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annotate LazyTensors/src/LazyTensors.jl @ 184:6945c15a6a7a boundary_conditions

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Rename package LazyTensor to LazyTensors
author Jonatan Werpers <jonatan@werpers.com>
date Thu, 20 Jun 2019 21:14:20 +0200
parents LazyTensor/src/LazyTensor.jl@b7397ae8afaf
children 715ff09bb2ce
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184
6945c15a6a7a Rename package LazyTensor to LazyTensors
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1 module LazyTensors
180
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3
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4 """
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5 Mapping{T,R,D}
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6
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7 Describes a mapping of a D dimension tensor to an R dimension tensor.
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8 The action of the mapping is implemented through the method
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9
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10 apply(t::Mapping{T,R,D}, v::AbstractArray{T,D}, I::Vararg) where {R,D,T}
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11
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12 The size of range tensor should be dependent on the size of the domain tensor
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13 and the type should implement the methods
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14
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15 range_size(::Mapping{T,R,D}, domain_size::NTuple{D,Integer}) where {T,R,D}
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16 domain_size(::Mapping{T,R,D}, range_size::NTuple{R,Integer}) where {T,R,D}
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17
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18 to allow querying for one or the other.
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19
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20 Optionally the action of the transpose may be defined through
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21 apply_transpose(t::Mapping{T,R,D}, v::AbstractArray{T,D}, I::Vararg) where {R,D,T}
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22 """
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23 abstract type Mapping{T,R,D} end
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24
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25 """
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26 apply(t::Mapping{T,R,D}, v::AbstractArray{T,D}, I::Vararg) where {R,D,T}
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27
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28 Return the result of the mapping for a given index.
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29 """
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30 function apply end
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31 export apply
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32
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33 """
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34 apply_transpose(t::Mapping{T,R,D}, v::AbstractArray{T,R}, I::Vararg) where {R,D,T}
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35
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36 Return the result of the transposed mapping for a given index.
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37 """
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38 function apply_transpose end
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39 export apply_transpose
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40
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41 """
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42 Return the dimension of the range space of a given mapping
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43 """
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44 range_dim(::Mapping{T,R,D}) where {T,R,D} = R
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45
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46 """
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47 Return the dimension of the domain space of a given mapping
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48 """
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49 domain_dim(::Mapping{T,R,D}) where {T,R,D} = D
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50
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51 export range_dim, domain_dim
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52
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53 """
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54 range_size(M::Mapping, domain_size)
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55
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56 Return the resulting range size for the mapping applied to a given domain_size
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57 """
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58 function range_size end
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59
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60 """
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61 domain_size(M::Mapping, range_size)
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62
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63 Return the resulting domain size for the mapping applied to a given range_size
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64 """
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65 function domain_size end
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66
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67 export range_size, domain_size
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68 # TODO: Think about boundschecking!
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69
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70
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71 """
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72 Operator{T,D}
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73
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74 A `Mapping{T,D,D}` where the range and domain tensor have the same number of
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75 dimensions and the same size.
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76 """
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77 abstract type Operator{T,D} <: Mapping{T,D,D} end
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78 domain_size(::Operator{T,D}, range_size::NTuple{D,Integer}) where {T,D} = range_size
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79 range_size(::Operator{T,D}, domain_size::NTuple{D,Integer}) where {T,D} = domain_size
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80
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81
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82
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83 """
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84 MappingTranspose{T,R,D} <: Mapping{T,D,R}
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85
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86 Struct for lazy transpose of a Mapping.
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87
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88 If a mapping implements the the `apply_transpose` method this allows working with
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89 the transpose of mapping `m` by using `m'`. `m'` will work as a regular Mapping lazily calling
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90 the appropriate methods of `m`.
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91 """
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92 struct MappingTranspose{T,R,D} <: Mapping{T,D,R}
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93 tm::Mapping{T,R,D}
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94 end
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95
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96 # # TBD: Should this be implemented on a type by type basis or through a trait to provide earlier errors?
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97 Base.adjoint(t::Mapping) = MappingTranspose(t)
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98 Base.adjoint(t::MappingTranspose) = t.tm
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99
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100 apply(tm::MappingTranspose{T,R,D}, v::AbstractArray{T,R}, I::Vararg) where {T,R,D} = apply_transpose(tm.tm, v, I...)
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101 apply_transpose(tm::MappingTranspose{T,R,D}, v::AbstractArray{T,D}, I::Vararg) where {T,R,D} = apply(tm.tm, v, I...)
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102
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103 range_size(tmt::MappingTranspose{T,R,D}, d_size::NTuple{R,Integer}) where {T,R,D} = domain_size(tmt.tm, domain_size)
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104 domain_size(tmt::MappingTranspose{T,R,D}, r_size::NTuple{D,Integer}) where {T,R,D} = range_size(tmt.tm, range_size)
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105
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106
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107 """
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108 Application{T,R,D} <: AbstractArray{T,R}
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109
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110 Struct for lazy application of a Mapping. Created using `*`.
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111
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112 Allows the result of a `Mapping` applied to a vector to be treated as an `AbstractArray`.
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113 With a mapping `m` and a vector `v` the Application object can be created by `m*v`.
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114 The actual result will be calcualted when indexing into `m*v`.
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115 """
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116 struct Application{T,R,D} <: AbstractArray{T,R}
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117 t::Mapping{T,R,D}
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118 o::AbstractArray{T,D}
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119 end
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120
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121 Base.:*(tm::Mapping{T,R,D}, o::AbstractArray{T,D}) where {T,R,D} = Application(tm,o)
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122
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123 Base.getindex(ta::Application{T,R,D}, I::Vararg) where {T,R,D} = apply(ta.t, ta.o, I...)
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124 Base.size(ta::Application{T,R,D}) where {T,R,D} = range_size(ta.t,size(ta.o))
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125 # TODO: What else is needed to implement the AbstractArray interface?
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126
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127
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128 # # We need the associativity to be a→b→c = a→(b→c), which is the case for '→'
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129 Base.:*(args::Union{Mapping{T}, AbstractArray{T}}...) where T = foldr(*,args)
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130 # # Should we overload some other infix binary operator?
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131 # →(tm::Mapping{T,R,D}, o::AbstractArray{T,D}) where {T,R,D} = Application(tm,o)
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132 # TODO: We need to be really careful about good error messages.
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133 # For example what happens if you try to multiply Application with a Mapping(wrong order)?
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134
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135
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136
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137 # struct TensorMappingComposition{T,R,K,D} <: Mapping{T,R,D}
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138 # t1::Mapping{T,R,K}
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139 # t2::Mapping{T,K,D}
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140 # end
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141
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142 # Base.:∘(s::Mapping{T,R,K}, t::Mapping{T,K,D}) where {T,R,K,D} = TensorMappingComposition(s,t)
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143
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144 # function range_size(tm::TensorMappingComposition{T,R,K,D}, domain_size::NTuple{D,Integer}) where {T,R,K,D}
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145 # range_size(tm.t1, domain_size(tm.t2, domain_size))
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146 # end
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147
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148 # function domain_size(tm::TensorMappingComposition{T,R,K,D}, range_size::NTuple{R,Integer}) where {T,R,K,D}
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149 # domain_size(tm.t1, domain_size(tm.t2, range_size))
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150 # end
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151
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152 # function apply(c::TensorMappingComposition{T,R,K,D}, v::AbstractArray{T,D}, I::Vararg) where {T,R,K,D}
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153 # apply(c.t1, Application(c.t2,v), I...)
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154 # end
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155
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156 # function apply_transpose(c::TensorMappingComposition{T,R,K,D}, v::AbstractArray{T,D}, I::Vararg) where {T,R,K,D}
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157 # apply_transpose(c.t2, Application(c.t1',v), I...)
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158 # end
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159
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160 # # Have i gone too crazy with the type parameters? Maybe they aren't all needed?
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161
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162 # export →
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163
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164
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165 end # module