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annotate LazyTensors/src/lazy_operations.jl @ 265:4308b500d6e7 boundary_conditions

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Add ideas to TODO.txt
author Vidar Stiernström <vidar.stiernstrom@it.uu.se>
date Thu, 05 Dec 2019 09:25:31 +0100
parents 8ffd9c2e2119
children
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1 """
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2 LazyArray{T,D} <: AbstractArray{T,D}
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3
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4 Array which is calcualted lazily when indexing.
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6 A subtype of `LazyArray` will use lazy version of `+`, `-`, `*`, `/`.
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7 """
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8 abstract type LazyArray{T,D} <: AbstractArray{T,D} end
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9 export LazyArray
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10
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11
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12
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13 """
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14 LazyTensorMappingApplication{T,R,D} <: LazyArray{T,R}
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15
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16 Struct for lazy application of a TensorMapping. Created using `*`.
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17
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18 Allows the result of a `TensorMapping` applied to a vector to be treated as an `AbstractArray`.
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19 With a mapping `m` and a vector `v` the LazyTensorMappingApplication object can be created by `m*v`.
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20 The actual result will be calcualted when indexing into `m*v`.
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21 """
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22 struct LazyTensorMappingApplication{T,R,D} <: LazyArray{T,R}
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23 t::TensorMapping{T,R,D}
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24 o::AbstractArray{T,D}
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25 end
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26 export LazyTensorMappingApplication
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28 Base.:*(tm::TensorMapping{T,R,D}, o::AbstractArray{T,D}) where {T,R,D} = LazyTensorMappingApplication(tm,o)
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29
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30 Base.getindex(ta::LazyTensorMappingApplication{T,R,D}, I::Vararg{Int,R}) where {T,R,D} = apply(ta.t, ta.o, I)
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31 Base.size(ta::LazyTensorMappingApplication{T,R,D}) where {T,R,D} = range_size(ta.t,size(ta.o))
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32 # TODO: What else is needed to implement the AbstractArray interface?
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33
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34 # # We need the associativity to be a→b→c = a→(b→c), which is the case for '→'
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35 Base.:*(a::TensorMapping{T,R,D}, b::TensorMapping{T,D,K}, args::Union{TensorMapping{T}, AbstractArray{T}}...) where {T,R,D,K} = foldr(*,(a,b,args...))
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36 # # Should we overload some other infix binary operator?
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37 # →(tm::TensorMapping{T,R,D}, o::AbstractArray{T,D}) where {T,R,D} = LazyTensorMappingApplication(tm,o)
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38 # TODO: We need to be really careful about good error messages.
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39 # For example what happens if you try to multiply LazyTensorMappingApplication with a TensorMapping(wrong order)?
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40
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41 """
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42 LazyElementwiseOperation{T,D,Op,T1,T2} <: LazyArray{T,D}
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43 Struct allowing for lazy evaluation of elementwise operations on AbstractArrays.
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44
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45 A LazyElementwiseOperation contains two datatypes T1, and T2, together with an operation,
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46 where at least one of T1 and T2 is an AbstractArray, and one may be a Real.
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47 The operations are carried out when the LazyElementwiseOperation is indexed.
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48 """
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49 struct LazyElementwiseOperation{T,D,Op,T1,T2} <: LazyArray{T,D}
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50 a::T1
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51 b::T2
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52
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53 @inline function LazyElementwiseOperation{T,D,Op}(a::T1,b::T2) where {T,D,Op,T1<:AbstractArray{T,D},T2<:AbstractArray{T,D}}
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54 @boundscheck if size(a) != size(b)
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55 throw(DimensionMismatch("dimensions must match"))
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56 end
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57 return new{T,D,Op,T1,T2}(a,b)
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58 end
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59
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60 @inline function LazyElementwiseOperation{T,D,Op}(a::T1,b::T2) where {T,D,Op,T1<:AbstractArray{T,D},T2<:Real}
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61 return new{T,D,Op,T1,T2}(a,b)
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62 end
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63
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64 @inline function LazyElementwiseOperation{T,D,Op}(a::T1,b::T2) where {T,D,Op,T1<:Real,T2<:AbstractArray{T,D}}
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65 return new{T,D,Op,T1,T2}(a,b)
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66 end
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67 end
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68 # TODO: Move Op to be the first parameter? Compare to Binary operations
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69
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70 Base.size(v::LazyElementwiseOperation) = size(v.a)
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71
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72 # TODO: Make sure boundschecking is done properly and that the lenght of the vectors are equal
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73 # NOTE: Boundschecking in getindex functions now assumes that the size of the
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74 # vectors in the LazyElementwiseOperation are the same size. If we remove the
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75 # size assertion in the constructor we might have to handle
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76 # boundschecking differently.
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77 Base.@propagate_inbounds @inline function Base.getindex(leo::LazyElementwiseOperation{T,D,:+,T1,T2}, I::Vararg{Int,D}) where {T,D,T1<:AbstractArray{T,D},T2<:AbstractArray{T,D}}
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78 @boundscheck if !checkbounds(Bool,leo.a,I...)
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79 throw(BoundsError([leo],I...))
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80 end
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81 return leo.a[I...] + leo.b[I...]
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82 end
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84 Base.@propagate_inbounds @inline function Base.getindex(leo::LazyElementwiseOperation{T,D,:-,T1,T2}, I::Vararg{Int,D}) where {T,D,T1<:AbstractArray{T,D},T2<:AbstractArray{T,D}}
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85 @boundscheck if !checkbounds(Bool,leo.a,I...)
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86 throw(BoundsError([leo],I...))
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87 end
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88 return leo.a[I...] - leo.b[I...]
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89 end
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91 Base.@propagate_inbounds @inline function Base.getindex(leo::LazyElementwiseOperation{T,D,:*,T1,T2}, I::Vararg{Int,D}) where {T,D,T1<:AbstractArray{T,D},T2<:AbstractArray{T,D}}
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92 @boundscheck if !checkbounds(Bool,leo.a,I...)
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93 throw(BoundsError([leo],I...))
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94 end
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95 return leo.a[I...] * leo.b[I...]
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96 end
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98 Base.@propagate_inbounds @inline function Base.getindex(leo::LazyElementwiseOperation{T,D,:/,T1,T2}, I::Vararg{Int,D}) where {T,D,T1<:AbstractArray{T,D},T2<:AbstractArray{T,D}}
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99 @boundscheck if !checkbounds(Bool,leo.a,I...)
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100 throw(BoundsError([leo],I...))
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101 end
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102 return leo.a[I...] / leo.b[I...]
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103 end
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104
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105 Base.@propagate_inbounds @inline function Base.getindex(leo::LazyElementwiseOperation{T,D,:+,T1,T2}, I::Vararg{Int,D}) where {T,D,T1<:AbstractArray{T,D},T2<:Real}
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106 @boundscheck if !checkbounds(Bool,leo.a,I...)
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107 throw(BoundsError([leo],I...))
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108 end
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109 return leo.a[I...] + leo.b
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110 end
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111
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112 Base.@propagate_inbounds @inline function Base.getindex(leo::LazyElementwiseOperation{T,D,:-,T1,T2}, I::Vararg{Int,D}) where {T,D,T1<:AbstractArray{T,D},T2<:Real}
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113 @boundscheck if !checkbounds(Bool,leo.a,I...)
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114 throw(BoundsError([leo],I...))
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115 end
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116 return leo.a[I...] - leo.b
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117 end
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118
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119 Base.@propagate_inbounds @inline function Base.getindex(leo::LazyElementwiseOperation{T,D,:*,T1,T2}, I::Vararg{Int,D}) where {T,D,T1<:AbstractArray{T,D},T2<:Real}
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120 @boundscheck if !checkbounds(Bool,leo.a,I...)
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121 throw(BoundsError([leo],I...))
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122 end
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123 return leo.a[I...] * leo.b
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124 end
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125
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126 Base.@propagate_inbounds @inline function Base.getindex(leo::LazyElementwiseOperation{T,D,:/,T1,T2}, I::Vararg{Int,D}) where {T,D,T1<:AbstractArray{T,D},T2<:Real}
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127 @boundscheck if !checkbounds(Bool,leo.a,I...)
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128 throw(BoundsError([leo],I...))
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129 end
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130 return leo.a[I...] / leo.b
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131 end
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132
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133 Base.@propagate_inbounds @inline function Base.getindex(leo::LazyElementwiseOperation{T,D,:+,T1,T2}, I::Vararg{Int,D}) where {T,D,T1<:Real,T2<:AbstractArray{T,D}}
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134 @boundscheck if !checkbounds(Bool,leo.b,I...)
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135 throw(BoundsError([leo],I...))
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136 end
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137 return leo.a + leo.b[I...]
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138 end
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139
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140 Base.@propagate_inbounds @inline function Base.getindex(leo::LazyElementwiseOperation{T,D,:-,T1,T2}, I::Vararg{Int,D}) where {T,D,T1<:Real,T2<:AbstractArray{T,D}}
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141 @boundscheck if !checkbounds(Bool,leo.b,I...)
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142 throw(BoundsError([leo],I...))
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143 end
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144 return leo.a - leo.b[I...]
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145 end
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146
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147 Base.@propagate_inbounds @inline function Base.getindex(leo::LazyElementwiseOperation{T,D,:*,T1,T2}, I::Vararg{Int,D}) where {T,D,T1<:Real,T2<:AbstractArray{T,D}}
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148 @boundscheck if !checkbounds(Bool,leo.b,I...)
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149 throw(BoundsError([leo],I...))
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150 end
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151 return leo.a * leo.b[I...]
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152 end
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153
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154 Base.@propagate_inbounds @inline function Base.getindex(leo::LazyElementwiseOperation{T,D,:/,T1,T2}, I::Vararg{Int,D}) where {T,D,T1<:Real,T2<:AbstractArray{T,D}}
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155 @boundscheck if !checkbounds(Bool,leo.b,I...)
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156 throw(BoundsError([leo],I...))
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157 end
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158 return leo.a / leo.b[I...]
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159 end
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160
194
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161 # Define lazy operations for AbstractArrays. Operations constructs a LazyElementwiseOperation which
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162 # can later be indexed into. Lazy operations are denoted by the usual operator followed by a tilde
202
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163 Base.@propagate_inbounds +̃(a::AbstractArray{T,D}, b::AbstractArray{T,D}) where {T,D} = LazyElementwiseOperation{T,D,:+}(a,b)
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164 Base.@propagate_inbounds -̃(a::AbstractArray{T,D}, b::AbstractArray{T,D}) where {T,D} = LazyElementwiseOperation{T,D,:-}(a,b)
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165 Base.@propagate_inbounds *̃(a::AbstractArray{T,D}, b::AbstractArray{T,D}) where {T,D} = LazyElementwiseOperation{T,D,:*}(a,b)
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166 Base.@propagate_inbounds /̃(a::AbstractArray{T,D}, b::AbstractArray{T,D}) where {T,D} = LazyElementwiseOperation{T,D,:/}(a,b)
194
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167
263
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168 Base.@propagate_inbounds +̃(a::AbstractArray{T,D}, b::Real) where {T,D} = LazyElementwiseOperation{T,D,:+}(a,b)
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169 Base.@propagate_inbounds -̃(a::AbstractArray{T,D}, b::Real) where {T,D} = LazyElementwiseOperation{T,D,:-}(a,b)
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170 Base.@propagate_inbounds *̃(a::AbstractArray{T,D}, b::Real) where {T,D} = LazyElementwiseOperation{T,D,:*}(a,b)
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171 Base.@propagate_inbounds /̃(a::AbstractArray{T,D}, b::Real) where {T,D} = LazyElementwiseOperation{T,D,:/}(a,b)
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172
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173 Base.@propagate_inbounds +̃(a::Real, b::AbstractArray{T,D}) where {T,D} = LazyElementwiseOperation{T,D,:+}(a,b)
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174 Base.@propagate_inbounds -̃(a::Real, b::AbstractArray{T,D}) where {T,D} = LazyElementwiseOperation{T,D,:-}(a,b)
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175 Base.@propagate_inbounds *̃(a::Real, b::AbstractArray{T,D}) where {T,D} = LazyElementwiseOperation{T,D,:*}(a,b)
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176 Base.@propagate_inbounds /̃(a::Real, b::AbstractArray{T,D}) where {T,D} = LazyElementwiseOperation{T,D,:/}(a,b)
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177
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178
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179
204
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180 # NOTE: Är det knas att vi har till exempel * istället för .* ??
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181 # Oklart om det ens går att lösa..
205
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182 Base.@propagate_inbounds Base.:+(a::LazyArray{T,D}, b::LazyArray{T,D}) where {T,D} = a +̃ b
202
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183 Base.@propagate_inbounds Base.:+(a::LazyArray{T,D}, b::AbstractArray{T,D}) where {T,D} = a +̃ b
205
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184 Base.@propagate_inbounds Base.:+(a::AbstractArray{T,D}, b::LazyArray{T,D}) where {T,D} = a +̃ b
204
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185
205
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186 Base.@propagate_inbounds Base.:-(a::LazyArray{T,D}, b::LazyArray{T,D}) where {T,D} = a -̃ b
202
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187 Base.@propagate_inbounds Base.:-(a::LazyArray{T,D}, b::AbstractArray{T,D}) where {T,D} = a -̃ b
199
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188 Base.@propagate_inbounds Base.:-(a::AbstractArray{T,D}, b::LazyArray{T,D}) where {T,D} = a -̃ b
204
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189
206
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190 # Element wise operation for `*` and `\` are not overloaded due to conflicts with the behavior
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191 # of regular `*` and `/` for AbstractArrays. Use tilde versions instead.
194
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192
195
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193 export +̃, -̃, *̃, /̃
194
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194
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195
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196
197
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197 """
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198 LazyTensorMappingTranspose{T,R,D} <: TensorMapping{T,D,R}
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199
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200 Struct for lazy transpose of a TensorMapping.
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201
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202 If a mapping implements the the `apply_transpose` method this allows working with
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203 the transpose of mapping `m` by using `m'`. `m'` will work as a regular TensorMapping lazily calling
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204 the appropriate methods of `m`.
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205 """
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206 struct LazyTensorMappingTranspose{T,R,D} <: TensorMapping{T,D,R}
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207 tm::TensorMapping{T,R,D}
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208 end
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209 export LazyTensorMappingTranspose
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210
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211 # # TBD: Should this be implemented on a type by type basis or through a trait to provide earlier errors?
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212 Base.adjoint(t::TensorMapping) = LazyTensorMappingTranspose(t)
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213 Base.adjoint(t::LazyTensorMappingTranspose) = t.tm
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214
237
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215 apply(tm::LazyTensorMappingTranspose{T,R,D}, v::AbstractArray{T,R}, I::NTuple{D,Int}) where {T,R,D} = apply_transpose(tm.tm, v, I)
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216 apply_transpose(tm::LazyTensorMappingTranspose{T,R,D}, v::AbstractArray{T,D}, I::NTuple{R,Int}) where {T,R,D} = apply(tm.tm, v, I)
197
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217
232
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218 range_size(tmt::LazyTensorMappingTranspose{T,R,D}, d_size::NTuple{R,Integer}) where {T,R,D} = domain_size(tmt.tm, d_size)
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219 domain_size(tmt::LazyTensorMappingTranspose{T,R,D}, r_size::NTuple{D,Integer}) where {T,R,D} = range_size(tmt.tm, r_size)
197
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220
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221
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222
210
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223
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224 struct LazyTensorMappingBinaryOperation{Op,T,R,D,T1<:TensorMapping{T,R,D},T2<:TensorMapping{T,R,D}} <: TensorMapping{T,D,R}
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225 A::T1
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226 B::T2
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227
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228 @inline function LazyTensorMappingBinaryOperation{Op,T,R,D}(A::T1,B::T2) where {Op,T,R,D, T1<:TensorMapping{T,R,D},T2<:TensorMapping{T,R,D}}
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229 return new{Op,T,R,D,T1,T2}(A,B)
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230 end
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231 end
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232
237
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233 apply(mb::LazyTensorMappingBinaryOperation{:+,T,R,D}, v::AbstractArray{T,D}, I::NTuple{R,Int}) where {T,R,D} = apply(mb.A, v, I...) + apply(mb.B,v,I...)
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234 apply(mb::LazyTensorMappingBinaryOperation{:-,T,R,D}, v::AbstractArray{T,D}, I::NTuple{R,Int}) where {T,R,D} = apply(mb.A, v, I...) - apply(mb.B,v,I...)
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235
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236 range_size(mp::LazyTensorMappingBinaryOperation{Op,T,R,D}, domain_size::NTuple{D,Integer}) where {Op,T,R,D} = range_size(mp.A, domain_size)
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237 domain_size(mp::LazyTensorMappingBinaryOperation{Op,T,R,D}, range_size::NTuple{R,Integer}) where {Op,T,R,D} = domain_size(mp.A, range_size)
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238
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239 Base.:+(A::TensorMapping{T,R,D}, B::TensorMapping{T,R,D}) where {T,R,D} = LazyTensorMappingBinaryOperation{:+,T,R,D}(A,B)
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240 Base.:-(A::TensorMapping{T,R,D}, B::TensorMapping{T,R,D}) where {T,R,D} = LazyTensorMappingBinaryOperation{:-,T,R,D}(A,B)
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241
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242
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243 # TODO: Write tests and documentation for LazyTensorMappingComposition
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244 # struct LazyTensorMappingComposition{T,R,K,D} <: TensorMapping{T,R,D}
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245 # t1::TensorMapping{T,R,K}
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246 # t2::TensorMapping{T,K,D}
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247 # end
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248
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249 # Base.:∘(s::TensorMapping{T,R,K}, t::TensorMapping{T,K,D}) where {T,R,K,D} = LazyTensorMappingComposition(s,t)
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250
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251 # function range_size(tm::LazyTensorMappingComposition{T,R,K,D}, domain_size::NTuple{D,Integer}) where {T,R,K,D}
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252 # range_size(tm.t1, domain_size(tm.t2, domain_size))
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253 # end
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254
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255 # function domain_size(tm::LazyTensorMappingComposition{T,R,K,D}, range_size::NTuple{R,Integer}) where {T,R,K,D}
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256 # domain_size(tm.t1, domain_size(tm.t2, range_size))
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257 # end
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258
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259 # function apply(c::LazyTensorMappingComposition{T,R,K,D}, v::AbstractArray{T,D}, I::NTuple{R,Int}) where {T,R,K,D}
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260 # apply(c.t1, LazyTensorMappingApplication(c.t2,v), I...)
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261 # end
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262
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263 # function apply_transpose(c::LazyTensorMappingComposition{T,R,K,D}, v::AbstractArray{T,D}, I::NTuple{D,Int}) where {T,R,K,D}
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264 # apply_transpose(c.t2, LazyTensorMappingApplication(c.t1',v), I...)
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265 # end
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266
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267 # # Have i gone too crazy with the type parameters? Maybe they aren't all needed?
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268
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269 # export →