# csa1s

csa1s calculates an approximating cubic spline for one-dimensional input data. If you want to weight the input data values, calculate derivatives, or handle data sparse areas specially, then you will need to use csa1xs.

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 csa1s(
xi[*]    : float,
yi[*]    : float,
knots[1] : integer
xo[*]    : 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.
knots
The number of knots to be used in constructing the approximation spline. knots must be at least 4. The larger the value for knots, the closer the approximated curve will come to passing through the input function values.
xo
A one-dimensional array containing the X coordinates of the output curve.

## Return value

csa1s returns an array containing the calculated functional values. The returned value has the same size as xo and contains functional values for each element of xo.

## Description

csa1s 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

;----------- Define original data --------------------------------------

xi = (/0.0, 0.1,  0.2,  0.3, 0.5,  0.6, 0.65,  0.8,  0.9, 1./)
yi = (/0.0, 0.8, -0.9, -0.9, 0.9,  1.0, 0.90, -0.8, -0.8, 0./)

npts   = 101
xo     = fspan(0.0,1.0,npts)  ; Create the output X coordinate array.

;--- Calculate approximated function values using differing number of knots.

knots = 4
yo = csa1s(xi,yi,knots,xo)

end
```

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\$Revision: 1.4 \$ \$Date: 1999/03/19 15:32:23 \$