csa2xs
csa2xs calculates an approximating cubic spline for
two-dimensional input data.
csa2xs
is called if you want to
weight
the input data values,
calculate
derivatives,
or
handle data
sparse areas specially.
If you do not want to do any of these three things, then use
csa2s.
Note: This function is only available in version 4.1.1 of
NCL. If your site is licensed for version 4.1, then you can get
version 4.1.1 for free. To get version 4.1.1 of NCAR Graphics
software, please contact your site representative. If you don't know
who your site representative is, then send email to ncarginf@ucar.edu or call (303)
497-1201.
Synopsis
function csa2xs(
xi[*] : float,
yi[*] : float,
zi[*] : float,
wts[*] : float,
knots[2] : integer
smth[1] : float
nderiv[2] : float
xo[*] : float
yo[*] : float
)
Arguments
- xi
- A one-dimensional array of any size containing the X coordinates of the
input data points.
- yi
- A one-dimensional array of the same size as xi containing the Y
coordinates of the input data points.
- zi
- A one-dimensional array of the same size as xi and yi
containing the functional values at the input data coordinates given
by xi and yi. zi[k] is the input function
value at (xi[k],yi[k]) for k=0 to
dimsizes(xi)-1.
- wts
- An array containing weights for the zi values at the input
xi and yi values,
that is, wts(k) is a weight for the value
of zi(k) for k=0,dimsizes(xi)-1.
If you do not desire to weight the input zi values, then set
wts to -1, and in that case wts can be a scalar.
The weights in the wts array are relative and
may be set to any non-negative value. When csa2xs is called,
the weights are summed and the individual weights are normalized
so that the weight sum is unity.
-
knots
- The number of knots to be used in constructing the approximating
surface. knots(0) and knots(1) must both
be at least 4. The larger the value for knots,
the closer the approximated surface will come to passing through the
input function values.
- smth
- A parameter that controls extrapolation into data sparse regions.
If smth is zero, then nothing special is done in data sparse
regions. A good first choice for smth is 1.
- nderiv
- Specifies whether you want functional values (=0),
first derivative values (=1), or second derivative
values (=2) in each of the two coordinate directions.
- xo
- A one-dimensional array containing the X coordinates of the
output surface.
- yo
- A one-dimensional array containing the Y coordinates of the
output surface.
Return value
csa2xs returns a two-dimensional array containing the
calculated functional values. The first dimension of the
returned value has the same size as xo and the
second dimension of the returned value has the same size as yo.
If zo is the returned value, then zo(i,j)
contains the functional values at coordinate
(xo(i),yo(j)).
Description
csa2xs is in the
csagrid package
- a software package that
implements a cubic spline approximation algorithm to
fit a function to input data. The input for the approximation is
a set of randomly-spaced data. These data may be one-dimensional,
two-dimensional, or three-dimensional.
The general documentation for csagrid contains several
complete examples
for entries in the csagrid package.
Example
begin
;
; Create the input arrays.
;
xmin = -1.
xmax = 1.
ymin = -1.
ymax = 1.
nx = 29
ny = 25
ndata = 1000
xi = new(ndata,float)
yi = new(ndata,float)
zi = new(ndata,float)
;
; Generate input data using the function f(x,y) = y**2 - 0.5*y*x**2
;
do i=0,ndata-1
xi(i) = xmin + (xmax-xmin)*rand()/32767.
yi(i) = ymin + (ymax-ymin)*rand()/32767.
zi(i) = yi(i)*yi(i) - 0.5*xi(i)*xi(i)*yi(i)
end do
;
; Set up the output grid.
;
xo = fspan(xmin,xmax,nx)
yo = fspan(ymin,ymax,ny)
knots = (/4,4/)
;
; Calculate the approximated function values.
;
wts = -1.
smth = 0.
nderiv = (/1,2/)
yo = csa2xs(xi,yi,zi,wts,knots,smth,nderiv,xo,yo)
end
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$Revision: 1.3 $ $Date: 1999/03/18 22:38:59 $