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|
! Grid data demo.
!
! Copyright (C) 2004 Joao Cardoso
! Copyright (C) 2008 Andrew Ross
! Copyright (C) 2008-2016 Alan W. Irwin
!
! This file is part of PLplot.
!
! PLplot is free software; you can redistribute it and/or modify
! it under the terms of the GNU Library General Public License as
! published by the Free Software Foundation; either version 2 of the
! License, or (at your option) any later version.
!
! PLplot 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 Library General Public License for more details.
!
! You should have received a copy of the GNU Library General Public
! License along with PLplot; if not, write to the Free Software
! Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
! N.B. the pl_test_flt parameter used in this code is only
! provided by the plplot module to allow convenient developer
! testing of either kind(1.0) or kind(1.0d0) floating-point
! precision regardless of the floating-point precision of the
! PLplot C libraries. We do not guarantee the value of this test
! parameter so it should not be used by users, and instead user
! code should replace the pl_test_flt parameter by whatever
! kind(1.0) or kind(1.0d0) precision is most convenient for them.
! For further details on floating-point precision issues please
! consult README_precision in this directory.
!
program x21f
use plplot, double_PI => PL_PI
implicit none
real(kind=pl_test_flt), parameter :: PI = double_PI
integer pts, xp, yp, nl, knn_order, randn, rosen
real(kind=pl_test_flt) threshold, wmin
parameter (pts = 500)
parameter (xp = 25)
parameter (yp = 20)
parameter (nl = 16)
parameter (knn_order = 20)
parameter (threshold = 1.001_pl_test_flt)
parameter (wmin = -1e3_pl_test_flt)
parameter (randn = 0)
parameter (rosen = 0)
real(kind=pl_test_flt) xmin, xmax, ymin, ymax
real(kind=pl_test_flt) x(pts), y(pts), z(pts), clev(nl)
real(kind=pl_test_flt) xg(xp), yg(yp), zg(xp,yp)
real(kind=pl_test_flt) zmin, zmax, lzmin, lzmax
integer i, j, k
integer alg
character(len=80) title(6)
data title /'Cubic Spline Approximation', &
'Delaunay Linear Interpolation', &
'Natural Neighbors Interpolation', &
'KNN Inv. Distance Weighted', &
'3NN Linear Interpolation', &
'4NN Around Inv. Dist. Weighted'/
real(kind=pl_test_flt) opt(6)
data opt /0._pl_test_flt, 0._pl_test_flt, 0._pl_test_flt, 0._pl_test_flt, 0._pl_test_flt, 0._pl_test_flt/
real(kind=pl_test_flt) xt, yt
real(kind=pl_test_flt) r
integer ii, jj
integer :: plparseopts_rc
real(kind=pl_test_flt) dist, d
xmin = -0.2_pl_test_flt
ymin = -0.2_pl_test_flt
xmax = 0.6_pl_test_flt
ymax = 0.6_pl_test_flt
! call plMergeOpts(options, "x21c options", NULL);
plparseopts_rc = plparseopts(PL_PARSE_FULL)
if(plparseopts_rc .ne. 0) stop "plparseopts error"
opt(3) = wmin
opt(4) = real(knn_order,kind=pl_test_flt)
opt(5) = threshold
! Initialize plplot
call plinit
call cmap1_init
call plseed(5489)
do i=1,pts
xt = (xmax-xmin)*plrandd()
yt = (ymax-ymin)*plrandd()
if (randn.eq.0) then
x(i) = xt + xmin
y(i) = yt + ymin
else
x(i) = sqrt(-2._pl_test_flt*log(xt)) * cos(2._pl_test_flt*PI*yt) + xmin
y(i) = sqrt(-2._pl_test_flt*log(xt)) * sin(2._pl_test_flt*PI*yt) + ymin
endif
if (rosen.eq.0) then
r = sqrt(x(i)*x(i) + y(i)*y(i))
z(i) = exp(-r*r)*cos(2._pl_test_flt*PI*r)
else
z(i) = log((1._pl_test_flt-x(i))**2 + 100._pl_test_flt*(y(i)-x(i)**2)**2)
endif
enddo
zmin = z(1)
zmax = z(1)
do i=2,pts
zmax = max(zmax,z(i))
zmin = min(zmin,z(i))
enddo
do i=1,xp
xg(i) = xmin + (xmax-xmin)*(i-1._pl_test_flt)/(xp-1._pl_test_flt)
enddo
do i=1,yp
yg(i) = ymin + (ymax-ymin)*(i-1._pl_test_flt)/(yp-1._pl_test_flt)
enddo
call plcol0(1)
call plenv(xmin, xmax, ymin, ymax, 2, 0)
call plcol0(15)
call pllab("X", "Y", "The original data sampling")
do i=1,pts
call plcol1( ( z(i) - zmin ) / ( zmax - zmin ) )
! The following plstring call should be the the equivalent of
! plpoin( 1, &x[i], &y[i], 5 ); Use plstring because it is
! not deprecated like plpoin and has much more powerful
! capabilities. N.B. symbol 141 works for Hershey devices
! (e.g., -dev xwin) only if plfontld( 0 ) has been called
! while symbol 727 works only if plfontld( 1 ) has been
! called. The latter is the default which is why we use 727
! here to represent a centred X (multiplication) symbol.
! This dependence on plfontld is one of the limitations of
! the Hershey escapes for PLplot, but the upside is you get
! reasonable results for both Hershey and Unicode devices.
call plstring( x(i:i), y(i:i), '#(727)' );
enddo
call pladv(0)
call plssub(3,2)
do k=1,2
call pladv(0)
do alg=1,6
call plgriddata(x, y, z, xg, yg, zg, alg, opt(alg))
! - CSA can generate NaNs (only interpolates? !).
! - DTLI and NNI can generate NaNs for points outside the convex hull
! of the data points.
! - NNLI can generate NaNs if a sufficiently thick triangle is not found
!
! PLplot should be NaN/Inf aware, but changing it now is quite a job...
! so, instead of not plotting the NaN regions, a weighted average over
! the neighbors is done.
!
if ((alg.eq.GRID_CSA).or.(alg.eq.GRID_DTLI).or. &
(alg.eq.GRID_NNLI).or.(alg.eq.GRID_NNI)) then
do i=1,xp
do j=1,yp
if (myisnan(zg(i,j))) then
! average (IDW) over the 8 neighbors
zg(i,j) = 0._pl_test_flt
dist = 0._pl_test_flt
ii=i-1
do while ((ii.le.i+1).and.(ii.le.xp))
jj = j-1
do while ((jj.le.j+1).and.(jj.le.yp))
if ((ii.ge.1) .and. (jj.ge.1) .and. &
(.not.myisnan(zg(ii,jj))) ) then
if (abs(ii-i) + abs(jj-j) .eq. 1) then
d = 1._pl_test_flt
else
d = 1.4142_pl_test_flt
endif
zg(i,j) = zg(i,j) + zg(ii,jj)/(d*d)
dist = dist + d
endif
jj = jj+1
enddo
ii = ii+1
enddo
if (dist.ne.0._pl_test_flt) then
zg(i,j) = zg(i,j) / dist
else
zg(i,j) = zmin
endif
endif
enddo
enddo
endif
call a2mnmx(zg, xp, yp, lzmin, lzmax, xp)
lzmin = min(lzmin, zmin)
lzmax = max(lzmax, zmax)
lzmin = lzmin - 0.01_pl_test_flt
lzmax = lzmax + 0.01_pl_test_flt
call plcol0(1)
call pladv(alg)
if (k.eq.1) then
do i=1,nl
clev(i) = lzmin + (lzmax-lzmin)/(nl-1._pl_test_flt)*(i-1._pl_test_flt)
enddo
call plenv0(xmin, xmax, ymin, ymax, 2, 0)
call plcol0(15)
call pllab("X", "Y", title(alg))
call plshades(zg, xmin, xmax, ymin, &
ymax, clev, 1._pl_test_flt, 0, 1._pl_test_flt, .true. )
call plcol0(2)
else
do i = 1,nl
clev(i) = lzmin + (lzmax-lzmin)/(nl-1._pl_test_flt)*(i-1._pl_test_flt)
enddo
call plvpor(0._pl_test_flt, 1._pl_test_flt, 0._pl_test_flt, 0.9_pl_test_flt)
call plwind(-1.1_pl_test_flt, 0.75_pl_test_flt, -0.65_pl_test_flt, 1.20_pl_test_flt)
!
! For the comparison to be fair, all plots should have the
! same z values, but to get the max/min of the data generated
! by all algorithms would imply two passes. Keep it simple.
!
! plw3d(1., 1., 1., xmin, xmax, ymin, ymax, zmin, zmax, 30, -60);
!
call plw3d(1._pl_test_flt, 1._pl_test_flt, 1._pl_test_flt, xmin, xmax, ymin, ymax, &
lzmin, lzmax, 30._pl_test_flt, -40._pl_test_flt)
call plbox3("bntu", "X", 0._pl_test_flt, 0, &
"bntu", "Y", 0._pl_test_flt, 0, &
"bcdfntu", "Z", 0.5_pl_test_flt, 0)
call plcol0(15)
call pllab("", "", title(alg))
call plot3dc(xg, yg, zg, ior(ior(DRAW_LINEXY, &
MAG_COLOR), BASE_CONT), clev)
endif
enddo
enddo
call plend
contains
subroutine cmap1_init
use plplot
implicit none
real(kind=pl_test_flt) i(2), h(2), l(2), s(2)
i(1) = 0._pl_test_flt
i(2) = 1._pl_test_flt
h(1) = 240._pl_test_flt
h(2) = 0._pl_test_flt
l(1) = 0.6_pl_test_flt
l(2) = 0.6_pl_test_flt
s(1) = 0.8_pl_test_flt
s(2) = 0.8_pl_test_flt
call plscmap1n(256)
call plscmap1l(.false., i, h, l, s)
end subroutine cmap1_init
!----------------------------------------------------------------------------
! Subroutine a2mnmx
! Minimum and the maximum elements of a 2-d array.
subroutine a2mnmx(f, nx, ny, fmin, fmax, xdim)
use plplot
implicit none
integer i, j, nx, ny, xdim
real(kind=pl_test_flt) f(xdim, ny), fmin, fmax
fmax = f(1, 1)
fmin = fmax
do j = 1, ny
do i = 1, nx
fmax = max(fmax, f(i, j))
fmin = min(fmin, f(i, j))
enddo
enddo
end subroutine a2mnmx
include 'plfortrandemos.inc'
end program x21f
|
