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update documentation
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@KristofferC
KristofferC committed Mar 6, 2016
1 parent 324e32a commit cf1d95c
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25 changes: 9 additions & 16 deletions doc/api/fe_values.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -45,7 +45,7 @@ An example of creating a ``FEValues`` object is shown below.
Upon creation, ``FEValues`` caches the values of the shape functions and derivatives in the quadrature points.

The points of FEValues is that for each element you call ``reinit!(fev, x)`` where ``x`` is the coordinate matrix for an element. This will update the global shape function derivatives, jacobians, weights etc.
The points of FEValues is that for each element you call ``reinit!(fev, x)`` where ``x`` is a `Vector` of `Tensor{1}`s. This will update the global shape function derivatives, jacobians, weights etc.

Different queries can now be performed.

Expand All @@ -64,25 +64,18 @@ Shape function queries
Gets the value of the shape function at a given quadrature point and given base function

.. function:: shape_gradient(fe_v, q_point::Int) -> gradient::Matrix
.. function:: shape_gradient(fe_v, q_point::Int) -> gradients::Vector{Tensor{2}}

.. Docstring generated from Julia source
Get the gradients of the shape functions for a given quadrature point

.. function:: shape_gradient(fe_v, q_point::Int, base_func::Int) -> gradient::Vector
.. function:: shape_gradient(fe_v, q_point::Int, base_func::Int) -> gradient::Tensor{2}

.. Docstring generated from Julia source
Get the gradient of the shape functions for a given quadrature point and base function

.. function:: shape_gradient(fe_v, q_point::Int, base_func::Int, component::Int) -> gradient_component

.. Docstring generated from Julia source
Get the gradient of the shape functions for a given quadrature point, base function and component


Discretized function queries
^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Expand All @@ -94,25 +87,25 @@ We can also compute different operatiors on a finite element discretized functio
Computes the value in a quadrature point for a scalar valued function

.. function:: function_scalar_gradient!(grad::Vector, fe_v, q_point::Int, u::Vector) -> gradient
.. function:: function_vector_value(fe_v, q_point::Int, u::Vector{Tensor{1}}) -> value::Tensor{1}

.. Docstring generated from Julia source
Computes the gradient in a quadrature point for a scalar valued function. Result is stored in ``grad``\ .
Computes the value in a quadrature point for a vector valued function.

.. function:: function_vector_gradient!(grad::Matrix, fe_v, q_point::Int, u::Vector) -> gradient
.. function:: function_scalar_gradient(fe_v, q_point::Int, u::Vector) -> grad::Tensor{1}

.. Docstring generated from Julia source
Computes the gradient (jacobian) in a quadrature point for a vector valued function. Result is stored in ``grad``\ .
Computes the gradient in a quadrature point for a scalar valued function.

.. function:: function_vector_symmetric_gradient!(grad::Matrix, fe_v, q_point::Int, u::Vector) -> sym_gradient
.. function:: function_vector_symmetric_gradient(fe_v, q_point::Int, u::Vector{Tensor{1}}) -> sym_grad::SymmetricTensor{2}

.. Docstring generated from Julia source
Computes the symmetric gradient (jacobian) in a quadrature point for a vector valued function. Result is stored in ``grad``\ .

.. function:: function_vector_divergence(fe_v, q_point::Int, u::Vector) -> divergence
.. function:: function_vector_divergence(fe_v, q_point::Int, u::Vector{Tensor{1}}) -> divergence

.. Docstring generated from Julia source
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35 changes: 11 additions & 24 deletions src/utilities/fe_values.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -81,25 +81,19 @@ Gets the value of the shape function at a given quadrature point and given base
@inline shape_value(fe_v::FEValues, q_point::Int, base_func::Int) = fe_v.N[q_point][base_func]

"""
shape_gradient(fe_v, q_point::Int) -> gradient::Matrix
shape_gradient(fe_v, q_point::Int) -> gradients::Vector{Tensor{2}}
Get the gradients of the shape functions for a given quadrature point
"""
@inline shape_gradient(fe_v::FEValues, q_point::Int) = fe_v.dNdx[q_point]

"""
shape_gradient(fe_v, q_point::Int, base_func::Int) -> gradient::Vector
shape_gradient(fe_v, q_point::Int, base_func::Int) -> gradient::Tensor{2}
Get the gradient of the shape functions for a given quadrature point and base function
"""
@inline shape_gradient(fe_v::FEValues, q_point::Int, base_func::Int) = fe_v.dNdx[q_point][base_func]

"""
shape_gradient(fe_v, q_point::Int, base_func::Int, component::Int) -> gradient_component
Get the gradient of the shape functions for a given quadrature point, base function and component
"""
@inline shape_gradient(fe_v::FEValues, q_point::Int, base_func::Int, component::Int) = fe_v.dNdx[q_point][base_func][component]

const shape_derivative = shape_gradient

Expand All @@ -116,15 +110,13 @@ Computes the value in a quadrature point for a scalar valued function
@inbounds for i in 1:n_base_funcs
s += N[i] * u[i]
end
return dot(u, N)
return s
end

# u should be given as [x, y, z, x, y, z, ...]
"""
function_vector_value!(vec::Vector, fe_v, q_point::Int, u::Vector) -> value
function_vector_value(fe_v, q_point::Int, u::Vector{Tensor{1}}) -> value::Tensor{1}
Computes the value in a quadrature point for a vector valued function. Result is stored
in `vec`
Computes the value in a quadrature point for a vector valued function.
"""
@inline function function_vector_value{dim, T}(fe_v::FEValues{dim}, q_point::Int, u::Vector{Vec{dim, T}})
n_base_funcs = n_basefunctions(get_functionspace(fe_v))
Expand All @@ -138,10 +130,9 @@ in `vec`
end

"""
function_scalar_gradient!(grad::Vector, fe_v, q_point::Int, u::Vector) -> gradient
function_scalar_gradient(fe_v, q_point::Int, u::Vector) -> grad::Tensor{1}
Computes the gradient in a quadrature point for a scalar valued function. Result
is stored in `grad`.
Computes the gradient in a quadrature point for a scalar valued function.
"""
@inline function function_scalar_gradient{dim, T}(fe_v::FEValues{dim}, q_point::Int, u::Vector{T})
n_base_funcs = n_basefunctions(get_functionspace(fe_v))
Expand All @@ -154,12 +145,10 @@ is stored in `grad`.
return grad
end

# u should be given as [x, y, z, x, y, z, ...]
"""
function_vector_gradient!(grad::Matrix, fe_v, q_point::Int, u::Vector) -> gradient
function_vector_gradient(fe_v, q_point::Int, u::Vector{Tensor{1}}) -> grad::Tensor{2}
Computes the gradient (jacobian) in a quadrature point for a vector valued function. Result
is stored in `grad`.
Computes the gradient (jacobian) in a quadrature point for a vector valued function.
"""
@inline function function_vector_gradient{dim, T}(fe_v::FEValues{dim}, q_point::Int, u::Vector{Vec{dim, T}})
n_base_funcs = n_basefunctions(get_functionspace(fe_v))
Expand All @@ -172,9 +161,8 @@ is stored in `grad`.
return grad
end

# u should be given as [x, y, z, x, y, z, ...]
"""
function_vector_symmetric_gradient!(grad::Matrix, fe_v, q_point::Int, u::Vector) -> sym_gradient
function_vector_symmetric_gradient(fe_v, q_point::Int, u::Vector{Tensor{1}}) -> sym_grad::SymmetricTensor{2}
Computes the symmetric gradient (jacobian) in a quadrature point for a vector valued function.
Result is stored in `grad`.
Expand All @@ -184,9 +172,8 @@ Result is stored in `grad`.
return convert(SymmetricTensor{2, dim, T}, grad)
end

# u should be given as [x, y, z, x, y, z, ...]
"""
function_vector_divergence(fe_v, q_point::Int, u::Vector) -> divergence
function_vector_divergence(fe_v, q_point::Int, u::Vector{Tensor{1}}) -> divergence
Computes the divergence in a quadrature point for a vector valued function.
"""
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