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‎LICENSE‎

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finterp: Modern Fortran Multidimensional Linear Interpolation
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https://github.com/jacobwilliams/finterp
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Copyright (c) 2016-2021, Jacob Williams
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Copyright (c) 2016-2022, Jacob Williams
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All rights reserved.
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Redistribution and use in source and binary forms, with or without modification,

‎README.md‎

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## Status
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[![GitHub release](https://img.shields.io/github/release/jacobwilliams/finterp.svg?style=plastic)](https://github.com/jacobwilliams/finterp/releases/latest)
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![Build Status](https://github.com/jacobwilliams/finterp/actions/workflows/CI.yml/badge.svg?branch=master)
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[![codecov](https://codecov.io/gh/jacobwilliams/finterp/branch/master/graph/badge.svg?token=BHtd51oUTE)](https://codecov.io/gh/jacobwilliams/finterp)
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## Description
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The library also includes classes for nearest neighbor interpolation (`nearest_interp_1d`, `nearest_interp_2d`, ...). The interfaces are the same as for the linear classes.
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## Compiling
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A `fmp.toml` file is provided for compiling finterp with the [Fortran Package Manager](https://github.com/fortran-lang/fpm). For example, to build:
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```
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fpm build --profile release
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```
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By default, the library is built with double precision (`real64`) real values. Explicitly specifying the real kind can be done using the following processor flags:
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Preprocessor flag | Kind | Number of bytes
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----------------- | ----- | ---------------
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`REAL32` | `real(kind=real32)` | 4
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`REAL64` | `real(kind=real64)` | 8
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`REAL128` | `real(kind=real128)` | 16
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For example, to build a single precision version of the library, use:
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```
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fpm build --profile release --flag "-DREAL32"
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```
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To run the unit tests:
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```
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fpm test
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```
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To use `finterp` within your fpm project, add the following to your `fpm.toml` file:
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```toml
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[dependencies]
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finterp = { git="https://github.com/jacobwilliams/finterp.git" }
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```
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or, to use a specific version:
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```toml
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[dependencies]
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finterp = { git="https://github.com/jacobwilliams/finterp.git", tag = "1.3.0" }
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```
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To generate the documentation using [ford](https://github.com/Fortran-FOSS-Programmers/ford), run: ```ford finterp.md```
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## Documentation
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The latest API documentation can be found [here](https://jacobwilliams.github.io/finterp/). This was generated from the source code using [FORD](https://github.com/Fortran-FOSS-Programmers/ford) (note that the included `build.sh` script will also generate these files).

‎finterp.md‎

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protected
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source: true
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graph: true
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exclude_dir: ./tests
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exclude_dir: ./test
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extra_mods: iso_fortran_env:https://gcc.gnu.org/onlinedocs/gfortran/ISO_005fFORTRAN_005fENV.html
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{!README.md!}

‎fpm.toml‎

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name = "finterp"
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version = "1.2.3"
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version = "1.3.0"
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author = "Jacob Williams"
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maintainer = "Jacob Williams"
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copyright = "Copyright (c) 2016-2021, Jacob Williams"

src/linear_interpolation_module.f90 renamed to src/linear_interpolation_module.F90

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! which have been tabulated at the nodes of an n-dimensional rectangular grid.
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! If any coordinate \( (x_i, y_i, ...) \) lies outside the range of the corresponding
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! variable, then extrapolation is performed using the two nearest points.
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!
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!@note The default real kind (`wp`) can be
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! changed using optional preprocessor flags.
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! This library was built with real kind:
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#ifdef REAL32
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! `real(kind=real32)` [4 bytes]
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#elif REAL64
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! `real(kind=real64)` [8 bytes]
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#elif REAL128
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! `real(kind=real128)` [16 bytes]
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#else
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! `real(kind=real64)` [8 bytes]
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#endif
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module linear_interpolation_module
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use iso_fortran_env, only: wp => real64 ! working precision
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use iso_fortran_env
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implicit none
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private
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#ifdef REAL32
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integer,parameter,public :: finterp_rk = real32 !! real kind used by this module [4 bytes]
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#elif REAL64
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integer,parameter,public :: finterp_rk = real64 !! real kind used by this module [8 bytes]
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#elif REAL128
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integer,parameter,public :: finterp_rk = real128 !! real kind used by this module [16 bytes]
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#else
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integer,parameter,public :: finterp_rk = real64 !! real kind used by this module [8 bytes]
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#endif
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integer,parameter :: wp = finterp_rk !! local copy of `finterp_rk` with a shorter name
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real(wp),parameter,private :: zero = 0.0_wp !! numeric constant
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real(wp),parameter,private :: one = 1.0_wp !! numeric constant
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‎test/test.f90‎

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program linear_interpolation_test
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use linear_interpolation_module
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use,intrinsic :: iso_fortran_env, only: wp => real64
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use linear_interpolation_module, wp => finterp_rk
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implicit none
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integer,parameter :: ns = 6 !! number of points in s
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real(wp) :: x(nx),y(ny),z(nz),q(nq),r(nr),s(ns)
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real(wp) :: fcn_1d(nx)
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real(wp) :: fcn_2d(nx,ny)
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real(wp) :: fcn_3d(nx,ny,nz)
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real(wp) :: fcn_4d(nx,ny,nz,nq)
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real(wp) :: fcn_5d(nx,ny,nz,nq,nr)
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real(wp) :: fcn_6d(nx,ny,nz,nq,nr,ns)
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real(wp),dimension(:),allocatable :: fcn_1d
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real(wp),dimension(:,:),allocatable :: fcn_2d
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real(wp),dimension(:,:,:),allocatable :: fcn_3d
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real(wp),dimension(:,:,:,:),allocatable :: fcn_4d
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real(wp),dimension(:,:,:,:,:),allocatable :: fcn_5d
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real(wp),dimension(:,:,:,:,:,:),allocatable :: fcn_6d
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type(linear_interp_1d) :: s1
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type(linear_interp_2d) :: s2
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real(wp) :: tol,rnd
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real(wp),dimension(6) :: val,tru,err,errmax
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logical :: fail
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integer :: i,j,k,l,m,n,idx,idy,idz,idq,idr,ids
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integer :: i,j,k,l,m,n
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integer,dimension(6) :: iflag
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allocate(fcn_1d(nx))
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allocate(fcn_2d(nx,ny))
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allocate(fcn_3d(nx,ny,nz))
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allocate(fcn_4d(nx,ny,nz,nq))
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allocate(fcn_5d(nx,ny,nz,nq,nr))
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allocate(fcn_6d(nx,ny,nz,nq,nr,ns))
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fail = .false.
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tol = 1.0e-14_wp
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do i=1,nx

‎test/test_nearest.f90‎

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program nearest_neighbor_test
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use linear_interpolation_module
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use,intrinsic :: iso_fortran_env, only: wp => real64
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use linear_interpolation_module, wp => finterp_rk
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implicit none
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type(nearest_interp_1d) :: s1
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real(wp) :: val,tru,err,errmax
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integer :: i,idx,iflag
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integer :: i,iflag
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! initialize
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call s1%initialize(x,fcn_1d,iflag)

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