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annotate src/Grids/grid.jl @ 2016:e17d90763a3f feature/grids/multiblock_grids

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Add ndims for grid types
author Jonatan Werpers <jonatan@werpers.com>
date Wed, 12 Mar 2025 08:59:28 +0100
parents 863385aae454
children
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1 """
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2 Grid{T,D}
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3
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4 A grid with coordinates of type `T`, e.g. `SVector{3,Float64}`, and dimension
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5 `D`. The grid can be embedded in a higher dimension in which case the number
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6 of indices and the number of components of the coordinate vectors will be
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7 different.
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8
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9 All grids are expected to behave as a grid function for the coordinates.
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10
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11 `Grids` is top level abstract type for grids. A grid should implement Julia's interfaces for
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12 indexing and iteration.
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13
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14 ## Note
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15
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16 Importantly a grid does not have to be an `AbstractArray`. The reason is to
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17 allow flexible handling of special types of grids like multi-block grids, or
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18 grids with special indexing.
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19 """
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20 abstract type Grid{T,D} end
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21
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22 Base.ndims(::Grid{<:Any,D}) where D = D
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23 Base.ndims(::Type{<:Grid{<:Any,D}}) where D = D
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24 Base.eltype(::Type{<:Grid{T}}) where T = T
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25
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26 Base.getindex(g::Grid, I::CartesianIndex) = g[Tuple(I)...]
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27
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28 """
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29 coordinate_size(g)
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30
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31 The length of the coordinate vector of `Grid` `g`.
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32 """
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33 coordinate_size(::Type{<:Grid{T}}) where T = _ncomponents(T)
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34 coordinate_size(g::Grid) = coordinate_size(typeof(g)) # TBD: Name of this function?!
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35
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36 """
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37 component_type(gf)
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38
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39 The type of the components of the elements of `gf`. I.e if `gf` is a vector
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40 valued grid function, `component_view(gf)` is the element type of the vectors
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41 at each grid point.
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42
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43 # Examples
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44 ```julia-repl
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45 julia> component_type([[1,2], [2,3], [3,4]])
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46 Int64
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47 ```
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48 """
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49 component_type(T::Type) = eltype(eltype(T))
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50 component_type(t) = component_type(typeof(t))
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51
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52 """
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53 componentview(gf, component_index...)
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54
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55 A view of `gf` with only the components specified by `component_index...`.
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56
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57 # Examples
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58 ```julia-repl
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59 julia> componentview([[1,2], [2,3], [3,4]],2)
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60 3-element ArrayComponentView{Int64, Vector{Int64}, 1, Vector{Vector{Int64}}, Tuple{Int64}}:
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61 2
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62 3
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63 4
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64 ```
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65 """
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66 componentview(gf, component_index...) = ArrayComponentView(gf, component_index)
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67
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68 struct ArrayComponentView{CT,T,D,AT <: AbstractArray{T,D}, IT} <: AbstractArray{CT,D}
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69 v::AT
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70 component_index::IT
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71
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72 function ArrayComponentView(v, component_index)
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73 CT = typeof(first(v)[component_index...])
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74 return new{CT, eltype(v), ndims(v), typeof(v), typeof(component_index)}(v,component_index)
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75 end
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76 end
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77
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78 Base.size(cv::ArrayComponentView) = size(cv.v)
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79 Base.getindex(cv::ArrayComponentView, i::Int) = cv.v[i][cv.component_index...]
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80 Base.getindex(cv::ArrayComponentView, I::Vararg{Int}) = cv.v[I...][cv.component_index...]
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81 IndexStyle(::Type{<:ArrayComponentView{<:Any,<:Any,AT}}) where AT = IndexStyle(AT)
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82
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83 # TODO: Implement `setindex!`?
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84 # TODO: Implement a more general ComponentView that can handle non-AbstractArrays.
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85
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86
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87 """
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88 min_spacing(g::Grid)
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89
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90 The smallest distance between any pair of grid points in `g`.
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91 """
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92 function min_spacing end
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93
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94 """
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95 refine(g::Grid, r)
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96
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97 The grid where `g` is refined by the factor `r`.
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98
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99 See also: [`coarsen`](@ref).
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100 """
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101 function refine end
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102
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103 """
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104 coarsen(g::Grid, r)
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105
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106 The grid where `g` is coarsened by the factor `r`.
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107
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108 See also: [`refine`](@ref).
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109 """
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110 function coarsen end
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111
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112 """
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113 BoundaryIdentifier
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114
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115 An identifier for a boundary of a grid.
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116 """
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117 abstract type BoundaryIdentifier end
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118
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119 """
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120 boundary_identifiers(g::Grid)
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121
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122 Identifiers for all the boundaries of `g`.
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123 """
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124 function boundary_identifiers end
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125
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126 """
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127 boundary_grid(g::Grid, id::BoundaryIdentifier)
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128
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129 The grid for the boundary specified by `id`.
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130 """
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131 function boundary_grid end
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132 # TBD: Can we implement a version here that accepts multiple ids and grouped boundaries? Maybe we need multiblock stuff?
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133
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134 """
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135 boundary_indices(g::Grid, id::BoundaryIdentifier)
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136
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137 A collection of indices corresponding to the boundary with given id. For grids
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138 with Cartesian indexing these collections will be tuples with elements of type
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139 ``Union{Int,Colon}``.
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140
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141 When implementing this method it is expected that the returned collection can
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142 be used to index grid functions to obtain grid functions on the boundary grid.
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143 """
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144 function boundary_indices end
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145
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146 """
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147 eval_on(g::Grid, f)
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148
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149 Lazy evaluation of `f` on the grid. `f` can either be on the form `f(x,y,...)`
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150 with each coordinate as an argument, or on the form `f(x̄)` taking a
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151 coordinate vector.
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152
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153 For concrete array grid functions `map(f,g)` can be used instead.
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154 """
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155 eval_on(g::Grid, f) = eval_on(g, f, Base.IteratorSize(g))
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156 function eval_on(g::Grid, f, ::Base.HasShape)
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157 if hasmethod(f, (Any,))
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158 return LazyTensors.LazyFunctionArray((I...)->f(g[I...]), size(g))
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159 else
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160 # TBD This branch can be removed if we accept the trade off that we define f with the syntax f((x,y)) instead if we don't want to handle the vector in the body of f. (Add an example in the docs)
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161 # Also see Notes.md
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162 return LazyTensors.LazyFunctionArray((I...)->f(g[I...]...), size(g))
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163 end
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164 end
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165
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166 """
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167 eval_on(g::Grid, f::Number)
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168
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169 Lazy evaluation of a scalar `f` on the grid.
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170 """
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171 eval_on(g::Grid, f::Number) = return LazyTensors.LazyConstantArray(f, size(g))
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172
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173 _ncomponents(::Type{<:Number}) = 1
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174 _ncomponents(T::Type{<:SVector}) = length(T)
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175
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176