@PaigeMiller wrote:
@ballardw wrote:
If you have SAS/Graph licensed and access to Proc G3Grid that might be another option.
The OP specifically ruled out PROC G3GRID for this task. Is there a way to obtain interpolations from PROC G3GRID?
I suspect the OP either did not test G3grid or the data he has to work from does not cover the area well.
From the documentation there are some concerns:
If the points that are generated by the horizontal variables tend to lie along a curve, a poor interpolation or spline can result. In such cases, the vertical variable(s), and one of the horizontal variables should be modeled as a function of the remaining horizontal variable. A scatter plot of the two horizontal variables enable you to determine the appropriate function.
However I suspect any model approach may have a similar problem going much outside of the existing range of values.
The first example from the documentation creates an example input set and the uses the proc.
data nums;
keep x y z;
do i=1 to 30;
x=10*ranuni(33)-5;
y=10*ranuni(33)-5;
z=sin(sqrt(x*x+y*y));
output;
end;
run;
proc g3grid data=nums out=default;
grid y*x=z /
axis1=-5 to 5 by .5
axis2=-5 to 5 by .5;
run;
quit;
It is pretty easy to see that for this example we end up with lots of interpolated Z values from X and Y that do not actually exist in the data. When I ran the NUMS data step above none of the x or y variables have values that were values in the axis statements above but every one has a Z associated. The question might be how good for the intended use. There are a number of interpolation options available but the question may be suitable for specific purpose.
I think the code is simple enough to be worth testing as the AXIS statement will accept a list of values.
proc g3grid data=nums out=list;
grid y*x=z /
axis1=1 2 3
axis2= 4 5 6;
run;
quit;
Has output values for y=1 2 3 each paired with x=4 5 6. This might create a few more points than the OP needs but it should not be hard to drop any unneeded ones.
