RAMP_mapping.f90

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module ramp_mapping
  use num_types, only: rp
  use mapping, only: mapping_t
  use json_module, only: json_file
  use field, only: field_t
  use coefs, only: coef_t
  use neko_config, only: neko_bcknd_device
  use device_ramp_mapping, only: device_convex_down_ramp_mapping_apply, &
       device_convex_down_ramp_mapping_apply_backward, &
       device_convex_up_ramp_mapping_apply, &
       device_convex_up_ramp_mapping_apply_backward
  use json_utils, only: json_get, json_get_or_default
  implicit none
  private
 
 
  type, public, extends(mapping_t) :: ramp_mapping_t
     real(kind=rp) :: f_min
     real(kind=rp) :: f_max
     real(kind=rp) :: q
     logical :: convex_up
 
   contains
     procedure, pass(this) :: init => ramp_mapping_init_from_json
     procedure, pass(this) :: init_from_attributes => &
          ramp_mapping_init_from_attributes
     procedure, pass(this) :: free => ramp_mapping_free
     procedure, pass(this) :: forward_mapping => ramp_forward_mapping
     procedure, pass(this) :: backward_mapping => ramp_backward_mapping
  end type ramp_mapping_t
 
contains
 
  subroutine ramp_mapping_init_from_json(this, json, coef)
    class(ramp_mapping_t), intent(inout) :: this
    type(json_file), intent(inout) :: json
    type(coef_t), intent(inout) :: coef
    real(kind=rp) :: f_min, f_max, q
    logical :: convex_up
 
    call json_get_or_default(json, 'f_min', f_min, 0.0_rp)
    call json_get(json, 'f_max', f_max)
    call json_get_or_default(json, 'q', q, 1.0_rp)
    call json_get_or_default(json, 'convex_up', convex_up, .false.)
 
    call this%init_base(json, coef)
    call this%init_from_attributes(coef, f_min, f_max, q, &
         convex_up)
 
  end subroutine ramp_mapping_init_from_json
 
  subroutine ramp_mapping_init_from_attributes(this, coef, f_min, f_max, q, &
       convex_up)
    class(ramp_mapping_t), intent(inout) :: this
    type(coef_t), intent(inout) :: coef
    real(kind=rp), intent(in) :: f_min, f_max, q
    logical, intent(in) :: convex_up
 
    this%f_min = f_min
    this%f_max = f_max
    this%q = q
    this%convex_up = convex_up
 
  end subroutine ramp_mapping_init_from_attributes
 
  subroutine ramp_mapping_free(this)
    class(ramp_mapping_t), intent(inout) :: this
 
    call this%free_base()
 
  end subroutine ramp_mapping_free
 
  subroutine ramp_forward_mapping(this, X_out, X_in)
    class(ramp_mapping_t), intent(inout) :: this
    type(field_t), intent(in) :: X_in
    type(field_t), intent(inout) :: X_out
 
    if (this%convex_up .eqv. .true.) then
       call convex_up_ramp_mapping_apply(this%f_min, this%f_max, &
            this%q, x_out, x_in)
    else
       call convex_down_ramp_mapping_apply(this%f_min, this%f_max, &
            this%q, x_out, x_in)
    end if
 
  end subroutine ramp_forward_mapping
 
 
  subroutine ramp_backward_mapping(this, sens_out, sens_in, X_in)
    class(ramp_mapping_t), intent(inout) :: this
    type(field_t), intent(in) :: X_in
    type(field_t), intent(in) :: sens_in
    type(field_t), intent(inout) :: sens_out
 
    if (this%convex_up .eqv. .true.) then
       call convex_up_ramp_mapping_apply_backward(this%f_min, this%f_max, &
            this%q, sens_out, sens_in, x_in)
    else
       call convex_down_ramp_mapping_apply_backward(this%f_min, this%f_max, &
            this%q, sens_out, sens_in, x_in)
    end if
 
  end subroutine ramp_backward_mapping
 
  subroutine convex_down_ramp_mapping_apply(f_min, f_max, q, X_out, X_in)
    real(kind=rp), intent(in) :: q, f_min, f_max
    type(field_t), intent(in) :: x_in
    type(field_t), intent(inout) :: X_out
    integer :: n, i
 
    ! x_out = f_min + (f_max - f_min) * x_in / (1 + q * (1 - x_in) )
 
    n = x_in%dof%size()
    if (neko_bcknd_device .eq. 1) then
       call device_convex_down_ramp_mapping_apply(f_min, f_max, q, &
            x_out%x_d, x_in%x_d, n)
    else
       do i = 1, n
          x_out%x(i,1,1,1) = f_min + (f_max - f_min) * &
               x_in%x(i,1,1,1) / (1.0_rp + q * (1.0_rp - x_in%x(i,1,1,1) ) )
       end do
    end if
 
  end subroutine convex_down_ramp_mapping_apply
 
 
  subroutine convex_down_ramp_mapping_apply_backward(f_min, f_max, q, &
       sens_out, sens_in, X_in)
    real(kind=rp), intent(in) :: f_min, f_max, q
    type(field_t), intent(in) :: x_in
    type(field_t), intent(in) :: sens_in
    type(field_t), intent(inout) :: sens_out
    integer :: n, i
 
    ! df/dx_in = df/dx_out * dx_out/dx_in
 
    ! dx_out/dx_in = (f_min - f_max) * (q + 1) / (1 - q*(x - 1))**2
 
    n = x_in%dof%size()
 
    if (neko_bcknd_device .eq. 1) then
       call device_convex_down_ramp_mapping_apply_backward(f_min, f_max, q, &
            sens_out%x_d, sens_in%x_d, x_in%x_d, n)
    else
       do i = 1, n
          sens_out%x(i,1,1,1) = (f_max - f_min) * (q + 1.0_rp) / &
               ((1.0_rp - q * (x_in%x(i,1,1,1) - 1.0_rp))**2) * &
               sens_in%x(i,1,1,1)
       end do
    end if
 
  end subroutine convex_down_ramp_mapping_apply_backward
 
  subroutine convex_up_ramp_mapping_apply(f_min, f_max, q, X_out, X_in)
    real(kind=rp), intent(in) :: f_min, f_max, q
    type(field_t), intent(in) :: x_in
    type(field_t), intent(inout) :: X_out
    integer :: n, i
 
    ! x_out = f_min + (f_max - f_min) * x_in * (q + 1) / (x_in + q)
 
    n = x_in%dof%size()
 
    if (neko_bcknd_device .eq. 1) then
       call device_convex_up_ramp_mapping_apply(f_min, f_max, q, &
            x_out%x_d, x_in%x_d, n)
    else
       do i = 1, n
          x_out%x(i,1,1,1) = f_min + (f_max - f_min) * &
               x_in%x(i,1,1,1) * (1.0_rp + q ) / (x_in%x(i,1,1,1) + q)
       end do
    end if
 
 
  end subroutine convex_up_ramp_mapping_apply
 
 
  subroutine convex_up_ramp_mapping_apply_backward(f_min, f_max, q, &
       sens_out, sens_in, X_in)
    real(kind=rp), intent(in) :: f_min, f_max, q
    type(field_t), intent(in) :: x_in
    type(field_t), intent(in) :: sens_in
    type(field_t), intent(inout) :: sens_out
    integer :: n, i
 
    ! df/dx_in = df/dx_out * dx_out/dx_in
 
    ! dx_out/dx_in = (f_min - f_max) * (q + 1) / (q + x)**2
 
    n = x_in%dof%size()
 
    if (neko_bcknd_device .eq. 1) then
       call device_convex_up_ramp_mapping_apply_backward(f_min, f_max, q, &
            sens_out%x_d, sens_in%x_d, x_in%x_d, n)
    else
       do i = 1, n
          sens_out%x(i,1,1,1) = (f_max - f_min) * (q + 1.0_rp) / &
               ( (x_in%x(i,1,1,1) + q)**2) * &
               sens_in%x(i,1,1,1)
       end do
    end if
 
  end subroutine convex_up_ramp_mapping_apply_backward
end module ramp_mapping