd13up2uzhGSsQxRiP8xV98bLNRQMgZIyWkxHiM55+3hkO8+ur8s5/tmKaKk+l0Or7vb7fbXq+32WzKsjw6OprNZq7rhmHo+76maTgNndb+/n6e52malmU5nU5ns1m32+Wce55nGAYIIWcSAyGEkEfPZrPJsixJksVi0TSNrutRFHHOO50OTkxKmaZpkiRVVQEwTZO3LMvCMVIijjEaIY4hJQAFhJxhUmI8xksvuRcv4ktfyq9etT3P0HV8MLvdbr1eM8YGg4Ft22VZpmmavcW27bBlWRZOg67rvV4viqLFYpG15i3TNH3fD8Ow0+koioJ32+12qqqCEPKEYiCEEPIoqes6TVMhRF3XAGzb5pyHYWiaJk6srmvRWq1WABzHiaIoDENd13GMlIhjjEaIY0gJQsjbpMTNm7h1y7csXLiAr31teeWKret4WNvtdrPZaJrGGFMUxW0NBoO0VVXVm2++eXR05Ps+59x1XVVVcWKKonRb+/v7eZ6naTqfzyeTyXQ67Xa7nHPf93Vdx1vW6/W3v/1t0zQ/9rGPMcZACHmyMBBCCHk0LBaLJEmyLJNSKoriui7nPAgCxhhObLFYJEmSZZmUUlEU13V7vZ7v+5qm4d2kRF3jxg1cu4Y4hpQghNyXlJAS4zFeeMEeDvHKK+XLL1vdLtN1PCAp5WazsSyLMYa3GIaxv7+/t7c3n8+FEHmeCyHSNHUch3MeBIFhGDgNuq73er0oihaLRZqmeZ7PW6Zp+r4fhmGn01EUZb1el2WpKApjDISQJw4DIYSQj9RutyuKIkmSoih2u52maWEYRlHkuq6qqjiZ3W5XluVsNiuKYrvdapoWhmGv13NdV1EUvJuUiGOMRrh9G3UNKUEIeRBSYjxGHHctCxcu4LXX1p/5jKHr+L6klE3TGIahqireTVVVv1XXtRAiy7JF6/DwMAiCMAy73a6iKDgxRVG6rcFgkOe5EKIsy8lkMp1OXdcNw3C9XgOwLAuEkCcRAyGEkI/IZrNJ0zRJkqqqmqbRdb3X60VR5DgOTmy73eZ5PpvNyrJsmkbXdc55FEWdTgfHSIk4xmiEOIaUIIR8AFJCSozH+PznjeEQX/3q4soV2zRVvLfVagXAMAy8N8uynn766X6/XxSFEKIsy+l0OpvNut0u59z3fV3XcRp0Xe/1elEULRaLNE3zPC9a8/l8s9lEUdQ0jaIoIIQ8WRgIIYT8wNV1LVqr1QqAbdu8ZRgGTmy9XmdZliRJVVUATNPkLcuycIyUiGOMRohjSAlCyMlJifEYL77YuXgRr7xSvPyy7bq6ruO49XoNwDAMfD+MMd6qqkoIkWXZvGWaZhAEnHPHcXAaFEXptvb394uiEEJMJpPlcvnmm29KKcMw9H1f13UQQp4UDIQQQn6AyrJMkiTPcymloiiu60ZR5Ps+YwwnVte1aK1WKwCdTodzHoahrus4RkrEMUYjxDGkBCHkdEmJmzdx65ZnWbhwAdeu1Zcvm4ah4B3W6zUAwzDwwJzWYDDIskwIUZbl0dHRdDp1XZdz7nkeYwynwTCMXq8XBEHRsiyraJmmGQRBGIadTgeEkMcfAyGEkA/fbrcrimI2m83n891up2laGIa9Xq/b7aqqihMry1IIkabpZrNRFMXzvCiKfN/XNA3HSIk4xmiEOIaUIE82RUHTgHxUpISUGI/x/PPWcIhXX51fueJYlgagaZr1eq0oimEYeEiMsV6vF0XRYrEQQmRZlrds2w6CIAxD27ZxGqSUmqbt7+//8A//cFmWQoiyLI+OjqbTqeu6YRj6vs8YAyHkscVACCHkwySlTNNUCFFVVdM0hmGEYcg5dxwHJ7bb7ebzeZIkeZ7vdjtN0zjnURS5rqsoCt5NStQ1btzAtWuIY0gJ8mTTdQyH+Gf/DK++ijt3QD5aUmI8xksvuRcvNl/6Unb1quM46nq9VlXVMAx8IIqidFuDwSDLMiFEVVV3796dTCae53HOPc9TVRUnsFqtdrudaZpWK4qixWIhhMjfYppmEARhGHY6HRBCHkMMhBBCPhx1XYvWarUCYNs2bxmGgRPbbDZ5nidJUpZl0zS6rvd6vSiKHMfBMVIijjEa4fZt1DWkBHmy6TqGQ/zmb+Lll6Hr+Cf/BMOhnEx0kI+alLh5U7l1K7AsfOpTzb/4F+pP/ITGGMPJGIbR7/d7vV5ZlkKIPM/TNM2yzHGcMAyDIDBNEx9IXdcALMtCS1GUbktKmWVZmqZlWR4dHU2nU9d1wzD0fZ8xBkLI44OBEELIaSvLcjab5Xm+2WwURXFdt9freZ7HGMOJrdfrNE2TJFkulwAsy+It0zRxjJSIY4xGiGNICfLE03UMh7h+HcMhdB33lGW5Wk1ee03+yq/82GajgDwCpISUuHlTieP/41Ofqv/1v15cvWp3u0zXcRKqqnqtuq6zLBNCLFpHR0e+74dh2O12VVXFw6jrGoBlWXg3Xdf39vZ6vd5isRBC5G8xTTMIAs654zgghDwOGAghhJyS3W6X53mSJEVRNE2jaVoURZxz13UVRcGJ1XWdJEmapqvVSlGUTqcTRVEYhowxHCMl4hijEeIYUoI88XQdwyGuX8dwCF3HPVVVTSaTLMu22+2nP2186lPLv/orB+RRstkof/VX9q/+KiwLFy7gtdfWn/mMoes4IcuyBoPB3t5eURRCiPl8PpvNkiTpdrthGPq+bxgGHkDTNHVdK4piWRbuR1GUbmu9Xud5nqZpWZZHR0fT6dR1Xc6553mMMRBCHmEMhBBCTmy9XmdZJoRYLBYADMMIw5Bz7jgOTkNZlkmSZFm22WwURfF9P4oi3/dVVcUxUiKOMRohjiElyFlw7hwODjAcQtdxT13X0+k0SZLtdssY29/f7/V6/+W/WJcu4c4dkEeNlJAS4zE+/3ljOMRXv7q4csU2TRUno2la2KqqKm3NW6ZpBq1ut4v3tdls1uu1pmmGYeB9GYaxt7cXRdFisUjTNMuyvGWaZhAEnHPHcUAIeSQxEEIIOYHlcimESNN0tVoBcByHcx6GoWEYOLHdblcURZIkRVHsdjtN06JWt9tVFAXvJiXqGjdu4No1xDGkBDkLdB3DIQ4OcO4c7lmtVrPZLEkSKaWmaXt7e71ez3EcAOfO4eAAzz0HKUEeTVJiPMaLL3YuXsSXv1y8/LLleYau44Sc1v7+fp7nQoj5fH50dDSdTl3X5Zx7nscYw/2s1+vNZmPbNmMMD0BVVbc1GAyyVlmWR0dHs9ms2+1yzj3PY4yBEPIoYSCEEPLwmqYpyzJJkizLttutoiie50VR5Pu+pmk4sc1mk2WZEKIsy6ZpdF3f29vjnDuOg2OkRBxjNMLt26hrSAlyFug6hkNcv47hELoOKeWstV6vVVWNoqjX63W7XbzDcIjhEOMxyKNMSty8iVu3PMvChQu4dq1+9llL13FCjLEoijjni8VCCJG/xbKsMAyDIHAcB+9W13XTNKZpqqqKh2EYRr/f7/V6i8UiTdMsy/KWZVlBEIRh6DgOCCGPBgZCCCEPY7vd5nkuhCiKomkaTdOiKOKcu66rKApObL1ei9ZyuQRg2zZvGYaBY6REHGM0QhxDSpAzQtcxHOL6dQyH0HVsNpvJREyn07quFUUJgqDf77uui2N0HQcHuHQJd+6APOKkhJQYj/H889ZwiFdfnX/2sx3TVHEyiqJ0W+v1OsuyNE0Xi8Xdu3cnk4nneZxzz/NUVUWrrmsAlmXhA1FV1W0NBoMsy9I0XSwWh4eH0+m02+1yzj3PY4yBEPKRYiCEEPJg1ut1lmVJklRVBcA0zTAMOee2beM0LJfLJEnSNF2v14qidDqdXq8XBAFjDMdIiTjGaIQ4hpQgZ4SuYzjE9esYDqHr2G63s1k6mUyWy6WiKJ7n9ft93/fx3s6dw3iMS5dw5w7IY0FKjMd46SX34kX82q9lV6/avm/qOk7IMIx+v7+3tzefz4UQRVGkaZplmW3bYRgGQWBZVl3XACzLwskYhtHv93u9XlmWaZrmb7EsKwiCMAwdxwEh5CPCQAgh5PtZLpdJkmRZtlqtAHQ6Hc55GIa6ruM0lGU5m82yLNtut4qi+L7f6/U8z1NVFcdIiTjGaIQ4hpQgZ4SuYzjE9esYDqHr2O12QmSTyWSxWADodrt7e3thGCqKgu/n3DkcHOC55yAlyONCSty8iVu3gtEIFy7ga19bPvusZRgKTkZRFK+1Wq3S1nK5rKpqMpm4rpumqaqqlmXhNKiq6rXW63WWZWmaLhaLw8PD6XTa7XY5557nMcZACPnBYiCEEPIemqaZz+dCiCzLttutoii+73POgyBQVWevRgsAACAASURBVBUnttvtiqKYzWZFUTRNo2laFEW9Xq/b7eIYKVHXuHED164hjiElyBmh6xgOcf06hkPoOpqmybJ8MpmUZdk0TafT6fV6nHNVVfHAhkMMhxiPQR4vUkJKjMd44QV7OMSXvzy/etXudpmu44RM0xwMBv1+vygKIURRFJPJ5PDw0LbtPM8ZY4Zh4JQYhtHv93u9XlmWaZrmb7EsKwzDIAgcxwEh5AeFgRBCyDHb7TbP8yRJ5vN50zSMsSiKer1ep9NRFAUnttlssixLkmSxWDRNYxhGGIacc8dxcIyUiGOMRrh9G3UNKUHOCF3HcIjr1zEcQtdxT1EU0+k0z/OmaWzb7vV6nHPGGB6SruPgAJcu4c4dkMeRlBiPEceuZeHCBXz966vLl01dxwmpqhq0qqq6c+fOdDrdbDZ37tyZzWZBEIRh2Ol0FEXBaVBV1Wut1+ssy4QQVVXdvXt3Mpm4rhuGoed5jDEQQj5kDIQQQt5hvV6naZokyXK5BGCaJm9ZloXTsF6vRWu5XAKwbZu3DMPAMVIijjEaIY4hJcjZoesYDnH9OoZD6DruKctyMplkWdY0jWmavRZjDB/UuXM4OMBzz0FKkMeUlJAS4zF+6qfM4RCvvlp+9rOOaao4McdxgiDo9/t2az6fTyaT6XTqui7n3Pd9xhhOiWEY/X6/1+uVZSmEKIoia9m2HbQcxwEh5EPDQAghpFVVlRAiTdP1eq0oSqfT4ZyHYajrOk5DVVWiJaVUFKXb7UZRFIahpmk4RkrEMUYjxDGkBDk7dB3DIa5fx3AIXcc9VVVNJpMsy7bbra7rvZZhGDix4RDDIcZjkMedlBiP8dJL3YsX8aUv5Vev2p5n6DpOYrlcaprW7/f39/fLskzTNMuyomWaZthyHAenRFVVr7VarfI8F0JUVXX37t3JZOK6bhiGnucxxkAIOW0MhBBytu12u7IskyTJ83y73SqK4vt+r9fzPE9VVZxY0zRlWSZJkmXZdrtVVTUIgiiKPM9TVRXHSIk4xmiEOIaUIGeHrmM4xPXrGA6h67inruvJZCKE2G63jLH9/f1er2dZFk6JruPgAJcu4c4dkCeAlLh5E7du+ZaFCxfwta8tr1yxdR0fzGq1AmBZFoBua39/P8/zNE3Lsjw8PJxOp57ncc5d19U0DafENM1+v9/r9cqyFEIURZG1bNsOWo7jgBByehgIIeSs2mw2eZ4nSVKWZdM0jLFerxdFUbfbxWnY7XZ5nidJUhRF0zSMsV6vF0VRt9vF/UiJOMZohDiGlCBnyrlzODjAcAhdxz2r1Wo2myVJIqXUNG1vb6/X6zmOg9N27hwODvDcc5AS5MkgJaTEeIwXXrCHQ3zlK+XLL9udjqbreHDb7Xa1WmmaZpom3mIYxt7eXhRFZVkKIYqiSFu2bXPOgyCwLAunRFVVr7VarbIsS9O0qqq7d+9OJhPP88IwdF2XMYZ3qKoqTVPHcTzP0zQNhJAHw0AIIWfPer0WreVyCcA0Td6yLAunYbPZpGmaJElVVU3TmKYZhiHn3LZtHCMl6ho3buDaNcQxpAQ5U3QdwyEODnDuHO5Zr9dJksxms/V6rapqFEV7e3udTgcfmuEQwyHGY5AnjJQYjxHHXcvChQt47bX1Zz5j6DoehGzpLbybqqpea7VapWmaZVlVVXfu3Dk6OvJ9n3Pe7XZVVcUpMU1zf39/b2+vLEshRFEUacu27SAIwjC0bRutuq4PDw/DFgghD4yBEELOkqqqkiRJ01RKqShKp9OJoigMQ8YYTsNqtRKtuq4B2LYdRVEYhoZh4BgpEccYjXD7NuoaUoKcKbqO4RDXr2M4hK5js9kIISaTyWq1UhQlDMO9vT3XdfEh03UcHODSJdy5A/LkkRJSYjzG5z9vDIf4D/+hunLFNgwF76uu691uZ5qmpml4D6ZpDgaDfr9fFIUQoiiKJEmEEI7jcM6DIDAMA6dEVVWvtVqtsixL07Sqqrt3704mE8/zwjD0PK+qKgC2bYMQ8jAYCCHkDNjtdvP5PEmSoii2262qqkEQRFHkeZ6qqjgNVVUlSZKmqZRSURTXdaMo8n2fMYZjpEQcYzRCHENKkLNG1zEc4vp1DIfQdWy329ksnUwmy+VSURTf9/f29nzfxw/KuXMYj3HpEu7cAXlSSYnxGD/9085wiC9/ubh61el2ma7jvuq6BmBZFr4fVVWD1nK5TNM0y7JF6/DwMAgCznmn01EUBafENM39/f29vb2yLIUQRVGkLdu2i6IA4DgOCCEPg4EQQp5om80myzIhRFmWTdPous5b3W4Xp6Fpmvl8niRJnufb7VZV1TAMoyhyXVdVVRwjJeIYoxHiGFKCnDW6juEQ169jOISuY7fbCZFNJpPFYgHAdd29vT3f91VVxQ/WuXM4OMBzz0FKkCeYlBiPEceeZeHCBXz966vLl01dx99R1zUA27bxwOxWv98vikIIMZ/Pp9PpbDbrdruc8yAIGGM4Jaqqeq26rrNWURSTyQRAGIZN07iuq2kaCCEPgIEQQh5/TdMoioJ3W61WaZoKIZbLJQDLssIw5JxbloXTsNvtsiwTQhRF0TQNY2xvb49z3u12cT9SIo4xGiGOISXIWaPrGA5x/TqGQ+g6mqbJsnwymZRl2TRNp9Pp9Xqcc1VV8REZDjEcYjwGeeJJCSkxHuOnfsocDvHqq+VnP+uYpopW0zR1XSuKYpomHhJjjLcWi0WaplmWzVuHh4dBEHDOHcfB6bEsazAY9Pv9w8PDLMt2u918Pi/L0rbtsGVZFggh74uBEEIeW6vVajqdrtfrT3ziE4wxvGWxWCRJkmWZlFJRlG63G0VREASMMZwGKWWapkKIxWIBwDRN3rIsC8dIibrGjRu4dg1xDClBzhpdx3CI69cxHELXcU9RFJPJpCiKpmls2+71epxzxhg+UrqOgwNcuoQ7d0DOCCkxHuOll7oXL+JLX8qvXrU9z1CU7Xq9VlXVMAx8UJ3W/v5+nudCiLIsj46OZrOZ67phGPq+r2kaTomqqoyxKIo8z3NdN8uyqqrefPPNo6Mjz/PCMPQ8T9M0EELuh4EQQh5bmqZlWbbZbLbbLWNst9sVRSGEKIpiu91qmhaGIefc8zxVVXEa6roWrdVqBcBxnCiKgiAwDAPHSIk4xmiE27dR15AS5KzRdQyHuH4dwyF0HfeUZTmZTLIsa5rGNM1eizGGR8O5czg4wHPPQUqQs0NK3LyJW7d8y8KFC/j3/74Mgm23a+q6jpPRdb3X60VRVJZlmqbZW2zbDluWZeE0VFUFwPf9fms+n6dpmud5mqZZllmWFbYsywIh5N0YCCHksaVpGmNsvV4vl8v5fJ4kyWKxaJpG13XOeRRFnU4Hp6SqqtlslmWZlFJRFNd1e72e7/uapuEYKRHHGI0Qx5AS5AzSdQyHuH4dwyF0HfcsFovpdJpl2Xa71XW91zIMA4+Y4RDDIcZjkLNGSkiJ8Rgvvxx88pM/9s//+fTpp5tOB7qOE1IUxW0NBoO0tVgslsvl0dGR7/ucc9d1VVXFB7Xb7ZbLpaIojuMAUFXVb9V1nWVZmqbL5fLNN988OjryPI9z7rqupmkghLQYCCHksaUoCoAsy771rW9pmgbAtm3OeRiGpmniNDRNM5/PZ7NZURTb7VbTtDAMe71et9tVVRXHSIk4xmiEOIaUIGeQrmM4xPXrGA6h67inruvJZCKE2G63jLH9/f1er2dZFh5Juo6DA1y6hDt3QM4mKfE//kfn3/wb59/+W+XCBbz22voznzF0HSdnGMb+/v7e3t58PhdC5HkuhEjT1HEcznkQBIZh4OFJKVerFWPMsiy8g2VZg8Gg3+8XRZGmaVEUaZpmWWZZFuc8CALLskDImcdACCGPp7IshRCHh4dZlqmq+vTTT3POgyBgjOE0bLfbPM9ns1lZlk3T6LrOOY+iqNPp4H6kRBxjNEIcQ0qQs0nX8c1v4oUXoOu4Z7VaTadTIYSUUtO0vZZt23i0nTuHgwM89xykBDmzNhtlPsd4jM9/3hgO8dWvLq5csU1TxYmpquq36rpOW4vW4eFhEARhGHa7XUVR8MCWy+V2u3UchzGGY1RVDVp1XWdZlqbpcrm8c+fO4eGh53mcc8/zVFUFIWcVAyGEPFZ2u11RFEmSFEWx2+1UVe10OoPB4Ed+5EdUVcVpkFKmaZokSVVVAEzT5C3LsnA/UiKOMRohjiElyBn35pv4b/8Nm83mR390liSJlNKysLcX7e3tdTodPCaGQwyHGI9BiJQYj/Hii52LF/HKK8XLL9uuq+s6Ts6yrKeeempvb68oCiFEWZbT6XQ2m3W7Xc657/u6ruMBLJdLAI7j4H1ZljUYDPb29ubzeZqmeZ6naZplmW3bYRgGQWBZFgg5exgIIeQxsdls0jRNkqSqqqZpdF3v9Xqapt29e1fXdVVVcWJ1XYvWarUC0Ol0OOdhGOq6jmOkRF3jxg1cu4Y4hpQgREq88gosCwBrmv2m6f+9v1c+9ZR86aXo/Hncc/kyvseyoOt4ZOk6Dg5w6RLu3AEh90iJmzdx65ZnWbhwAdeu1c8+a+k6To4xxltVVQkhsiybt0zTDIIgDMNOp4P3VVUVAMdx8AA0TQtadV1nWZam6XK5rKrq6OjI87wwDD3PU1UVhJwZDIQQ8sir61q0VqsVANu2OedhGJqmWZbl4eGhlLJpGkVR8EEtFoskSbIsk1IqiuJ5XhRFQRCoqopjpEQcYzTC7duoa0gJQt4mJaRESwGUP/szD8B//s+wLLzt8mWcP49nnsH587jn8mV8j2VB1/GIOHcOBwd47jlICUK+R0pIifEYzz9vDYf4ylcWV6/ajqPqOk7OaQ0GgyzLhBCLxeLo6Gg6nbquyzn3PI8xhmO22+1yuVRV1bZtPAzLsgaDQb/fL4oiTdM8z4UQaZrath2GYRAElmWBkDOAgRBCHmFlWQohsiyTUiqK4rpuFEW+7zPG0DIMQ1VVKeV2u2WM4SHtdrv5fJ4kSVEU2+1W07QwDHu9nuu6iqLgGCkRxxiNEMeQEoQ8ICkhJd72xhu45/XXYVl42+XLOH8ezzyD8+dxz+XL+B7Lgq7jIzEcYjjEeAxC/g4pMR4jjjuWhQsX8Nu/LS9d0nUdJ8cY6/V6URQtFgshRJZlecu27SAIwjC0bRvvsFqtpJSGYZimiYenqmrQqus6bS2Xy6qqjo6OfN8PgsDzPFVVQciTi4EQQh49u92uKIrZbDafz3e7naZpnPMoirrdrqqqeAdN0xhjmxZjDA9su93meT6bzcqybJpG13XOea/XcxwH9yMl4hijEeIYUoKQk5MSUuJtb7yBe15/HZaFt12+jPPn8cwzOH8e91y+jO+xLOg6Pmy6joMDXLqEO3dAyHFSQkqMx/hH/0gfDvG1ry2vXLF1HSenKEq3NRgMsiwTQlRVdffu3el06rou59zzPFVVAdR1vdvtbNtWVRUnYFnWU0891e/35/O5EKIoiiRJhBCO4wRB0O/3VVUFIU8iBkIIeZRIKdM0FUJUVdU0ja7re3t7nHPHcXA/mqbpur5erzebDR7Mer3Osmw2my2XSwCmaUZRFIahZVm4HykRxxiNEMeQEoR8qKSElHjbG2/gntdfh2XhbZcv4/x5PPMMzp/HPZcv43ssC7qO03XuHMZjXLqEO3dAyHuREuMxXnjBHg7xyivlyy9b3S7TdZycYRj9fr/X65VlKYTI8zxN0yzLHMcJwzAIgqqqADiOg9OgaVrQqus6bS0WizAMVVUFIU8oBkIIeTTUdS1aq9UKgG3bvGUYBt6XrutN06zXa3w/dV0nSZKm6Wq1AtDpdKIoCsOQMYZjpERd48YNXLuGOIaUIOSjIiWkxNveeAP3vP46LAtvu3wZ58/jmWdw/jzuuXwZ32NZ0HWcxLlzODjAc89BShDyPqTEeIw47loWLlzAa6+tP/MZQ9dxcqqqeq26rrMsE0IsWkdHR0VRKIpiWRZOlWVZTz31VL/fn8/ntm2DkCcXAyGEfNTKskySJMuyzWajKIrrur1ez/M8xhgegGEYANbrNd5bWZZJkmRZttlsFEXxfT+KIt/3VVXFMVIijjEa4fZt1DWkBCGPICkhJd72xhu45/XXYVl42+XLOH8ezzyD8+dxz+XL+B7Lgq7jwQ2HGA4xHoOQ70tKSInxGJ//vDEc4qtfXVy5YpumitNgWdZgMNjb2yuKIk1T0Wqa5s6dO1JK3/cNw8Dp0TQtCAIQ8kRjIISQj8hut8vzPEmSoiiaptE0LYoizrnruoqi4IEZhgFgvV7jmN1uVxSFECLP891up2laFEWcc9d1FUXBMVIijjEaIY4hJQh57EgJKfG2N97APa+/DsvC2y5fxvnzeOYZnD+Pey5fxvdYFnQd96Xr+I//cXnlCptMdBDyYKTEeIwXX+xcvIhXXileftl2XV3XcXKapoWtbrdbFMVms1kul9/5zndM0wyCIAzDTqcDQsiDYSCEkB+49XqdZZkQYrFYADAMIwzDKIps28bDMwwDgJQS77DZbLIsE0KUZdk0ja7re3t7nHPHcXA/UiKOMRohjiElCHmSSAkp8bY33sA9r78Oy8LbLl/G+fN45hmcP4/vfAc///P4HstC06xns1lVzb7+deNXf/WTm40CQh6YlLh5E7dueZaFCxdw7Vr97LOWruO0+L4fhqHv+0KI+Xx+dHQ0nU5d1+Wce57HGAMh5H0xEELID9ByuRRCpGm6Wq0AOI7DOQ/D0DAMfFCGYSiKsl6vd7udqqrr9Vq0lsslAMuyoigKw9A0TdyPlIhjjEaIY0gJQs4IKSEl3vbGG7jn9ddhWbjnX/0r3HP5Ms6fx6c/fXjxogCwWkUg5AORElJiPMbzz1vDIb7ylcXVq7bjqLqOk6iqCkC3242iiHO+WCyEEPlbLMsKwzAIAsdxQAh5DwyEEPLha5qmLMskSbIs2263iqJ4nhdFke/7mqbhZBhjqqpKKReLRZ7naZqu12tFUTqdTq/XC4KAMYb7kRJxjNEIcQwpQQiRElLibW+8gXsY+7hhnAOU9VrZbBQQcgJSYjxGHHcsC//wH+I//ad1p2PgA9ntdsvlUlEUx3EAKIrSba3X6yzL0jRdLBZ3796dTCae53HOPc9TVRWEkHdjIISQD9N2u83zXAhRFEXTNJqmRVHEOXddV1EUnAZN0zabTZZl6/Vaafm+3+v1PM9TVRXHSIm6xo0buHYNcQwpQQh5H5uNstloIOT0SAkp8ad/uvvLv/zWuXMe57zT6SiKgochpVytVowxy7LwDoZh9Pv9Xq9XlqUQoiiKNE2zLLNtOwzDIAgsywIh5C0MhBDy4Viv11mWJUlSVRUA0zTDMOSc27aNU7Lb7YqimM1m0+l0uVx2u93BYBBFkeu6uB8pEccYjXD7NuoaUoIQQshH5R/8g4KxzXQ6nc1mnudxzj3PY4zhwSyXy+126zgOYwzHqKrqteq6zrIsTdPlcllV1WQy8TyPc97tdlVVBSFnHgMhhJy2qqqEEFmWrVYrAJ1Oh3MeBIFhGDglm80my7IkSRaLRdM0hmHouv7xj3/83LlzuB8pEccYjRDHkBKEEEI+WrqOf/pPgwsXfjRt5S3btoMg4JxbloXvZ7lcAnAcB+/LsqzBYNDv94uiEEIURZEkiRCi0+mEYRgEgWEYIOQMYyCEkFPSNM18PhdCZFm23W4VRfF9n3MeBIGqqjglq9UqTVMhxHK5BGDbNuc8iqIkSTRNwzFSIo4xGiGOISUIIYQ8CiwLn/scOq1+v59lmRCiqqq7d+9Op1Pf9znn3W5XVVW8h6qqADiOgwegqmrQqqoqy7I0TcvW0dGR7/uc806noygKCDl7GAgh5MS2222e50mSzOfzpmkYY1Gr2+0qioJTUlWVECJN0/V6rShKt9uNoigIAsbYdDpNkmS9XuMdpEQcYzRCHENKEEIIeTQZhtHv93u93nw+F0LkeZ4kiRCi0+lwzoMg0HUd77bdbpfLpaqqtm3jYTitfr9fFIUQYj6fT6fT2Wzmui7n3Pd9xhgIOUsYCCHkBNbrdZqmSZIsl0sApmnylmVZOD3z+TxJkizLttutoii+7/d6Pc/zVFVFS9d1AOv1GoCUqGvcuIFr1xDHkBKEEEIeNYMBBgO8k6qqfmu5XKatsnV0dBQEAefccRy8ZbVaSSkNwzBNEw+PMcZbZVmmaZplWdEyTTNsOY4DQs4GBkII+UCqqhJCpGm6Xq8VRel0OpzzMAx1Xccp2e12RVHMZrOiKJqm0TQtiqJer9ftdvFuhmEoilJV8s/+bPfrv67evo26hpQghBDyaPr0p2FZuC+71e/38zwXQszn86Ojo9ls5nke59zzPFVV67re7Xa2bauqihPotvb39/M8T9O0LMvDw8PpdOp5XtgCIU86BkIIeRi73a4syyRJ8jzfbreKovi+H0WR7/uqquKUbDabLMtms1lVVU3TGIYRhmEURbZt436aht2+7b722sf+5/9UpQQhhJBHma7jpZeg63gfjLEoijjni8VCCJFlWZqmWZbZth2GYVVVABzHwWkwDGNvby+KorIs0zTNW/v7+yDkDGAghJAHs9ls8jxPkqQsy6ZpGGO9Xi+Kom63i9OzWq3SNE2SpK5rALZt85ZhGLgfKRHH+Jf/Ur9160c2GwWEEEIeeZaFz30OD0JRlG5rf38/bVVVtVgshBCKojz11FNN0yiKgtOgqqrXWq1WaZp2Oh0QcgYwEELI97Ner0VruVwCME2TtyzLwumpqkq0pJSKoriuyzkPgoAxhvuREnGM0QhxDCkVEEIIeXKZpjkYDPr9flEUk8nk7t27u93uu9/97mKx4Jz7vs8YwykxTXMwGICQs4GBEELeW1VVSZKkaSqlBNDpdKIoCsOQMYZT0jTNfD4XQmRZtt1uVVUNw5Bz7nmeqqo4RkrUNW7cwLVriGNICUIIIY+XwQCDAT4AVVWDINA0TQix2WwsyypalmWFYcg5tywLhJCHwUAIIcfsdrv5fJ4kSVEU2+1WVdUgCKIo8jxPVVWckt1ul+d5kiRFUTRNwxjr9XpRFHW7XdyPlIhjjEa4fRt1DSlBCCHkcfTpT8Oy8IEtl0td159q5XkuhFgsFnfv3p1Op57nRVHU7XZVVQUh5AEwEELIO2w2myzLhBBlWTZNo+s6b3W7XZyezWaTpmmSJIvFAoBpmmEYRlFkWRbuR0rEMUYjxDGkBCGEkMeXruPFFxtdV/BBVVUFwHEcwzD29vaiKCrLUgiRZZkQIk3TTqcThmEQBIZhgBDyvhgIIaS1Wq3SNBVCLJdLAJZlhWHIObcsC6enrus0TZMkWa1WAGzb7vV6QRAYhoH7kRJxjNEIcQwpQQgh5HFnGLtPfOL/OzrqhmFoGAYe0m63Wy6XiqLYto2Wqqpeq65rIUSWZWVrMpkEQcA5dxwHhJD3wEAIOfMWi4UQIk1TKaWiKN1uN4qiIAgYYzg9VVXNZrMsy6SUiqK4rtvr9Xzf1zQN9yMl4hijEeIYUoIQQsiToWma5XL53e9mR0dHYRhyzjudDh6YlHK1Wum6blkW3s2yrKeffrrf7xdFkSTJfD4/OjqazWau63LOPc/TNA2EkHdjIIScVbvdrigKIURRFNvtVlXVMAw5557nqaqKU9I0zXw+T5Ikz/PtdqtpWhiGURS5rquqKu5HSsQxRiPEMaQEIYSQJ8lgoPz9v/+x1Wo2n88nk8lsNvM8L4oiz/NUVcX3s1wut9ut4ziMMdwPY4xzHobhYrEQQmRvcRwnbJmmCULIWxgIIWfPZrPJsixJksVi0TSNruuc8yiKOp0OTs9ut8uyLEmS+XzeNI2u65zzKIo6nQ7uR0rUNW7cwLVriGNICUIIIU+eT3wi/+53/99Ll4ZVVQkhslae547jcM6DIDAMA++tqioAjuPgfSmK0m0NBoO0VbUmk4nv+5zzbrerKAoIOfMYCCFnSV3XaZoKIeq6BmDbNuc8DEPTNHF6pJRpmgohFosFANM0ecuyLNyPlIhjjEa4fRt1DSlBCCHkCSX/9E9/86d/+o9eeOGFL37xi88///xgMBBCpGm6aB0dHQVBwDnvdDq4n6qqADiOgwdjGMb+/v7e3l5RFEKIoihms1mSJK7rhmEYBAFjDIScYQyEkLOhLEshRJZlUkpFUVzX5ZwHQcAYw+mp61q0VqsVAMdxoigKw1DXddyPlIhjjEaIY0gJQgghT7oa+NP5fH5wcPDNb37z0qVLv/RLv/SFL3zhx37sx/I8F0LM5/PJZJIkied5nHPP81RVxVu2221d16qq2raNh6GqatCqqkoIkWVZ0To6Ogpbtm2DkDOJgRDyRNvtdkVRJElSFMVut9M0LQzDKIpc11VVFadnsVgkSZJlmZRSURTXdXu9nu/7mqbhfqREHGM0QhxDShBCCDkLGGPPP//Sf//vh/P5fLfb/T+t3/md3/m5n/u5X/zFX/zxH//xxWIhhMiyLE3TLMscx+GcB0FgGAaA1Wq1Xq/NFj4Qp7W/v5/nuRCiLMu7d+9OJhPf9znnruuqqgpCzhIGQsgTarPZZFk2m82qqmqaRtf1Xq8XRZHjODg9u92uLMvZbFYUxXa71TQtDMNer+e6rqIouB8pEccYjRDHkBKEEELOjh/6IfuP/uj/+l//6//8xje+cXBw8J3vfAfA3/zN33z961//vd/7vZdeeumLX/ziT/7kT+7v76dpKoRYtI6OjsIw5JxXVdU0jW3bqqriBHRd7/V6nPOyLIUQeZ4LIdI0dRzn6aef9jwPhJwZDISQJ05d16K1Wq0A2LbNOQ/D0DRNnJ7tdpvneZIk8/m8aRpd1znnvV7PcRzcj5Soa9y4gWvXEMeQEoQQQs6aT38atq38ROs3fuM3Dg4O/uAP/uDP//zPm6bJsuwP//AP//iP//jZZ5/95V/+5Z/5mZ/55Cc/mee5lpu4ZgAAIABJREFUEKIoiqOjo9lsVtf1ZrN56qmncBpUVfVadV2nLVVVu90uCDlLGAghT5CyLIUQWZZJKRVFcV03iqIgCDRNw+lZr9dZliVJUlUVANM0ecuyLNyPlIhjjEa4fRt1DSlBCCHkDNJ1vPQSdB3f8/GPf/zXf/3Xf+VXfuWNN974/d///T/5kz+pqmqz2fzfrd/+7d/++Z//+V/4hV/41Kc+tVgshBBpmgohVquV4ziMsSAIDMPAabAs66mnntrb2yuKQlVVEHKWMBBCHn+73a4oitlsNp/Pd7udpmlhGPZ6vW63q6oqTk9d16K1Wq0AdDod3mKM4X6kRBxjNEIcQ0oQQgg5yywLn/sc/g7XdX/2Z3/2C1/4wng8/sY3vvHNb37zzTffBPCtb33rt37rt373d3/35Zdf/uIXv/jcc89xzvM8ByCl/Nu//dvJZBIEAefccRycBsYY5xyEnDEMhJDHmZT/P3vwHyPJXd8J/10/vtXV1b+rqmd6utYYHLM4xCFJJTAEssSHzPErCOyR73CMEQmEP04orRApSKdH90/+iU+XRMMlugsyoGAbCNAYg4WPaCMuTB4uTZJSwhHnF45Z2z3T01NVXV1dXV3d366qx0+jRCbs2mu7d2d29/N68dFo5Pt+HMd5njPGms2mruuapmGtoijyfX80Gi2XS0EQarWaruv1el0URZwP53AcdDpwHHAOQggh5FmIovizKx/+8Ie/8IUvfPrTn/72t7+d57nneX/4h3/4mc985g1veMO73/3uG2644aUvfenm5uZoNArD8PDw0HXdarWq63q1WhVFEYSQ50kGIeTKlCSJvzKfzwEUi0V9RVEUrE+WZZPJxPO88XicZZkkSbquG4ZRqVQEQcD5cA7HQacDxwHnIIQQQr6v1UKrhWd3ww03/MZv/MYHP/jBRx555L777vv617+eJMlisTh79ux3vvOdV7ziFW94wxve8573vPzlL4+iyPf98Xg8Go2CINA0Tdf1er2uKAoIIRdNBiHkShNFked5QRAsl0tBECqVimma1WpVlmWsz3K5HI/HnudFUZTnOWPMNE3DMDRNwwVwDsdBpwPHAecghBBCnunmm6GquBj1ev3OO++84447vvnNb95///0PPfRQkiSmafb7/d///d//2Mc+9s53vvOuu+563etet7m5GQSB7/vTleFwWK/XdV3XNA2EkIsggxByhciybDwee54XhmGe55Ik6bpuGEalUhEEAeuzWCxGo5HnebPZDICqqvpKoVDA+XCOJMHZs7jnHjgOOAchhBDybzCGt74VjOHiybL8hje84ed+7ufe9773ffnLX/7zP//zxx57bDab+b7/sY997FOf+tQb3/jG97znPW9729tOnz4dhqHneZPJ5PDw0HXdarVqGEalUhFFEYSQC5NBCDnxFotFEAS+70+nUwCKojQaDV3XNU3DWiVJ4nneaDSaz+eCIJRKJcMwGo2GLMs4H87hOOh08OijSBJwDkIIIeS8VBW33ILnK47j/f39QqHw7ne/+73vfW+v13vggQf29vYWi0WSJF/96lcfeeSRn/iJn7jzzjvvuOOOG2+8MYoi3/fH4/FoNAqCoFQq6bper9cZYyCEnI8MQsgJNpvNfN8fjUbz+RyApmm6rjcaDUVRsFZRFHmeFwTBcrkUBKFWqxmGUavVRFHE+XAOx0GnA8cB5yCEEELWzvO8g4OD+XxeLBbb7Xa9Xn/lK1951113feMb37j//vsffvhhz/PyPP/rlY9+9KO33XbbXXfd9ZrXvGZzc3O0Eq0cHh42VjRNAyHkB8kghJw8eZ5HUeR5XhAEaZoKglCtVg3DqNVqkiRhfbIsC8PQ87wwDLMskyTJWCmXy4Ig4Hw4h+Og04HjgHMQQgghF6PVQquFi7RcLg8ODo6OjvI813XdsixFUbCiKMqtK3/7t3/72c9+9nOf+9w//uM/Auj3+7/3e7/3yU9+8tZbb7377rvf/OY3N5vN8XjseV4URYPB4OjoqFarGYZRLpdFUQQhZEUGIeQkSdN0PB77vh+GYZ7nkiQZhqHreqVSEQQB67NcLoMg8DxvOp3mec4Yazabuq5rmoYL4ByOg04HjgPOQQghhFy8m2+GquJiRFHU7/ejKJJleWtrq9lsCoKAH/JjP/Zjv/mbv/mhD33ooYceeuCBB775zW8ul8vpdPrQQw995Stf+emf/um77rrr9ttvf/nLXx5Fked54/HY9/3RaFQqlQzDqNVqjDEQcs2TQQg5GRaLRRAEnufFcQygUCjU63XDMIrFItZqsVj4K7PZDECxWNRXFEXB+XCOJMHZs7jnHjgOOAchhBDyvDCGt74VjOHZ5Xl+dHQ0GAw456VS6dSpU+VyGc9qc3Pzgx/84Hvf+96vf/3r991331e/+tXxeJxl2V+s/O7v/u7Ozs4v/uIv2rY9n8993x+NRtFKoVDQdb3RaBSLRRByDZNBCDlucRyPVubzOYBSqaTrer1eVxQFazWbzTzPG41Gi8VCEIRyuWwYRr1el2UZ58M5HAedDh59FEkCzkEIIYS8AKqKW27Bs1ssFvv7+77vA2g2m+12W5ZlXBxVVd/61re+5S1v+Zu/+ZvPfOYzn//85x9//HEA586d+53f+Z177733zW9+8913333rrbdubGwEQeD7fhRFBwcHw+GwVqsZhlEul0VRBCHXHhmEkGOS5/lkMvF9PwiCNE0FQajVarqu1+t1URSxVlEUua4bBEGapoIg1Go10zSr1aooijgfzuE46HTgOOAchBBCyCU1Ho/7/f5sNlMUpd1uG4aB508QhJ9c+dVf/dUHH3zwgQce+Na3vpVlWRiGn//857/4xS++9rWvveuuu971rne9/OUvn0wmvu+Px2Pf9+fz+enTp0HINUkGIeSyS9N0PB57njeZTPI8l2XZWCmXy4IgYH2yLAvD0HXdyWSSZZkkSYZhmKZZLpdxAZzDcdDpwHHAOQghhJAXr9VCq4XzyrLscCVN01qt1m63NU3Di2NZ1oc+9KFf+qVfOnv27H333fe1r30tiqI0Tf/fld/+7d++44477rzzzle96lVJkvi+L8uyKIog5JokgxByGS0Wi9Fo5HnebDYDUCgU9BVVVbFWy+UyCALXdeM4zvNcUZRGo2EYRrFYxAVwDsdBpwPHAecghBBC1uXmm6Gq+GGz2azf74/HY1EUt7a2Njc3JUnCmpRKpXe+853veMc7/uqv/uqBBx744he/+OSTTwJ47LHHfuu3fusP/uAP3va2t91999233HKLJEkg5FolgxByWcRx7Pv+aDRaLBaCIJRKJcMw6vU6YwxrtVgs/JXZbAagWCzqK4qi4Hw4R5Lg7Fnccw8cB5yDEEIIWSPGcPfdYAz/hu/7+/v78/m8WCy22+16vY5LQBTFV6/82q/9Wrfb/fSnP+04Tp7no9HogQce+NznPvf617/+/e9//3ve8x4Qck2SQQi5lLIsi6LI87zxeJymqSAItVrNMIxarSaKItYqjmN/hXMuCEKlUtF1vV6vy7KM8+EcjoNOB48+iiQB5yCEEELWTlVx8814puVyORgMhsNhnueNRqPdbquqikvs+uuv//CHP/yBD3zga1/72n333Xf27NnZbMY5933/7W9/Owi5VskghFway+VyPB57nhdFUZ7nsiybpmkYRrlcxlrleR5Fked5QRCkaSqKYr1eNwyjWq2Koojz4RyOg04HjgPOQQghhFxSrRb+VRRF+/v7k8lEkqStra1msymKIi6XarV6xx133H777b1e7/777//Sl7707ne/u9FogJBrlQxCyLotFgt/ZTabAVBVtdFo6LquqirWKsuy8XjseV4Yhnmey7JsmqZhGOVyGRfAORwHnQ4cB5yDEEIIudRuvRWqiqflee667sHBAee8VCpZllWpVHAcJEl63cqv//qv53kOQq5hMggh6xPHsed5o9GIcy4IQqlUMgyjXq8zxrBWy+VyNBp5nhfHcZ7nhUKh0WgYhqGqKi6AczgOOh04DjgHIYQQchlYFv77fwdjWCwW+/v7vu8DaDabW1tbjDEctx/5kR8BIdc2GYSQFy3Lsslk4nleGIZpmoqiWK/XDcOoVquiKGKt5vO5v5IkCYBisWgYRqPRUBQFF8A5HAedDhwHnIMQQgi5PFqtrNcTLQthGPb7/TiOGWPtdts0TRBCTgYZhJAXYblcBkHg+34URXmeM8b0lXK5jHWL49jzvNFoxDkXBKFSqRiGUavVZFnG+XCOJMHZs7jnHjgOOAchhBByechyftNN8X33TQ2jOhgEg8EgTdNKpXLq1ClN00AIOTFkEEJekPl8PhqNfN+fzWYAVFXVdb3RaKiqirXK83wymXieNx6P0zQVRbHRaBiGUalURFHE+XAOx0Gng0cfRZKAcxBCCCGXjWXhd3/3yeuv95Jk/md/FgEol8vXXXfd5uamLMsghJwkMgghz9N0OvU8LwgCzrkgCOVy2TCMer0uyzLWKsuyIAg8z5tMJnmey7LcbDYNwyiVSrgAzuE46HTgOOAchBBCyOXEGGwb3S62tk49+WT+2GOPRVEkSZKmaZzzOI4rlYogCCCEnBgyCCEXJ8uyMAx93w/DME1TURQbjYau69VqVRRFrBXnfDQa+b4/nU4BFAoFfUVVVVwA53AcdDpwHHAOQggh5DKzLHS7sG0IwnJ/f+B5XrVa3dzcVBQljmPP83zfr1aruq7X63VRFEEIOQFkEEL+BeecMYYfslwugyDwPG86neZ5zhjTdd0wjFKphHVLksRfmc/nADRNMwyjXq8rioIL4ByOg04HjgPOQQghhFx+loVeD5aF6XTa7/cnk4kkSe12e2NjQxTFJEk8zxuNRuOVUqmk63qj0WCMgRByrGQQQoD9/f3pdNpoNEzTxDMkSTIajXzfT5IEQLFYbKyoqop1m06nnucFQcA5FwShUqmYplmr1SRJwvlwjiTB2bO45x44DjgHIYQQcvkxBttGtwvLguu6+/v7nPNSqdRut6vVKlZUVbUsq9lsBkHged50ZTgc6iuqqoIQckxkEEIAWZbDMGSMmaaJlSiKfN8fjUbL5VIQhEqlout6vV6XZRlrlef5ZDJxXTcMwzRNJUlqNBqmaVYqFUEQcD6cw3HQ6eDRR5Ek4ByEEELIsbAsdLuwbeT54ty5A8/zAJimubW1pSgKfpCiKBsbG4ZhjMdj13WjKDo4OHBdt16vG4ZRKpVACLnsZBBCAE3TBEGI43i5XEZR5HleGIZZlkmS1Gg0DMOoVCqiKGKt0jQdj8eu60ZRlOc5Y0zXdcMwSqUSLoBzOA46HTgOOAchhBByXBiDbaPbhWUhDMP9/f3pdMoY29raajabuDBJknRdr9frURS5rhuG4dHRke/71WrVNM1yuSyKIgghl4sMQgigqqooip7n/d3f/R3nPM9zxphpmoZhaJqGdeOcj0Yjz/PiOAZQKBT0FVVVcQGcw3HQ6cBxwDkIIVcNxqCqSBJwDkKuFJaFbhe2DUnKBoPhYDBI07RSqViWVSqVcBFEUayuTKdTz/OCIBiNRkEQlMtl0zRrtZokSSCEXHoyCLnmJUni+77neePxOM9z0zR1XW80GoVCAeuWJIm/Mp/PAZRKJV3XG40GYwwXwDkcB50OHAecgxBy1WAMto3dXbzylXj0UXQ6cBxwDkJOOMtCrwfLQpIkTz65PxqNBEHY3NxstVqyLON5Kq1sbGz4K5MVTdMMw6jX64qigBByKckg5BoWRZHv+0EQcM5FUVRVVdf106dPy7KMdYuiyPf9IAg454IgVKtVwzDq9booirgAzuE46HTgOOAchJCrBmOwbezuwrbBGJ62vY29PTgOOh04DjgHIScQY7BtdLuwLARB0O/3kyQpFAqWZTUaDbwIqqq22+1mszkajXzfn06ncRwPh0N9RVVVEEIuDRmEXHuyLAvD0HXdyWSSZZkkSY1Go9VqHRwcMMYkScL6ZFk2mUw8zxuPx1mWSZKk67phGJVKRRAEnA/nSBKcPYt77oHjgHMQQq4ajMG2sbsL2wZjeCbGsL2NvT04DjodOA44ByEnh2Wh24VtQxTTfn8wHA6zLKvX65ZlqaqKdWCMbWxsmKYZBIHv+2EYHhwcHB0d1et1wzDK5TIIIesmg5BrCed8NBr5vh/HcZ7niqI0Gg1d1zVNWywWnuclScI5VxQFL1qapkEQeJ4XRVGe54wx0zQNw9A0DRfAORwHnQ4efRRJAs5BCLmaWBa6Xdg2GMOFMIbtbeztwXGws4N+H4ScBJaFXg+WhTiO+/1+GIaSJLXb7c3NTVEUsVaiKOq63mg0JpOJ7/tBELiu6/t+tVo1DKNarYqiCELImsgg5NqQJIm/Mp/PARSLRX1FURSsKIqiqupkMpnNZoqi4EVYLBaj0cjzvNlsBkBVVX2lUCjgAjiH46DTgeOAcxBCrjKMwbbR7cKycDEYw/Y2ej3s7MBxwDkIOS6MwbbR7cKy4Hlev9/nnGuaZllWtVrFJSMIQnUljmN/JQiC8XhcLpd1Xa/X67IsgxDyoskg5GoXRZHneUEQLJdLQRAqlYppmtVqVZZl/CBN0yaTyXQ6rdVqeEGSJPE8bzQazedzQRBKpZJhGI1GQ5ZlXADncBx0OnAccA5CyFWGMdg2dndh22AMz4tlYW8PjoNOB44DzkHIZWZZ6HZh2wD4E08cuK4LwDCMdrutKAouC22l2WyORiPf9ycrruuePn1aFEUQQl4cGYRcpbIsG4/HnueFYZjnuSRJuq4bhlGpVARBwPmUSiUAcRzj+YuiyPO8IAiWy6UgCLVazTCMWq0miiIugHM4DjodOA44ByHk6mNZ6HZh22AMLwxj2N7G3h4cB50OHAecg5DLgDHYNrpdWBYmk0m/359Op4yxVqvVbDYFQcDlVSgUWq2WaZpBELiuq+u6KIoghLxoMgi56iwWiyAIfN+P4zjPc0VRGo2GruuapuFZFYtFSZJms9lyuZRlGRchy7IwDD3PC8MwyzJJkgzD0HW9UqkIgoDz4RxJgrNncc89cBxwDkLI1Ycx2Da6XVgWXjzGsL2NvT04DjodOA44ByGXjmWh24VtQ5Kyw8OjwWCwXC4rlUq73S6Xyzg+siybpqnrepqmIISsgwxCriKz2cz3/dFoNJ/PAWiaput6o9FQFAUXQVEUVVXjOE6SpFwu41ktl8sgCHzfj6Ioz3NFURqNhq7rmqbhAjiH46DTwaOPIknAOQghVx/GYNvY3YVtgzGsEWPY3sbeHhwHnQ4cB5yDkLWzLPR6sCzM5/Onntr3fV8QhI2Nja2tLVmWcQKIKyCErIMMQq58eZ5HUeR5XhAEaZoKglCtVg3DqNVqkiThoomiqGnadKVcLuMCFouFvzKbzQAUi0V9RVEUXADncBx0OnAccA5CyFWJMdg2dndh22AMlwhj2N7G3h4cBzs76PdByLowBttGtwvLQhAE+/v7s9msUCi0221d10EIuRrJIORKlqbpeDz2fT8MwzzPJUkyDEPX9UqlIggCnj9N0wBMp1Ocz2w28zxvNBotFgtBEMrlsmEY9XpdlmVcAOdwHHQ6cBxwDkLI1cqy0O3CtsEYLgPGsL2NXg87O3AccA5CXiTLQrcL24YkZfv7g8PDwyzLarWaZVnFYhFXlDiOsSIIQrFYBCHkwmQQcmVaLBZBEHieF8cxgEKhUK/XDcMoFot4ETRNEwRhNpulaSpJEv5FFEWu6wZBkKapIAi1Ws00zWq1KooiLoBzOA46HTgOOAch5GrFGGwb3S4sC5eZZWFvD46DTgeOA85ByAtjWej1YFmI4/jcuf3xeCxJ0tbWVqvVEkURV5rlcun7/tHR0U033ZQkSZZlmqaBEHI+Mgi50sRx7Pt+EATz+RxAqVTSdb1eryuKghdNVdVCoTBf0TQty7IwDF3XDcMwz3NJkgzDME2zXC7jAjhHkuDsWdxzDxwHnIMQcrViDLaN3V3YNhjDsWAM29vY24PjoNOB44BzEHLxGINto9uFZcHzvIODg/l8XiwW2+12vV7HlalarcqyzBj77ne/WywWT506BULIBcgg5AqR5/lkMvF9PwiCNE0FQajVarqu1+t1URSxJqIoFovFJEnCMIzj2PO86XSa57miKI1GQ9d1TdNwAZzDcdDp4NFHkSTgHISQq5hloduFbYMxHDvGsL2NvT04Dv7Tf+Lf/ra8XAog5LlYFrpd2DYEYfnEE/uu6+Z5bhhGu91WFAVXMm2l2WwqijKfz0EIuQAZhJx4aZqOx2PP8yaTSZ7nkiQZK+VyWRAErJuiKOPxOIqicrkMoFgs6iuKouACOIfjoNOB44BzEEKubozBttHtwrJwojCGV786+/KXR3/6p5P/+l9PPfpogXMQcl6MwbbR7cKyEEVRv9+PokiW5VartbGxIQgCrgqKogAoFAoghFyADEJOsMViMRqNPM+bzWYACoWCvqKqKi6BOI5939/f3x+Px4qibG5umqZZr9dlWcaFcY7bbsMf/zE4ByHk6sYYbBu7u7BtMIaTJgzDwWAwmUxuukn43OfEg4Otu+5S+30Q8m9YFrpd2DZkOR8Ojw4ODpbLZalUOnXqVLlcBiHkWiKDkBMpjmPf90ej0WKxEAShVCrput5oNBhjWLc8z6Mo8jwvCII0TUVRrFQqmqa95CUv0TQNF8F1wTkIIVcxxmDb2N2FbYMxnDSLxeLw8NDzvDRNi8Viq9VqNBqnTwu9HnZ24DjgHIR8n2Wh14NlYbFYnDu373meIAjNZrPdbsuyDELINUYGISdJnueTycTzvPF4nKapIAi1Ws0wjFqtJooi1i3LsjAMXdcNwzDPc0mSDMMwTXMwGIzH4yRJNE3Dc2EMH/kI/uN/BOcghFyVLAvdLmwbjOGkybLM9/3Dw8MkSSRJarVaGxsbjDGsWBb29uA46HTgOOAc5FrGGGwb3S4sC+PxuN/vz2YzRVHa7bZhGCCEXJNkEHIyLJfL8XjseV4URXmey7JsmqZhGOVyGZfAcrkMgsB13TiO8zwvFAqNRkPX9WKxCEDTtPF4HMexruu4CDffDFUF5yCEXGUYg22j24Vl4QSKomgwGIzHYwC1Wq3VapXLZfwgxrC9jb09OA46HTgOOAe5BlkWul3YNiQp298fDIfDNE1rtVq73dY0DYSQa5UMQo7bYrHwV2azGYBCoaCvqKqKS2A+n49GI8/zkiQBUCwWDcNoNBqKouBflEolAHEc4+K0WiCEXGUYg21jdxe2DcZw0nDOj46OhsNhmqaFQqHVaum6LooiLoAxbG9jbw+Og04HjgPOQa4dloVeD5aF2Wx27lx/PB6Lori1tbW5uSlJEggh1zAZhByfOI79Fc65IAilUskwjHq9zhjDJRDHsed5o9GIcy4IQqVSMQyjVqvJsowfVCwWGWOz2WyxWCiKgueiqrj1Vjz4IAghVwfLQrcL2wZjOIF83x8MBrPZTBTFjY2Nzc1NRVFwERjD9jb29uA46HTgOOAc5OrGGGwb3S4sC77v7+/vz+fzYrHYbrfr9ToIIdc8GYRcdlmWRVHkum4YhmmaiqJYr9cNw6hWq6IoYt3yPJ9MJp7njcfjNE1FUWw0GrquV6tVURRxPowxVVUnk0mSJIqi4LkwhrvvxsMPg3MQQq5ojMG20e3CsnACxXE8GAyCIMjzvFKptFqtarWK54kxbG9jbw+Og04HjgPOQa5KloVuF7YNQVg+9dRgOBzmed5oNCzLKhQKIIQQQAYhl91isXj88ceXyyVjTF8pl8u4BLIsC4LA9/0wDPM8l2W52Wzqul4ul/GsBEHQNG0ymUyn02q1iueSpqllhYVCnXMBhJArE2OwbezuwrbBGE6aNE2Pjo6GwyHnXFGUzc1N0zRFUcQLxRi2t7G3B8fBzg76fZCrCWOwbXS7sCxEUbS/vz+ZTCRJ2traajaboiiCEEJWZBBy2amqWqvVFEXRdV1VVVwCy+XSX5lOpwAKhYK+oqoqLo6maQCm0ymeFed8NBq5rjufL7KsCkgghFxpGINtY3cXtg3GcAKNx+ODg4PpdCoIgmEYrVZLVVWsA2PY3kavh50dOA44B7kKWBa6Xdg2ZDkfDo8GgwHnvFQqWZZVqVRACCHPIIOQ43Dq1ClZlnEJJEnir8zncwCaphmGUa/XFUXB86FpmiRJs9lsuVzKsowfkiSJvzKfzwE0GuXXvS4+e7YCQsgVxbLQ7cK2wRhOoCRJDg8Pfd/PsqxUKrVarXq9jnWzLOztwXHQ6cBxwDnIlcuy0OvBsrBYLJ544sDzPADNZnNra4sxBkII+UEyCDkOsixj3eI4dl03CALOuSAIlUrFNM1arSZJEp4/RVEKhcJsNkuSpFwu4xniOPY8bzQacc4FQahWq4Zh1Ov1//AfxD/9U3AOQsgVgTHYNrpdWBZOoCzLXNc9PDxcLBaMsVar1Ww2ZVnGpcEYtrextwfHQacDxwHnIFcWxmDb6HZhWQjDsN/vx3HMGGu326ZpghBCzkcGIVe4PM8nk4nrumEYpmkqSVKj0TBNs1wui6KIF0oURU3T4pVyuYyVKIpc1w2CIE1TURQbjYZpmpVKRRAEALfcAlUF5yCEnHCMwbaxuwvbBmM4gSaTycHBwWQyEQRB1/XNzU1N03DpMYbtbeztwXHQ6cBxwDnIFcGy0O3CtiFJ2WAwHAwGaZpWq1XLsjRNAyGEXIAMQq5YaZqOx2PP8yaTSZ7njDFd1w3DKJVKWIdSqeS67nQ6zbIsDEPP88IwzLJMkiRzpVQqgRBypbEsdLuwbTCGE2ixWBweHnqel6ZpsVhstVqNRkMQBFxGjGF7G3t7cBx0OnAccA5yYjEG20a3C8tCkiRPPNEPgkAQhNaKJEkghJALk0HIFYhzPhqNfN+fTqcACoWCvqKqKtZH0zQAw+FwPp/HcZznOWOs2WwahlEsFvFDWi2tGmDMAAAgAElEQVS0WphMQAg5sRhDt4vtbZxAWZb5vn94eJgkiSRJrVZrY2ODMYZjwhi2t7G3B8fBzg76fZATyLLQ7cK2wRh839/f35/P56qqttvtRqMBQgh5LjIIeaGWy6Usy7i8kiTxV+bzOYBSqaTreqPRYIxhrZbLZRiGnufFcZxlWbVa1XXdMAxFUXABqoqbb8Y//RMIISeZ64JzMIYTJYqiwWAwHo8B1Gq1VqtVLpdxAjCG7W30etjZgeOAc5CTw7LQ68GysFwun3pqMBwO8zxvNBrtdltVVRBCyEWQQcjzl6ZpnudHR0etVksQBFwW0+nU87wgCDjngiBUq1XDMGq1miRJWKvFYuH7vud5SZJkWSbLsmEYN9xwgyzLeFaM4e678fDD4ByE/DDGoKq4GEkCzkEuBc5x222wbezuwrbBGI4d5/zo6Gg4HKZpWigUWq2WruuiKOIksSzs7cFx0OnAccA5yPFiDLaNbheWhel02u/3J5OJJEmtVmtjY0MURRBCyMWRQchFWy6XsiwDeOyxxxhjk8mkWCxWKhVJknDJZFkWRZHrumEYpmkqSVKj0TBNs1KpCIKAtZrNZp7n+b7PORcEobIyHo9VVZVlGRfh5puhquAc5JrFGFQV/6rdxtOuvx7XX4/Tp1Gv42m6jqdddx1uugnf9/d/jyefxNN8H08LAvzjP+LcOZw7h6ft7+NfJQk4B3kxOEevhzNnYNvodmFZOEa+7w8Gg9lsJopis9lstVqKouBEYgzb2/if/xP/7b/hgQdAjpFloduFbYMxuK67v7/POS+VSu12u1qtghBCng8ZhFy06XSapqkoigBKpRJjTJZlSZJwaaRpOh6PXdeNoijPc8aYruumaWqahnWLosjzvCAIlsulIAj1et0wjGq1GsdxFEVxHOd5LggCnkurBXJNkeVcVSEIAoBWC7fcgtOn8apX4WnXX4+ntdv4PlUFY7iQV78ar341nolzJAm+b38fTzt3Dk/79rfxzW/iO9/BYICnJQk4B3kBOEevh+1tdLuwbTCGyyyO48FgEARBnueVSqXValWrVZxgnMNx0OnAcUCOkWWh14NlYbFYnDt34HkeANM0t7a2FEUBIYQ8TzIIuTjL5XI0GoVheOrUqWq1qmmaaZqCIOASWCwWQRB4nhfHMYBCoaCvqKqKtcrzfDKZuK47Ho+zLJMkyTAM0zTL5TJWVFWVZTlJkvl8rqoqnouq4tZb8eCDIFcxWc4VJRME4cyZxWtf6910k/aqV1VOnZIBqCoYw1owBsbwfa94BZ72ilfgaf/+34NzJAkGAzztf/9vPPIIzp5FnudJguVSAHk++n2cOQPbxu4ubBuM4TJYLpeu6w6HQ865oiibm5umaYqiiBOs38fODhwHnIMcF8Zg2+h2YVkIw3B/f386nTLG2u22aZoghJAXRAYhFy0MQwCSJLVarTRNRVHEuiVJ4q/M53MApVJJX5FlGWuVZVkQBJ7nTSaTPM8ZY6ZpGoahaRqeQZZlTdPG4/FsNlNVFc+FMbz1rXj4YXAOctVgDKqKLMsNY/EjPzL7hV8Yvexl01YL7ba+tdVUFAWXF2NgDJUKnvbyl+N978Nslv/93wf/5/9MHnnE3NtTgXyxEJdLAeQicI5eD2fOwLaxuwvbBmO4dMbj8cHBwXQ6FQTBMIxWq6WqKk4wzuE42NlBvw9yjCwL3S5sG5KUDQbDwWCQpmmlUrEsq1QqgRBCXigZhFwcWZZ//Md/PMsyQRAASJKEtYqiyPf90Wi0XC4FQajVarqu1+t1URSxVsvlMggC13XjOM7zvFAo6CuqquJ8NE0bj8fT6bTRaOAi3HILVBWcg1wFGMNP/mT+K78i/OzPzn3fl6QjWV6qqmQYhmmaqqriBGAMjAmveU3jVa8qvv3tg4ODwHXlwcD4H/+j9vjjxflc4BzkOXGOXg9nzsC20e3CsrB2SZIcHh56npfnealUarVa9XodJ1u/j50dOA44BzkujMG20e3CspAkyZNP7o9GI0EQNjc3W62WLMsghJAXQQYhF00QBEmSsFZZloVh6Pv+eDzOskySJMMwdF2vVCqCIGCtFouFvzKbzQAUi0XTNOv1uqIouDBN0wDEcYyLE0VRnpcAAeSKxRhUFT/6o/lHPyrcfDMfj92nlUpckqRGw2g2m5qm4eRRVfXGG1+q6/5gMHjJS/Zf85qjSqX57W9v3HMP/uZvJM5BnhPn6PWwvY1uF7YNxrAWWZa5rjscDufzOWOsuSLLMk4wzuE42NlBvw9yjCwL3S5sG4whCIJ+v58kSaFQaLfbuq6DEEJeNBmEHKvlcvnUU0/N53PGmGmahmFomoZ1S5LEX5nP54IglMtlwzDq9bosy3gumqbJspwkyWKxUBQFF5BlWRiGrutGUaTrPxpFBZArDWNQVbzylfjIR3DrrZCkZRh6jz/uzudzQRB0XW82m+VyGSebruvlcnkwGHieN5ns//iPh//rf21997vVX/3V/O/+TkgScA7y7Pp9nDkD28buLmwbjOHFCMNwMBhMJhNBEBqNRqvV0jQNJ1u/j50dOA44BzlGloVeD5aFNE37/cFwOMyyrF6vW5alqioIIWQdZBByrBRF0XVdFMVGo1EoFLBucRy7rhsEAedcEIRarWaaZrVaFUURF4cxpqrqdDpNkkRRFPyQLMuCIHBdN4qiPM/L5cKNN86feKIAcoVgDKqKV74SH/kIbr0VqgpBWPq+f3R0lCSJIAj1er3ZbFarVVwhFEV5yUteUq1WB4NBFEVx/JhlNb/+9c00ZWfP4p574DjgHORZcI5eD2fOwLbR7cKy8AIsFovDw0PP89I0LRaLrVar0WgIgoATjHM4DnZ20O+DHCPGYNvodmFZiOO43++HYShJkmVZGxsboiiCEELWRAYhx21jY0OWZaxVnueTycTzvPF4nKapJEm6rhuGUalUBEHA8yEIgqZpURTFcVytVvEMy+UyCALXdafTKYBCoWCapq7rH/qQsrcHzkFOOMZg2/jIR3DrrVBVMIYsy3zfPzo6iuNYEIRqtbqxsVGtVgVBwJWmXq+Xy+XhyuHh4WQy2drauu22+i/8AhwHOzvo90GeHefo9bC9jW4Xtg3GcJGyLPN9//DwMEkSSZJardbGxgZjDCdbv4+dHTgOOAc5RpaFbhe2DVnOXdfb39/nnBeLxVOnTlWrVRBCyFrJIOS4ybKM9cmyLAxD13XDMMzznDGm67phGKVSCS9UqVQCEEUR/sVyufR933Xd2WwGoFgsmqbZaDRkWe71ep/97MPA/wOoICcVY7Bt7O7CtsEYnpZlme8Hw+FwOp0CKJfLzWazXq+LoogrlizL7Xa7UqkcHBxMJpN//ud/Nk2z1Wptbyu9HnZ24DjgHOTZ9fs4cwa2jd1d2DYYw7OLomgwGIRhmOd5rVZrtVrlchknG+dwHOzsoN8HOV6WhV4PlgXO+ZNPHriuC8AwjHa7rSgKCCFk3WQQcrVYLpfj8dh13el0mud5oVBoNBqGYaiqihdH0zRJkpIkWS6XWZb5vu95XpIkAEqlkmma9XpdEIS9vb177733y1/+8mQC4COACnLyMAbbxu4ubBuM4Wl5no/H4+FwGEVRnueapjWbTV3XRVHEVaFSqWiadnR0NBwOj46OJpNJq9Vqt/W9PcFx0OnAccA5yLPgHL0ezpyBbaPbhWXhvJbL5XAlTdNCodBqtXRdF0URJxjncBx0OnAccA5yjBiDbaPbhWVhMpn0+/3pdMoYa7VazWZTEAQQQsglIIOQKx/nfDQaeZ4XxzGAYrGoryiKgnVQViaTyfe+973ZbLZYLARBqFQqpmnW6/U0Tf/4j//43nvvfeSRR5Ikwf+PAWeB20BOEsZg29jdhW2DMXxfGIbD4TAMwzzPi8WiaZq6rsuyjKuLJEmtVqtare7v74/H43PnzoVh2Gq1treLe3twHHQ6cBxwDvIsOEevh+1tdLuwbTCGZ/J9fzAYzGYzURSbzWar1VIUBSdbv4+dHTgOOAc5XpaFbhe2DUnKDg+PDg4O0jStVCrtdrtcLoMQQi4ZGYRcyZIk8Vfm8zmAUqlkmma9XpdlGeuTJEkURYPBYDabVavVWq1mmmatVkuS5MEHH7z33nv/5E/+hHOOFU3T3v72t1vWK37v9/LlUgA5ARiDbWN3F7YNxvB9URQNh8MgCPI8LxQKpmkahsEYw9VL07QbbrjBdd3Dw0Pf96Mo2tzcNE1ze1vc24PjYGcH/T7Is+v3ceYMbBu7u7BtMIY4jg8PD0ejUZ7nlUql1WpVq1WcbJzDcbCzg34f5HgxBttGtwvLwnw+f/LJ/mg0EgRhc3Oz1WrJsgxCCLmUZBByZYrj2PO80WjEORcEoVqtGoZRr9dFUcT6TKdT13VHo1Ecx3meK4py4403VqvVyWRy//33f/zjH9/b28uyDCu1Wu1d73rX+9///te//vWPPSZ+/OOYTECOnWWh24VtgzF8XxzHR0dHo9EoTVPGmLmiKAquAaIobmxsVKvVg4OD0Wj05JNPhmHYbrc1TdveRq+H7W30+yDPjnP0ejhzBraN//JfvFZrP88XiqJsbm6apimKIk62fh87O3AccA5yvCwL3S5sG4whCIL9/f3ZbFYoFNrttq7rIISQS08GIS/OcrmUZTkMQ2VFFEVcYlEUua4bBEGapqIoNhoN0zQrlYogCFifMAxd1w3DME1TSZJarZaqqtVqdT6f/8Ef/MEnPvGJv/iLv8jzHCumad5xxx2//Mu//DM/8zMgJwZjsG10u7AsfF+SJEdHR57npWkqy/Lm5qZpmqqq4hqjqupLX/rSarU6GAzG43EcxxsbG81m07KkXg8//dPLw0MZ5Llwjl4P73qXcdNNxY99zPuxH2uqqoqTjXM4DnZ20O+DHDvLQq8Hy0KWZfv7g8PDwyzLarWaZVnFYhGEEHJZyCDkxZlMJoIgLBaL4XD4spe9DJdMlmVhGHqeNx6P8zyXJMk0TcMwyuUy1ifLsjAMXdcNwzDPc8aYsVIoFP7sz/7sj/7oj7761a/+5V/+Jf5Fu92+88473/e+99188814hlYLrRYmE5BjwRhsG7u7sG0whqctFoujoyPP8zjnkiQ1m03TNDVNw7VKEATDMCqVymAwcF233++HYdhqtTQt/ehHx3fddf1yKYBcBM7xf/+vdttthS99SbJtMIYTq9/Hzg4cB5yDHC/GYNvodmFZiON4f39/PB5LktRutzc3N0VRBCGEXC4yCHlBsizzfb9er0+nU1EUwzAsFouSJOESSNN0PB67rhtFUZ7njDFd1w3DKBaLWJ8sy4IgcF03iqI8zxVFMQxD13VVVc+dO3f//fd/5StfCYJgOp1i5WUve9l73vOe9773vTfeeCN+iKri5pvxT/8EcvlZFrpd2DYYw9M4557nua47n88FQdB1vdlslstlEEBRlJe85CXVavXg4MB13e9973uyLMdxC+R5GgykM2dg29jdhW2DMZwonMNxsLODfh/k2FkWul3YNhiD53n7+/uLxaJYLFqWVavVQAghl5cMQl6Qxx9/vFKphGFYr9cPDg5Onz6d5znWbblc+ivT6RSAqqqGYei6rigK1me5XAZB4LrudDoFoKqqYRi6riuK8g//8A+f+tSnHnjggXPnzjWbzUqlomnaq1/96ttvv/2uu+667rrrcAGM4e678fDD4BzkcrIs9HqwLDxtuVz6vn90dJQkiSAI9Xq92WxWq1WQH6SqaqFQSJJkMkm+973GPffcuFwKIM8T5+j1cOYMbBvdLiwLJ0S/j50dOA44Bzl2loVeD5aF5XL5xBP7ruvmeW4YRrvdVhQFhBBy2ckg5PlbLpelUimOY03T6vX6y172MlEUsVaLxcL3fc/zkiQBUCqVDMNoNBqyLGN9OOej0cjzvDiOARSLRdM0G40GY+zb3/72Jz/5yc9+9rODwQArnue94hWveNOb3vS6173u9OnTW1tbeFY33wxVBecgl41lodeDZSHLMt/3h8PhbDYTBKFarTabzVqtJggCyDMsl0vXdY+OjhaLxXK5+Z//80899lg9TQWQF4pz9HrY3ka3C9sGYzhGnMNxsLODfh/k2DEG20a3C8tCFEX9fj+KIlmWt7a2ms2mIAgghJDjIIOQ50+SpFarlWWZKIoARFHE+sxmM8/zfN/nnAuCUKlUTNOs1WqSJGF9FouF7/uu687ncwClUsk0zXq9LknSt771rU984hNf+MIXfN/HiiAIr33ta9///vfffvvtaZru7+8fHR0tFotTp06pqooLaLVALhvGYNvodrG1lfl+MBwOp9MpgHK53Gw26/W6KIogz5Bl2Wg0Gg6HcRwLgrBYmHff3R4OGcg69Ps4cwa2jd1d2DYYw2XGORwHnQ4cB5yDHDvLQrcL24Ys58Ph0cHBwXK5LJfLlmWVy2UQQsjxkUHI8ycIAgBRFLFWURR5nhcEwXK5FAShXq8bhlGtVkVRxPokSeJ5nu/7i8VCEIRKpWKaZr1eB/CNb3zj4x//+EMPPTSZTLAiSdLP//zPf+ADH3jHO95RLpexoijKU089NR6PF4vFddddV6lUcD6qiltvxYMPglxqloVuFz/1U3kcj7/73WEURXmea5rWbDZ1XRdFEeQHhWE4HA7DMMzzvFKppGnrbW/ThkMZZH04R6+HM2dg2+h2YVm4bPp97OzAccA5yLFjDLaNbheWhcVice7cvud5giA0m812uy3LMggh5FjJIOTE0DRtf38/z3PDMEzTLJfLWKs4jj3PG41GnHNBEGq1mmma1Wo1TdOvfe1r99577yOPPDKbzbCiKMqb3vSmD3zgA295y1tUVcUzVKvVG2644amnnhqPx48//rhlWYZh4Icwhre+FQ8/DM5BLp12O+/1hEolfOKJYRiGeZ4Xi0XTNHVdl2UZ5AfNZrPDw8PRaJRlmaqqGxsbSWJsb+PwUAS5BDhHr4ftbXS7sG0whkuKczgOdnbQ74OcBJaFbhe2DcYwHo/7/f5sNlMUpd1uG4YBQgg5AWQQcmKIomgYxqlTpzRNw1pFUeS6bhAEaZpKktRoNEzTrFars9nsS1/60r333nv27FnOOVY0TXvb2972K7/yK2984xtlWcb5qKr60pe+dH9/33Xdc+fOzefzVqsliiJ+0C23QFXBOcgl0mqlX/96Mp8fHh4GeZ4XCgXTNA3DYIyB/CDO+dHRkeu6nHNZljc3N2s18zvfUXZ2cHAAckn1+zhzBraN3V3YNhjDpdDvY2cHjgPOQU4Cy0KvB8tClmX7+4PhcJimaa1Wa7fbmqaBEEJOBhmEnCSGYWB98jyfTCau647H4yzLJEkyTdMwjHK5PJlM7r///nvvvXdvby/LMqxUq9V3vetdH/jAB17/+teLoohnJcvyddddVygUDlYWi4VlWYwxkMtlY4M/+OAgjr00TRlj5oqiKCA/KMsy3/eHw+FsNhMEwTCMjY2N0Uj7d/8u/+u/BucglwHn6PVw5gxsG90uLAtrxDkcBzs76PdBTgLGYNvodmH9f+zBW4wr930f8O/ch/fbDC/z556zZxVLtiPb6cAOH5oTNIFS1AjgFKABGbFjQ5EeA+gp8GPfiqboix7y4tjyJRbiAJk4KIy0cB0U6KZJx2noykgVXfecPcsZksPhnVySM+RMV2socOPYkXT2nMPd/X0+DMvl0nGcyWTC83ytVqtUKoIggBBCdoYIQq6iKIqm06nv+9PpNI5jSZI0TSuVSslkcjgcfulLX3rxxRe///3vx3GMc5qmffrTn/7t3/7tT3ziE3jXOI6rVCqKorTb7cFgEARBvV5PJpN4R7WKahWzGciFK5fDP/zD1yVpxXFipVLRNE1VVZCfMB6PPc+bzWYAstlspVJJJLKtFppNOA4H8nCFIWwbjQYsC6YJScL9cxw0m2i1EIYgu4AxWBZME5KE4XDouu56vU4kEoZh5PN5EELIjhFByNWy3W4nk4nv+/P5PI5jRVGK51RV7Xa7X/rSl7761a/+8Ic/xDsMw/jMZz7zzDPPPPnkk3hf8vm8JEknJyez2ezo6Kher+fzeZxTVTz5JN54A+Rilcvh17729+VyVCzqmqYlk0mQn3B6etrr9UajURzHiUSiXC4Xi8VOh//X/xqtFsIQ5FFxHNy+DdPECy/ANCFJeH/CEK0Wmk04DsiOYAy2Dcaw2Wza7a7neXEcFwoFxpiiKCCEkN0jgpCrYrPZjMdj3/cXiwUAVVVLpVKxWJRl+fj4+KWXXvrGN77x2muv4R37+/uf+9znPv/5z3/gAx/A/UmlUgcHB+12ezQa3b171zCMcrkMQJLwW7+F73wHYQhyUSqVzde//toTT2Q1TUun0yA/IQgCz/N8399ut5Ik6efiWPybv0GzCccBeeTCELaN27dhmnjhBZgmJAnvieOg2USrhTAE2QWSBNOEZYExzOdz13Vns5kgCLVaTdd1nudBCCE7SQQhl18YhqPRyPf95XIJIJFIaJpWLBZFUXz99de/8Y1vfPOb3zw+PsY7PvjBD37hC1/4zd/8zRs3buCCyLK8v7+vKEqv12u32+v12jAMQRCeegqqijAEuSi/8Rvzj350v1ZLg/yE7XY7GAw8z1uv14Ig6LpeLpcFQf3bv8Xzz6PVQhiC7I4whG3j9m2YJiwLjOHdCEO0Wmg24TggO4IxWBZME6IYe16/2+2GYZhKpRhjmUwGhBCyw0QQctE2mw1/Dg9eEASDc+v1muO4VCqlaVo+nxdF8Yc//OHXvva1b33rW51OB+/4hV/4hWeeeebpp5+uVCq4aDzPM8YURXEcx/O8IAjq9bqqKr/8y/judxGGIBfixRdzrVb0Z38GxkD+QRzH4/G41+stFgsAuVyuUqmoaqbVwvPPo9VCGILspjCEbaPRgGXBNCFJ+GnCEK0Wnn8erRbCEGQXSBJME5YFxhAEwfGxOxwOAei6XqvVJEkCIYTsNhGEXJzNZiOK4ng8XiwWN2/exIO0Wq0Gg8FwOAyCgOO4TCajaVo+n+c47m/+5m9efPHFP/mTPxkMBjjHcVyj0Xj22WebzWahUMCDpGmaLMvtdns8HgdBsLe39+1vp1st/Nt/u+12BZD7ttlw//t/C40GLAumCUkCmc/nnueNx+M4jlOpVLlcTqcLP/gB9/zzaLUQhiC7z3Fw+zZMEy+8ANOEJOEfcRw0m2i1EIYgO6Jc3vzn/yyaJiQJ0+nUcZzT01NJkgzD0DQNhBByGYgg5CJst1tBEEajkeu6wrntdisIAh6A09NT3/fH43EYhjzP53I5TdOy2SyAw8PDr3zlK3/2Z382m81wThCEX/7lX37uuec+9alPpdNpPBTZbPbg4ODk5GQ6nR4dHdXr9X/xL9J//ufjf/NvCp4ngVwEx8Ht2zBNvPACTBOShOtptVp5njccDrfbraIouq5ns6Uf/lB8/nm0WghDkEskDGHbuH0bpgnLAmP4kTBEq4VmE44Dsjsqlc23vnX02GNFjst3u363291ut9lsljGWTCZBCCGXhAhCLsLx8XGxWOz3+7VardPpZLNZQRBw0ebzue/74/F4u90KglAsFjVNy2QyYRh+97vf/fKXv/znf/7ny+US52RZfuqpp5577rlPfvKTqqri4VJV9datW67rdrvdl19+WRTFRCLx9a/3nnvuI44DciHCELaN27dhmnjhBZgmJAnXx2az8X2/3+8HQSAIQqlUSaf1w0PlP/yH+Ac/QBiCXFJhCNtGowHLwoc/jFdewfPPo9VCGILsCEmCaeI//sfjVGr25pvD1WrF83w6na6eEwQBhBByeYgg5L5NJpNCoeC6riAIQRB87GMf22w2uDhxHM9mM9/3J5NJFEWCIGjnUqnUarX69re//Qd/8Aff+973wjDEuUQi8eu//uvPPffcr/7qr0qShEdku93yPB8EwWQyieO4Uql84hO3/tf/ij/9aa7VQhiCXIgwhG3j9m2YJl54AaYJScLVFkXReDzu9Xqnp6ccx2UyRdet/vZvC2++Ka9WCEMO5PJzHNy+DVXFaoUwBNkdjMGyYJoQhFt3795988035/O5LMvZbDadTguCAEIIuVREEHLfksnka6+9Vq/X0+k0z/MARFHERYiiaDqd+r4/nU7jOJYkSdf1YrGYTCZns9lLL7305S9/+fDwcLvd4lw2m/2N3/iN55577pd+6Zd4nscjslqtBufCMEwmk/v7+0EQ8Dw/GAzq9cThYbLVQrMJxwG5KGEI28bt2zBNvPACTBOShCtpOp16njedTsMQkpR95RXjP/0n8ZVXlDAEuWLCEGEIsjskCaYJywJj2Gw2rtudTCaFQkHTNJ7nt9vtW2+9lc/ny+VyOp0GIYRcEiIIuW+SJD355JPb7VYQBFyQKIrG47Hv+/P5PI5jRVGK51RVHQ6HL7300le+8pXvf//7cRzjXKlU+vSnP/3ss89+/OMf5zgOj8hqtfJ9fzgchmHIcVyhUNA0LZvNzufzdrs9m83u3LlTr9cbjZxto9GA44BcoDCEbeP2bZgmvvhFPPUUVBWShKthuVx6bxutVvjBD7Q/+IPSnTuJIODDEISQB40xWBZME5KExWLhOM5sNhNFcW9vr1wubzabwWDg+/5oNJpMJoVCoVwuJ5NJEELIzhNByAURBAEXJwiCdrsdhqGqqqVSqVgsyrLc7Xb/+I//+Ktf/erLL7+Md9Rqtc985jPPPPPMRz7yETw6q9XK9/3hcBiGIc/zhUJB1/VMJoNz6XT64OCg3W6PRqM7d+4YhsFY2bbRaMBxQC5WGMK28fTTUFV8+MP44hfx1FNQVUgSLqnT07Dd9l9/ffrqq+LXv/6BoyM1CPjNhgMh5KFgDLYNxnDG933XdcMwTKVShmFks1kAsizXarVisdjv94fD4WAwGI/HpVJJ13VVVUEIITtMBCE7SVXVYrEoy3KxWBRF8d69e1gJpT4AACAASURBVC+99NLXv/711157De/Y39//3Oc+9/nPf/4DH/gAHp3lcun7/nA43Gw2PM8Xi0Vd19PpNP5/sizv7+/Lsux5XrvdDoLAMAzb5hsNOA7IhQtDhCFsG08/DVXFhz+ML34RTz6JahWqCknCjgtDrFZw3ci253/6p+m/+ItqHFfWa26z4UAIeVgkCaYJywJjCIKg0+kMBgMAmqbVajVZlvFjFEWp1+ulUqnf7w+HQ8/zRqORdk6WZRBCyE4SQQiw2Ww4jhMEAbukVqsJgvDGG2984xvf+OY3v3n37l2844knnvjCF77w2c9+9saNG3h0Tk9Pfd8fjUabzUYQhFKppGlaOp3GT8HzPGNMURTHcXq9XhAE9XrdtuVmE60WwhDkQQhDhCFsG08/DVXFmaeewm/9Fp58EtUqVBWShB0Rhlit0O3i7/4Of/iH+N73APCrVTYMcY4DIeQhYgyWBdOEJGE6nbquu1gsJEkyDEPTNPwUiUTixo0bpVLJ87zRaNTpdIbDoXZOFEUQQsiOEUGuvTiOX3755RdffPH3f//3sUteeeWVr371q9/61rc6nQ7e8bGPfeyZZ555+umnq9UqHp3T01Pf94fD4Xa7FQShVCppmpZOp/HP4ThO13VFUU5OTkajURAE9Xr98DDdaqHZhOOAPDhhiDDEmW9/G9/5DlQVZ556Cp/8JG7exK1bqFZxRlUhSXjQwhCrFX7kr/8aZ46P8V/+C773PZxZrRCGIIQ8QozBtsEYoijqdr1ut7vdbjOZDGMslUrhn5NKpW7dulUqlTzPm06njuMMh0Nd14vFoiAIIISQnSGCXHuLxUKSpM985jMnJyf1ep3jOOyGbDb7p3/6p51OBwDHcb/4i7/47LPPNpvNYrGIR2exWPi+PxqNttutIAiapum6nkwm8V5ks9mDg4OTk5PZbHZ0dFSv1xuNom2j0YDjgDwEYYgwxJlvfxvf+Q5UFT9SreJf/Ss8/jjyedy4gZs3ccYw8A9UFZKEdyMMsVrhH7guzhwf4949jMd4/XUcH+Ov/xr/YLVCGIIQ8shJEkwTlgXGsFqtXNcdjUYcx1UqlWq1Kooi3rVsNpvJZCaTied5s9ns3r17g8GgXC7n83me50EIITtABLn20un0l7/85V/7tV9jjHEch51x8+bNz372s7/3e793+/bt55577lOf+lQmk8GjM5/Pfd8fj8fb7VYQBF3XNU1LJpN4XxKJxMHBgeM4vu8fHx8HQWAYFdvmGg04DsjDFIYIQ/zIbIY33oAkQVXx4wwDZ27exEc/ikoF+TzOFIv4+Z+HYeBHXBf/9/9iOMSZ8Ri9Hn74Qxwf44zr4setVghDEEJ2EGOwLJgmJAnj8dhxnNVqpSiKYRjFYhHvHcdx+Xw+m82Ox2PP8xaLxZ07dzKZTLlczuVyHMeBEEIeKRHk2ovj+IUXXoiiiOd57JgvfOELH//4xz/5yU+qqopHZz6f+74/Ho+3260oirqua5qWTCZxf0RRvHHjhqIonU7HcZz1es0Ys22x2USrhTAEeVTCEGGIH/faazjz2mv47nchSVBV/GyrFcIQhJBLRJJgmrAsMIbtdus4Xc/zoijK5/OMMVVVcR94ni8Wi7lcbjgc9vv92Ww2n89zuZyu69lsFoQQ8uiIINcex3EABEHA7nn8HB6d+Xze7/fH43EURZIklUolTdMSiQQuCMdx1WpVluV2u+37/nq93tvbOzxMtFpoNuE4IDsoDBGGIIRcJYzBsmCakCScnp46jjOdTgVBYIyVy2We53ERBEHQdb1QKPjnxuPxZDIpFAq6rqfTaRBCyKMggpAHJo7j7Xa72WwUReE4DpfKdDr1fX8ymURRJEmSruuapqmqigegWCzKstxut2ez2dHR0d7eXqORtW00GnAcEEIIeaAYg22DMZzxfd913TAMk8kkYyybzeKiiaJYrVaLxaJ/bjgcTiaTYrGo63oikQAhhDxcIgh5MKIoGg6HnU5HUZSDgwNRFHFJTKdT3/fH43Ecx5Ik6bquaZqqqniQ0un0wcFBu90ejUZHR0fsbbpto9GA44AQQsiDIEkwTVgWGEMYhp1Ox/d9AKVSyTAMWZbxwMiybBhGsVjs9/uDwaDf74/H42KxqOu6oigghJCHRQQhFy0MQwC9Xk9RlPV6nclkeJ7HzovjeDab9fv9yWQSx7Esy8VisVQqqaqKh0KW5f39fVmWPc87OTlZr9eGYdg232yi1UIYghBCyAViDJYF04QkYTabOY6zWCwkSapWq7qucxyHB09V1b29vVKp5HneaDTq9Xqj0UjTtFKpJMsyCCHkwRNByIWKoqjdbs9ms2KxOBqNnnjiiUQiwfM8dlgcx5PJxPf96XQax7Esy6VziqLg4eJ5vl6vy7Lsum6v1wuCoF6vHx7KrRaaTTgOCCGEXAjGYNtgDFEU9Xr9Tqez3W4zmYxhGOl0Gg9XMpnc39/XNM3zvPF47LrucDjUdb1YLIqiCEIIeZBEEHKhoihaLpdRFCmKYhgGAJ7nsaviOJ5MJr7vT6fTOI4VRSkWi5qmybKMR6dcLiuK0m63R6NREAR7e3uNRsq20WjAcUAIIeR+SBJME5YFxrBerx3HGY1GHMdVKpVqtSqKIh6R9LnJZOJ53mw2Ozk5WSwWt27dAiGEPEgiCLlQgiD83M/9HM/zAHiex66Komg6nfb7/dlsFsexoiiaphWLRVmWsQNyuZwkSe12ezabHR0d1et1xgq2jUYDjgNCCCHvD2OwLJgmJAnj8dh13eVyqSiKYRjFYhE7IJfLZTKZyWTieZ6u6yCEkAdMBCEXiuM4WZaxw6Iomkwm/X5/Pp/HcayqaumcJEnYJclk8uDgoN1uDwaD4+Pj9XptGBXb5hoNOA4IIYS8J5IE04RlgTFst1vX7Z2JoiifzxuGkUgksDN4ni8UCrlcjud5EELIAyaCkGsjiqLxeOz7/nw+j+NYVdXSOUmSsJNEUbxx44Ysy91u13GcIAgMw7BtsdlEq4UwBCGEkHeDMVgWTBOShNPTU9d1J5OJIAi1Wq1arfI8j93D8zwIIeTBE0HINRBF0Xg87vf78/kcgKqquq4Xi0VRFLHbeJ43DENV1Xa73e/3gyCo1+uHh2qrhWYTjgNCCCE/G2OwbTCGM4PBwHXdIAgSiQRjLJfLgRBCrjcRhFxp2+12PB73+/3FYgEgkUhomlYsFkVRxOVRLBZlWT45OZlMJkEQ1Ov1RiNr22g04DgghBDyT5IkmCYsC4xhs9m4ruv7fhzHpVLJMAxZlkEIIdeeCEKuqO12OxqNfN9fLBYAksmkpmmFQkEURVxC6XT64ODg5ORkMpncuXOHvU2zbTQacBwQQgj5RxiDZcE0IUmYz+ftdnuxWIiiWKvVdF3nOA6X3Gq1iqJos9nIsqyqKggh5H0RQciVs9lsxuOx7/uLxQJAKpXSNC2fz4uiiMtMUZRbt265rtvv9+/duxcEQa1WtW2+2USrhTAEIYSQH2EMtg3GEMex5/U7nc5ms0mn04yxdDqNKyGKItd1oygql8s4p6oqCCHkPRJByNWyXq/feuut5XIJIJVKaZpWKBQEQcCVIAjC3t6eoiiu63Y6ndVqVa/XDw/lVgvNJhwHhBByzUkSTBOWBcYQBIHruoPBgOM4XdcNwxBFEVeFIAj7+/uvvvqq67pRFMmy/Pjjj4MQQt4jEYRcLYqi5PN5nud1Xc/n84Ig4Mopl8uyLLfb7dFoFATBjRs3Go2kbaPRgOOAEEKuLcZgWTBNSBLG47HrusvlUpZlwzBKpRKuFkVRADz++OObzWY2m+Xz+SiKeJ4HIYS8FyIIuXKKxWK1WuV5HldXPp+XZbndbs9ms6Ojo3q9zljettFowHFACCHXjSTBNGFZYAxRFLlut9frRVGUy+UMw0gmk7ii5HPJZBKEEPK+iCDkylFVFddAMpm8deuW4ziDweDu3bu1Wo2xim2j0YDjgBBCrg/GYFkwTUgSlsul4ziTyYTn+VqtVq1WeZ4HIYSQn0IEIeTSkiTpxo0bsix3u13HcdbrtWEYti02m2i1EIYghJArjzHYNhjDmeFw6Lruer1OJBKGYeTzeRBCCPmZRBBCLjOe5w3DkGXZdd1+vx8EQb1ePzxUWy00m3AcEELIVSVJME1YFhjDZrPpdrue58VxXCgUGGOKooAQQsg/RwQh5PLTNE1RlJOTk8lkEgTB3t5eo5GxbfziL8auy4EQQq4cxmBZME1IEubzueu6s9lMEIRarabrOs/zIIQQ8i6IIIRcCZlM5rHHHjs5OZlMJnfu3GFvK/33/356+7bseRIIIeQKYQy2DcYQx7Hn9bvdbhiGqVSKMZbJZEAIIeRdE0EIuSoURdnf33dd1/f9N954486dOzzPf+1r4r/7d0/+n//DhyEIIeSykySYJiwLjCEIAtd1h8MhAF3Xa7WaJEkghBDyXoggZCcFQSCKYhRFoiiCvGuiKGqaNhwOPc/bbDa5XO5DH3rsL/4ieOUVtdmE44AQQi4vxmBZME1IEqbTabvdXi6XkiQZhqFpGgghhLx3IgjZPVEUvf7669lsVlXVcrkM8u6s1+t+vz8cDrfbraZpQRCoqhoEgSBEjQZsG40GHAeEEHLpSBJME5YFxhBFUbfrdbvd7XabzWYZY8lkEoQQQt4XEYTskvF47Pt+FEWiKG6323w+D/IuBEHg+/5gMAiCgOf5Uqmk6zrHcffu3ZvNZkdHR/V6nbG8baPRgOOAEEIuEcZgWTBNSBJWq5XjOOPxmOf56jlBEEAIIeT9EkHIzthsNjzPL5fLZDJ569atKIpkWQb5mTabzWAw6Pf76/Wa47hCoVAul9PpNM4dHBw4jjMcDu/evWsYBmNl20ajAccBIYRcCozBtsEYzgyHQ9d11+u1qqqMsXw+D0IIIfdHBCE7QxTFbDb7kY98ZLvdCoIA8jNtt9vhcNjv95fLJcdxuVyuXC5ns1n8GFmWb968qShKt9ttt9vr9dowDNsWmk20WghDEELIzpIkmCYsC4xhs9l0u13P8+I4LhQKhmGoqgpCCCH3TQQhu0cQBJCfLoqi0WjU7/cXiwWATCZTLpdzuRzHcfgJPM8bhiHLsuM4nuet1+u9vb3DQ6XVQrMJxwEhhOwgxmBZME1IEhaLheM4s9lMEIRqtVoul3meByGEkIsgghByecRxPJlMPM+bzWYAUqmUruuFQoHnefxMmqbJstxutyeTSRiGe3t7jUbattFowHFACCE7hTHYNhjDGd/3XdcNwzCVShmGkc1mQQgh5OKIIIRcEtPp1PO86XQax3EikdB1vVgsCoKAdyebzR4cHLTb7clkcnR0VK/XGSvaNhoNOA4IIWQXSBJME5YFxhAEQafTGQwGADRNq9VqsiyDEELIhRJBCNl58/nc87zxeBzHsaIouq6XSiVRFPEeqaq6v7/vum6/37979+5qtarVqrbNN5totRCGIISQR4gxWBZME5KE6XTquu5isZAkyTAMTdNACCHkARBBCNlhi8Wi3++PRqMoimRZLpVKmqbJsoz3SxTFvb09WZa73W6n0wmCgDF2eCi1Wmg24TgghJCHT5JgmrAsMIYoirpdr9vtbrfbTCbDGEulUiCEEPJgiCCE7KTlctnv94fD4Xa7lSRJP6coCu4bx3HValVRlHa7PRgMgiCo1+uNRtK20WjAcUAIIQ8TY7AsmCYkCavVynXd0WjEcVylUqlWq6IoghBCyAMjghCyY1arle/7w+EwDENBEPRziUQCF6pQKMiyfHJyMpvNjo6O6vU6Y3nbRqMBxwEhhDwcjMG2wRjOjEYj13VXq5WiKIZhFItFEEIIecBEEEJ2RhAE/rkwDHmeL5VK5XI5mUziwUilUgcHB+12ezQa3b171zAMxsq2jWYTrRbCEIQQ8uBIEkwTlgXGsN1uu91ur9eL4zifzzPGVFUFIYSQB08EIWQHbDYb/9x6veY4rlAolMvldDqNB0yW5f39fVmWPc9rt9tBEBiGcXjIt1poNuE4IISQB4ExWBZME5KE09NTx3Gm06kgCNVqtVwu8zwPQgghD4UIQsgjtd1uh8Nhv99fLpccx+VyuXK5nM1m8bDwPF+v11VVdRyn1+ut1+u9vb1GQ7ZtNBpwHBBCyAWSJJgmLAuM4Yzv+67rhmGYTCYZY9lsFuSfEkXRyy+//Pjjj4uiqCgKCCHkgogghDwiURSNRqN+v79YLABkMplyuZzL5TiOw0OnaZosyycnJ+PxOAzDer3OWNq20WjAcUAIIReCMVgWTBOShDAMO52O7/sASqWSYRiyLIP8U9br9V/+5V/+7d/+7R/90R89++yzTzzxBAgh5IKIIIQ8dFEUTSaTfr8/m80ApFKpcrmcz+d5nsejk81mH3vssXv37s1ms6Ojo3q9zljRttFowHFACCH3iTHYNhjDmdls5jjOYrGQJKlareq6znEcyE8RRdGv/Mqv/P3f//3v/u7v6roOQgi5OCIIIQ/XZDLp9/vT6TSO40Qioet6sVgUBAE7QFXVg4MDx3F83z8+Pg6CwDAqts01m2i1EIYghJD3QZJgmrAsMIYoivr9fqfT2W63mUzGMIx0Og3yMyUSCQC/8zu/A0IIuWgiCCEPy2w26/f74/E4jmNFUXRdL5VKoihil4iieOPGDUVROp2O4zir1aperx8eiq0Wmk04Dggh5D1hDJYF04QkYbVaua47Go04jqtUKtVqVRRFEEIIeXREEEIevMVi0e/3R6NRFEWyLJdKJU3TZFnGTuI4rlqtyrLcbrcHg0EQBHt7e41GwrbRaMBxQAgh7xJjsG0whjPj8dh13eVyqSiKYRjFYhGEEEIeNRGEkAdpuVz2+/3hcLjdbiVJ0s8pioKdVywWZVlut9uz2ezo6Ghvb4+xrG2j0YDjgBBCfjZJgmnCssAYtttt71wURblcjjGWSCRACCFkB4gghDwYq9XK9/3hcBiGoSAI5XJZ07REIoHLI51OHxwctNvt0Wh0dHTE3qbbNppNtFoIQxBCyD+JMVgWTBOShNPTU9d1J5OJIAi1Wq1arfI8D0IIIbtBBCHkogVB4J8Lw5Dn+VKpVC6Xk8kkLiFZlvf392VZ9jzv5OQkCIJarXZ4yLdaaDbhOCCEkB8nSTBNWBYYw5nBYOC6bhAEiUSCMZbL5UAIIWSXiCCEXJzNZuOfW6/XHMcVCoVyuZxOp3GZ8Txfr9dlWXZdt9vtrtfrer3eaMi2jUYDjgNCCPkRxmBZME1IEjabjeu6vu/HcVwqlQzDkGUZhBBCdowIQshF2G63g8HA9/3lcslxXC6X03U9l8vhqiiXy4qinJycjEajIAjq9TpjadtGowHHASGEMAbbBmM4M5/P2+32YrEQRbFWq+m6znEcCCGE7B4RhJD7E8fxcDjs9/uLxQJAJpMpl8u5XI7jOFwtuVxOluWTk5PZbHbnzh32tqJto9GA44AQcm1JEkwTlgXGEMdxv9/vdDqbzSadTjPG0uk0CCGE7CoRhJD7w3GcJEmnp6epVKpcLufzeZ7ncUUlEomDg4N2uz0YDI6Pj4MgMIyKbXPNJlothCEIIdcNY7AsmCYkCUEQuK47GAw4jtN13TAMURRBCCFkh4kghNy3bDZ748aNQqEgCAKuOlEUb9y4oShKp9NxHCcIAsMwDg/FVgvNJhwHhJDrgzHYNhjDmfF47LrucrlUFKVWq5VKJRBCCNl5IgghF0HTNFwbPM/XajVFUdrtdr/fX6/Xe3t7jYZq22g04DgghFx5kgTThGWBMURR1O12Pc/bbre5XM4wjGQyCUIIIZeBCEIIeV+KxaIsyycnJ9Pp9OjoqF6vM5a1bTQacBwQQq4wxmBZME1IEpbLpeM4k8mE5/larVatVnmeByGEkEtCBCGEvF/pdPrg4KDdbo/H4zt37rC3abaNZhOtFsIQhJArRpJgmrAsMIYzw+HQdd31ep1IJAzDyOfzIIQQcqmIIISQ+6Aoyv7+fqfT8Tzv3r176/W6VqsdHvKtFppNOA4IIVcGY7AsmCYkCZvNptPp9Pv9OI6LxaJhGIqigBBCyGUjghBC7o8gCPV6XZZl13W73e56va7X642GbNv4xCeiTocHIeTyYwy2DcZwZj6fu647m81EUaxWq7qu8zwPQgghl5AIQgi5COVyWZbldrs9Go2CINjb2zOM5H/7b9Nf/dWU50kghFxakgTThGWBMcRx3O/3u91uGIapVIoxlslkQAgh5NISQQghFySfz8uy3G63Z7PZK6+8Isvydrv92tfE5577qOuCEHIZMQbLgmlCkhAEgeu6w+EQgK7rtVpNkiQQQgi5zEQQQs5tNhtRFLfbrSAIIO9XMpk0DOOVV15xXReAruum+XN/9Vebp58WWy2EIQghlwhjsG0whjPT6bTdbi+XS0mSDMPQNA2EEEIuPxGEkHOvvvpqOp2uVqtRFEmSBPLebTYb3/c9z+N5Pp/PR1EkSdJ6vWYMh4dotdBswnFACNl9kgTThGWBMURR1Du33W6z2SxjLJlMghBCyJUggpDrLQzD4+PjZDJZq9W63e7p6Wk2mwV5j6IoGo1GvV5vuVxyHFcsFj/0oQ+tVivHcfr9fhAE9Xq90VBtG40GHAeEkF3GGCwLpglJwmq1chxnPB7zPF89JwgCCCGEXBUiCLneRqORoijD4bBSqTz22GOqqoK8R9Pp1PO86XQax3EmkymXy/l8HkAqlZJl+eTkZDKZBEFQr9cZy9o2Gg04DgghO0iSYJqwLDCGM8Ph0HXd9XqtqipjLJ/PgxBCyNUigpDrrVQqxXFcq9UAiKII8l6cnp56njcajaIoUlW1XC6XSiWe5/GOTCZzcHDQbrcnk8ndu3cNw2BMs200m2i1EIYghOwOxmBZME1IEjabTbfb9TwvjuNCoWAYhqqqIIQQcuWIIOR6EwQB5L0LgsA/F4ahJEmVSkXTNFmW8RNUVb1165bruv1+/969e0EQ1GrVw0O+1UKzCccBIWQXMAbbBmM4s1gsHMeZzWaCINRqNV3XeZ4HIYSQq0gEIYS8F1EUDYdDz/OWyyXHcaVSqVwuJ5NJ/HSCIOzt7SmK4rpup9NZr9eMsUZDtm00GnAcEEIeIUmCacKywBjO9Pv9TqcThmEqlWKMZTIZEEIIubpEEELIuzYejz3Pm81mALLZbKVSyWazeHfK5bIsy+12ezgcBkGwt7fHWNK20WjAcUAIeSQYg2XBNCFJCIKg0+kMBgMAmqbVajVZlkEIIeRKE0EIIe/C6elpr9cbjUZxHCcSiXK5XCwWeZ7He5HP52VZPjk5mc/nR0dH9Xqdsbxto9GA44AQ8jBJEkwTlgXGcGY6nbquu1gsJEkyDEPTNBBCCLkGRBBCyM8UBIHneb7vb7dbSZLK5bKmaaIo4n1JJpO3bt1yHGc4HN69e9cwDMbKto1mE60WwhCEkIeAMVgWTBOShCiKPM/rdrvb7TaTyTDGUqkUCCGEXA8iCCHkp9hut4PBwPO89XotCIKu6+VyWVVV3B9Zlm/evKkoSrfbbbfb6/XaMIzDQ6HVQrMJxwEh5IFiDLYNxnBmtVq5rjsajXier1Qq1WpVFEUQQgi5NkQQQshPiON4PB73er3FYsFxXC6Xq1ar6XQaF4TnecMwZFl2XdfzvPV6Xa/XGw3VttFowHFACHkQJAmmCcsCYzgzGo0cx1mv14qiGIZRLBZBCCHkmhFBCCH/v/l83uv1JpNJHMepVKpcLhcKBY7jcNE0TZNlud1uTyaTIAj29vYYy9g2Gg04DgghF4sxWBZME5KEzWbT6/U8z4uiqFAoGIahqioIIYRcPyIIIeQdq9XK87zhcLjdbhVF0XW9VCqJoogHJpvNHhwctNvtyWRy584d9raSbaPZRKuFMAQh5EIwBtsGYzhzenrabrdns5kgCIyxcrnM8zwIIYRcSyIIIQTYbDa+7/f7/SAIBEGoVCq6riuKggdPVdX9/X3XdX3fPz4+Xq/XtVr18JBvtdBswnFACLkfkgTThGWBMZzxfd913TAMk8kkYyybzYIQQsg1JoIQcr1FUTQajTzPOz095TiuUChUKpVUKoWHSBTFvb09WZa73W6n0wmCgDHWaEi2jUYDjgNCyPvDGCwLpglJQhiGnU7H930ApVLJMAxZlkEIIeR6E0EIucam06nnedPpNI7jTCZTLpfz+TweBY7jqtWqoijtdnswGARBUK/XGUvaNhoNOA4IIe+JKMYf/ODyv/7XJGM4M5vNHMdZLBaSJNVqNU3TOI4DIYSQa08EIeRaWi6XvV5vNBpFUaSqarlcLpVKPM/jkSoUCrIsn5yczGazo6Ojer3OWN620Wyi1UIYghDybhgG/v2/f+3nf34dx6UgKI9Go06ns91uM5mMYRjpdBqEEELIORGEkGsmDMN+v+/7fhiGkiRVKhVN02RZxm5IpVIHBwftdns0Gt29e9cwDMbKh4dotdBswnFACPnZGMP//J8bScp6ntdut998801BENLpdKVSqVaroiiCEEIIeYcIQsi1EUXRcDj0PG+5XHIcVyqVyuVyMpnEjpFleX9/X1GUXq/XbreDIKjVao2GYNtoNOA4IIT8kyQJpgnLAmMiYERR9Oqrr06nU1mWC4VCuVwWRRGEEELIjxFBCLkexuOx53mz2QxANputVCrZbBa7iud5xpiiKI7j9Hq99Xpdr9cZU2wbjQYcB4SQf4QxWBZME5KE7Xbb6/X6/X4+n8/lchzHrdfrN954o1qtFotFjuNACCGEnBNBCLnqTk9Pe73eaDSK4ziRSJTL5WKxyPM8dp6mabIst9vt8XgcBMHe3h5jadtGowHHASHkHzAG2wZjOHN6euq67mQyEQSBMVapVFarleu6k8nk+Ph4Op3WajVVVUEIIYQAIgghV1cQBJ7n+b6/3W4lSdLPiaKIyyObzR4cHJycnEyn06Ojo3q9zljRkQn6lgAAIABJREFUttFsotVCGIKQa06SYJqwLDCGM77vdzqdIAgSiQRjLJfLAUgmkwcHB77v93q94XA4n88rlYqmaTzPgxBCyPUmghByFW2328Fg4Hneer0WBEHX9XK5rKoqLiFVVW/duuW6br/fPz4+Xq/XtVrl8JBvtdBswnFAyLXFGCwLpglJwmazcV3X930ApVLJMAxZlvEOnufL5XI2m+10OqPR6OTkZDqdGoaRTCZBCCHkGhNBCLla4jgej8e9Xm+xWHAcl8vlKpVKJpPBZSaK4t7enizLnU7Hdd31el2v1xsN0bbRaMBxQMh1I0kwTVgWGMOZ+XzebrcXi4UkSdVqVdd1juPwE1RV3d/fz2az3W53Mpmcnp6Wy2Vd1wVBACGEkGtJBCHkCpnP557njcfjOI5TqVS5XC4UChzH4fLjOK5arcqy3G63B4NBEAR7e3uMJWwbjQYcB4RcH4zBsmCakCTEcdzv9zudzmazSafTjLF0Oo2fjuO4UqmUyWS63a7v+47jTKfTWq2WyWRACCHk+hFBCLkSVquV53nD4XC73SqKout6qVQSRRFXS7FYlGW53W7PZrOjo6N6vc5YzrbRbKLVQhiCkCuPMdg2GMOZ9Xrtuu5wOOQ4rlwu12o1URTxLsiyfOPGjWw22+l0ZrPZ6elp+ZwoiiCEEHKdiCCEXHKbzcb3/X6/HwSBIAiVSkXXdUVRcEWl0+mDg4N2uz0aje7cucPeph8eotVCswnHASFXlSTBNGFZYAxnxuOx67rL5VJRlFqtViqV8B7l8/lUKtXr9Xzf73Q60+m0Wq3m83kQQgi5NkQQQi45z/M6nQ7HcYVCoVKppFIpXHWyLO/v78uy7HneycnJer02DKPR4G0bjQYcB4RcPYzBsmCakCREUdTtdj3P2263uVzOMIxkMon3RZKker2ezWY7nc58Pj86OtI0rVqtyrIMQggh14AIQsglp2nabDarVCr5fB7XBs/z9XpdURTHcXq9XhAE9XqdMdm20WjAcUDIVcIYbBuM4cxyuXQcZzKZ8Dxfq9Wq1SrP87g/2Ww2mUx65/r9/nw+r1arxWIRhBBCrjoRhJBLTpblD3zgAzzP4/rRdV2W5Xa7PRqNgiCo1+uMpW0bjQYcB4RcAZIE04RlgTGcGQ6Hruuu1+tEImEYRj6fxwURRdEwjGw22+12J5PJ3bt3p9NptVpVVRWEEEKuLhGEkMuP53lcV7lcTpblk5OT2Wx2dHRUr9cZK9o2mk20WghDEHJ5MQbLgmlCkrDZbDqdTr/fj+O4WCwahqEoCi5aOp0+ODjwfb/b7Q4Gg/l8Xq1WS6USx3EghBByFYkghJBLLpFIHBwctNvtwWBwfHwcBIFhVA4PuVYLzSYcB4RcOpIE04RlgTGcmc/nruvOZjNRFKvVqq7rPM/jweB5vlwup9Ppbrc7Ho/v3bs3nU6r1WoymQQhhJArRwQhhFx+oijeuHFDUZRut+s4znq9Zow1GqJto9GA44CQS4QxWBZME5KEOI77/X632w3DMJVKMcYymQwevGQyeevWrcFg0O12R6PRfD6vVCq6rvM8D0IIIVeICEIIuRJ4nq/VaoqitNtt3/eDINjb22NMtW00GnAcEHIpMAbbBmM4EwSB67rD4RCAruu1Wk2SJDwsHMdpmpZOp7vd7nA4bLfb0+m0Vqul02kQQgi5KkQQQsgVUiwWZVk+OTmZTqdHR0f1ep2xrG2j2USrhTAEITtLkmCasCwwhjPT6bTdbi+XS1mWa7Wapml4FFRVvXnzZjab7Xa70+l0sViUz4miCEIIIZefCEIIuVrS6fTBwUG73R6Px3fu3GFv0w4P8T/+x/w3f1PxPAmE7B7GYFkwTUgSoijqndtut9lsljGWTCbx6HAcVywW0+l0r9fzfb/T6cxms1qtls1mQQgh5JITQQghV46iKPv7+51Ox/O8e/fuzedzAIXC8GtfE5977qOuC0J2CmOwbTCGM6vVynGc8XjM83z1nCAI2AGyLO/t7WWz2U6nM5/P33rrLV3XK5WKJEkghBByaYkghJCrSBCEer0uiuLrr7/uOI4sy5qmfexj2l/91eZf/kvRcUDILpAkmCYsC4zhzHA4dF13vV6rqsoYy+fz2DG5XC6VSnnner2eqqqapoEQQsilJYIQsgPeeuutSqWSTCajKBJFEeQizOfz2WzG8zyAOI5FUczlcqmUaNtoNOA4IOTRYgyWBdOEJGGz2XS7Xc/z4jguFAqGYaiqip0kiqJhGNls1vO8YrEIQgghl5kIQsijs91uAXAct1wu79y5c/PmzWw2C3LfgiDwPM/3/e12WywWb926NT93dHRUr9cZK9g2mk20WghDEPLwSRJME5YFxnBmsVg4jjObzQRBqNVquq7zPI/dlk6nk8kkz/MghBBymYkghDwiURS9+uqrmUxms9mIovjBD35ws9mA3J84jofDYa/XWy6XgiBUKpVyuSzLchiGjuMMBoPj4+P1em0YlcNDrtVCswnHASEPE2OwLJgmJAln+v1+p9MJwzCVShmGkc1mcUnwPA9CCCGXnAhCyCMSRVGpVBoMBrVaLZ/PAxBFEeQ+LBaLXq83Ho/jOM7lctVqNZ1O45wkSTdu3JBludvtOo4TBIFhGI2GaNtoNOA4IOThYAy2DcZwJggC13WHwyEAXder1aosyyCEEEIeIhGEkEdEFMXquSiKeJ4HuQ+bzcbzvH6/v9lsFEWpVCqlUonnefwYnucNw1AUxXGcfr8fBEG9XmdMtW00GnAcEPJASRJME5YFxnBmOp06jnN6eipJkmEYmqaBEEIIeehEEEIeNZ7nQe7DaDTq9XqLxYLneV3XK5WKoij4KUqlkqIo9+7dm0wmQRDU63XGsraNZhOtFsIQhDwIjMGyYJqQJERR5Hlet9vdbreZTKZeryeTSRBCCCGPgghCCLm0lstlr9cbDodxHGcymWq1ms1m8c9Jp9MHBwftdnsymdy9e9cwDMa0w0O0Wmg24Tgg5AJJEkwTlgXGcGa1WrmuOxqNOI6rVCrValUURVxdm81GFMXtdisIAgghhOweEYQQcgltt1vf93u9XhiGkiSVy2Vd1wVBwLujquqtW7dc1+33+/fu3QuCoFqtNhq8baPRgOOAkAvBGCwLpglJwpnRaOQ4znq9VhSFMVYoFHDVxXH8d3/3d/v7++l0GoQQQnaPCEIIuWym02m3253NZhzHlUqlSqWSSCTwHgmCsLe3J8ty59x6vWZvk20bjQYcB4TcJ8Zg22AMZzabTbfb9TwvjuNCoWAYhqqquOqiKHrttddu3LgRRdGbb76Zy+U0TeM4DoQQQnaGCEIIuTzW63Wv1xsMBlEUpVKpSqVSKBRwHyqViqIo7XZ7OBwGQbC3t8dY0rbRaMBxQMj7I0kwTVgWGMOZ09PTdrs9m80EQahWq+Vymed5XAM8z3/oQx8aDAaO49y8eXM8Huu6DkIIIbtEBCGEXAZRFA0Gg16vt16vRVGsVCrlclkURdy3fD4vy/LJycl8Pj86OqrX64zlbRvNJlothCEIeU8Yg2XBNCFJOOP7vuu6YRgmk0nGWDabxXUiCIKmacViMQiCmzdvbjYbURRBCCFkZ4gghJCdN5/Pu93uZDLhOK5QKFQqlVQqhYuTTCZv/b/24GW3kTax7/C/im9VURQlURRFFuul+uvWjIEBjHjBRbjJXWiTC8jSvoIsjVxCAC+8yA0QvoUAjSy40Q3Yoz6IVTyIokSROrB4iqY/TOCJZwYzX6u7JdXved69S5Lk8vLyw4cPURRZW3v/XqenOjlRHAv4C1mrTkfW6tFisej1eqPRSNLBwUEURb7vK3vcL4wxAgA8P0YA8IylaTocDkej0Wq12traqtVq5XLZcRw9Nd/337x54/t+v9+P43g+n0dR1GqZTketluJYwJ/neWo21W7LWj26ublJkuT29tbzvHq9XqlUHMcRAADPjBGAr7BcLtfrtTHGdV3hSW02m/F4PBgM7u/vc7lc7QvP8/TNuK4bRZHv+0mSXFxcpGnaaDSszXc6arUUxwL+FGvVbqvZlOdpvV4Ph8N+v79arXZ2dqIoKhaLAgDgWTIC8ItsNpvFYjEcDv/pn/7pH//xH4UndXt7OxgMrq+vN5vN3t5eGIbFYlHfRaVS8X2/2+1OJpM0TY+Ojqzd6XR0cqLTUy0WAv49z1OzqXZb1urRw8NDkiRXV1eO49RqtTAMjTECAOC5MgLwi2w2m8+fP//Lv/zL5eXleDw+ODgQnsJyuRwOhxcXF8vlMgiCarVaqVRc19V3tLu7e3x83O12J5PJhw8f7O8cvH+v01OdnCiOBfzMWrXbajbleXp0fX0dx/HDw0MQBFEUlctlAQDwvBkB+EVc1/31r3/993//9//wD//g+77wFK6urgaDwe3treu6h4eHtVotCAL9CPl8/u3bt0mSjEajT58+zefzMAxbLbfTUaulOBZgrTodWatHq9Vq8MV6vd7b27PWbm1tCQCAZ88IwFfY2tr653/+5/V6LXyd+/v7wWAwHo83m02xWAzDcG9vTz+UMebo6CgIgt4XaZra3/E6HbVaimMhszxPzababVmrR3d3d0mSTCaTXC4XRVGtVnNdVwAAvARGAL6a67rCL7VarS4uLobD4WKx8DyvWq0eHh7mcjk9A47j1Gq1IAi63e7l5WWapo1Gw9pCp6OTE52earEQssZatdtqNuV5ejQajXq9XpqmhUIhiqK9vT0BAPByGAHAj3Nzc9Pv96fTqeM4BwcHtVpta2tLz0ypVPJ9//Pnz9Pp9OzsrNFoWFt6/16npzo5URwL2WGtOh1Zq0fL5TJJktFoJOng4CCKIt/3BQDAi2IEAD/CfD4fDAaXl5fr9Xp7e7tWq+3v7+u5KhQKx8fH3W736urq48ePURRVq9VWS52OWi3FsfDqeZ6aTbXbslaPZrNZt9u9vb31PC8Mw8PDQ8dxBADAS2MEAN/Xer2+vLwcDAbz+dwYU6vVqtWqMUbPm+/7b9++DYJgMBh0u935fB5FkbW5TketluJYeMWsVbutZlOep81mc3Fx0ev1lstlsVi01haLRQEA8DIZAcB3NJvN+v3+ZDJxHGd/f79Wq21vb+uFcF3XWhsEQRzHw+EwTdNGo2Ft0Omo1VIcC6+P56nZVLsta/VoPp8nSTIejx3HqVar9XrdGCMAAF4sIwD4LtI0HQ6Ho9FotVptbW3VarVyuew4jl6aSqXi+363272+vk7T9OjoyNpip6OTE52earEQXg1r1W6r2ZTn6dH19XWSJPf390EQRFFULpcFAMALZwQA39hmsxmPx4PB4P7+PpfL1Wq1arXq+75erN3d3ePj4/Pz85ubm7Ozs0ajYW35/XudnurkRHEsvALWqtORtXq0Xq/7/f5wOFytVnt7e1EUFQoFAQDw8hkBwLd0d3fX7/evr683m83u7m4Yhjs7O3r58vn8u3fvkiS5uLj4+PHjfD6v1WqtltvpqNVSHAsvl+ep2VS7LWv16P7+Po7jyWTium69Xg/D0HVdAQDwKhgBwLexXC6Hw+HFxcVyuQyCoFqtVioV13X1Whhjjo6OfN/v9XpJkszn80ajYa3pdNRqKY6Fl8hatdtqNuV5ejQej5Mkmc/nW1tbURSVSiUBAPCKGAHAN3B9fd3v929vbx3HOTw8rFar+Xxer47jOGEYBkHQ7XYvLy/TNG00GtYWOh2dnOj0VIuF8IJYq05H1urRcrns9XoXFxebzaZcLkdRFASBAAB4XYwA4End398PBoPxeLzZbIrFYhiGe3t7etX29/c9z+t2u9Pp9Ozs7OjoyNq99+91eqqTE8Wx8Px5nppNtduyVo9ms1kcx7PZzBhTr9crlYrrugIA4NUxAoAnslqtLi4uhsPhYrHwPK9arR4eHuZyOWVAsVg8Pj7udrtXV1cfPnyIoqharbZa6nTUaimOhefMWrXbajbledpsNhcXF/1+f7FYbG9vNxqNYrEoAABeKSMAeCK9Xm8wGDiOc3BwUKvVtra2lCW+7799+9b3/eFw2O120zSNoshat9NRq6U4Fp4hz1OzqXZb1upRmqZJkozHY0mHh4f1et3zPAEA8HoZAcATqVar0+k0DMP9/X1lkuu6jUYjCII4jgeDQZqmjUbDWr/TUaulOBaeFWvVbqvZlOfp0WQyieP4/v7e9/16vV6pVAQAwGtnBABPxPf9v/mbvzHGKNsODw+DIDg/P7+6ukrTtNFoWFvsdHRyotNTLRbCc2CtOh1Zq0fr9XrwxWq12t3dtdYWCgUBAJABRgDwdIwxgrS7u3t8fHx+fj6dTs/OzhqNhrXl9+91eqqTE8Wx8AN5nppNtduyVo8eHh7iOL6+vnZdt16v12q1XC4nAACywQgA8A1sbW0dHx/HcTwajT59+pSmaa1Wa7WcTketluJY+CGsVbutZlOep0fj8ThJkvl8ns/nrbWlUkkAAGSJEQDg2zDGvHnzJgiCXq8Xx/F8Pre/YzodtVqKY+E7s1adjqzVo+Vy2e/3h8PhZrPZ39+PoiifzwsAgIwxAgB8M47jhGHo+3632x2NRvP5/OjoyNqtTkcnJzo91WIhfAeep2ZT7bas1aPZbJYkyXQ6zeVyYRhWq1XXdQUAQPYYAQC+sXK57Pt+t9udTqdnZ2dHR0fW7r5/r9NTnZwojoVvylq122o25XnabDaj0ajX6y0Wi+3t7SiKdnd3BQBAVhkBAL69YrF4fHzc7Xavrq7Ozs6stYeHh62WOh395/+8SRJH+AY8T82m2m1Zq0dpmiZJMh6PJR0eHoZh6Pu+AADIMCMAwHfh+/7bt2993x8Oh+fn5/P5PIoia93//b/v/8t/8YZDT3hS1qrdVrMpz9Ojm5ubOI7v7u48z4uiqFKpCACAzDMCAHwvrus2Gg3f95MkGQwGDw8P+Xz+/n78v/6X/tt/+09J4ghPxFp1OrJWj9br9XA47Pf7q9VqZ2en0WgUCgUBAADJCADwfVWr1SAIfvvb3/7rv/7rer0ul8t/+7f2//yf5X/9r97pqRYL4Wt4nppNtduyVo8eHh6SJLm6unIcp1arhWFojBEAAPjCCAB+L03TJElqtVoQBK7rCt/Ger2+v79frVabLxzHKRaL5bL3/r1OT3VyojgWfhlr1W6r2ZTn6dHV1VUcx/P5PAgCa+3+/r4AAMC/YwQg81arVS6Xk9Ttdu/v7z9+/PirX/3K933hG5jNZr1e7+bmJpfL/eY3v1mv15PJ5NOnT2ma1mq1VsvpdNRqKY6Fv4rnqdlUuy1r9Wi5XPb7/eFwuNls9vf3oyjK5/MCAAB/yAhA5s3n88+fP0tqNBr9fv/g4MDzPOGprdfr4XA4GAyWy+XW1la9Xt/f31+v14PBoNfrxXGcpmkURdaaTketluJY+AtZq3ZbzaY8T4/u7u7iOL65ucnlcmEYVqtV13UFAAD+AyMAmbdarSSVSqWHh4fj42PXdYWnNpvNer3ezc2N4ziHh4dhGPq+L8l13Xq9HgRBt9u9uLhI07TRaFib73R0cqLTUy0Wwp9nrTodWaufjUajJEkWi0WhULDW7u7uCgAA/AlGADJve3v717/+tST3C+FJrdfr4XA4GAyWy+XW1lYURaVSSX+oXC77vn9+fj6ZTNI0bTQa1u6+f6/TU52cKI6FP8rz1Gyq3Za1erRYLHq93mg0knRwcBBFke/7AgAAf5oRgMxzvxC+gdls1uv1bm5uHMepVqu1Ws33ff0xxWLx+Pj4/Px8Mpl8+PDBWlupVFotdTpqtRTHwv/HWrXbajbleXp0c3OTJMnt7a3nefV6vVKpOI4jAADwZxkBAL6B9Xo9HA4Hg8Fyudza2oqiqFQq6c8KguDdu3dJklxcXHz+/DlN0zAMrXU7HbVaimPh/7FWnY6s1aP1ej0cDvv9/mq12tnZiaKoWCwKAAD8BYwAAE9tNpslSTKdTh3HOTw8DMPQ9339BXK53NHRURAESZL0er35fG5/x+90dHKi01MtFso4z1OzqXZb1urRfD6P4/jq6spxnFqtFoahMUYAAOAvYwQAeDqr1eri4qLf769Wq62trSiKSqWS/krVatX3/W63Ox6P5/P5mzdvrC28f6/TU52cKI6VWdaq3VazKc/To+vr6ziOHx4egiCIoqhcLgsAAPw1jAAAT2Q2myVJMp1OHcepVqu1Ws33ff0ipVLJ9/1utzudTs/OzhqNRqlUarXU6ajVUhwrazxPzababVmrR6vVavDFer3e29trNBr5fF4AAOCvZAQA+Gqr1Wo4HA4Gg9VqtbW1FUVRqVTS1ykUCu/evYvj+PLy8uPHj/V6vVqtWut0Omq1FMfKDmvVbqvZlOfp0d3dXZIkk8kkl8tFUVSr1VzXFQAA+OsZAQC+zmw2S5JkOp06jlOtVmu1mu/7egqe571588b3/X6/H8fxfD6Posha0+mo1VIcKwusVacja/Wz0WjU6/XSNN3a2rLW7u3tCQAA/FJGAIBfarVaDYfDwWCwWq0KhUK9Xi+VSnpSrutGUeT7fpIkFxcXaZo2Gg1r852OTk50eqrFQq+V56nZVLsta/VosVj0er3RaCTp4OAgiiLf9wUAAL6CEQDgF5nNZkmSTKdTx3Gq1WoYhp7n6duoVCpBEJyfn08mkzRNj46OrN15/16npzo5URzr9bFW7baaTXmeHs1ms263e3t763leGIaHh4eO4wgAAHwdIwDAX2m1Wg2Hw8FgsFqtCoVCvV4vlUr6xnZ2do6Pj7vd7mQy+fDhQxRFlUql1VKno1ZLcazXxFp1OrJWj9br9Wg06vV6y+WyWCxaa4vFogAAwFMwAgD8NWazWZIk0+nUdd3aF57n6bvI5/Nv375NkmQ0Gn3+/DlN0zAMrXU7HbVaimO9Ap6nZlPttqzVo/l8niTJeDx2HKdardbrdWOMAADAEzECAPxlVqvVYDAYDoer1apQKNTr9VKppO/LGPPmzZsgCHpfpGlqf8frdHRyotNTLRZ6uaxVu61mU56nR9fX10mS3N/fB0EQRVG5XBYAAHhSRgCAv8B0Ou31etPp1HXd2hee5+kHqdVqQRB0u93Ly8v5fH50dGRt4f17nZ7q5ERxrBfH89Rsqt2WtXq0Xq/7/f5wOFytVnt7e1EUFQoFAQCAp2YEAPizlsvl8IvVarW9vR2GYalU0o9WKpV83z8/P5/NZmdnZ41Go1QqtVrqdNRqKY71glirdlvNpjxPj+7u7pIkmUwmuVyuXq+HYei6rgAAwDdgBAD406bTaa/Xm06nruvWvvA8T89DoVB49+5dHMfj8fjjx49RFFWrVWvV6ajVUhzrRbBWnY6s1c/G43GSJPP5fGtrK4qiUqkkAADwzRgBAP6Y5XI5/GK1Wm1vb9fr9b29PT0zvu//9NNPQRD0+/1utzufz6MosjbX6ajVUhzrOfM8NZtqt2WtHi2Xy16vd3FxsdlsyuVyFEVBEAgAAHxLRgCA/2A6nfZ6vel06rpurVYLw9AYo2fJdd0oinzfj+N4OBzO5/OjoyNrg05HJyc6PdVioWfIWrXbajbleXo0m83iOJ7NZsaYer1eqVRc1xUAAPjGjAAA/85yuRx+sVqttre36/X63t6enr1KpeL7frfbnUwmaZq+efPG2uL79zo91cmJ4ljPirXqdGStHm02m4uLi36/v1gstre3G41GsVgUAAD4LowAAL93c3PT6/Vms5nrurVaLQxDY4xeiN3d3ePj4263O5lMzs7OrLUHBwetljodtVqKYz0HnqdmU+22rNWjNE2TJBmPx5IODw+jKDLGCAAAfC9GAABpuVwOv1itVtvb2/V6fW9vTy9NPp9/+/ZtkiSj0ejTp0/z+TwMQ2vdTketluJYP5a1arfVbMrz9GgymcRxfH9/7/t+vV6vVCoCAADflxEAZN50Ok2SZDabua5bq9XCMDTG6GUyxhwdHfm+3+/3e71emqb2d7xORycnOj3VYqHvz/PUbKrdlrV6tF6vB1+sVqu9vb0oigqFggAAwHdnBAAZtlwuh1+sVqvt7e0oinZ3d/XCOY4ThmEQBN1u9/LyMk3TRqNhbeH9e52e6uREcazvyVq122o25Xl6dH9/H8fxZDJxXbder9dqtVwuJwAA8CMYAUBW3dzc9Hq92WyWy+XCMKzVasYYvRb7+/u+75+fn0+n07Ozs0ajUSqVWi11Omq1FMf6PqxVpyNr9bPxeJwkyXw+z+fz1tpSqSQAAPDjGAFA9iyXy+EXq9Vqe3s7iqLd3V29Otvb28fHx91u9+rq6uPHj1EUHR4eWut0Omq1FMf6pjxPzababVmrR8vlst/vD4fDzWazv78fRVE+nxcAAPihjAAgY25ubpIkub29zeVyYRjWajVjjF4p3/ffvn3r+/5wOOx2u2ma1ut1a3OdjlotxbG+EWvVbqvZlOfp0Ww2S5JkOp3mcrkwDGu1muM4AgAAP5oRAGTGcrkcDAYXFxer1Wp7ezuKot3dXb12rus2Go18Ph/H8WAwmM/njUbD2qDT0cmJTk+1WOhpWatOR9bq0WazGY1GvV5vsVhsb29HUbS7uysAAPA8GAFANtzc3CRJcnt7m8vlwjCs1WrGGGVGpVLxff/8/Pz6+nqxWDQaDWuL79/r9FQnJ4pjPQnPU7OpdlvW6lGapkmSjMdjSYeHh/V63fM8AQCAZ8MIAF675XI5GAwuLi5Wq9X29nYURbu7u8qe3d3dX/3qV+fn5zc3N2dnZ41Go1wut1rqdNRqKY71laxVu61mU56nRzc3N3Ec393d+b5fr9crlYoAAMAzYwQAr9rd3d3nz59vb29zuVwYhrVazRijrMrn8+/evYvjeDQaffr0KU3TWq1mrdPpqNVSHOuX8Tw1m2q3Za0erdfr4XDY7/dXq9XOzk6j0SgUCgIAAM+PEQC8aoVCoVwuO45Tr9d3d3eVecaYN2/eBEGNiWqCAAAO2UlEQVTQ6/XiOH54eGg0GtaaTkcnJzo91WKhv4q1arfVbMrz9Ojh4SFJkqurK8dxarVaGIbGGAEAgGfJCABeu0qlUi6XjTHCF47jhGHo+3632728vEzT9OjoyNqt9+91eqqTE8Wx/kLWqtORtfrZ1dVVHMfz+TwIAmvt/v6+AADAM2YEAK+d+4Xwh8rlsu/73W53Op2enZ0dHR3t7u62Wup01GopjvXneZ6aTbXbslaPlstlv98fDoebzWZ/fz+Konw+LwAA8LwZAQCyqlgsHh8fd7vdq6urs7Mza+3h4aG16nTUaimO9adYq3ZbzaY8T4/u7u663e50Os3lcmEYVqtV13UFAACePSMAQIb5vv/27Vvf94fD4fn5eZqm9XrdWrfTUaulONb/x/PUbKrdlrX62Wg0SpJksVgUCgVr7e7urgAAwAthBADINtd1G42G7/tJkvT7/fl83mg0rPU7HZ2c6PRUi4V+Zq3abTWb8jw9StO03++PRiNJBwcHURT5vi8AAPByGAEAIFWr1SAIzs/Pr66u0jRtNBrWFt+/1+mpTk4Ux7JWnY6s1c9ubm6SJLm9vfU8r16vVyoVx3EEAABeFCMAAL7Y29vzff/8/Hw6nX748MFaWy6XWy11Ovof/0P//b/LWj1ar9fD4bDf769Wq52dHWvt9va2AADAC2QEAMDvbW1tHR8fd7vdy8vLT58+pWlaq9Wsdf7n/5Tj6NF8Po/j+OrqynGcWq0WhqExRgAA4GUyAgDg3zHGvHnzJgiCXq8Xx3GaplEUGWMkXV9fx3H88PAQBEEUReVyWQAA4CUzAgDgD7muW6/XgyDodrsXFxfz+TyKoslkMhgM1ut1qVSy1ubzeQEAgBfOCACAP6ZcLvu+f35+PhqNPn/+HARBsViMoqhWq7muKwAA8PIZAcDztv7C/UL4vorF4t7eXhzHNzc3W1tb1tp6vS4AAPBaGAHA83Z9fb1cLmezWbVaLRaLwveyWCx6vd5oNCqVSru7u5Kurq5836/X667rCgAAvHxGAPAsrdfrxWKxWq0KhcJvf/vbSqVyf39fLBaF72I6ncZxfHt763leGIaVSmU0GiVJ0u/35/N5o9HwfV8AAOCFMwKAZylN08FgkMvlVl8cHBzkcjnh21uv16PRqNfrLZfLYrForS0Wi5Kq1arv+91u9+rqKk3To6Oj7e1tAQCAl8wIAJ6lIAgkLRYLz/P+7u/+brPZOI4jfGPz+TxJkvF47DhOtVqt1+vGGP1eqVTyfb/b7U6n0w8fPlhr9/f3BQAAXiwjAHiufvrpJ/2e4zjCN3Z9fZ0kyf39fRAEURSVy2X9B4VC4d27d3EcX15efvr0aT6f12o1x3EEAABeICMAeJYcxxG+l/V63e/3B4PBer3e29uz1m5tbelP8DzvzZs3vu/3+/0kSdI0jaLIGCMAAPDSGAEAsu3u7i5Jkslkksvl6vV6GIau6+rPcl03iqIgCOI4vri4SNO00Wjk83kBAIAXxQgAkGHj8ThJkvl8vrW1FUVRqVTSX+zg4MD3/fPz88lkkqZpo9HY3d0VAAB4OYwAAJm0XC57vd7FxcVmsymXy1EUBUGgv9LOzs7x8XG3251MJh8/foyiqFKpCAAAvBBGAIDsmc1mcRzPZjNjTL1ePzw8dBxHv0g+n3/79m2SJKPR6PPnz2mahmHouq4AAMCzZwQAyJLNZnNxcdHv9xeLxfb2dqPRKBaL+jrGmDdv3uTz+SRJer3efD631vq+LwAA8LwZAQAyI03TJEnG47Gkw8PDKIqMMXoi1WrV9/1utzsej9M0PTo6KhQKAgAAz5gRACAbJpNJHMf39/e+79fr9UqloqdWKpV83z8/P5/NZmdnZ41Go1QqCQAAPFdGAIDXbr1eD75YrVZ7e3tRFBUKBX0bhULh3bt3cRyPx+OPHz9GUVStVgUAAJ4lIwDAq3Z/fx/H8WQycV23Xq/XarVcLqdvyff9n376KQiCfr/f7XYfHh6stblcTgAA4JkxAgC8XuPxOEmS+Xy+tbUVRVGpVNJ34bpuFEW+7ydJcnFxkaZpo9HI5/MCAADPiREA4DVaLpf9fn84HG42m/39/SiK8vm8vq9KpRIEwfn5+WQySdP06OhoZ2dHAADg2TACALw6s9ksSZLpdJrL5cIwrFarruvqR9jZ2Tk+Pu52u5PJ5MOHD9bag4MDAQCA58EIAPCKbDab0WjU6/UWi8X29nYURbu7u/qh8vn827dvkyQZjUafPn2az+f1et1xHAEAgB/NCADwWqRpmiTJeDyWdHh4WK/XPc/TM2CMOTo68n2/3+/3er00Ta21nucJAAD8UEYAgFfh5uYmjuO7uzvP86IoqlQqek4cxwnDMAiCbrd7eXmZpmmj0SgUCgIAAD+OEQDghVuv18PhsN/vr1arnZ2dRqNRKBT0LO3v7/u+f35+Pp1Oz87OGo1GqVQSAAD4QYwAAC/Zw8NDkiRXV1eO49RqtTAMjTF6xra3t4+Pj7vd7tXV1cePH6MoqlarAgAAP4IRAODFurq6iuN4Pp8HQWCt3d/f10vg+/7bt2+DIBgMBt1uN03Ter2ey+UEAAC+LyMAwAu0XC77/f5wONxsNvv7+1EU5fN5vRyu61prgyC4uLg4PDzM5XICAADfnREA4KW5u7vrdrvT6TSXy4VhWK1WXdfVC1SpVPL5fBAEAgAAP4IRAOBFGY1GSZIsFotCoWCt3d3d1UtWLBYFAAB+ECMAwAuRpmmv17u8vJR0cHAQRZHv+wIAAPiljAAAL8HNzU2SJLe3t57n1ev1w8NDAQAAfB0jAMDztl6vh8Nhv99frVY7OzvW2u3tbQEAAHw1IwDAM/bw8JAkydXVleu6tVotDENjjAAAAJ6CEQDgubq+vo7j+OHhIQiCKIrK5bIAAACejhEA4PlZrVb9fn84HK7X61KpZK3N5/MCAAB4UkYAgGfm7u4ujuObm5tcLhdFUa1Wc11XGbZer//t3/6tUCg0Gg0BAICnYwQAeE5Go1Gv10vTtFAoWGt3d3eVeePxOJfLRVG02Wwcx9lsNo7jCAAAfDUjAMDzsFgser3eaDSSdHBwEEWR7/vKvPV6vVqtDg4O0jT9+PHjcrn8zW9+Y4wRAAD4akYAgGdgNpt1u93b21vP88IwPDw8dBxHkFzXrdVqvV4vSZIoitI0dRxHAADgKRgBAJ6BYrF4cHDgum4URcViUfhD9Xrd87zpdGqtdV1XAADgKRgBAJ6HSqWyv79vjBH+mEqlIgAA8KSMAADPg+M4xhgBAAB8L0YAAAAAgEwyAgAAAABkkhEAAAAAIJOMAAAAAACZZAQAAAAAyCQjAAAAAEAmGQEAAAAAMskIAAAAAJBJRgAAAACATDICAAAAAGSSEQAAAAAgk4wAAE/h+vr648ePjUajUqkIAADgJTACADyF8Xj87t27q6urIAh2dnYEAADw7BkBAL7CcrlMkuTNmzc//fTThw8fFovF9va2AAAAXgIjAMBXmM1mW1tbZ2dnYRgWi8UwDAUAAPBCGAEAvkKpVJKUy+Vc1w3DUAAAAC+HEQDgq5XLZQEAALw0RgAAAACATDICAAAAAGSSEQAAAAAgk4wAAAAAAJlkBAAAAADIJCMAAAAAQCYZAQAAAAAyyQgAAAAAkElGAAAAAIBMMgIAAAAAZJIRAAAAACCTjAAAAAAAmWQEAAAAAMgkIwAAAABAJhkBAAAAADLJCAAAAACQSUYAAAAAgEwyAgAAAABkkhEAAAAAIJOMAAAAAACZZAQAAAAAyCQjAAAAAEAmGQEAAAAAMskIAAAAAJBJRgAAAACATDICAAAAAGSSEQAAAAAgk4wAAAAAAJlkBAAAAADIJCMAAAAAQCYZAQAAAAAyyQgAAAAAkElGAAAAAIBMMgIAAAAAZJIRAAAAACCTjAAAAAAAmWQEAAAAAMgkIwAAAABAJhkBAAAAADLJCAAAAACQSUYAAAAAgEwyAgAAAABkkhEAAAAAIJOMAAAAAACZZAQAAAAAyCQjAAAAAEAmGQEAAAAAMskIAAAAAJBJRgAAAACATDICAAAAAGSSEQAAAAAgk4wAAAAAAJlkBAAAAADIJCMAAAAAQCYZAQAAAAAyyQgAAAAAkElGAAAAAIBMMgIAAAAAZJIRAAAAACCTjAAAAAAAmWQEAAAAAMgkIwAAAABAJhkBAAAAADLJCAAAAACQSUYAAAAAgEwyAgAAAABkkhEAAAAAIJOMAAAAAACZZAQAAAAAyCQjAAAAAEAmGQEAAAAAMskIAAAAAJBJRgAAAACATDICAAAAAGSSEQAAAAAgk4wAAAAAAJlkBAAAAADIJCMAAAAAQCYZAQAAAAAyyQgAAAAAkElGAAAAAIBMMgIAAAAAZJIRAAAAACCTjAAAAAAAmWQEAAAAAMgkIwAAAABAJhkBAAAAADLJCAAAAACQSUYAAAAAgEwyAgAAAABkkhEAAAAAIJOMAAAAAACZZAQAAAAAyCQjAAAAAEAmGQEAAAAAMskIAAAAAJBJRgAAAACATDICAAAAAGSSEQAAAAAgk4wAAAAAAJlkBAAAAADIJCMAAAAAQCYZAQAAAAAyyQgAAAAAkElGAAAAAIBMMgIAAAAAZJIRAAAAACCTjAAAAAAAmWQEAAAAAMgkIwAAAABAJhkBAAAAADLJCAAAAACQSUYAAAAAgEwyAgAAAABkkhEAAAAAIJOMAAAAAACZZAQAAAAAyCQjAAAAAEAmGQEAAAAAMskIAAAAAJBJRgAAAACATDICAAAAAGSSEQAAAAAgk4wAAAAAAJlkBAAAAADIJCMAAAAAQCYZAQAAAAAyyQgAAAAAkElGAAAAAIBMMgIAAAAAZJIRAAAAACCTjAAAAAAAmWQEAAAAAMgkIwAAAABAJhkBAAAAADLJCAAAAACQSUYAAAAAgEwyAgAAAABkkhEAAAAAIJOMAAAAAACZZAQAAAAAyCQjAAAAAEAmGQEAAAAAMskIAAAAAJBJRgAAAACATDICAAAAAGSSEQAAAAAgk4wAAAAAAJlkBAAAAADIJCMAAAAAQCYZAQAAAAAyyQgAAAAAkEn/F6orYhPyNdF0AAAAAElFTkSuQmCC", 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", "text/html": [ - "" + "" ] }, - "execution_count": 16, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -152,7 +152,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -162,7 +162,7 @@ " \"mesh.vtu\"" ] }, - "execution_count": 46, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -182,7 +182,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -191,7 +191,7 @@ "(7475, [7475, 41858, 63541, 29160])" ] }, - "execution_count": 17, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -211,7 +211,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -246,7 +246,7 @@ " [0.2251334943566448, 0.5163151069021665, 0.02626007329870325]" ] }, - "execution_count": 18, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -264,7 +264,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -299,7 +299,7 @@ " [5805, 4535, 4024, 6788]" ] }, - "execution_count": 21, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -317,7 +317,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -332,7 +332,7 @@ " \"sides\" => [3395, 3396, 3397, 3398, 3399, 3400, 3401, 3402, 3403, 3404 … …" ] }, - "execution_count": 6, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -352,7 +352,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -361,7 +361,7 @@ "GalerkinToolkit.PhysicalDomain(…)" ] }, - "execution_count": 36, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -372,17 +372,17 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/html": [ - "" + "" ] }, - "execution_count": 37, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -400,7 +400,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -409,7 +409,7 @@ "GalerkinToolkit.PhysicalDomain(…)" ] }, - "execution_count": 38, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -420,17 +420,17 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 12, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/html": [ - "" + "" ] }, - "execution_count": 39, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -448,7 +448,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -457,7 +457,7 @@ "GalerkinToolkit.PhysicalDomain(…)" ] }, - "execution_count": 40, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -468,17 +468,17 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 14, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", "text/html": [ - "" + "" ] }, - "execution_count": 41, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -498,7 +498,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -507,7 +507,7 @@ "GalerkinToolkit.LagrangeSpace(…)" ] }, - "execution_count": 43, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -534,7 +534,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -543,7 +543,7 @@ "(GalerkinToolkit.Quantity(…), GalerkinToolkit.DiscreteField(…))" ] }, - "execution_count": 44, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -560,7 +560,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -570,48 +570,46 @@ "" ] }, - "execution_count": 37, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "# Plot with WriteVTK\n", "WriteVTK.vtk_grid(\"Γd\",Γd) do plt\n", " GT.plot!(plt,g;label=\"g\")\n", "end\n", "\n", "# Plot `Quantity <: AbstractQuantity` instances with Makie\n", - "plt = GT.plot(Γd)\n", - "GT.plot!(plt,g;label=\"g\")\n", - "GLMakie.plot(plt,color=GT.NodeData(\"g\"))" + "GLMakie.plot(Γd,color=g)" ] }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 18, "metadata": {}, "outputs": [ { "data": { - "image/png": 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+ "image/png": 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", "text/html": [ - "" + "" ] }, - "execution_count": 47, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "# Plot with WriteVTK\n", "WriteVTK.vtk_grid(\"Ω\",Ω) do plt\n", " GT.plot!(plt,uhd;label=\"uhd\")\n", "end\n", "\n", "# Plot `DiscreteField <: AbstractQuantity` instances using Makie\n", - "plt = GT.plot(Ω)\n", - "GT.plot!(plt,g;label=\"uhd\")\n", - "GLMakie.plot(plt,color=GT.NodeData(\"uhd\"))" + "GLMakie.plot(Ω,color=uhd)" ] }, { @@ -636,7 +634,7 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -645,7 +643,7 @@ "GalerkinToolkit.Measure(…)" ] }, - "execution_count": 48, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -675,7 +673,7 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -684,7 +682,7 @@ "GalerkinToolkit.Measure(…)" ] }, - "execution_count": 49, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -702,7 +700,7 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 21, "metadata": {}, "outputs": [ { @@ -711,7 +709,7 @@ "∇ (generic function with 1 method)" ] }, - "execution_count": 50, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -734,7 +732,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -743,7 +741,7 @@ "l (generic function with 1 method)" ] }, - "execution_count": 51, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -779,16 +777,16 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "([7.291212384108405e-304, 2.121995791e-314, 2.834986376732e-311, 4.0474e-320, 2.529418982843e-311, 0.0, 0.0, 0.0, 7.71e-321, 6.76e-321 … 5.439857071e-314, 2.121995795e-314, 2.121995791e-314, 5.21501990224866e-310, 2.6300848696e-314, NaN, 0.0, 2.794628673e-314, 0.0, 5.21501729013624e-310], sparse([1, 22, 74, 289, 337, 338, 339, 340, 341, 1872 … 6303, 335, 465, 467, 468, 1806, 6201, 6224, 6232, 6304], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 6303, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304], [0.06443080405538211, -0.0011816946972152084, -0.0019141180663583925, -0.03255921926190384, -0.013954244941888471, -0.009620087896820673, -0.0021278804315064915, -0.004654033162377993, -0.005173786773138719, 0.003329780400807812 … 0.21999530084991323, -0.015615599976174236, 0.003972555304119093, -0.009088995023018824, -0.00030902681072076353, -0.013784861561036393, -0.014076977113079436, -0.024457375688586837, -0.013734513123868308, 0.17287503833373258], 6304, 6304), [0.0015677351619201938, 0.0015207565876126684, 0.0015232957017090134, 0.0016182302571138272, 0.0013414312146763385, 0.0014776038723584638, 0.001306589310230424, 0.0014160610368619696, 0.0014136920830547547, 0.0014139259120884476 … 0.09466909943634595, 3.837716427462898e-5, 4.067983156302676e-5, 3.40747082227309e-5, 3.410273174605993e-5, 0.08456444214161216, 0.07001671663821094, 3.7083120014430675e-5, 3.516169468651288e-5, 0.17159606501883534])" + "([7.291212384108405e-304, 2.121995791e-314, 2.834986376732e-311, 4.0474e-320, 2.529418982843e-311, 0.0, 0.0, 0.0, 7.71e-321, 6.76e-321 … 2.530061924e-314, 4.0e-323, 2.121995791e-314, 1.0e-323, 0.0, NaN, 0.0, 0.0, NaN, 3.38e-321], sparse([1, 22, 74, 289, 337, 338, 339, 340, 341, 1872 … 6303, 335, 465, 467, 468, 1806, 6201, 6224, 6232, 6304], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 6303, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304], [0.06443080405538211, -0.0011816946972152084, -0.0019141180663583925, -0.03255921926190384, -0.013954244941888471, -0.009620087896820673, -0.0021278804315064915, -0.004654033162377993, -0.005173786773138719, 0.003329780400807812 … 0.21999530084991323, -0.015615599976174236, 0.003972555304119093, -0.009088995023018824, -0.00030902681072076353, -0.013784861561036393, -0.014076977113079436, -0.024457375688586837, -0.013734513123868308, 0.17287503833373258], 6304, 6304), [0.0015677351619201938, 0.0015207565876126684, 0.0015232957017090134, 0.0016182302571138272, 0.0013414312146763385, 0.0014776038723584638, 0.001306589310230424, 0.0014160610368619696, 0.0014136920830547547, 0.0014139259120884476 … 0.09466909943634595, 3.837716427462898e-5, 4.067983156302676e-5, 3.40747082227309e-5, 3.410273174605993e-5, 0.08456444214161216, 0.07001671663821094, 3.7083120014430675e-5, 3.516169468651288e-5, 0.17159606501883534])" ] }, - "execution_count": 52, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -811,7 +809,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 24, "metadata": {}, "outputs": [ { @@ -846,7 +844,7 @@ " 2.0089547066118425" ] }, - "execution_count": 32, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -866,7 +864,7 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 25, "metadata": {}, "outputs": [ { @@ -875,7 +873,7 @@ "GalerkinToolkit.DiscreteField(…)" ] }, - "execution_count": 53, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -893,26 +891,30 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 27, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "1-element Vector{String}:\n", - " \"Ω.vtu\"" + "image/png": 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", + "text/html": [ + "" ] }, - "execution_count": 55, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "# Plot with WriteVTK\n", "WriteVTK.vtk_grid(\"Ω\",Ω) do plt\n", " GT.plot!(plt,uhd;label=\"uhd\")\n", " GT.plot!(plt,uh;label=\"uh\")\n", - "end" + "end\n", + "\n", + "# Plot with Makie\n", + "GLMakie.plot(Ω,color=uh)" ] }, { From ec7bca06eefd5254425c15d76ac93cbb9f8d4609 Mon Sep 17 00:00:00 2001 From: Cmurilochem Date: Fri, 18 Oct 2024 17:14:03 +0200 Subject: [PATCH 14/14] Remove WriteVTK plots and shorten notebook --- notebooks/t001_poisson.ipynb | 514 ++++++++--------------------------- 1 file changed, 120 insertions(+), 394 deletions(-) diff --git a/notebooks/t001_poisson.ipynb b/notebooks/t001_poisson.ipynb index 667f9c20..59c2f3e8 100644 --- a/notebooks/t001_poisson.ipynb +++ b/notebooks/t001_poisson.ipynb @@ -49,11 +49,16 @@ "$$\n", "The problem is solved numerically by approximating the spaces $U_g$ and $V_0$ by their discrete counterparts associated with a FE mesh of the computational domain $\\Omega$. As we have anticipated, we consider standard conforming Lagrangian FE spaces for this purpose.\n", "\n", - "The implementation of this numerical scheme in GalerkinToolkit is done in a user-friendly way thanks to the abstractions provided by the library. As it will be seen below, all the mathematical objects involved in the definition of the discrete weak problem have a correspondent representation in the code.\n", - "\n", + "The implementation of this numerical scheme in GalerkinToolkit is done in a user-friendly way thanks to the abstractions provided by the library. As it will be seen below, all the mathematical objects involved in the definition of the discrete weak problem have a correspondent representation in the code." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ " ## Setup\n", "\n", - " The step number 0 in order to solve the problem is to load the GalerkinToolkit library in the code. If you have configured your Julia environment properly, it is simply done with the line:" + "Import the GalerkinToolkit library in the code:" ] }, { @@ -71,12 +76,12 @@ "source": [ "## Computational mesh\n", "\n", - "As in any FE simulation, we need a discretization of the computational domain (i.e., a FE mesh). All geometrical data needed for solving a FE problem is provided in GalerkinToolkit by types inheriting from the abstract type `GenericMesh`. In the following line, we build an instance of `GenericMesh` by loading a `msh` file." + "Load a FE mesh:" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 26, "metadata": {}, "outputs": [ { @@ -96,7 +101,7 @@ "GalerkinToolkit.GenericMesh(…)" ] }, - "execution_count": 2, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -109,24 +114,24 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The file `\"model.msh\"` (which contains a FE mesh and information about user-defined physical boundaries) was generated by using the [GMSH](http://gmsh.info/) mesh generator. See the documentation of [GMSH](http://gmsh.info/#Documentation).\n", + "Note that the file `\"model.msh\"` (which contains a FE mesh and information about user-defined physical boundaries) was generated by using the [GMSH](http://gmsh.info/) mesh generator. See the documentation of [GMSH](http://gmsh.info/#Documentation).\n", "\n", - "You can easily inspect the generated discrete model using [Makie](https://docs.makie.org/) and [GLMakie](https://docs.makie.org/stable/explanations/backends/glmakie#GLMakie) backend, like so:" + "Plot the mesh using [Makie](https://docs.makie.org/) and [GLMakie](https://docs.makie.org/stable/explanations/backends/glmakie#GLMakie) backend:" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 36, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/html": [ - "" + "" ] }, - "execution_count": 3, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } @@ -134,20 +139,22 @@ "source": [ "using GLMakie\n", "\n", - "# for a larger figure\n", - "#f = Figure(; size = (600, 400))\n", + "# for a larger figures\n", + "#f = Figure(; size = (1500, 1500))\n", "#lscene = LScene(f[1, 1])\n", - "#GLMakie.plot!(lscene, mesh;shading=Makie.NoShading,color=:blue)\n", + "#GLMakie.plot!(lscene,mesh,strokecolor=:black)\n", "#f\n", "\n", - "GLMakie.plot(mesh;shading=Makie.NoShading,color=:blue)" + "GLMakie.plot(mesh)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Alternatively, the generated discrete model can also be viewed using [Paraview](https://www.paraview.org/) by writing it in [WriteVTK](https://github.com/JuliaVTK/WriteVTK.jl) format." + "## Computational domains\n", + "\n", + "Define the discrete solution space:" ] }, { @@ -158,8 +165,7 @@ { "data": { "text/plain": [ - "1-element Vector{String}:\n", - " \"mesh.vtu\"" + "GalerkinToolkit.PhysicalDomain(…)" ] }, "execution_count": 4, @@ -168,16 +174,7 @@ } ], "source": [ - "using WriteVTK\n", - "\n", - "WriteVTK.vtk_grid(\"mesh\", mesh) |> close" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Apart from visualizations, users can additionally inspect general mesh attributes by resorting to several GalerkinToolkit's built-in functions, *e.g*, `num_dims`, `num_nodes`, `num_faces`, `node_coordinates`, `physical_faces`, etc. For example, you can check the total number of nodes and faces in your loaded mesh:" + "Ω = GT.interior(mesh;physical_names=[\"volume\"])" ] }, { @@ -187,8 +184,9 @@ "outputs": [ { "data": { - "text/plain": [ - "(7475, [7475, 41858, 63541, 29160])" + "image/png": 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UmgaFB1BK2c56veac375923Ecxlin09F1vSxLSim8lWVZ/X5/b29vuVxyzqfTqed5jDHXdQkhgNCHgAJC6AFxHC8Wi9FotFgs4jher9eMsePjY9u24QLb7TZN0/l8LqVkjB0eHhqGIRXwvBrPUlFUUsElowCSvBI53MmTA73aZ0HbcYgGD3J2+v1+mqbn5+eTyYQxtl6vfd+HhyGEeDtFUQghJpMJADDGgiAwTRMQ+kBRQAg9QEophCjLUkoZRdFoNKKUwgWqqkqSJI5jSmm32w2CgBAiFfC8Gs9SUVRSwSWmAJKiFqC9vMk8a33U1oehR3UdHmAYRrfbjaJouVwmSXLnzp3BYGBZluu6hBB4GMuy+v3+3t7ecrnknE+nU9/3wzB0XZcQAgh9ECgghO6T53mSJKenp3meX7t2zfM8QghcIM9zvtNutw8ODjqdjqZpUgHPq/EsFUUlFTSEAqiV4nmV5NV3V9uRsd1ngW1ZRIPvoWlap9NxXTfLMtd1J5OJpmlhGAZBYJomPAwhxNvJ81wIMZlMNE0LwzAIAtM0AUAIYZqm4ziA0LtHASG0s1wuOedCiCAIDg8PsywLggAusFqt4jgWQoRheHR05DgOAEgFSV6NZ6koKqmgmRRAklcih39bJZ5Jjz1zEHhEg+8hpQSA/f19wzAWi0WSJNPpNAgCxli73dY0DR7Gtu3BYNDr9RaLRZIk0+nU9/0wDJMk6XQ6juMAQu8eBYSaTUqZZRnnfLPZMMaOj49t214ul0IIeICUcrFYxHG82WwYYzdv3rQsSyqopcrKejxLRVFJBUgB1FLxvHopr8KsvGbDQRQaVIc3bbdbpZSu64QQfyfP8yRJTk5ODMMIwzAIAkopPAwhxN/J81wIcffu3bOzs2eeecbzPNM0AaF3iQJCTVXXtRAijmMAiKJoNBpRSmGHEKKUklISQmBnu90KIeI4llJGUTQajSilUgHPq/EszcpaKiUVoO+hAHheJTm8lieHtB6EvtNqEQ3qutZ1nRACb7Jte39/v9frZVnGOZ9Op+GO4zhwAdu2B4NBFEWLxaKqqpdffjkIgjAM2+02IQQQemcoINQ8eZ5zzpMkabVa/X7f8zxCCNyHECKlhJ2yLJMkiePYNM29vT3f9wkhUgHPq/EsFUUlFaBHUwBJXgmAb69Tz1zdcKmra4ZhEELgrXRdD3fW6zXn/LXXXrNtmzHmeZ6u6/AwSinHcY6Ojuq6FkKcnp7quh7smKYJCL0dCgg1yXK55JwLIYIguHbtWrvdhochhCil1ut1mqZJkriue3h46LqupmlSAc+r8SwVRSUVoHdOAdRS8bz6P/OqY5BOXuVlZRoG0eBBzs5gMBBC3Lt37+zsLNyxbRveqixLSqmu65TSwWDQ6/WyLEuSZDqdBkEQhmG73SaEAEIXoIBQA0gpsyyL47goCsbYzZs3LcuCi61Wq3v37tV13e12j46OHMcBAKkgyavxLBVFJRWg90wBZJVcmOHs9dgz6bFvDfwO0eBBlNJutxtF0Wq14pzfunXL87wwDDudDiEEdsqyNE1T0zTYIYQEO3meCyFOT091XQ/D0Pd90zQBoQdQQOhSq6pKCBHHMSGEMRYEAaUULiClzLIsjuP1ek0pvXHjhuu6UkEtVVbW41kqikoqQB8IBVBLxfPqpaIK0+LIIUPmU12HB2ia5u4MBgMhxHQ6PTs7Y4wFQWCaZlmWlmXBA2zbHgwGvV4vy7IkSabTqe/7jLF2u61pGiD0JgoIXVJ5nvMdx3H29/c7nQ4hBC5Q17UQgnMupex2u1euXHnllVd0avC8Gs/SrKylUlIB+jAoBTyvkhy+u05GxnafBbZlEQ0eZJpmr9frdrvL5ZJzPp1OgyBYr9eMMbgAISTYyfNcCPHGG2/ouh6Goe/7pmkCQgAUELp0lstlHMdpmoZheHR05DgOXKwsS75jmmav1/M8jxBSb7eFbn5rmmVlLRWgj4ACSPJK5PBvq8Qz6bMdYz/0iQYPIoR4O3meCyFeffXVPM8JIb7vG4YBF7BtezAY9Hq9LMs459Pp1Pd9xli73dY0DVCDUUDospBSpmkax3FZloyx5557zjRNuNhms4njOEmSTqczGo1c1wUAqYDn1X+bpYJ0VFED+mgpgFoqnlf/nFfhorpmw5AFpkHhYWzb7vV68/m82+1mWTadToMgYIw5jgMXIIQEO3meJ0lycnJCKWWMeZ5nmibs1HVNKQXUGBQQevpVVZUkCeecEBJFke/7lFK42HK5nM/ni8UiDMMbN260Wi0AkApEUY1nqSgqqQA9XgqA51WSw2ub5NDYDkLfabWIBt+jrmspZbfbpZRuNhvO+e3bt23bZox5nkcphQvYtr2/v9/r9RaLBef87OzM933GWLvdnkwmtm33ej1AzUABoadZnud8x3Gc4XDoui4hBC4gpcyybD6fl2XJGBsOh6ZpSgW1VFlZj2epKCqpAD05FEBS1KKAb69Tz1xdd+l+0KG6Dm+qqso0TV3XAaDVah0cHPT7/TRNOefT6TQIAsaYbdtwAV3Xg508z5MkOTk5oZRmWXbt2jVAjUEBoaeQUmq5XMZxvFgswjA8OjpyHAcuVte1ECKOY03TGGNBEFBKpQKeV+NZmpW1VEoqQE8mBVBLxfMqyatgWV+z1D4LTMMgGpRlaZqmpmnwJkppFEWMsdVqlSTJK6+84rouY6zT6RBC4AK2be/v7/d6PSHE6enpycnJZrMJw7DdbmuaBuhSo4DQU0VKKYTgnJdlyRgbDoemacLFyrLkO5Zl9ft9z/MIIVIBz6vxLBVFJRU0B9GAaNpWKgVPJQWQ5JXI4V8WsWfSY98iZWmaJjxA0zR3p9/vCyGm0+nZ2VkYhkEQWJYFF9B1vd1u9/v9q1evZll2cnJCKWWM+b5vGAagS4oCQk+JsiyFEJxzQki32/V9X9d1uNh6veY7vu+PRiPXdQFAKuB5NZ6loqikguYgGvgm/eQgaGnqzj3+8kopeFopgFoqnlcvFZVLYADVYLulug4PY5pmr9frdrvL5ZJzPpvNfN9njLXbbUIIPCDPc8uy3J1+v79YLDjn0+nU9/0wDNvttqZpgC4XCgg98TabTRzHQgjXdYfDYafT0TQNLqCUWi6XcRwvl8swDI+Pj23bBgCpQBTVeJaKopIKmoNo4FvGJ/u+q2si4bfv3XPabUczVorAU04pWGxhCfb8NBkZ230W2JZFNHgQIcTbyfNcCHF6eqrrOmPM933DMOA+eZ7btg07uq4HO5vNJkmSk5MTwzDCMPR93zAMQJcFBYSeVEqpxWLBOV8sFmEYHh0dOY4DF5NSZlk2n8/LsoyiaDgcmqYJAFKBKKrxLBVFJRU0B9HAt4xP9n3PICJJXj0/t2376tWrrusO6u3fvR5v6i08/RRAklcih39bJZ5Jn+0Y+6FPNHgo27YHg0Gv18uyjHM+nU6DIAjDsN1uw06e567rwlu1dnq93mKxSJJkOp0GO+12W9M0QE85Cgg9ebbbbZqmcRzXdc0YGw6HpmnCxeq6FkLM53NCSBRFvu9TSqWCWqqsrMezVBSVVNAcRAPfMj7Z9z2DZGn66vk5pfTKlSue58FOi+rPH4TfPJlLBZeDAqil4nn1z3kVLqprNgxC3zQMosGDCCHBzmazSZLkzp07lmUxxjqdTp7n3W4XHoZSGu6s12shxMnJiWEYYRj6vm8YBqCnFgWEniRlWSZJwjmnlEZR5Pu+rutwsaIokiSJ47jVau3v73uep2maVMDzajxLs7KWSkkFjdKi+vMHoW/qiyy7fXIOAIPBwPd9TdPgPoFlBJbB8wouFwXA8yrJQc9iz6TPBXbPc4kGD9Xa6fV6WZZxzk9PT4UQw+EQHsnZ6fV6WZYlSTKdToMgCMOw3W4DegpRQOjJsNls4jhOkqTT6Vy5csV1XU3T4GLr9TqO4yRJgiC4evWq67oAIBUkeTWepaKopIKmIRp0DP0/HUbVevXa6Xld171eLwgCQgg8gGjw/EH4d6/Hm3oLl44CqKXiefWtWRWK/LpL94MO1XV4GEop25nP51mW3blzx3VdxpjneYQQuACllO2s12shxOuvv26aZrBDKQX09KCA0GOllFosFnEcr1arMAxv3LjRarXgYkqpxWIRx/FqtWKMHR8f27YNAFKBKKrxLBVFJRU0DdGgY+g/sB8aVXF28nqe53t7e4wxXdfhYi2qv3g1+rvX4029hUtKKeB5leRVsKyvWWoQ+pZpEg0eihAyHA6vXLmSZdn5+fnZ2VkYhkEQ2LYNF3N2er1elmVJkkyn0yAIwjBst9vwJqWUpmmAnkgUEHpM6rrOsmw+n0spGWNXrlwxDAMuJqUUQnDOq6qKoujg4MA0TQCQCkRRjWepKCqpoGmIBp5J/8MgsLbVvend5XK5t7c3Go0opfAOtKj+/EH4zZO5VHCJKYAkr0QO+oJ7Jj32rYHfIRp8jzzPbds2TbPb7TLGlstlkiS3bt3yPI8x5rouIQQuQCllO+v1Wghx584dy7LCMPR9n1J6cnLiOM7e3h6gJw8FhD5yZVlyzpMkMQyj2+0GQUAIgYvVdc13CCHdbtf3fV3XpYJaqqysx7NUFJVU0DREA8+k/2EQ2Gob35veFaLb7Q6HQ9M04d0ILCOwDJ5XcNkpgFoqnlcvFVWYFkcOGTKf6jq8Kc/zIAhghxDi7RRFIYSYTCaapjHGfN83TRMu5uz0er0sy5IkOTs7C4IgSZIoigA9kSgg9CGTUhJCYGe9XnPOkyTpdDqHh4ftdlvTNLhYnud8x3Gc4XDoui4hRCrgeTWepVlZS6WkgqYhGvgm/eQgcDQVz89P45gxdnx8bFkWvHtEg+cPwr97Pd7UW2gGpYDnVZLDd9fJId0Oo8C2LA1Unue2bcNbWZbV7/f39vayLOOcT6fTIAjCMGy325qmwQUopWxnvV6fn5+fnZ21Wq29vT3P8yilgJ4kFBD6ME0mEwAYDAbL5XI+n6/Xa8bYs88+a9s2PNJ6vZ7P50KIIAieeeaZdrsNAFIBz6vxLBVFJRU0ENHAN+knB0GbQMLjyXzued7x8bFt2/A+tKj+/EH4zZO5VNAcCiDJKwHw7XXimfSaDVVdm6YJD0MICXbyPE+S5OTkxDTNMAx936eUwsUcx2GMPfPMM3t7e5zzyWQSBAFjzHEcQE8GCgh9mCil0+l0uVxKKaMoOjw8NAwDLqaUWiwW8/l8vV4zxo6Pj23bBgCpQBTVeJaKopIKGoho4FvGJ/u+q2si4a/eu9dut4+OjhzHgQ9CYBmBZfC8goZRALVUPK+SHCwj8GKxH/qmYRANHsq27f39/b29vSzLOOfT6TQMwyAIHMeBC6zXa9d12c56vU6S5LXXXrMsizHmeR6lFNBjRQGhD0dRFEmSnJ6ertfrT3ziE57nEULgYtvtNk3TOI632y1j7PDw0DAMAJAKRFGNZ6koKqmgsQ46rQPXWqViEs8t2xqNrnY6LnxwiAbPH4R/93q8qbfQSAogJ8Z/FdW/ZLFn0ucCu+e5RIOHopSynfV6zTm/ffu24ziMsU6no+s6vNV6vQ6CAHacnX6/n2UZ53wymYQ7juMAekwoIPRBW6/XcRwnSeL7/rVr187Pzz3PI4TABaqqSpKEc67rehRFQRAQQgBAKhBFNZ6loqikgoa7u9icLXOllK53tJokad6TxKG6Y+g21WGHaBrR4D1rUf35g/CbJ3OpoLEUQC0Vz6tvzapQ5Ndduh90qK7DBZydfr+fpun5+flkMmGMBUFg2zbsSCk3m83+/j7ch1LKdtbrNef89u3btm0zxjzPo5QC+mhRQOgDIqVcLBZxHK/Xa8bY8fGxbdt1XU8mk+12SwiBB+R5znfa7fZwOOx0OpqmSQW1VFlZj2epKCqpAP13UoFUCgC2oIOC01U1WadE02DHprpj6A7VWctwqO4Yuk112CGaRjR4hwLLCCyD5xU0nlLA8yrJq2BZXzXlIPRtyyIaPJRhGN1uN4qi1WrFOb9165bneYwx13WLogAAy7LgYZydwWCQZRnn/OzsLAiCMAwdxwH0UaGA0PtW17UQgnMupYyiaDRDVYhcAAAgAElEQVQaUUphhxBCKa3r2jAMuM9qtYrjWAgRhuHR0ZHjOAAgFSR5NZ6lWVlLpaQC9AhSgVQKdpZlvSxrADjJgGga7NhUdwzdoTprGQ7VHUO3qQ47RNOIBg8iGjx/EP7vr8/zWgICUABJXokc/nWZeCY99q2B3yEaPJSmae7OYDAQQkwmEwDQdd0wDEIIXIxSynbW6zXnHNBHiwJC70NRFJzzJEksy+r1ep7nEULgPoQQ0zSrqmq1WgCglFosFvP5fLPZMMaOj49t2wYAqUAU1XiWiqKSCtB7JhVIpWBnWdbLsgaAkwyIpsGOTXXH0B2qs5YBAN2WaVMddoimEQ1aVP8f+t7/MRFKAfp3CqCWiufVS0UVpsUzLW0Q+galRIOHMk2z1+t1u93FYnHr1q08z23bZoy1221N0+Bizg6gjxYFhN6T1WoVx7EQIgiC0Wjkui5cwDCMsiy3222apvP5XEoZRdFoNKKUAoBUIIpqPEtFUUkF6MMgFUilYGdZ1suyBoCTDIimwY5NdcfQHapf9Wy5Wd25x0FrA3qAUsDzKslBT+eeSX9gr+07LbgAIcTfuXr16na7PTk5MQwjDMMgCCilgJ4YFBB6N6SUWZZxzjebTRiGx8fHtm3DI2maNp1O7927ZxjG3t6e7/uEEACQCkRRjWepKCqpAH3EpAKpFOwsy3pZ1gBwkq01AKm1FaALKYBaKp5X/2XCr5vbiLF2u61pGjygrus8z4MgME2z1+tlWcY5n06nQRAwxhzHAfQEoIDQO1PXtRAijmMAiKJoNBpRSuGR8jznnN+9e1fTtI997GOdTkfTNKmglior6/EsFUUlFaAnh1SA3rlcEWroJycnhmEwxnzfp5TCffI8N03TMAwA0HU93Fmv15zz1157zbZtxpjnebquA3p8KCD0dvI855wnSdJqtfr9vud5hBB4pOVyyTkXQjDGrl+/LoTwPE8qSPJqPEuzspZKSQUIPdVq0Pr9/qC3l6Yp53w6nYY7rVYLdjabTavV0jQN7uPsDAYDIcR8Pj87Owt3bNsG9DhQQOhiy+WScy6ECILg2rVr7XYbHklKmWUZ53yz2URRdPPmTcuy8jw/v3cvXhf/cm8hikoqQOhysKkOALqus53VapUkyauvvuq6LmOs0+ms12vHceBhKKXdbjeKotVqxTm/deuW53lhGHY6HUIIoI8QBYQeIKXMsiyO46IoGGM3b960LAseqa7rNE3jOJZSdrvd0WhEKQUAqWBRqxPde/WUSwUIXSaeSYmmwZvaO71eTwgxnU7Pzs7SNL158yZcTNM0d2cwGAghNpuN7/uAPloUELpPVVVCiDiOCSGMsSAIKKXwSGVZJkkSx7Fpmr1ez/M8QggASAWiqMazNCkqpVFQgNBlQjQY+S2iwfcwTbPX63W73TiOJ5PJnTt3ut1uGIbtdhsuZppmr9eTUgL6yFFAaCfPc77jOM7+/n6n0yGEwCNtNps4joUQruseHh52Oh3YkQpEUY1nqSgqqQChS4lommvocAFCiGmah4eHBwcHQog7d+5YlhVFked5uq7DBQghgD5yFFDjLZfLOI7TNA3D8OjoyHEceDvL5XI+ny8WizAMr1+/3mq1AEAqkEplZT2epaKopAKELjEp5elrt/ciFgSBYRjwgM1m02q1nJ1er5em6b17987OzhhjQRDYtg3oyUABNZWUMk3TOI7LsmSMPffcc6ZpwiNJKbMsi+O4KArG2HA4NE0TAKQCUVTjWZqVtVRKKkDo0qOgdF1fLBaz2SwIAsaY4zhwn/V6HQQB7FBKoyhijK1WK875rVu3fN9njLmuq2kaoMeKAmqeqqqSJOGcE0KiKPJ9n1IKj1TXtRAijmMAiKIoCAJKKQBIBaKoxrNUFJVUgFBz/N/f+sf/+Xf+1//pZ37ms5/9LADcvn3bcZwoijzP0zRNSrnZbIbDIdxH0zR3p9/vJ0lyenqq6zpjLAgCSimgx4QCapI8z/mO4zjD4dB1XUIIPFJZlnzHNM1+v+95HiEEAKQCUVTjWSqKSipAqFmU+oGjKy//4A/+wR/8wR/+4R9++tOf/vmf//mPf/zjZ2dn0+k0iiLTNDVNM00THsayrMFgsLe3l2UZ53w6nTLGgiBwHAfQR44CagCl1HK5jON4sViEYXh0dOQ4Dryd9XrNOU+SpNPpjEYj13VhRyoQRTWepaKopAKEGojq5MVP/fD/+OM/Mh6P/+zP/uxrX/vaV7/61R/7sR/74he/+OKLL2ZZdn5+TggpiqLVasEFdF0Pd9brNefctm1AjwMFdKlJKYUQnPOyLBljw+HQNE14O4vFIo7jxWIRhuGNGzdarRYASAVSqaysx7NUFJVUgFCT2VTXNO2TO7/+67/+9a9//Stf+cqv/Mqv3Lx583Of+9yP/uiP7u3tffe7322321EUua5LCIELODuAHhMK6JIqy1IIwTknhHS7Xc/zKKXwSFLKLMvm83lZloyx4XBomiYASAWiqMazNCtrqZRUgFDD2VSH+wyHw1/7tV/7pV/6pb/5m7/58pe//Hu/93vf+MY3PvnJT37uc5/7vu/7vslkQghhjAVBQCkF9IShgC6dzWbDOU+SxHXd4XDY6XQ0TYNHqutaCDGfzwkhURT5vk8pBQCpQBTVeJaKopIKEEL/zjMp0TR4K8dxPvOZz7zwwgt/+7d/+w//8A9/+Zd/+cd//McvvvjiL/zCL/z4j/94lmXT6ZQxFoZhq9UC9MSggC4LpdRiseCcLxaLMAyPjo4cx4G3UxRFkiScc9u2B4OB53mEEACQCkRRjWepKCqpACH0/yEajPwW0eB7SClns1kcxy+++OLP/MzPfOlLX/qLv/iLP/3TP/3FX/zFj3/845///Oc/85nPSClfffXVTqfDGHNdlxAC6HGjgJ5+2+02TdM4juu6ZowNh0PTNOHtrNdrvhMEwWg0cl0XdqQCUVTjWSqKSipACH0PommeSeGt8jy/e/cuANy4ccO2bQAYjUZf+tKXfvmXf/mv/uqvvvzlL//2b//27//+7//0T//05z//+W63O5lMCCGMsSAIKKWAHh8K6GlWlmWSJJxzSmkURb7v67oOj6SUWiwWnPPlcskYOz4+tm0bAKQCqVRW1uNZKopKKkAIXcSmOtyHcz6ZTKIo6vf7hBC4T6fT+dmf/dnPfvazL7300le+8pWvf/3rf/RHf/STP/mTX/ziF3/kR34kTdPpdMoYGw6HgB4TCujptF6vOedJknQ6nStXrriuq2kaPJKUMk3TOI7Lsux2u8Ph0DRNAJAKRFGNZ2lW1lIpqQAh9Ag21eFNdV1Pp9Msyw4PD33fhwvouv6fdn7jN37ja1/72le/+tXPf/7zP/iDP/iFL3zhp37qp8IwBPT4UEBPFaXUYrGI43i1WoVheOPGjVarBW+nruskSeI4JoR0u13f93VdBwCpQBTVeJaKopIKEELvhGdSomkAsFqt7t69a5rmjRs3TNOEd+D69eu/+Zu/+au/+qvf+MY3vvzlL//Wb/3W7/7u7/71X//1zZs3AT0mFNBToq7rLMvm87mUkjF2cHBgmia8naIo+E6r1drf3+90OoQQAJAKRFGNZ6koKqkAIfQOEQ2OI5docO/evbOzs8FgsLe3p2kavBtBEHzhC1/4uZ/7uX/8x3/8kz/5k5s3bwJ6fCigJ15ZlpzzJEkMw+h2u0EQEELg7azX6ziOkyQJguDatWvtdht2pAJRVONZKopKKkAIvXMagCMrR1Ovv/56nudHR0eu68J7RSn9iR1AjxUF9ARbr9d8x/O8w8PDdrutaRo8klJqsVjEcbxarRhjx8fHtm3DjlQgimo8S0VRSQUIoXfFpqS7jts6vPz/fJsxdv36dUopoKcfBfTkkVIul8v5fL5er8MwPD4+tm0b3o6UUggRx3Fd11EUXblyxTAMAJAKpFJZWY9nqSgqqQAh9G7ZOvmJwyieFicnJ4ZhVFW1XC49zyOEAHrKUUCP23K5XK/XvV4PAOq6TtM0jmMpJWPs8PDQMAx4O1VVJUnCOdd1PYoi3/d1XQcAqUAU1XiWZmUtlZIKEELvFtHApeQ/9juz0xMp5Q/90A8ZhiGEmM1m5+fnjLEgCCilgJ5aFNDjRgiZz+edTidNU865aZq9Xs/zPEIIvJ08z/mO4zjD4bDT6WiaBgBSgSiq8SwVRSUVIITeG5uSTx0w2Czv3nktDMPBYEAIAYBut8sYy7JsPp+fn5+zHdM0AT2FKKDHbbvdzufz9Xq9t7c3Go1c14V3YLVaxXEshAiC4OjoyHEc2JEKRFGNZ6koKqkAXW5Eg8AyRr7znXi5qbeAPlC2Tl44CNP4PE3Tg4ODIAjgPoSQYGe5XM7n8+985zthGDLGHMcB9FShgB4TKeVisYjjeL1et1qtg4OD/f19eDtSyuVyOZ/PN5tNGIbHx8e2bcOOVCCKajxLRVFJBehyIxoElvGJvh9YBtFg37VeupuIopIK0PtHNGjr2g/12pOTO4ZhXL9+3bIsuIC7s9ls4ji+ffu267pRFLmuq2kaoKcBBfSRq+taCME5l1JGUTQajeI4LssSHmm73aZpOp/PpZSMsdFoRCkFAKlAKpWV9XiWiqKSCtCl16L68wdhYBlEg3/XovoLo64oqvEsFUUlFaD3zKbkUwdsu0xPX7s9GAz29vY0TYO302q1rly50uv1kiR54403TNOMosj3fUIIoCcbBfQRyvM82bEsq9freZ5HCAEAx3GSJFFKaZoGDyjLUggRx7FhGN1uNwgCQggASAWiqMazNCtrqZRUgC49okFgGc8fhC2qw1sRDZhtvDDqiqIaz1JRVFIBeleIBh1D/+GBn5yfrdfro6Mj13Xh3TBNs9/vR1GUpum9e/eUUowxQE82CugjsVqt4jgWQgRBMBqNXNeF+7RarbIsq6oyTRPuk+c532m32wcHB51OR9M0AJAKRFGNZ6koKqkANQHRILCMT/T9wDKIBhchGjDbeGHUFUU1nqWiqKQC9E7YlHzqgNEyv/v6a47j3Lhxg1IK7wmlNIqiMAyVUoCeeBTQh0lKmWUZ53yz2YRheHx8bNs2PIBS6jjOer02TRN2lssl51wIEYbh0dGR4ziwIxWIohrPUlFUUgFqAqJBYBmf6PuBZRAN3gmiAbONF0ZdUVTjWSqKSipAj2Dr5CcOo2US3z0/39/f73a78L4RQuA+0+m03W7HcXzt2jVATxIK6MNR17UQIo5jAIiiaDQaUUrhYo7jrNdrz/MWi0Ucx5vNhjF28+ZNy7JgRyoQRTWepaKopALUEC2qP38QBpZBNHi3iAbMNl4YdUVR/ee7PK8loAcQDVxK/mO/Mzs9kVJev37dcRz4EGy329deey1N07Ozs49//OOu6wJ6MlBAH7Q8zznnSZK0Wq1+v+95HiEE3o5t23fu3Fkul1LKbrc7Go0opbAjFYiiGs9SUVRSAWoIokFgGc8fhC2qw/tANGC28ROH0Tdfm+agK0D/P5uSTx0wbbOavH4nCIJ+v6/rOnw4Dna+/e1vX716td1uA3piUEAfnOVyyTkXQgRBcO3atXa7De9AVVWc89lsxjk/PDyMoogQAm+SCv7zXX6+LqQC1BBEg8AyPtH3A8sgGrx/y+VyNpsdaVsn6n13WYuikgoajmjQMfRPDcM0vieEGA6HQRDAh+9jH/sYoCcMBfS+SSmzLIvjuCgKxtjNmzcty4J3IM/zOI6TJHFd99q1a6Zp2rZNCIG3KrdSKkAN0aL68wdhYBlEg/evqqp79+7Fcdzv97vdLiHkgIEoqvEsFUUlFTRTi+rPH4TWtjp743VCyNHRkW3bgJqKAnofqqoSQsRxTAiJosj3fUopvAPL5TKO4zRNGWNHR0eO4wBAmqar1arT6cB9iAbHkfvPk0QqQJcb0SCwjOcPwhbV4YPAOZ9Op47jPPvss7Ztww7RgNnGC6OuKKrxLBVFJRU0ik3Ji1ejdSpuTyZ7e3u9Xo8QAqjBKKD3ajKZcM4dx9nf3+90OoQQeDtSyizL4jguioIx9txzz5mmCW9qt9tCCHiARxTRNKkUoEuKaBBYxif6fmAZRIP3b71eT6fTsiyHw2EQBPAAogGzjRdGXVFU41kqikoquPSIBh1Df34/uDe5u16vr1696nkeoMajgN4r13WDIHAcB96Buq6FEJxzpVQURUEQUErhrRzHmUwm2+1W13XYWa/X8/mci1RaEYAG6NIhGgSW8Ym+H1gG0eD9q+t6Pp+fn5/3er3RaEQphYsRDZhtvDDqiqJ66W6yqbdwebUoef6AGVVxeue24zjXr183DAMQAqCA3ivP8+AdKMuS75im2ev1PM8jhMDDmKZJCCmKwnGcLMviOF6tVoyx42efXc2Xs3UF6HJpUf35gzCwDKLBB0IIMZ1OTdO8ceOG4zjwzhANmG28eDV66W4iikoquHxsnfzEKFom/HQ6HQ6H3W4XEHoTBfRIm82m1WrBe7LZbOI4TpKk0+mMRiPXdeGRCCGtVms6nUopy7LsdrtXrlwxDAMAngnh3iaRCtClQTR4/iBktgEfhDzPZ7PZarUaDAZhGGqaBu9Si+ovjLqiqMazVBSVVHA5EA1cSn544M9O36iq6saNG47jAEL3oYAucHp6CgCe57VaLXiXlsvlfD5fLBZhGP6/7cFbjOPofSj4Pz9+/EhRFEVSd4qSqiR1zcTH0ztnNzNVO5lMFxDkIX4xEOfBQAAjMPIcIMDBPgVBHvKS5CUBFrkgNoIYCZA8JEgeYmCx9k67x8ebmsQ55+ycGLanpy4SdaOoS6lUEkVR5PHWYgB7PT1d3V3dLZX+v1+9Xo/FYvA4QRCcn5+7rut53s/8zM9omkYphY+pjBKOC6MIthvhgHAcfKowisIINoK/CsMICAfPIgxD13Udx9F1/c6dO4IgwNMiHBiS8E45PV4sj1qjebCCDSdRclA0uPmlfXqsqmqpVKKUAkI/iQL6Kb7vX1xcNBoNSZISiQRcWxiGk8nEdV3f9w3DME2TMQaPs1wuR6PRYDAQBKFYLI7HY8MwCCHwYyTKw/bhAAgAx3GSwANAOsYSjAo8BwCMEFWkEuXhihesJovAD0MAWK6iCz9w5z4AeMEKAFZhFMHaCSP459ZQE4W7uaQmCoSDpzCZTLrdLiFkZ2dHURS4CYQDldGSGvvhcAobi3CgCvx+0Th3neFwWCwWdV0HhD4JBfRTZrOZ67qU0nQ6TSmFawiCYDweDwYDjuMMw9A0jVIKj7NYLAaDwWg0kmW5WCwmEokwDIfDoe/7kiTBT5IoP/UDuO04DghAFEUJEkrLeUYWdcPQlTgAEI4jHHwihVGFUfhYGEEYRQDgBasfOXEGg5Be+EEEXARrJIxg6C0fNFxNFPaLeozycG2+7/d6vfPz83w+bxgGIQRuyDxYHbVG48USNlaM8vtFXQqDduOUEFKv1yVJAoQegQL6KZIkJa/k83l4HN/3h1dEUczlcqqqEkLgcWaz2fCKpmm7u7uyLMMVnudlWZ7NZpIkwY/hIFIZnfoB3F6EA4XnXs2o1Lt0XVdmUrZQUBQFnhzhgHAcACiMAtDXK+bFxbTV6QS80PDJkhcigDCCNRFGMPSW988G+0VdEwXCwacLw3A4HPZ6PVVV9/b2GGNwQ8IIxovlUWs0D1awsSRKDiup+eT8uN1Op9PZbJYQAgg9GgX0UyRJyufzcD2TyWSxWJTLZUVR4Bqm06nrutPpVNf1vb09SZLgJ8myPJvNDMOAK2EYTiYT13VJABwXj+C2IRwQjpN57j/mtWg+ddsNQRDKVlFVVbg5iYSyF685jrO6dDJ6TlS1/9o7v1iuwgjWxDxYPWi4mijczSU1USAcfKLpdNrtdsMwLJVKqqrCzZkHq6PWaLxYhhFsKMJBQuD3C5rbaU+n03K5rKoqIPQ4FNCz0TQtnU7D44RheHFx4bruYrEwDMM0TcYYfBJZljudTnRlPB67rhtFka7rZ//+PSjcAY7AbUE40EThbi6ZEPiLyblrnwFAPp9PJpMcx8FNI4Tk83lVVdvt9uXF5M18YSmI/607PveDMIJ1EEYw9JYPGq4mCvtFPUZ5+DFBEDiOMxgMcrlcOp0mhMANCSMYL5ZHrdE8WMHGilGyXzSE5aLdOGWM1Wo1xhggdA0U0LOhlMKnCsNwPB67rhuGYTqd1jSNUgqPFovF5vN5t9s9Pz/neV7TtH/913/96le/+u6DB//7//F/S/E4bD7CgSYKd3NJTRSmF5Mz21mtVplMRtd1juPgeZJluVar9fv909OTVCr1c8XsdBUdtUbzYAXrIYxg6C3vnw32i7omCoSDHxkOh91uV5blO3fuSJIEN2cerI5ao/FiGUawuSSe3CunpqOh3e0WCoVMJgMIXRsF9Di2bedyOUEQ4AkFQTC8wvN8Op3WNI0QAp9quVwOh8PBYEAIyeVy3/72t7/yla9885vfrFar/9t/+k/B+QDicdhkhANNFO7mkpoozC6nJ62G7/uZTMYwDEIIvBAcx2WzWVVVO53O8UcPTdM8rKT+r9P+YhXB2pgHqwcNVxOFvaTojVx/sTBNU9M0uDlhBOPF8qg1mgcr2FiEgwQlb+STTsv2fb9Wq8XjcUDoSVBAj+a6bhiGw+FQlmXDMODafN8fDoeDwSAWi5mmmUgkOI6DT+X7/uBKPB5Pp9Pf+c53/uZv/ua999577bXX/uAP/uCLX/xiLpdrT73326Mwgg0Vo/x+UddEYT67bJy1Li8vM5mMYRiUUnjhJEna3d0dDofNZjOZTL5uJN7vzyJYI2EEQ295tFjGgL29U1QkBjckjGC8WP4/vfPxYhlGsLkkSg6KBr+Y26fHqqqWSiWe5wGhJ0QBPUIQBD/4wQ84jqOUiqIYBAGlFB5nPp8PBoPRaKSqaqVSURQFHsfzPNd1R6NRMpnUNO3rX//6X//1X/f7/VQq9ad/+qdf+MIXDMOAKyqjhOPCKIINJPHksJKCpW83O5PJJJ1OF4tFQRDgpTIMQ5KkH/7wh+3RcVSoA8fBmokimAF50BodFA1NFAgHz2gerI5ao/FiGUawuQgHKqP7pj4Z9AeDgWmahmEAQk+FAnqEyWSSSCTS6bTnefF4HB5nOp0Oh8PxeGwYRr1ej8Vi8Diz2cx13fF4bBhGIpH4+7//+7/4i7/493//93feeec3f/M3X3/99VdeeUVVVfiYRHnYQBwHcQJvFhKDbmc4HKZSqb29PcYYvGxRFI1GI8dxYonkQjCA42BdeUH4oOFqonA3l9REgXDwFMIIxovlUWs0D1awyWKU3y/qUrTqNM8AoF6vS5IECD0tCugRVFV95ZVXRFGEa2i326PRKJVKvfrqq4wxeJzpdOq67nQ6NQwjFot97Wtf+8u//MuTk5Nf/MVf/J3f+Z1f+qVfkiRpOByenp6applOp+FjEuWnfgCbgxF4M59cXowbHz00DGNvb0+SJFgD0+m02+0Gq5Wcyv63oRdRDtZbGMHQWz5ouJoo7Bf1GOXhScyD1VFrNF4swwg2mkTJYSU1n5wft9upVCqXyxFCAKFnQAE9Ar0C12MYRjabpZTCp4qi6OLiwnVdz/MMw5jNZn/8x3/8V3/1V47jfO5zn/ujP/qjX/iFXxAEAa4YhsEYs23b8zzTNMmPcJzK6NQPYENQCO/GeefsOJFI1Ot1WZZhDXie5zjOxcVFMpX54Nz3hosIONgQYQRDb3n/bLBf1DVRIBw8VhjBeLE8ao3mwQo2GeEgIfD7BW3Q7Uwmk3K5rKoqIPTMKKCbIEkSfKowDCeTieu6y+UylUqdn5//3u/93t/+7d9eXl5+/vOf//Vf//W3336bEAI/SVGUarVq2/bp6allWYyxvZTSvfTCCNafAFFldbFaiDs7O4qiwBoIgqB/xUilMuXd97vnPvCwgebB6kHD1UThbi6piQLh4FHmweqoNRovlmEEGy1G+f2izgK/3ThljNXrdcYYIHQTKKBrm81msizDEwrDcDweu64bRVEqlXr48OEf/uEf/t3f/R0A/Mqv/MqXv/zlN954g+M4eATG2M7OTrvdPj4+LpVKmhzXRGHoLWHt5chyp2CqqgprIAzD4XDoOE5MltPl3f/uTi8vz6MINlcYwdBbPmi4mijczSU1USAc/LgwgvFiedQazYMVbDiJJ4eV1HQ0PO508vl8JpPhOA4QuiEU0DW0Wi2e5yVJkmUZri0IgvF47Louz/OpVOqDDz743d/93X/8x39UFOVLX/rSr/3ar929exeugRBiWVa/3z8+PrYsa7+o/58fdQMgsN56oVBnsTACwsHLNZlMer1eGEWJnPm9weXMmUYR3A5hBENv+aDhaqKwX9RjlIcr82B11BqNF8swgo3GAUiw+jlT79lN3/er1aqiKIDQjaKAPtVyuRyNRrZtz+fzbDYbj8cFQYDHWS6Xw+FwMBiIopjJZN5///2vfvWrX//617PZ7G/8xm986Utf2tvbgyeUyWQYY41GQxCE3YhrMs0LQlhjS+AeNFxNFO7mkpooEA5evNls5jjO5WwmG5nvny88dx4BgVsnjGDoLe+fDfaLusroxA+OWqN5sIINJ1GSng2SIj19+ENd16vVKqUUELppFNCnury8bLfbURRZlqWqqiAI8KkWi8VwOBwMBoqiZLPZ995778///M+/8Y1vVKvV3/qt3/rVX/3VSqUCTyUIAt/3wzB0HCedTv+8qb3XGnurENZYGMHQWz5ouJoo3M0lNVEgHLwYvu/3XbfvDuJGukF47zyIgIdbbR6sHjRcwnFhFIURbDTCgcrovqkPuouTkxPGWCaTCcMQEHoOKKBPpWnaZz7zmV6vVyqV4HFs2x4Oh5qmZTKZb3zjG1/5ylfee++9z372s7//+7//xS9+MZ/Pw1MJgmA4HLquK4ri7u6uJEntdrvXar5VMP9zZ7JYRbDewgiG3vJBw9VE4cF4jCEAAB+JSURBVG4uqTJKOI5w8JwEq5U7GLbc4YCpMzEVXULEUdgOYQRhFMGGi1F+v6hL0aprN8IwfPPNN6Mochznww8/zGQyhmFQSgGhm0Nh6333u9+1LCuXy8EjMMZKpRJcg6ZphJB/+qd/+upXv/r++++/+eabf/Inf/KFL3zBMAx4KkEQDIdD13UlSbIsS1VVuFIul3u9Xvvs9M1C8b8O55erKIxgzYURDL3lg4ZLOE5ldC+lqIxKlAcAwnGEg6cWRhBGEQB4waozOre9aLIIQl6NVgDAAdooEiWHlZR3MTlutQzDyOfzhBAA2NnZmU6njuMMBoNMJmMYBiEEELoJFLZbv9//5je/+cYbb3Q6nddffx2ezQ9/+MMvf/nLH3zwwTvvvPO1r33t85//fCKRgKeyXC6Hw+FgMJAkqVQqJRIJ+DGEkEKhIIqi3Tx73TR5JfnPraEXhLD2wgjCKBp6y/fbI8JxACBRXmU0FWMCzwEAIwQAYgIPH0swCgAXfgAfmy9XAOCHIQAsV9Fg7k/8wAtWALAKowjQRiIcJAR+v6ANup3JZGJZlqZp8GOUK5PJxHGcwWCQzWaTySQhBBB6NhS222KxuHv3rqZphUIBntn/fOW3f/u3P/e5z0mSBE/F9/3RaOS6rizL5XJZURR4BMMwGGPNZjPp+/dK2W81Bt4qhA0RRhBGEQBM/WDqB91Lj3AcPLkwisII0KaLUX6/qIurZatxKghCrVYTRRE+iaqqiqKcn587jjMYDLLZrKqqgNAzoLDdLMuilObzebgex3E0TWOMwSP82Z/9mSAI8FR83x8Oh67rKopSqVQURYHHURSlWq3atr1oNd82C99un3urEDZQGEEYRYC2kkTJYSV1OR4ddzq5XC6TyXAcB49GCNF1PZlMDofDVqvlum42m1UUBRB6KhS2Xj6fh2vo9XoA8IMf/EBRlM985jOSJMEnEQQBnpzv+4MriqLs7u7G43G4NlEUd3Z2Oj/SPDswi//Wv5wGYRgBQuuPcJCg5M2C1m+3ZrPZ7u6uoihwPYSQdDqtadpwODw7O4vH49lsVpZlQOgJUUDX4Hlev98fjUapVCqTyUiSBDfE933XdYfDYSKRqFarsizDk+N53rIsx3HaZ6f/S9GKYvGj1mgerAChNSZRclA0+MW8dXYiy3K9XqeUwhOilGazWU3TBoPBRx99pGlaLpdjjAFC10YBXYMkSXt7e91ut1wuww1ZLBaDK8lkslqtyrIMzyabzTLGbNvOZDKHlfS7Z64XhIDQ+iEcqIzum/rF0O33+6ZpplIpeAaMsUKhYBjGeDxmjAFCT4ICuh7GWLlchpvged7giqZptVpNlmW4IZqmiaLYbDYXi8U7xfwDe+StQkBoncQov1/UpWjVtRthGNZqNVmW4SaIopjL5QChJ0QBvUCe57muOxwOdV2/c+dOLBaDmxaLxXZ3d1utVtduvFUw/3NnslhFgNB6kCg5rKQW04vTdlvTtFwux/M8PDf9fl9RlH6/Xy6XAaFHoIBeCM/zXNcdDoeGYezt7UmSBM+NIAjlcrnb7bbPTvdN678MZperKIwAoZeIcJAQ+ANTHzm98XhsmqamafA8eZ7n+/53vvMdSZIIIZqmKYoCCP0UCuiFkCQJAPb29iRJguePEGKapiiKrcbp66bJK8l/bg29IASEXoYY5feLurhadppnhJBqtSpJEjxnkiQVi8XLy0tZliVJUhQFEPokFNCLYlkWvFipVEoUxUajofn+vVL2W82BF4SA0AtEOEgyemAZs/PxcbudzWYzmQwhBF6Uvb09QOhTUUC3mqIo1Wq11Wr5bfvnzcL95mAZcYDQCxGj/H5RV3iu227NZrOdnZ1EIgEIrRkK6EZ5nidJEqwTSZJ2dnba7Xbz5KNXY/GTFZuFEEaA0HMVo+Swklp58+NTW5blWq0mCAIgtH4ooBsyGAw+/PDDWq0WhqEsy7BOoigSRbHZbHrd7n949dWYkTlqDedBCAg9B4QDldGDon4xHHS7XdM00+k0ILSuKKBn5nle94qqquPxOJPJwNoIw3A4HLquKwjCa6+9tlqtbNsWKL1XTt1vDLwgBIRuVIzy+0U9BmHXbi6Xy3q9LssyILTGKKBnJklSLpeTZTmbzcLaCMPw/Py83+9zHFcoFJLJJFxhjDWbzcVicc/Kf6s59FYhIHRDJEoOKyn/cnrSaiWTyVKpRCkFhNYbBXQTYldgbZyfnzuOE4ZhJpPRNI0QAh+TZXl3d7fVanWaZz9nFr/dPl+sIkDo2RAOVIHfLxojpzccDovFoq7rgNAmoIBul4uLi36/7/t+Op02DIMQAj+FMVapVLrdbvvs9MC0/ot7OV1FYQQIPZ0Y5feLuhQG7cYpIaRer0uSBAhtCArotri8vOz3+7PZLJ1OG4ZBKYVHI4SYpskYa52d/EfL4uTEP7eGXhACQk+CcJBk9MAy5pPz43Y7nU5ns1lCCCC0OSigzTebzVzXnUwm6XTasixKKVxPOp1mjNm2rWnevVL2W82BF4SA0PXEKL9f1BWe63Xal5eX5XJZVVVYAycnJwCwu7sLCF0DBbTJPM9zXXc4HKbT6b29PcYYPCFVVavVqm3bftt+p2g+sEfeKgSEHidGyWEltfLmJ2ctSZKq1SpjDNbA97//fUrpP/zDP7x1BRB6HApoM/m+714xDGNvb0+SJHhakiTt7Oy0f6RxelAw/61/OQ3CMAKEPhHhQGX0oKhfDAfdbrdQKGQyGVgbr7766gcffPDaa6/t7u4CQtdAAW2aIAjcK6qq1ut1WZbhmVFKS6WS4zjts9OftUqhJB+1RvNgBQj9pBjl94u6zEXdlu37fq1Wi8fjsGZeuwIIXQ8FtDmCIBgOh67ryrK8u7sbj8fh5nAcl8vlRFG07WY2mz2spN49c70gBIQ+JlFyWEn5l9PjVktVVcuyKKWA0IajgDZBGIbD4dB1XcZYqVRKJBLwfGiaJghCs9n0ff9eKf+txsBbhYC2HuFAZXTf1Md9ZzAYmKZpGAYgdCtQQOstDMPxeNzv93meLxQKyWQSnrN4PF6tVm3b7tmNt03zX3qTi+UqjABtrRjl94u6FK06zTMAqNfrkiQBQrcFBbTeCCGLxSKbzSaTSUIIvBCMsZ2dnU6n026cvlm0loJ41BrNgxWgLUM4SDJ6YBnzyflxu51KpXK5HCEEELpFKKC1l8vlCCHwYhFCisWi67onJ8eWZR1WUvfP3HkQAtoaMcrvF3WF55xuZzKZlMtlVVUBoVuHAlp7hBB4SdLpNGPMtm3D9++V0/fPBt4qBLQFYpQcVlLhwjtttBhj9XqdMQYI3UYUEPpUqqpWq9Vms7lYLN42c/cbg4AjgG4vwoHK6EFRn46GnU4nn89nMhmO4wChW4oCWgOXl5er1UpVVVhLkiTt7u4+fPjw7F/ft3RjFM9cBGEYAbp9YpTfL+oyF/XarcViUa1WFUUBhG41Cuil6nQ6o9FoOp3GYrHd3V1FUWD9eJ7nOE4QBOl0erVa/WwqthJjR63RPFgBukUkSg4rqeXs8qTVUhSlWq1SSgGh244Cennm87kgCI7jmKa5t7cH6ycIAtd1+/2+rut7e3uMseFw2Gic5fP5w0rq3TPXC0JAm49woDK6b+rnbt91XdM0DcMAhLYDBfTyxGIxnuffeustxhismTAMx+Nxr9eTJKlWq8myDFcMw2CM2ba9WCzulfLfagy8VQhok8Uov1/UpWjVtRthGNZqtVgsBghtDQropWKMwfqZTCaO44RhWCgUNE2Dn6QoSrVatW27ZzfeNs1/6U0ulqswArRxCAdJRg8sw7uYHLdaqVQql8sRQgChbUIBoR8zn88dx7m8vMxms4ZhEELgkzDGdnZ22j/SOH2zaC0F8ag1mgcrQJsjRvn9oq7wnNPtTCYTy7I0TQOEtg8FhK4sl0vXdfv9fjqdrtfrjDH4VIQQy7L6/f7p6UmxWDyspO6fufMgBLQJYpQ/rKQif3HasBlj9XqdMQYIbSUKaOuFYTgcDh3HkWX5zp07sVgMri2TyYii2Gw2U75/r5y+3xh4QQhojREOkoweWMbleNRut/P5fCaT4TgOENpWFNB2Oz8/7/V6hBDLslRVhSenqmq1Wm02m77vv1PMP7BH3ioEtJYohG+Xs3ECvXZrNptVq1VFUQCh7UYBbavZbNbr9ebzeS6X03WdEAJPKxaLVavVVqvVaZ69ZRa/27u4CMIwArRWJEqsxblzehEEgaqq9XqdUgoIbT0KaPv4vu84znA4zGazpVKJUgrPjFJaLpd7vV777PRni9ZKjB21RvNgBWgNEA5URvdNfeQsHz58KElSoVCglAJCCIAC2iar1WowGDiOo6rq3t6eJElwcziOy+fzjLGzs1PTNA8rqXfPXC8IAb1UMcrvF3UpWnXtRhiGb775ZhAE7Xb74uIin89LkgQIbTcKaDtEUXR+ft7tdgVB2NnZURQFng/DMBhjtm0vFot7pdy3GgNvFQJ6GQgHSVE4KOqL6cVJq6Xrei6X43keAGRZdhznww8/zOfzqVSKEAIIbSsKaAtMp1PHcXzfz2azuq5zHAfPk6Io1WrVtu2e3XjbNP+lN7lYrsII0IsUo/x+UU9Q0nd64/G4WCxqmgYfo5SapqmqaqfTmUwmhUJBlmVAaCtRQLdaEASdTuf8/DybzRqGQSmFF4IxtrOz0/6Rxum+VfIpO2qN5sEK0AsRo/xhJRX5i7PTNiGkWq1KkgQ/RVGUWq3W7/cfPnyYvUIIAYS2DAV0q1FKZVnO5XKMMXixCCGWZTmOc3p6YlnWYSV1/8ydByGg54lwkGT0wDIux6NOp5PNZjOZDCEEHoEQksvlEolEt9t9+PChaZqKogBC24QCuu1SqRS8PNlsVhTFZrOZyWTulVP3GwMvCAE9HzHK7xd1hee67dZsNtvZ2UkkEnANsizv7OwMh8PT01PDMLLZLKUUENoOFBB6zpLJpCAItm0vFot3ivkH9shbhYBuFOEgKQoHRX3lzY9PbVmWa7WaIAhwbYSQdDqtKEq323348GGhUEgmk4DQFqCA0PMny3K1WrVtu2s33iqY3z7rL3kWAboZMcrvF3VVIMPBoNfrFQqFdDoNT0WSpJ2dneFw2Gq1JpNJLpdjjAFCtxoFtPl831+tVrFYDNYYpbRcLne73R/89w9yPK+kc6crcR6sAD2bGOUPKymyCpoNOwiCWq0myzI8G8MwFEXpdrsPHz7M5/OGYQBCtxcFtMlGo5Eoiv/2b//22c9+lud5xhissfkVSmkQBBkltqPp7565XhACeiqEg6QoHBT1xfSi3W4nk8lyuczzPNwExli5XB6Px8lkEhC61SigjbVcLvv9vuM41Wp1PB5rmgbrKggCx3EGg0E2m93d3Z3NZs1m0/f9e6XstxoDbxUCekIxyu8XdVUgTq83Go1M09R1HW6apmmA0G1HAW0sQRAqlYphGOl0GtbYaDTqdruxWOzOnTuSJAGAoijVarXZbC5azbfNwr/0JhfLVRgBuqYY5Q8rqchfnJ60CSG1Wk2SJHhRgiCglAJCtwUFtMnEK7Cu5vN5t9tdLBaFQkHTNPgxoiju7u622+1O8+zAKi144ag1mgcrQJ+KcJBk9MAy5pPzdrudTqez2SwhBF4I3/c9zzs5OalUKpqmAUK3AgWEnoPVatXv9x3HyWQypVKJUgo/hef5UqnkOM7JybFlWYeV1P2zwTxYAXqEGOX3i7rCc71O+/Lyslwuq6oKL9BsNptMJhcXF47jxONxjuMopYDQhqOA0E07Pz/vdruCINTrdVmW4VNls1nGmG3b2Wz2sJJ698z1ghDQTyIcJEXhoKivvPnJWUuSpGq1yhiDF0u7QinVNO3i4sIwDEBo81FA6+373/++7/t3796FTeB5nuM40+k0n8/rus5xHFyDpmmMMdu2F4vFPSt/1BlP/CCMAP1/YpTfL+pJxg9ct9vtmqaZTqfh5TFNEwBkWQaEbgUKaF11Op3vfe97H3744S//8i/D2gvD0HVdx3E0Tbtz544gCPAkZFne3d1ttVqd5tlB0fI4/qg1mgcr2Hoxyh9WUny4ajYavu/XarV4PA4IoZtDAa2rQqEgy3IQBKPRKJvNwhq7uLjodrscx+3s7CiKAk9FEIRyudztdk9Pjkul0mEldf9sMA9WsK0IB0lROCjq/uW01WqpqmpZFqUUEEI3igJaY8lkcn9/X9M0WFe+7zuOMx6P8/m8YRiEEHgGhBDTNBljJycnxWLxsJJ698z1ghC2T4zy+0VdFUjfcQaDgWmahmEAQug5oIDWm6ZpsJaiKBoMBo7jKIpy584dURThhqTTaVEUm82mtljcK2W/1Rx4QQjbJEb5w0qKC5Znpw0AqNfrkiQBQuj5oIDQk7u8vOx2u6vVyrIsVVXhpiUSiWq1atu237Z/3iy83z2/WK7CCG49wkGS0QPLmE/O2+12Op3OZrOEEEAIPTcUEHoSQRA4juO6bi6Xy2QyhBB4PiRJ2tnZabfbnebZQdFa8MJRazQPVnB7xSi/X9QVnnO6nclkUi6XVVUFhNBzRgGhaxuNRt1uNxaL7e3tSZIEzxmltFwu93q9k5Njy7IOK6n7Z4N5sIJbh3CQFIWDor7y5qeNNmOsXq8zxgAh9PxRQOga5vN5t9tdLBaFQkHTNHiBcrmcKIq2bWez2cNK6t0z1wtCuEVilN8v6knGDweDTqeTz+czmQzHcYAQeiEoIHQNjuNIklQqlSil8MJpmsYYazQavu/fs3JHnfHED8IIboEY5Q8rKT5cNRsN3/er1aqiKIAQeoEoIHQN+XxeFEV4eWRZrlarrVarazf+16I1B3LUGs2DFWwswkFSFA6K+nJ2edpqJRIJy7IopYAQerEoIHQNoijCy8YYq1Qq3W739OS4VCodVlL3zwbzYAUbKEb5/aKuCsTt913XNU3TMAxACL0MFBDaHIQQ0zQZY8fHx5ZlHVZS7565XhDCRolR/rCS4oJl46wZhmGtVovFYoAQekkoILRp0uk0Y8y2bX2xuFfKfPO4F3AENgHhIMnogWV4F5NWq2UYRj6fJ4QAQujloYDQlSAIKKWwIVRVrVarp6enrVbLEqWxkp0sV2EE6yxG+f2irvCc0+1MJhPLsjRNA4TQy0YBbb3JZHJ5eTkej4vFoizLlFLYBIvFYrVahWEo8+Qgl/AIPWqN5sEK1g/hQBOF/aIe+YvThs0Yq9frjDFACK0BCmiLBUEAAB999NF0Oi2VSrPZTFVVWHtBEHS73fPz80KhoGma4zgnJ8eWZR1WUvfPBvNgBeskRvn9oq6JwnDgttvtfD6fyWQ4jgOE0HqggLYYpRQAXnnllel0ms1mYROcn593Op1YLHbnzh3GGADk83lRFBuNRj6fP6yk3j1zvSCE9RCj/GElxYcru9mYzWbValVRFEAIrRMKaOvJV2DtLZfLXq83mUwKhYKu6/BjdF1njDWbzcVica+UP2qPJn4QRvASEQ6SonBQ1Jezy7N2W5bler1OKQWE0JqhgNAmGI/H3W5XluV6vc4Yg58Sj8er1apt2z278VbRmkXcUWs0D1bwMsQov1/UVYG4/f+XaZqpVAoQQmuJAkLrbblc9nq9yWSSz+cNw4BHY4zt7Oy02+3Tk2PLsg4rqftng3mwghcrRvnDSooLlo2zZhiGtVpNlmVACK0rCgitsfF43Ol04vF4vV5njMHjEEIsy3Jd9/j42LKsw0rq/pk7D0J4IQgHSVE4KOqL6UWr1dI0LZ/P8zwPCKE1RgGhtbRcLnu93mQyyefzhmHAk0in04yxZrOZ8v175fT9xsALQnjOYpTfL+oJSvpObzweF4tFTdMAIbT2KCC0fsbjcafTicfj9XqdMQZPTlXVWq3WaDQWi8U7xcL73fOJH4QRPA+EA00U9ot65C9OT1o8z9dqNVEUASG0CSggtE6Wy2W32724uCgUCrquwzOQJKlarbZarU7z7MAqeRx/1BrNgxXcqBjl94u6JgrDgdvpdLLZbCaTIYQAQmhDUEBobYzH406nE4/H6/U6YwyeGaW0XC73er3Tk2PLsg4rqftng3mwghsSo/xhJUWj0G42ZrPZzs5OIpEAhNBGoYDQGvB9v9frXVxcFAoFXdfh5nAcl8/nGWOnp6emaR5WUu+euV4QwrMhHCRF4aCor7z5mW3Lslyr1QRBAITQpqGA0Ms2Ho/b7baiKPV6nTEGz4FhGIwx27YXi8W9Uu6oPZr4QRjB04lRfr+oqwIZDgbdbtc0zXQ6DQihzUQBoZfH9/1utzudTguFgq7r8DwpilKtVm3b7tmNt4rWLOKOWqN5sIInQTjQRGG/qJNV0GzYQRDU63VZlgEhtLEoIPSSjMfjdrudSCTq9TpjDJ4/xtjOzk673T49OS6VSoeV1P2zwTxYwfXEKL9f1DVRmJyP2+12Mpksl8s8zwNCaJNRQOiF832/2+1Op1PTNDVNgxeIEGJZluM4x8fHlmUdVlL3z9x5EMLjxCh/WEmJhOt22qPRyDRNXdcBIbT5KCD0Yo3H43a7rShKvV5njMHLkM1mRVFsNpvp9OJeOX2/MfCCEB6BcKCJwn5Rj/zFcbtNCKnVapIkAULoVqCA0IsliqJpmpqmwUuVTCYFQbBt2/f9e1bhqDOe+EEYwf9PjPL7RV0ThfFo2G630+l0LpfjOA4QQrcFBYRerNgVWAOyLFerVdu2O82zg6LlcfxRazQPVvCxGOUPKykBopbdvLy8LJfLqqoCQuh2oYDQFqOUlsvlXq93enJsWdZhJXX/bDAPVoSDpCgcFPWVN2+0WpIkVatVxhgghG4dCghtN0JIoVAQRfH09NQ0zcNK6vvuRUWLJxk/cN1ut2uaZjqdBoTQLUUBIQRgGAZjrNls+r7/P+XzQRA0Gw3f92u1WjweB4TQ7UUBoZsWhiEhBDaNoijVatW27e9973tRFOm6blkWpRQQQrcaBYRuznw+932/0WiUSiVN02DTCIIgSVKr1YrH44ZhUEoBIXTbUUDohoRhOBgMHMeZzWaFQiEMQ0IIbA7P82zb5jjujTfeuLi4OD4+tixL0zRACN1qFBC6IbPZTFGU2WxmWVY6nYaNMhwO2+12Op3OZrOEkFgsxhizbXuxWORyOUAI3V4UELohiqKEYaiqKiEENkcQBN1udzKZlMtlVVXhY5qmMcZs214sFqZpUkoBIXQbUUDo5hBCYKNMp9N2u80Yq9frjDH4SbIs7+7utlqt09NTy7IkSQKE0K1DAaGtFEWR67qdTiefz2cyGY7j4JMIglCpVDqdzvHxcalUSiQSgBC6XSggtH1832+3277vV6tVRVHgU3EcZ5qmKIonJyfFYjGVSgFC6BahgNCWmUwmrVYrkUhYlkUphetJpVKMsWazuVgs8vk8IQQQQrcCBYS2RhiGjuO4rmuapmEY8IQSiUS1WrVtu9FoFItFQRAAIbT5KCC0HTzPa7fbYRjWarVYLAZPRZKknZ2ddrt9cnJiWZYsy4AQ2nAUENoCo9Go1WoZhpHP5wkh8AwopeVyudfrHR8fW5alaRoghDYZBYRutSAIut3uZDKxLEvTNLghuVxOFEXbtn3fz2azgBDaWBQQur1ms5lt24yxer3OGIMbpWkaY6zZbEqSpKoqIIQ2EwWEbinXddvtdj6fz2QyHMfBcyDL8u7uLmMMEEIbiwJCt47v+91udz6fV6tVRVHgeWKMAUJok1FA6HaZTCbtdluW5VqtRikFhBD6VBQQui3CMHQcp9/vm6aZSqXgJZlMJolE4uLiQlVVQAitPQoI3Qqe57Xb7TAMa7WaLMvwkkRRxBj77ne/+5nPfOb8/DyZTAJCaL1RQGjzjcfjVqul63oul+N5Hl6ei4uLxZVGo2Ga5nK5FAQBEEJrjAJCm0+SpGKxqGkavGyqqrbb7VdeeUWSJAAQBAEQQuuNAkKbT7oC68E0TUAIbQ4KCCGE0BajgBBCCG0xCgghhNAWo4AQQghtMQoIrb3pdBqPxy8vLxVFAYQQulEUEFpvnuf1+33btkulEiCE0E2jgNB6azabhJDZbLZYLOLxOCCE0I2igNAam0wmtVrNcRxd1w3DAIQQumkUEFpjqqoCQD6fB4QQej4oIIQQQluMAkIIIbTFKCCEEEJbjAJCCCG0xSgghBBCW4wCQgghtMUoIIQQQluMAkIIIbTFKCCEEEJbjAJCCCG0xSgghBBCW4wCQgghtMUoIIQQQluMAkIIIbTFKCCEEEJbjAJCCCG0xSgghBBCW4wCQgghtMUoIIQQQluMAkIIIbTFKCCEEEJbjAJCCCG0xSgghBBCW4wCQgghtMUoIIQQQluMAkIIIbTFKCCEEEJbjAJCCCG0xSgghBBCW4wCQgghtMUoIIQQQluMAkIIIbTFKCCEEEJbjAJCCCG0xSgghBBCW4wCQgghtMUoIIQQQluMAkIIIbTFKCCEEEJbjAJCCCG0xSgghBBCW4wCQgghtMUoIIQQQluMAkIIIbTFKCCEEEJbjAJCCCG0xSgghBBCW4wCQgghtMUoIIQQQluMAkIIIbTFKCCEEEJbjAJCCCG0xSgghBBCW4wCQgghtMUoIIQQQluMAkIIIbTFKCCEEEJbjAJCCCG0xSgghBBCW4wCQgghtMUoIIQQQluMAkIIIbTFKCCEEEJbjAJCCCG0xSgghBBCW4wCQgghtMUoIIQQQluMAkIIIbTFKCCEEEJbjAJCCCG0xSgghBBCW4wCQgghtMUoIIQQQluMAkIIIbTFKCCEEEJb7H8Ad7uP8fnMn24AAAAASUVORK5CYII=", + "text/html": [ + "" ] }, "execution_count": 5, @@ -197,53 +195,27 @@ } ], "source": [ - "GT.num_nodes(mesh), GT.num_faces(mesh)" + "GLMakie.plot(Ω)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "where the latter array output by `num_faces` gathers information on the number of $0D$ (nodes), $1D$ (lines), $2D$ (triangles?), and $3D$ (tetrahedral?) faces. \n", - "\n", - "If you want, you can also access the position vectors $x_{i}=(x_1,x_2,x_3)$ of each node $i$ in the mesh:" + "Define the Dirichlet boundary $\\Gamma_{\\rm D}$:" ] }, { "cell_type": "code", "execution_count": 6, - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { "text/plain": [ - "7475-element Vector{StaticArraysCore.SVector{3, Float64}}:\n", - " [0.0, 0.0, 0.0]\n", - " [1.5, 0.0, 0.0]\n", - " [1.5, 1.0, 0.0]\n", - " [0.0, 1.0, 0.0]\n", - " [0.095, 0.2, 0.0]\n", - " [0.63, 0.2, 0.0]\n", - " [0.3625, 0.675, 0.0]\n", - " [0.58, 0.5, 0.0]\n", - " [0.94, 0.5, 0.0]\n", - " [0.94, 0.86, 0.0]\n", - " [0.58, 0.86, 0.0]\n", - " [1.0, 0.39, 0.0]\n", - " [1.38, 0.39, 0.0]\n", - " ⋮\n", - " [0.6139875445382094, 0.4291099956974653, 0.07620766137880404]\n", - " [1.018820603903195, 0.5835488719740961, 0.1178301433344384]\n", - " [1.468372621304459, 0.3167189270535148, 0.08909060159961962]\n", - " [0.1806463128669575, 0.05567344069086867, 0.121587118230767]\n", - " [0.7265068184253736, 0.06797205524672663, 0.1232031560754262]\n", - " [1.470041808060199, 0.7146914675810988, 0.06742882101485732]\n", - " [0.4065025834426161, 0.8576895536696636, 0.08533633828561348]\n", - " [0.4430988134021598, 0.6529389841406555, 0.1232060341691886]\n", - " [0.9322295533397462, 0.9286533831291607, 0.1210197504572378]\n", - " [1.049623143250591, 0.829259829515705, 0.1242986642343036]\n", - " [0.3580932193740206, 0.02808866532662774, 0.04155394970851191]\n", - " [0.2251334943566448, 0.5163151069021665, 0.02626007329870325]" + "GalerkinToolkit.PhysicalDomain(…)" ] }, "execution_count": 6, @@ -252,14 +224,7 @@ } ], "source": [ - "GT.node_coordinates(mesh)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Or, even access the node composition (in terms of node indexes) of all $3D$ faces:" + "Γd = GT.boundary(mesh;physical_names=[\"sides\"])" ] }, { @@ -269,34 +234,9 @@ "outputs": [ { "data": { - "text/plain": [ - "29160-element PartitionedArrays.JaggedArray{Int32, Int32}:\n", - " [776, 1429, 5550, 6016]\n", - " [1329, 5691, 5657, 6088]\n", - " [4756, 3588, 5682, 7070]\n", - " [4332, 5605, 5615, 5919]\n", - " [5656, 5912, 2862, 6808]\n", - " [5891, 5965, 1212, 6969]\n", - " [4866, 5702, 5607, 6073]\n", - " [1621, 1953, 1165, 5618]\n", - " [5414, 5887, 5340, 6945]\n", - " [5350, 5310, 5682, 6309]\n", - " [5249, 6207, 5864, 6509]\n", - " [1244, 5678, 5946, 6190]\n", - " [884, 5537, 6213, 7003]\n", - " ⋮\n", - " [6986, 3691, 4068, 4615]\n", - " [5061, 543, 3293, 4317]\n", - " [3293, 543, 5061, 3291]\n", - " [3293, 6072, 5061, 4317]\n", - " [5061, 6072, 3293, 3291]\n", - " [7130, 6683, 7038, 5486]\n", - " [7130, 2906, 6683, 2904]\n", - " [6683, 2906, 7130, 7038]\n", - " [7426, 6735, 6535, 4507]\n", - " [7426, 6535, 6735, 5858]\n", - " [5805, 4024, 4535, 5125]\n", - " [5805, 4535, 4024, 6788]" + "image/png": 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", + "text/html": [ + "" ] }, "execution_count": 7, @@ -305,151 +245,20 @@ } ], "source": [ - "GT.face_nodes(mesh,3)" + "GLMakie.plot(Γd)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Finally, we can also check the node composition of each physical $2D$ faces of the problem:" + "Define the Neumann boundary $\\Gamma_{\\rm N}$:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dict{String, Vector{Int32}} with 6 entries:\n", - " \"triangle\" => [5401, 5402, 5403, 5404, 5405, 5406, 5407, 5408, 5409, 5410 … …\n", - " \"bottom\" => [1, 2, 3, 4, 5, 6, 7, 8, 9, 10 … 3385, 3386, 3387, 3388, 3389…\n", - " \"circle\" => [6609, 6610, 6611, 6612, 6613, 6614, 6615, 6616, 6617, 6618 … …\n", - " \"top\" => [7053, 7054, 7055, 7056, 7057, 7058, 7059, 7060, 7061, 7062 … …\n", - " \"square\" => [6053, 6054, 6055, 6056, 6057, 6058, 6059, 6060, 6061, 6062 … …\n", - " \"sides\" => [3395, 3396, 3397, 3398, 3399, 3400, 3401, 3402, 3403, 3404 … …" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "GT.physical_faces(mesh,2)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Computational domains\n", - "\n", - "The discretization of the computational domain. Instantiation of `PhysicalDomain`." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "GalerkinToolkit.PhysicalDomain(…)" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Ω = GT.interior(mesh;physical_names=[\"volume\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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oPB5rmoYpxpg1tb29HYZho9EAIITI5/PpdBqEvJ04CCGvZjAYeJ4XBEE+n19YWDBNE7uYTCbdbrfVag0GAyHE8vKyrutSol5HrYYzZxBFkBK3NCkhJXNd9r73qaur+JM/CR94wMxkOK7CORdTg8HA9/3nnnvOMAwhRC6XS6VSo9GIc46XS6fT5XJ5Zmam1+v5vt9sNi3LEkKYpskYAyFvAw5CyFU8z+t2uwsLC91u1/O8wWAghFheXtZ1HbvY2dlpt9utViuOYyHE/Py8qqpSol5HrQbXhZTYY6REvY7jx+0jRya/8zv+8eMZx8moKq5mTJXL5Xa7vbm52Wg0hBCDwSCfz+NaGGPW1Pb2dhiGjUYDgBDCtm1N00DIW4qDEHKVOI7DMByNRnEcFwqFhYUFzjl2IaUMgsDzPM55sVi0bZsxJiXqddRqcF1IiT1MSpw6pbiu0HX83M/hc5/r3X+/kU4zXEVV1WKxWCgUer1eEATnz5+vVCrpdNo0TcYYriWdTpfL5ZmZmV6v5/t+s9nM5/OO45imyRgDIW8FDkLIFaIoCoLg4sWLURQdOHDAsizGGHYRRZE/lc1m5+bmcrmcoihS4nvfQ60G14WUSIjxGL0e6nU8/LB55Agef7z9yCMZy9JUFa+gKEoulzNNs9PpmKbZaDQURXEcx7ZtTdNwLYwxayqKojAMG42GoiiO49i2rWkagDAMNU0zDAOEvH4chJCpXq/n+34YhrZtz8/Pdzod27axi36/73leGIaO4ywuLhqGAUBKuC5qNbgupEQySYlTp3D6dF7XsbKCL3xheN99GVXFK8RxDGB2dlZV1W63GwRBs9m0bVsIkc1mFUXBtei6XqlUSqVSt9sNgqDZbObzecdxgiDI5XKGYYCQ14+DkGSL47jT6fi+PxwOhRDLy8u6rvd6vTAMcZU4jrvdrud5w+FQCHH48OF0Oi0lul2cOIG1NbgupASRElKiXsf73pdZXcVnPtN54IGsrqfwop2dnclkkkqlGGP5qSiKgiC4cOGCqqqO49i2zTnHtTDG8lNRFIVheOnSpY2NjYMHD1qWpWkaCHmdOAhJqvF4HIah53kACoXCwsIC5xxTjLHJZBLHMWMMUzs7O2EYep4Xx3GhUFhYWOCcS4l6HbUazpxBFEFKkFeQEvU6PvAB68iRySc+ER4/rtu2rqoYj8epVIoxhhfpuj47O1sqlTqdju/7zWbTmTIMA7vQdb1SqRQKhW63K6X80Y9+ZNu24zjZbJYxBkJeGw5CkieKIt/3gyDIZDLlctmyLMYYrsAYi+MYU6PRKAgCz/M0TZuZmcnn84wxKVGvo1aD60JKkOuTEqdOKadP27qOlRX81/86uPNOqaoqYwwvl0qlnKnBYOD7/rlz53RdF0JYlpVKpXAtk8nEMIzFxcXxeByG4cWLF1OplD2laRoIeTUchCRJr9fzfT8MQ9u2Dxw4kM1mcS2MsclkMhgM2u12EASmac7Pz5umqSiKlPje91CrwXUhJchrJyWkRL2Of/fvjLvv3vnIR4L/8B/GpslVFVczpiqVShiGW1tbGxsbzpSu63i50WjEOU+lUpzzSqVSKpU6nU4QBM1m07Ztx3Gy2SxjDITsgoOQBIjjuNPpeJ63vb0thDh8+HA6ncbu+v3+1tbWeDwuFouLi4uGYQCQEq6LWg2uCylB3jAp8f3vp37wg/3/5b8oKytYW4vuvVdXVVyNc14sFguFQr/f933/7NmzlmU5jpPL5RhjmBqNRpqmKYqCKcaYPRVFURiGFy9eTKVSjuPk83lN00DIVTgI2dOklGEYep7HGBNC2LbNOccu4jjudDqe5w0GA8750tKSaZpSotvFiRNYW4PrQkqQt8R4rHS7qNfx0EP66io+97nu/fdn02mGqyiKYk5VKpUwDJvN5sbGhhDCtm1N00ajUTqdxlV0Xa9UKqVSqdPpBEHQbDbz+bwQIpvNKooCQl7EQcgeFUWRP2UYxuzsbC6XY4xhF+PxOAxD3/fjOC4Wi/v27XvmmWcAtV5HrYYzZxBFkBLk7SAl6nU8/HDuyBE8/nj7kUcylqWpKq6maVqpVCoWi71ez/f9ZrNp2/ZgMBBCYBeMMXsqiqIwDJ9//vlUKuU4Tj6f1zQNhAAchOw5vV7P87x2u+04zuLiomEY2N1oNPKnNE0rlUqWZTHGtrfjH/4w+/GPaz/4AaQEeQdIiVOncPp0XtexsoIvfGF4330ZVcXVGGPWVBRFYRg+++yzURQxxvL5vKqq2IWu65VKpVQqdTod3/ebzWY+nxdCZLNZRVFAEoyDkL0ijuN2u+153mg0EkLcfvvtmqZhd8Ph0PO8IAhyudzCwoJpmgCkxPe+h09+krnugfFYAXlnSQkpUa/jfe/LrK7iM5/p3H+/kclwXIuu66VSqdVqFYvFTqfTbDZt2xZCGIaBXTDG7KkoioIguHDhAudcCGFZlqZpmBqPx5xzkMTgIOTWJ6UMgsD3fcZYoVDI5/Occ+yu1+u1Wq1ut+s4ztLSUiaTASAlXBe1GlwXUgJQQG4cKVGv4wMfsI4cmXziE+Hx47pt66qKVxiPx3EcF4tFzvlwOPR9/7nnntN1XQhhWRbnHLvQdX12drZUKnW7Xd/3NzY28vm8ECKbzTYaDV3XS6USSDJwEHIri6LInzIMo1qtmqbJGMMu4jjudDqtVms0GgkhqtWqpmlSotvFiRNYW4PrQkqQm4eUOHVKOX3a1nWsrODzn+/fd18mnWZ4kZRS07RUKgUgk8nMzc2Vy+V2u+37frPZtG1bCKHrOnaRSqXsqSiKgiC4cOEC57zT6Rw4cAAkMTgIuQVNJpNer+d5XrfbdRxncXHRMAzsbjweh2HoeZ6iKEII27Y551KiXkethjNnEEWQEuTmJCWkRL2O978/e+QInnii88gjhmlyVcVoNNI0TVEUvIhzXigUhBD9fj8IgmeeecY0TSFELpdjjGEXuq7Pzs6WSqUwDC9evHjhwoXhcOg4TjabVRQFZE/jIOSWEsdxGIa+749GIyFEtVrVNA27G41G/lQ6nS6Xy5ZlMcakRL2OWg2uCymRHKoKXUcUQUrciqTEqVM4fdrSdaysYG0tOnRopGkarqIoijlVLpfDMGw2mxsbG47j2LadTqexi1Qqlc1my+Xy/v37O53OhQsXOOdCiHw+r6oqyB7FQcgtYjQahWHo+z5jrFgs5vP5VCqF3Q0GA38qn88vLCyYpglASnzve6jV4LqQEsmhqjhyZPLUU8ptt8lvfav38Y87UuIWJSWkRL2Ohx7S77wz9cd/fHlmJk6nGa5F07RSqVQsFnu9nu/7ly9fzufzQohsNssYw1WiKEqn0+ZUuVzudru+7zebzXw+7zhONptVFAVkb+Eg5KY3HA49zwvD0DTNarWay+UURcEuJpNJr9fzPK/X6zmOs7y8rOs6ACnhuqjV4LqQEsmhqjhyBE89hbvu2ul2/Y2Nrfe8J/tzP2f84Adp3OKkhOuqjz46t7qqPP54+5FHMpalqSquxhizpqIoCsPw4sWLqVRKCJHP51VVxRWiKNJ1HVOpVMqeGg6HQRBcuHBBVVXHcfL5vKqqIHsFByE3q8lk0u12fd/vdruO4ywuLhqGgd3FcdzpdFqt1mg0KhQK1WpV0zQAUsJ1UavBdSElkkNVceQInnoK99wTd7v+uXObuq7v37/fNM1vfhNHj+LSJewB47Fy6hROn87rOlZW8IUvDO+7L6OquCZd1yuVSqlU6nQ6vu83m03bth3HyWazmIqiyDRNvFxmqlQqdbvdIAiazaY9lc1mFUUBucVxEHLz2dnZabfbnueNx2MhRLVa1TQNuxuPx2EYtlotxlihUMjn85xzKdHt4sQJrK3BdSElkkNVsbqKJ5/EPffE/X547twm53zfvn2WZWFqbg7r63jgAUiJvUFKSIl6He97X2Z1FU880Tt+XDdNrqq4GmPMnhoOh0EQnD9/Pp1OCyFyuVwURcViEdfCOXemBoNBGIYXLlxQVdVxnHw+r6oqyC2Lg5CbyWg0CoLA933OeaFQyOfzqVQKu9ve3g6CwPO8TCYzOztrWZaiKFKiXkethjNnEEWQEokyN4f1dRw5MhkM2j/96SaASqWSz+cVRcEVVlexuop6HXuMlKjX4bqmrmNlBX/6p6P3vEdTVVxTZqpUKnU6Hd/3L168GIZhtVrFdRlTpVKp0+kEQdBsNm3bdhwnm82C3II4CLk5DIdDz/OCIMjlcvv27TNNU1EU7G4wGHieFwSBbdv79+83TROAlHBd1GpwXUiJpFFV3H33zv/8n6lcrnPhwuZ4PC6VSrZtM8ZwFVXF+jqOHsWlS9h7pISUqNfx3vdqq6v4/Of7992XSacZroVzLqZarVan0zl//rxpmkIIy7IYY9gF51xMDQaDMAx/+tOfappmT3HOQW4dHITcUJPJpNvtep7X7/cdx1laWspkMtjdZDLpdrue5/X7fSHE8vKyrusApITrolaD60JKJI2q4p574i9+kS0vD4Ngs92OZmZmhBCpVAq7m5tDvY6jR3HpEvYqKVGv4/3vzx45giee6Bw/nsnlVFXFNTHGqtXqvn37Op3O5ubmxsaG4zi2beu6jt0ZU6VSqdPpBEHQbDZt23YcJ5vN4kWTyURRFJCbEgchN8h4PO50Oq1WK45jIcS+fftUVcXu4jgOw9D3fSlloVCYm5vTNA2AlHBd1GpwXUiJpFFV3HNP/MUvsttvj4Jg89Kl3szMzMLCAuccr8HcHNbX8cADkBJ7mJQ4dQqnT1u6jpUVrK1F996rqypeIYoiXdc1TSsWi0KIXq8XBMHZs2ctyxJCmKbJGMMuOOdiajAYhGF4/vz5dDrtOE4+n+ecX7hwwTCMmZkZkJsPByHvuNFo5Pt+EASqqhaLRdu2GWPY3Xg89qcYY8ViMZ/Pp1IpKdHt4sQJrK3BdSElkkZVcc89ky9+UVlZGYXh1oULYbFYrFarmqbh9Vhdxeoq6nXseVJCStTreOghfXUVn/tc9/77s+k0w4uiKLJtG1OMMWtqe3s7DMNGo6EoihAin89rmobdGVOlUqnT6QRBsLGxYdt2EASFQgHkpsRByNssjmPGGKYGg4Hv+0EQ5HK5+fn5bDarKAp2F0WRP2UYRrVaNU2TMSYlvv991Go4cwZRBCmRNKqKI0cmTz2l3HGHDMOtc+c8IcTy8nI6ncbrp6pYX8fRo7h0CQkhJep1PPxw7sgRPP54+MgjhmVpnE+iKNJ1HS+XTqfL5fLMzEyn0/F9v9ls2rbtOE42m1UUBbvgnIupwWCwubm5sbGRyWRmZmYsy+Kcg9xMOAh5OzUaDQCVSqXX67VarcFgIIS47bbbdF3HdQ0Gg1arFYahbdsHDx7MZrMApMT3vodaDa4LKZFAqoojRyZPPaXceee40/HOnWtZlrW8vKzrOt6EuTmsr+OBByAlkkNKnDqF06dtXcfKCj7zmW6hsKNpGq6FMWZPRVEUBMGFCxc0TXMcJ5/Pc86xO8MwhBAHDx6cmZnxfb/RaNi2LYQwDAPk5sBByNuJc95sNnu9XhzHhUJhfn5eVVXsbjKZdLvdVqs1GAyEEMvLy7quA5ASrotaDa4LKZFAqoojR/DUU7jrrp1u1z93biubzS4uLhqGgbfC6ipWV1GvI2mkhJSo1/GBD1i3337oP/2n4SOPZEyTqyquSdf12dnZmZmZTqfj+36z2XQcx7ZtwzCwi8FgYJqmmBoMBkEQnDt3Lp1OCyEsy+Kcg9xQHIS8Pba3t4MguHjx4mAwuOuuuyzLYoxhdzs7O+122/O8nZ0dIcT8/LyqqgCkhOuiVoPrQkok1q/9Gh57bKIo4Q9/eFnX9X379juOibeOqmJ9HUeP4tIlJJOU+Nd/NX7rt6DrWFnBn/7p6D3v0VQV18Q5F1ODwcD3/eeee84wDCFELpdLpVJ4ucFgYNs2poypcrnc6XR83280Gs6UYRggNwgHIW+1wWDgeV4QBPl8/sCBA5ubm5ZlMcawCyllEAS+76dSqUKhYNs2YwyAlHBd1GpwXUiJhPvqV/G3f6tMJvZkkp+Z2XnwQdx7L/bvxwuOHcMn2neIAAAgAElEQVTP6DpUFW/Y3BzW1/HAA5ASiSUlpES9jve+V1tdxec/37/vvkw6zbALY6pcLrfb7c3NzUajIYSwbVvXdUzFcTwcDmdnZ3EFzrmYGgwGvu8/99xzuq4LISzL4pyDvLM4CHmLxHHc7XY9zxsMBkKI5eVlXdfH43Gj0djZ2WGM4SpRFPlT2Wy2Wq3mcjlFUaREv48TJ7C2BteFlCAvkBJSAlAApd9nTz+NL38Zuo6XHDuG/fvx7ndj/3684Ngx/IyuQ1XxGq2uYnUV9TqIlKjX8f73Z48cwe/+buf4cd2yNFXFNamqWiwWC4VCv9/3ff/s2bOWZQkhTNPc3t4GkE6ncS3GVKVS6XQ6vu9vbGzYtu04jmEYIO8UDkLetPF4HIah7/txHBcKhYWFBc45phhjnPPxeKyqKq7Q7/c9zwvD0HGcxcVFwzAASAnXRa2GM2cQRZAS5DqkhJR4ybe/jRc8/TR0HS85dgz79+Pd78b+/XjBsWP4GV2HquJqqor1dfzbf4tGA+QFUuLUKZw+bek6Vlawthbde6+uqrgmRVHMqUqlEoZho9EAkEqlVFVljGF3nHMxNRgMfN8HeWdxEPImbG9v+74fBEE6nS6VSpZlMcZwBcaYpmlSykwmA2AymXS73VarNRwOhRDLy8u6rgOQEq6LWg2uCylB3jApISVe8u1v4wVPPw1dx0uOHcP+/Xj3u6EoWFjAsWP4GV2HqmJuDl/72s6DD6akBPkZKSEl6nU89JC+uorf+73e8eOZbDalqrgmTdNKpVKxWOx2u2fPno2iSNd1IUQ2m1UUBbszpkDeWRyEvCH9ft/zvDAMbdteWFgwTRO7UFV1NBrt7Oy02+1WqxXHcaFQWFhY4JwDkBKui1oNrgspQd4OUkJKvOTb38YLnn4auo6XHDuG/fvx8Y/H1Wr7X/6lN5nsAxSQl5MS9Tpc19R1rKzgr/96dPCghl0wxvJT+/fv39nZuXDhgqqqjuPYts05B7lpcBDyesRx3Ol0fN8fDoeO4ywvL+u6jutSFKXZbG5tbamqOjMzk8/nGWMApITrolaD60JKkHeYlJASL/n2t/GCp59m6bQdRfZ4rIDsQkpIiXodf/zHo89+9nKp5GSzWUVRcJXxeBxFkW3bmqaVSqVOp+P7frPZtG1bCGEYBshNgIOQ12Y8Hodh6HkegEKhsLCwwDnHdUVR5Pv+pUuXFEVZWVnJ5XKKokiJfh8nTmBtDa4LKUFuHlJCSgXktfnudzNx3L9w4YKqqkKIfD7POccVoijSNE1VVQCpVMqZGgwGvu+fO3dO13UhhGVZqVQK5MbhIOTVRFHk+34QBJlMplwuW5bFGMN19Xo93/fDMBRCHDp0KAxDy7KkhOuiVsOZM4giSAlCbmmtVqpcLhtGsd1u+77fbDadqUwmg6nhcJjJZBRFwRWMqUqlEoZhq9Xa2NhwpnRdB7kROAjZXa/X830/DEPbtg8cOJDNZnFdcRx3Oh3f94fDYaFQOHz4cDqdjqJoY6P13e/Gv//7zHUhJQjZGyoVvCCVSompfr8fBMGzzz5rmqYQIpfLDQYDwzBwLZzzYrFYKBT6/b7v+2fPnrUsy3GcXC7HGAN5B3EQcpU4jjudjud529vbQojDhw+n02lc13g8brfbnufFcVwsFhcWFjjnAKSE66qPP37w//5fJiUI2UsefBC6jpdkp0qlUhiGzWZzY2Oj3W4fPnwYu1MUxZyqVCphGA6Hw3w+D/LO4iDkClLKMAw9z2OMCSFs2+ac47pGo1EQBJ7naZpWKpUsy2KMAZASrotaDa6bkjIDQvYWVcW73w1VxStomlYqlYrFoud5jUbj/PnzxWLRcZxsNovdaZpWKpXiOAZ5x3EQMhVFkT9lGMbs7Gwul2OM4bqGw6HneWEYmqY5Pz+fy+UwJSVcF7UaXBdSgpA9SdfxC78QAwzXwhjTNG1+fn5ubi4Mw/Pnz6fT6UKhYFlWKpXCLhhjIO84DpJ4vV7P87x2u+04zuLiomEYeDW9Xq/VanW7XcdxDh06lMlkAEiJKMKJE1hbg+tCShCyh8VxfP78eSFytm2rqoqrDIfDTCZjTJVKpXa7vbW1tbGxIYSwbVvXdZCbAwdJqjiO2+2253mj0UgIcfvtt2uahuuK47jT6Xiet729LYSoVquapgGQEq6LWg1nziCKICUI2fOKxZ1yedLtdi9fvmzbthDCMAxcYTAY2LaNKc55oVAQQvT7fd/3z549m8/nhRCmaSqKAnJDcZDkkVIGQeD7PmOsUCjk83nOOa5rPB6HYeh5HoBCoWDbNuccgJRwXdRqcF1ICUKSo9X6/371Vz/56KO/8qEPfQjAc889ZxhGoVCwLEtRlDiOh8NhtVrFFRRFMafK5XIQBBcvXkylUkII27Y55yA3CAdJkiiK/CnDMKrVqmmajDFc12g08qc0TSuXy5ZlMcYASAnXRa0G14WUICRROJ/8x/8422qt/tmf/dmf//mfHz9+/Nd//dfvvPPOjY2NZrNZKBQ0TVMURdM0XEs6na5UKjMzM51Ox/f9ZrMphLBt2zAMkHccB0mAyWTS6/U8z+t2u47jLC4uGoaBVzMYDHzfD4Igl8stLCyYpokpKeG6qNXgupAShCRQJqP83u/dsbT0l//yL//y13/911/72te+8pWv3H///R/96EcffPDBTqezubnJGNve3s5kMthFKpVypgaDge/7uq6D3AgcZE+L4zgMQ9/3R6OREKJarWqahlfT7XY9z+t2u47jLC0tZTIZAFIiinDiBNbW4LqQEoQknKIod0998pOf/MY3vvHlL3/5t3/7tw8fPvzoo4/ed999MzMzP/nJT7LZbKFQME2TMYZdGFMgNwgH2aNGo1EYhr7vM8aKxaJlWZxzXFccx51Op9VqjUYjIUS1WtU0DYCUcF3UajhzBlEEKUFIwlUqqFTwkmq1+sQTT/zmb/7miRMnvvSlLz311FPf+ta37r777kcfffRd73pXo9FgjAkhbNvmnIPcZDjInjMcDn3fD4LANM1qtZrL5RRFwXWNx+MwDFutFmOsUCjk83nOOQAp4bqo1eC6kBKEkJ+54w7oOl7BMIwPfvCDv/ALv/AP//APJ0+e/OY3v/kXf/EXDz744G/8xm888MADnU6n2WwKIRzHyWQyIDcNDrJXTCaTbrfr+36323UcZ3Fx0TAMvJrt7e0gCHzf13W9UqlYlsUYAyAlXBe1GlwXUoIQ8hJVxcMPQ1XxCnEcX7582fO8Bx988Fd+5Vc+9alPra+v/9Vf/dXHPvaxO++887HHHvvgBz8Yx/Gzzz6by+WEEKZpMsZAbjQOcuvb2dlpt9ue543HYyFEtVrVNA2vZjAY+FO2bS8sLJimiSkp4bqo1eC6kBKEkFfQdTz4IF4hiqJLly4BWFpa0nUdwMLCwqc+9anf+q3f+ru/+7svfelLn/3sZ7/4xS/+8i//8mOPPVYsFhuNBmNMCGHbNucc5MbhILey0WgUBIHv+5zzQqGQz+dTqRSuazKZdLtd3/d7vZ4QYnl5Wdd1AFIiinDiBNbW4LqQEoSQ18j3/UajUSgUyuUyYwxXyOVyv/qrv/qhD32oXq9/+ctf/sY3vvH000//4i/+4kc/+tFjx4612+1msymEqFarIDcIB7k1DQYD3/eDIMjlcvv27TNNU1EUXFccx+122/O80WhULBar1aqmaQCkhOuiVsOZM4giSAlCyHVUKqhU8DPj8bjZbHY6nfn5+Xw+j12kUql7p/7gD/7ga1/72le+8pXHHntsdXX1Ix/5yC/90i85jgNy43CQW8pkMul2u57n9ft9x3GWlpYymQxezXg8DoLA8zzGWLFYzOfzqVQKgJRwXdRqcF1ICULIa3HHHdB1vKDf71+6dEnTtKWlJU3T8BocOnToD//wDz/xiU9861vf+tKXvvRHf/RH//2///e///u/P3z4MMgNwkFuEePxuNPptFqtOI6FEHNzc5qm4dVsb2/7U5lMZnZ2NpfLMcYASAnXRa0G14WUIIS8RqqKT38aqoqtra2NjY1KpTIzM6MoCl4P27Y/8pGP/Nqv/do//dM//eVf/uXhw4dBbhwOctMbjUa+7wdBoKpqsVi0bZsxhlczGAw8zwuCwLbtAwcOZLNZTEkJ10WtBteFlCCEvHacT44d699xh/bTn25EUbS4uGiaJt4ozvn/MwVyQ3GQm9hgMPCnLMuan5/PZrOKouC6JpNJt9v1PK/f7wshlpeXdV3HlJRwXdRqcF1ICULI6zI3h7W1n9x5p3zmmW0hxKFDhzjnILc+DnLzieO41+u1Wq3BYOA4zvLysq7reDVxHIdh6HneeDwuFAr79u1TVRWAlIginDiBtTW4LqQEIeT1qlYn3/nOZDLRLlxoqqoqpez1epZlMcZAbnEc5Ebr9XqDwaBUKgEYj8ftdtvzvDiOhRDz8/OqquLVSCmDIPB9P5VKFQqFfD6fSqUASAnXRa2GM2cQRZAShJDXS1Vx113jr351R8pLcRz//M//vKqqYRhevnx5c3NTCGHbNucc5JbFQW40xlir1crlcu122/d9TdNKpZJlWYwxvJooivwpwzCq1Woul1MUBYCUcF3UanBdSAmytykKJhOQt0O1ir/5Gxw82N3aajiOU6lUGGMAisWiEKLT6bRarc3NTTGlaRrILYiD3Gg7OzutVmswGMzMzCwsLJimideg3+97nheGoW3bi4uLhmFgSkq4Lmo1uC6kBNnbVBWrq/jYx/C5z+HSJZC3VrU6+ed/3uH8cqvVnpubs20bV2CM2VO9Xq/Vav34xz92HEcIYRgGyC2Fg9wgcRx3u13P8waDQSaTmZubm52dxauJ47jX67VareFw6DjO8vKyruuYkhKui1oNrgspQfY2VcXqKj79aRw/DlXFBz+ID38YrgspQd48VcWdd47/x/+Q29vPx7F66NChdDqNXZhTw+HQ87znnnvONM1CoWCapqIoILcCDvKOG4/HYRj6vh/HcaFQWFhY8DxvNBrhunZ2dtrtdqvViuNYCLGwsMA5ByAloggnTmBtDa4LKUH2vLk5rK9jdRWqip+Zm8PJk3Bd1GpwXUgJ8oZVq/ibv8HCQri11ahUKjMzM4qi4NVkMpl9+/aVSqUgCJ5//nlN0wqFQj6fZ4yB3Nw4yDsoiqJgKp1Ol0oly7IYYwAMwwiCYDKZKIqCq4xGozAMPc9TVbVYLNq2zRgDICVcF7UazpxBFEFKkD1PVbG6ivV1zM3hFVQVR4/i5Em4Lmo1uC6kBHldVBV3373zta/FjG2024PFxUXTNPF6aJpWLpcLhUK73d7a2ppMJkIIkJsbB3lH9Pt9z/PCMLRte2FhwTRNXCGTyYxGIymlpmm4QhRF/lQ2m52bm8vlcoqiAJASrotaDa4LKUGSQFWxuoonn8TqKlQVu1FVHD2KkyfhuqjV4LqQEuS1mJvD+jpuu22wuXnJMIylpSXOOd4QznmhUHAcZzKZgNz0OMjbKY7jTqfj+/5wOHQcZ3l5Wdd1XIVzbhjGYDDQNA1TvV7P9/0wDB3HWVxcNAwDU1LCdVGrwXUhJUgSqCpWV/Hkk1hdharitVBVHD2KkyfhuqjV4LqQEuQ6qtXJd74z0bStS5c2Z2dni8Ui3jTGGK7QbDaz2azneQcOHAC5mXCQt8d4PA7D0PM8AIVCYWFhgXOO3RmGMRgMLMvqdrue5w2HQyHE4cOH0+k0pqSE66JWg+tCSpCEmJvD+jpWV6GqeL1UFUeP4uRJuC4+/GFcugRyNVXFXXftfPWrYykvbW/Hhw4dMgwDb4OdnZ1z58612+2NjY0777zTNE2QmwMHeatFUeT7fhAEmUymXC5blsUYw6vRdf38+fO9Xi+O42KxuLCwwDnHlJRwXdRqcF1ICZIQqorVVayvY24Ob4aq4uhRfOc78SOPjM6c0aUEecncHNbXsbjY3dpq2LZdLpdTqRTeHnNTZ86c2b9/fzabBblpcJC3Tq/X830/DEPbtg8cOJDNZvEaSCl93798+bLv+/Pz84VCgTGGF0mJD30I3/42pARJCFXF6iqefBKrq1BVvHm9Xm80uvxXfxU3m9U/+qOs60JKJJyq4p574q9/fcL55a2tsFqt2raNt9/KygrITYaDvGlxHHc6Hc/ztre3hRCHDx9Op9N4DaIo8jwvCALTNA8cOKBpmq7rjDG8XKsFKUESYm4O6+tYXYWq4s2TUm5tbXmeVy6XDx4srqywkyfhuqjV4LqQEsk0N4f1ddx+e7S11RiP2eLioq7rIEnFQd4EKWUYhp7nMcYKhUI+n+ec4zXo9Xqe57XbbSHE4uKiYRgA2u12v9/P5XK4gqri05/Go49CSpC9TVWxuor1dczN4S3h+36z2TQM47bbbtN1HVOqiqNHcfIkXBe1GlwXUiJRqlXU69B178KFxszMTKlUYoyBJBgHeaMajYbv+4ZhzM7O5nI5xhheTRzHnU7H87zt7W0hxO23365pGl6UzWbDMMRVbrttW9fTUoLsVaqK1VU8+SRWV6GqePMGg0Gz2RyNRtVq1bZtXEVVcfQoTp6E66JWg+tCSux5qoq77975+tcnOzuNra3B/v37LcsCSTwO8kaZpmnbtmEYeA3G43EYhr7vTyaTQqFg2zbnHC9nGEaj0djZ2UmlUpgaDAatVqvb7cTxCsBA9hxVxeoqnnwSq6tQVbx54/G41Wptbm6WSqWFhQXOOXanqjh6FCdPwnXx4Q/j0iXsYXNzWF/H8vLw8uWLhmEcOnRIVVUQAnCQN8qyLLwGo9HIn9I0rVQqWZbFGMO1aJrGGNve3jYMo9PpeJ7X7/eFEHfcsfTe907+9m9B9pi5OayvY3UVqoq3RBiGzWZT07SlpSXDMPDaqCqOHkW9jg9/GK4LKbH3VKuT734Xmrb1/PPNarVaLBZByIs4yHUNh8NMJoM3ZDgcep4XBEEul1tYWDBNE9fFGMtkMs1mM47j0WhULBb37dunqiqA48fxv/83pATZM1QV6+s4ehRviSiKLl++3O/3K5WK4ziKouB1mpvDyZNwXdRqcF1Iib1BVXHXXTtf/3os5cXBQC4tLRmGAUKuwEF2cfHiRQCWZWUyGbxOvV6v1Wp1u13HcZaWljKZDF7NeDxut9utViuKone96122bXPO8aIHH4SuQ0oknKpC13F9UQQpcUtotSAl/v/24Da2jfy+E/iXw/8Mh6MhORzxcYakJZKWd727Xol3WblOHATNpUDyJrhyk+aSQxCkfdUCORQFLmhRFAUuwCHtmxropS2SoNcgi0uQUE3vNtkiyTYtnLWXQaPzZh+zlmRb5AzJ4YMoSqJIDjW8PRcNkma9lm3ZJsXf58PzuBeO4zQaDcuygsHgyZMneZ7H3eJ5LC/j4kWsriKfh2Fg0uk6CgWk0zv1uun3+5PJJGMMhPwiBvJLBoPBzs7O5uamKIo+nw+H5jhOp9NpNBqDwUBVVU3TBEHA7di2vbW11Ww2eZ7Xdb3dbquqynEcph5jI49n5HJxLhdiMbzvfVhYgKLgLaqKxx6DpuFfmCZefRWtFt7SbuPNN/GP/4hqFf9ifx/DIcaNbeM//kfkcrhwAbkceB53odPpVKtVjuPm5uZkWcZR4HmcPo3//J/x+c9jcvE8FhedQgFud7VWa+m6HgwGQcjbYSC/pNvtNhoNxlgoFGKM4RCGw2G73W42my6XS1VVRVEYY7idfr/fbDa3trYkSdJ13efzOY7TarUGg4Eoivg5sRhiMezs4NjjeXg8o7e8+929c+e2Mhn25JP+uTkvAFEEz+NtnTqFU6fwM7aNXg9vqVaxtnbw6qs7X/+67/XXXf2+azh0YWzYNopFnD+PXA6FAnQdhzcYDGq12vb2diwWU1WV4zgcEcNAPo/VVUwuXUehgEcf7VuWwXFcNpsVRRGE3AID+SWiKAZuisViuJ3BYNC6yePxRKNRv9/PcRxup9vttm5SFGV+fl6SJNzkdrslSep2u6Io4ud4PKPHHnNdvYpjjOdx5szw93+fSyTaHGcpihiPh2RZxp3jefA83uLz4eRJ9wc/qPzmb+5ev14tFn1f+ILv2jVvv++ybYwJ20axiOVlFArI5cDzeGeO47RarVqt5vf7FxYWBEHAEbFtrK4in4dhYHJpGopFeL2tzU0zFApFIhGO40DIrTGQXyKKYiwWw+F0Op1+v59KpWRZxiHs7u42Go3d3d1gMLiwsCCKIn6RJEndbldVVdzkOE6n02k0Gr/6q+Kzz+rDoQvHC89DFLGwMPzzP+fm5rbb7TrP8+Gw5vf7cXSCQTkQSMfj1lNPrQcC0ZdeCv/3/+689JLbtjEmDAPnzyOXw4ULyOXA83hbu7u71WrVcZxkMun3+3F0DAP5PFZXYduYUDyPJ588+OY3R45TqdV2U6mU3+8HIbfDQO6NoiihUAi34zjOzs5Oo9Ho9/uqqmqaJggC3o4kSZVKZXRTu91uNBqj0SgYDCrKuiDEh0M3jgueRy6Hz34W73//qNfbabfrnQ5isVggEHC5XDhqHMfFYjG/32+a5hNPbH/3u/E335Q/85nR//2/LtvGOLBtFIs4fx65HAoF6Dp+3nA4tCyr2WxGo9FQKMRxHI6IbWN1Ffk8DAOTS9dRKGBhYb9eNwVByGQygiCAkENgIPeGMYZ35DhOu91uNBqO44RCIUVRGGO4Na/Xu7+/X61Wt7e33W63oij//M///OUvf/m55y7u728AMiYfzyOXw4ULyOWwv9+xLOvg4CAcDgeDQZfLhftJkqRMJlOv18vla8nk7D/+Y+QnP2H5PAwDY8K2USxieRmFAnI58Dze0mq1qtWqJEknT54URRFHxzCQz2N1FbaNyaVpoxdfhCDUS6VqPB4Ph8Mg5NAYyO2Uy+VoNMrzPO7QcDhs3eR2u0OhkKIoHMfhHdm23Wq1ms0mx3HRaPSHP/zhl770peeffz6dTv/BH/ze//pf5muvLWCS8TxyOVy4gFwO/f7u5mZtMBiEw2FVVTmOwwPhcrkikYjf769UKjdurD36qFYs+p96amSaLowNw8D588jl8PnP9zStenDQ0zRNURQcHdvG6iryeRgGJhfP48knD77xDWc4NLrdQSaTmZmZASF3goHcWqPRcByn1WpJkqSqKg5tMBi0Wq1ms+n1ejVN8/l8LpcL72gwGDRvmpmZCYVCly5d+trXvnbx4sUnnnjiT//0Tz/2sY9F/z/8zu/AtjGhdB2FAnI5DAZ7hlHf29sLh8OqqjLG8MCJojg/P99qtUqlUiAQeOaZ2V/7Na9tY3zYNopFfOAD4mOPxb/1LbeiMBwR28bqKv7Lf8HqKmwbk0vXUSggm92r1cp+vz+ZTLrdbhByhxjILQyHw5/+9Kcul4sx5vF4hsMhYwy3s7+/32w2t7a2/H7/iRMnZFnG7fR6vUajsbW1FQgEFEX5zne+88wzz9Tr9dnZ2b/8y7/M5/OqquKm970PogjbxiTStFGx6FLV/Uql3ul0QqGQrus8z+OhUlVVFMU333zzpZdKo9FZwIUxY9u4csVz7hxWVpDLgedxjwwD+TxWV2HbmFw8j8VFp1AAY7VKpalpmqqqIOSuMJBb6HQ6Pp8vFAr1er2ZmRnczu7ubqvVarfbqqpms1mv14vb6Xa7jUaj3W6rqurz+VZWVv76r//61Vdffe973/u7v/u7i4uLp06d8vv9mHA8j8cfH3zzm6PRqH71amt2dnZhYUEQBDxso9Foa2vLsqz9/eB/+2+PDIcujCvTxPnzyOVw4QJyOfA87oJtY3UV+TwMAxNN11Eo4PTpgWUZgwGy2awoiiDkbjGQW/D7/adOnfJ4PDgE0zS3trZmZ2cfeeQRQRBwO7u7u41GY3d3V1VVr9f7la985W/+5m+uXbv2gQ984I//+I8/+MEPiqLYarWuX7+uaVooFMJNsRhiMezsYILEYs43vnGQTDa2txuqqi4sLIiiiDGwu7tbrVb7fada1T/xCW+zyTDebBvFIs6fRy6HQgG6jjtiGMjnsboK28ZE0zQUi/B6WzdumLOzs9FolOM4EHIPGMgtsJtwOKqqRiIRxhje0Wg02tnZaTQavV5PVdVut/uFL3zhq1/9qmVZH/rQhy5cuPD+97+f53ncpKqqIAjlcrnX62maxnGcKOLxx3H1KiZFJDJ87rkWYxbgy2azkiRhDPR6PcuydnZ2hsPoJz8pv/66aNuYFLaNYhHLyygUkMuB53Fbto3VVeTzMAxMNJ7Hk0863/ymMxpVq9VOKpXy+/0g5J4xkKMgiiLekeM4nU6n0WjYtj07O7u9vf35z3/+61//+t7e3oc//OHf+q3fes973sNxHH6RLMvpdLpcLl+/fj2RSAiC8NnP4tlnYdsYf9Ho8Gtf2wgE+HB4TpZljIHhcFi/ye+f3dpa+OhH3ZUKhwlkGDh/HrkcLlxALgeex60YBvJ5rK7CtjHRdB2FAk6d2rcsQxCEbDYrCAIIOQoM5NC63a4kSbhDjuO02+1GozEajWZnZ9fW1v7sz/6sUCgAePrppz/96U+/613vcrlcuAVBEObm5kzT3NjYSCaTudxMLodiEePvd35nK5eL+f1+jAHHcVqtlmVZgiBtbS186lPcK6/wto3JZdsoFnH+PHI5XLiAXA48j59n21hdRT4Pw8Ck07RRsegShPrmZiUWi4XDYZfLBUKOCAM5BMMw3G63KIqSJOHQhsNhu91uNBput3t2dvbll1/+3Oc+93d/93eyLH/yk5/81Kc+debMGRwCx3GJRKJer29sbCQSiUIh+O/+3bBWYxhv/+N/BH/t11guB57Hw9XpdGq1mm2jWj3xe7/HXn3VY9s4HmwbxSLOn0cuh0IBuo5/YRjI57G6CtvGRGNs9Nhj/W99y23bxt7eIJ1Oy7IMQo4UA3lHtm1vbW2Vy+X9/f1IJDIzM8PzPG7Htu1Wq9VsNj0eT7rE+lgAACAASURBVDgc/tGPfvTlL3/5O9/5TiQS+cxnPvPJT35yYWEBdygcDguCsLm5yfO1r33N/YlPnDRNjLNajZ0/j1wOFy4glwPP48HrdruWZXU6+9Vq/L/+V/G110TbxvFj2ygWsbyMQgGnT+O115DPwzAw6XQdn//8+tLSqNPZDwaD6XSaMQZCjhoDeUd7e3umaY5Go0Qi4ff7eZ7HO+r3+61Wq9lsyrIciUQuXrz4xS9+8fvf/346nf7DP/zDT3ziEydOnMBdGQ6Hg8HAcRzLsiKR0Asv2O9+NzNNF8aYbaNYxPnzyOVw4QJyOfA8HozBYFCpNEyz9frr+oUL0ddf99o2jjfDwPnzEEX0erBtTDSex+KiUyhgNBKuXbsmCEI4HHYcB4TcBwzkHSmKcvr06VqtlkwmcTvlcrnVaimKEg6Hv//973/pS1+6ePHi448//id/8icf+9jHYrEY7spwOGy1Wo1Gw+PxzM/Pi6JomuZweOPixeR73iNUKi6MN9tGsYjz55HL4bOfxX/4DxBF8Dzuk37fMc3W//k/3f/5P2Nvvhnr97nhEFPCtmHbmHS6jkIBp08P6nXTcZynnnpqNBpZlnX16tVwOKyqKmMMhBwdhqn34x//OJFIRKNR3IIgCMlkEoegKArHcd/+9re//OUv/+hHP3rqqaf+4i/+Ip/Pq6qKuzIcDlutVqPREEUxkUj4/X7clEqlarXa1tb6D36Q/PjHvS+/zGwbY862USziN34DoojTp/Gbv4n3vQ9vicUgiuB53DXbRq+HahVvee657jPPSK+9NtvrzQ6HLpBJo2koFiFJWzduGKqqxmIxjuMAzM3N7e7uWpbVbDbD4bCqqhzHgZCjwDDd6vX6888//653vatSqSwuLuLevPnmm5/+9Kdffvnl9773vV/5ylc+/OEP+3w+3BXbtlutVrPZFEUxmUz6fD78HI7j4vG4x+Mpl689+6y2uRnK52EYGH+2DdtGsYjVVYgi3hKL4fHHce4cFAVvUVW8JZnEzzzyCN7yxhv4mVIJb2m18JZ2G5cu4ZVXUK3iLb2eZNsAXCCThuexuOh84xvOaFStVDqJREJRFPwc+aZOp2NZVrPZjEQigUCA4zgQcm8Yplu/3z9z5oyiKPF4HPcsd9Mf/dEffehDHxJFEXdlMBhsbW01Gg1JklKplCzLuAVVVQVBKJVKyeTg8uXY2bMu03RhQtg2bBtv2dnB1at49lmIIu5CrwfbBpl0uo5CAY880qvVyjzPZzIZj8eDt+P3+2VZ3t7etiyr2WxGIhG/3w9C7gHDdEskEoyxWCyGw7EsS1EUQRBwC3/1V3/F8zzuymAwaLVajUZDluUTJ07IsozbkWU5nU6Xy2WOu/HCC4l3v5uZpgsTyLZh2yDTSdNQLMLjaWxuVqLRaDgcdrlcuDWO44LBYCAQaLVahmE0Go1IJCLLMgi5KwxTLxaL4RBqtRqAn/70p7Isnz59WhRFvB2e53HnBoNB8yZZlufn52dmZnBoHo9nbm6uUqns7W380z+lPvYx4Sc/cds2CBl/PI8nnzz4xjecg4NKo9Gdn5+XZRmHw3FcKBRSFKXVat24cWNmZiYSiUiSBELuEAM5hF6vV6/Xt7a2Zmdnw+GwKIo4IoPBoNFotFotn8+XTqclScKdc7vdiUTC+v/Wn3susbGh5PMwDBAyznQdhQKy2b163ZQkKZvNMsZwhxhjkUhEUZRms7m+vq4oSjQaFQQBhBwaAzkEURQXFhaq1WoqlcIR6ff7zZsCgUA6nZYkCfcmEokIglAul+fm+sVi9KmnYJogZAzxPBYXnUIBPG+ZZl3TtNnZWdwDQRDi8biqqu12WxAEEHInGMjhCIKQSqVwFHq9XvMmRVEymYwkSTgiiqJ4PJ5SqSSK/UuXtHPn3KbpAiHjRNdRKOD06UG9bvb7TiaTkSQJR8Hj8USjURByhxjIA9Tr9RqNRqvVCgaDJ0+e9Hq9OGper3d+ft4wjOHw+sWLyfPnBdN0gZDxoOsoFjEz0y6VTEVRotGo2+3GfVOv12VZrtfrqVQKhNwCA3kger1eo9FotVqqqi4sLIiiiPuG5/lUKlWtVtvt9X/4h9THPy6+/DKzbRDyEPE8Fhedb35z5HLVTLOtaZqiKLifer3eYDC4dOmSKIocxymKIssyCPklDOSBEEURwMLCgiiKuP84jtM0zePxGMbGs89qm5uhfB6GAUIeCl1HoYBHHunV6+ZwyKXTaVEUcZ+Joqjr+t7eniRJoijKsgxC3g4DeVASiQQerNnZWY/Hs7m5mUwOLl+OnT3LmSYIeZB4HktLo5UVlyg2NzfNSCQSDoc5jsODsrCwAELeEQM51mRZTqfThmG43ZsvvKD/yq9w1aobhDwQuo5CAWfOHNTrZr3enZub8/l8IGTMMJAj1ev1RFHEOBFFcW5uzjTNnZ2rf/u3vt/+7egrrwi2DULuK11HsYhAYPfGjbIkSZlMhud5EDJ+GMgRaTabV69ezWQyjuNIkoRxMhqNPB5PqVTq9ap/+7fualXL52EYIOR+4HksLo5WVsDz9Y2NqqZpoVAIhIwrBnLPer1e9Sa/399ut8PhMMaG4zitVqvRaPA8/8QTTxwcHJTL5fl59uKL4bNnXYYBQo6WrqNQwGOPDep1s9u1s9msJEkgZIwxkHsmimI0GpUkKRKJYGw4jrO9vV2v110uVzweDwQCuEkQhFKpJEn9S5e0X/kVzjRdIOSI6DqKRcjy9uamEQgEkskkYwyEjDcGchS8N2FsbG9vW5blOE44HFYUheM4/CtJkubn5w3DODi49sMfpt7zHt40XSDk3vA8FhedQgEuV7VUaum6HgwGQcgkYCDHy87OTr1eHwwGoVBIVVWO4/BLBEE4ceJEtVrd3l7/wQ9SH/+45yc/YbYNQu6OrqNQwKOP9i3L4Dgum82KoghCJgQDOS729vbq9Xq32w2FQqqqMsZwaxzHaZomCIJprn/724nr19V8HoYBQu4Iz2NpabSy4vJ6W5ubZigUikQiHMeBkMnBQCZft9ttNBqdTicUCiUSCcYYDicUCgmCUC6Xk8ne5cuxs2c50wQhh6TrKBRw5sxBo1GxrL1UKuX3+zEGrl27BmB+fh6EHAIDmWS9Xq/RaLRarVAotLCwIAgC7pDf70+n0+VymbHNS5cS5865TdMFQm5H11EsIhDY3dw0RFFMp9OCIGAMvPHGG4yxb33rW+duAiG3w0Am02AwaNykqurCwoIoirhboijOzc2ZptnrbfzTPyX/038SXnrJbdsg5G3xPBYXRysr4Pn6xkY1Ho+Hw2GMjUceeeTll19+4okn5ufnQcghMJBJMxwOGzf5/f5sNitJEu4ZYyyZTFqWVa+vP/dccn09kM/DMEDIv6HrKBTw+ON2vW52u4NMJjMzM4Mx88RNIORwGMjkGA6HrVar0WhIkjQ/Pz8zM4Oj43K5otGox+Mpl0vz8/1iMbK8DMMAIT+j6ygWIcvbN24Yfr8/kUgwxkDIhGMgk8BxnFar1Wg0BEFIJpM+nw/3h6IoPM+XSiVZHly+rJ096zJNF8jU43ksLjqFAjiuVio1NU1TVRWEHAsMZLw5jtNut+v1utvtjsfjgUAA99nMzEw6nS6Xy8D1F15IfuQj3EsvuW0bZGrpOgoFnD49sCxjMEA2mxVFEYQcFwxkvHEc1+/3I5FIIBDgOA4PhCAIc3NzlUplZ2f9u99NvPmmnM/DMECmDc9jaWm0suLyels3bpizs7PRaJTjOBByjDCQsReNRjmOw4PFcZyu641Go1TaOHkyUSyqy8swDJDpoesoFHDmzEGzWa1WO6lUyu/3g5Bjh4GMPY7j8JCEQiFBEMrlsqoOXnwxurwM03SBTAFdR7EIRdkrlQxBELLZrCAIIOQ4YiDkHfn9/nQ6XSqVBKH/wgva8jIsiwc5vngei4ujlRUIQmN9vRKLxcLhsMvlAiHHFAMZA3t7ewcHB36/H2NJFMX5+fm1tTXLuvzMM+Hf//2Fl15y2zbI8aPrKBTw+ON2o1HZ2uqn02lZlkHIscZAHqpKpbK1tbW7u+v1eufn52VZxvjp9XqWZQ2Hw1AodHAw/Pu/31tb8+fzMAyQ40TXUSzC5+tsbhqyLKfTacYYCDnuGMjDs7+/z/O8ZVmapi0sLGD8DIfDRqNRr9eDweDCwoIgCK1WyzBupNOxYjG8vAzDADkGeB6Li06hALfb2txsaJqmqioImQ4M5OHxer1ut/vcuXOCIGDMOI7TbrdrtZooiplMRpIk3KSqqiAI5XJZlvuXL2tnz7pM0wUyyXQdhQJOnx7U62a/72QyGa/XC0KmBgN5qARBwPjpdDqWZTmOE4/HFUXBL5JlOZ1Ol8tl4PoLLyQ/8hHupZfctg0ycXgeS0ujlRWXJG3duGHMzs5Go1GO40DINGEg5Ofs7+9blrW3txeJRFRV5TgOb0cQhLm5OdM0d3fXv/vdxJtvyvk8DANkgug6CgWcOXPQbFYrlU4ikVAUBYRMHwZCbrJtu9Fo1Ov1UCiUzWYFQcA74jgukUjU6/Vy+drJk3qxqC4vwzBAJoKuo1hEMNgtlcqCIGSzWUEQQMhUYiBTz3GcVqtlWZYkSSdPnvR6vTi0cDjs8XhKpdLs7ODFF6PLyy7TBBlnPI+lpdHKisvjaaytmbFYLBwOu1wuEDKtGMh0297ertVqHMclEgm/34875/f70+l0qVQSxcGlS9q5c27TdIGMpUhk+L//N3viiWGjUWk0uul0WpZlEDLdGMi06na7tVptf38/Go0Gg0GO43C3vF5vOp02DGMwuHbxYuo3foO99JLbtkHGiq7jq1/dCAScjY2h3+/PZrOMMRAy9RjI9BkMBpZltVqtSCSSTCYZY7hnjLFUKlWr1Vqt9b//+8Tamj+fh2GAjAOex+KiUyjA5ZLW1tZEUYzH44wxEEIABjJNDg4Oms2mZVl+v39hYUEURRwdl8sVi8UEQSiXr2cyWrEYWl6GYYA8XLqOQgGnTw/qddNxnKeeemo4HJqmubOzE4vFRFEEIdONgUyH0Wi0vb1drVZ5np+bm5NlGfeHqqqCIJTLZZ+vf/ly/OxZl2m6QB4GnsfS0mhlxTUz097cNILBYDQadbvdACRJsizr6tWrsVhsdnaW4zgQMq0YyBTY3d21LGswGEQikWAw6HK5cD/JspxOp8vlMnD9hReSH/mI+6WXONsGeZB0HYUCnnzSabVqptnWdV1RFPwrxpimaX6/v1KpdDqdeDwuSRIImUoM5FgbDoeVSmV7ezsSiaiqyhjDAyEIwtzcnGmau7vr3/te8qc/ncnnYRggD4auo1hEMNgtl02O49LptCiK+CWyLGcymXq9vra2FrmJ4zgQMmUYyLHGGJMkKRqNCoKAB4vjuEQiYVlWuXzt1KlEsagsL8MwQO4rnsfS0mhlxeXxNNbXK5FIJBwOcxyHW+A4LhqN+ny+arW6tramaZosyyBkmjCQ4252dhYPTyQS8Xg8pVIpHO6/+GJkedllmiD3ia6jUMCZMwf1utlodOfm5nw+Hw5BkqS5ublWq3X9+nVVVSORCGMMhEwHBkLus0AgwPN8uVwWxf6lS9q5c27TdIEcKZ7H0hJWVhAI7N64UZYkKZPJ8DyPQ+M4LhQKybJcrVbX1tbi8XggEAAhU4CBkPtPkqR0Ol0ul4fD6xcvJj/84eEbb0jDoQvkKOg6CgUsLjrb241r12rxeDwUCuGuiKI4NzfXarUMw+h0OtFoVBAEEHKsMZDJNxgMDg4OvF4vxhhjLJVKVavVUunKF7/ILEv/7d+OGQbIPdJ1FIsIhfqmaQ6Hw0wmI0kS7o2qqrIsV6vVtbW1WCymqioIOb4YyCTb2tryeDyrq6uPP/642+0WBAFjbP8mxthwODx3jhWLWF6GYYDcHZ7H0hJWVjAz015fNwOBQCqVcrvdOAqCIKRSqXa7HQgEQMixxkAmlm3b9Xrdsqx0Ot1utxVFwbgaDoeWZTWbzUgkMj8/3+12S6VSIDC4fDl29qzLNF0gd0jXUShgcdFpNquGsaVpWjAYxFFTFAWEHHcMZGLxPH/ixAlVVUOhEMbY1tZWtVr1er0nT54URRGALMvpdLpUKrndN154IfHRj7qvXOFsG+SQdB3FIoLBbqlkchyXyWREUcSDMhwOGWMg5LhgIJPMcxPG1f7+frVa7ff78XhcURT8HI/HMz8/b5pmt7vxve8l33hDyudhGCDvjOextDRaWXF5va2NDTMUCkUiEY7j8EAMBoNer3ft2rUTJ04oigJCjgUGQu6Dg4ODer1uWVY4HE4mk4wx/BK3251MJi3LKpU2Tp1KFIvK8jIMA+RWdB2FAs6cOWg0Kpa1l0ql/H4/HqBut9vpdHZ2dizLmpmZcblcjDEQMuEYCDlq29vb1WqV5/lsNitJEt5RJBIRBKFcLkcig2IxsrwMwwD5N3geuRwKBQQCu5ubhiiK6XRaEAQ8WMpNjDFFUXZ2dlRVBSGTj4GMtzfeeGMwGJw5cwaToNfrWZa1u7sbi8WCwaDL5cIhKIoiCEK5XPZ6+5cuaU8/7bpyhbNtkH+h6ygUsLQ0arfrGxtVTdNCoRAeHk3TAEiSBEKOBQYyriqVymuvvXb16tVf//Vfx9hzHKfRaFiWpSjKyZMneZ7HnZAkaX5+3jCM4fDa888nXntNzOdhGCC6jmIR4fDANM3BYJDJZGZmZkAIOToMZFzF43FJkobD4dbWViQSwRjb2dmpVqsul2tubk6WZdwVnudTqVS1Wi2VNk6fThaLvuVlGAamFs9jaQkrK5Dl7bU1w+/3JxIJxhgIIUeKgYyxQCCwvLysKArG1WAwsCyr3W7HYjFVVTmOwz3gOE7TNEEQrl27put6sTi7vAzDwBTSdRQKWFx0Wq1aqdTUNE1VVRBC7gMGMt4URcFYGo1GzWbTsixZlk+ePOnxeHBEQqGQx+MplUqK0r98OXb2LGeamCq6jmIRs7O9ctkAkM1mRVEEIeT+YCDkzu3t7VWr1YODg0Qi4ff7cdR8Pl86nS6Xy4xtvvCC/tGPuq9c4Wwbxx7PY2lptLLi8npba2tmKBSKRCIcx4EQct8wEHInhsOhZVmNRiMajYbDYY7jcH+Iojg3N2eaZq937XvfS7zxhpTPwzBwjOk6CgWcOXPQbFar1U4qlfL7/SCE3GcMhBza1tZWtVr1er0LCwuiKOI+Y4ylUqlarVYqbZw6lSgWleVlGAaOH55HLodCAYHAbqlkCoKQzWYFQQAh5P5jIOQQ9vf3q9Vqv9+Px+OKouABikajHo+nXC5HIoNiMbK8DMPAcaLrKBSwtDTa3m5sbFRisVg4HHa5XCCEPBAMhByCZVmiKCaTScYYHjhFUQRB2NzclOXBpUvxp5/mrlxx2TaOAV1HsYhweGCa5mAwSKfTsiyDEPIAMRByCLFYzOPx4OGRJCmdThuG4TjX/+EfEq++6snnYRiYXDyPpSWsrMDn66yvGz6fL5FIMMZACHmwGAg5BI/Hg4dNEIQTJ05Uq9VSaeOxx5LFory8DMPAJNJ1FApYXHS2tqzNzYamaaqqghDyMDAQMjk4jtM0TRCEjY2NRCJRLKrLyzAMTBZdR7GI2dmeYZiO42QyGa/XC0LIQ8JAyKQJhUKCIJTL5WCwf/ly9N//+wPL4jEJeB5LS6OVFZckba2tGaqqxmIxjuNACHl4GAi5aTgcMsYwIfx+fzqdvn79+u6u8cwzM3/wB6euXOFsG+NM11Eo4MyZg2azWql0EomEoigghDxsDGTqdTqdvb29drut67okSYwxTIJ+v39wcOA4jqaNvv/9/uuve/N5GAbGEM8jl0OhgGCwWyqVBUHIZrOCIIAQMgYYyBQbDocA1tfXd3d3k8lkt9v1+/0Ye8PhsFqtbm9vx+NxRVEsyyqVNh55JFEsBpaXYRgYK7qOQgG5HLa3G2trZiwWC4fDLpcLhJDxwECmGGMMwKlTp3Z3dyORCCbB9vZ2pVLxer0nT54UBAFALBbzeDybm5uxWKxYDC8vwzAwJnQdxSLC4UGlUu12u+l0WpZlEELGCQOZetJNGHu2bddqtU6nE4/Hg8Egfk4wGBQEoVQqyXL/8mUtn3ddueKybTxEPI+lJayswOfrbGyYkiRls1nGGAghY4aBkEnQbrer1aokSdlsVhAE/JKZmZl0Ol0ul4HrP/hB4pVXhHwehoGHQtdRKGBx0dnasm7cqGuaNjs7C0LIWGIgZLzZtl2r1TqdTiwWU1UVtyYIwtzcnGmapdLGY48likV5eRmGgQdM11EsYna2Zxim4ziZTEaSJBBCxhUDIWOs3W5XKpWZmZlsNisIAm6H47hEItFoNDY2NhKJRLGoLi/DMPBg8DyWlkYrK66Zmfb6uqEoSiwWc7vdIISMMQZCxpJt27VardPpxGIxVVVxJ0KhkCAIpVJpdnbw4ovR5WWXaeJ+03UUCnjySafVqplmW9d1RVFACBl7DISMn3a7XalUZmZmstmsIAi4c36/P5PJbG5uejz9S5f0j3yEu3KFs23cDzyPXA6FAoLBbqlkuN3uTCbj8XhACJkEDISME9u2q9Xqzs5OPB4PBoO4B6IoptNpwzAGg2vPP5987TUxn4dh4GjpOgoF5HLY3m6sr1cikUg4HOY4DoSQCcFAyNhot9uVSmVmZiabzQqCgHvGGEulUrVarVTaePTRRLHoX16GYeCo6DqKRUQidqVS6Xa7c3NzPp8PhJCJwkDIGBgMBrVabWdnJx6PB4NBHB2XyxWLxQRBuH79uqZpxWJoeRmGgXvE81hawsoKAoHd9fWyJEmZTIbneRBCJg0DIQ9bu902TVOW5Ww2KwgC7gNVVQVBKJfLPl//8uV4Pu+6csVl27g7uo5CAYuLzvZ2Y2OjqmlaKBQCIWQyMRDy8AwGg2q1uru7G4/Hg8Eg7idZltPpdLlcBq7/4AeJV14R8nkYBu4IzyOXQ6GAUKhvmuZwOMxms5IkgRAysRgIeUja7bZpmj6fL5vNCoKA+08QhLm5OdM0S6WNxx9PFoszy8swDBySrqNQQC6Hvb32+roZCARSqZTb7QYhZJIxEPLADQaDarW6u7uraZqiKHiAOI5LJBKWZW1sbCQSiWIxuLwMw8Bt6TqKRcTjTrVa3dra0jQtGAyCEDL5GAh5sNrttmmasixns1lBEPAwRCIRj8dTKpVCof6LL0bPnnUZBm6F55HLoVBAMNjd2DA5jstkMqIoghByLDAQ8mB5PB5N0xRFwUMVCAR4ni+Xy6I4uHRJf/pp15UrnG3j39B1FArI5bCz09rYMEOhUDQadblcIIQcFwyEPFjemzAGJElKp9Plcnk4vPb884nXXhPzeRgGfkbXUSwiGh1WKpW9vb1UKuX3+0EIOV4YCJlijLFUKlWr1UqljUcfTRSL/uVlGAZ4HrkcCgUEArvr64Yoiul0WhAEEEKOHQZCphvHcfF43OPxXL9+XdO0YjH0uc+NPvUp19LSqN2ub2xUNU0LhUIghBxTDIQQQFVVQRBKpVIgMPjzP48dHNimaQ4Gg0wmMzMzA0LI8cVAyFFzHIfjOEwaWZbT6XS5XH799ddGo1EwGEwkEowxEEKONQZCjs7+/v5gMNjc3Ewmk4qiYNLwPC+KomEYMzMzqqoyxkAIOe4YCDkijuM0m03LsrrdbjwedxyH4zhMjl6vVy6XXS7Xu971rp2dnY2NjUQioSgKCCHHGgMhR6Tb7cqy3O12E4lEKBTCRGm1WqZphkKhSCTCcZzX6xUEoVwu9/v9aDQKQsjxxUDIEZFl2XEcv9/PcRwmx3A4rFarnU4nlUr5/X78K0VRBEEol8v9fl/TNMYYCCHHEQMhR4fjOEyU3d1d0zQFQchms4Ig4BdJkjQ/P28YxvXr1xOJhCiKIIQcOwyETKXRaNRoNCqVSiwWC4fDLpcLb4fn+RMnTlQqlY2NjWQy6fP5QAg5XhgImT6DwcA0zcFgkE6nZVnGO3K5XJqmeTyea9eu6bo+OzsLQsgxwkDIlOl0OoZh+Hy+RCLBGMPhzM7OCoJQKpX6/X4sFuM4DoSQY4GBkKnhOI5lWY1GQ9M0VVVxh3w+XzqdLpfLm5ubuq7zPA9CyORjIGQ69Ho90zQdx8lkMl6vF3dFFMW5uTnTNK9du5ZIJCRJAiFkwjEQMgW2trYMw1BVNRaLcRyHe8AYS6VStVptY2MjkUgoigJCyCRjIORYGw6H1Wq10+kkEglFUXBEotGox+Mpl8uDwSASiYAQMrEYCDm+ut1uuVwWBCGbzQqCgCOlKIogCKVSSRRFv98PQshkYiDkmGo0GqZpxmKxcDjscrlwH0iSND8/LwgCCCETi4GQY2cwGFSr1f39/XQ6Lcsy7idBEEAImWQMhBwvnU7HNE1JkjKZDGMMhBDyjhgIOS4cx7Esq16va5o2OzuLh6TT6fh8vp2dHb/fD0LI2GMg5Fjo9XqmaTqOk8lkJEnCQzIajQRB+PGPf3z69Ont7e1AIABCyHhjIGTytdttwzCCwWA0GnW73Xh4dnZ2+jdtbm5qmmbbNs/zIISMMQZCJp8oirquK4qCh83v95umeerUKVEUAfA8D0LIeGMgZPKJN2E8aJoGQsjkYCCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQsbe7u7uzMzM3t6eLMsghJAjxUDIeOv1evV6vVwuJ5NJEELIUWMgZLyVSiWO47rdbr/fn5mZASGEHCkGQsZYp9PJZDKWZQWDQVVVQQghR42BkDHm9/sBxGIxEELI/cFACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliZ7GwGAAAAWVJREFUDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVOMgRBCCJliDIQQQsgUYyCEEEKmGAMhhBAyxRgIIYSQKcZACCGETDEGQgghZIoxEEIIIVPs/wGOL6frCyl7JgAAAABJRU5ErkJggg==", - "text/html": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "GLMakie.plot(Ω;shading=Makie.NoShading,color=:blue)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Definition and visualization of the Dirichlet boundary $\\Gamma_{\\rm D}$. This corresponds to the \"sides\" of the model." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "GalerkinToolkit.PhysicalDomain(…)" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Γd = GT.boundary(mesh;physical_names=[\"sides\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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bzabruo7jGIaBN43HY03TMMUYs6YODw/jON7d3QUghLBtO5/Pg5D3Ewch5CcZDAZBEERRZNv28vKyaZo4xmQy6Xa77XZ7MBgIIVZXV3VdlxKbm2g08MILSFNIiQ81KSEl83322GPq+jr+4A/iX/5ls1DguAfnXEwNBoMwDG/dumUYhhCiVCrlcrnRaMQ5x9vl8/larVapVHq9XhiGzWbTsiwhhGmajDEQ8j7gIITcIwiCbre7vLzc7XaDIBgMBkKI1dVVXddxjKOjo06n0263sywTQiwtLamqKiU2N9FowPchJT5ipMTmJq5eddbWJl/4Qnj1asF1C6qKexlTtVqt0+m0Wq3d3V0hxGAwsG0b98MYs6YODw/jON7d3QUghHAcR9M0EPKe4iCE3CPLsjiOR6NRlmXlcnl5eZlzjmNIKaMoCoKAc+55nuM4jDEpsbmJRgO+DynxESYlbt5UfF/oOj72MXzta71HHjHyeYZ7qKrqeV65XO71elEU3blzp16v5/N50zQZY7iffD5fq9UqlUqv1wvDsNls2rbtuq5pmowxEPJe4CCEvEWaplEU3b17N03Ts2fPWpbFGMMx0jQNp4rF4qlTp0qlkqIoUuK730WjAd+HlJgZzie6jr+XphiPFczWeIxeD5ubePxxc20NTz7ZeeKJgmVpqoofoyhKqVQyTTNJEtM0d3d3FUVxXddxHE3TcD+MMWsqTdM4jnd3dxVFcV3XcRxN0wDEcaxpmmEYIOTd4yCETPV6vTAM4zh2HGdpaSlJEsdxcIx+vx8EQRzHruuurKwYhgFASvg+Gg34PqTEzKgqrlyZ/OZvvvGZz+QA/I//Mf4v/+XU888zKTF7UuLmTWxt2bqOy5fx1FPDhx8uqCp+TJZlABYWFlRV7Xa7URQ1m03HcYQQxWJRURTcj67r9Xq9Wq12u90oiprNpm3brutGUVQqlQzDACHvHgch8y3LsiRJwjAcDodCiNXVVV3Xe71eHMe4R5Zl3W43CILhcCiEuHTpUj6flxLdLm7cwMYGfB9SYmZUFWtrk2eeUR58UO7vj3Z2drIs++xnl37rt0YvvKB/+ctHP/pRLk0hJWZMSkiJzU089lhhfR1f/Wryy79c1PUc3nR0dDSZTHK5HGPMnkrTNIqinZ0dVVVd13Uch3OO+2GM2VNpmsZx/MYbb+zt7Z07d86yLE3TQMi7xEHIvBqPx3EcB0EAoFwuLy8vc84xxRibTCZZljHGMHV0dBTHcRAEWZaVy+Xl5WXOuZTY3ESjgRdeQJpCSsyMquLKlcn168rHPz7udsPXXgt0Xf/FX/zFXC4XBMHt29sLC87//J+Cc/PGDTz1FLa2ICVmT0psbuLzn7fW1iZf/GJ89aruOLqqYjwe53I5xhjepOv6wsJCtVpNkiQMw2az6U4ZhoFj6Lper9fL5XK325VSvvTSS47juK5bLBYZYyDkp8NByPxJ0zQMwyiKCoVCrVazLIsxhrdgjGVZhqnRaBRFURAEmqZVKhXbthljUmJzE40GfB9SYpZUFVeuTK5fVx58UHa74e3bgWEYy8vLxWJRURQAhmFUq9UwDHd3XysUCv/kn5Q/97nS88+za9cmW1uKlJg9KXHzprK15eg6Ll/Gf/yPg49/XKqqyhjD2+VyOXdqMBiEYXj79m1d14UQlmXlcjncz2QyMQxjZWVlPB7HcXz37t1cLudMaZoGQn4SDkLmSa/XC8MwjmPHcc6ePVssFnE/jLHJZDIYDDqdThRFpmkuLS2ZpqkoipT47nfRaMD3ISVmSVVx5crk+nXlwQdltxvevt02TfPMmTOmaeLt8vn8wsJCpVKJ43hvb4+x/QsXyt/8pv397/OvfGXy/POKlJg9KSElNjfxmc8Yn/jE0T//59Fv/dbYNLmq4l7GVL1ej+P44OBgb2/PndJ1HW83Go0457lcjnNer9er1WqSJFEUNZtNx3Fc1y0Wi4wxEHIMDkLmQJZlSZIEQXB4eCiEuHTpUj6fx/H6/f7BwcF4PPY8b2VlxTAMAFLC99FowPchJWZJVXHlyuT6deXBB2WSBLdvB6VS6ezZs6Zp4nicc8/zhBBJkrTb7f39/TNnxLPPih/+UPvKV7KXXmJpCikxe1Lie9/LPf/8mf/wH5TLl7GxkX7yk7qq4l6cc8/zyuVyv98Pw3B7e9uyLNd1S6USYwxTo9FI0zRFUTDFGHOm0jSN4/ju3bu5XM51Xdu2NU0DIffgIOQjTUoZx3EQBIwxIYTjOJxzHCPLsiRJgiAYDAac8wsXLpimKSW6Xdy4gY0N+D6kxCypKq5cmVy/rjz4oOx02rdvh6VSaWVlxTAM/HQYY85Ut9sNguDg4EenTrk3bpQVpXDjBjY24PuQErM3HivdLjY38eij+vo6vva17iOPFPN5hnsoimJO1ev1OI6bzebe3p4QwnEcTdNGo1E+n8c9dF2v1+vVajVJkiiKms2mbdtCiGKxqCgKCHkTByEfUWmahlOGYSwsLJRKJcYYjjEej+M4DsMwyzLP806fPv3yyy8D6uYmGg288ALSFFJillQVV65k16+zj31slCTBrVuBbdsrKyuGYeBnUpoaDAZhGL722iulUunRR72rV03fx7Vr2NqClDgRUmJzE48/Xlpbw5NPdp54omBZmqriXpqmVatVz/N6vV4Yhs1m03GcwWAghMAxGGPOVJqmcRy//vrruVzOdV3btjVNAyEAByEfOb1eLwiCTqfjuu7KyophGDjeaDQKpzRNq1arlmUxxg4Psx/+sPjbv609/zykxIypKq5cya5fZ5cvj5IkuHUrcBzn/PnzhmHg52ZMVavVMAx3dnY0Tbt0yXvuOev559m1a5OtLUVKnAgpcfMmtrZsXcfly3jqqeHDDxdUFfdijFlTaZrGcfzKK6+kacoYs21bVVUcQ9f1er1erVaTJAnDsNls2rYthCgWi4qigMwxDkI+KrIs63Q6QRCMRiMhxAMPPKBpGo43HA6DIIiiqFQqLS8vm6YJQEp897u4do35/tnxWMFsqSquXMmuX2eXL486nfbt26HruhcvXiwUCnhPaZpWr9c9z4vjuNVqZVnz/Hnvm990vvOd0b/5N/yHP9SkxImQElJicxOPPVZYX8dXv5o88ohRKHDcj67r1Wq13W57npckSbPZdBxHCGEYBo7BGHOm0jSNomhnZ4dzLoSwLEvTNEyNx2POOcjc4CDkw09KGUVRGIaMsXK5bNs25xzH6/V67Xa72+26rnvhwoVCoQBASvg+Gg34PqQEoGCGVBVXrmTXr7Nf+IXDJAlu3w6FEKurq7qu433DOfc8TwiRJMndu3cPDn6Qz+f/8i/P7u7WGw289BJLU0iJEyElNjfx+c9ba2uTL34xvnpVdxxdVfFjxuNxlmWe53HOh8NhGIa3bt3SdV0IYVkW5xzH0HV9YWGhWq12u90wDPf29mzbFkIUi8Xd3V1d16vVKsh84CDkwyxN03DKMIzFxUXTNBljOEaWZUmStNvt0WgkhFhcXNQ0TUp0u7hxAxsb8H1IiRlTVVy5kl2/zh54IE2S4M6dSAixurqq6zpmIk3TTqcD4Ny5c1mWdTrtpaXsf/0vwZhx4wY2NuD7kBInQkrcvKlsbTm6jsuX8fWv9x9+uJDPM7xJSqlpWi6XA1AoFE6dOlWr1TqdThiGzWbTcRwhhK7rOEYul3Om0jSNomhnZ4dzniTJ2bNnQeYGByEfQpPJpNfrBUHQ7XZd111ZWTEMA8cbj8dxHAdBoCiKEMJxHM65lNjcRKOBF15AmkJKzJiq4sqV7Pp19sADaafTfu212PO81dVVXdcxE2maHhwcxHFcLpdXV1c1TQOQpmkYhq+/fss0zU99Snz+86WtLeXaNWxtQUqcCCkhJTY38dnPFtfW8KUvJU88YZgmV1WMRiNN0xRFwZs45+VyWQjR7/ejKHr55ZdN0xRClEolxhiOoev6wsJCtVqN4/ju3bs7OzvD4dB13WKxqCgKyEcaByEfKlmWxXEchuFoNBJCLC4uapqG441Go3Aqn8/XajXLshhjUmJzE40GfB9SYvZUFZ/4RPZHf8QeeCDtdNo7O51yuXzp0qV8Po+ZGI1G7SkhxOrqaj6fx5t0XV9cXPQ8L47jN954Q1XVixfFc885zz/Prl2bbG0pUuKkSImbN7G1Zek6Ll/GxkZ6/vxI0zTcQ1EUc6pWq8Vx3Gw29/b2XNd1HCefz+MYuVyuWCzWarUzZ84kSbKzs8M5F0LYtq2qKshHFAchHxKj0SiO4zAMGWOe59m2ncvlcLzBYBBO2ba9vLxsmiYAKfHd76LRgO9DSsyYqkLXcenS0R/9Ue7SpWGn03799a4Q4tKlS5qmYSaklEEQtNtty7IuXrxYKBRwP5qmVavVcrnc6XTa7Xar1Tp3Tjz7rPuDH6hf+Ur20kssTSElToSUkBKbm3j0Uf3jH8/9/u/vVypZPs9wP5qmVatVz/N6vV4Yhvv7+7ZtCyGKxSJjDPdI0zSfz5tTtVqt2+2GYdhsNm3bdl23WCwqigLy0cJByAfecDgMgiCOY9M0FxcXS6WSoig4xmQy6fV6QRD0ej3XdVdXV3VdByAlfB+NBnwfUmLGVBXr6/i938OnP43xeNjptO/e7Xmet7CwoGkaZmI8HodheHBwUCwWV1ZWDMPAT5LL5YQQrut2u912u91qtZaWxP/+3wLQb9zAxgZ8H1LipEgJ31d/7ddOra8rTz7ZeeKJgmVpqop7McasqTRN4zi+e/duLpcTQti2raoq3iJNU13XMZXL5Zyp4XAYRdHOzo6qqq7r2ratqirIRwUHIR9Uk8mk2+2GYdjtdl3XXVlZMQwDx8uyLEmSdrs9Go3K5fLi4qKmaQCkhO+j0YDvQ0rMmKpifR1PP421tclo1G+3271ez/O8xcVFTdMwE1mWhWHYarV0XT9z5oxpmng3FEWxpgaDQbvdvn1723Gcxx4rX71a9H1cu4atLUiJkzIeKzdvYmvL1nVcvoynnho+/HBBVXFfuq7X6/VqtZokSRiGzWbTcRzXdYvFIqbSNDVNE29XmKpWq91uN4qiZrPpTBWLRUVRQD7kOAj54Dk6Oup0OkEQjMdjIcTi4qKmaTjeeDyO47jdbjPGyuWybduccynR7eLGDWxswPchJWZMVbG+jqefxtra5PCw98Yb7cFg4HneqVOnVFXFTGRZFsdxq9XinJ8+fdqyLPwcDMNYXl6uVqthGN6+fdswjF/4Be+558znn2fXrk22thQpcVKkhJTY3MRjjxXW1/GlL/WuXtVNk6sq7sUYc6aGw2EURXfu3Mnn80KIUqmUpqnnebgfzrk7NRgM4jje2dlRVdV1Xdu2VVUF+dDiIOSDZDQaRVEUhiHnvFwu27ady+VwvMPDwyiKgiAoFAoLCwuWZSmKIiU2N9Fo4IUXkKaQEjOmqlhfx9NPY30dw2Fy9247TVPP85aWljjnmInJZNLpdFqtFoB6vW7btqIoeC/our64uFitVsMw3N3dZYxdvOh961v23/5t7itfmbz4ItIU47GCEyIlNjfh+6au4/JlfOMbo1/6JU1VcV+FqWq1miRJGIZ3796N43hxcRHvyJiqVqtJkkRR1Gw2HcdxXbdYLIJ8CHEQ8sEwHA6DIIiiqFQqnT592jRNRVFwvMFgEARBFEWO45w5c8Y0TQBSwvfRaMD3ISVmT1Wxvo6nn8b6OobD5PXX22maep63vLzMOcesJEnSarXG43G1WnUchzGG9xrnvFqtep7X6XSCIGg2m+fOec8+63Q6h//tv/X+839e2NqClDgpUkJKbG7iU5/S1tfx9a/3H364kM8z3A/nXEy12+0kSe7cuWOaphDCsizGGI7BORdTg8EgjuPXXntN0zRninMO8uHBQciJmkwm3W43CIJ+v++67oULFwqFAo43mUy63W4QBP1+Xwixurqq6zoAKeH7aDTg+5ASs6eqWF/H009jbW2Spt2dnYPRaOR53vLyMuccs9Lr9VqtVpqmlUpFCJHL5fB+Yoy5rus4Trfb3dvb+7u/+ztVVf/pPz3327+dPf88azTg+5ASJ0hKbG7is58trq3hS18Fp1/JAAAgAElEQVRKrl4tlEqqquK+GGOLi4unT59OkqTVau3t7bmu6ziOrus4njFVrVaTJImiqNlsOo7jum6xWMSbJpOJoiggH0gchJyQ8XicJEm73c6yTAhx+vRpVVVxvCzL4jgOw1BKWS6XT506pWkaACnh+2g04PuQErOnqlhbwzPPYG1tMhh0dnba4/HY8zzHcTjnmJXBYNBqtXq9XqVSWV5e5pxjVqSUvV7v8PDwzJkzjLEgCMbj8cc+Vv72t03fx7Vr2NqClDhBUuLmTWxtWbqOy5exsZF+8pO6quLHpGmq67qmaZ7nCSF6vV4URdvb25ZlCSFM02SM4RicczE1GAziOL5z504+n3dd17ZtzvnOzo5hGJVKBeSDh4OQmRuNRmEYRlGkqqrneY7jMMZwvPF4HE4xxjzPs207l8tJiW4XN25gYwO+Dykxe6qKtTU88wyuXMmGw2Rnpz0ejz3Pc103l8thVtI0PTg4iOPY87zFxUVN0zArWZaFYdhqtYrF4sWLFwuFAoDRaBSG4c7OTj6fv3Sp/Nxz1vPPs2vXJltbipQ4QVJCSmxu4tFH9fV1fO1r3UceKebzDG9K09RxHEwxxqypw8PDOI53d3cVRRFC2LataRqOZ0xVq9UkSaIo2tvbcxwniqJyuQzygcRByPssyzLGGKYGg0EYhlEUlUqlpaWlYrGoKAqOl6ZpOGUYxuLiommajDEp8b3vodHACy8gTSElZk9VsbaGZ57BlSvZcJjs7BwcHR1VKhXXdRljmJXRaHRwcBAEgRBidXU1n89jhuI4brVajLHTp09bloU3aZpWr9c9z4vjeH9/X1Fa58+Lb37T+f73+Ve+MnnpJSVNISVOkJTY3MTjj5fW1vDkk/ETTxiWpXE+SdNU13W8XT6fr9VqlUolSZIwDJvNpuM4rusWi0VFUXAMzrmYGgwGrVZrb2+vUChUKhXLsjjnIB8kHIS8n3Z3dwHU6/Ver9dutweDgRDi4sWLuq7jHQ0Gg3a7Hcex4zjnzp0rFosApMR3v4tGA74PKXEiVBWXL6d//MfqL/6i0u/Hr73WnkwmlUrFcRzGGGZFShkEQbvdtixrdXVV13XM0GAw2N/fT9O0Vqs5jsMYwz04557nCSGSJGm3261W68wZ8eyzIsu0GzewsQHfh5Q4QVLi5k1sbTm6jsuX8dWvdsvlI03TcD+MMWcqTdMoinZ2djRNc13Xtm3OOY5nGIYQ4ty5c5VKJQzD3d1dx3GEEIZhgHwwcBDyfuKcN5vNXq+XZVm5XF5aWlJVFcebTCbdbrfdbg8GAyHE6uqqrusApITvo9GA70NKnAhVxdoannpqsLCw1+tFP/gBTNOsVquO4zDGMCvj8TgMw4ODg2KxuLKyYhgGZmg0GrVarSiKKpXK0tIS5xzviDHmTPV6vXa7fXDwI9d1P/MZcfWq4ftoNOD7kBInSEpIic1NfP7z1gMPnP+3/3b4xBMF0+SqivvSdX1hYaFSqSRJEoZhs9l0XddxHMMwcIzBYGCappgaDAZRFN2+fTufzwshLMvinIOcKA5C3h+Hh4dRFN29e3cwGDz00EOWZTHGcLyjo6NOpxMEwdHRkRBiaWlJVVUAUsL30WjA9yElToSqYm1t8swzypUrWb+fHhyMOedZlgFgjCmKgpnIsiwMw1arpev6mTNnTNPEDB0dHQVB0Gq1LMu6ePGirut4N8yp4XAYhuGtW7dM07x8ufzcc+bWlnLtGra2ICVOlpT4wQ+Mf/2voeu4fBnf+Mbol35JU1XcF+dcTA0GgzAMb926ZRiGEKJUKuVyObzdYDBwHAdTxlStVkuSJAzD3d1dd8owDJATwkHIe20wGARBEEWRbdtnz55ttVqWZTHGcAwpZRRFYRjmcrlyuew4DmMMgJTwfTQa8H1IiROhqlhbmzzzjPKJT2T9fnz79kEul6vVapZlAYjjuNlsttvtarVqWRbeN1mWxXHcarU456dPn7YsCzM0mUziOG61Wqqqnj171jRN/KwKhcKpU6cqlUoURa+//rqmaaur5eees59/nl27NnnxRSVNISVOkJSQEpub+NSntPV1fP3r/YcfLuTzDMcwpmq1WqfTabVau7u7QgjHcXRdx1SWZcPhcGFhAW/BORdTg8EgDMNbt27pui6EsCyLcw4yWxyEvEeyLOt2u0EQDAYDIcTq6qqu6+PxeHd39+joiDGGe6RpGk4Vi8XFxcVSqaQoipTo93HjBjY24PuQEidCVbG2NnnmGeUTn8h6vejOnTbnvF6vW5bFGMOUEMK27SiK7t69WygUKpWKaZp4T00mk06n02q1ANTrddu2FUXBDPV6vf39fSllrVZzHEdRFPzcNE2r1WrlcrnT6RwcHGTZ/spK+ZvfdMdjfuMGNjbg+5ASJ0tKbG7is58trq3hd34nuXpVtyxNVXFfqqp6nlcul/v9fhiG29vblmUJIUzTPDw8BJDP53E/xlS9Xk+SJAzDvb09x3Fc1zUMA2RWOAj5uY3H4ziOwzDMsqxcLi8vL3POMcUY45yPx2NVVfEW/X4/CII4jl3XXVlZMQwDgJTwfTQaeOEFpCmkxIlQVaytTZ55RnnooaN+P75zp805X1hYsCxLURS8XS6X8zzPcZx2u33nzh3LsjzPMwwD74UkSVqt1ng8rlarjuMwxjBDaZq2Wq0kSarVarlczuVyeE9xzsvlsuu63W43CIJWqyWE+NznxNWred/HF76Q/t3f5cdjBSdKSty8ia0tS9dx+TI2NtJPflJXVdyXoijmVL1ej+N4d3cXQC6XU1WVMYbjcc7F1GAwCMMQZLY4CPk5HB4ehmEYRVE+n69Wq5ZlMcbwFowxTdOklIVCAcBkMul2u+12ezgcCiFWV1d1XQcgJXwfjQZ8H1LipKgq1tYmzzyjPPTQUbcb3r7dzufzi4uLpVJJURQcj3Ner9eFEO12+5VXXhFCeJ6n6zp+Vr1e7+DgYDgcVqtV13VzuRxmaDwet9vtg4MD13VXV1c1TcP7hjFmT/V6vTAMf/SjH7mue/as9l//a/Lii4VvfOO070NKnCwpISU2N/Hoo/r6Or785d7Vq4ViMaequC9N06rVqud53W53e3s7TVNd14UQxWJRURQcz5gCmS0OQn4m/X4/CII4jh3HWV5eNk0Tx1BVdTQaHR0ddTqddrudZVm5XF5eXuacA5ASvo9GA74PKXFSVBVra5NnnlEeeuio2w1v327run769GnLsvBT0zRtcXFRCNFut19++eVyuex5nqZpeDcGg0Gr1er1epVKZWlpiXOOGcqyLI7j/f19XdfPnz9vGAZmxZxyHOfVV1/d39+v1+uf+lTliScmW1vKtWuTrS1FSpw4KbG5Cd83dR2XL+NP/3R07pyGYzDG7KkzZ84cHR3t7Oyoquq6ruM4nHOQDwwOQt6NLMuSJAnDcDgcuq67urqq6zrekaIozWbz4OBAVdVKpWLbNmMMgJTwfTQa8H1IiZOiqlhbmzzzjPLQQ0fdbnj7dlvX9dOnT1uWhZ+JruunT58WQrRare3t7Wq1KoTgnOMnSdP04OAgjmPP8xYXFzVNw2wlSdJqtbIsW1hYcBwHs5VlWRiGzWbT87zV1dV+v99sNnO5g4sXy9/6lv23f5u7dm3y4otKmkJKnCwpISU2N/H7vz/6wz/cr1bdYrGoKAruMR6P0zR1HEfTtGq1miRJGIbNZtNxHCGEYRggHwAchPx0xuNxHMdBEAAol8vLy8ucc7yjNE3DMHzjjTcURbl8+XKpVFIURUr0+7hxAxsb8H1IiZOiqrhyZXL9uvLxj4+TJLh1KzAMY3l52TRN/NwMwzh79myv12u1Wu12u1qtCiEYY7ifw8PDdrsdBEG5XF5dXc3n85it4XDYarX6/X61WhVCMMYwW71er9lsZlm2vLxsWRaAYrHoeV4cx0EQtFqtc+fEs8+6R0fqjRvY2IDvQ0qcuO98p5Bl/Z2dHVVVhRC2bXPO8RZpmmqapqoqgFwu504NBoMwDG/fvq3ruhDCsqxcLgdycjgI+UnSNA3DMIqiQqFQq9Usy2KM4R31er0wDOM4FkKcP38+jmPLsqSE76PRwAsvIE0hJU6KquLKlcn168qDD8puN7x1q22a5pkzZ0zTxHvKnEqSpNVqBUFQrVZt22aM4U2j0SgIgna7bdv26uqqruuYLSnlwcFBu932PO/ixYuqqmK2pJStVisMw1qt5nkeYwxvYowJIVzX7Xa7QRC0Wi0hxOOPi6tXdd9HowHfh5Q4Qe12rlarGYbX6XTCMGw2m+5UoVDA1HA4LBQKiqLgLYyper0ex3G73d7b23OndF0HOQkchByv1+uFYRjHseM4Z8+eLRaLeEdZliVJEobhcDgsl8uXLl3K5/Npmu7ttb/znex3f5f5PqTECVJVXLkyuX5defBBmSTB7duBaZpnz541TRPvG8uyTNPsdDoHBwdBEFQqFdu2x+NxGIYHBwfFYvH8+fOGYWC2siwLw7DVahmGcfHixUKhgNmaTCZRFDWbzWKxePHiRV3XcT+KolhTg8EgCILt7W3HcT72MfHtb5u+j2vXsLUFKXEi6nX8vVwuJ6b6/X4URa+88oppmkKIUqk0GAwMw8D9cM49zyuXy/1+PwzD7e1ty7Jc1y2VSowxkBniIOQeWZYlSRIEweHhoRDi0qVL+Xwe72g8Hnc6nSAIsizzPG95eZlzDkBK+L765JPnXnyRSYmToqrQdTzwwOT6deXBB2Wn0759OyyVSufOnSsWi3j/McZc17VtOwzDu3fvvvrqqwAcxzlz5oxpmpi5Tqezv7/PGDt9+rRlWZi5wWDQbDZHo9Hi4qLjOPgpGFPVajUMw9dee61QKDzwQPm550rPP8+uXZu8+KKSppASs/QrvwJdx/+vOFWtVuM4bjabe3t7nU7n0qVLOJ6iKOZUvV6P43g4HNq2DTJbHIS8hZQyjuMgCBhjQgjHcTjneEej0SiKoiAINE2rVquWZTHGAEgJ30ejAd/PSVnACVFVrK/j934Pn/40FGWUJMGtW4Ft2ysrK4ZhYOYYY4qiZFkGgE1htgaDwf7+fpqm1WrVdV3GGGZrPB632+1Wq1WtVpeXlznneDfy+fzCwkKlUonjeG9vj7H9CxfK3/ymPR7zGzewsQHfh5SYAVXFP/yHUFX8GE3TqtWq53lBEOzu7t65c8fzPNd1i8UijqdpWrVazbIMZOY4CJlK0zScMgxjYWGhVCoxxvCOhsNhEARxHJumubS0VCqVMCUlfB+NBnwfUuKkqCrW1/H001hfR5YdttvtIAgcxzl//rxhGJityWTS6XRarRaAxcVF27bH43G73X711Vcdx6lUKrqu4312eHh4cHAQRVGlUllaWuKcY+biOG42m5qmXbhwwTAM/Kw4557nCSGSJGm32/v7++Vy+fOfd69e1XwfjQZ8H1LifaXr+Mf/OAMY7ocxpmna0tLSqVOn4ji+c+dOPp8vl8uWZeVyORyDMQYycxxk7vV6vSAIOp2O67orKyuGYeAn6fV67Xa72+26rnv+/PlCoQBASqQpbtzAxgZ8H1LipKgq1tfx9NNYX8fRUdpqBX/Pdd2LFy8WCgXMXJIkrVZrPB5Xq1XHcRhjAFRVXVhYEEIcHBxsb297U5qm4X1wdHQUBEGr1bIs6+LFi7quY+bSNG02m4PBoF6vCyHwXmCMOVPdbjcIglar5bruQw+Vv/3tgu+j0YDvQ0q8T7Isu3PnjhAlx3FUVcU9hsNhoVAwpqrVaqfTOTg42NvbE0I4jqPrOsgHAweZV1mWdTqdIAhGo5EQ4oEHHtA0De8oy7IkSYIgODw8FEIsLi5qmgZASvg+Gg288ALSFFLipKgq1tfx9NNYX8fRUbq/3w7DUAixurqq6zpmrtfrtVqtNE2r1arrurlcDm+Xz+dPnz5dLpcPDg62t7e9Kc453iOTySSO4/39fVVVz549a5omZi7Lsna7vb+/L4S4ePGiqqp4r5WmBoNBGIavvPJKqVT62Me8b3/b9H1cu4atLUiJ95znHdVqk263u7+/7ziOEMIwDLzFYDBwHAdTnPNyuSyE6Pf7YRhub2/bti2EME1TURSQE8VB5o+UMoqiMAwZY+Vy2bZtzjne0Xg8juM4CAIA5XLZcRzOOQAp4ftoNOD7kBInSFWxvo6nn8b6OsbjYbPZjqJICLG6uqrrOmZuMBi0Wq1er1etVpeXlznnOF6hUFheXu73+wcHB9vb25VKRQiRy+Xw8+n1eq1WazQa1Wo1x3EURcHMJUnSbDYZY+fOnTNNE+8nY6parYZhuLOzo2napUvec89Z/+f/9P/dvyu8/DJPU0iJ90q7/c1/9s+u/dqv/V+/+qu/CuDWrVuGYZTLZcuyFEXJsmw4HC4uLuItFEUxp2q1WhRFd+/ezeVyQgjHcTjnICeEg8yTNE3DKcMwFhcXTdNkjOEdjUajcErTtFqtZlkWYwyAlPB9NBrwfUiJE6SqWF/H009jfR1SDvb22nEcl8vl1dVVXdcxc2matlqtTqfjed7i4qKmafjpFKeSJGm1WkEQVKtVx3EYY3j30jQ9ODjodDrVarVcLudyOczcaDTa399PkqRWqwkhGGOYCU3T6vV6pVKJomh3dzcMf1gs8r/6qwum6d24gY0N+D6kxM+J88m/+lcL7fb6H//xH//Jn/zJ1atXf/3Xf/3jH//43t5es9ksl8uapimKomka7iefz9fr9UqlkiRJGIbNZlMI4TiOYRggM8dB5sBkMun1ekEQdLtd13VXVlYMw8BPMhgMwjCMoqhUKi0vL5umiSkp4ftoNOD7kBInSFWxvo6nn8b6OqQc7O21O51OuVy+dOlSPp/HzB0eHrbb7SAIyuXy6upqPp/Hu2dZVqlU6nQ6rVar3W5Xq1XbthVFwU9nPB632+2DgwPXdVdXVzVNw8xlWRaGYbPZtG374sWLmqZh5nK5HOccgBAil8tFUUtRxp/7nHv1at730WjA9yElfmaFgvLlLz944cL/8/3vf/9P//RP/+Iv/uLP/uzPHnnkkd/4jd/4lV/5lSRJWq0WY+zw8LBQKOAYuVzOnRoMBmEY6roOchI4yEdalmVxHIdhOBqNhBCLi4uapuEn6Xa7QRB0u13XdS9cuFAoFABIiTTFjRvY2IDvQ0qcIFXF+jqefhrr6xiN+ru77W63K4S4dOmSpmmYudFoFARBu922bfvixYuFQgE/B0VRHMexLCuO42az2W63a7VaqVTCO5pMJlEU7e/v67p+/vx5wzBwEnq9XrPZzLJseXnZsiychNFotL+/3+12FxYWXNcF0Ov9v+zBbYwj+UEn/m/9/KvqcrlcLpfLZbft9ri73Z7dzT7MGpJJSDa3OuAFEUoAR2S1QQGiIKFDyij8XwQBQrzInbTwJr1IPBzkgDxwgWxvjlOyEccGdLdkNx2ROimBFTsPOzvdU3a5nvzQtrtcZZf/XJ9y2rCZme4Zz7g38eczcF33lVdeURTloYeUF14QdB0XLkDXEYa4bQzDPHLkox/96Be/+MXPfe5zv/RLv3T27NkPfOAD73znO7PZ7JUrVxKJRCaTEUWREIIbEI5gaUEolr5PBUHQ7XY9zyOEqKoqSRKlFDcVRVG/33ccJwgCRVEKhQLHcQDCELqOCxfw8svwfYQhFohlUa9jexv1OsbjgWE4g8Egk8nUajWO43DPTSYT13Vt2xZFcXNzUxAEzAkhRFGUVCrled7+/n48Htc0LZFI4Hvp9/uWZUVRtLq6KssyFiEMQ8uyPM/L5XKqqhJCsAjdbrfZbIqiWK1WOY7DEfGI7/ue57366quiKN5/v/K//lfyf/9vptGAYeCk8nnk8/h/CoXCr/zKr/ziL/7i888//5nPfObpp59+7rnnHnnkkQ984AP3339/s9kkhCiKIssypRRLpwzF0vedw8NDz/M6nY4oioVCIZlMMgyDm5pMJt1u13EcQkgmk0mlUpRSAGEIXceFC9B1hCEWi2VRr2N7G/U6xuOBYTiDwUBV1UKhwHEc7rnpdNrpdCzL4nm+UqmIooi7IBaLZbPZdDrtOM7Vq1clScpms/F4HN9xeHhoWdZgMMjlcoqiEEJwz81ms06nY5pmIpHY2trieR6LEASBaZqDwaBQKMiyjDfgeb5QKKiq2u12DcNgWXZ1NfPBD8q/8zsMTujBB8Hz+DcEQXjve9/77ne/++/+7u9eeOGFL33pS5/+9Kcff/zxD37wg4899li/3zdNU1GUdDodj8exdGpQLH2/mM1mBwcHnucdHByk0+mNjQ1BEHAr4/G40+l4nsfzfD6flySJEAIgDKHruHABuo4wxGKxLOp1bG+jXsd4PLh+3R6NRplMplgssiyLey6Kom63a1kWpbRUKkmShLuMUprP5xVFcRzn0qVLiqJks1lCiG3bjuOoqrq1tcVxHBZhNBqZphkEQaFQkGUZC9LtdpvNpiiK1WqV4zjcGMdxmqZlMpl/+ZeDJ54Qv/UtBifEsviJnwDL4t+Ioqjdbruu+/jjj//Mz/zMxz72sZ2dnb/4i7/4+Z//+YceeuiJJ55473vfG0XR5cuXk8mkoiiiKBJCsLRoFEtvftPptNfrua47mUwURSkUChzH4VZGo5F3RJblcrksiiKOhCF0HRcuQNcRhlgslkW9ju1t1Ovw/YP9fdv3/UwmUyqVWJbFPTebzXq9nmVZAPL5fCqVYhgG9wrHcYVCQVEUy7K++c1vzmazXC5XrVYFQcAiTCYTx3Esy9I0rVwuU0qxCEEQmKY5GAwKhYIsyzge04z9+I9LrRbByfE8Hn8c/4bv+4ZhAKhWqzzPAyiXyx/72Mc+8pGP/M3f/M1nPvOZT3ziE7/3e7/3Uz/1U0888YSqqs1mkxCiKIosy5RSLC0OxdKbWRAEnU7H8zxKaSaTSaVSsVgMNzWbzQ4ODjzPGwwGiqLUajWe5wGEIXwfzz+Pp56CriMMsVgsi3od29uo13F42N/fd3zfV1W1XC5TSrEI/X7fsqzJZKJpmizLhBAswng89n1fkiRCyHg8HgwGHMdRSnFvdbtd0zQ5jqtWq4IgYEG63W6z2RRFsVqtchyHYwhD6DoaDbRaBHPieV6z2cxkMrlcjhCC10kmk+9///t/+qd/end393Of+9wXv/jFP/uzP/uxH/uxn/u5n3vHO97R6/VM01QUpVAoYGlBKJbenEajked5nU4nmUyWSiVRFBmGwU1FUdTr9VzXDYJAVdVCocBxHIAwhK7jwgW8/DJ8H2GIxWJZ1OvY3sajj858/2Bvzx6Px6qqlstlSikWYTAYWJbl+76maYqiEEKwCKPRyLKs0WiUy+XS6TQhZDAYWJblum42m1UUhRCCu8/3/Xa7PRwO8/l8Op1mGAaLEASBaZqDwaBQKMiyjOMxDDQa0HWEIW5bPo98Hv/XZDIxTbPf76+traVSKdxALBb7kSO/+qu/+oUvfOHzn//8E088Ua/Xn3zyyfe85z3pdBpLi0Ox9KYym80ODg5c1x0Oh+l0ulqtxuNx3MpkMul0Oq7rEkJUVU2lUrFYDEAYQtdx4QJ0HWGIhWNZ1OvY3sajj84OD/t7e3YYhtlsVpZlSikWYTQaWZY1HA6z2Wy5XKaUYhGCILAsy/M8TdNKpRKlFEfEI71ez7Ztz/Oy2WwqlSKE4O6IoshxnHa7nclktra2WJbFgnS73WazKYpitVrlOA7HEIbQdTQaMAzcoQcfBM/jXw2HQ8MwOI6rVqscx+EYNjc3f+3Xfu2Xf/mXn3vuuc985jO//uu//slPfvJv//Zvz549i6UFoVh6k5hMJv1+33GcKIoURSkWixzH4VbG47F3JB6Pr66uJpNJQgiAMISu48IF6DrCEAvHsnj0UTz9NB59dDYa9fb2nMlkoqpqOp2OxWJYBN/3Lcvq9/uqqhaLRZZlsQjT6dR1XcuyJEmq1Wo8z+MNUqlUMpnsdruWZbmuq2maJEmYt36/b5omIWR9fV0URSxIEASmaQ4Gg0KhIMsyjscw0GhA1xGGuEMsi49/HCwL27ZbrVY+n89mswzD4CRkWX7yySd/9md/9mtf+9pnP/vZs2fPYmlxKJZOvSAIPM/rdDosy6qqKssyIQS3MhqNXNftdDqyLFcqlUQigSNhCF3HhQvQdYQhFo5lcf/9h//5P8fPnYsOD/vXrtnT6VRV1XQ6HYvFsAjj8di2bc/zMplMrVbjOA6LMJvNer1eu92mlFYqFVEUcWOEEEVRZFn2PM8wDMdxNE0TRRHzEARBu93u9/u5XE5RFEIIFqTT6bRarWQyWa1WOY7DMYQhdB2NBgwDd47S2TveMXzwQe7atZbv+xsbG6Io4nZRSv/dESwtFMXSKTYajbwjkiStra0lEgmGYXBTs9ns4ODAdd3hcKgoSq1W43keR8IQuo4LF6DrCEMsHMvi0Ufxn/7TQTZ7nZDp5csMpVRV1XQ6TQjBIoRh6ByRZblWq/E8jwUZDAaWZQVBoGlaOp1mGAbHQAhRVVWWZc/zXnvtNVEUNU0TBAG3azabua7bbrclSapWqysrK1iQIAhM0xwOh4VCQZZlHI9hoNGAriMMceeKRTz11JWHHgovXRorirK5uUkpxdKbH8XS6RNF0WAwcBxnNBql0+larcbzPG4liqJut+u67mQyyWQypVKJZVkAYQjfx/PP46mnoOsIQywcy+LRR/H00zh3LhoOw3Yb3e4BwzAbGxuKojAMg3tuMpm4rmvbtiiKm5ubgiBgQXzft2271+tpmqYoCqUUJ0Qp1TRNlmXHca5cuZJOp1VV5XkeJzQYDEzTjKJobW1NkiQsTqfTabVayWSyWq2yLItjCEPoOhoNGAbmolCYvfTSbDbj9vZMlmXDMBwMBpIkEUKw9CZHsbRog8FgNBppmgZgMpn0ej3XdaMoUhRlbW2NZVncShiGnU7H87xYLJbJZFKpVCwWAxCG0N7mLuUAACAASURBVHVcuICXX4bvIwyxcCyLRx/F00/j3LloOOxeu+YAyOVyZ8+eHQ6HrVZrMBjk83lBEHCvTKfTTqdjWRbP85VKRRRFLMhkMnEcx7btdDpdq9U4jsMd4DiuUCgoiuI4zsWLF9UjHMfhGMIwtG3bdd1cLqeqKiEECxIEgWmaw+GwUCjIsozjMQw0GtB1hCHuHMvi4Ycnf/VX0zA0oij6oR/6IZZlu91uu922LEtRFFmWKaVYetOiWFo0QojjOMlkstfreZ7HcZymaZIkEUJwK77ve0cEQSgUCslkkmEYAGEIXceFC9B1hCFOA5bFo4/Onn6aOXcuGgw6V6/asVhM0zRJkgghAJLJpCAItm1fvnw5l8tls1lCCO6mKIq63a5lWSzLlkolSZKwIFEUdbtdy7I4jtvY2EgkEpgTnudLpVImk7Ft++LFi+oRSiluzPM80zQFQdja2uJ5HovjeZ5pmpIkVatVlmVxDGEIXUejAcPAXBQKePZZrK8f2HYznU7n83lCCABVVRVF6ff7juNYlqUc4TgOS29CFEuLNp1OHccZjUbZbLZcLouiiGMYDoeu63a7XVmWNzY2BEHAkTCEruPCBeg6whALx7Lgedx//+zpp5lHHokGg87Vqw6lNJ/PS5JECMHrxGKxfD4vSVKz2ez3+6urq6Io4i6YzWa9Xs+yLIZh8vl8KpViGAYLcnBw0G63oyjK5/OyLOMuiMfj5XJ5MBjYtn3x4kVN09LpdCwWw3cbjUamaQZBUCgUZFnG4gRBYJrmcDgsFAqyLON4DAONBnQdYYi5KBRmL744pbTtOL1isSjLMl6HECIfGQwGjuO88sor6XRaURRBELD0pkKxtCBRFB0cHLiuOxqN4vF4sVhcXV3FrURRNBgMHMc5PDxMp9O1Wo3neRwJQ+g6LlyAriMMsXAsi3odH/84fuzHQOl0MOi89ppLKc3n86lUimEY3IAgCBsbG67rXr16NZPJaJpGKcX89Pt9y7Imk4mmabIsE0KwIL7vW5Z1cHCgaVomkyGE4G4Sj/T7fdu2HcfRNE2WZUIIgMlk4jiOZVmappXLZUopFqfT6bRaLUmSqtUqy7I4HsPA+fMwDMwFy+KhhyZ/+ZfheLwfRezm5ubKygpuQDxyeHjouu6rr74qimImkxFFkWEYLL0ZUCzdc5PJpNvtep4XRVEmkymXy67rBkGAm5pOp71ez3GcKIoURSmXy5RSAGEI38fzz+Opp6DrCEMsHMuiXsf2Nup1MMyk0+k4jsOy7OrqqiRJDMPgVggh2Ww2mUy2Wq0rV66srq5KkoQ7NhgMLMvyfV/TNEVRCCFYkDAMbdt2HEdV1a2tLY7jcK9IkpRMJnu9nmVZjuNomgbANE2O46rVqiAIWJwgCEzTHI1GhUJBlmUcTxhC19FowDAwF4UCnn0W5XLXtpv5fD6bzTIMg1uJx+OlUknTtE6ns7+/z3FcJpNJpVKEECydbhRL95Dv+50jKysrmqZJkkQIASAIQqfTmc1mDMPgDYIg6Ha7ruuyLKuqqizLhBAAYQhdx4ULePll+D7CEAvHsqjXsb2Neh0MM/E8z3EcnueLxaIkSTghnucrlYrnefv7+6lUKpfLsSyL2zIajSzLGg6H2Wy2XC5TSrEgURR5nmdZliAIW1tb8Xgc9xzDMLIsS5Jkmua3vvWt6XS6ubm5trbGMAwWx/M80zQlSdrc3GRZFsdjGGg0oOsIQ9w5lsUjj0y/8IWIkFavN9rY2BBFESfBcVwul8tkMr1ez7bt2WymKAqWTjeKpXtiOBy6rtvtdmVZLpfLoijideLxeBAEYRhyHIfX8X3fO5JIJIrFYjKZZBgGQBhC13HhAnQdYYjTgGVRr2N7G/U6GGbieZ7jODzPl0olSZJwuxiGyWQyyWTSNM1Lly4VCgVZlnESh4eHtm33+31VVYvFIsuyWJx+v2+aJsMwpVJJkiQsThRFjuO4rlupVCil3W732rVr2Ww2kUjgnguCoNVqHR4eFovFVCqF4wlD6DoaDRgG5qJYxM4OtrZGlmUIglCtVimluC2U0kwmk06nZ7MZlk49iqW7KYqifr/ved7h4WE6na7VajzP4w0opYIgjEYjjuNwZDAYeJ7X7XbT6fTGxoYgCDgShtB1XLgAXUcY4jRgWdTr2N5GvQ4g9DzPdV2e59fW1pLJJOaB47hyudztdlutVr/fz+VyKysruJXxeGzbtud5mUymVqtxHIfFGY1GlmWNRiNN0xRFIYRgcfr9frvdZhhmfX1dFEUA2WzWdd2rV69KkqRpGs/zuFc8zzNNU5KkarVKKcXxGAYaDeg6whBzUSjMXnppxnG2YVirq6uqquKOEULwOqZpJhIJ13UrlQqWThOKpbtjMpl0u13XdQFkMplyuUwpxY0JgjAajSRJOjg4cF338PBQUZSzZ8+urKzgSBhC13HhAnQdYYjTgGVRr2N7G/U6ZrPAdT3HcURRLJfLoihi3mRZTiQS7Xb70qVLq6uriqIwDIPvJQgCx3Fc15VluVar8TyPxQmCwLZt13U1TSuVSpRSLE4QBO12u9fr5fN5RVEIITjCsmw+n1cUxbbtixcvZjKZbDbLcRzupiAIWq3W4eFhsVhMpVI4njCErqPRgGFgLlgWDz88/au/moShMR5Hm5ubgiDgLphOp1evXu31eq1W66GHHhJFEUunA8XSvPm+73lep9OJx+O5XE6SJEIIboXn+ddee20wGERRpKpquVymlOJIGELXceECdB1hiNOAZVGvY3sb9Tpms8B1PcdxRFGsVCqiKOKuYVm2VCpJktRqtfr9/urqKs/zeJ3JZOK6rm3byWRyc3NTEAQsznQ6dV3XsixJkmq1Gs/zWJwoijzPa7fbkiTVajWO4/AGHMcVi8VMJmNZ1sWLF1VVzWQyLMviLvA8r9VqpVKparVKKcXxGAYaDeg6whBzUSxiZwcbGwe23ZRlOZfLxWIx3B3FIy+//PKZM2cSiQSWTg2KpfkZDAae53W7XVmWK5VKIpHAMYRh6Hleu932PG9tbS2TyRBC8B1hiJ/+afyP/4EwxGnAsqjXsb2Neh2zWeA47r8SRXF9fT2RSOCekCRJEATLsi5dupTL5bLZLMMw0+nU8zzbtnmer1QqoihiobrdbrvdjsVilUpFFEUs1GAwaLfb0+l0bW1NkiTcFM/z5XJ5NBpZlnXp0iVVVRVFoZRiTsbjcavV8n2/VCqlUikcTxhC19FowDAwFyyLc+eiZ56ZUdq27W6hUJBlGXffAw88gKVThmLpjkVR1O/3Xdcdj8eKopw9e3ZlZQXH4Pu+67qdTkcUxUqlwnEcz/OEEHw3x0EYYuFYFvU6trdRryOKxrbtep4nSdLGxoYgCLi3KKWFQkGSJNM0e71ePB4fDAaU0lKpJEkSFmowGFiWFQSBpmnpdJphGCxOGIa2bbuum8vlVFUlhOB4BEGoVCoHBwe2bXuel81m0+k0IQR3xvO8VquVSqWq1SqlFMdjGGg0oOsIQ8xFsYidHdx3n2/bzcmEbGxs8DyPpR9UFEt3IAzDbrfrui4hJJPJpFIpSimOYTAYuK7b6/UURdnY2BAEAUCv1xsOh8lkEq/Dsvj4x/GBDyAMsSgsi3od29uo1zGd+rbtua6bSqU2NjYEQcDiJBIJRVEuX7589erV9fX1SqVCKcXijMdjy7J6vV42mz1z5kwsFsNCeZ5nmqYgCFtbWzzP4+SSR7rdrm3brutqmpZKpRiGwcmNx+NWq+X7/tramiRJOJ4whK6j0YBhYF4KBezugufdvb1mNpvVNI0QgqUfYBRLt6vZbHqeJwjC6upqMpkkhOBWoijq9/uu647HY0VR7rvvPo7j8B2JRKLb7eINtrbGPL8Shrj3WBb1Ora3Ua9jOvXbbcfzPFmWNzc3BUHAQvX7fcuyJpNJtVpdWVlpt9uvvvrq6upqMpnEPTeZTJwjsixvbW2trKxgoUajkWmaQRAUCgVZlnFnZFmWJKnb7Zqm6TiOpmmSJOEkPM9rtVqpVKparVJKcTyGgUYDuo4wxFywLB55ZPrMM7PptGnbozNnzkiShKUfeBRLt0sURVmWBUHAMUwmk26363nebDbLZDKyLFNK8d0EQWg2m9PpNBaL4choNHIc5+CgH0UPAAT3EMuiXsf2Nup1TKd+u+14nqcoytbWVjwex0INBgPLssbjcTabVRSFEAJgfX3ddd1r166l0+lcLkcpxT0xm806nY5lWRzHra+vJxIJLNRkMnEcx7IsTdPK5TKlFPNACFEURZZlz/OuX7/O87ymaaIo4lbG43Gr1fJ9f21tTZIkHJth4Px5GAbmpVjEzg5qtcN2+7ogCJubmyzLYmkJoFi6XZIk4RiCIPCOcBynaZokSYQQfC8cxxFCxuOxIAj9ft913eFwqCjKgw9Wf/RHZ//9v+PeYFnU69jeRr2OyeSw3XY9z1MUpVar8TyPhRqNRpZlDYfDbDZbLpcppfgOhmFUVRVF0TTNy5cv5/N5WZZxlx0cHLTb7SiK8vm8LMtYtG63a5omx3HValUQBMwbIURVVVmWXdd97bXXkslkNpsVBAE34Hles9mUZblarVJKcTxhCF1HowHDwLwUCrOvfx0cZ+/vm4VCQVVVLC19B8XSTR0eHsbjcdyWw8ND13U7nU4ymSyXy6Io4qYIIfF43DTNKIqCIFBVtVQqsSwL4Cd/El/5CsIQdxXLol7H9jbqdYThqNVyut1uJpOp1Wo8z2OhDg8Pbdvu9/uqqhaLRZZl8b3wPF+pVDzPazab/X4/n89zHIe7wPd9y7IODg6y2ayqqoQQLJTv++12ezgc5vP5dDrNMAzuGkppLpdLp9Ou616+fFlRFFVVeZ7H64zH41ar5ft+uVyWJAnHZhhoNKDrCEPMBcvi4YenzzwTheH10SisVquCIGBp6XUolm7g+vXrACRJisfjOKHBYOA4zsHBQTqdrlar8XgctzKZTHq9nuM4vu/ff//9sixTSvEdjz8OnkcY4i5hWdTr2N5GvY4wHLVaTq/Xy2QyZ8+eXVlZwUKNx2Pbtj3PU1W1VqtxHIdbURRFFMV2u3358uV8Pq8oCuZnMpnYR1RV3dra4jgOCxVFkeM4lmWl0+mtrS2WZXFPcBy3urqaTqcdx7l48aJ6hOM4AK7rtlqtdDpdKpUopTieMISuo9GAYWBeikXs7GBj48C2m5Ikra2tUUqxtPTdKJbeIAiCg4ODvb09nueTySSOLYqifr/vOE4QBIqiFAoFjuNwK2EYdjod13VZli0Wi91uV1EUQgjuCZZFvY7tbdTrCMNRq+X0+31FUc6ePctxHBYqCALHcVzXlWW5VqvxPI9j4zhubW2t1+u1Wq1+v5/P53mex52JosjzPMuyBEGoVquCIGDR+v2+aZqEkEqlIooi7jme50ulkqIotm1fvHgxlUoFQRCGYblcliQJx2YYaDSg6whDzAXL4ty5aGcHsZjZbnvFYjGdTmNp6XuhWHqD0WjkOA6lVFVVSimOYTKZdLtd13UZhlEURZZlSiluZTweu67b6XQEQSgWi8lkMooiz/OCIOB5Hq+TzyOfx8EB5ohlUa9jexv1OoJgaBj2YDDIZDK1Wo3jOCzUZDJxXde27WQyubm5KQgCbksqlUokEpZlXb58OZ/PK4pCCMFt6ff7pmkyDFMqlSRJwqIFQdBut3u9Xj6fVxSFEILFEQThzJkz+/v7ly5d4jiuWq2KoojjCUPoOhoNGAbmpVjEzg7uv39sWQYhpFqt8jyPpaUboFh6A57nU0fy+TxuJQgC78jKykoul5MkiRCCWxmNRt4RWZbX19cFQcCRWCwmCMJoNOJ5Hq+zsjJ7y1uYS5cwFyyLeh3b26jXMR4PDMMZDAaqqhYKBY7jsFDT6dTzPNu24/F4pVIRRRF3hlJaKBQkSWo2m/1+P5/PC4KAkxiNRpZljUYjTdMURSGEYKGiKPI8r91uS5JUq9U4jsOi+b5vmqbv+z/8wz8MwLKsbreraZosy4QQ3JhhoNGAriMMMS+FAnZ3EY97e3tNVVU1TSOEYGnpxiiW3oDn+Xw+j+Pp9/vj8bhcLouiiGMYDAaO4wwGg3Q6XavVeJ7HdxMEYTQaKYqCI1EU9ft9x3H+/b/nv/Sl4mTC4A6wLOp1bG+jXsd4PLh+3R6NRplMplAocByHhYqiqNPp2LbNsmypVJIkCfMjimK1WrUs6/Lly7lcLpvNEkJwK0EQ2Lbtum42my2VSpRSLNpgMDBNM4qitbU1SZJwCjiOY5qmoiilUolSCiCZTPZ6PcuyXNfVNC2VSuENwhC6jkYDhoF5YVk88sj0mWdmUdRqtwflclmSJCwt3QrF0p2RZVlVVdxKFEUHBweO44zHY0VRCoUCx3H4XgRBaLVasyPdbtdxnNlslk6nZfkKx61OJjHcFpZFvY7tbdTr8P2D/X3b9/1MJlMqlViWxULNZrNut2vbNoB8Pp9KpRiGwbwRQvL5vCRJzWaz3++vrq6KoogbiKLIcRzbtpPJZK1W43keizaZTCzLcl03l8upqkoIwaL5vm+a5ng8LpfLkiThOxiGkWVZkiTP81qtluu62Ww2mUziOwwDjQZ0HWGIeSkWsbODWu3Qtpscx21ubnIch6WlY6BYujOUUtxUFEXdbtdxnCiKVFWVZZlSihuLx+OHh4emafZ6vVgsJsvyP/7jP37qU5/6yldeODx8FRBxQiyLeh3b26jX4fsH+/u27/uqqpbLZUopFq3f71uWNZ1Os9lsOp1mGAZ3kyAIm5ubtm1fvXo1k8lomkYpxXfrdrvtdjsWi5XL5WQyiVPA8zzTNAVB2Nra4nkeizabzVzXNU1TUZRSqUQpxRsQQlRVTafTruvu7e0lEglN01hW0HU0GjAMzFGhMPv618Fx9v6+ubq6ms1msbR0bBRLt3L9+vVcLseyLE5oMpl4R2KxmKqqsiwTQnBTYRh6nue6LiEkl8v9wz/8w5/8yZ989atf3djY+PVf///+639tvvxyDSdRLGJnB/U6Dg/7e3v2eDxWVbVcLlNKsWiDwaDdbgdBkM1mFUUhhOCeYBhG0zRJklqt1uXLlwuFgiRJODIcDtvtdhAEmqal02mGYbBoo9Go3W6Px+NCoSDLMk4B3/dN0xyPx+VyWZIk3FQsFtM0LZ1Ou6770kt7v/Eb9+k6whDzwrJ45JHpF74QTSbGaBRsbm4mEgksLZ0ExdKNOY4TRZHneYIgKIqCYwuCwPM813Xj8XihUEgmkwzD4KaCIHCPJBIJVVVffPHFz3/+8y+88MJDDz30u7/7u0888UTu/8Cv/ArCEMf3G78xu+++/rVrdhiGqqqm02lKKRZtOBzatj0cDrPZrKIolFLcczzPr6+ve563v7+fSqVkWe4eyWaz5XKZUopFm0wmjuNYlqVp2traGqUUizabzVzXNU1TUZRSqUQpxfGwLDud5p98MmNZmKNiETs7qFaH7fZ1SZLW1tZisRiWlk6IYukGJpPJK6+8wjAMpXRlZWUymVBKcSuHh4eu63Y6HUmSzpw5I4oibsX3fcdxOp1OKpWSZfm555773Oc+Z9t2JpP5wz/8w0ajoSgKjjz+OHgeYYjj+4//kXngAfstb5H/FaUUi3Z4eGjbdr/fV1W1WCyyLIuFUhSF5/mLFy/+0z/905kzZ6rVKs/zOAW63a5pmhzHVatVQRBwCvi+32q1giAol8uSJOHYwhC6jkYDlsViTlgW585FOzugtN1quYVCQVEULC3dFoqlG+j3+8lkUlVV3/cTiQRuZTAYeJ7X7XYVRalWq/F4HLcyGo0cx+l2u4qiJJPJZ5999k//9E//+Z//+d3vfvfHPvaxc+fOnT17VpIk3AHDwAc+UPnrv6b1OhbL933HcTzPy2QytVqN4zgs2mw263Q6lmVJkqRpWq/Xa7fb+Xx+ZWUFi+P7frvdHg6H+Xw+nU4zDINFm81mruuapqkoytraGqUUx2YYaDSg6whDzEuxiJ0dPPBAYFlGEKBarfI8j6Wl20WxdAOSJJ09e3ZlZQXH0Gw2O51OJpO57777OI7DrQwGA8dxBoOBoijxePzTn/70n//5n1+9evXHf/zHf/u3f/snfuIneJ73PO+1114rFAqqquJIPo98HgcHOJF2mz72GOp17OygWMS9FwSBc0RRlFqtxvM8ToHBYGCa5nQ6zefzqVSKYZhsNttuty9dupTP5zOZDMMwuLeiKHIcx7KsdDq9tbXFsixOAd/3W61WGIZnzpxJJpM4tjCErqPRgGFgjgoF7O4iHveuXWtmMplcLkcIwdLSHaBYugF6BMejKIqmaZRS3NRsNjs4OHAcx/d9RVFGo9Hv//7vf/azn7Us6z3vec/29vaP/uiPsiyLI4qicBx3/fp13/cLhQIhhOfx4IO4dAknFYbY3cX589jdRbGIe2YymThHkslktVoVBAGngO/7lmUdHBxks9lMJhOLxXCEZdlSqSRJkmma/X5/dXU1Ho/jXun3+6ZpEkIqlYooijgFZrOZ67qmaSqKsra2RinFsRkGGg3oOsIQ88KyeOSR6JlnotnMNM1+uVyWJAlLS3eMYmkeeJ7HTUVR1O/3HccJwzCTyfR6vaeeeuov//Ivh8Ph+973vo985CPvete7CCH4bqIobmxsXL9+/bXXXiuVShzHffzj+NKXEIa4DYaB8+exs4N6HSyLu2o6nXqeZ9t2PB6vVCqiKOIUmEwm9pFMJrO1tcVxHN5AkqREImFZ1qVLl/L5vKqqhBDcTUEQtNvtXq+Xz+cVRSGE4BTwfb/VaoVheObMmWQyiWMLQ+g6Gg0YBuaoWMTODs6ePbQsg+O4arXKcRyWluaBYunYRqORIAg4oSiKut2u4ziz2SyTyVy+fPmTn/zkzs4OgPe///0f/vCH3/rWtzIMgxvgOK5SqTSbzVdffXVtba1eT9Tr2N3F7TEMPPYY6nXs7KBYxN0QRVGn07Ftm2XZUqkkSRJOgSiKPM+zLEsQhGq1KggCbiwWi62uriaTSdM0+/3+6upqIpHAXRBFked57XZbkqRarcZxHE6B2Wzmuq5pmoqilMvlWCyGYzMMNBrQdYQh5qhQmO3uMhxn7+218vl8NptlGAZLS3NCsXQMhmHEYjGe5wVBwLFNJpNut+s4TiwWy2Qy3/72tz/xiU/89V//tSiKH/rQh37hF37h4YcfxjEQQkqlkm3br776aqlU2tlJ/9APTdptitsShtjdxfnz2N1FsYg5iqKo1+vZts0wTD6fT6VSDMPgFOj3++12ezablUolSZJwPKIobmxsOI5z5coVTdOy2WwsFsP8DAYD0zSjKFpbW5MkCaeD7/vNZnMymZw5cyaZTOLYwhC6jkYDhoE5onT2lreM/9t/i4WhMRwGGxsboihiaWmuKJZuKgzDTqdz/fr1w8NDTdMSiQTLsriVMAw9z3Ndd2VlJZvNfuMb3/jUpz713HPPaZr20Y9+9EMf+lCtVsMJZbNZjuP29vZYtv35z8c++MGtZhO3zTBw/jx2d1EsYi56vZ5t29PpNJvNyrJMCMEpMBqNLMsajUaapimKQgjBSRBCNE0TRdE0zStXruTzeUmScMcmk4llWa7r5nI5VVUJITgFZrOZ67qmaSqKksvlYrEYjs0w0GhA1xGGmKNiEU89deXRR2f9/mE6nd7Y2KCUYmlp3iiWbmo4HDabzdlsViqVJEliWRY3NR6PPc9zXVcURU3TXnjhhT/+4z9+/vnnNzY2fvM3f/ODH/zgmTNncFsmk0kQBFEUWZalaerXvha+85202WRwuwwD589jZwf1OlgWt+3g4MC27fF4nM1mFUUhhOAUCILAOZLNZovFIsuyuF2CIKyvr7uuu7e3l06nc7kcpRS3y/M80zQFQdja2uJ5HqeD7/vNZnMymVQqFVEUcWxhCF1HowHDwByxLM6di3Z2MJtxV69e5Tgum81GUYSlpbuAYummZFl+4IEH2u322toabuX69eue58mynM1mn3/++T/5kz954YUXHnzwwd/5nd954okn8vk8bstkMvE8z3GclZWV9fV1nuebzeZkcu2FF9be9S6u1WJwuwwDjz2Geh07OygWcVLD4dC27dFopKpquVymlOIUiKLIdV3LspLJZK1W43ked4xhGFVVRVE0TfPy5cv5fF6WZZzQaDRqt9vj8bhQKMiyjNNhNpu5rttqtVRV1TQtFovh2AwDjQZ0HWGIOSoWsbODBx4IbLsZRdHb3va22WxmWdalS5ey2ayiKJRSLC3ND8UPvG9+85ulUimXy+EGOI5bW1vDMciyTAj58pe//KlPfeob3/jG2972tj/4gz9oNBqKouC2TCYTz/Mcx+F5vlQqSZKEI+Vyud1udzpX/v7v1558Mv7tb9MwxO0JQ+zu4vx57O6iWMQxHR4e2rbd7/dVVS0WiyzL4nTodruWZRFCyuVyMpnEXPE8X6lUPM9rNpv9fj+fz3Mch2OYTCaO41iWpWna2toapRSnw+HhYavVmkwm6+vroijiJAwD58/DMDBfhQJ2dyEInWvXDEVR8vk8IQRApVIZDAaWZbmum81mFUUhhGBpaR4ofrDZtv3Vr371rW99a6vVOnfuHO7MxYsXP/zhD3/7299+97vf/elPf/p973tfMpnEbQnD0PM813V5nl9bW0smk3gdQsjq6urKysr161e/9KXC3p7aaMAwcNsMA+fPY2cH9TpYFjfh+77jOJ7nqapaq9U4jsPpMBwO2+12EASapsmyTAjB3aEoiiiK7Xb78uXL+XxeURTcVLfbNU2T47hqtSoIAk6H2WzmOI5pmqqqapoWi8VwbGEIXUejAcPAHLEszp2LvvCFaDYzW61+qVSSZRmvIx7p9/uWZbmuq2laKpUihGBp6c5Q/GAbj8cPP/ywLMurq6u4Y/Ujv/Vbv/We97yH53ncliAIOp2O4ziCIJTLZVEUfUe/GQAAIABJREFUcQOKonAct7+/v7YWvPRS/u1vZ5pNBrfLMPDYY6jXsbODYhFvFASBc0RRlFqtxvM8TocgCCzL6nQ62Wy2XC5TSnGXcRy3trbW6/VarVa/38/n8zzP4w1832+328PhMJ/Pp9NphmFwOhweHrZarel0ur6+LooiTsIw0GhA1xGGmKNiETs7uO8+v92+zrLs5ubmysoKvhdJkkRR7PV6lmW5rqtpmiRJWFq6AxQ/2EqlEqU0n8/jeCzLkmWZ4zjcwB/90R+xLIvbEgSB53mO44iieObMGVEUcSuiKG5sbFy/fp2Qa1/7Wumd76TNJoPbFYbY3cX589jdRbGI/2cymThHJEmqVquCIOB0mEwmruvatp1Kpba2tniexz2USqUSiYRlWZcvX87n84qiEEJwJIoix3Esy0qn01tbWyzL4nSIosh1XdM0VVXVNC0Wi+HYwhC6jkYDhoH5KhSwu4uVFWdvr5XL5bLZLMMwuDFCSDqdTqVSnucZhuE4jqZpoihiaem2UPzAy+fzOIZ2uw3glVdeEUXxgQce4Hke3wvLsji5IAjcI6Iorq+vJxIJHNvKykqlUmm1WsPhq//zf5afeIL71rdiYYjbZhg4fx67uygWMZlMPM9zHCcej1cqFVEUcTrMZrNOp2NZFsdxlUpFFEUsAqW0UChIktRsNnu93urqqiAI/X7fNE1CSKVSEUURp8bh4WGr1ZpMJuvr66Io4iQMA40GdB1hiDliWTzyyPQLX4im05bjjNbX10VRxPEQQlRVlWXZ87xr164lEglN0wRBwNLSCVEsHYPv+7ZtdzqdTCaTzWZ5nsecBEHgOI7neclkcmNjQxAEnFwsFiuVStb/ceUrXym9+qrcaMAwcNsMA+fP47/8l16hYMbjtFQqSZKEU2MwGLTb7clkks/nU6kUwzBYKFEUq9WqZVn/8i//QillGGZ1dVVRFEIITofZbOY4jmma2SOxWAzHFobQdTQaMAzMV7GInR1Uq0PbbgqCUK1WKaU4IUqppmmyLLuue+XKFVmWc7kcx3FYWjo2iqVj4Hm+VquZplkulzEn4/HYPZJKpTY2NgRBwJ3RNI3juOvXr1cq493d3NvehmYTt80w8JM/mbr/fu7LX+YlicHp4Pu+ZVn9fl/TtEwmE4vFcGpQSgGMRiNJknieJ4TgdBiNRqZpTiaT9fV1URRxEoaBRgO6jjDEHLEszp2LdnbAslazaRcKhUwmgzvAcdzq6qqiKN1ul+M4LC2dBMXS8XAcVy6XMQ++77tHZFne3NwUBAFzIsvyysrK/v4+z49ffLHwIz8SazYZ3K4wxLe+FX/727G7i2IRizWZTBzHsSwrk8nUajWO43BqDAYD0zSjKKpWq6Iouq772muvKYqiaRqlFIsTRZHjOKZpakcIITi2MISuo9GAYWC+ikXs7OCBBwLbbo7H0ebmpiAImIeVlZVcLoelpROiWLqHfN93HMfzvHQ6vbW1FY/HMW/xeHx9fd0wjMnktRdeWHvsMa7ZZHAHDAPnz2NnB/U6WBb3XhRFnU6n3W4LglCtVgVBwKkxmUwsy3JdN5fLqapKCAGQzWaTyaRpmleuXFldXZUkCYswGo1M05xOpxsbG6Io4iQMA40GdB1hiPkqFrG7i0Siu7/flGU5l8vFYjHcNbZti6Jo23a5XMbS0g1QLN0Tvu87juN5nqIotVqN53ncNSzLlstl0zS73St/93flJ5/kv/1tGoa4bYaBxx5DvY6dHRSLuJf6/X673Z7NZsViMZVK4TTxPK/dbsfj8a2tLZ7n8To8z1cqFc/z9vf3U6mUpmkcx+FeiaLIcRzTNLUjhBAcWxhC19FowDAwXyyLc+eiZ56ZMUy72ewWCgVZlnE3+b4fBMGLL77I8zwhRJZlURSxtPQGFEv3BM/zAGq1Gs/zuPsIIYVCYWVlxTBe/dKXCnt7aqMBw8BtC0Ps7uL8eezuoljEPXB4eNhut0ejkaZpiqIQQnBqjEajdrs9Ho9XV1dlWcYNKIoiiqJpmpcvX15dXU2n07j7RqNRq9WKomhjY0MURZyEYaDRgK4jDDFfxSJ2dnDffb5tNycTsrGxwfM87jKe54vF4nA4FASB53lRFLG09L1QLN0rpVIJ91Ymk1lZWdnb21tbC156Kf/2t5NmE3fCMHD+PHZ3USzi7gmCwDmiqmqxWGRZFqfGZDJxHMeyrGw2u7a2RinFTXEcVy6Xu91uq9Xq9/v5fH5lZQV3RxRFjuOYpqkdIYTgJAwD58/DMDBfLItHH509+yzD8+7eXlPTtGw2SwjBvVKr1bC0dFMUS9/XRFHc2NgwDCMW2/va14rveAcxzRjugGHg/Hns7KBeB8tivqIocl3XsixRFLe2tuLxOE6TbrdrmibHcdVqVRAEHJssy6IomqZ56dKlfD6fyWQYhsFcjUajVqsVRdHGxoYoijiJMISuo9GAYWC+ikXs7ODhh6e23bTtUaVSSSaTWFo6ZSiW5sr3fZ7ncZrwPF+pVJrN5sHBpS9+Mfkf/kPun/6JC0PcNsPAY4+hXsfODopFzEu327UsixCytrYmSRJOE9/32+32cDjM5/PpdJphGJwQpbRUKkmSZJpmv99fXV2Nx+OYhyiKHMcxTVM7QgjBSRgGGg3oOsIQ81UsYncXqdTg2rXrgiBsbm6yLIulpdOHYmlOXNe9dOnS5uZmFEWCIOA0mc1mKysr+/v7vm9+8Ysx0yw0GjAM3LYwxO4uzp/H7i6KRdyh4XDYbrfH43Eul5NlmRCCUyOKIsdxLMtKp9NbW1ssy+IOSJKUSCQsy7p06VI+n1dVlRCCOzAajVqt1mw229jYEEURJxGG0HU0GjAMzBfL4ty52bPPgmXtV181C4WCqqpYWjqtKJbumO/75hFJkrrdbjabxakRRZHneY7jsCz70EMPTafT69evr6/Tr389+/a3M4aBO2EYOH8eOzuo18GyuA1BEFiW1el0stlsuVymlOI0OTg4aLVahJBKpSKKIuYhFoutrq4mk0nTNPv9/urqaiKRwMlFUeQ4jmma2hFCCE7CMNBoQNcRhpivYhE7O3jLWwLbbo5GYbVaFQQBS0unGMXSHeN5PpfLCYKgaRpOjSiKer2ebdsMw6yurqZSKRzhOG5/f18Qxi++WHjHO0izyeAOGAYeewz1OnZ2UCzi+KbTqeu6lmWlUqmtrS2e53GaBEFgWVa3283n84qiEEIwV6IobmxsOI5z5coVTdOy2WwsFsOxjUajVqs1m802NzcTiQROIgyh62g0YBiYu2IRu7sQxd7enpFKpdbW1iilWFo63SiW5iF+BKdGr9ezLCuKomw2K8syIQTfIQjC+vq6YRjT6dV/+Ifyu97FNpsM7kAYYncX589jdxfFIm5pNpt1u912u81xXKVSEUURp0kURZ7ntdvtZDJZq9U4jsPdQQjRNC2ZTLZarStXruTzeUmScCtRFDmOY5qmdoQQgpMwDDQa0HWEIeaLZXHuXLSzA4Yx9/e9YrGYTqextPRmQLH0/eXg4MC27SAIVFVVFIUQgjfgOO7MmTOmafZ6V/7+78tPPrnyrW/RMMSdMAycP4/dXRSLuInBYNBut8MwzOVysiwzDIPTZDAYtNvt6XS6trYmSRLuvng8vr6+7rru3t6eLMv5fJ5SihsYjUbNZnM2m21ubiYSCZxEGELX0WjAMDB3xSJ2dnD//WPLMggh1WqV53ksLb1JUCx9vxgOh7Ztj0YjVVUVRaGU4sYIIYVCgeO4ZvPKl79ceu01pdGAYeBOGAbOn8fODup1sCz+Dd/3Lcvq9/uapmUymVgshtNkMplYluW6bi6XU1WVEIJ7hWEYVVWTyWSr1bp8+XI+n5dlGd8tiiLHcUzTzOVy2WyWEIKTMAw0GtB1hCHmi2Xx6KOzZ59l4nFvb6+pqqqmaYQQLC29eVAsvfmNRiPHcfr9vqqqpVKJUorjUVWV47jr16+vrfkvvZR/+9tJs4k7YRh47DHU69jZQbGI/2symTiOY1mWoii1Wo3jOJwynue12+14PL61tcXzPBZhZWWlUql0Op1ms9nv9/P5PMdxODIajZrNJoDNzc1EIoGTCEPoOhoNGAbmrljEzg4efnjqOC3LGpbLZUmScApcvXoVwPr6OpaWjoFi6c3M933HcTzPU1W19v+3Bze/baSHHYB/M3pnOBpR/P4YciitRI28yWbjWETb2S7gQy49FQhQZtP21nMvvfTSnvsPFOitlx6SI4WiRZEg6TYogl3vHErYaLrZJrLsFfkOyRFFURQlSxyKamGgRdp8WSvRpsTf89y7p+s6rigWi5XL5WazKcTexx+X3n9/wfcVXEMYwvPguvA8FAqTw8PDIAgMw3AcxzRNzJjT09NOp3N+fl4oFBKJBN60ZDK5tLQUBMHOzo5lWYlEYn9/v9Pp5PP5bDarqiquQkpUq6jXEYa4cbYNz0M8Ptzbk4ZhlMtlXdcxAz777DMhxN///d+//xKIfhMBup1Go1H3pVQqde/ePcMw8EUZhrG2tub7/tnZ7r/+68of/7H+5MlCGOI6pITr4q//2v/yl1/YdjEej2PGjMfjbrcbBEE2m11dXV1YWMBs0HW9VCoNBoNnz559+umnqVTKcRzTNHFFUsJ1ISVunKbhwYPL7W1o2v7ubrtQKGSzWcyML33pS//+7//+1a9+dX19HUSvQIBum/F43H0pFos5jmOaJq5NCLGyshIEwf7+0+9+d+Xp03i1CilxHVLij/7I/spXzv/pn4x4HDOl3+93Oh1N0xzHMU0TM2Yymbx48eLy8jKRSIzH45OTE8MwVFXFqwlD1OuoViElbpxto1bDu++G+/v+6eloY2NjaWkJM+arL4Ho1QjQ7TEej3u9XrfbNU1zfX19aWkJN0dRlHw+H4lEms3G+vq55+VcF1LiOsZj5ckTw3XhebBtzIKzs7NOp3NycmJZVjKZVBQFM+bk5KTVagG4d++eaZrD4dD3/cFgUCgUTNPEbyIlqlXU6whD3DjbhuchGj36/HMZi8VKpZIQAkS3nADdBpPJpNfrdbtdXddXVlaWl5cxHYlEQtO0RqMRjY4ePSq+957i+wquR0q4LjwPto03aDKZdLvdIAiSyeTm5qamaZgxk8kkeMmyrEwmo6oqgGg06jhOEAQ7Ozu5l1RVxS8ThqjXUa1CStw4TcODB5NaDaraaTQOisViKpUC0Z0gQLNtMpn0+/39/f2FhYVCoRCPxzFlS0tL5XK52WwCzz/6aOWDD9QnTxbCENchJVwXtRoqFWgaXr/j4+N2u60oytraWjQaxew5OTlptVoAHMcxTRM/R1VVy7JisVir1drZ2SkWi9FoFP+XlKhWUa8jDHHjbBu1Gt55ZxQEcjSC4ziGYYDorhCg2aaq6vn5eS6Xi8fjqqritdB1fW1trdVqHR8//f73Sz/9abRahZS4Dinx8CEqFdRqsG28NqPRKAiCfr9vWVYqlVJVFTNmMpkEL1mWlclkVFXFL2Oa5vr6+sHBwfPnz1OpVC6XE0IACEPU66hWISVunKZha+tye1tZXOx9/rmfTqfz+byqqiC6QwRo5uXzeVVV8XqpqmrbdrfbbTR2NzdLnpdyXUiJ6whDeB5cF54H28a0TSaTXq/X6XRisdi9e/d0XcfsOTk5abVaABzHMU0Tv5aqqtlsdnl5ud1u7+zsFAqF4TBeraJeRxjixtk2ajXcv39xcNButwerq6uxWAxEd44AzTxVVfGGZDIZXdebzWYqNfrkk7zrwvcVXI+UcF3UaqhUoGmYkpOTk3a7fXFxsbKyEovFMHsmk0nwkmVZmUxGVVW8GsMw1tbWOp3ed7/b+/M/j0uJabBteB4SiZNGQ+q67jiOrusguosEiH6tWCxWLpcbjYaun3/0UdF1EQQarkdKPHyISgW1GmwbN2s8HgdBcHBwkM/nM5mMqqqYPcPhsN1uK4riOI5pmrgiKfGNb8SePEmOx7hxmoYHDy63t6Hr3adPW5ZlZbNZRVFAdEcJ0Aw4OTm5uLiIxWKYSYZhrK+v7+zsBMGj73wn+xd/ce/Jk4UwxHWEITwPrgvPg23jpvR6vU6ns7i4uLm5aRgGZs9kMglesiwrk8moqoqrCEPU66hWIaXAFNg2ajW8+27Y7bYOD8/L5XI0GgXRnSZAb1Sr1To8PBwOh4uLi+vr69FoFLPn7OwsCILxeJzJZC4uxt/73snOTqxahZS4JinhuvA82Dau6fT0tNPpnJ+fFwqFRCKBmTQcDlutlqqqjuOYpokrkhLVKup1hCGmwbbheVheHuztyWg0Wi6XhRAguusE6M158eKFpmlBEBSLxXv37mH2jMfjbre7v7+fTCbv3bun63qv15Py83LZ8rys60JKXJOUcF3UaqhUoGn4AsbjcbfbDYIgm82urKwIITB7JpNJ8JJlWZlMRlVVXJGUcF1IiWnQNDx4MKnVsLAQ7O11i8ViKpUC0XwQoDdncXFxYWHh/fff13UdM2YymfT7/U6nYxjGxsaGaZp4KZVK6brebDaj0fNHj4rvvaf4voLrkRIPH6JSQa0G28aVHB0dtdttTdMcxzFNEzNpOBy2Wi1VVR3HMU0TVxSGqNdRrUJKTINto1bDO++M9vf98/PJxsbG4uIiiOaGAL1Ruq5j9gwGgyAIJpNJoVBIJBL4v6LRaLlcbjabwPOPPlr54AP1yZOFMMR1hCE8D64Lz4Nt41WcnZ11Op2TkxPLspLJpKIomD2TySR4ybKsbDarKAquSEpUq6jXEYa4cZqGra3L7W3FNA8//1ym0+l8Pq+qKojmiQDRz3nx4kUQBCcnJ7lcLpVKqaqKX0bX9bW1Nd/3h8On3/9+6ac/jVarkBLXJCVcF7UaKhVoGn6VyWTS7XaDIEgmk5ubm5qmYSYNh8NWq7WwsOA4jmmauKIwRL2OahVSYhpsG7Ua7t+/ODhot1qDUqmUSCRANH8EiF4Kw7Db7e7v72cyGcdxdF3Hr6WqaqlU2t/fbzafbW7anpdyXUiJa5ISDx+iUkGtBtvGLzo+Pm6324qirK2tRaNRzKTJZNLpdPb39y3LymaziqLgiqREtYp6HWGIabBteB6SydNGo6nruuM4uq6DaC4J0NybTCa9Xi8IAtM0Nzc3FxcX8cqy2WwkEmk0Gun06JNP8q6r+D6uKQzheXBdeB5sG/9rNBoFQdDv9y3LSqVSqqpiJg2HQ9/3hRCO45imiSsKQ9TrqFYhJaZB07C1dbm9rUQi3Z0d37KsbDarKAqI5pUAzbejo6NOp6OqaqlUisViuLpYLFYulxuNhmGMPv64+P77C76v4NqkhOvC82DbmEwmvV6v0+ksLy/fu3dP13XMpIuLi/2X8vl8JpNRVRVXJCWqVdTrCENMQy43/od/EF/96rjbbXW7p+VyORqNgmi+CdC8Oj097XQ6L168yOfzyWRSVVV8UYuLi+VyWUo5Gj370Y9W//APxZMnC2GIa5ISrotvf/tFodBSlPHKykosFsOsGg6Hvu8LIRzHWVxcxBWFIep1VKuQElNi2/j2t3fj8cnu7jgWizmOI4QA0dwToPkzGo2CIOj1erlcbmVlRQiBaxNCrK6udjqdXu/p975X2tmJVauQEtckJX7v9xbfeaf4j/+ox2IqZtLFxUUQBN1u17KsdDqtqiquSEpUq6jXEYaYBk3DgweTWg2KYu7s7BiGUSgUhBAgIkCA5snFxcXBwUEQBLFY7N69e4Zh4OYoimJZlq7rzebzjY2i52VcF1LimsIQT54Yv/u78DzYNmbNcDj0fV8I4TjO4uIirigMUa+jWoWUmBLbRq2Gd94Z7e/7k8nkd37nd8bjse/7x8fHlmUZhgGi+SZA8+Hy8vLo6Kjdbmuatra2Fo1GMR2pVErX9Wazubx8/uhR4b33FN9XcG1SwnVRq6FSgaZhFlxcXARB0O12LcvKZDKKouCKpES1inodYYhp0DRsbV1ubytLS/29PZlMJvP5/MLCAgDTNIMg+NnPfmZZVjqdVlUVRPNKgObAcDgMgmA0GuVyuWQyqSgKpikajZbL5WazCTz/6KOVDz5YePJEDUNck5R4+BCVCmo12DberOFw6Pu+EMJxnMXFRVydlHBdSIkpsW3Uavja1ya9Xsf3+7ZtJxIJ/A8hRLFYjMVirVZrMBgUCgXTNEE0lwToThuPx61W6+joKJfLpVIpIQReC13X19bWfN8fDp/+4Acr//mfS9UqpMQ1hSE8D64Lz4Nt4424uLjodDoHBweFQiGdTiuKgisKQ9TrqFYhJabEtuF5SCZPm01fVdVyuWwYBn5BNBrd2NjY39/f2dnJvaSqKojmjADdaUII0zTz+byu63i9VFUtlUpBEDSbz95+u+R5CdeFlLg+KeG68DzYNl6z4XDo+74QYnNz0zAMXJ2UqFZRryMMMQ2ahq2ty+1tJRLpPn3ayuVy2WxWVVX8Cqqq5vP55eXldru9s7NTLBaj0SiI5okA3XXpdBpvTi6Xi0QijUYjmz3/5JOc6yq+j+uTEq6LWg2VCjQNr8HFxUUQBAcHB5ZlpdNpRVFwRWGIeh3VKqTElNg2ajXcv3+xv+93u6dra2vLy8t4BaZprq2t9Xq958+fp1KpXC4nhADRfBAgmrJ4PK5pWrPZNIzzjz8uvv/+gu8ruDYp8fAhKhXUarBtTNXx8XGr1RJCOI5jGAauTkpUq6jXEYaYBk3D1ha2txGPDz//vGma5sbGhqZpeGWqqmYymWg02m63d3Z2CoVCPB4H0RwQIJo+0zTL5XKz2RyPn//oRyvf+Mb4s8/M8VjB9YQhPA+uC8+DbWMaxuNxEAS9Xs+yrHQ6rSgKrigMUa+jWoWUmBLbRq2GBw8mR0fdZ886hUIhk8ngCzEMY21trdfrSSkHg0E+n9d1HUR3mgDdfqPR6OLiYnFxETNMCLG6utputxuNx3/7tyII7D/9U0tKXJ+UcF3UaqhUoGm4QcfHx61WS9M0x3EMw8DVSYlqFfU6whBTYtvwPGQy577vj8fjjY0N0zRxPalUKhqNttvtnZ0dy7JSqRSI7i4Bus0ODw8jkUi9Xn/33XcXFhZ0XccMe/GSEGI8Hr//vvA8uC6kxPVJiYcPUamgVoNt4/rG43EQBL1ez7KsdDqtKAquKAxRr6NahZSYEk3D1ha2t7G01H/61I/H46urqwsLC7gJuq6vrq72+/14PA6iO02Abq0wDPf394MgKJfL/X4/kUhgVo3H4yAIDg4Ocrnc+vr66elpo9GIx0ePHlnvvaf4voJrC0N4HlwXngfbxnUcHx+3Wi1N0xzHMQwDVyclqlXU6whDTIlto1bDgweTg4O2lIfFYjGZTOKmJRIJEN11AnRraZr21ltvpVKpTCaDGXZ4eNhutxcXFzc3Nw3DABCNRsvlcqPRWFj4/KOPSt/61sLjx2oY4vqkhOvC82Db+ALG43EQBL1ez7KsdDqtKAquKAxRr6NahZSYHtuG5yGZPG00fFVVNzY2DMPA6zIej4UQILorBOg2i7yEWfXixYt2u31+fl4oFBKJBH5OJBJZX1/3ff/0dPcHP1j57DOzWoWUuD4p4bqo1VCpQNPw6gaDQavV0nXdcRzDMHB1UqJaRb2OMMSUaBq2ti63t5XFxd7urp/JZHK5nKqqeC1Go9HZ2dmzZ8/eeuutRCIBojtBgGgKLi4u9vf3gyDIZrMrKytCCPyChYWFlZWVIAgajd233y55XsJ1ISWuT0o8fIhKBbUabBu/0Xg8DoKg1+tZlpVOpxVFwdVJCdeFlJge20athvv3L7rdVhCcrK6uxmIxvEanp6eDweD4+DgIgqWlJUVRhBAguuUEiG7a0dFRu93WNM1xHNM08Wvlcjld15vNZi438ryc60JKXF8YwvPguvA82DZ+jcFg0Gq1IpGI4ziGYeDqwhD1OqpVSIkp0TRUKqjVEI8P9/akYRjlclnXdbxeiZeEEIlE4vj4OJVKgej2E6DZ9tlnn41Go/v37+M2ODs7C4JgOBxalpVMJhVFwStIJBK6rjebzcXF848/Ln7zm8rjx2oY4vqkhOuiVkOlAk3D/zMej4Mg6PV6lmWl02lFUXB1UqJaRb2OMMSU2DZqNWxtXfb7+7u77WKxmMlk8OYUi0UApmmC6E4QoFnVarU+/fTTn/3sZ3/wB3+AmTeZTLrdbhAEiURic3NT0zRchWma6+vrUsrx+NmHH5Y+/dSoViElrk9KPHyISgW1Gmwb/2swGLRarUgk4jiOYRi4ujBEvY5qFVJiemwbnodsduT7/mg02tjYWFpaAhHdHAGaVYVCwTTN8Xh8eHiYy+Uww46Pj9vttqIoa2tr0WgUX4imaaurq+12u9HYfeedFc9bdl1IiesLQ3geXBeeB9vGeDwOgqDX61mWlU6nFUXB1UmJahX1OsIQU6Jp2NrC9jai0aOdHRmLxUqlkhACRHSjBGiGxeNx13UTiQRm1Wg0CoKg3+9blpVKpVRVxTWoqlosFnVdf/bsmW3bnpd2XUiJGyElXBcffnh8eSkjkYjjOIZh4OrCEPU6qlVIiemxbdRqePBg0ut1Go2DYrGYSqVARFMgQLMtkUhgJl1eXh4cHARBEI1GNzc3I5EIbkgmk4lEIo1GI5E4f/TIeu891fdxI6TE178e/bu/K3z963FNwxcgJapV1OsIQ0yPbcPzkE6fNZsSgOM4hmGAiKZDgOjqTk5O2u32xcVFqVSKxWK4acvLy+VyudlsCrH30Uf2t7618PixGoa4vlZL+f3fj1cqqNVg23h1YYh6HdUqpMT0aBq2ti63t5XFxd7Ojp/JZHK5nKqqIKKpESC6ivF4HARBt9vN5/PZbFZVVUyHYRhra2u+75+dPfvBD0qffWZWq5AS1xeG8Dy4LjwPto1XISWqVdTrCENMj22jVsP9+xcHB+12e7C6uhqLxUBEUyZA9MoODw/b7fbi4uK9e/cMw8DMNh3xAAAMeklEQVSUCSFWV1c7nU6jsfv22yXPS7gupMSNkBKui1oNlQo0Db9KGKJeR7UKKTE9moZKBbUa4vFho+Hruu44jq7rIKLpEyB6BS9evGi32+fn54VCIZFI4DXK5/ORSKTZbOZyI8/LuS6kxI2QEg8folJBrQbbxi+SEtUq6nWEIabHtlGrYWvr8uiou7vbsiwrm80qigIiei0EiF5BEASGYaysrAgh8NolEgld1/f29qLR0ccfF775TfXxYyUMcX1hCM+D68LzYNv4eVLCdSElpsq24XnIZke+749Go3K5HI1GQUSvkQDRK7AsKxKJ4M0xTbNcLkspJ5Pn//Ivpf/4j0i1CilxI6SE68LzYNv4b2GIeh3VKqTE9GgatrawvY3l5cHTp3J5eblUKgkhQESvlwDRK4hEInjTdF1/66232u12o7H7la+seF7UdSElboSUcF3Uavhvf/ZnqNcRhpge20athgcPJoeHwd5et1gsplIpENGbIEB0e6iqWiwWdV3f3d0tlUqel3JdSIkbISUePsR/C0NMlW3D85BOn0npTyaTjY2NxcVFENEbIkB022QyGV3Xm81mMnn+6FH+t37rIgg03IQwxFRpGra2Lre3FdM83NmRqVTKsixVVUFEb44A0Uvj8VgIgVsiFouVy+Xnz58Ph/I731n6y798+/FjNQwxy2wbtRru3784OGi3WoNSqZRIJEBEb5oAzb3BYHByctLv923bNk1TCIHb4Pz8/OLiYjKZFIuX//zP5z/5yWK1CikxgzQNlQpqNSSTp41GU9d1x3F0XQcRzQABmmPj8RjA06dPh8PhysrK6elpLBbDzBuPx+12++joqFAoJBKJIAgajd0vfankeXHXhZSYKbaNWg2VCo6Oujs7vmVZ2WxWURQQ0WwQoDkmhADw9ttvD4fDXC6H2+Do6KjVai0uLm5ubuq6DsCyrEgksre3Z1mW52VdF1JiRtg2PA/Z7KjVap+enpbL5Wg0CiKaJQI098yXMPPCMOx0OoPBoFAoJJNJ/JxkMqnreqPRiEbPHz0qVqvK48dKGOIN0jRsbWF7G8vLg91d3zRNx3GEECCiGSNAdBv0+/12u22apuM4uq7jFywtLZXL5WazCTz/4Q9LP/6xXq1CSrwRto1aDQ8eTA4Pg88/3y8Wi+l0GkQ0kwSIZlsYhp1OZzAYWJaVSqXwq+m6vra25vt+o7H7la+UPC/qupASr5ltw/OQTp9J6U8mk42NDdM0QUSzSoBohvX7/VartbS05DiOruv4TVRVLZVK3W53d3e3VCp5Xsp1ISVeD03D1tbl9raytNR/+lQmEgnLshYWFkBEM0yAaCaFYdjpdAaDgWVZqVQKV5HJZHRdbzQa6fTok0/yrqv4PqbNtlGr4Wtfm/R6Hd/v27adSCRARDNPgGj29Pv9Vqu1tLTkOI6u67i6WCy2sbGxt7cXiZx//LH9wQfq48dqGGIaNA2VCmo1JJOnjYZcWFjY2NiIRCIgottAgGiWhGHYbrePj48LhUIymcQ1GIZRLpellKPRsw8/XPn0U6NahZS4WbaNWg2VCo6Ouk+ftnK5XDabVVUVRHRLCBDNjH6/32q1lpaWHMfRdR3XJoRYXV3tdDqNxu6Xv1zyvJjrQkrcFNuG5yGXC1ut1unp6dra2vLyMojoVhEgmgGj0ajT6RwfHxcKhWQyiZujKIplWbquP3/+vFgsel7GdSElrknTsLWF7W3E48OnT5umaW5sbGiaBiK6bQSI3rR+v+/7fjQadRxH13VMQSqV0nW92WwuL58/elSoVpXHj5UwxBdj26jV8ODB5Oiou7vbLhaLmUwGRHQ7CRC9OaPRqN1uD4fDQqGQTCYxTdFotFwuN5tN4PkPf1j68Y/1ahVS4ko0DZUKajVkMue+74/HY8dxTNMEEd1aAkRvSL/f931/eXnZcRxd1zF9uq6vra35vt9o7L777ornLbkupMQrsm3UaqhUcHLSf/rUj8fjq6urCwsLIKLbTIDotRuNRu12ezgcFovFRCKB10hV1VKpFATB7u5uqVTyvKTrQkr8RrYNz0OhMGm324eHh8ViMZlMgohuPwGi16vf7/u+H41GHcfRdR1vQi6Xi0QijUYjkzn/5JP8e+8pUuJX0TRUKqjVkEye7u76qqpubGwYhgEiuhMEiF6vSCRSLBYTiQTeqHg8rmlas9k0jNHHH9vf/Kby+LEahvh/bBu1GioVHB/3dnf9TCaTz+cVRQER3RUCRK/X4kuYAaZplsvlZrM5Hj/78MPSp58a1SqkxP+ybXge8vlxq9U6OTlZXV2NxWIgortFgGiOCSFWV1c7nU6jsfvlL5c8L+a6kBKahkoFtRri8eHTp9IwjHK5rOs6iOjOESCab6qqFgqFSCTy/PnzYrHoeZm/+qvLP/kTZWvrst/f391tF4vFTCYDIrqjBIgISKVSuq43Go14fPQ3f2NdXIS+749Go42NjaWlJRDR3SVAdNMmk4mqqrhtotFouVxuNps/+cmnl5eXyWSyVCoJIUBEd5oA0c158eLFaDTa29tbWVlJJBK4bTRNMwxDSrm0tJRKpYQQIKK7ToDohkwmk4ODgyAITk9PC4XCZDJRVRW3x9nZWbPZVBTlt3/7t4+Pj3d3d0ulUiKRABHdaQJEN+T09DQajZ6enpZKpUwmg1ul1+v5vp/JZHK5nKqqi4uLuq43m83z8/N8Pg8iursEiG5INBqdTCaxWExVVdwe4/G43W4PBoPV1dVYLIb/kUgkdF1vNpvn5+fFYlEIASK6iwSIbo6qqrhVhsOh7/u6rjuOo+s6/i/TNNfX16WUz58/L5VKhmGAiO4cAaK5dHl52e12W62WZVnZbFZRFPwymqa99dZbrVZrd3d3ZWVleXkZRHS3CBDNn9Fo5Pv+aDQql8vRaBS/lqIoxWIxEok8e/bMtu10Og0iukMEiObMYDCQUi4vL5dKJSEEXk06ndZ1vdFonJ+fW5alqiqI6E4QIJobk8kkCIJut1ssFlOpFK5oeXm5XC43m829vT3btjVNAxHdfgJE8+Hs7Mz3/clksrGxsbi4iC/EMIy1tTXf9589e1YqlUzTBBHdcgJEc+Dw8FBKmUqlLMtSVRXXIIRYXV3tdDq7u7ulUimRSICIbjMBojttPB632+3BYFAqlRKJBG5IPp+PRCLNZnM0GuVyORDRrSVAdHednp42m01d1x3H0XUdNyqRSOi63mg0DMOIxWIgottJgOiO6na7vu9blpXNZhVFwRSYprm+vq7rOojo1hIgunNGo1G73X7x4kW5XI5Go5gmXddBRLeZANHdMhgMfN83TXNjY0MIASKiX0uA6K6YTCZBEOzv7xeLxXQ6jTdkMBgsLy8fHx/HYjEQ0cwTILoTzs7OfN+fTCYbGxumaeINuby81HX93/7t3955552jo6N4PA4imm0CRLdfv9+XUiaTyXw+v7CwgDfn+Pj4/KW9vb1isRiGoaZpIKIZJkB0+xmGYdt2IpHAmxaLxXzff/vttw3DAKBpGohotgkQ3X7GS5gNxWIRRHR7CBAREc0xASIiojkmQERENMcEiIiI5pgA0cwbDodLS0snJyfRaBRERDdKgGi2nZ2d7e/vN5vNlZUVEBHdNAGi2dZoNFRVPT09PT8/X1paAhHRjRIgmmGDwWBjYyMIgmQymUqlQER00wSIZlgsFgNgWRaIiKZDgIiIaI4JEBERzTEBIiKiOSZAREQ0xwSIiIjmmAAREdEcEyAiIppjAkRERHNMgIiIaI4JEBERzTEBIiKiOSZAREQ0xwSIiIjmmAAREdEcEyAiIppjAkRERHNMgIiIaI4JEBERzTEBIiKiOSZAREQ0xwSIiIjmmAAREdEcEyAiIppjAkRERHNMgIiIaI4JEBERzTEBIiKiOSZAREQ0xwSIiIjmmAAREdEcEyAiIppjAkRERHNMgIiIaI4JEBERzTEBIiKiOSZAREQ0xwSIiIjmmAAREdEcEyAiIppjAkRERHNMgIiIaI4JEBERzTEBIiKiOSZAREQ0xwSIiIjmmAAREdEcEyAiIppjAkRERHNMgIiIaI4JEBERzTEBIiKiOSZAREQ0xwSIiIjmmAAREdEcEyAiIppjAkRERHNMgIiIaI4JEBERzTEBIiKiOSZAREQ0xwSIiIjmmAAREdEcEyAiIppjAkRERHNMgIiIaI4JEBERzTEBIiKiOSZAREQ0xwSIiIjmmAAREdEcEyAiIppjAkRERHNMgIiIaI4JEBERzTEBIiKiOfZfUVVtHicS2mAAAAAASUVORK5CYII=", - "text/html": [ - "" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "GLMakie.plot(Γd;shading=Makie.NoShading,color=:blue)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Definition and visualization of Neumann boundary $\\Gamma_{\\rm N}$. This defines the walls of the circular ($\\Gamma_{\\rm B}$ boundary), triangular ($\\Gamma_{\\rm G}$ boundary), and square ($\\Gamma_{\\rm Y}$ boundary) holes, identified in the model with the names \"circle\", \"triangle\" and \"square\" respectively." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, "outputs": [ { "data": { @@ -457,7 +266,7 @@ "GalerkinToolkit.PhysicalDomain(…)" ] }, - "execution_count": 13, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -468,23 +277,23 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/html": [ - "" + "" ] }, - "execution_count": 14, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "GLMakie.plot(Γn;shading=Makie.NoShading,color=:blue)" + "GLMakie.plot(Γn)" ] }, { @@ -493,12 +302,12 @@ "source": [ "## FE spaces\n", "\n", - "Once we have a discretization of the computational domain, the next step is to generate a discrete approximation of the finite element spaces $V_0$ and $U_g$ (i.e. the test and trial FE spaces) of the problem. To do so, first, we are going to build a discretization of $V_0$ as the standard Conforming Lagrangian FE space (with zero boundary conditions) associated with the discretization of the computational domain. The approximation of the FE space $V_0$ is built as follows:" + "Set up a finite element space:" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -507,7 +316,7 @@ "GalerkinToolkit.LagrangeSpace(…)" ] }, - "execution_count": 15, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -517,33 +326,18 @@ "V = GT.lagrange_space(Ω,order;dirichlet_boundary=Γd)" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### TO BE EDITED...\n", - "\n", - "Here, we have used the `lagrange_space` constructor, which constructs a particular FE space (to be used as a test space) from a set of options described as positional and key-word arguments. The first positional argument is the model on top of which we want to build the space. The second positional argument contains information about the type of FE interpolation (the reference FE in this case). Here, we select a scalar-valued Lagrangian FE of order 1.\n", - "\n", - "\n", - "where the value of the shape functions will be represented with 64-bit floating point numbers. With the key-word argument `conformity` we define the regularity of the interpolation at the boundaries of the cells in the mesh. Here, we use `conformity=:H1`, which means that the resulting interpolation space is a subset of $H^1(\\Omega)$ (i.e., continuous shape functions). On the other hand, we pass the identifiers of the Dirichlet boundary via the `dirichlet_tags` argument. In this case, we mark as Dirichlet all objects of the discrete model identified with the `\"sides\"` tag. Since this is a test space, the corresponding shape functions vanishes at the Dirichlet boundary.\n", - "\n", - "\n", - "Once the space $V_0$ is discretized in the code, we proceed with the approximation of the trial space $U_g$." - ] - }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(GalerkinToolkit.Quantity(…), GalerkinToolkit.DiscreteField(…))" + "GalerkinToolkit.DiscreteField(…)" ] }, - "execution_count": 16, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -551,64 +345,50 @@ "source": [ "uhd = GT.dirichlet_field(Float64,V)\n", "g = GT.analytical_field(Ω) do x\n", - " 2.0\n", + " sum(x)\n", "end\n", - "GT.interpolate_dirichlet!(g,uhd)\n", - "\n", - "g, uhd" + "GT.interpolate_dirichlet!(g,uhd)" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 12, "metadata": {}, "outputs": [ { "data": { - "image/png": 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+ "image/png": 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SPAZVkFQlFRSARwQACRAUUoUCKinCYyKEkgFFlYETEjwmJJRMU1z89M73fG8nl/NrZ2rf9rdf88SrljOZAFNpmnrvATjnylMHBwdJkty5c8c5V6vVKpVKGIZ4kDAMm81mo9GI43h7e/vq1avVajWKomKx6JyDMS86D2PMZ09Vh8Nhu93e29uLomh9fT2Xy+EhDg8Pu91uHMfOuUajUalUgiBIU730bPudP/tHzz7XPjykKo+oggr+CYBQJQgCVCpBQpVKgCBIhSpUSYIECBIkleIIVTonqnQiBHhERJUiooSQoKjSiSjheER4DEJRMqCkKff2Di9+eue7vvs/nF9vvPWbHnvta1ay2cxkMvHe4zNks9mFhYX5+fl+vx/HcavVqlartVqtWCziQZxzc3Nzi4uLp0+f7vf7m5ubAGq1WrVazWazMOZF5GGM+WykaZokSRzHqhpF0crKSiaTwUOMRqN4Kp/PLy8vl0olEUkn+uxz7Z/5uY8+d7l9eKiq4DFQQZCEKkioUgkSqqSCBEhVkCCpCipUCYAESVWqgiBVKOAx4TGhggGpQoEAqgiEqhIIKADBY0KChCpEAEIVTkiKgIeHuPRs+x993wfPrze+4b98pFZ1tVoZ93HOVaf29/e73e7GxkYYhrVarVKpeO9xr8PDQ+99bqrRaAyHwziO7969Wy6XoygqFovOORjz+edhjPmzOTg46Ha7cRyHYdhsNsvlsnMOD7G7u9vpdJIkqVarZ86cKRQKk4mORunGrd7P/fwfP3elfThWVZCgkgSVJKhQJUBVkOARhRIklVAFj4EK5RGQUCWVqqCCIBV0oJIiVFKEBI+o0IFKBgJSVVwAVToRVToRElRSjlAVgQiFVKGAAhCqTFNcenbnB3+4k8m61ZOlv/UtTz7xxImMD3Cfualms9nv9+M4brVatVqtWq3m83m8IE3TMAwx5ZwrTx0cHCRJsrm5CSCKokqlks1mYcznk4cx5k+zt7fX6XS63W6lUlldXS0Wi3gIkoPBoN1u7+3tRVG0vr6ey+UmE718pf3z7/rYzeeTg1F6mKpOQIKkKgiokoSSqiShCh4DFSRBqIJKEiSoVBKEKo+oQgkeAxUklBSKKiUQVYhQVUSgpFBUGTghAZIQKhkIFRRSRJUiAkCVToQAlRQRkBQek3TCyWhy9Vrve9/2/nPnGt/wN8+99jUr2WyI+3jvo6m9vb04jq9fv57P56MoKpVKQRCMx2PvPe6VzWYXFhbm5+eHw2Ecx61Wq1wuR1FULBadczDm88DDGHOfTqczGAxWV1cHg0Gn09nb24uiaH19PZfL4SEmk0mv12u326oaRdHKykomk5lM9PLV9rv+1cevXGkfptQJVUEFj4EESFWAUBIECR4DCVWSUEKVBEhQqUoSJFRJQhXgEVChpCpJBCJKBhRVBI6qEgRQZSCiZEBRwpGq4gKQoIKOVKFAAFUEAUmhggFJUaUEAoIECZJCoTBN8dzl9g+9vXP27JW//vWnH3v0RKVcCAKH++SnFhYWer3e9vb25uZmFEV7e3uVSgUP4pwrTx0cHCRJsrm5CSCKomq1GoYhjPmc8jDG3EdVkyQZj8eqWq/XV1dXvfd4iMPDw2632+l0vPeNRqNarTrnJhO9crXzrl/42LXrnfGYVKqShPIIVEFSFUqQVAUJVU6BShIglKSSBJWqJABCSSpUwWNQgkolqSBBQJVORBVOqBRHqNI5UaUTUYUTkkKCSjohqRQhVCmBgFQV58AjKnQQQhXOkRSSqiICEASoTIErV9o/9pNxLvf06kr1G/7mo0+86kQm43GfTCbTaDTq9fpwOOx2uzdv3lxcXMxms8Vi0TmHB8lmswsLC/Pz88PhMI7jVqtVqVRqtVqxWHTOwZjPBQ9jzGcYjUbdbvf27duj0ej06dPlctk5h4cYjUbxVKFQOHHiRKlUEpHJRK9e6/yrd3/86rX4MFWdEKQSIJQEoUoAqgCPgAqCVJAgoUoCqlQlCRIkVQFClaqggiQAVZBUpSpIBAHm5jyJ8XiiCgakCgU8JjwmVDAgVSigkiI8JkIoGVBUGTghwWNCQkmhgEeESsoRqNJBGJAUkErBhPv76eWrnR/+0Q+dfaT+17527dHzy4VCLggc7iUipVKpWCz2+/1isbi5uSkitVqtWq2GYYgHcc6Vp0ajUZIkm5ubIlKr1arVahiGAJIkCcMwn8/DmM+ehzFmajgcxnGcJEm1Wl1ZWen3+9VqFQ+xu7vb6XSSJKnVamtra/l8HsBkojduxv/rL37i2o3O4VhVQSUJJUiqgoQqSaiShBJUkqCCU6oAoUoqCFCpBAmSSlBBkIQqVEklCRA+I69+ovmN33jiySeXAHzyk5u//Mt3nnmmPZmQSopQSRESPKJCByoZiCpFRAkhQVGlE1HC8YjwGISiZEAhQYEqRAgIj6jQQQgSVFJEyMkEV662f/yfxblssLpS/a/+xmOPPbocBA73UlUAS0tLmUxmMBh0u91Wq1WtVqMoKhQKIoIHyeVyi4uLzWZzMBh0u91Wq1WpVGq1WrfbLZVK+Xwexnz2PIyZbara7/fjON7f34+iaH19PZfLDYfDJElwH1UdDAadTmd/fz+KovPnz2ez2clER6P0zmbv3b/0ies34sNDVQUJHgOVJKggSAUJHgOPgYTyCFRBgqQSJHhEQQKkKkjwGKhQ5RQIBIE8+drmT/zEVzz+eO3u3c2NjQ1V/eqvXnnrW7/k0qXe29/x4Q9+YOswnUwmSoLHhARBUlQZOFFFIFSVQEABFRSSQoKEKkQAQhVOSIqAqhIEIEFCSaGApAiVCnEBSOiE+6P0ytXO23/8Dx9Zq3/9Wx551eMnwzCDF0wmE5JBEDjnKlOj0ajb7W5sbGQymVqtVq1Wvfd4EOdcZWo0GiVJcufOna2trTNnzpTL5TAMYcxnycOYWZWmaZIknU4HQL1eX11d9d5jyjlHUlWdc5iaTCZJknQ6HVWt1+urq6ve+8lEr9+If/Fff+L27d7BweQwVSqUIKkECSoJUEmCCh4DCSpJUEkChCoBqoIEjyiUIKmEKqgkQYWSqiRBwgfyqtc2f+zHvuJVj9cGg+T556/ncrnXve51QRB0Op0bN64uLlb/5bv+UiaTe+97b/3ET/7xM5/anihJ8IgKHYQgAFJVXABVOhGCVKGASsoRqiIQoZAqCkogIFTpnJAUipIBhQQBEFTSCUlQCE5SXLna/ql3xmfOXPurX33q3LmlUjEfBC5N0yAInHN4QS6XW1paajab/X4/juNWq1WbyufzeIhcLre4uFiv1weDweHh4bPPPlutVmu1WqFQcM7BmD8bD2Nmz2g0iuO42+3Ozc0tLCyUy2XnHD6Dc05VMTUej7vdbqfTCcNwfn6+Uqk45yYTvX4z/pVf/eT1G3GaUpWqBKEkCFWAVAUJVZJQHoEqSKqCgCpJKKlKEqqgkgQVSoJQBZUkCFCpJAgS3svjj8//0x/9isceqw4GyY0bV/P5/OrqaqFQEBEA+Xy+2WzGcby5eWtubu5Nb2r85b/8N555pv0//k9/cPHiTppSBEoKRZWBExJU0gmVDISEKiUQVYoIAFU6EQJCqCJwJIXHhAQIVTghRYRHhMdECApIgEgnvHat87P/SzebfebkicrXv2V9eamUyWScc7hXEAS1qb29vTiOb9y4kcvloigql8tBEOBBSObz+bW1tTRNkyS5fft2EATVqTAMYcyfxsOYWTIcDuM4TpKkWq2ePn26UCjgQZxzJPf29nq9XrfbLRaLKysrxWJRRCYTvXEz/te/9tSNm3GaqiqoJEFClSRUSUAVIAmAIAFClQBUAVIVIJSkggSPgYAqSZBQJQESVKqSBIkgkNe8ev7tb/8Ljz5aHQySGzeuFovFU6dOFYtF3CubzS4tLc3PzydJsrW15Zw7c6b+2//ur3/60/F3f/cfXLjYVqWSAUUJxyPCY0IFHYWiysCJKoKApFChjkIBqRRHkCChykCEQqooKE5AkFACSidCUCg8IpKmqspr1+Of/tk/Wl2pfMnrykvLo7lcGAQO98lPLS4uJkmys7OztbVVm8rlcrjXeDz23gdB4L1fXFxsNpv9fr/b7bZarWq1WqvVCoWCcw7GPISHMTNAVfv9fqfTOTg4iKLo/Pnz2WwWD7e7u7uzs5OmaaPRWFtby+fzACYT3bjd/dVff/rG8/Ek1ckEJEgQ4BEFASpJgEdAQpUklEdAQpUklCCpChL8E6BSlSCUpJIElapUAkQQyKtfPf8jP/zm8+er/X73xo2rpVLp9OnTxWIRD+e9bzQaURT1+/12u3337t0TJ6Lf/M2vf/a55Cd/8qMf/sjm4YFOqKSQIKGEkEoRAoQSjlQV50hCKEoGFBI8JiQBUaUTISCEEgGPiJCEUMlASIAgIQAJkmmK5zeS25v9f/c7rRPL5a/7q+fPnV0MAof7eO8bjUa9Xt/d3Y3j+PLly+VyuVarlUol5xymxuNxGIYiginnXHVqNBolSXL79u0gCGq1WqVSCcMQxtzHw5hXtMPDwyRJOp2Ocy6Komq16r3HQ6hqv9/vdDp7e3ve+7NnzxaLxclEDw7SrVb/Pf/mUzdvxulEqVAFQBJUkqCCRxQkCKgCpBIglAShSgAkeAxUEKRCFSRUSYCEKkmQIKkKEEEgjz8x/0M/9Obz65VeL75x42qpVFpbW8vn8/izcc5VpwaDQafT2dm5stCs/dzP/kWR8AMfuPXOn/n4xU+3daIUEVJVAoGSAYXHhAQJVYgAhCqckBQqKUdAggoGJAWkUhxBAgISVKhjQOEREfCIiFBVkOqIhzduxv/85z9y+lT0NX9p7fz6cibjcR8RKU4tLi4mSdJqtba2tqIoqlarYRiOx+NsNov75HK5xcXFZrPZ7/e73W6r1apUKlEUFQoFEYExL/Aw5hVqNBrFU/l8fmlpqVQqOefwEGmaJkkSx7GqNhqNkydPXrlyxTn//Eb31//t01tb/YPxJD1UVZBQJQkSqiSgShJK8BioJKEESVWQUCUJVZIgQSUJKkgCVAUIVVJBgEolSASBPPZE4wf/yZvX18u9Xvf69SuVSmVtbS2fz+P/l9LU3t5eHMc3b14vlUpvfGPzq77qv3jmmZ3v/f73X7zYJgmBKp2IKp0ICSopR6iKQIRCqlBAgSpECAiPqNBBCBJUKiQQEkISFFU6ERICkCBxhAQV6igT3LgZ/4tf6K6uXv+Lb145u7aUz+eCwOE+YRg2m81GozEcDuM4brVa1Wp1b28viiI8hHOuOjUajZIkuXXrVhAEtVqtUqmEYQhjAA9jXnGGw2Gn0+n1erVabW1tLZ/P4+HG43E8FYZhs9ksl8vOucPDtB2Pf/cPPnLrdpKmpHKiJEGQShIAVQFClSBIgiDBY6CSBBUEqSDBYyCpShLKI1CFKkgqQQWPKFQROHns8cbb3vamc2dLvV732rUr1Wr1kUceyefz+HPLTzWbzTiONzY2wjA8c6bxG7/21y5+uvN93/+BS5d2VAGCAioopIgqRQSAKp0IASopIqCqBAFIkFBSKCApIqSquAAkhKCACgUlEPCIiJAUkqCowoEp8Pzz8bt/JQnDi8uLlb/yVWfPPbIcBIL7OOfKU6PRKEmSq1evjkYj51ylUslkMniIXC63uLjYbDb7/X4cx61Wq1KpRFFUKBREBGaGeRjzSqGqvV6v0+mMx+Moih599NEwDPFw+/v7nU6n2+2WSqXV1dVisQhgMuHG7e5v/tannr+VTCaqCpBKgCBBBQkSqiCpBAkSSpBUggSVBKgkQQWPgQSVJEAoCUKVAEmQ4DEoEQTy+OON7/++N559pJQk8fXrV2u12rlz5+bm5vA5FYbh4uJio9FIkmR7e1u1tXKy8Z7//Ws/8Yk7P/z2P7p6tackQapQIIAqgoCkUMGApKhSAgGhSueEpFCUdCoUEABBJZ2QBIWgUFTpnJAgcYSEEBSSAlIpSHWkfP5W913v/tjqSu0r33jq3NmlbDbEg+RyuWaz2W63G41Gv99vtVrVajWKonw+j4dwzlWnRqNRt9vd2Njw3kdRVC6XwzDEVJoVxn/QAAAgAElEQVSm3nuYmeFhzMvf4eFht9uN49g5V6/XK5WK9x4PNxwO2+32YDCo1Wpnz56dm5sDMFFubib/9refuXUnOTxUEiRIKMFjUP5/wGMgQRKEkiBUAVIVJFRJQnkEqiCpCgKqVAUJVZJQBZUkqHCBPP5Y/Xv/8RvX1oq9Xvf69atRFK2vr+dyOXzeeO8bjUYURf1+//bt2zs7z2Sz2Z9955e3O8HP//wnPvqxVnqoE1UJBKSqOAceUaGDEKoIHEkhqSoiAEGASgYiPCIkVSUQUEACBAkqFRIEJIUkKASEIEEAhCoB3Hw+/t/uJCdP3Hzjl55YO7NYLBYCJ7hXmqaq2mg0vPf7+/txHF+/fj2Xy0VRVC6Xvfd4iFwut7S01Gw2B4NBHMdbW1uVSiWKokKhsLm5mcvlms0mzGzwMOblbDQaxVP5fH55eblYLDrn8BCq2u/32+32eDyOomh5eTkMw4nyYJxu7wx+699fuHUnSSeqE5LgMVBJAoSSIEjwGKgkQUKVJFRJQBUglQChJAhVAlAFSFWAIEgFCZKqJOCcPPZo/R/9wzeeOZ3v9bo3blyLomh9fT2Xy+FFMRqNer0egDNnzqhqksTN+eif/uibgyD74Y/cfte7nrr0XJtKEjwmJJQUCkilOIKECFQZiFBIiirFCQgSEKjSiRAUCo+IgFQV50BCCApJAUkR4REhCchkorduJ7/6f/TC8LnFhfJXvunMI2uLGe/xgsPDwzAMgyAAMDc3d+LEiYWFhV6vF8dxq9WqVqtRFOVyOTxEEATVqdFo1O12NzY2vPf9fv/06dMwM8PDmJchksPhsNPpDAaDWq22traWz+fxcGmaJknS6XREJIqiarXqvVfl7c3kt3/nQmt7MB6nk5SqpILEERJUEiCpChIkVUFClQR4REGAShJUklCCpCpIqJKEKkkoQVIVVPBPwAfu3LnaP/yeN54+lU+S+ObNVqPRWF9fz+VyeFGMRqOdnZ0kSer1+vr6ehiGAEajURzHGxs3i8XiG15ff/ObvvbSs50fefsfPne5o8opCEXJgEKCx4QkIKp0IgSEUCLgERGSECrViRAgSAhAgqSqiBAUAkKQIACChAhIkJgoDw4mt253f+k9vZNLlS//0pW104u5XNY5GY/HYRiKCF7gva/X61EU7e7udrvdK1euFIvFKIpKpZJzDg+Ry+WWlpaazWaSJLdv397Y2Njf36/VaoVCQURgXtE8jHlZUdUkSeI4Ho/HURQtLy+HYYiHG4/H8VQ2m11YWCiXy845Vd7ZTP7971+4s9lLD1UJKkmQ4DGoUhUkSFBBEIQqAKoCBAkqeERBgscAHgEIgiBI8Bh4DFQQJKEK59z59er3fPcbT53KJ0n8/PN36/X6+fPns9ksXhTj8bg9FUXR+vp6NpvFC3K53PLycqPRSJLkzp07mUzm5Ino3b/wnz93OX77Oz50+UpnMqEIQKjCCUmhknIEJKhgQFJAKsUpKQIBCSGUDCg8IgIeERGqigPVQSggKSI8IiQBISkUgqRMJnprM/m13+xlMpcWFkpf+eVn83MIwxD3EZHi1MLCQpIkrVZra2urVqtVq9VsNouHCIKgUCgsLCycOnWq3+9vbGx476MoqlQqmUwG5hXKw5iXifF4nCRJHMfOuUajUalUgiDAw+3t7cVTlUpldXW1WCwCUOWdreT//v2Lm1u9w1SpJMBjUB4BCR4DSAJUkiChShKq4BFAlSSU4DGQIKEESVWQUCUJElSSoJJE4FyYcV/8Rc1v/VuvW1mZS5J4Y2M7iqLz58+HYYgXxeHhYafTabfb5XL53Llzc3NzeJAwDJvNZr1e7/V67XZ7e3t7oRm96198zbVrvX/5C5/42MfvpulESapQQIEqADonPKKijgGFBAFVBEJCSIKiSgehQAASJI6QEEJJp0IBARAkRECCBAQkhCAxmVA5uX0n+ZVf/8R8I//Fr24sLi55H+BBwjBsNpuNRmM4HMZxfPfu3UqlEkVRoVBwzuE+o9Eom80WpxYWFgaDQRzHrVarUqnUarVCoSAiMK8sHsa85O3v73c6nSRJisXi8vJyqVQSETwEyeFw2Ol0hsNhrVZbX1/P5XIAVNm62/ud9356cytJU6qSBAkSVKgSBI+BBAkSqiRBkEoSPAYQqgShJAgSPAYqSVBBkAoSPAYCqgwCd/589NZveu0bXr88Hu8nSXzr1naj0VhaWgrDEC+KNE3jON7Z2SkUCmtra/l8Hn+aIAiiKKrVaoPBoN1ub29vR1H0A297k3OZj/7x5rt/6ekrl2NVpYiApPCYkAChCiekiJCq4hxJEYICEqqEE8cjIkJSSIJCgEp14pQUIQkISaEQJAUkRYRHZKJ6d2f3d9+3d+Fy7w1ftHx6dSGfn3NOcB/nXHlqNBolSXL79u0gCKIoqlQqmUwGn2E0GuVyOUwFQVCd2t/f73a7GxsbmUymVqtVKpVMJgPzSuFhzEsVycFgEMfxYDCo1Wpra2v5fB4Pp6r9fr/dbo/H43q9vry8HIYhAFW2tnu/995Lm3eTSUpVTgEkASpJECChCh4DlUqAIEEFCR4DSSVIqJIESSVIUEmAShJU8BhIUOmcO78e/f3v/E/Xz0UHB/vb23eGw2Gj0VheXg7DEC8KVY3jeHt7O5fLnTp1qlgs4rMhIuWpvb29drt9/frVarX6+v+k8eVf9pbnLnd+4qc+cuVqhyQIEiRICoVCqlBAAAQJJYQEhaBQeExIkDhCQggKSQFJESoV4hxVRQQQkBCCBAEQJABOJrizmfyfd/uZzOWF+fKXfcnpM6cWnRM8SC6XW1xcbDab/X4/juNWq1WtVmu1WqFQwNRoNCoWi7jX3FSz2RwMBt1ut9VqVacKhYKIwLzMeRjz0jOZTHq9XqfTSdM0iqLl5eUwDPFwaZomSdJut51z9Xq9Uql471U5Pkw78e7vve/TrVYvTVUJVVJBggQJVZIgCUKVAEhQSYCkKpTHVEGCBAkeURAAoQqQqiChShLKI1AFSefc+fXoO/+7Lzl3NhqN9m7f3tjb22s0GidOnMhkMnhRqGqSJNvb2977kydPlstl/Dnk8/nV1dVmsxnH8Y0bN/L5/MrJxs+982uuXO3+1D/7yLVr8UR5RFVEAIIAlQxEeESEVJVAQAEJECSoVEgQkBSSoBAQggQBECREoEoHUUeoOFCdOKVCnIMAJFQ5Ppzc2Up+47eeXlq8+YYnT6ysNHPZrHOC+zjnqlP7+/vdbvfmzZvZbDaKolKpNBqNGo0GHsR7X5va29tLkmRjYyOTydRqtUqlkslkYF62PIx5KRmPx91uN45j7329Xq9UKkEQ4OEODg663W6n05mbm1taWiqXyyKiyq27vfd+8NJOe3CYapoqFQSoJEGQBEglQJAgoEoSJFVBggQVBEGoAiAJKklQwWNQJQFVgFQChJIgVBkE8sgjje/4e29YP1ff2xveuvX8aDRqNBorKyvee7woSPZ6ve3tbQCLi4uVSkVE8LmQy+WWl5ebzWYcx5ubm865pcXGO3/6r1y7nvziLz/91NOtNFVVBiIUkqJKOHEECQhU6SB0FAqPiIBUFedIihAUkgKSIsIjQhIQkkIhSApIigiPCIWgkASFoCo2W8lv/W4/Ez43Xy992RvWVk7MOyd4kLmpZrPZ7/fjOL59+3aSJMvLy/iPyk81m81+v9/tdlutVrVardVqhUIB5mXIw5iXhv39/U6n0+12S6XSyZMni8WiiODh9vb2Op1Ot9utVqunTp0qFosAVHl3p/cHf3iptd1PU6VCSRA8oiABggQJJXgMPKIgcUQVIAlQSYKEKkmQUCUBHgMBKklQSUIJkqog4ZycO1v/9v/2S86djfb2hhsbN0ejUaPRWF1d9d7jxdLv97e3t9M0bTab1WrVOYfPNe99s9lsNBq9Xq/T6bRarUaj8Y+/58sHg733f+DKe9/fvn49VpKAECSopIiQhJBUihAgSAhAgoQqADoRAkKQIACChAhIkICAhBAkCIAgIQAJISggAULJw/Fk627v3/z2U4sL5dc/uXpqZcH7AA/ivY+m2u12v9+/efNmsViMoqhcLjvn8BDe+2hqb28vSZLnn38+DMPqlPce5uXDw5gvKJKDwaDT6ezu7tZqtbNnz87NzeHhSA4Gg06ns7u7G0XR+vp6LpcDoMqddv99H362td2fTFQVIAiQUKUSPAaCqqCSBAgSJHgMqiRBQpUkCFJJAqAqQJCggkcUJHgMVJKgwgU4d6bx9/7uGx55pLa/v/v88zfG43Gj0VhdXfXe48UyHA63t7dHo9H8/HwURUEQ4PPJOVer1arV6mAw2NraunjxYiaT+c++9MzXfe3rrl9PfuZ//ui1GzGVIClCJUUgICGEkk6FQoqAR0SEpFCpDlBxQooIjwhJQEgKhSApICkiPCIUgkISFIJCIakQp5wAW3d7v/37FxfmN5581dLKiYVcLuuc4EGcc8vLyydPnuz3+9vb21tbW7VarVqt5nI5PFx+qtls9vv9brfbarWq1WqtVisUCngBSRGBeUnyMOYLJE3Tfr/fbrdVNYqikydPZjIZPJyqJkkSx/Hh4WG9Xj9x4kQYhgBUudPpv/8jz23v9NKUU+Ax8IiCAAgSIFTx/7IH/zGy73d931/vz3x3dnZ2duY73/mxP845e8895+we/8AYnBDh2LiGmghSagEh+EecUBpoSNOiOFXVKFKlqqJS/ojUKJFArfoD4TigOshpSq0ECEghlIJwCdgY33PP73vO7uzszHd+z87OzryfndnIki37XF//uHsM7OMhQALc5SwIxJIEjoRAuEAgd7EguQNyBDgC4SBlgt26Ufmbf+Pbbt4oj0aDR48ezGazarUax3EURboo4/G42WwOh8Narba7uxtFkS7K2dnZcDg8PT194YUXQgjtdns2m129Wvkf/8H33L2X/vT/9DsPH3TmgOSuIAgGCEPg5iITDARaABnCwM2FBRMCmQkEkglkCIQkBDIJZAgTSC4FkIkFc/dGs/8r7cHKyr1qUvizb33h2pV6CKYvNJlMcrlcNputVqtJkgyHw06nc+fOnWKxmCRJoVAIIegZoihKzo3H4263+/Dhw9XV1XK5XCqVoih6/PhxPp+v1Wq69I0n0qVLF246naZp2ul0VlZWqtVqHMchBD3bbDZLz4UQqtVqqVTKZDLunJ3NO73hb/z2neZxbz7HHRAIJOSAiyWxJGdBIBAuQIglgUCOWJLz74klCbkj5CDkLrGgEMLNF8s/8ePf9uL1eDwePnr0YDabVavVcrmcyWR0USaTyfHxcbfbrVarOzs72WxWF8Xd0zRtNpvr6+t7e3tra2uSptNpmqaPHz9eXV3d2qz8g7//Fx487P7M//w7Dx52cQdjyQxhAgk5CiyYGWCAMCRDjoLjMokQDDAMASbAzFgwDGHuBJkHgkwIkyEQaMGds7P5YbP3iX/9qc1a6a1v2nnh2lYUZfQ5k8kkjmOdCyEUz52enna73YODAzNLkqRUKmWzWT1b/ly9Xu/3+51O5/DwMI7jTqdTqVR06RtSpEuXXmfuHkLQufF4nKZpp9PZ2Ni4du3a+vq6menZJpNJei6fz+/s7BQKhRCCO81W/7c++VI7Hc7OfDZ3RyxJAgQ4AoGQhNzFkgRIOCAkkLtYEg5IyEEIxJIARyB3QO4ghRBuvhj/Z3/9266/GI9Hw0ePHszn81qtVi6XQwi6KNPp9Pj4uN1uJ0myv7+/urqqC9TtdpvNZgjh6tWrxWJRn5PNZre2tqrVarfbPTo6MmtWkuTv/w/vefSo/7F/9qlPfeZ4Nps7GAhDGMaSuWNmkkCGMMAEmBkLBribRAjmTpC5ULDguCwEJAOEIQxjQSYWzAwwwGTuHB33fvXf9uvVgzferF27urmWy5lpMpnkcjl9odXV1c3NzVqt1u/30zRtNBpxHJfL5fX1dTPTM0RRlJwbj8fNZvPw8HBtba1WqxWLxSiKdOkbSaRLl15PBwcHkra2tobDYavVGo/HSZLs7e3lcjm9qvF43Gq1ut1uHMcvvvji+vq6JHeO2/3f+uSdVqs/c9zBBRICgUDu4AKEWJI7QiAQyB0QIOSOJBAOEuAuEOAuEAjEggtJKAS7up3/iR//9ps3K8NB/+GD+0CtVovjOISgi3J2dtZut1utVrFY3N/fz+VyukDj8fjo6GgymWxubsZxHELQF4miqFqtJknS7/dbrVaz2UyS5L/68NulzO9/qvHx//Mz9x90cCdjICGQSe4KATBAGJIhEJIQyEwgkEwgQyAkIZBJIEOYQEKYDIFAC+4KAZmx4Gq2eu10EP3ew6RcePPe1tnZLJvN6ksJIcTnJpNJp9N5/PhxNpstl8ulUimKIj1bPp9PkuTFF1+s1Wppmh4cHMRxnCRJPp/XpW8MkS5dej1FUdRoNIbDobtXKpVr166trKzo2YDBYNBqtcbjcZIk+/v7uVxOkjvt7uB3/r+Xm+3+fA7OghALEksC3CWEBAIh4YAQIBxHQiCQOyDAXSAQLoSQuyRAOCBcQAjh+vX4/X/5jWu508HglT/4/VcKhUK9Xo/jOISgizKbzdI0PT4+Xl9fv3HjRj6f1wWaTqfNZrPT6dRqtWvXrkVRpFcVQojPDYfDVqt1fPxyuVz+5m+qfNuf+e77Dzr/68/+7sNHXXDDWDATCwa4W8aEASbAzFgwQDLAMASYADNjwTCEAcIQhrEgEwsmIRnIEBJIyOHsbN5s9dudQWEtWi8eXtmur2azIZi+lFwut729XavV+v1+mqaNRqNcLsdxnM/n9Qzj8bhQKCTnxuNxp9N58ODB6upqkiTFYjGKIl16riJduvT6OD097XQ6T548GY/H3/zN31wsFkMIerb5fN7r9drt9nw+T5Lk2rVrKysrktxJu4Pf+XcvH7cHviQBEggEEnIXS2JJgJADLpAQCAeJJTkLAi24S4CEAwK5AwK5g+ROCOHFF0s/+tf+7PXd0mDQPz4+iaLI3SWFEMxMF8Ld0zRtNpu5XO6FF14oFAq6QPP5vN1uN5vNYrG4t7eXy+X0lSicOzk5SdP0/v37hUJha7PyU//dex487P5vP/fJR486LMkkEGjBnSAjyBAISQhkJhBIJpAhEJIQyCSQIUwgIUyG3AnBzAADZAYY5k4IZuCu4cnZb/7uvZXofjneeOsbd7fqlRBMX0oURcm58Xicpun9+/fz+XySJBsbG5lMRl9oPB7Hcaxz+XObm5v9fj9N04ODg/K5fD6vS89JpEuXvt7G43G73e50OqVS6fr1681ms1gshhD0DGdnZ51OJ03TTCZTqVTiOA4hSHJIu4Pf/f27rXQwnzsuEAgECLEguQMCgYSQQO6AWBLCXSCQkDtCLMkdEMgdEAIHJOEuITO7+WL5P/mrf2b3WnEw6N+7dzeTyWxubhaLRUndbrfRaLRarXq9XiwW9bpx926322w2oyi6evVqsVjUBQK63W6z2VxZWbl+/XqhUNBXa21t7cqVK7VardPpvPLKK9lstlqp/Pf/7Xc9etz75//iD//ws02fu7NgZoABjuQWBBkzFgyQDDAMASbAzFgwDGGAMIRh7ihYkECgBZAhJJBJLMiEQDjTM47bvV//rT+sljfeeGt7Z6seRRk9Q/7c5uZmr9drNpsHBwdJksRxnMvldM7dT05Otre39XmiKErOjcfjNE3v37+fy+WSJCkWi1EU6dLFinTp0teJuw8Gg3a7PR6PkyTZ39/P5XKz2ezg4GA+n4cQ9EUmk0l6bn19fWdnZ2Njw8wcZrN5bzD65KfutdK+O+6AECABEsgdRzggCRBLcgcXkhBIyF0CJMBdSCAQSxI4EgLhAoHcFYLt7pb/2ofetnu12O/37t+/F0XR1tZWsVgMIehckiSlUqnT6Tx58mRtba1WqxUKBX1dAb1er9lsStra2iqVSmamCzQcDo+Ojs7OzjY3N+M4NjN9zbLZ7ObmZqVS6fV6x8fHR0dHlUrlv/zPvx3Cpz/T+KVPfPbRK11wSSBDGGDuKFhwsAWBQDKBDIGQhEAmgQy5JCcEY0EmFswMMEBm7oRgQpiMBcMwDOTOcaeffnJYiQ9v7la3N2u5tVww05eysrJSrVYrlcpoNErT9M6dO8ViMUmSQqFwenoqaXV1VV9K/tzW1la/30/T9PDwMI7jcrmcz+d16aJEunTpazabzbrdbpqm7l6pVHZ3d6Mo0rkQQhRFs9lsZWVFn2c0GrXb7W63Wy6Xb9y4kc/nJTl0uoPf+8O73f54NpvP5zgLAgmBQCB3cIGEQCAQSMhBiCWx4HIWBALhAoRYEgjkiCU5/55CsBd2y3/1A9969crGYNC/f/9eFEXb29vFYtHM9IUymUy1Wo3juNVqPXz4sFgsVqvVfD6vr4d+v99sNmezWb1ej+M4hKALNJlMms1mv9+v1+uVSiWTyejrKoqiSqVSLpcHg0G73W42m0mSvOXNtW99687Dx93/5X//f5rHJyBAGJIhEJK7JEIwdzJmCDABZsaCuQhuLkIwTCAhTIZAoAWQIUyAYSzIhEAyhAGGuXurM+j0h5nPPi4X19948+rWZjWY6Usxs8K5ra2tbrd7cHAgKZPJrKyshBD0bFEUJefG43Gaprp0sSJduvQ1OD09TdO00+msrq7W6/VisRhC0OcJIWSz2bOzs7W1NUnAYDBotVonJydJkuzv7+dyOUkO3f7w9z9zL+0O5nMccAFCLAnhLhwHIRYkliQBwnEEAiEJuQsBEiDhgJDccRdLwgEJOQiFEHavlT70/rdd2Sn0et179+6urq7u7OxsbGyYmZ4tiqKtra0kSVqt1t27d5MkqVaruVxOX63hcHh8fHxyclKv18vlciaT0QWazWatVuv4+LhcLu/v72ezWb1uQgilc8PhME3Tl156qVwuF/LZH/ng3tHx5N/8ZuuVJ10WDDABZsaCAZK5E4K5E2QuFCw4CoYhDBCGMIwFmVgwM8DcCcGQQEKYDNwtBJkEAskkcBezebsz+K3f+2w53rh5tba1WVtZWQlm+lKy2Wy9Xq9Wq4PB4M6dO5PJJJfLJUmyvr5uZnq2/DlduliRLl36qoxGo3a73e124zje3d0tFAp6hpWVlel0Op/Pe71eq9Vy90qlsru7G0WRJKDbH/7BZ++nvcF8Dg6SEAgJ5C7AXQIkEAgkBAK5yx0QIMSS3BECgRy5A2LBBVoA4SAB7gohXLta/MD73nZlu9Drde/du5vL5a5evVosFvWaZbPZnZ2dJElardbLL79cqVSq1Wo2m9VXYjweN5vN4XBYq9WuXbsWRZEukLt3u92jo6NcLnfz5s18Pq+LUjgXx/G9e/eOjo62trbe+pbr73j7Nz1+0vv5/+P3XnnawzEEQhICmQkEkglkCIQkBDIJZAgTSAiTIRBIQjJAZoBhLMhMgGEIAwzDBDKEaT4n7fS7/WF052Fpo/Atb7hRKm7oGUIIpXMvvPDCfD5//PjxyspKuVyO4ziKIl36hhHp0qWvhLv3+/00TU9OTsrl8v7+fi6X06sys0ajcXx8vLKyUqvVSqVSCEES0B0MP/XS/U53OPcF4TjCcZcDLneEQCAQIMSCxJJYkhASCOQIB4QA4YCEQCCWBLgLBAoWru0WP/CXv3Vnu9Drde/du5vL5a5evVosFvVVyeVyV69eTZKk2WzeuXOnXq8nSRJFkb6cyWRyfHzc7Xar1erOzk42m9XF6vf7zWbT3be3t+M41sVy9zRNG41GtVrd398fjUaNRiOTOa5UKv/1337X04PBJ375j15+uTVzB4wFAyQDDEOACTAzFgxDGCAMYRgLMoG7haAFkCEkkJCLIBMCmQRyJwRDgAlkBnJnNqPTHXzqs/eubZYrlcr6+rqZ6YvMZrPJZBLHcTabrdfr/X4/TdNGoxHHcZIk+Xxel74BRLp06bWZzWbdbrfdbkuqVCq7u7tRFOlVTSaTNE2fPn1qZm9605s2NjbMDJjN58PR+FMvP+j2BvM55yQWxJIAIZaEAAmQQCCQkLtYEksChByEQEIgHCSW5CwItOAugQXb3S6974e+ZXtzvdvt3L37cj6f393dLRQK+prl8/nr168Ph8Nms9lqter1epIkIQR9Kaenp61Wq91uVyqV/f391dVVXayTk5Nmszkajer1epIkIQRdrOFw2Gg03H13d7dYLEpaX1+vVqvdbrfdbjebzSRJ/vpf+7OyzGdfav7yr915+rTrLMhMIJBMIEMgJCGQSSBDmEBCmORSAMwMMEBmgGFImIwFwxAmCSQTyBACmbFgGCfTabSy8vjx45WVlSRJSqVSFEX6PJPJJJvNrqysSMpkMuVz4/E4TdMHDx7kcrkkSYrFYiaT0aXnJ9KlS1/OZDJJ07TT6aytrW1ubhaLxRCCXtVwOEzTtNvtJkly8+bNbrdbLBaB3mD4mXv3+8OT2Xzuc9wRAoFASEIgJBBICAQCAUIsyR0QCCSEhMsdEEtycBcIJOSOEEtyJ4Sws7Pxwz/4LZv1fK/XvXv3oFAovPDCC4VCQV9XhXP9fr/ZbLbb7Xq9XiqVQgj6nOl02m63W61WqVTa39/P5XK6WGdnZ8fHx61Wq1qt7u3trays6GKdnZ01m800TTc3N6vVaghBnxNCSJKkXC4PBoN2u91sNpMkecN+8pY3v+uVJ91f/Od/8OSwBy4ZYBgCTICZsWAYwgBhCLm5CMEMgUALIENI7oRgLMiEQCYhAYYhwEzCBFrPZ+bO9Gy+ubm5tbnZ6/XSNG00GuVza2trOndycrK2tmZm+jz5c1tbW91ut9VqHR4els/lcjldeh4iXbr0bMPhME3Tbrcbx/H169fX19f1qty93++naXpyclKpVG7fvr26ujqZTJrHx51+/87DR93B0Oe444glIUBiQSwJEGJJCJAACZc7jliSBIgluQNCEgKxJAES4EbvZQQAACAASURBVC4kkLtCsCs7pR/6/m/ZrK11u5179w4KhcL169cLhYJeN8VisVAo9Hq94+Pjdrtdq9VKpdJsNkvT9Pj4eH19/ebNm/l8XhfL3dM0bTab+Xx+b29vbW1NFwvodDqNRmN9fX1vby+Xy+lLMbPiufF43G6379y5E8dxtZL87f/iXU+e9v7ZP//9g0aPJckEMgRCEgKZ5K4gPFgQhrEgEwtmBhggMyGQECZjwTAMA4FkAi3BRrwyn4Erl80KZaJMcm40GnU6nbt37xYKhSRJNjY2xuNxPp/XlxJFUbVarVQqo9EoTdM7d+4Ui8VyubyxsRFC0KULFOnSpS/i7v1+v91un56eJkly+/bt1dVVvarZbNbr9drttrtXq9Xd3d0oiiQB49PT1mh0+OnPzN1BICQhkBAIBEISAiGBQEIgkCN3QCAhEAgEwuUgxJJYcIFAIHdwAcEsrIQ37Fe++7veUK+udTrpvXtPNzY2XnzxxfX1db3+QgjlcrlUKqVp+uTJk3v37kmK4/iFF14oFAq6cL1e7+joKIRw9erVYrGoCzcejxuNxnQ63dnZieNYr0H+XL1eT9P00aNHa2trlUrlJ//mOw8ag1/99Zfu3m/5AsgtCA8WHJcpEGQgQ5hAQpgMgUALIDkKBhjGgkzIXSEgDDAMUd/Kzef4HEfuFNbXQiboc9bP1ev1brfbaDQODw97vd7t27f1bGZWOLe1tdXtdk9OTkqlki5drEiXLn2es7OzbrfbbrdDCEmSxHEcRZFe1XQ67XQ67XY7m83W6/VisRhCkAQMxqM7jx72BiOfuyMQLmdBLAkBEgtiSYAQS3JwF86CEAsSS5JwFw4SCISE4y4ESOBIKAS7shN/53fs7d2szeezbje9e/dJqVS6ceNGPp/XhQshmJm7SwrndLHG4/HR0dFkMqnX6+VyOYSgizWbzVqtVrPZrNfru7u7URTpK7G6urq9vV2r1brd7uHhYQihUql86H1vk8LL945//d+8fNDoggSYGQuGIQwQhjCMBZlYMDPcLQQZQgIJYTJABjIJBNq+kvM57riDY9hWLQlm+kLZbLZer1er1Xa7fXBw8PDhw2q1Wi6X19fX9WzZbLZer7u7Ll24SJcunZtMJum5fD6/vb29sbERQtCrOjk5abfb3W63UChcu3ZtY2ND54DBeHT38aP+aDif4w4IEGJJOO4C3AUCIQm5A3LHXSxJgAQCgYRAIHexJECIBRdICARyFEzbV8rv/d5v2tmOZ7Npq3XUbrfjOL5582Y+n9fFAnq9XrPZlLSzs1MqlWazWavVunfvXhzHtVotl8vpdXZ6enp8fNzpdGq12rVr16Io0oXrdruNRiObzd66dSufz+urFUVRtVpNkqTf77daraOjo0qlsn+r8sbbW08Pu//iE59uNLqOkIRAJoEMYQIJYTIEclcIgAEyAwwDXBYEGIawq7u52QxHuBy5y8ySeEPPEELIZrPXrl27cuVKt9t9+PDh6upqpVIpFouZTEbPEELQpQsX6dKfesPhsN1u93q9crl848aNfD6vL2c4HLZarcFgUC6Xb968uba2JglwfHxycvfJo8FoNJ9zTkJIIBCSEEgIBMJxhOMuJBBICAQCAUIsSIC7WJIQEgjkiCUhQEHa2Ym/73u+aWc7PpueNhoH7Xa7XC7v7e2tra3pwvX7/WazOZvN6vV6HMchBEkrKyvb29tJkhwfH9+5c6d6LpvN6nUwn8/b7Xaz2SwWi3t7e7lcThduMpk0Go3xeLy1tZUkib4eQgjxucFg0G63m81muVyuVSp/88feeXDQ/b/+5acPj3piwTCEAcIQhrEgk6NgoAWQISSQkASyTMauXstFUXAHlzsOOAs+nz95/LhWq8ZxvLKyoi9ycnKytraWP1ev13u93vHx8eHhYZIkcRzncjld+sYQ6dKfVu7e6/Xa7fZ0Ok2S5A1veEM2m9Wrcvd+v99ut09PT5Mk2dnZyWazkoDRyfj+waPReDx35nN3lwSIJQFCLIklIUBiQSwJEGJJCJAACQQC4bhLAsSSWHA5CIGETHZlu/gf/YVv2t6Oz6anhwdP0zRNkmR/fz+Xy+nCDYfDZrM5mUzq9Xq5XM5kMvpCq6urV69erVQqx8fHd+7cqZ6LokhfJ0C32z06OlpZWbl+/XqhUNCFc/dWq3V0dJQkyd7e3srKir7eNs6Nx+M0Te/evbuxsVGtVv/Gf/rOg8Pu//0vP33Y7AMmgQxhAgm5CDKxYGaAATID5GYZ5fKZK9fWMkHzOe444MLlLndFIRMymcFgcHR0FMdxkiT5fF6fZzwex3Gsc1EUVSqVJElGo1Gapnfu3CmVSkmSFAoFM9Ol5yrSpT99zs7OOp1OmqYhhEqlUiqVoijSq5rNZt1ut91uS6pUKnEcR1EkCRhNxg8PHw3H4/ncHeGAJNwFEkICgZCEQEIgEAhJCIQEAgmBQCBAyB0QCAQCCSHhYkmAmW1vF7/3u79pe6s0PZ0cPH3S6XSSJNnf38/lcrpw4/G42WwOh8N6vb67uxtFkZ5tbW1td3d3NBodHx/fuXOnVqslSZLJZPS1GQ6HzWZzOp1ubm7GcWxmunD9fr/RaIQQXnzxxUKhoNdT/ly9Xk/T9PHjx9lstlqt/vUfefvde4e/88lXnjb687kDwlwENwVhMgQCLYAMIa2s2I299dXV4M58LnfhwuXgjjs4v/Eb//q/+cWP/qW/9Jd+4Ad+QNL9+/fz+XylUikWi2bm7icnJzs7O/o8ZlY4t7m52el0njx5kslkkiSJ4ziKIl16TiJd+tNkMpmk5/L5/M7OTqFQCCHoVU2n0/RcNpvd3NwsFoshBEnAeDJ+1Hg8OBm5gwskBAKBQDggQIglsSQESCyIJQFCLAkBEiDhcgeJJUmAAEfugJCC2eZW6Xv+wzdvb5Umk5OnT17pdruVSmV/fz+Xy+nCTSaTZrPZ6/Wq1erOzk42m9Vrs36u3+83m812u12v1+M4DiHoKzeZTI6Pj3u9Xr1er1QqmUxGF246nR4dHfX7/c3NzSRJQgi6ENlsdmtrq1ardTqdg4ODNE2jKPre9+zFcfn+w9a//X/vHR33QAjDWJCJBTMDTGJ9feXGfj7KhLnjLhYcB3dw4XKXu971jm8/fPjZn/7pn/6Zn/mZ7/u+7/vABz7wlre85fDwsNFoVCqVbDZrZtlsVl/K6urq1tZWrVbr9/tpmjYajSRJ4jjO5/O6dOEiXfpTABgOh+12ezAYlMvlGzdu5PN5fTnj8ThN006ns7Gxsbu7WygUdA4Yn44fH70yOhnNHXdwsSCxJAkQS3LABUISAgmBQCAkIRASCCQEwnHkDggkBAKB3MEFCJlpZzP+C9/5pu3N0mRy8uTJK71er1Kp3L59e3V1VRfu9PS01Wq12+1KpbK/v7+6uqqvXLFY3NjY6PV6zWaz1WrV6/VSqWRmem1ms1mr1To+Pi6Xy/v7+9lsVhfO3dM0bTQapVJpb28vm83qwmUymSiKJCVJkslkWq1j9/mLL5T3b/35w6PeL//aZxrHPZAQJkMgUDYb3vSWjbW1jMN8Bs6CuxzhcuSOA07IhO981zv/4+99zx/8wR/8/M///Mc+9rFf+IVfeOc73/mhD33o3e9+d7/fbzabIYTT09O1tTU9QyaTKZ8bj8dpmuZyOV16HiJd+hPN3bvdbpqm0+k0SZKdnZ1sNqsvZzAYtNvtwWBQLpdv3bq1trYmCXB8MOo30sb49GTujgsQYklCIBAIJIQEAjngcgeEAIkFsSRAyB1cDu4CAUIsSCxJwl1CSGa2tVn67ne/cWuzdHIyfuWVx4PBIEmS27dvZ7NZXbjpdNput1utVqlU2tvbW1tb09fAzOI4LhaL3W630Wi0Wq3Nzc2NjQ29KqDT6RwdHeVyuZs3b+bzeT0Pw+Gw0Wi4++7ubrFY1PMwnU6Pjo4Gg8H29na5XJY0HA7b7fZLL72UnPuRD7y9cdT75V//TLPVZ0FmorCx8ua3bKyshLmDC+Qud+G44w6OO+5yFObKrWbN7K3nfvInf/LjH//4Rz/60R//8R+/ffv2+973vne84x21Wu3evXvr6+uVSqVQKIQQ9Az5c7r0nES69CfUdDrtdrtpmoYQqtVqsViMokivyt37/X6r1ZpOp0mS7OzsZLNZScB4Mjo8PhiMB27IDCSEBAKBQCxJAsSSACGWxJIAd+G4ywGXOyB3QAiQAAkEAgmBAHcBZrZVL77nXW/cqpfG49Hjx4+Gw2GlUtnf389ms7pws9ms3W4fHx8XCoWbN2/m83l9nYQQkiQplUppmr7yyitra2v1en19fV1fSr/fbzab7r69vR3HsZ6Hs7OzZrOZpunm5ma1Wg0h6HnodrsHBweFQuHWrVvZbFbnCucmk0mapvfv3y8UCkmS/NX3ffvRcf+P7hzeffhkbz+/UcpaCPM5uNxxZ8EdR7gcuctdODjZtRV9np2dnb/1t/7Wj/7oj/7qr/7qRz7ykX/0j/7RJz7xibe+9a3ve9/73vjGNx4cHIQQkiSJ4ziKIl36BhPp0p84JycnaZp2Op1CobCzs7OxsWFmelWz2azb7bZarRBCpVIplUpRFEkCxiejR4cPxpORzGTBzEAsCRBiQQLcBQKBhJBAICQhkBAIBEISAiGBQEIgEAgQYkFyx10gM9uuF7/rXW/arBXH49Hjx4+Gw2G1Wt3Z2clms7pw8/m80+k0m81cLnf9+vVCoaDXQSaTqdVq5XK51Wo9ePCgWCzWarW1tTV9zsnJSbPZHA6Hm5ubSZKEEHThgE6n02g01tfX9/b2crmcnofpdNpoNIbD4c7OThzH+iK5XG5nZ6darXa73adPn66srBRLG9/85qvFpGshY5ngc9xxB+Qud+Fyx8HnLDmO3LVZiTMh6Avl8/n3vve973rXu37t137tN37jN37pl37p537u59797nf/lb/yV77jO76j3+83Go0kScrl8trami59w4h06U8KYDAYpGk6GAzK5fKNGzfy+by+nNPT006nk6ZpLpfb2toqFoshBEnA6GT4+Mn98ekYk8xMJpPMcHAhgUAgIRCIJbEkQIglsSQESCyIJQFCLAkBEiCBQI5wQCGompS+851v3KwVx+PRo0cPx+NxpVK5cuXKysqKLpy7d7vdZrMZRdHVq1eLxaJeZ1EUbW1tJUnSarVefvnlJElqtVoI4fj4uNVqVavVvb29bDar52E8Hjcajel0urOzE8exnpNut3twcFAoFG7dupXNZvVs2Wy2Xq9XKpV22m4cP576zEJQMHcc4XLkzoI7Drhw4XKXu3yOTNWkGILpC7n70dFRu91+97vf/YM/+IMf/vCHf/EXf/Gf/tN/+iM/8iNvectb3v/+97/3ve9197t3725sbCRJUigUQgi69LxFuvTH33w+7/V67XZ7NpslSbKzs5PNZvXljMfj9Fwcx7u7u4VCQeeA0Xj46Mnd8WSEzEKQLcmWQEJIgBALEkuSALkjhAQCIQmBhEAgEJIQCAkEEgKBQCy43BEys81a8d3veEO9WhyNhg8fPphMJpVK5erVqysrK7pwQK/Xazabkra2tkqlkpnpomSz2Z2dnSRJms3mJz/5SWBzc/PWrVv5fF7Pw2w2a7VazWazXq/v7u5GUaTnYTqdNhqN4XC4s7MTx7Fem7nPnzTuz3xuUcYsWAg+wx13cNzlLly45o47DjgO7oSQ2azG+kKTyeTp06eSbt26lcvlJO3u7n74wx/+sR/7sX/1r/7VRz7ykZ/6qZ/6x//4H3//93//+9///mq1enBwEEJIkiSO4yiKdOn5iXTpj7PpdNrpdNI0jaKoUqmUSqVMJqNXBQwGgzRNh8NhkiT7+/u5XE4S4O79fnrQeGU0GckkmQWTycxkQSaZ4YBYcIFAQiAQCCTkyB0hlsSSECCxIJYECLEkBAjHARdgZrXKxrve/oZ6tTgcDh4+fDCZTKrV6u7ubhRFeh76/X6z2ZzNZvV6PY7jEIKeh9PT08lkUiwWQwinp6fD4TCbzUZRpIvV7XYbjUY2m71161Y+n9dz0u12Dw4OCoXCrVu3stmsXgNgNB7cffBHs/nMMhmzYMHcccCF5C4WHAd3cHC5y124QO7K5bL6PGmaHhwcVCqVzc3NEII+z8bGxg/90A/9wA/8wG//9m9/9KMf/fjHP/6zP/uz73nPez70oQ+9/e1v7/V6jUYjSZKdnR1dek4iXfrjaTwep2na6XQ2NjauXr1aKBTMTK/K3Xu9Xrvdnk6n1Wp1Z2cnm81KAkaj/sHBo96gw4KZhSCZzGQmM8lkMjOQEBIIxILEkiRALAkQcseREEgIBAIhCYGQQCDAXThIIJPVqxvf8e1vqCYbo9HwwYP7p6en1Wp1d3c3iiI9D8PhsNlsTiaTer2eJEkIQc/DeDxuNpvj8Xhzc7NcLocQhsNhs9lst9u1Wi1JkhCCXn+TyeTo6Gg0Gm1tbZXLZTPT8zCdThuNxnA43NnZieNYr810enrn7qfGJyNlgoWMgskMGQ4ud3AW3OUIlyN3OeC444476/lInzObzRqNRr/fv3btWqlU0jNkMpk/f+7v/J2/87GPfewXfuEX3v/+97/tbW/74Ac/+Bf/4l8sl8u69PxEuvTHCjAYDNrt9mg0KpfLt27dWltb05czm806nU673Q4hVKvVUqmUyWQkAaNh/8GDl8YnA8xkSzKTSbYkk5nJlmSGAwKEAEdCIBAIJIQEAiEJuYPLwV04IBx3OeByBxcIBDJTvVJ8x5+7XU02hsPBgwf3z87OarVaHMdRFOl5GI/HzWZzNBrVarXd3d0oivQ8TKfTZrOZpmm9Xr969WoURTpXONfr9Y6Pj9M0rdVqpVIphKDXh7u3Wq2jo6NKpbK3t7eysqLnpNvtHhwcFAqFW7duZbNZvQbAaNR/+eVPT2dTZTImUzCzYMHccXAH5C534bgzd3AW3OXIXSB3bVbLmRAkjUajp0+fZrPZW7duZbNZvQY3b978u3/37/7ET/zEJz7xiY985CN/7+/9vX/4D//hr/zKr9y+fVuXnpNIl/6YmM1m/X6/1Wq5e5IkV65cyWaz+nJOT0/Tc2tra9vb2xsbGyEEScBo2H/w4I9GwwEmC0FmJsmWJFuQmcwkk0lm7gghgUAgIXdAEiCWBAixJJaEAIkFOQsChFgSAhRM5UrxHd+2XylvDAb9Bw/uz2azarVaLpczmYyeh8lk0mw2+/1+tVq9cuXKysqKnof5fN5ut5vNZrFY3N/fz+Vy+iKlUmljY6Pb7TabzXa7Xa/Xi8Wivt76/X6j0QghvPjii4VCQc/JdDptNBrD4XBnZyeOY7020+npS5/9vdF4qEzGQrBgFoKFoGDIHHA5cmfBHUe4cLnLXTg4DvM5km7f3AnBjo+PDw8Pt7a2arWamekrEcfxBz/4wR/+4R/+zd/8zX/yT/7J7du3den5iXTpG950Ok3TtNPprKysVKvVOI5DCPpyxuNxu93udDpxHF+/fn19fV3ngNGwd//uH43GfclkSzIzSWYyk0lmMpPJzGRLICEQIMSCxJJYEkgICQRCEgIJgUAgJCEQEggkZLL1tei73vnWJF4fDgf379+bz+fVarVcLmcyGT0Pp6enx8fHaZpWKpX9/f1sNqvnAej1ekdHR1EUXb9+vVAo6NlCCEmSxHGcpunTp09brVa9Xi8UCvp6mE6nR0dH/X5/c3MzSZIQgp6TTqdzeHi4sbFx69atbDar1wAYDXsvffbfTc/OLBNMshBkQcFkwULwOe64g+Mud+HyOQ7uLDlzx124hLbrycb66qNHjyaTyY0bNwqFgr5aURT9B+d06bmKdOkb2Hg8Ts8Vi8Vr166tr6+bmV4VMBgM2u32aDRKkmR/fz+Xy+kcMBz0Htz9w9FogLAQZCaTzGQmM4VgZpItyCQzyWSSGQ4ICQQCCYFAIHexJECIJbEkBEgsiCUBQoCZJUnhzXvbJ6Nus/H4+MiiKKpWq+VyOYSg5+Hs7Kx1Lo7j/f39XC6n52Q4HDabzel0Wq/Xy+Wymek1CCFUq9U4jtM0ffjwYaFQqNfr+XxeXy2g3W4fHR0Vi8Vbt26trq7qOZlOp41GYzQa7ezsxHGs12Z6OvnsH/7uaDRUCJYJCkEhyMxCsBAsmDuOcDlyF+BzHNzBhctd7sLlsJbLXqnmioXos5/9oyRJbt68GUWRLv3xF+nSNx53Hw6HrVZrPB6Xy+X9/f1cLqcvx9273W673Z7NZpVK5erVqysrK5LAF7pp6+mjl4ejvmQKJjPJZDIzmZkkW5JJZjKTLQTZEkgIyR0hFiSWJAFiwYUEAiEJgYRAIBCSEAjJzCrlwp/71v1ycb3f752e9LvdrpnduHEjSRIz04WbzWbtdvv4+LhQKNy8eTOfz+s5mUwmx8fHvV6vXq8nSRJFkb5CURTV6/U4jlut1r1798rlcrVazeVy+goNh8NGo+Hu165dKxaLen46nc7h4eHGxsatW7dWVlb0GgDDQfelT39yejZVJpiZQrCFEGSmYLIgM+a44w7Ogrsc4XLkjgOOgzu5bPZ73v22tN18/PjxysrK2dnZcDgsFoshBF36Yy7SpedtOByOx+N6vS5pNpv1er12u+3uSZJcu3ZtZWVFX87Z2Vmn00nTNJPJVCqVUqmUyWQkgQ/7vScP7nQ7LQRCFiyYbEm2JDOZyUxmMkm2IJOZyUwmmeGAACEQSAgEAoGEkNzBxZJYEgIkFsSSzFQpbXzbW/fi4nq/37t//56kzc3N27dvj0ajw8PD4XC4tbWVz+d1UebzeafTaTabuVzu+vXrhUJBz8lsNmu1WsfHx+VyeX9/P5vN6muQ/f/Zg9sgR/K7TvDf70+prFQqlUqlHkpVpVLXc3tm7PFgPAYv4GMhuDv8xi9MxPmCw8E62H1xe0EcLyDiLgiCF9xGYC4WE8uTF3sBHwRwBNxyB96As43xgA2DH/Az7u6Znu6uLkmpzCxJpVJJKtX/d1XFOWIc45mumemeasL6fGx7eXk5DMM4jq9du1Y5Z9s2LuD4+Ljb7SZJsri4WKlURASXZDqdttvtw8PD5eXlIAhwMdPJ+Kuf/7vDwwMlmRFSKDwFEZAUIYVCY9SoqoEqjIExUKPGqDGqRtXAGJwYQFks5L7rza+LOnvGmG//9m/PZrO9Xq/T6URRFIZhEASWZWHuny0Lc5dNROI4LhQK/X4/TVPbtmu1mu/7IoJ7GY/H6TnXdZeXlwuFAkkAqmY46D3z1S8cHvQVChEKwTMgSAIEARIiBMAzAEGCBAkQBElVQKGAKlRhjCqgZwCoKvQMVBUKVTUKNaoKKFShClUoQLBU9L79jVtBId/v927cuJ7JZGq1mu/7IgKgUCi4rtvtdm/cuLG4uFitVkUED5IxptfrRVGUzWYbjYbv+7gkxpherxdFkW3bGxsb+Xwe94njOI1Go1wud7vda9euVc5ZloUXl6Zpu912XXd7e9txHFyeNE3b7bbv+1tbW9lsFhegaoaD3lc///R0OmFGKBmKQAgRkBRSBEIIFVSjamCMGqOnjFGjUAOjMAZGVY3mFuzvevOj1Nne3TulUqler4sIgEqlEobhYDCI4ziKovCcbduY+2fIwtxlOzk5ieN4NBpVq9Vms+l5Hi7g8PAwSZJerxcEwcbGhuu6OKdqhv3eja/8w+FBT0mCEJ4CCRAkSIDgGZAEQIIEAZ4BQRI8o6CegapCoacANaoKVahCFVAooApVKACFKtTAqBoDKpjJLJaKj+00fc/t93s3buxZllWv133fFxE8TyaTqdfrvu/v7e0NBoOlpSXP8/AAqGq/34+iiGS9Xi8WiyRxSQ4ODjqdjjGmXq8HQYAHIJfLNZvN4XDY7XavXbtWq9VKpVImk8E3Go1G7XZ7Op0uLy8HQYDLM51O2+324eHh8vJyEAS4mOn46Muf/dThcACCmQwoIEChCEmIgAIhKRQxJ2pUjVFVGANjoAbGqFFVo6fMiS7Y9r986+OD/n6/319ZWQmCAM8jIsG54XAYx/HXvva1UqkUhqHrupj7Z8XC3CUxxhwcHCRJMhqNcrncysrK0tIS7sUYMxwO4zg+OjoqlUo7OzuO4+Ccqhn292986XPDgz6gECEIAiQIgKdAkAQJAiRIkOAZgKdAggQIAqQahUIBVahCFVCowhgAqgo9A1WFQs9Az0ChBMNi/urG6mKlZIzp93vPPLNnWVa9Xi8WiyTxIlzX3djYSJLk5s2b5XK5VqtZloX7ZzAYRFE0m81qtVoQBCKCSzIej6MoOjg4qNVq5XJZRPAgeecGg0G3243juFarBUEgIgBms1kcx1EU1Wq1ZrNpWRYuz/7+fqvV8n1/a2srm83iYqbjo8/9zcemx2NKBiIQUoQiICACEQrPiECoCqNQA6MwRk8Zo0ZVDdTAGKjSc523vHG7tbebzWY3NzcXFhbwIrxzR0dHSZI8++yznueVy2XP80hi7p8DC3Ovudls1uv10jQ1xpTL5WazmSTJdDrFSzo5Oen3+3EcG2PCMGw2m5ZlAVBz6mS/27lz46vDQU8BCkGCBAGeAc+ABAkQBEmQBECCBAESJISnwDOqgEIVqgqFngL0DAA1BqqAQgFVqEIBKFQhoO97jz+yGfieOTnZ30/jOM5ms0tLS77vk8S9iEi1Wi0UCq1W65lnnllaWvJ9H6/acDiMomg8HtdqtTAMRQSX5Pj4uNvtxnFcqVS2t7dt28Zrxff9QqHQ7/ejKIrjuFarAWi327Ztb21tua6LyzOdTtvt9mg0Wl5eDoIAF6PGHPT3v/rZT04mE2YEBIWkQAgKRXhKBBQIQaGIOVFj1BhVo8bAGKiBGhhVY9Sxs2954tGT6Xj3zu16vV6tVkniXnK5XKPRqNVq+/v7d+7csW27XC4Xi0URwdzDzcLca2g8Hu+fW1hYqNVqvu+LCADXrMETcQAAIABJREFUdff391WVJF5gOp32er0kSbLZbKVSCYJARACoMQf99Pa1r/S6HaMKKkCIgARJECRIEABBgiAJngEJEiR4BuApECQBggCpRlVh9BRUoQooVKEKVahCjapCVaHQMzgV+IXHr24Ufc+cnMTdbhzHjuOsrKz4vo+XyXGctbW1NE3v3LlTLBYXFxez2SxekdFoFEXR4eFhtVptNpuWZeGSGGPSNI2iyHXd7e3tXC6H1xzJIAh832+321/4whdOTk42NzdXV1dJ4vKkadput33f39zczGazuJjp+OjLf/eJg4M+SGaEFIiAhJAUCiECEiRFKEKhMWoUamAUxkBPGTWqxiiUBTf35ONX99NkNBptbGx4noeXw7btxcXFcrnc7/e73a6qhmGIuYebhbnXxOHhYZIkvV4vCIJms+l5Hp4nl8tNp9Pj42PbtvE84/E4PZfP51dWVgqFAkkAasxBL73x+b8/6KcAQUJICHgKIEGCAM+AZ0CABAgCJEgC4BkQIEGCBAieUQUUCqgCCj0F6BkAqgo9A6OnoAqQgee9fme9WPDMyUnc7cZx7DhOo9HwfR+vFMlyuVwoFNrt9vXr15eXl4MgwMtxdHTU7XYHg0GlUllZWclms7g8g8Gg3W6TbDQavu/j8hhj4jhOkmRtbc2yrF6vd+vWrWq1ms/n8ZqbTqetVuvo6GhlZaVYLOJi1JiDXvrlp5+aTicUoRAiEFJICkgIIcJTIhSBEBQF1agxaoyq0VPGwCjUYGFh4dsfu5qB3t2947ru1taWZVl4RSzLKpfLpVJJVTH30LMw9yAZYwaDQZqmR0dHpVJpZ2fHcRy8gGVZruuORiPbtnFuOBymadrr9Uql0sbGhuu6OKfGHPSS6597etjfVwAkheAZkCBBgiQIngEBECR4BjwDEiRIkCAAngJBEiQIkGpUFaoKhTGqCihUoQpVqAIKBVQBpV/Iv35rvVjwZrNZN4qSJHEcZ3V1tVAo4H6wbbvZbPZ6vVarNRgMFhcXFxYWcC+TyaTb7aZpWi6Xd3Z2bNvG5RmNRlEUjUajWq0WhqGI4PIMBoNOp0NyfX3d8zwA1Wo1SZKbN2/6vl+r1RzHwWslTdN2u+37/tbWlmVZuJjJ0ehLn/zL4aAHEhkBCRGeEgEFQlJ4DiIgISSFQmPUqKqBKoyBMVCjxqidzb71215/0O9HUbS0tFSpVPCqiQiep91u5/P5JEnW1tYw9zCxMPdgzGazXq+XJAmAcrncbDYty8KLc113NBr5vn9wcJAkydHRURiGV69eXVhYwDk15mA/uf65pw96iQIUAUESJAiA4CmAJAgCJAjwDAiSAEGABEkAPAMQJEiQAEFQRBVQKKAKVahCFXoGgKpCz+BU4HmPbG4UC/nj4+NOpxPHsed5zWbT8zzcb0EQ5PP5Tqdz/fr1paWlMAxJ4puZTqdxHCdJEgTBzs6O4zi4PNPptNvtJklSq9UajYZlWbg80+m00+n0+/16vR6GoYjgXDabrdfrYRh2u91r166Vy+VqtWrbNh6k6XTaarWOjo5WVlaKxSIuRo052E++9KmPTydjiFCEFApBgoSQIhSBECIQoZAiICFUUE8ZGKPG6CljVMG847zx6lZ7b88Ys7m56bouHoCTk5ObN2/2+/1Wq/WGN7zB8zzMPRwszN1v4/E4TdP9/f1cLre4uOj7vojgXhzHee6554bDoTGmUqk0m03LsnBOjTnYT6595lMH/X2ogqQICIAgAZAEiVMkSBDgGZAAQYIECJ4BSQAkSBAgKQKCJHhGFXoGqgqFngL0DFShClUQLBTyj6yv+17++Pi40+nEcex53tramud5eGCy2Wyj0fB9v9VqDQaDpaUlx3HwPLPZLEmSbrdbKBQ2Nzdd18XlOTk5SZIkiiLf93d2dhzHweUxxqRp2ul0fN/f2dmxbRsvYNv2yspKuVyOoujatWuVSqVcLmezWTwAaZq2Wq1isbi1tWVZFi5mcjT64lMfGfZ7SjAjFKEQIhDhKRGAEIJCEZIgQYGQFIqYEzWqxqgqjIExcLILj1/dMbPju7t3giBYXFzMZDJ4MFbOfeUrX7ly5Uo+n8fcQ8PC3P0zHA7TNO31ekEQrK2t5fN5XMDx8XGapp1OJ03T1dXVcrksIvg6NeYLn/hI2t5VgBQIQYIEQBIkCIDgKYAkCBIkCICnQJAECQIkSJDgGYCnQIAECAKkGlUDBVShClVAoQpjAChAP+9eXV/38/nj4+N2u50kied56+vr+Xwerwnf913XjaLo+vXri4uL1WqV5MnJSZqm3W7XcZy1tTXP83Cper1ep9PJZDJra2ue5+FSDYfDTqdzcnKyurrq+z5ekuM4zWZzNBpFUXT9+vVKpRKGoWVZuE8mk0mr1RqPx41Go1gs4mLUmIM0/uJff3QyGVOEkiEFQlAoJAUiEFKEp4QQgQiFFKEIhMaoUaiBURijAPJO7vGdq739tNfrLS8vB0GAB+/RRx/F3EPGwtyrZowZDAZJkkwmkzAMr169urCwgAsYj8dJkuzv73uet7a2Ztu24zgigm90PDk6OT4W2wZxiiQIgCBBkARPASRIEOAZ8AxIkABBkARJACRIECBBgmfAM6qAQgFVhUJPAXoGJPI57+qVtUI+P51OW61Wmqa+729sbLiui9eWZVnLy8u+77fb7X6/n8vlhsOhZVmNRsP3fVyq4XAYRdF0Oq3VaqVSiSQuz/HxcbfbTZJkcXGxUqmICC7Gdd21tbWDg4Nut5umabVaLZVKIoJXJ03TVqtVLBa3trYsy8LFTEaHX/j4nx/09kFQMiBBgGdAQgRCCkmBEBTwnAgoEIJCETNTY9QYVaO2tfDY5laG3Lu7KyIbGxuO42DuW5WFuVfh+Pi41+slSSIi5XK5WCxaloULGA6HSZL0+/0wDDc2NlzXBdDv9w8PDwuFAp6HIlcefeMgjs14knFzIEECPAWeAQgSJEiC4BkQAEGCIAmeAQkSJHgG4CkQJAGCAKlGVaFnoApVQAGw4Oa3r1wpuPnJZNJqtZIkKRaLGxsbruvi8uTz+TAMb9y4cfPmzfX19bW1NcuycHkmk0kURf1+v1qtXrlyJZPJ4FKladput13X3d7edhwHL1/hXK/X63a7SZLUarVisUgSL99kMmm1WuPxeHV11fd9XIwaM0i6X/yr/3cyHlEEkoGQIqRACAqFBEGCAiEpFEIEIiApwlNCY9SoqoFRZC37TY88Ohwc3Nrbq1artVpNRDD3LczC3Cu1t7eXpqnruktLS4VCQURwL8aYwWCQJMlkMgnD8HWve51t2/i6fD7f6/XwAm6pLFbGmNnJ4cgqeCBIggQBEDwFkCBBgMQpngEBEiAIkCAJgGdAgAQJEiCEp1QBhQKqUANVBenl3M3GlYKbn0wmd+/eTdM0CILNzU3XdXGpBoNBFEWz2Wxra2thYaHT6Tz77LNLS0uFQgGvudlsFp8LgmB7e3thYQGXajQatdvt6XS6vLwcBAFenSAIfN/v9XrtdjuO41qt5vs+Xo40TVutVrFY3NrasiwLFzMZHX7+ox8+2E+VoGQgwlMiICFCCoUQgZDCMyIQQoT/RARCUBRUo2qgCtd2Hlnf7rTao9HoypUrvu9j7luehblXyvO8IAhc18UFzGazXq+XpqmqlsvlIAgsy8I3cl13b2/v5OQkk8ng3Gg0iuN4P02UoGRU9bg/UGMWqhXwDEiQIEESBM+AAAgSPAOeAQkSJEgQoJAEQRI8A1KNqkJVoTiVz3mbjaaXy08mk7t376ZpGobh9vZ2LpfDpRoOh1EUTSaTarUahqGIAFhfX0+S5NatW6VSaXFx0bIsvCZUdX9/P4oi27bX19fz+Twu1Ww2i+M4iqJardZsNi3Lwv0gImEYBkGQpunu7q7jOLVazfM83MtkMmm1WuPxeHV11fd9XNhkdPh3//cfTo5GzAiZoRAkSPCcECIQ4SkRUCAESBGSEAEJISkUGqNG1bbsnSubONHbt265rru5uZnNZjE3B1iYe6V838cFTKfT9Jxt27Vazfd9EcE3Y9u2iEwmE9d1B4NBkiSHh4dhGO7sXL02SJK7t6ACUUAnnWhhaREgeAogCYIACQI8A4IkQBAgQRIAzwA8BRIkQBAgVQGF4hTzOXd9uenl8uPx+O7du2mahmG4s7PjOA4u1Wg0iqLo8PCwWq02m03LsvB1JCuViud57Xb7xo0b9Xo9CAI8YAcHB51OxxhTr9eDIMBl6/V67Xbbtu2trS3XdXG/iUilUgmCIEmS5557rlAoVKtV13XxItI03dvbC4Jga2vLsixcjBoziKPPf/S/TI5GFAEJEjwnAhIiAEmAhAiEFKEIhCAhQiFFKAKhgkY1m7Ffv/FIv9drt9vLy8uVSgVzc19nYe4lHR0d5XI5vCJHR0dJkuzv7xcKhWaz6XkeXpKI5HK5drttjJlOp5VKpdFoZLNZAMsb22l7V41CDFQgOtlrO40VEiBBggDPgAQIEiRA8AxIAiBBggAJEgRJ8Iwq1CjAvJNbW7qSd9yjo6M7d+70er1yubyzs+M4Di7V0dFRt9sdDAaVSmVlZSWbzeKbcRxnbW0tTdO9vb3BYFCv123bxgMwHo+jKDo4OKhWq5VKRURwqcbjcafTOTw8rNfrpVKJJB4Yy7IWFxdLpVKSJDdu3AjDsFKpOI6D55lMJq1WazweN5tN3/dxYZPD4ef+4k8Pki5IiEBICoWkQARCilAIEYjw/ycQgkIRnhIBBUKAFFGDBWthu7Gxd/fu8fHx1taW67qYm3seC3MvYnd3F4Dv+7lcDi/TcDiM4/jg4KBUKm1tbeVyOdzLbDbr9/txHI/H40ceeSQIAsuy8HVeUMpYlp6cQDNQQI2qHN3ZddeaIAmCBAkC4CkQJEGCAAkSJHgG4CkQIAGCAAlF3sk368284x4dHd25c6ff75fL5atXry4sLOBSTSaTbrebpmmlUtnZ2bFtG/cShqHneZ1O58aNG/V6PQxD3D+z2ax7rlKpbG9v27aNS2WMieM4iqJSqbS9vZ3NZvGasG17aWmpVCrFcXzt2rXKOdu2ASRJ0mq1SqVSo9GwLAsXo8YMup1/+Is/nYwOkcnwlAhFKIQIhBQhBUJQKCQFIhCCp4RCiEAEBEUoAqEl2a3Vzel4euu5W77vr66uWpaFublvZGHuBabT6cHBwe3btx3HKRQKuDBjzGAwiON4Op2GYbi8vGzbNu7l+Ph4f38/SZJsNruystLr9cIwFBE8j+3kIAIR6inCCAUwZnTzFi0rt7rCTJYkeAYkSIAgSIIkABIkCJAgwTMghZJbyDdrq67jHh0d3blzZzAYhGF49epV27ZxqabTaRzHSZIEQbCzs+M4Di7Mtu3V1dV+v99qtQaDQb1edxwHr44xJk3TKIpc193a2nJdF5dtMBi0220RWVtb8zwPrznHcRqNRhiG3W732rVrxWJxOp0eHx83m03f93Fh48Ph5/7sPx+kXSUpQiFFIAQIkiBIEOA5IUQgpJAUCEFChKdEQIGQksk57ubyZhInaZqurKyUSiXMzX0zFuZeYDQaxXFsWValUrEsCxcwm816vV6SJCTDMAyCwLIs3MtkMkmSZH9/33XdlZWVQqFgjEnTdDqdOo6Db7Tg5k+mUxWhUWT0FEQAmOl0dPNWfnMdWQsgSBAkwTMgQYIESSHAUyB4SjKu4zbrV9wFdzQa3bp1azgclsvlnZ0d27ZxqWazWZIk3W63UChsbm66rotXpFgs5vP5KIpu3LhRr9fDMBQRvCKDwaDdbpNsNBq+7+OyTafTTqfT7/fr9XoYhiKCy+O67pUrV+7cuXP9+nXbtre2tjzPw8WoMf2o/Q//5U/Go0NmMjwlAhA8J4QIhBQhBUJQQBKkCCgQkkIhSIiApEjWsrebV6m8c/uOiGxtbTmOg7m5F2Fh7gUcxymeq9fruJfpdJqeW1hYWFxc9H1fRHAvo9EoPRcEwfr6uuu6OJfJZFzXHY1GjuPgeUjJ+8HRwQAKiAEEolCFKkT0xBw+82zuyqrl5kGABAgCJEgC4BmAIEFSJJ8rNOtXXMc9PDy81b41HA4rlcry8rJt27hUJycnaZp2u91cLre2tuZ5Hl4dy7KWl5d939/b2xsMBvV63XVdvByj0SiKotFoVKvVwjAUEVwqY0yapp1Ox/f9nZ0d27Zx2cbjcbvdHo/Hb37zmwFEUdTr9Wq1WhAEIoIXNxkOP/v//FE/iQAyIyBBgqAIhKBAhKdEQEKEFAohAiEIilAEQojwlJAiVjb72ObrDwbDvb29SqVSq9VEBHNzL87C3As4jlOv13Exg8FgMpk0m03P83ABw+EwjuPhcFgqlXZ2dhzHwTdyXXc0GoVhiHPGmMFgEMfxTGyIQAxUoIAYGEIEqlTV2cnh9ZuyYOevbmVsGzwDEiRIkCBAiojreleW110nf3h4+Nxzz41Go3K5vLy8bNs2LpUxZn9/v9vtZrPZRqPh+z7uH8/ztra2oii6cePG4uJitVoVEdzLdDrtdrtJklSr1UajYVkWLttwOGy328aY1dVV3/fxEIjjuN1uh2HYaDQsywJQKBT6/X4URUmS1Gq1YrGIF1Bj+p32Z//0jyejISUDAXhOBBQISaGQFIhASBEKIQIRnhIBBQQoFCEJEVJyufzm6na71RkOh81m0/d9zM3di4W5VycIgkqlgnsxxhwcHMRxPJlMwjBcXl62bRvfjOu6rVZLz/V6vTiOVbVUKt2+dStDgQiMQhQqyABQGKoIjIInJ6Oj4Ze+WnjDY7JggwRJAPwnks8XrixvuLn8cDi8efPmeDwul8uNRiObzeJSqWqv1+t2uwDq9XqxWCSJ+01E6vW67/t7e3uDwWBpacnzPLwIY0wcx91ut1Ao7OzsOI6DyzabzaIoSpJkcXGxUqmICC7beDxut9uTyaTZbPq+j68jGQSB7/tpmrZarSRJqtVqoVDA142HB5/5z384iDsAIQRJEZIQAUkRkCBBgiAJECRACkmBCIQUoQgIiEAka9s7G4/pCe7c3rVte3Nz07ZtzM1dgIW5V8eyLLwkY0yv14vj2BhTqVSCILAsCy8ul8sdHR212+1+v5/JZIIg+PSnP/3BD37w4x//y9/79ffZliAjgMIoRGEEolSFECoQNcfHgy98qfC6HavoE4AIRbx8odnYzOe84XB48+bN8XhcqVSazaZlWbhsg8EgiqKTk5NqtVoqlUjiQXJdd3Nzs9vt3rx5s1wu12o1y7LwjXq9XqfTyWQyzWazUCjgIZCmabvddl13e3vbcRxcNlVNkqTdbodh2Gg0LMvCC4hIpVIplUpJkty+fTufz9dqtZzj9Nutz/zJH05GQ1CYISkUQgQiJEGCIIVCUiACIUUohAhIEBSSAiEoFCGQzdqP7Xxbv9dvt9tLS0vVahVzcxdmYe5ednd3FxcXs9ksXqbZbJaey2QylUolCAIRwUs6Pj5O0zRJEhFZXFz867/+6w984AMf/ehHNzY2fvInf+rweLaQdSCAMRBCBaLQM1CFKpRU0ePj/j98MZN3gzd/WyabfWT7jXnXOzg4ePbZZyeTSaVSaTablmXhsg2Hw06nM51Oq9VqGIYigtcEyVqt5vt+q9W6cePG8vKy7/s4d3h42Ol0ptNprVYrlUokcdlGo1Gn05lMJsvLy0EQ4CEwHo/b7fZkMmk2m77v4yVlMplarVYqlZIkufblLw2/8vlB1FaAGaEIRSAESQAkSIpQhEKIQEgRUiAEhUJSIAISPCUUMpPJ5fKb64+09lrT6XRzczOfz2Nu7uWwMPfi4jg2xqRp6rpuGIa4sOl0mqZpkiS5XG55eblQKJDES5pOp8m5fD5fqVQ++clP/v7v//5TTz31hje84Rd+4Rfe9a53LS4uxu3dr3z6b/RYIUIF9BSpAlUYAxEYVVGogHpycJh87BNv/R/eczIzzzzzzPHxcaVSKZVKlmXhsh0eHna73cPDw2q1GoahZVl4zTmOs76+nqbpnTt3isViEAS9c9VqtdlsWpaFyzabzeI4jqKoVqutrq5aloXLpqpJkrTb7TAMG42GZVm4mGw2G+TdL/3tJyaHhxAyI6RACPAURCBCIUUgBAUiPCUCEiKkUAgRCCkkBUIILXvhdVffeDLTW8/d9n1/dXU1k8lgbu5lsjD3Imaz2de+9jWSlmUtLCzMZjPLsnAvR0dHSZLs7+/7vn/lyhXP83Av4/E4juP9/f1isRgEwYc//OHf/d3f7Xa75XL513/919/5zneGYYhz+UIgGUtPDPQMVGhURWGITAanxBACBdSoUk/w2f/rD+vf83311WYQBJZl4bIdHR11u93BYFCpVFZWVrLZLC5VGIaO41y7du1LX/rSlStXtra2HMfBQ6DX67Xbbdu2t7a2XNfFQ2A8Hrdarel02mw2fd/Hhak56bVan/mj3xsfDilCEVDAMxBChKdEQAH/CUCCBM+AAAmeEwEFQpGMm/d3dh7f3+8lSbK8vByGIebmXhELcy9iMBgUCoVKpTIej/P5PO5lOBymadrr9cIw3NrayuVyuJfRaBTHca/XC8OwUCj88R//8W/+5m9++ctfftvb3vYTP/ETTzzxxNWrV33fx9fZCw5EIIQhRWAUYgCBKKAwhIgqIAojFMDoeDhof+KjKz/0royUcKnG43Ecx2malsvlnZ0d27Zx2VR1f38/iiLf92u1Wr/f73Q69Xp9YWEBl2c8Hnc6ncPDw3q9XiqVSOKyqWqSJO12OwzD1dVVy7JwYeODwd//n7/b73QAQ8lABMJTEIJCEZIgQZCEEBSI8JQISIiQQiFEQIKgiL3gvO6RN2Us++7dPQBbW1uO42Bu7pWyMPcifN+/evXqwsICLmBvb29/f79cLr/uda+zbRv3MhwO4zgeDodhGOZyuQ996EO//du/ffPmzR/4gR/42Z/92R/8wR90HCdN0+eee255eblSqeDrnJw7Oj5GBgqFEMhAATFQgShVoQoViCoUQkCODgZ/85v/sbhYf/JdP+IUfLzmptNpfC4Mw52dHcdx8BAYDoftdvvk5KRerxeLRZLVarXT6Vy/fr1er5fLZZJ4bRlj4jiOoqhUKm1vb2ezWTwExuNxq9U6Pj6+cuVKoVDAhenJSa+19+k//N3x8IAiyGQgPAUQQlIoBAmSIqBASAqFpEAEQopQCBGI8JQIKFnbfvyJfzEcHu7deqZcLi8uLooI5uZeBQtzL8I6h4sJw7BWq1mWhZekqgcHB3Ecj8fjMAxHo9Gv/uqv/s7v/E4URW9/+9t/6Zd+6fu///uz2SzOhWFo2/bu7u54PF5eXpZTGXH94OjwAFAYgShUIYQKFFCjKlCFKpRUgShUIdQTs7+3+4n3//Lb/s2/dfwiXiuz2Sw+VygUtra2XNfFQ2A8HkdRdHBwUK1Wy+VyJpPBuWw222g0fN9vt9uDwWBpaSmXy+G1MhgM2u22iKytrXmeh4eAqiZJ0m63wzBcXV21LAsXNh70n/69/6PfaQEKyUCEIEgIKUIRkOAZiICkCEUoBAmCJECQoFBICkSYEdcr7jzybVHUHQwGzWbT933Mzb1qFubuB8dx8JKMMYPBII7j4+Pjcrnc7/d//ud//g/+4A8ODw/f8Y53/NiP/dh3f/d3iwi+ked5Gxsbu7u7zz33XKPRsG17dX07jfbUKEShBipQhVGIwggFMAYiMKqiUEIFqlQFZHww+MT7/8OT//27i0srksngQTo5OUnTtNvt5nK5tbU1z/PwEJjNZt1z5XJ5e3vbtm28gO/7+Xw+iqLr16/X6/VKpSIieJCm02mn0+n3+/V6PQxDEcFDYDwet1qt4+PjK1euFAoFXJg5Oem37v79731ofHCAjFAyFIKEkEJSQACkECIQoRAkCIDgKYEIhBShECRICO2FhUce/w6Ktbt717btra0t27YxN3c/WJi7sNFo5LouXiZjTK/Xi+NYVcvl8o0bN973vvf90R/9EYAf+qEfes973vPkk0+SxIuwbXttbW1vb+/ZZ59dXV31/KBQDAdpF0poBgoYg4xAFaKnIIJTYgiBUYjCUEWggJjxwcFT//FXiotL3/Ej/8rxi3gAjDH7+/vdbjebzTYaDd/38RAwxqRpGkWR67pbW1uu6+LFZTKZpaWlQqHQbrcHg8HS0lI+n8cDYIxJ07TT6fi+v7OzY9s2HgKqmiRJu90Ow7DZbGYyGVzYeND/u9/5rX57T1WZyVAEJHhOBCRIikAIEQIgAVKEIhRCBEKKkAIhKBSSkrUXnnjyv+oPDlqt2/V6vVqtksTc3H1iYe4C7t69m8lkHMdxXRcXNpvNer1eHMeZTKZcLn/xi1/8uZ/7uT/5kz/xPO/d7373j/7ojz7++OO4ABFpNBrdbvfZZ59tNBqPPPEdf//Un58ooApDiFABMaqkClShChFVQAxUIEoFRKGiCj052b97569+5X1v+7f/c84v4v4xxvT7/W63S7JerxeLRZJ4CAwGg06no6qNRsP3fVyM53kbGxtxHD/zzDO1Wq1arWYyGdw/w+Gw3W4bY1ZXV33fx8NhPB7v7e3NZrMrV64UCgVcmDk56e/tPv07vzUeHkBIyVAIkEJSQIIgBUJQSIKECIUUgRAUiPCUCEiIkEIhRLKO+9i3fedeqz2dTjc2NjzPw9zcfWVh7iUdHx/v7+/v7u4eHR3VarV8Pp/NZnEvx8fHaZomSbKwsFCtVp9++ukPfvCDH/7wh2u12o//+I+/+93v3tnZwctUrVZt2759+3Y2mw3qGwed56ZHBqLQM1ChURWFIUSgSlWoQAE1qoQSFIrCECJHg/5f/fIvfu//9BOOX8T90O/3u93uyclJtVoNgkBE8BAYjUZRFI1Go1qtFoahiODlEJFareZ5XrvdfuaZZ+r1uu/7eNVms1kURUmSLC4uVioVEcFDQFWTJGm322EYLi40HQZqAAAgAElEQVQuZjIZXNhRv/d3H/pgv7WnAEVIAQmSQoiAoAgoEJ4CARGeEgEFwnMACRI8AwIiWSe34FfzXvHZm8+VSqWNjQ3LsjA3d79ZmHtJh4eHe3t7qtpoNHzfz2azeEmTySRN0yRJPM+r1WpPPfXUb/zGb3zkIx/Z2Nj46Z/+6R/+4R++cuUKXpHZbDadTo0xURRVKpU3fMf3fuFvPz49OqQKVGEUGQUUooDCUEVgFKIwQgGMQlRVIApViowH/Y//h3//HT/yr4orq5LJ4JU6ODjodruTyaRarYZhKCJ4CEyn0/hctVpdWVnJZrN4pVzXXV9fT5Lk9u3bpVJpcXHRsiy8Ummatttt13W3t7cdx8HDYTwe7+3tzWaztbU1z/NwYebkpHf3ztMf+k9HBwOeymRAgqQQFJAEIQLhKZCgUIQkRECQBAkKRHhKBCTkVCZfDB5901ujbnLz5k3btqvVqjEGc3MPgIW5lxQEwaOPPtrpdFZXV3Evu7u7aZoGQVCtVj/ykY984AMfeOqpp17/+te/973vfde73lWv1/GKzGazNE3jOF5YWFhfX3ccZ29vr9XuPPbk93z56U9Mj0ZQAyEgMAoxUIEoVSGECkQVCiEgVIUSKgqF4dGg/4lfeV9xeeU7f/TfOMUiXqbDw8NutzsajSqVSrPZtCwLDwFjTJIkURQVCoWdnR3HcfCqkaxUKp7ntdvtGzdu1Ov1IAjwMo1Go06nM5lMlpeXgyDAw0FVkyRptVqVSqVWq2UyGVzYuN//29/6j727dxVKEYhAeApCUEhABMJTACEkhUKQ4BlQICSFQlIgAiFF7Jzz+iffZi04e622MeYtb3mLqkZRdP369Wq1GoahZVmYm7t/LHzL+8xnPtNoNBYXF/EibNteXV3FBQRBICJ/9md/9sEPfvDpp59+y1ve8mu/9mvvfOc7wzDEKzKbzdI0jePYcZxGo+H7Ps41m81Op7N7d2/nie989sufOer3jChUIYQKFFCjKlCFKpRUgShUVQRGIUoViELVGJPevv2xX/z5f/kTP5UrBriYo6Ojbrc7GAwqlcrKyko2m8XDodfrRVEkIs1ms1Ao4L5yHGdtbS1N0729vcFgUK/XbdvGBcxmsziOoyiq1Wqrq6uWZeHhcHR01Gq1ZrPZ+vq653l4OY76vb/8xfeOBwNmBCLgGYAQIQkSIiRBQkgRioAEz0AEJEUoQiFEIKQIKXYu96bv+W9GR+NbzzwbhmG9XhcRAGtra8PhMIqiJEmq1WoYhiKCubn7wcK3tm63+9GPfvTJJ59stVpPPPEEXp1r16695z3v+eIXv/i2t73tQx/60Dve8Y5CoYBX5Pj4OE3TJEkcx1ldXS0UCngeEVlaWlpYWNjd3V177M0LlnzxUx+fjg6hSj0DIxTAGIjAqIpCCRWoUgiIGoUQKgSgOh70//Lfv/c73/Ovg0ZTMhm8uPF4HMdxmqaVSmVnZ8e2bTwcDg8PO53OdDqt1WpBEIgIHowwDD3P63Q6N27cqNfrYRjiJfV6vXa7bdv21taW67p4OKhqHMftdrtSqdRqtUwmgwszJye93dt/+59+Y3zQpwh4BiSEFAEBCoUgQVJICgiAFEIEIhRSBARAkARBUpgPwkff/F3dOBkMBo1GIwgCPI93bjAYRFGUJEmtVisWiyKCublXx8K3tslk8vjjjwdBsLS0hFftTed+5md+5u1vf7vjOHhFptPp/v5+HMeu6zabTc/z8CLCMLRt+86dO8Vi8U3f+99+9mMfno4OVYRGIXoKIjglhhAYhSgMVQQKiKEKBKoKEpTxoPdX7/vfiysrb/3X/2OuGOAFptNpfC4Mw52dHcdx8HCYTqdRFO3v71er1WazaVkWHjDbtldXV/v9fqvVGgwG9XrdcRy8wHg87nQ6h4eH9Xq9VCqRxMPh6Oio1WqdnJysr697noeX46jX+9QHf62/u6tQUEBSBCRFAIKkCIXgORGQICkCIURIggQIkiIUQgRCO+e+4V98b8Z2du/uZbPZzc3NhYUFfDO+73ue1+/3oyhKkqRWq/m+j7m5V8HCt7ZGo2FZVr1ex8VEURQEgW3beBHvf//7s9ksXpHpdJqmaRzHnudduXLF8zzci+d5Gxsbu7u7k8nkjW/7rz//V38+HY0gBhCoQhWqEFEFxEAFolRAFCqqgCpIikBPiTEn6a3nPvbef/d9P/m/5IISvm42m8XnfN/f2tpyXRcPh9lsliRJt9stFovb29uO4+A1VCwW8/l8FEU3btyo1+thGIoIzhlj4jiOoqhUKm1vb2ezWTwcjDFJkrTb7UqlUqvVMpkMLsycnPTu3P7UB35t3O8jIxShECQAioCgCIUAwVMCERCkQAgKRUCCpJAiEIICEZJ2zn3z97394HDUevbm4uJitVoliRcnIqVSqVgspml69+7dOI5rtZrneZibe0UsfMur1+u4gE6nA+BrX/ua53mPPvqo4zj4ZrLZLF6+6XSanPM8b319PZ/P48IWFhbW1tZardbdVvux7/r+r336b0b7iSogBoYQgSpVoQIF1KgSEBilKFSgZyBCVShBOervf+y9/+77fup/zQWl2WyWpmkcx7lcbm1tzfM8PBxUdX9/P4oi27bX1tY8z8NlsCxreXnZ9/29vb1+v7+0tOS67mAwaLfbIrK2tuZ5Hh4aR0dHrVZrNputr697noeX46i3/8n3/0pv945CKRmSoICkCETAUwIhSAohAoIkKBCeAgGeEwEFQlIoFMm4Qemxt35vpxuPRqP19XXP83AxIlKpVIIgSNP01q1b+Xy+Vqu5rou5uZfJwtwFjMfjbre7v79fLper1arjOLhPptNpHMdpmhYKhY2NDdd18fJlMplGoxFF0e5ea+fJ786Yky984i8mh4cQBRSGKgKjEIURCqAKoapAFIYUgaqSoECUKkf93sd+/n979L/74bG9YC8sNBoN3/fx0BgOh51OZzab1ev1YrFIEpfK87ytra0oiv7xH//RsiySS0tLYRiKCB4OqhrHcbvdrp7LZDK4MHNy0rt965Pv/+WjwYBCSgYEKCQgAp4BCZ4BBSIEIQIhRUCCQhGSEAHPgARp53KPf88PqJW9c3fPdd2trS3LsvAyWZZVq9WCIEiS5JlnngmCYHFx0bZtzM1dmIW5C3AcZ2dnp91uN5tN3CeTySQ5VywWNzY2XNfF/8cenIA3ftd34n+/3/pZlmVZlnVZ9tiOLcuGbgnbli5XIaQpd4CWlPu+CxQSrkAhTcMRoFwthQLbbunxb7ds6QEFEhqOFuixtFtYIBAC4zntsX766fAp+Rjp+1lpnn+fpzwUiJuZiTLze73unHw+H41GV1ZWcrncf3vk4//l5o/ttbZhBhnNIMIEmcFgghnNYIRkMJhgRjNAZgCstbH+r7/7gaFM9opXvjaeTKI/7O7uBkGwubmZz+czmUwkEkHf8DwPQKvVSiaTsVhMEvpDq9Xyfb/dbs/NzSUSCRzEzvraP37wfesry+YcIxFSICmBhEQSJMQuiKBIgIRIESAIUhQhgT0gIUpeIpO59MEP3djarq76k5OTmUwGd0I0Gp2YmEin0+vr69FoFKHQQXgI3THRaHRmZgZnw+7ubv2MVCo1Pz8fj8dxlqRSqcHBweXl5b29vZ96+GO/cstf7zebMGcmmMEMRppAA2kSnEFGE2ggTYKBMjiCtE6nVfE///Y3PfQNbxwaG8Ndqt1u12q1IAgymczi4mI0GkXf2N7e9n3fOVcqlRKJRL1eP378eDqdzufznufhruOcq9Vqvu/nz5CEO8x1Omsnjv/Th963s7FBEpEICJAUAVIECZISQEiUQEIiCRIkJUoQQRKABJLSYHz4v17+iIF4ouz7zrn5+fl4PI6zYXBwcHx8HKHQAXkInUe7u7u1Wq3RaIyNjS0sLAwNDeFsGxoampubO3XqVLkS/MTPXfl/P/vJ/WaTApyDBGcmgxEmGiAHyAwwBxMBWBchAQYTzXbW1z/31jc+8KVXj10yq0gE551zbm1trVKpxOPxUqkUj8fRN9rtdhAE9Xp9fHw8m81KApDL5UZGRnzfP3LkyMTERDKZxF2h1Wr5vt/pdIrFYiKRwEHsrDX+8bffu3bypMEgQWKPQIKkCPaABEEJBECKpEBSJAURYBckSBQpRePx+z76qp3908eOH0+lUuPj45FIBOdMtVpNJBLVanVmZgah0A/gIXRe7O7u1mq1RqORTqcXFxdjsRjOmYGBgZmZGd/3V8r+vS5/5He+/MVWvW5y6JIjBGeQmREmGCiDEwQzAwmKMpggMxOAnfW1z7/tzWPTMw+6+pVDY2mcR5ubm5VKxcwOHTo0OjqKftJoNCqVytDQ0MLCQiwWw78Ti8VmZ2cbjcby8vLo6Gg+n49GozhfnHO1Ws33/fwZknCHuU5n7fixf/zt9+5srFOCRBIkRJAUQYGkBJISKZCUKIIEQQkU2AMRErskKpLI5O59+cPr6xvr6+uTk5OpVArn0u7u7v7+/j/90z/FYjFJqVQqkUggFPo+HkLnRSwWA7C4uBiLxXDuSZqcnBwcHDx16tTC/S+P0r722Zv2trcgmQFyMFGAM8jMCAlmlGAG6xJkNBmNgJHWcfVjRz77xl992BtvHBpL49zb2dmpVCqtViufz6fTaUnoG61Wq1Kp7O3tTUxMpFIp/ADpdDqRSPi+v7S0NDExMTY2hnOv1WqVy2XnXLFYTCQSOIidtcbfv/c968snzAwS2AOSIkGIYBcgAaAEAiRFgGCXIIEgCREUJZAgo/H4Tzz0Sm9oeNX3JRWLxVgshnMsFosdOnSo2WzG4/FYLJZIJBAK/Uc8hM6XqakpnF+ZTGZwcPDkyZOpVOq+j3viP3/8z/aa2zSDCQaDQQQEZ5TBZGYgIdEMkDmjaCYANAPUWl/7zBt/9eFvvHFoLI1zZn9/v3ZGNps9dOjQwMAA+ka73a7VakEQ5HK56elpz/PwQ0Wj0ZmZmfX19XK5vLm5WSgUBgcHcW4452q1mu/7+TMk4SB21hqfueG6nfV1iFSEJCSQlEBCIgkKEklIYJcggqQICWIXKIikQIBUJJLMjf/Ew67c3tk9eexYPp/P5XKScL4sLi4iFPqhPIQuaIlEolgsnjp1an9//6cf+4R//cSf7zW34QwymiCDGUQzQQZHSjAzCc4g0gQBZibBjNLO2tpnbrjuQVe/amyuqEgEZ5Vzrl6vB0GQSCQWFhaGhobQT9bX133fj0ajpVIpHo/jDkulUolEwvf9w4cPFwqFTCZDEmdVq9Uql8vOuWKxmEgkcBCu01k7dvQffus9O+vrECmBgEQAEghSIECRAAn2gIREEhQkgiAhUgIJktLg8PBPPuJx8VS67PutVmt2dnZkZAShUJ/xEDqrdnd3Y7EY+kksFpudnV1dXT15anXqvg8uf+1fdtbq7rQZDSJMMKMZIMgMBhPMKAIyA2Aw0QySmYFoNRqfe9P1qZlLLnv164bSaZwl6+vrQRBImp6eTiaT6Ce7u7uVSqXZbBYKhbGxMZI4IM/zpqamksmk7/ubm5sTExNDQ0M4G5xztVrN9/38GZJwEDuNxpd+453rJ447M0qUAFICCYk9AkkJJCSSICF2gQBFAiREigBBkKIYHU484KqnnTYcOXo0Ho/Pz88PDAwgFOo/HkJnSb1eP3z48Pz8vHMuHo+jn5jZ4ODg8vLy7u7uPX7misRA5Cs3fWxve4smyOBoEpxBpAkCnDMJBspgAs1IkCApweBcp370yC3Xvfbhb31nPJ3GndNsNiuVyt7e3vj4eCqVkoS+4Zyr1WpBEIyNjS0sLAwMDOBOSCaTw8PDQRAcPny4UChks1lJuBNarVa5XDazYrGYSCRwEK7TWTt25O/f867W+hojIgURJEWwByREkBQBUgQJkhJASJRAQmKXBJISJXqRZL7wk4947Eaz5fv+5ORkNptFKNSvPITutN3dXf+MZDK5vr6ey+XQN5xzjUajVqsNDAxceumlnU5nZWVlIJ9/wJOe+b//7I/3tjdhgowGyAEyA8xBIgDrEmgQYaIZJDNARhNkrbW1W6577YNf9dp0cV6RCA5uf38/CIK1tbVcLjczM+N5HvrJ1tZWuVyWNDs7m0gkcDZEIpGJiYmRkRHf9zc3NycmJoaHh3Fwzrlareb7fv4MSTiIVqP+9+9+x9rxo84ZIwIIsQskSJAgKRKECJIieIYEghJFgBRJgQRBCuLg8MhPXfkLg8lU2fdPnz5dKpXi8ThCoT7mIXSnxWKx8fHxeDyez+fRN5xzGxsb1WqV5MTExOjoKM6IRqPLy8t7e3v3f+LTv/zRP97b3oY5M8IEA2VwgmBmkOCMIkyQmQkAzQCZGUwUdhqNz17/+rFL5i573evj6QzusE6nU6/XgyAYHR1dWFiIxWLoJ/v7+0EQrK+vFwqFdDotCWdVIpEoFou1Wu3IkSP5fD6Xy0UiEdxhrVarXC6b2fz8/PDwMA7CdTqNo0f+/t2/3lpbY1ckApISSLAH7AEJEhJJUCApgQS7BBIkRZAgKIECOTg8/IAnP3Ov3Tl67Njo6Oj09LTneQiF+puH0NkwdAb6xsbGRhAEzrlcLpdKpSTh38Tj8bm5uVOnTq0G1Z++6qn/8pd/ur+1RQHOIDMTZDCjBDOIZoKMJggwMxIg2GMESOdc/cjhv3ntax75jnfHMxn8KGa2vr5eqVSi0ejs7GwikUA/cc41Go1KpTIyMrK4uBiNRnFuSMrn8yMjI+Vy+ciRI4VCIZlM4kdxztVqNd/382dIwkG06vUvvfNta8eOOjOKkECQAkESJNgDkiJBEKBIQAJACSRIiqDALkGCqEhkZLzwU1c+vrGx2Wg0Dh06NDY2hlDo7sBD6MKytbVVrVb39/ez2Ww6nZaE7xONRi+55BLf909Vgp/8+Sfd9pmbtmsVcw4QzWCEyWBwhEQzQGaAOZCQaAbIzGCiADMjW43637z2VY9852/EMxn8YNvb25VK5fTp0+Pj46lUiiT6yfb2dqVS6XQ609PTyWQS597Q0NDc3Fy9Xj958mQqlSoUCp7n4QdotVqrq6tmNj8/Pzw8jINwnXbjyJEvveNtrbU1ipBAkQQFEiQokpBAUgIJiSRISCQhgT0QwS5Agtg1ODxyn59/QnRk9FS5LKlUKsViMYRCdxMeQheKZrNZrVZbrVY2m02n057n4QeTNDk5GY1GT62u/pdHPi5yev8rH//o7uaGkaAggyMlmJkEA+hIQYCZSTCjBIPBYCIMxlaj8elrX/mQX7kuPT+viIfvtbu7GwTB5uZmPp/PZDKRSAT9pN1uB0FQr9fHx8ez2awknC8ks9nsyMhIuVxeWloqFAqpVArfyzlXq9V83x8fH8/lcpJwEK16/Ytve0vj2FEzowj2gITYBYISCEgEIIEgBQIURZBgD0hIJEFBIshIZHRi8j6Pe0Jr//TRY8ey2Ww+n5eEUOjuw0Po7q/VatVqtc3NzWw2OzU15Xke7phsNhuNRldWVlKp1AOe/tx/+pMP725u0gwQZAaDiQCcg2QGwGCiGSQzQEYTZGaCQLOdtcYtr7t2rDh3+Ruuj2eyOKPdbtdqtSAI0un04uJiNBpFn2k0GpVKZWhoaGFhIRaL4a4wODg4Ozu7tra2urq6ublZKBSi0SjOaLVaq6urAObn54eHh3EQrt1uHFn64ttvbDUajAgUSIogKQIESQkgJZCQ2COQlECCPSAhUgIBiiLIwZGRn77qycOZnF+pNJvNmZmZZDKJPnDs2DEAc3NzCIXuAA+hu7Pd3d1ardZoNLLZ7OLiYjQaxQElk8lisbiysrK/v3//pz33y3/y+7tbmzBAjiYI5hwkGCiDCTJzBAmCpJEgwS4YCdCsU//ud29+1dWP/o33xcbSa2trQRDEYrFSqRSPx9FnWq1WpVLZ29ubmJhIpVK4q42NjQ0PDwdBsLS0VCgUUqlUtVqtVCrj4+O5XE4SDqJVr33hxjc3jh4x5xgRQBKQAIIEeyCCpAj2gIQIkiJAipRAUgIIkhJIkLHEyIOe/cI2ePTYsVgsViwWo9Eo+sDtt9/ued7HP/7xB56BUOhH8RC6e9rf36+dkU6nFxcXY7EY/rNisdjs7OxqV1C9z5OeeetNH9uqlJ05M8AMEgFYlyCDERLNIJkBMpogMxMEmpkjyJ164+ZXXj3/rOfGD01NTk6Ojo6iz7Tb7VqtFgRBLpebmZmJRCLoD9FodGpqanNz89ixY7fddls6nS6VSvF4HAfUqtdufsXLW406KUQEEiQkEiApAoTYBRLsAUmRIESQFEECoASCEkWA8iKjhUP3uerJm60d3/cnJiZyuRz6xj3vec9bb7310ksvnZubQyh0B3gI3d202+3aGclkslQqxeNx3Gme501PTwdBcCoI7v0LT8JO818++qd7m+swwXog0QxGUJCZCQDNAJkZTBRgZhIMlJmxVa/d+pvvHj40Nf22d6DPrK+vVyqVgYGBUqkUj8fRZ5xzOzs7ZpZKpdrtdrPZjMViknDHuHa7sXT47258806jDhESSYAUQQKkBJISSFAkIYGkBBISSVAgKUECuwQSZCyZ/G9PfNpQOlv2/f39/fn5+eHhYfSZS89AKHTHeAjdfbTb7UajUavV4vH43Nzc8PAwzh6S4+Pjg4ODKysr+Xz+sue/+Eu/98HdjQ2QlGBmJCjIaIIAM5NgBvYYAYkwGM0EGU3m3PaJ4596+Usf8/4PxrNZ9IHd3d1KpdJsNguFwtjYGEn0mWazWS6XASwuLsbj8e3t7dXV1c3NzYmJiXg8jh+lVav93ZtvaBxZMucgkgIBkiLYBUggSIGgBAIkAZAgSIEARQISAJIgQVIcHBl98PNevOfsyNGjyWRyamrK8zyEQndzHkJ3B865RqNRq9Wi0ej09PTIyAjOjVQqNTAwsLy8vJ9IPOh5L/6H3/vg7uamweAIiWaAzAAYHMEeSGYGE+kMBAn2mAQYTTv12qde/pLHvP9D8WwWdx3nXK1WC4JgbGxsYWFhYGAAfcY5F5xRKBSy2awkAIlEolQqBUGwtLSUP0MS/iOu3a4vHf67N92wU69BokQK7AEFEiQokqBAUgLYBQkkJZAgKYGERBISxB4vMjox9dNPfOradrNer09OTqbTaYRCFwQPof7mnFtfX69Wq5FIZGJiYnR0FOfY8PBwsVhcWVnx6437P+dFX/3Lj2ytrjpnMDMJBsrgCAlmJsGMEgwGg4kwGM0EdgiaCNNOvf6pl734Z294c2ZhUZ6H825ra8v3fZKzs7OJRAL9p9lslstlAKVSKR6P49+RVCgUkslkuVxeWlqanJxMJBL4Xq1a9W9/7frG0SVzDuyBCBIEKBJgD0iIXSBAgoBEABIIUiAAUgQJ9gAcTI7e96nPjI1lVstlAKVSKRaLIRS6UHgI9TdJe3t7+Xx+dHRUEs6LaDQ6OztbLpdXq7X7POXZ7c2Nf/6ff7C7sUEA1kVIgMFEM0hmgIwmyMwEgWaAzABnJI1s1eufvuZl6fnSFW95azybw/myv78fBMH6+nqhUEin05LQZ5xzwRmFQiGbzUrCfyQej8/NzdXr9ePHj6fT6Xw+73keANdu1w9/929v+NWdeh0SuySIBEFSAgmSIkiKAEFSAkgJJCT2CCQlimAPSHqR1KHp+z71Wa3T7SNHj2YymfHxcUkIhS4gHkJ9b3x8XBLOL0mHDh2q1WrHjh+fmpq6/CXXfOGDv7W7sQ4SFGUwQWYmdDlH0kiQYBdMgoEymEwGY5dzrnr77Z988Yse+99/N57N4RxzzjUajUqlkkwmFxcXo9Eo+k+z2SyXywBKpVI8HscPJSmXy42MjPi+v7S0NDExMbC///nr31BfOgznIJGEBBIkSIoASUACSAnsgQiSItgDEiJIigBBUgIZS47e7xnPGc6NB9Xq5ubmzMxMMplEKHTB8RDqe5JwF8lms9FodGVlJZ1OP+QlV3/hA+/d29yAdQkymoxGAJIZIKMJMjOBjoSREGmCYGZgF1r12id/6YVXvOWtmcV7yPNwbjSbTd/3O53O9PR0MplE/3HOBWcUCoVsNisJd0wsFpudna0FwXf+4e+Pffj3Wo0aKIogwR4QBCGCBAmJBCQQACF2gQR7QFIkCBEkRUgAYsnRy196TSfiHT9xIhqNlkqlaDSKUOhC5CEU+qGSyWSxWFxeXt7b2/uZF73six/8zXazSTMYjaRoJgA0A2RmMFGAmUkwkGYkCEowMwkd16pVb/rll6RLpYe+7R3xXA5nVbvdDoKgXq+Pj49ns1lJ6D/b29u+75MslUrxeBwH1KpWv/S612wcPQoYJBJgD0iQICGRBEgRJCiSICmBBEUSEkhKICGRBAVSkcjooen7PeM5W3v75fKJQqGQy+VIIhS6QHkI9YFms9npdJLJJPpSLBabm5tbWlo6ceLEoUc8dv2f/3FzdcWcQUYTBJiZBDNKMBgMJsJgNBNkNBkdSEowM8h12rVvf/sTL3zu4/7HH8RzOZwljUajUqkMDQ0tLCzEYjH0H+dccEahUMhms5JwEK7drn/nO5+/7nWtag0RUQIIkhLYA5EUCJAUwR6QIEiBoAQCEgFIIEiBAEUiNjp6/2e/YCibrwTB3t5esVhMJBIIhS5oHkJ3qXK5vLa2tr29PTQ0NDc3l0gk0H92d3eDIGi329lsttPp3OdZz3Obm1/+w9/dWV83A2AwwYykkSAAdhkIkiIgMwBGk3U6YA8kM9esVj/xguc+7vf+IJ7L4c5ptVqVSmVvb29iYiKVSqEvbW9vl8tlSaVSKR6P44Ca1eBzr3tt4/B3zTlIJMEuQEIXCZEg2AMKJEWwBxRISgApgYTEHoGkBHJwdPTyq19zGjx2/HgikSgWi57nIRS60HkI3XV2dnYGBgaCIJicnFxcXET/abfbtVqtWq2OjY0tLi5Go9FGo32931UAACAASURBVHFyeaVQKFx+zbV/99537a6vwREkSJNgRgkGg8FEmBkBgiBlMpgImBlIijA1q8Ennv+cK97+juw97inPw8G12+1arRYEQS6Xm56e9jwP/cc5F5xRKBSy2awkHFCzGnziuc9u1WqIiBQIsAcSSZCUQIIEAYoEJIAgIXZBBAkCJAGQIEBSVMQbnZq+37Ofv9HaqdVqk5OT6XQaodDFwUPorjM0NBSJRB74wAdGo1H0Gefc+vp6pVKJxWLz8/PxeBxnpNPpaDS6srKyl0g85OrXfOG979hd3wAMJppBMgNkNEFmJgg0A2TmwB4jIdHMSIg0NavVT73w+Zl73OOh73j3cD6Pg9jY2PB9f2BgoFQqxeNx9KXt7e1yuSypVCrF43EckGu3a7ff/vnXXduq1yASBHtAgQQJgBIIghApgYREAiRFgBC7AFICCYk9ghgbTd3/uS8ayubKlYpzbn5+fmhoCKHQRcND6C4VjUbRfzY3N4MgcM5NTEykUil8r0QiUSwWV1ZWKvv7D375q//PH314Y/mks9NmAkAzQGYGEwWYmQQDZTCZDMYuk2AgzUiI1nHVb37zr5/zrJ//w/9vOJ/HHbC7u1upVJrNZqFQGBsbI4n+45wLzigUCrlcjiQOqBkEn7v21bXvfsecowQSJAhIJMAeSCBBQiIJkCJIgJRAUgIJkiLYAxIiI5GxSy65//N+adfZkWPHMpnM+Pi4JIRCFxMPodC/s7OzEwRBs9nM5/PpdFoS/iPRaHR2dna1q1a/7wtecnq98b9/90M762twzkiAYI8RIMEuGAUZTRDMDOyCSTBjhybC1KwGf/3sZz70Xe/O3vPH5Hn4AZxztVotCIKxsbGFhYWBgQH0pe3t7XK5HIlESqVSPB7HAbl2u3b7tz937aubtRq7JBAEQVICCBIk2AOCFAiQFMEuQAJBCgRJkGAPSIpDo2MPeOGLE4XJoFrd3NycmppKpVIIhS4+HkKhM06fPl2r1arVajabLZVK0WgUP5SkqamparV6/OTJQ4cOXXHtGz7/zht31tYA0AyQmcFEAWYmwRxJIyHSBDOT0HGUzABnJEE2q8Ennvvs7D3v+bD3vHc4n8f32dra8n2f5OzsbCKRQF9yzlUqlWq1WigUcrkcSRxQMwg+++pX1G6/3cxIggQJEhJFsAtgD0iwS2APKJAgQZEECRIkKJKQQFKKjaaueM3rLRo9fuJENBotlUrRaBSh0EXJQ+ii55xrNBpBEMTj8YWFhaGhIdxhuVxucHBweXk5k8lcce11f/vOG3fW1kyCGSUYDAYTYTCaCTJ2aCQkAjAzRxCkTAZjlzkX3PrNjz/jqb/wJx8Zzufxb/b394MgWF9fLxQK6XRaEvrS9vb26uqq53mlUikej+OAXLtd+/Ztn331K5vVKiVIYA8IUiBAAgRJCeyBCBIEKBJgD0gQpEBQAgGJAD1v7JJLHvjCX26226snTxYKhVwuRxKh0MXKQ+jitrGxUalUJE1NTSWTSRxcMpksFovLy8v7sdhDXvP6L7zr7btrDUhmBgJgl4GQaAbIDIDRaAAkmkEyc6QgmBlIis0g+NjTn/L4//mR4fy4c67RaFQqlZGRkcXFxWg0ir7U6XSqZ4yPj2ezWUk4oGZQ+cwrrqnf/m3njCJIAiDBLoE9IClCQhcJkSBISiBBUgR7QIGkBJASyNjY2M+8+OXDhYlKELRarWKxmEgkEApd3DyELlatVqtSqezs7IyPj4+NjUnCf9bQ0FCxWDx16pTfWHvwK6/9lw//zsbJE+YcJRgMBhNdx0iAFGEyGUx0zkhQlJkRBCWYGQmyFQQfe+pTHvz2Xz89mnLk9PR0MplEv9re3l5dXfU8r1QqDQ0N4YBcu1277bbPvPKaZjWgBBIkSJCUIIIEAfaAPSApgQRJESAJSABBQuyCCJIiyKFUauaqpwS7e+2lpWQyWSqVPM9DKHTR8xC6+Ozv7wdB0Gg08vn89PS053m40zzPm5mZqVQqq/XG/V5ydWd97R9++707a2uQ0QSZmSDQzBxBgqRkZpBoHSMh0mR0kADQzKhmNfjMC1+QmJt7zId+ZySZRF/qdDpBENRqtUKhkMlkJOGAmpXKLde8vP7tbzvXoQSwCyQBSiAIgj2gQIIEQAkEQYggQUIiAZIiQIhdIBmJjF0y+4AXv2yttbO0tBSLxSYmJjzPQygUAjyELiadTqderwdBkEwmFxcXY7EYzh6ShUIhGo2eWF6enJx82PVv+uxbbthZa5gZTBRgZhIMlMFk7IA9JsFAmkmA0QjAJFiHpHOdje9+9+NPffJVf/bnw+Pj6DPb29urq6ue55VKpaGhIRyQa7drt33rlmte3qwElCCCBAH2QAIJEiQISCTAHkggQUIiCZAiSICUQFICCWooNfagl10Tyxf8SsU5d9/73rfdbq+urm5tbRUKhVgshlDo4uYhdHEws42NDd/3BwYGZmdnE4kEzo10Oh2NRldWVvZGRn7uuhs+95YbdtYaJI0ACZKimSCjCYKZgaRoEKxD0ESY4BwlM4BGqRlU/urJT3z4b70/9+M/Ls9DH+h0OkEQ1Gq1QqGQzWZJ4oCalcrfvOyl9W9/27kOKRAkAXZBAntAEIRICSBIkGAPCFIgQFIEuwAJBCkQinhjc3MPetkr9sBjx4+PjY2Nj49HIhEA8Xg8CILDhw8XCoVMJiMJodDFykPoIrC9vR0Ewf7+fj6fHxsbI4lzKZFIFIvFlZWVyt7e5a+//sv//bfXjx2z00YBZkaCPSYBRhPMjARIyQxwRglmRlIEZNYh1az4H3/aU7I/9mOP/MCHhsfHcZfa3t5eXV31PK9UKg0NDeHgmpXKXz7hqmYQUAQFEiRIipAIgAQJEhJJsAuQSIIEuwT2gAIJEhRJUCCHxtIPuvpVyanpaq22vr5+6NChVCqFf+N53uTkZDKZLJfLm5ubExMT8XgcodBFyUPogtZut8vl8sbGRj6fT6fTnufhvIhGo7Ozs6urq+XG2gNfce1+NfiH33pPq1GHiTAYzQR2CBoJiQDMzJEiTMYO2GMkQEpmDpR1OsHXv/4Xv/j4J/zlXw2PF3BX6HQ6lUqlXq9PTExkMhmSOCDXble/9c1bfvklzaBKCewBQQkkSJBgDwhSIEAChEQS7IEIEgQoEmAPSIhdQ2NjD7/hLTYYO3HypKRisRiLxfB9EonE/Px8tVpdWlrKnyEJodBFxkPoguZ5XjweHx8fj0ajOL8kTU1NBUFw4uTJqamph7/prbf82ht2GnUzQaAZIDMARqMBkGhmJNglCGYGiWbmCJFGIyC1Kv5fXPX4J/zVx4bHCzi/tre3V1dXPc9bWFiIxWI4uKbv/81LX1y97TbrdCCBAAiREsAukARAQiQF9oCkCBJdJESCICmBBEkRJEVFvLG54oOveVWz48pHjuTz+VwuJwk/gKTx8fGRkRHf95eWliYnJxOJBEKhi4mH0IUuk8ngrpPP5wcHB5eXl3O53MPf9NZbfu31O/UGCSNBUQaTyWCic0aCosyMICih0zES7DERJtIZ1axU/uLxj3/kBz+Uu9e95Hk49zqdThAE9Xq9UChkMhmSOCDXble/eevfvOQlzaBCERRJUJRAggQBEiRISiBBggB7wB6QlECCpAiQBCSAlIbS6Qe/4tqRqWm/Umm1WrOzsyMjI7gD4vH47Oxso9E4fvx4Op3O5/Oe5yEUujh4CIXOsdHR0YGBgZWVlb1Y7KE33Pi5G67baTQg0DpGgl2CYGaQaB2TYEaT0UECQDOjQCNpIoxdzYr/sSf+Yva//Pijfud3hwsFnEtbW1vlctnzvFKpFIvFcHBN3//0L72o+q1vmnOQQFGC2AWCJMAu8AwJBEGQlECBBAmSEgiCEEGChESCAwOZYvHBr7y2MxA9euxYPB6fn58fGBjAHSYpm80mEgnf95eWliYmJkZHRxEKXQQ8hELnXjweLxaLKysrlY3Ny69/8xfe9eu75VPODAbKzAiCEsxMQseRNAkwGkGaBOtQMjN0SNGMFF2nU/n61/7i5x/7hL/+5HChgHOg3W4HQdBoNAqFQiaTIYkDcu129dZbP/3iFzUrFUqQSIIEARAkSJAgwB6QIEGCpAh2AewBCRIkJJIAKYIcGstc9prXjV4y21hbq6ycmpiYyGaz+E+JxWKzs7ONRuPUqVObm5vj4+PRaBSh0AXNQ+jub39/v9PpDA0NoY95njczM+P7/ndPnpx6ytPj+3vf+ePf36k3zAQZTUYHkhLMDIJ1CJoII0hK1nEgKZkzStYxSDTb9it//rjHPOp3/kfu0kvleTh7tra2yuXywMBAqVSKxWI4uKbv3/zCF9S+9U3XcRTBLoA9YA8IkgApQQJ7QBCECBIgSEpgDwhSIEBSBBkfG3vk296p4eHllZV2uz0/Px+Px3HnpNPpRCLh+/7S0lKhUEin0wiFLlweQndna2trg4ODX/3qV+91r3tFIpFoNIo+tnOG53ntdnv8nj9WfPt7Pv26V7fqdUpmAIwm63TAHkhmgDNKMDOSIiCzDiljBxJdxyRYp1mp/OXjfyH34/d69Id/b7gwgTut3W4HQdBoNAqFQiaTIYkDcu3T1Vtv/fQLX7hd8SmBBAkSIEgQAEGCBEURJAGQIEFCIgl2ARK6SLBLYA8oel56vvSQ1/zKnrR65Mjo6OjMzEwkEsHZEI1GZ2Zm1tfXR0dHEQpd0DyE7rZOnz5drVaDICgWi+vr66lUCv2q3W4HQVCv1/P5/NzcXKvVWl5e3h8dfcTb33XL61/TqtVBEDQRJgJmBpIiTMYO2GMkQEpmDhTpjAIdSTO4Trvytf/70Ssf/aSbbh4uTOBO2NraKpfLAwMDpVIpFovh4Jrl8k0veF7t1m8516EIsAvsAtgD9kCkBAIkSLAHIikQIAFCIgmSEkSQIEDF02OXve661OxcUK2ura1NTk6OjY3hbEulUgiFLnQeQndbAwMDl1xySTqdzmaz6GNra2u+7w8NDS0sLMRiMQCJRKJYLC4vL+/t7f3cW379H3/jnWtHjzg7DWckjYREMyPBLkEwM0g0M0eINJoIIwmTYB1KZq5Z9j/66Ec96aZPD09M4ODa7XYQBI1Go1AoZDIZkjggd/p09dZbb37+87YrPimIIEGABAkQJAhSELsAdoEkABIiQbAHJEWQACiBIAiS0lAm88h3vgexoeMnTkian5+PxWI4X9rttud5CIUuFB5Cd2eDZ6Bf7ezs+L6/t7c3MTGRSqXw7wwODs7Nza2urvobG5dd/6bd8uoX335jq1YzGYxdJsFAmRkh0oROxySYkTQRHVI0E+goWcdRNOO273/00Y961Id/P3/ppRoYwB22ublZLpej0WipVIrFYji47XL55uc8p/qtb7pOmxTYA7AL7AIkiqBAggQJAiRISJRAggQBiSTYAwkkSJAa8NLzCw/5lTfsgqtHj2az2Xw+Lwnnxf7+/u7u7rFjxy655JJUKoVQ6ILgIRQ6BzqdTrVaDYIgl8tNT097nofvE4lEpqengyA4fuLE1NTUo9793ptffc1OrQbBzMAumAQzdmgkJDhH0ijQKJkzsMdIiuYIkR1u++W/eOxj8ve616P/8I8SExP4UdrtdhAEjUajUChkMhmSOLjtcvmjj3xE0/dBQgQJAiRFSBRBkQR7QJAE2AX+/0AQBEkJIEiQYA8IgkOZzOVvuD55yWwlCJrN5szMTDKZxHnUarU2Nze3traCIBgeHibpeR5Cobs5D6HQ2baxseH7/sDAQKlUisfj+KHy+Xw0Gl1ZWcnn849+z2/d/MqrW/UqJZiZhI4jaRJgNII0CdahZNYBSNGMFM0I9pgEZ9bp+F/96kcf/rAnfeaziYkJ/GCbm5vlcnlwcLBUKsViMRycO306+MY3bn7uc7Z9nxJEUhApgQQJEiBIEABBggQJAhJJkCBBgqQIdgHsAQlS3kBmYfEhr/9VNzh47PjxWCxWLBaj0SjOr9QZnuelUqmtra10Oo1Q6O7PQ6i/3X777fv7+/e+971xd7C7uxsEwfb2dqFQGBsbI4k7IJVKRaPRlZWVvaGhR7z7N7/09hsbS4fNOUowMwjWIWUyGLsgWcdRgsGcUbKOQaKZUWCHlLFDabtc/rOHP+zKP/yj/L3vrYEBfK92ux0EQaPRKBQKmUyGJA5uu1y+6VnPrN56q+t0KIEgCPYA7AK7APaAPSBIgqQEEuwBQQoiSIAgKYE9Q9nMz153w1hxvr625h89Ojk5mc1mcdeZnJwEEI/HEQpdEDyE+lW5XL7tttsOHz581VVXoe8552q1WhAEqVRqYWFhYGAABxGPx+fm5k6dOlXZ3PzZG9/WWln5uzff0KpWwR5IZg4kJTMDSdEcQZAydiDRdUyCdSiZOVJGB6lZLv/5ox+Vv/TSK//4TxITE/g3m5ub5XJ5cHCwVCrFYjEcnDt9Ovj612969rO2fZ8kJJAgQYIACQIkSIAgQQAESQkUSZAEQIJdAnvALkBCFzmUzVz5m+/3RpLLp07t7+/Pz88PDw8jFAqdPR5C/WpiYiIej7fb7bW1tXw+jz62tbXl+z7J2dnZRCKB/5SBgYGZmRnf94+fODk9PX3l+z5w09W/3KpWzQwkRZiMHUowMxIkJTMHinRGgY6SdRxFM0Kk0UjXbvtf+cr/uuKKp/zt5xMTk+12OwiCRqNRKBQymQxJHNx2efVTz3hG9RvfcJ0OJbAHBEGwB2AX2AWwByQliCBBgAQJ9kAECQLsgURSAwOZxXtc/qu/dtobOL60lEwmp6amPM9DKBQ6qzyE+tjo6Oj97ne/VCqFfrW/vx8Ewfr6eqFQSKfTknAnSJqcnIxGo8eOHTt06NCV7/vAp172klatRjMjIdJkdCAh0cxIiDSaCGOXkRTNESI7NBHGLiOb5dU/vfzyx33yU+vODQ4OlkqlWCyGg3OnTwdf//qnnvGMpl8GCQldJEiQIEGABAESJECQEEmBIAmwCyQBShAJgj2gQIKMZzI/e8ObU8X5ar1eL/uTk5PpdBqhUOgc8BDqb6lUCn3JzOr1ehAEiURiYWFhcHAQZ0k2mx0cHFxeXk6lUo9+3wdufvlLW7UaDKQZCZEmdDomwYykieiQohkpmhFgl0lwRsnMKJlZy6988rGPueyDH7rksss0MICD215d/eTTnla99Ruu3aEIiSTYA4Ig2AOwC+yBRBEgSJAgQYAECQkkSJAgIJEAGc9kr3z/h5RInFheBlAqlWKxGEKh0LnhIRQ6uGaz6ft+p9OZmppKJpM420ZGRorF4srKyr7nPeK97//iW960dvi77rTBjB2aCBOco2QG0CiZM0rWMZAUzRE0gkajZJ0OJFqn6fu3POEXv3rv//rYj3wkMTmJO8ydPh187WuffPrTm+VVSCTBHpCUIJKCRBEURUgUwR6wBwRJgF2QeAYIgiApAaTnZRbvccUb37IrrS4tZbPZfD4vCaFQ6JzxEAodRLvdDoKgVquNj4/ncjlJODdisdjs7Ozq6mplc+uKt79z59Spv73+ulYtMAOckQRpJAhKZh1Sxg5IimYEe0yCMxCQ6JxJ6DjX6fhf+dePXHbZU7/0pcTkJO6A7dXVTzzlydWvf8N12pQAggSJLhIkSJAgQIIACRIgSBAAQYIESRES/1978BYb6X2eB/x5Xv75cXZmODskh+RwOKR2Z0ZeZyXb6YUvWqEu6vogpZHkQyKpLoK2cZCkB7RG0DYoCvQiaOLAcOrWieOTHKduLFm1bMtKYDttilz5poFhFzFsozYpajjn5e7ODg+7HHK+tzMCCqRIk8r1Hkh+z+8HgAQJEmY0gswUCn/zV371/MWLvZ2dwWCwvr6ey+UgIndYgMirdv369U6nc+7cude85jWpVAp3WAhhfX292+1u1evlcvnRj33ixV/8uYNejzQ3h3MMZj6KaeYeg6SZjxxmdHcaOCLNOSLpJEgaPebYXrv9zJv++qPPPrv843/FpqfxF4iPjrrf+ubvP/XUfqsNMxrBMYAT4AQIguAEwDFwDOAEOAGCJEiQIMEJEKSBYAiFS69986/8apxKbdXrURTVarUoiiAid16AyKtw8+bNTqdzeHi4srKSz+dxFy0vL8/MzDQajaWlpcc+9skXf+HnDnpXSIPB3UHS6DFhpJtzBDPGIzeDj2jmHpPmjMEJ54SToO+32s+9+c1Lb/jxx557Lru6ij9nr9l88ckne//jW348ghkIkABBgsQYCRIkSBAgQYAECRAkCIAgaQYaSZAEQIJjBjKzuPjmf/v++dr91/r99uZmsVhcXFwkCRG5KwJEXoVer5dKpdbW1kIIuOvy+XwURfV6fZjN/u3f/sQf/5t/ffV73/OjIc3g7iQ44SRoZOw0MKaZj2Ia3QkjnU6CBAka6U748ajzJ3/yzEMPvefrX8+uruLP2Gs2n3noob12G0bSQNAMNBLgBDgBgiA4AXAMHAM4ARrNYAQJAiRIkDSDEWR6sfDox58OufPbzeZwOKxUKtlsFiJyFwWIvArFYnFmZgb3TjqdrlQqzWazd3j41n/3H/Ze3vpv/+qX93s9mAGgu9NgTqcb4RxzkkaPCSNHdCOcY84xdzP4CCSMe63WMw899J6vfz27ugogPjrqfvObv//EE3utFowEwQlwDDADiTESJEiQIECCAAkSIM1gHANBEuAYSAI0AzEVphcuvfZv/dr7j6OZlzc2Zmdny+VyCAEicncFiLwKMzMzuNeiKLrvvvs6nc5Wvb62ft9jT3/6y+/9+we9HgA3g49o5u4YkUZ30uhOcMLNEDvN3J1m7g4HzdxjOt2422x+9q/91cc+/zzc//h97+t+61vx8THNQIIEARIgSHACZjQDQRCcAEgzmJGEGQiAIEGCBAFOwAxkenHxLe//wFzt/p1r13Y69VKpND8/DxG5FwJETg8zK5VKURRtbm6Wy+XHP/W7L/zs3zvo9RDHNPNRDJJmHjvNfOQwo7vTwBFpzhHNfDSCGX3kII3uBEizvWbrc296k4+NjkGjGQiC4AQ4BnACnABBGsxoBI1GcAzgBDgBgiRAmsEMnEgvLj7+9O/a7Gy90YjjuFqtnjt3DiJyjwSInDaFQiGKokajMTc399jTn37xvf/goNd1kkbA3EekOUcwYzxyEnSSTpDmjGHGOHYzjGKQMHJEp9MsPj6CA5wAARIkCJAAQYLEGAkSJEgQIEGABAkQJAiAIEGCpBEkAQth4ccuv/XXP3AYQvMHP5ifny8Wi2YGEbl3AkRecXx8HELAKZHL5SqVytbWVnNv7zX/8pe3f+dT17/33dHREUCaucegkbGDMKO708ARSBAknQRJo8ccczPEDgI0IAYJEhwzcAIcAzgBToAgCE4AHAPHAE6AEyBoBhIkyPTS0ls+8MF8tdbb2RlcuVIul/P5PETkXguQxBsMBvv7+/1+f3V1NZ1OhxBwGhweHo5GoziOs4XFt/3mR/Zffvm//otfOuh2PSaMdLoRboxHbgYf0cw9Js0ZgxPOCSdBJ805IunOMRAEQdIIEiBIkBgjQYIECQIkCJAgAYIEARBGmgEcsxAKly+/5QMfZCa7Va9HUVSr1aIogoicAAGSYMfHxwA2Njb29vbW1tYODg5yuRxOvOPj406nc+PGjZWVlXw+3+v1tur18traOz7zey/8zN/d73ZJuhEjjjkNjGnmo5hGd8JIp5M0c3fQSHeCNGcMEiRIkCBAgkYCnAAnQBAEJwCOgWMASSNoNAMJEkR6aemtH/xQ4bWvvdbvt37wg2KxuLi4SBIicjIESIKFEABcunRpb29vaWkJp8GNGzfa7fa5c+fuv//+KIoAFIvFmZmZer1eLBbf8ZnPvvAz79nv9kAn6UY4x5yk0WPCyBHdCCfcYUYfuRl8BBJGOkEQBCfAMcCMZiBBggQJEgRIECBpBI1m4AQIkgAzS0vv+Mxnp/P5Rqt1cHBQqVSy2SxE5CQJkMRLvwIn3tHRUbfbHQwGKysrc3Nz+DPm5uaiKNre3j7MZh/7j7/3R//8l65+9zsjH2JEGt1JozvBCTdD7DRzdwJuhlFMM/eYTjeCBAkCJECQIDFG0gxG0mCkGUiawQwgSBAAQYK0EBYuP/C23/jQKJXa3txMp9O1Wi2EABE5YQJEToN+v9/pdNLpdK1Wi6IIf04mk6lUKo1G48pw+Mgnnh5sbPyX9/3T/W7XY6eZjxxmdHcaOCLNOaKZj0YgafSYNLoTIEFwAhwDOAFOgCAITgAcA8cAToATIDJLS2/70IfnL13auXbtyssvl0qlhYUFiMiJFCBysh0dHXW73cFgUCwW5+fn8ReLoujChQutVmurXi9fvPjOZ5/74lNPHHS7zhHMGI/cDD6imXtMmjOGGePYOeEkjBwRJAiQAEGCxBgJEiRIECBBgAQJECQIgCDTS8vvfOa5qVyu3mjEcVytVtPpNETkpAoQOcH6/X673c5kMrVaLYoi/L+YWblc3tnZ2dzcLJfL7/rcc1988sn9boeMnQbGNPNRTKM7YaTTSZAgQSPdzUCQBMcAToATIAiCEwDHwDGAEyCnpqcXHnjg7f/+w0dRtLWxkc/ni8Xi1NQUROQECxA5kY6Ojrrd7mAwKBaL8/Pz+GEUCoUoira3txcWFt75uc996akn97sdOMecBAEQJJ1uhHPMOeZuBh+RhBlAkCAxRoIECRIESBAgQQIECSKztPz2D//W3KVLV65e7e/srK6u5vN5iMiJFyBy8vT7/Xa7nclkarVaFEX44eVyuWq1Wq/XD2dmHvvss3/0vn929TvfHg2PQNLMRzGN7gRIM3enmbvDQTNMkEaYkQQnQBAEJwCOgWOA2dR0KDz4urd/+DeZnd2q16empqrV6szMDETkNAgQOUmOjo46nc7u7u7Kysrc3Bx+BKlUqlKpNJvN3v7+I7/z6b3Nja/943+03+k4f2sEoAAACQNJREFUSaPHhJEjOh0k3GFGHzkIgAQ4AZJmMIIECQI0GmFGI2iZ5eWHf+sjhcsPXOv32xsbS0tLi4uLZgYROSUCRE6Mfr/fbrczmUytVouiCD+yEML6+nq3292q18sXLr77+S9+4d3v3O923AlOuBlip5m7E3AzjGKMkSAxRoIExwxGmoEACRJgZnn53Z//QjQ/32i1Dg4OLly4MDs7CxE5VQJEToDhcNjtdnd3d1dWVubm5nD7kCwWi1EUbW1tlUqld3/hS8+/6x373S7dnQaOSHOOaOajEUga4Q5OgBMgCIITAMdAToWpwoOvf/gjv+2ZzMbGRjqdrlar09PTEJHTJkDkXuv3+61WK5vN1mq1KIpwB8zPz0dR1Gg0Zmdn3/X8F//wn/zDnT/99mg4pJl7TJozhhnj2EmMkRgjQYIECQIkCJCZ5eLDH/3owo9dvtbvdzY3S6VSoVCAiJxOASL3znA47HQ6e3t7Kysrc3NzuJOy2WylUmk0GleAn/xPz9z4/v/86i/8/H67Q6M7YaTTSZAASIITIAiCEwCnQlh8/Rse/ujHQj6/3WweHx/XarV0Og0RObUCRO6Rfr/farVmZ2drtVoURbjzoii6cOFCq9XaqtfXavf/9JdffP7xx/babRg5ohvhHHO8ggQJEiQIkJni8iMf/+Tigw8O9vZe3tg4f/78+vr61NQUROQ0CxC564bDYafT2dvbK5VK+Xwed5GZlcvlXq+3ublZLpd/6oUXP//4o/vttpshdpq5OwFwAgRBcCJTXPnpL794bmmp0+lcv369VCrNzc1BRE6/AJG7q9/vt1qtbDZbq9WiKMK9sLS0NDMzs729XSgUfuqFF59//NG9dpug02nmcUwzGEmD2VQ0vfi6Nzzy8Y8zl9vc3DSzarWaSqUgImdCgMjdNTMzUyqV8vk87qnz589PT083Go1hKvWuL335a7/48zt/+u3R8BAESJAgQWaKyz/xyU8tvu51/cGgtblZKBSWl5dJQkTOigCRu+vcK3ACpNPpSqXSaDR6w+FPPvvc7ve//5X3/uxeu0USBMFMsfjEH3xlplBottv7+/vr6+u5XA4icrYEiCRYCGF9fb3b7W7V6+Vq9YmvfPU/P/LwXrtt09NLr3/DTzz9Kc9mNzY2UqlUpVKJoggicuYEiCSbma2srMzMzGxtbZVKpSe++rX//qHfuPzU3yk88ODVfr+zuVkqlQqFAkTkjAoQEWB+fj6Kou3t7fPnz/+NX/v149Fou9UaDofVajWTyUBEzq4AkdstjmMzw2mTzWYrlUqj0fjOd7/r7nNzc+VyOYQAETnTAkRun5s3bw6Hw3q9vra2ls/ncdpMT0+nUqlms5nJZObn50MIEJGzLkDkNonj+OrVq71e7+DgYGVlJY5jM8PpcevWrUajQfKNb3zj7u7u5uZmuVzO5/MQkTMtQOQ2OTg4yGazBwcH5XK5UCjgVLl27Vqr1SoUCktLS2Z27ty5KIoajcbh4eHy8jJE5OwKELlNstlsHMe5XM7McHocHx93Op3BYLC+vp7L5fC/5fP5KIoajcbh4WGpVAohQETOogCR28fMcKrs7e21Wq0oimq1WhRF+D+l0+mLFy82m82tra1yuZxKpSAiZ06ASCK5+87OTrvdLhaLi4uLJPF/Mz09fd9997Xb7c3NzbW1tdnZWYjI2RIgkjzD4bDVag2Hw0qlks1m8ZciWSqVZmZmXnrppdXV1YWFBYjIGRIgkjCDwaDZbM7OzpbL5RACXp2FhYUoira3tw8PD4vFoplBRM6EAJHEiOO41+vt7OyUSqX5+Xn8kGZnZyuVSqPRqNfrq6ur09PTEJHTL0AkGW7dutVqteI4rlar586dw/+XVCp14cKFVqv10ksvlcvldDoNETnlAkQS4Pr1681mc35+vlgsmhl+BCGE9fX1bre7ublZLpfz+TxE5DQLEDnTjo+PO53OYDAol8v5fB63yfLy8szMTKPRGA6HS0tLEJFTK0Dk7Do4OGg0GlEU1Wq1KIpwW+Xz+SiKtre3U6lULpeDiJxOASJn1M7OTqvVKhaLi4uLJHEHpNPpixcvRlEEETm1AkTOnOFw2Ol0bt68WalUstks7qQoiiAip1mAyNkyGAxarVY6na5WqyEEiIj8pQJEzoo4jnu93pUrV0ql0sLCAu6RwWAwOzu7u7uby+UgIidegMiZcOvWrVarFcdxtVpNp9O4R9w9iqJvfOMbly9fvnHjxvnz5yEiJ1uAyOnX7/ebzebc3Nzy8vLU1BTund3d3cNX1Ov1Uql0dHQ0PT0NETnBAkROv1Qqtbq6ms/nca/lcrlWq3Xp0qVUKgVgenoaInKyBYicfqlX4GQolUoQkdMjQEREJMECREREEixAREQkwQJEREQSLEDkxNvb28tkMvv7+9lsFiIit1WAyMl269atK1euNBqNtbU1iIjcbgEiJ9v29raZHRwcHB4eZjIZiIjcVgEiJ9hgMKhWq71eb25ubn5+HiIit1uAyAmWy+UAFItFiIjcGQEiIiIJFiAiIpJgASIiIgkWICIikmABIiIiCRYgIiKSYAEiIiIJFiAiIpJgASIiIgkWICIikmABIiIiCRYgIiKSYAEiIiIJFiAiIpJgASIiIgkWICIikmABIiIiCRYgIiKSYAEiIiIJFiAiIpJgASIiIgkWICIikmABIiIiCRYgIiKSYAEiIiIJFiAiIpJgASIiIgkWICIikmABIiIiCRYgIiKSYAEiIiIJFiAiIpJgASIiIgkWICIikmABIiIiCRYgIiKSYAEiIiIJFiAiIpJgASIiIgkWICIikmABIiIiCRYgIiKSYAEiIiIJFiAiIpJgASIiIgkWICIikmABIiIiCRYgIiKSYAEiIiIJFiAiIpJgASIiIgkWICIikmABIiIiCRYgIiKSYAEiIiIJFiAiIpJgASIiIgkWICIikmABIiIiCRYgIiKSYAEiIiIJFiAiIpJgASIiIgkWICIikmABIiIiCRYgIiKSYAEiIiIJFiAiIpJgASIiIgkWICIikmABIiIiCRYgIiKSYAEiIiIJFiAiIpJgASIiIgn2vwCth7AjKTScDgAAAABJRU5ErkJggg==", "text/html": [ - "" + "" ] }, - "execution_count": 17, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# Plot with WriteVTK\n", - "WriteVTK.vtk_grid(\"Γd\",Γd) do plt\n", - " GT.plot!(plt,g;label=\"g\")\n", - "end\n", - "\n", - "# Plot `Quantity <: AbstractQuantity` instances with Makie\n", "GLMakie.plot(Γd,color=g)" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/html": [ - "" + "" ] }, - "execution_count": 18, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# Plot with WriteVTK\n", - "WriteVTK.vtk_grid(\"Ω\",Ω) do plt\n", - " GT.plot!(plt,uhd;label=\"uhd\")\n", - "end\n", - "\n", - "# Plot `DiscreteField <: AbstractQuantity` instances using Makie\n", "GLMakie.plot(Ω,color=uhd)" ] }, @@ -618,23 +398,12 @@ "source": [ "## Numerical integration\n", "\n", - "Once we have built the interpolation spaces, the next step is to set up the machinery to perform the integrals in the weak form numerically. Here, we need to compute integrals on the interior of the domain $\\Omega$ and on the Neumann boundary $\\Gamma_{\\rm N}$. In both cases, we need two main ingredients. We need to define an integration mesh (i.e. a triangulation of the integration domain), plus a Gauss-like quadrature in each of the cells in the triangulation. \n", - "\n", - "### TO BE EDITED...\n", - "\n", - "In Gridap, integration meshes are represented by types inheriting from the abstract type `Triangulation`. For integrating on the domain $\\Omega$, we build the following triangulation and the corresponding Lebesgue measure, which will allow to write down integrals in a syntax similar to the usual mathematical notation." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Compute $\\Omega$ integration domain" + "Compute $\\Omega$ integration domain:" ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -643,7 +412,7 @@ "GalerkinToolkit.Measure(…)" ] }, - "execution_count": 19, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -657,23 +426,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### TO BE EDITED...\n", - "\n", - "Here, we build a triangulation from the cells of the model and build (an approximation of) the Lebesgue measure using a quadrature rule of degree 2 in the cells of this triangulation. This is enough for integrating the corresponding terms of the weak form exactly for an interpolation of order 1.\n", - "\n", - "On the other hand, we need a special type of triangulation, represented by the type `BoundaryTriangulation`, to integrate on the boundary. Essentially, a `BoundaryTriangulation` is a particular type of `Triangulation` that is aware of which cells in the model are touched by faces on the boundary. We build an instance of this type from the discrete model and the names used to identify the Neumann boundary as follows:" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Compute $\\Gamma_{\\rm N}$ integration domain" + "Compute $\\Gamma_{\\rm N}$ integration domain:" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -682,7 +440,7 @@ "GalerkinToolkit.Measure(…)" ] }, - "execution_count": 20, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -695,12 +453,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Differential operators" + "## Differential operators\n", + "\n", + "Define the gradient operator and generic function:" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -709,7 +469,7 @@ "∇ (generic function with 1 method)" ] }, - "execution_count": 21, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -727,12 +487,12 @@ "source": [ "## Weak form\n", "\n", - "With all the ingredients presented so far, we are ready to define the weak form. This is done by defining functions representing the bi-linear and linear forms:" + "Define functions representing the bi-linear and linear forms:" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -741,52 +501,46 @@ "l (generic function with 1 method)" ] }, - "execution_count": 22, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "using LinearAlgebra\n", + "\n", "f = GT.analytical_field(Ω) do x\n", " 1.0\n", "end\n", "h = GT.analytical_field(Ω) do x\n", " 3.0\n", "end\n", + "\n", "a(u,v) = GT.∫( x->∇(u,x)⋅∇(v,x), dΩ)\n", "l(v) = GT.∫( x->v(x)*f(x), dΩ) + GT.∫( x->v(x)*h(x),dΓn)" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Note that by using the integral function `∫`, the Lebesgue measures `dΩ`, `dΓ`, and the gradient function `∇`, the weak form is written with an obvious relation with the corresponding mathematical notation." - ] - }, { "cell_type": "markdown", "metadata": {}, "source": [ " ## FE Problem\n", "\n", - "### TO BE EDITED...\n", - " At this point, we can build the FE problem that, once solved, will provide the numerical solution we are looking for. A FE problem is represented in Gridap by types inheriting from the abstract type `FEOperator` (both for linear and nonlinear cases). Since we want to solve a linear problem, we use the concrete type `AffineFEOperator`, i.e., a problem represented by a matrix and a right hand side vector." + "Build up the linear problem:" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "([7.291212384108405e-304, 2.121995791e-314, 2.834986376732e-311, 4.0474e-320, 2.529418982843e-311, 0.0, 0.0, 0.0, 7.71e-321, 6.76e-321 … 2.530061924e-314, 4.0e-323, 2.121995791e-314, 1.0e-323, 0.0, NaN, 0.0, 0.0, NaN, 3.38e-321], sparse([1, 22, 74, 289, 337, 338, 339, 340, 341, 1872 … 6303, 335, 465, 467, 468, 1806, 6201, 6224, 6232, 6304], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 6303, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304], [0.06443080405538211, -0.0011816946972152084, -0.0019141180663583925, -0.03255921926190384, -0.013954244941888471, -0.009620087896820673, -0.0021278804315064915, -0.004654033162377993, -0.005173786773138719, 0.003329780400807812 … 0.21999530084991323, -0.015615599976174236, 0.003972555304119093, -0.009088995023018824, -0.00030902681072076353, -0.013784861561036393, -0.014076977113079436, -0.024457375688586837, -0.013734513123868308, 0.17287503833373258], 6304, 6304), [0.0015677351619201938, 0.0015207565876126684, 0.0015232957017090134, 0.0016182302571138272, 0.0013414312146763385, 0.0014776038723584638, 0.001306589310230424, 0.0014160610368619696, 0.0014136920830547547, 0.0014139259120884476 … 0.09466909943634595, 3.837716427462898e-5, 4.067983156302676e-5, 3.40747082227309e-5, 3.410273174605993e-5, 0.08456444214161216, 0.07001671663821094, 3.7083120014430675e-5, 3.516169468651288e-5, 0.17159606501883534])" + "([7.291212384108405e-304, 2.121995791e-314, 2.834986376732e-311, 4.0474e-320, 2.529418982843e-311, 0.0, 0.0, 0.0, 7.875e-321, 6.76e-321 … 2.6704900206e-314, 8.487983168e-314, 2.1219957924e-314, NaN, NaN, NaN, 2.842271464e-314, 2.6704684467e-314, 0.0, 5.21502070370693e-310], sparse([1, 22, 74, 289, 337, 338, 339, 340, 341, 1872 … 6303, 335, 465, 467, 468, 1806, 6201, 6224, 6232, 6304], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 6303, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304, 6304], [0.06443080405538211, -0.0011816946972152084, -0.0019141180663583925, -0.03255921926190384, -0.013954244941888471, -0.009620087896820673, -0.0021278804315064915, -0.004654033162377993, -0.005173786773138719, 0.003329780400807812 … 0.21999530084991323, -0.015615599976174236, 0.003972555304119093, -0.009088995023018824, -0.00030902681072076353, -0.013784861561036393, -0.014076977113079436, -0.024457375688586837, -0.013734513123868308, 0.17287503833373258], 6304, 6304), [0.0015677351619201938, 0.0015207565876126684, 0.0015232957017090134, 0.0016182302571138272, 0.0013414312146763385, 0.0014776038723584638, 0.001306589310230424, 0.0014160610368619696, 0.0014136920830547547, 0.0014139259120884476 … 0.11944317760885609, 3.837716427462898e-5, 4.067983156302676e-5, 3.40747082227309e-5, 3.410273174605993e-5, 0.07847908620614856, 0.07057584867307046, 3.7083120014430675e-5, 3.516169468651288e-5, 0.21447856405151927])" ] }, - "execution_count": 23, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -801,50 +555,47 @@ "source": [ "## Solver phase\n", "\n", - " We have constructed a FE problem, the last step is to solve it. \n", - " \n", - "### TO BE EDITED...\n", - "In Gridap, FE problems are solved with types inheriting from the abstract type `FESolver`. Since this is a linear problem, we use a `LinearFESolver`:" + " Solve the linear system:" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "6304-element Vector{Float64}:\n", - " 2.288817650800605\n", - " 3.191214461559076\n", - " 3.2437698279963745\n", - " 4.51302196004918\n", - " 4.137978510723659\n", - " 2.651183214561197\n", - " 3.9985286410715637\n", - " 2.3676403246611577\n", - " 2.6253865316943625\n", - " 3.1924629585377917\n", - " 2.2896951265865444\n", - " 3.1863629312428032\n", - " 3.244574102492009\n", + " 0.583983093442735\n", + " 2.080513886884785\n", + " 2.383517868303316\n", + " 3.678673361557304\n", + " 3.6304538438432963\n", + " 2.659196595893013\n", + " 3.3109024299487757\n", + " 2.3000125990285785\n", + " 1.9571913681097337\n", + " 3.2446815470013384\n", + " 0.6070946802454475\n", + " 2.0767748974364917\n", + " 2.385048334143519\n", " ⋮\n", - " 4.285487712910334\n", - " 2.9668852150686487\n", - " 2.020241401823711\n", - " 2.3980575528123103\n", - " 3.991208223188683\n", - " 3.6282800936694914\n", - " 3.817091127051114\n", - " 2.0771951682489314\n", - " 2.0995109886643184\n", - " 2.4363879401098414\n", - " 4.398698443572706\n", - " 2.0089547066118425" + " 3.4554164897441195\n", + " 2.1526565397492563\n", + " 2.5052713709379653\n", + " 0.8436925250103349\n", + " 3.663735716962159\n", + " 2.8473164198005643\n", + " 3.6026210550320883\n", + " 1.9241105367780258\n", + " 2.120869552315746\n", + " 1.5432753167154554\n", + " 3.5462578026955396\n", + " 2.4914847685009494" ] }, - "execution_count": 24, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -857,14 +608,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### TO BE EDITED...\n", - "\n", - "`LinearFESolver` objects are built from a given algebraic linear solver. In this case, we use a LU factorization. Now we are ready to solve the FE problem with the FE solver as follows:" + "Build the PDE solution from the basis-set coefficients in $x$:" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -873,7 +622,7 @@ "GalerkinToolkit.DiscreteField(…)" ] }, - "execution_count": 25, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -882,38 +631,24 @@ "uh = GT.solution_field(uhd,x)" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The `solve` function returns the computed numerical solution `uh`. This object is an instance of `FEFunction`, the type used to represent a function in a FE space. We can inspect the result by writing it into a `vtk` file:" - ] - }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 21, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/html": [ - "" + "" ] }, - "execution_count": 27, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# Plot with WriteVTK\n", - "WriteVTK.vtk_grid(\"Ω\",Ω) do plt\n", - " GT.plot!(plt,uhd;label=\"uhd\")\n", - " GT.plot!(plt,uh;label=\"uh\")\n", - "end\n", - "\n", - "# Plot with Makie\n", "GLMakie.plot(Ω,color=uh)" ] }, @@ -925,20 +660,11 @@ "\n", "[1] C. Johnson. *Numerical Solution of Partial Differential Equations by the Finite Element Method*. Dover Publications, 2009." ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---\n", - "\n", - "*This notebook was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).*" - ] } ], "metadata": { "kernelspec": { - "display_name": "Julia 1.11.0", + "display_name": "Julia 1.11.1", "language": "julia", "name": "julia-1.11" }, @@ -946,7 +672,7 @@ "file_extension": ".jl", "mimetype": "application/julia", "name": "julia", - "version": "1.11.0" + "version": "1.11.1" } }, "nbformat": 4,