remove shape_symmetric_gradient from CV and FV in favour of default

Author: henrij22

src/FEValues/CellValues.jl

@@ -100,7 +100,6 @@ shape_hessian_type(cv::CellValues) = shape_hessian_type(cv.fun_values)
 @propagate_inbounds shape_value(cv::CellValues, q_point::Int, i::Int) = shape_value(cv.fun_values, q_point, i)
 @propagate_inbounds shape_gradient(cv::CellValues, q_point::Int, i::Int) = shape_gradient(cv.fun_values, q_point, i)
 @propagate_inbounds shape_hessian(cv::CellValues, q_point::Int, i::Int) = shape_hessian(cv.fun_values, q_point, i)
-@propagate_inbounds shape_symmetric_gradient(cv::CellValues, q_point::Int, i::Int) = shape_symmetric_gradient(cv.fun_values, q_point, i)
 
 # Access quadrature rule values
 get_quadrature_rule(cv::CellValues) = cv.qr

src/FEValues/FacetValues.jl

@@ -93,7 +93,6 @@ get_fun_values(fv::FacetValues) = @inbounds fv.fun_values[getcurrentfacet(fv)]
 @propagate_inbounds shape_value(fv::FacetValues, q_point::Int, i::Int) = shape_value(get_fun_values(fv), q_point, i)
 @propagate_inbounds shape_gradient(fv::FacetValues, q_point::Int, i::Int) = shape_gradient(get_fun_values(fv), q_point, i)
 @propagate_inbounds shape_hessian(fv::FacetValues, q_point::Int, i::Int) = shape_hessian(get_fun_values(fv), q_point, i)
-@propagate_inbounds shape_symmetric_gradient(fv::FacetValues, q_point::Int, i::Int) = shape_symmetric_gradient(get_fun_values(fv), q_point, i)
 
 """
     getcurrentfacet(fv::FacetValues)

src/FEValues/common_values.jl

@@ -135,7 +135,7 @@ shape_gradient(fe_v::AbstractValues, q_point::Int, base_function::Int)
 Return the symmetric gradient of shape function `base_function` evaluated in
 quadrature point `q_point`.
 """
-function shape_symmetric_gradient end
+@propagate_inbounds shape_symmetric_gradient(cv::AbstractValues, q_point::Int, base_func::Int) = symmetric(shape_gradient(cv, q_point, base_func))
 
 """
     shape_divergence(fe_v::AbstractValues, q_point::Int, base_function::Int)
@@ -161,8 +161,6 @@ end
 curl_from_gradient(∇v::SecondOrderTensor{3}) = Vec{3}((∇v[3, 2] - ∇v[2, 3], ∇v[1, 3] - ∇v[3, 1], ∇v[2, 1] - ∇v[1, 2]))
 curl_from_gradient(∇v::SecondOrderTensor{2}) = Vec{1}((∇v[2, 1] - ∇v[1, 2],)) # Alternatively define as Vec{3}((0, 0, v))
 
-@propagate_inbounds shape_symmetric_gradient(cv::AbstractValues, q_point::Int, base_func::Int) = symmetric(shape_gradient(cv, q_point, base_func))
-
 """
     function_value(fe_v::AbstractValues, q_point::Int, u::AbstractVector, [dof_range])