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include "trebin.h"
# tuifit -- initialize or fit
# The input arrays of independent and dependent variable values are copied
# to output arrays, skipping indef values. The number of good values
# (i.e. not indef) is checked to make sure there are enough for the type
# of interpolation specified. In the case of spline interpolation, the
# array y2 of second derivatives is computed.
#
# Phil Hodge, 18-Apr-1988 Subroutine created
# Phil Hodge, 17-Jun-1993 Require at least two values for linear interpolation.
procedure tuifit (i_func, xin, yin, inrows,
xa, ya, y2, n)
int i_func # i: interpolation function code
double xin[ARB] # i: array of independent-variable values
double yin[ARB] # i: array of dependent-variable values
int inrows # i: size of xin, yin arrays
double xa[ARB] # o: array of independent-variable values
double ya[ARB] # o: array of dependent-variable values
double y2[ARB] # o: used only by spline interpolation
int n # o: size of xa, ya, y2 arrays
#--
pointer sp
pointer work # scratch for spline fit
int k # loop index
begin
n = 0 # initial value
do k = 1, inrows {
if ( ! IS_INDEFD(xin[k]) && ! IS_INDEFD(yin[k])) {
n = n + 1
xa[n] = xin[k]
ya[n] = yin[k]
}
}
switch (i_func) {
case I_NEAREST:
if (n < 1)
n = 0 # flag it as bad
case I_LINEAR:
if (n < 2)
n = 0
case I_POLY3:
if (n < 4)
n = 0
case I_SPLINE:
if (n >= 4) {
call smark (sp)
call salloc (work, n, TY_DOUBLE)
call tucspl (xa, ya, n, Memd[work], y2)
call sfree (sp)
} else {
n = 0
}
}
end
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