Refactor/tensor values

NEWS.md

@@ -4,6 +4,25 @@ 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
+
+  - Added `⊙` (\odot) as an alias of `inner`. Since PR [#239](https://github.com/gridap/Gridap.jl/pull/239).
+  - Added `⊗` (\otimes) as an alias of `outer`. Since PR [#239](https://github.com/gridap/Gridap.jl/pull/239).
+
+### Changed
+
+  - Major refactoring in the module `Gridap.TensorValues`.
+  Since PR [#239](https://github.com/gridap/Gridap.jl/pull/239).
+   **The following changes are likely to affect all users:**
+    - The operator `*` is not allowed for expressing the dot product anymore. Use `LinearAlgebra.dot`
+  function aka `⋅` (\cdot).
+    - The syntax `∇*u` is not allowed anymore.  Use `∇⋅u` instead.
+    - Gridap re-exports `dot`, `⋅`, and other names from LinearAlbegra that are used 
+  often in Gridap code. 
+    - Function `n_components` is renamed to `num_components`.
+
 ## [0.10.4] - 2020-6-8
 
 ### Added

Project.toml

@@ -1,7 +1,7 @@
 name = "Gridap"
 uuid = "56d4f2e9-7ea1-5844-9cf6-b9c51ca7ce8e"
 authors = ["Santiago Badia <santiago.badia@monash.edu>", "Francesc Verdugo <fverdugo@cimne.upc.edu>"]
-version = "0.10.4"
+version = "0.11.0"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"

src/Exports.jl

@@ -5,6 +5,10 @@ macro publish(mod,name)
   end
 end
 
+# Reexport from LinearAlgebra (just for convenience)
+using LinearAlgebra:  det, inv, tr, cross, dot, norm, ×, ⋅
+export det, inv, tr, cross, dot, norm, ×, ⋅
+
 @publish Helpers operate
 @publish Helpers GridapType
 
@@ -33,6 +37,9 @@ end
 @publish TensorValues inner
 @publish TensorValues outer
 @publish TensorValues diagonal_tensor
+@publish TensorValues num_components
+using Gridap.TensorValues: ⊙; export ⊙
+using Gridap.TensorValues: ⊗; export ⊗
 
 @publish Fields gradient
 @publish Fields ∇

src/FESpaces/CLagrangianFESpaces.jl

@@ -138,7 +138,7 @@ function _generate_dof_layout_component_major(::Type{<:Real},nnodes::Integer)
 end
 
 function _generate_dof_layout_component_major(::Type{T},nnodes::Integer) where T
-  ncomps = n_components(T)
+  ncomps = num_components(T)
   V = change_eltype(T,Int)
   ndofs = ncomps*nnodes
   dof_to_comp = zeros(Int8,ndofs)
@@ -175,7 +175,7 @@ function _generate_cell_dofs_clagrangian_fespace(
   cell_to_ctype,
   node_and_comp_to_dof) where T
 
-  ncomps = n_components(T)
+  ncomps = num_components(T)
 
   ctype_to_lnode_to_comp_to_ldof = map(get_node_and_comp_to_dof,reffes)
   ctype_to_num_ldofs = map(num_dofs,reffes)

src/FESpaces/ExtendedFESpaces.jl

@@ -175,7 +175,7 @@ function get_cell_basis(f::ExtendedFESpace)
   vi = testitem(cell_to_val)
   Tv = field_return_type(vi,xi)
   T = eltype(Tv)
-  D = n_components(eltype(xi))
+  D = num_components(eltype(xi))
   void_to_val = Fill(VoidBasis{T,D}(),length(f.trian.void_to_oldcell))
 
   array = ExtendedVector(

src/Fields/AffineMaps.jl

@@ -2,9 +2,9 @@
 """
 """
 struct AffineMap{D,T,L} <:Field
-  jacobian::TensorValue{D,T,L}
+  jacobian::TensorValue{D,D,T,L}
   origin::Point{D,T}
-  function AffineMap(jacobian::TensorValue{D,T,L}, origin::Point{D,T}) where {D,T,L}
+  function AffineMap(jacobian::TensorValue{D,D,T,L}, origin::Point{D,T}) where {D,T,L}
     new{D,T,L}(jacobian,origin)
   end
 end
@@ -28,11 +28,11 @@ end
 function _apply_affine_map(h,x)
   t = h.origin
   s = h.jacobian
-  (s*x)+t
+  (s⋅x)+t
 end
 
 struct AffineMapGrad{D,T,L} <: Field
-  jacobian::TensorValue{D,T,L}
+  jacobian::TensorValue{D,D,T,L}
 end
 
 function field_gradient(h::AffineMap)

src/Fields/Attachmap.jl

@@ -32,7 +32,7 @@ function kernel_cache(k::PhysGrad,a,b)
   _attachmap_checks(a,b)
   Ta = eltype(a)
   Tb = eltype(b)
-  T = return_type(*,return_type(inv,Tb),Ta)
+  T = return_type(⋅,return_type(inv,Tb),Ta)
   r = zeros(T,size(a))
   CachedArray(r)
 end
@@ -53,7 +53,7 @@ end
   for p in 1:np
     @inbounds jacinv = inv(b[p])
     for i in 1:ni
-      @inbounds c[p,i] = jacinv * a[p,i]
+      @inbounds c[p,i] = jacinv ⋅ a[p,i]
     end
   end
   c

src/Fields/DiffOperators.jl

@@ -49,14 +49,24 @@ function laplacian(f)
 end
 
 """
-    ∇*f
+    ∇⋅f
 
 Equivalent to
 
     divergence(f)
 """
-(*)(::typeof(∇),f) = divergence(f)
-(*)(::typeof(∇),f::GridapType) = divergence(f)
+dot(::typeof(∇),f) = divergence(f)
+dot(::typeof(∇),f::GridapType) = divergence(f)
+
+function (*)(::typeof(∇),f)
+  msg = "Syntax ∇*f has been removed, use ∇⋅f (\\nabla \\cdot f) instead"
+  error(msg)
+end
+
+function (*)(::typeof(∇),f::GridapType)
+  msg = "Syntax ∇*f has been removed, use ∇⋅f (\\nabla \\cdot f) instead"
+  error(msg)
+end
 
 """
     outer(∇,f)
@@ -118,23 +128,23 @@ function gradient(f::Function)
 end
 
 function _grad_f(f,x,fx)
-  VectorValue(ForwardDiff.gradient(f,x.array))
+  VectorValue(ForwardDiff.gradient(f,get_array(x)))
 end
 
 function _grad_f(f,x,fx::VectorValue)
-  TensorValue(transpose(ForwardDiff.jacobian(y->f(y).array,x.array)))
+  TensorValue(transpose(ForwardDiff.jacobian(y->get_array(f(y)),get_array(x))))
 end
 
 function _grad_f(f,x,fx::MultiValue)
   @notimplemented
 end
 
 function divergence(f::Function)
-  x -> tr(ForwardDiff.jacobian(y->f(y).array,x.array))
+  x -> tr(ForwardDiff.jacobian(y->get_array(f(y)),get_array(x)))
 end
 
 function curl(f::Function)
-  x -> grad2curl(TensorValue(transpose(ForwardDiff.jacobian(y->f(y).array,x.array))))
+  x -> grad2curl(TensorValue(transpose(ForwardDiff.jacobian(y->get_array(f(y)),get_array(x)))))
 end
 
 function laplacian(f::Function)
@@ -144,14 +154,14 @@ function laplacian(f::Function)
 end
 
 function _lapl_f(f,x,fx)
-  tr(ForwardDiff.jacobian(y->ForwardDiff.gradient(f,y), x.array))
+  tr(ForwardDiff.jacobian(y->ForwardDiff.gradient(f,y), get_array(x)))
 end
 
 function _lapl_f(f,x,fx::VectorValue)
   A = length(x)
   B = length(fx)
-  a = ForwardDiff.jacobian(y->transpose(ForwardDiff.jacobian(z->f(z).array,y)), x.array)
-  tr(MultiValue{Tuple{A,A,B}}(Tuple(transpose(a))))
+  a = ForwardDiff.jacobian(y->transpose(ForwardDiff.jacobian(z->get_array(f(z)),y)), get_array(x))
+  tr(ThirdOrderTensorValue{A,A,B}(Tuple(transpose(a))))
 end
 
 function _lapl_f(f,x,fx::MultiValue)

src/Fields/Fields.jl

@@ -19,6 +19,7 @@ using Gridap.Arrays: BCasted
 using Gridap.Arrays: NumberOrArray
 using Gridap.Arrays: AppliedArray
 using Gridap.Arrays: Contracted
+using LinearAlgebra: ⋅
 
 using Test
 using DocStringExtensions
@@ -81,6 +82,7 @@ import Gridap.TensorValues: symmetric_part
 import Base: +, - , *
 import LinearAlgebra: cross
 import LinearAlgebra: tr
+import LinearAlgebra: dot
 import Base: transpose
 import Base: adjoint
 

src/Geometry/GenericBoundaryTriangulations.jl

@@ -416,8 +416,8 @@ function kernel_evaluate(k::NormalVectorValued,x,J,refn)
   apply(k,Jx,refn)
 end
 
-function _map_normal(J::TensorValue{D,T},n::VectorValue{D,T}) where {D,T}
-  v = inv(J)*n
+function _map_normal(J::TensorValue{D,D,T},n::VectorValue{D,T}) where {D,T}
+  v = inv(J)⋅n
   m = sqrt(inner(v,v))
   if m < eps()
     return zero(n)

src/Geometry/Geometry.jl

@@ -8,6 +8,7 @@ module Geometry
 using Test
 using DocStringExtensions
 using FillArrays
+using LinearAlgebra: ⋅
 
 using Gridap.Helpers
 using Gridap.Arrays

src/Gridap.jl

@@ -36,10 +36,10 @@ include("Io/Io.jl")
 
 include("Algebra/Algebra.jl")
 
-include("TensorValues/TensorValues.jl")
-
 include("Arrays/Arrays.jl")
 
+include("TensorValues/TensorValues.jl")
+
 include("Fields/Fields.jl")
 
 include("Polynomials/Polynomials.jl")

src/Polynomials/MonomialBases.jl

@@ -116,7 +116,7 @@ get_value_type(::Type{MonomialBasis{D,T}}) where {D,T} = T
 function field_cache(f::MonomialBasis{D,T},x) where {D,T}
   @assert D == length(eltype(x)) "Incorrect number of point components"
   np = length(x)
-  ndof = length(f.terms)*n_components(T)
+  ndof = length(f.terms)*num_components(T)
   n = 1 + _maximum(f.orders)
   r = CachedArray(zeros(T,(np,ndof)))
   v = CachedArray(zeros(T,(ndof,)))
@@ -127,7 +127,7 @@ end
 function evaluate_field!(cache,f::MonomialBasis{D,T},x) where {D,T}
   r, v, c = cache
   np = length(x)
-  ndof = length(f.terms)*n_components(T)
+  ndof = length(f.terms)*num_components(T)
   n = 1 + _maximum(f.orders)
   setsize!(r,(np,ndof))
   setsize!(v,(ndof,))
@@ -145,7 +145,7 @@ end
 function gradient_cache(f::MonomialBasis{D,V},x) where {D,V}
   @assert D == length(eltype(x)) "Incorrect number of point components"
   np = length(x)
-  ndof = length(f.terms)*n_components(V)
+  ndof = length(f.terms)*num_components(V)
   xi = testitem(x)
   T = gradient_type(V,xi)
   n = 1 + _maximum(f.orders)
@@ -159,7 +159,7 @@ end
 function evaluate_gradient!(cache,f::MonomialBasis{D,T},x) where {D,T}
   r, v, c, g = cache
   np = length(x)
-  ndof = length(f.terms) * n_components(T)
+  ndof = length(f.terms) * num_components(T)
   n = 1 + _maximum(f.orders)
   setsize!(r,(np,ndof))
   setsize!(v,(ndof,))
@@ -178,7 +178,7 @@ end
 function hessian_cache(f::MonomialBasis{D,V},x) where {D,V}
   @assert D == length(eltype(x)) "Incorrect number of point components"
   np = length(x)
-  ndof = length(f.terms)*n_components(V)
+  ndof = length(f.terms)*num_components(V)
   xi = testitem(x)
   T = gradient_type(gradient_type(V,xi),xi)
   n = 1 + _maximum(f.orders)
@@ -193,7 +193,7 @@ end
 function evaluate_hessian!(cache,f::MonomialBasis{D,T},x) where {D,T}
   r, v, c, g, h = cache
   np = length(x)
-  ndof = length(f.terms) * n_components(T)
+  ndof = length(f.terms) * num_components(T)
   n = 1 + _maximum(f.orders)
   setsize!(r,(np,ndof))
   setsize!(v,(ndof,))
@@ -386,7 +386,7 @@ function _hessian_nd!(
     _hessian_1d!(h,x,orders[d],d)
   end
 
-  z = zero(mutable(TensorValue{D,T,D*D}))
+  z = zero(mutable(TensorValue{D,D,T}))
   o = one(T)
   k = 1