Added more documentation and did some minor changes

doc/ford-front-matter.md

@@ -15,15 +15,15 @@ display: public
 source: false
 proc_internals: true
 sort: permission-alpha
-docmark_alt: -|
-docmark: |
+docmark_alt: !>
+docmark: !
 predocmark_alt: *
 print_creation_date: true
 creation_date: %Y-%m-%d %H:%M %z
 md_extensions: markdown.extensions.toc
                markdown.extensions.smarty
 graph: true
-license: MIT
+license: MPL
 page_dir:pages
 
 {!../README.md!}

src/adiff/autodiff.f90

@@ -1,5 +1,5 @@
 module yaeos_autodiff
-    !-| This module holds the diferent ways of automatic differentiation
-    use hyperdual_mod
-    implicit none
-end module
+   !! This module holds the diferent ways of automatic differentiation
+   use hyperdual_mod
+   implicit none
+end module

src/adiff/autodiff_api/armodel_adiff_api.f90

@@ -1,5 +1,48 @@
 module yaeos_ar_models_hyperdual
-    !-| Module that contains the automatic differentiation logic for an Ar model
+    !! Module that contains the automatic differentiation logic for an Ar model.
+    !! 
+    !! All that is needed to define an Ar model that uses automatic
+    !! differentiation with hyperdual numbers is to define a new derived type
+    !! that overloads the method to the Ar function that you want to use.
+    !! A minimal example follows:
+    !!
+    !! ```fortran
+    !! module newmodel
+    !! use yaeos_ar_models_hyperdual, only: ArModelAdiff
+    !!
+    !! type, extends(ArModelAdiff) :: YourNewModel
+    !!       type(Substances) :: composition
+    !!       real(8) :: parameters(:)
+    !!     contains
+    !!       procedure :: Ar => arfun
+    !!       procedure :: get_v0 => v0
+    !! end type
+    !! contains
+    !! subroutine arfun(self, n, v, t, Ar)
+    !!    class(YourNewModel), intent(in) :: self
+    !!    type(hyperdual), intent(in) :: n(:) ! Number of moles
+    !!    type(hyperdual), intent(in) :: v ! Volume [L]
+    !!    type(hyperdual), intent(in) :: t ! Temperature [K]
+    !!    type(hyperdual), intent(out) :: ar_value ! Residual Helmholtz Energy
+    !! 
+    !!    ! A very complicated residual helmholtz function of a mixture
+    !!    Ar = sum(n) * v * t
+    !! end subroutine
+    !! 
+    !! function v0(self, n, p, t)
+    !!    class(YourNewModel), intent(in) :: self
+    !!    real(pr), intent(in) :: n(:) ! Number of moles
+    !!    real(pr), intent(in) :: p ! Pressure [bar]
+    !!    real(pr), intent(in) :: t ! Temperature [K]
+    !!    real(pr) :: v0
+    !! 
+    !!    v0 = self%parameters(3)
+    !! end function
+    !! ```
+    !! 
+    !! A complete implementation of the PR76 Equation of State can me found in
+    !! `example/adiff/adiff_pr76.f90`
+    !!
     use yaeos_constants, only: pr
     use yaeos_models_ar, only: ArModel
     use yaeos_autodiff
@@ -58,6 +101,8 @@ subroutine residual_helmholtz(&
             end if
         end if
 
+        Ar = d_Ar%f0
+
     contains
 
         subroutine get_dardn()
@@ -163,7 +208,6 @@ subroutine reset_vars()
             d_v = v
             d_t = t
         end subroutine
-
     end subroutine
 
 end module