Merge pull request #653 from ConnorMallon/shape_derivative

Shape derivative

NEWS.md

@@ -4,6 +4,11 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## Unreleased
+
+### Added
+- Extra support for dual number propagation. Since PR [#653](https://github.com/gridap/Gridap.jl/pull/653)
+
 ## [0.17.8] - 2022-02-14
 
 ### Added

src/CellData/CellFields.jl

@@ -2,15 +2,15 @@
 A single point or an array of points on the cells of a Triangulation
 CellField objects can be evaluated efficiently at CellPoint instances.
 """
-struct CellPoint{DS} <: CellDatum
-  cell_ref_point::AbstractArray{<:Union{Point,AbstractArray{<:Point}}}
-  cell_phys_point::AbstractArray{<:Union{Point,AbstractArray{<:Point}}}
-  trian::Triangulation
+struct CellPoint{DS,A,B,C} <: CellDatum
+  cell_ref_point::A
+  cell_phys_point::B
+  trian::C
   domain_style::DS
 end
 
 function CellPoint(
-  cell_ref_point::AbstractArray{<:Union{Point,AbstractArray{<:Point}}},
+  cell_ref_point::AbstractArray,
   trian::Triangulation,
   domain_style::ReferenceDomain)
 
@@ -20,7 +20,7 @@ function CellPoint(
 end
 
 function CellPoint(
-  cell_phys_point::AbstractArray{<:Union{Point,AbstractArray{<:Point}}},
+  cell_phys_point::AbstractArray,
   trian::Triangulation,
   domain_style::PhysicalDomain)
   cell_map = get_cell_map(trian)
@@ -38,7 +38,7 @@ function get_data(f::CellPoint)
 end
 
 get_triangulation(f::CellPoint) = f.trian
-DomainStyle(::Type{CellPoint{DS}}) where DS = DS()
+DomainStyle(::Type{CellPoint{DS,A,B,C}}) where {DS,A,B,C} = DS()
 
 function change_domain(a::CellPoint,::ReferenceDomain,::PhysicalDomain)
   CellPoint(a.cell_ref_point,a.cell_phys_point,a.trian,PhysicalDomain())

src/Fields/AffineMaps.jl

@@ -92,4 +92,3 @@ function lazy_map(::typeof(∇),a::LazyArray{<:Fill{typeof(affine_map)}})
   gradients = a.args[1]
   lazy_map(constant_field,gradients)
 end
-

src/Geometry/AppendedTriangulations.jl

@@ -120,7 +120,7 @@ function get_grid(t::AppendedTriangulation)
   lazy_append(a,b)
 end
 
-function get_glue(t::AppendedTriangulation,::Val{D}) where D 
+function get_glue(t::AppendedTriangulation,::Val{D}) where D
   a = get_glue(t.a,Val(D))
   b = get_glue(t.b,Val(D))
   if a==nothing || b==nothing

src/Polynomials/MonomialBases.jl

@@ -116,15 +116,17 @@ end
 return_type(::MonomialBasis{D,T}) where {D,T} = T
 
 # Field implementation
-
 function return_cache(f::MonomialBasis{D,T},x::AbstractVector{<:Point}) where {D,T}
   @assert D == length(eltype(x)) "Incorrect number of point components"
+  zT = zero(T)
+  zxi = zero(eltype(eltype(x)))
+  Tp = typeof( zT*zxi*zxi + zT*zxi*zxi  )
   np = length(x)
   ndof = length(f.terms)*num_components(T)
   n = 1 + _maximum(f.orders)
-  r = CachedArray(zeros(T,(np,ndof)))
-  v = CachedArray(zeros(T,(ndof,)))
-  c = CachedArray(zeros(eltype(T),(D,n)))
+  r = CachedArray(zeros(Tp,(np,ndof)))
+  v = CachedArray(zeros(Tp,(ndof,)))
+  c = CachedArray(zeros(eltype(Tp),(D,n)))
   (r, v, c)
 end
 
@@ -146,31 +148,54 @@ function evaluate!(cache,f::MonomialBasis{D,T},x::AbstractVector{<:Point}) where
   r.array
 end
 
-function return_cache(
+function _return_cache(
   fg::FieldGradientArray{1,MonomialBasis{D,V}},
-  x::AbstractVector{<:Point}) where {D,V}
+  x::AbstractVector{<:Point},
+  ::Type{T},
+  TisbitsType::Val{true}) where {D,V,T}
 
   f = fg.fa
   @assert D == length(eltype(x)) "Incorrect number of point components"
   np = length(x)
   ndof = length(f.terms)*num_components(V)
-  xi = testitem(x)
-  T = gradient_type(V,xi)
   n = 1 + _maximum(f.orders)
   r = CachedArray(zeros(T,(np,ndof)))
   v = CachedArray(zeros(T,(ndof,)))
   c = CachedArray(zeros(eltype(T),(D,n)))
   g = CachedArray(zeros(eltype(T),(D,n)))
-  (r, v, c, g)
+  (r,v,c,g)
 end
 
-function evaluate!(
+function _return_cache(
+  fg::FieldGradientArray{1,MonomialBasis{D,V}},
+  x::AbstractVector{<:Point},
+  ::Type{T},
+  TisbitsType::Val{false}) where {D,V,T}
+
+  cache = _return_cache(fg,x,T,Val{true}())
+  z = CachedArray(zeros(eltype(T),D)) 
+  (cache...,z)
+end
+
+function return_cache(
+  fg::FieldGradientArray{1,MonomialBasis{D,V}},
+  x::AbstractVector{<:Point}) where {D,V}
+
+  xi = testitem(x)
+  T = gradient_type(V,xi)
+  TisbitsType = Val(isbits(T))
+  _return_cache(fg,x,T,TisbitsType)
+end
+
+function _evaluate!(
   cache,
   fg::FieldGradientArray{1,MonomialBasis{D,T}},
-  x::AbstractVector{<:Point}) where {D,T}
+  x::AbstractVector{<:Point},
+  TisbitsType::Val{true}) where {D,T}
 
   f = fg.fa
   r, v, c, g = cache
+  z = zero(Mutable(VectorValue{D,eltype(T)}))
   np = length(x)
   ndof = length(f.terms) * num_components(T)
   n = 1 + _maximum(f.orders)
@@ -180,14 +205,49 @@ function evaluate!(
   setsize!(g,(D,n))
   for i in 1:np
     @inbounds xi = x[i]
-    _gradient_nd!(v,xi,f.orders,f.terms,c,g,T)
+    _gradient_nd!(v,xi,f.orders,f.terms,c,g,z,T)
     for j in 1:ndof
       @inbounds r[i,j] = v[j]
     end
   end
   r.array
 end
 
+function _evaluate!(
+  cache,
+  fg::FieldGradientArray{1,MonomialBasis{D,T}},
+  x::AbstractVector{<:Point},
+  TisbitsType::Val{false}) where {D,T}
+
+  f = fg.fa
+  r, v, c, g, z = cache
+  np = length(x)
+  ndof = length(f.terms) * num_components(T)
+  n = 1 + _maximum(f.orders)
+  setsize!(r,(np,ndof))
+  setsize!(v,(ndof,))
+  setsize!(c,(D,n))
+  setsize!(g,(D,n))
+  for i in 1:np
+    @inbounds xi = x[i]
+    _gradient_nd!(v,xi,f.orders,f.terms,c,g,z,T)
+    for j in 1:ndof
+      @inbounds r[i,j] = v[j]
+    end
+  end
+  r.array
+end
+
+function evaluate!(
+  cache,
+  fg::FieldGradientArray{1,MonomialBasis{D,T}},
+  x::AbstractVector{<:Point}) where {D,T}
+
+  r, v, c, g = cache
+  TisbitsType = Val(isbitstype(eltype(c)))
+  _evaluate!(cache,fg,x,TisbitsType)
+end
+
 function return_cache(
   fg::FieldGradientArray{2,MonomialBasis{D,V}},
   x::AbstractVector{<:Point}) where {D,V}
@@ -372,15 +432,15 @@ function _gradient_nd!(
   terms::AbstractVector{CartesianIndex{D}},
   c::AbstractMatrix{T},
   g::AbstractMatrix{T},
+  z::AbstractVector{T},
   ::Type{V}) where {G,T,D,V}
 
   dim = D
   for d in 1:dim
     _evaluate_1d!(c,x,orders[d],d)
     _gradient_1d!(g,x,orders[d],d)
   end
-
-  z = zero(Mutable(VectorValue{D,T}))
+
   o = one(T)
   k = 1
 

src/TensorValues/VectorValueTypes.jl

@@ -107,4 +107,3 @@ length(::VectorValue{D}) where {D} = length(VectorValue{D})
 
 num_components(::Type{<:VectorValue{D}}) where {D} = length(VectorValue{D})
 num_components(::VectorValue{D}) where {D} = num_components(VectorValue{D})
-