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axis_utils.F90
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!***********************************************************************
!* GNU Lesser General Public License
!*
!* This file is part of the GFDL Flexible Modeling System (FMS).
!*
!* FMS is free software: you can redistribute it and/or modify it under
!* the terms of the GNU Lesser General Public License as published by
!* the Free Software Foundation, either version 3 of the License, or (at
!* your option) any later version.
!*
!* FMS is distributed in the hope that it will be useful, but WITHOUT
!* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
!* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
!* for more details.
!*
!* You should have received a copy of the GNU Lesser General Public
!* License along with FMS. If not, see <http://www.gnu.org/licenses/>.
!***********************************************************************
module axis_utils_mod
!
!<CONTACT EMAIL="[email protected]">M.J. Harrison</CONTACT>
!
!<REVIEWER EMAIL="[email protected]">Bruce Wyman</REVIEWER>
!
!<OVERVIEW>
! A set of utilities for manipulating axes and extracting axis
! attributes
!</OVERVIEW>
!<DESCRIPTION>
!
! subroutine get_axis_cart(axis,cart) : Returns X,Y,Z or T cartesian attribute
! subroutine get_axis_bounds(axis,axis_bound,axes) : Return axis_bound either from an array of
! available axes, or defined based on axis mid-points
! function get_axis_modulo : Returns true if axis has the modulo attribute
! function get_axis_fold : Returns is axis is folded at a boundary (non-standard meta-data)
! function lon_in_range : Returns lon_strt <= longitude <= lon_strt+360
! subroutine tranlon : Returns monotonic array of longitudes s.t., lon_strt <= lon(:) <= lon_strt+360.
! subroutine nearest_index : Return index of nearest point along axis
!
!</DESCRIPTION>
!
use mpp_io_mod, only: axistype, atttype, default_axis, default_att, &
mpp_get_atts, mpp_get_axis_data, mpp_modify_meta, &
mpp_get_att_name, mpp_get_att_type, mpp_get_att_char, &
mpp_get_att_length, mpp_get_axis_bounds
use mpp_mod, only: mpp_error, FATAL, stdout
use fms_mod, only: lowercase, string_array_index, fms_error_handler
implicit none
# include <netcdf.inc>
public get_axis_cart, get_axis_bounds, get_axis_modulo, get_axis_fold, lon_in_range, &
tranlon, frac_index, nearest_index, interp_1d, get_axis_modulo_times
private
integer, parameter :: maxatts = 100
real, parameter :: epsln= 1.e-10
real, parameter :: fp5 = 0.5, f360 = 360.0
! Include variable "version" to be written to log file.
#include<file_version.h>
interface interp_1d
module procedure interp_1d_1d
module procedure interp_1d_2d
module procedure interp_1d_3d
end interface
contains
subroutine get_axis_cart(axis, cart)
type(axistype), intent(in) :: axis
character(len=1), intent(out) :: cart
character(len=1) :: axis_cart
character(len=16), dimension(2) :: lon_names, lat_names
character(len=16), dimension(3) :: z_names
character(len=16), dimension(2) :: t_names
character(len=16), dimension(3) :: lon_units, lat_units
character(len=8) , dimension(4) :: z_units
character(len=3) , dimension(6) :: t_units
character(len=32) :: name
integer :: i,j
lon_names = (/'lon','x '/)
lat_names = (/'lat','y '/)
z_names = (/'depth ','height','z '/)
t_names = (/'time','t '/)
lon_units = (/'degrees_e ', 'degrees_east', 'degreese '/)
lat_units = (/'degrees_n ', 'degrees_north', 'degreesn '/)
z_units = (/'cm ','m ','pa ','hpa'/)
t_units = (/'sec', 'min','hou','day','mon','yea'/)
call mpp_get_atts(axis,cartesian=axis_cart)
cart = 'N'
if ( lowercase(axis_cart) == 'x' ) cart = 'X'
if ( lowercase(axis_cart) == 'y' ) cart = 'Y'
if ( lowercase(axis_cart) == 'z' ) cart = 'Z'
if ( lowercase(axis_cart) == 't' ) cart = 'T'
if (cart /= 'X' .and. cart /= 'Y' .and. cart /= 'Z' .and. cart /= 'T') then
call mpp_get_atts(axis,name=name)
name = lowercase(name)
do i=1,size(lon_names(:))
if (trim(name(1:3)) == trim(lon_names(i))) cart = 'X'
enddo
do i=1,size(lat_names(:))
if (trim(name(1:3)) == trim(lat_names(i))) cart = 'Y'
enddo
do i=1,size(z_names(:))
if (trim(name) == trim(z_names(i))) cart = 'Z'
enddo
do i=1,size(t_names(:))
if (trim(name) == t_names(i)) cart = 'T'
enddo
end if
if (cart /= 'X' .and. cart /= 'Y' .and. cart /= 'Z' .and. cart /= 'T') then
call mpp_get_atts(axis,units=name)
name = lowercase(name)
do i=1,size(lon_units(:))
if (trim(name) == trim(lon_units(i))) cart = 'X'
enddo
do i=1,size(lat_units(:))
if (trim(name) == trim(lat_units(i))) cart = 'Y'
enddo
do i=1,size(z_units(:))
if (trim(name) == trim(z_units(i))) cart = 'Z'
enddo
do i=1,size(t_units(:))
if (name(1:3) == trim(t_units(i))) cart = 'T'
enddo
end if
return
end subroutine get_axis_cart
subroutine get_axis_bounds(axis,axis_bound,axes,bnd_name,err_msg)
type(axistype), intent(in) :: axis
type(axistype), intent(inout) :: axis_bound
type(axistype), intent(in), dimension(:) :: axes
character(len=*), intent(inout), optional :: bnd_name
character(len=*), intent(out), optional :: err_msg
real, dimension(:), allocatable :: data, tmp
integer :: i, len
character(len=128) :: name, units
character(len=256) :: longname
character(len=1) :: cartesian
logical :: bounds_found
if(present(err_msg)) then
err_msg = ''
endif
axis_bound = default_axis
call mpp_get_atts(axis,units=units,longname=longname,&
cartesian=cartesian, len=len)
if(len .LE. 0) return
allocate(data(len+1))
bounds_found = mpp_get_axis_bounds(axis, data, name=name)
longname = trim(longname)//' bounds'
if(.not.bounds_found .and. len>1 ) then
! The following calculation can not be done for len=1
call mpp_get_atts(axis,name=name)
name = trim(name)//'_bnds'
allocate(tmp(len))
call mpp_get_axis_data(axis,tmp)
do i=2,len
data(i)= tmp(i-1)+fp5*(tmp(i)-tmp(i-1))
enddo
data(1)= tmp(1)- fp5*(tmp(2)-tmp(1))
if (abs(data(1)) < epsln) data(1) = 0.0
data(len+1)= tmp(len)+ fp5*(tmp(len)-tmp(len-1))
if (data(1) == 0.0) then
if (abs(data(len+1)-360.) > epsln) data(len+1)=360.0
endif
endif
if(bounds_found .OR. len>1) then
call mpp_modify_meta(axis_bound,name=name,units=units,longname=&
longname,cartesian=cartesian,data=data)
endif
if(allocated(tmp)) deallocate(tmp)
deallocate(data)
return
end subroutine get_axis_bounds
function get_axis_modulo(axis)
type(axistype) :: axis
logical :: get_axis_modulo
integer :: natt, i
type(atttype), dimension(:), allocatable :: atts
call mpp_get_atts(axis,natts=natt)
allocate(atts(natt))
call mpp_get_atts(axis,atts=atts)
get_axis_modulo=.false.
do i = 1,natt
if (lowercase(trim(mpp_get_att_name(atts(i)))) == 'modulo') get_axis_modulo = .true.
enddo
deallocate(atts)
return
end function get_axis_modulo
function get_axis_modulo_times(axis, tbeg, tend)
logical :: get_axis_modulo_times
type(axistype), intent(in) :: axis
character(len=*), intent(out) :: tbeg, tend
integer :: natt, i
type(atttype), dimension(:), allocatable :: atts
logical :: found_tbeg, found_tend
call mpp_get_atts(axis,natts=natt)
allocate(atts(natt))
call mpp_get_atts(axis,atts=atts)
found_tbeg = .false.
found_tend = .false.
do i = 1,natt
if(lowercase(trim(mpp_get_att_name(atts(i)))) == 'modulo_beg') then
if(mpp_get_att_length(atts(i)) > len(tbeg)) then
call mpp_error(FATAL,'error in get: len(tbeg) too small to hold attribute')
endif
tbeg = trim(mpp_get_att_char(atts(i)))
found_tbeg = .true.
endif
if(lowercase(trim(mpp_get_att_name(atts(i)))) == 'modulo_end') then
if(mpp_get_att_length(atts(i)) > len(tend)) then
call mpp_error(FATAL,'error in get: len(tend) too small to hold attribute')
endif
tend = trim(mpp_get_att_char(atts(i)))
found_tend = .true.
endif
enddo
if(found_tbeg .and. .not.found_tend) then
call mpp_error(FATAL,'error in get: Found modulo_beg but not modulo_end')
endif
if(.not.found_tbeg .and. found_tend) then
call mpp_error(FATAL,'error in get: Found modulo_end but not modulo_beg')
endif
get_axis_modulo_times = found_tbeg
end function get_axis_modulo_times
function get_axis_fold(axis)
type(axistype) :: axis
logical :: get_axis_fold
integer :: natt, i
type(atttype), dimension(:), allocatable :: atts
call mpp_get_atts(axis,natts=natt)
allocate(atts(natt))
call mpp_get_atts(axis,atts=atts)
get_axis_fold=.false.
do i = 1,natt
if (mpp_get_att_char(atts(i)) == 'fold_top') get_axis_fold = .true.
enddo
deallocate(atts)
return
end function get_axis_fold
function lon_in_range(lon, l_strt)
real :: lon, l_strt, lon_in_range, l_end
lon_in_range = lon
l_end = l_strt+360.
if (abs(lon_in_range - l_strt) < 1.e-4) then
lon_in_range = l_strt
return
endif
if (abs(lon_in_range - l_end) < 1.e-4) then
lon_in_range = l_strt
return
endif
do
if (lon_in_range < l_strt) then
lon_in_range = lon_in_range + f360;
else if (lon_in_range > l_end) then
lon_in_range = lon_in_range - f360;
else
exit
end if
end do
end function lon_in_range
subroutine tranlon(lon, lon_start, istrt)
! returns array of longitudes s.t. lon_strt <= lon < lon_strt+360.
! also, the first istrt-1 entries are moved to the end of the array
!
! e.g.
! lon = 0 1 2 3 4 5 ... 358 359; lon_strt = 3 ==>
! tranlon = 3 4 5 6 7 8 ... 359 360 361 362; istrt = 4
real, intent(inout), dimension(:) :: lon
real, intent(in) :: lon_start
integer, intent(out) :: istrt
integer :: len, i
real :: lon_strt, tmp(size(lon(:))-1)
len = size(lon(:))
do i=1,len
lon(i) = lon_in_range(lon(i),lon_start)
enddo
istrt=0
do i=1,len-1
if (lon(i+1) < lon(i)) then
istrt=i+1
exit
endif
enddo
if (istrt>1) then ! grid is not monotonic
if (abs(lon(len)-lon(1)) < epsln) then
tmp = cshift(lon(1:len-1),istrt-1)
lon(1:len-1) = tmp
lon(len) = lon(1)
else
lon = cshift(lon,istrt-1)
endif
lon_strt = lon(1)
do i=2,len+1
lon(i) = lon_in_range(lon(i),lon_strt)
lon_strt = lon(i)
enddo
endif
return
end subroutine tranlon
function frac_index (value, array)
!=======================================================================
!
! nearest_index = index of nearest data point within "array" corresponding to
! "value".
!
! inputs:
!
! value = arbitrary data...same units as elements in "array"
! array = array of data points (must be monotonically increasing)
!
! output:
!
! nearest_index = index of nearest data point to "value"
! if "value" is outside the domain of "array" then nearest_index = 1
! or "ia" depending on whether array(1) or array(ia) is
! closest to "value"
!
! note: if "array" is dimensioned array(0:ia) in the calling
! program, then the returned index should be reduced
! by one to account for the zero base.
!
! example:
!
! let model depths be defined by the following:
! parameter (km=5)
! dimension z(km)
! data z /5.0, 10.0, 50.0, 100.0, 250.0/
!
! k1 = nearest_index (12.5, z, km)
! k2 = nearest_index (0.0, z, km)
!
! k1 would be set to 2, and k2 would be set to 1 so that
! z(k1) would be the nearest data point to 12.5 and z(k2) would
! be the nearest data point to 0.0
!
!=======================================================================
integer :: ia, i, ii, unit
real :: value, frac_index
real, dimension(:) :: array
logical keep_going
ia = size(array(:))
do i=2,ia
if (array(i) < array(i-1)) then
unit = stdout()
write (unit,*) '=> Error: "frac_index" array must be monotonically increasing when searching for nearest value to ',&
value
write (unit,*) ' array(i) < array(i-1) for i=',i
write (unit,*) ' array(i) for i=1..ia follows:'
do ii=1,ia
write (unit,*) 'i=',ii, ' array(i)=',array(ii)
enddo
call mpp_error(FATAL,' "frac_index" array must be monotonically increasing.')
endif
enddo
if (value < array(1) .or. value > array(ia)) then
! if (value < array(1)) frac_index = 1.
! if (value > array(ia)) frac_index = float(ia)
frac_index = -1.0
else
i=1
keep_going = .true.
do while (i <= ia .and. keep_going)
i = i+1
if (value <= array(i)) then
frac_index = float(i-1) + (value-array(i-1))/(array(i)-array(i-1))
keep_going = .false.
endif
enddo
endif
end function frac_index
function nearest_index (value, array)
!=======================================================================
!
! nearest_index = index of nearest data point within "array" corresponding to
! "value".
!
! inputs:
!
! value = arbitrary data...same units as elements in "array"
! array = array of data points (must be monotonically increasing)
! ia = dimension of "array"
!
! output:
!
! nearest_index = index of nearest data point to "value"
! if "value" is outside the domain of "array" then nearest_index = 1
! or "ia" depending on whether array(1) or array(ia) is
! closest to "value"
!
! note: if "array" is dimensioned array(0:ia) in the calling
! program, then the returned index should be reduced
! by one to account for the zero base.
!
! example:
!
! let model depths be defined by the following:
! parameter (km=5)
! dimension z(km)
! data z /5.0, 10.0, 50.0, 100.0, 250.0/
!
! k1 = nearest_index (12.5, z, km)
! k2 = nearest_index (0.0, z, km)
!
! k1 would be set to 2, and k2 would be set to 1 so that
! z(k1) would be the nearest data point to 12.5 and z(k2) would
! be the nearest data point to 0.0
!
!=======================================================================
integer :: nearest_index, ia, i, ii, unit
real :: value
real, dimension(:) :: array
logical keep_going
ia = size(array(:))
do i=2,ia
if (array(i) < array(i-1)) then
unit = stdout()
write (unit,*) '=> Error: "nearest_index" array must be monotonically increasing &
&when searching for nearest value to ',value
write (unit,*) ' array(i) < array(i-1) for i=',i
write (unit,*) ' array(i) for i=1..ia follows:'
do ii=1,ia
write (unit,*) 'i=',ii, ' array(i)=',array(ii)
enddo
call mpp_error(FATAL,' "nearest_index" array must be monotonically increasing.')
endif
enddo
if (value < array(1) .or. value > array(ia)) then
if (value < array(1)) nearest_index = 1
if (value > array(ia)) nearest_index = ia
else
i=1
keep_going = .true.
do while (i <= ia .and. keep_going)
i = i+1
if (value <= array(i)) then
nearest_index = i
if (array(i)-value > value-array(i-1)) nearest_index = i-1
keep_going = .false.
endif
enddo
endif
end function nearest_index
!#############################################################################
subroutine interp_1d_linear(grid1,grid2,data1,data2)
real, dimension(:), intent(in) :: grid1, data1, grid2
real, dimension(:), intent(inout) :: data2
integer :: n1, n2, i, n, ext
real :: w
n1 = size(grid1(:))
n2 = size(grid2(:))
do i=2,n1
if (grid1(i) <= grid1(i-1)) call mpp_error(FATAL, 'grid1 not monotonic')
enddo
do i=2,n2
if (grid2(i) <= grid2(i-1)) call mpp_error(FATAL, 'grid2 not monotonic')
enddo
if (grid1(1) > grid2(1) ) call mpp_error(FATAL, 'grid2 lies outside grid1')
if (grid1(n1) < grid2(n2) ) call mpp_error(FATAL, 'grid2 lies outside grid1')
do i=1,n2
n = nearest_index(grid2(i),grid1)
if (grid1(n) < grid2(i)) then
w = (grid2(i)-grid1(n))/(grid1(n+1)-grid1(n))
data2(i) = (1.-w)*data1(n) + w*data1(n+1)
else
if(n==1) then
data2(i) = data1(n)
else
w = (grid2(i)-grid1(n-1))/(grid1(n)-grid1(n-1))
data2(i) = (1.-w)*data1(n-1) + w*data1(n)
endif
endif
enddo
return
end subroutine interp_1d_linear
!###################################################################
subroutine interp_1d_cubic_spline(grid1, grid2, data1, data2, yp1, ypn)
real, dimension(:), intent(in) :: grid1, grid2, data1
real, dimension(:), intent(inout) :: data2
real, intent(in) :: yp1, ypn
real, dimension(size(grid1)) :: y2, u
real :: sig, p, qn, un, h, a ,b
integer :: n, m, i, k, klo, khi
n = size(grid1(:))
m = size(grid2(:))
do i=2,n
if (grid1(i) <= grid1(i-1)) call mpp_error(FATAL, 'grid1 not monotonic')
enddo
do i=2,m
if (grid2(i) <= grid2(i-1)) call mpp_error(FATAL, 'grid2 not monotonic')
enddo
if (grid1(1) > grid2(1) ) call mpp_error(FATAL, 'grid2 lies outside grid1')
if (grid1(n) < grid2(m) ) call mpp_error(FATAL, 'grid2 lies outside grid1')
if (yp1 >.99e30) then
y2(1)=0.
u(1)=0.
else
y2(1)=-0.5
u(1)=(3./(grid1(2)-grid1(1)))*((data1(2)-data1(1))/(grid1(2)-grid1(1))-yp1)
endif
do i=2,n-1
sig=(grid1(i)-grid1(i-1))/(grid1(i+1)-grid1(i-1))
p=sig*y2(i-1)+2.
y2(i)=(sig-1.)/p
u(i)=(6.*((data1(i+1)-data1(i))/(grid1(i+1)-grid1(i))-(data1(i)-data1(i-1)) &
/(grid1(i)-grid1(i-1)))/(grid1(i+1)-grid1(i-1))-sig*u(i-1))/p
enddo
if (ypn > .99e30) then
qn=0.
un=0.
else
qn=0.5
un=(3./(grid1(n)-grid1(n-1)))*(ypn-(data1(n)-data1(n-1))/(grid1(n)-grid1(n-1)))
endif
y2(n)=(un-qn*u(n-1))/(qn*y2(n-1)+1.)
do k=n-1,1,-1
y2(k)=y2(k)*y2(k+1)+u(k)
enddo
do k = 1, m
n = nearest_index(grid2(k),grid1)
if (grid1(n) < grid2(k)) then
klo = n
else
if(n==1) then
klo = n
else
klo = n -1
endif
endif
khi = klo+1
h = grid1(khi)-grid1(klo)
a = (grid1(khi) - grid2(k))/h
b = (grid2(k) - grid1(klo))/h
data2(k) = a*data1(klo) + b*data1(khi)+ ((a**3-a)*y2(klo) + (b**3-b)*y2(khi))*(h**2)/6.
enddo
end subroutine interp_1d_cubic_spline
!###################################################################
subroutine interp_1d_1d(grid1,grid2,data1,data2, method, yp1, yp2)
real, dimension(:), intent(in) :: grid1, data1, grid2
real, dimension(:), intent(inout) :: data2
character(len=*), optional, intent(in) :: method
real, optional, intent(in) :: yp1, yp2
real :: y1, y2
character(len=32) :: interp_method
integer :: k2, ks, ke
k2 = size(grid2(:))
interp_method = "linear"
if(present(method)) interp_method = method
y1 = 1.0e30
if(present(yp1)) y1 = yp1
y2 = 1.0e30
if(present(yp2)) y2 = yp2
call find_index(grid1, grid2(1), grid2(k2), ks, ke)
select case(trim(interp_method))
case("linear")
call interp_1d_linear(grid1(ks:ke),grid2,data1(ks:ke),data2)
case("cubic_spline")
call interp_1d_cubic_spline(grid1(ks:ke),grid2,data1(ks:ke),data2, y1, y2)
case default
call mpp_error(FATAL,"axis_utils: interp_method should be linear or cubic_spline")
end select
return
end subroutine interp_1d_1d
!###################################################################
subroutine interp_1d_2d(grid1,grid2,data1,data2)
real, dimension(:,:), intent(in) :: grid1, data1, grid2
real, dimension(:,:), intent(inout) :: data2
integer :: n1, n2, i, n, k2, ks, ke
real :: w
n1 = size(grid1,1)
n2 = size(grid2,1)
k2 = size(grid2,2)
if (n1 /= n2) call mpp_error(FATAL,'grid size mismatch')
do n=1,n1
call find_index(grid1(n,:), grid2(n,1), grid2(n,k2), ks, ke)
call interp_1d_linear(grid1(n,ks:ke),grid2(n,:),data1(n,ks:ke),data2(n,:))
enddo
return
end subroutine interp_1d_2d
!###################################################################
subroutine interp_1d_3d(grid1,grid2,data1,data2, method, yp1, yp2)
real, dimension(:,:,:), intent(in) :: grid1, data1, grid2
real, dimension(:,:,:), intent(inout) :: data2
character(len=*), optional, intent(in) :: method
real, optional, intent(in) :: yp1, yp2
integer :: n1, n2, m1, m2, k2, i, n, m
real :: w, y1, y2
character(len=32) :: interp_method
integer :: ks, ke
n1 = size(grid1,1)
n2 = size(grid2,1)
m1 = size(grid1,2)
m2 = size(grid2,2)
k2 = size(grid2,3)
interp_method = "linear"
if(present(method)) interp_method = method
y1 = 1.0e30
if(present(yp1)) y1 = yp1
y2 = 1.0e30
if(present(yp2)) y2 = yp2
if (n1 /= n2 .or. m1 /= m2) call mpp_error(FATAL,'grid size mismatch')
select case(trim(interp_method))
case("linear")
do m=1,m1
do n=1,n1
call find_index(grid1(n,m,:), grid2(n,m,1), grid2(n,m,k2), ks, ke)
call interp_1d_linear(grid1(n,m,ks:ke),grid2(n,m,:),data1(n,m,ks:ke),data2(n,m,:))
enddo
enddo
case("cubic_spline")
do m=1,m1
do n=1,n1
call find_index(grid1(n,m,:), grid2(n,m,1), grid2(n,m,k2), ks, ke)
call interp_1d_cubic_spline(grid1(n,m,ks:ke),grid2(n,m,:), data1(n,m,ks:ke),data2(n,m,:), y1, y2)
enddo
enddo
case default
call mpp_error(FATAL,"axis_utils: interp_method should be linear or cubic_spline")
end select
return
end subroutine interp_1d_3d
!#####################################################################
subroutine find_index(grid1, xs, xe, ks, ke)
real, dimension(:), intent(in) :: grid1
real, intent(in) :: xs, xe
integer, intent(out) :: ks, ke
integer :: k, nk
nk = size(grid1(:))
ks = 0; ke = 0
do k = 1, nk-1
if(grid1(k) <= xs .and. grid1(k+1) > xs ) then
ks = k
exit
endif
enddo
do k = nk, 2, -1
if(grid1(k) >= xe .and. grid1(k-1) < xe ) then
ke = k
exit
endif
enddo
if(ks == 0 ) call mpp_error(FATAL,' xs locate outside of grid1')
if(ke == 0 ) call mpp_error(FATAL,' xe locate outside of grid1')
end subroutine find_index
end module axis_utils_mod
#ifdef test_axis_utils
program test
use fms_mod, only : fms_init, file_exist, open_namelist_file, check_nml_error
use fms_mod, only : close_file
use mpp_mod, only : mpp_error, FATAL, stdout
use mpp_mod, only : input_nml_file
use axis_utils_mod, only: interp_1d
implicit none
integer, parameter :: maxsize = 100
integer :: n_src = 0
integer :: n_dst = 0
real, dimension(MAXSIZE) :: grid_src = 0
real, dimension(MAXSIZE) :: grid_dst = 0
real, dimension(MAXSIZE) :: data_src = 0
namelist / test_axis_utils_nml / n_src, n_dst, grid_src, grid_dst, data_src
real, allocatable :: data_dst(:)
integer :: unit, ierr, io
call fms_init()
!--- default option of data
n_src = 31
n_dst = 40
grid_src(1:n_src) = (/ -63.6711465476916, -63.6711455476916, 166.564180735096, 401.25299580552, &
641.056493022762, 886.219516665347, 1137.35352761133, 1394.4936854079, &
1657.17893448689, 1925.64572676068, 2200.13183483549, 2480.9124139255, &
2768.35396680912, 3062.86513953019, 3675.47369643284, 4325.10564183322, &
5020.19039479527, 5769.85432323481, 6584.25101514851, 7475.94655633703, &
8462.01951335773, 9568.28246037887, 10178.3869413515, 10834.1425668942, &
11543.5265942777, 12317.3907407535, 13170.4562394288, 14125.6466646843, &
15225.8720618086, 16554.7859690842, 19697.1334102613 /)
grid_dst(1:n_dst) = (/ 1002.9522552602, 1077.51144617887, 1163.37842788755, 1264.19848463606, &
1382.57557953916, 1521.56713587855, 1684.76300370633, 1876.37817787584, &
2101.36166220498, 2365.52429149707, 2675.68881278444, 3039.86610206727, &
3467.4620678435, 3969.52058529847, 4553.81573511231, 5159.54844211827, &
5765.28114912423, 6371.01385613019, 6976.74656313614, 7582.4792701421, &
8188.21197714806, 8793.94468415402, 9399.67739115997, 10005.4100981659, &
10611.1428051719, 11216.8755121778, 11822.6082191838, 12428.3409261898, &
13034.0736331957, 13639.8063402017, 14245.5390472076, 14851.2717542136, &
15457.0044612196, 16062.7371682255, 16668.4698752315, 17274.2025822374, &
17879.9352892434, 18485.6679962493, 19091.4007032553, 19697.1334102613 /)
data_src(1:n_src) = (/ 309.895999643929, 309.991081541887, 309.971074746584, 310.873654697145, &
311.946530606618, 312.862249229647, 314.821236806913, 315.001269608758, &
315.092410930288, 315.19010999336, 315.122964496815, 315.057882573487, &
314.998796850493, 314.984586411292, 315.782246062002, 318.142544345795, &
321.553905292867, 325.247730854554, 329.151282227113, 332.835673638378, &
336.810414210932, 341.64530983048, 344.155248759994, 346.650476976385, &
349.106430095269, 351.915323032738, 354.709396583792, 359.68904432446, &
371.054289820675, 395.098187506342, 446.150726850039 /)
!---reading namelist
#ifdef INTERNAL_FILE_NML
read (input_nml_file, test_axis_utils_nml, iostat=io)
ierr = check_nml_error(io,'test_axis_utils_nml')
#else
if(file_exist('input.nml')) then
unit = open_namelist_file()
ierr=1
do while (ierr /= 0)
read (unit, nml=test_axis_utils_nml, iostat=io, end=10)
ierr = check_nml_error(io,'test_axis_utils_nml') ! also initializes nml error codes
enddo
10 call close_file(unit)
endif
#endif
if(n_src >MAXSIZE) call mpp_error(FATAL, 'test_axis_utils: nml n_src is greater than MAXSIZE')
if(n_dst >MAXSIZE) call mpp_error(FATAL, 'test_axis_utils: nml n_dst is greater than MAXSIZE')
allocate(data_dst(n_dst) )
!--- write out data
unit = stdout()
write(unit,*)' the source grid is ', grid_src(1:n_src)
write(unit,*)' the destination grid is ', grid_dst(1:n_dst)
write(unit,*)' the source data is ', data_src(1:n_src)
call interp_1d(grid_src(1:n_src), grid_dst(1:n_dst), data_src(1:n_src), data_dst, "linear")
write(unit,*)' the destination data using linear interpolation is ', data_dst(1:n_dst)
call interp_1d(grid_src(1:n_src), grid_dst(1:n_dst), data_src(1:n_src), data_dst, "cubic_spline")
write(unit,*)' the destination data using cublic spline interpolation is ', data_dst(1:n_dst)
end program test
#endif /* test_axis_utils */