Cubic Spline function in scipy.interpolate returns a numpy.ndarray

Question

I need to use CubicSpline to interpolated between points. This is my function

cs = CubicSpline(aTime, aControl)
u = cs(t)   # u is a ndarray of one element.

I cannot convert u to a float. uu = float(u) or uu = float(u[0]) doesn't work in the function. I can convert u to a float in the shell by float(u) . This shouldn't work because I have not provided an index but I get an error if I use u[0] . I have read something about np.squeeze . I tried it but it didn't help.

I added a print ("u=",u) statement after the u=cs(t) . The result was

u= [  1.88006889e+09   5.39398193e-01   5.39398193e-01]

How can this be? I expect 1 value. The second and third numbers look about right.

Answer 1

I found the problem. Programming error, of course but the error messages I got were very misleading. I was calling the interpolate function with 3 values so it returned three vales. Why I couldn't get just the one afterwards is still a mystery but now that I call the interpolate with just one value I get one float as expected. Overall this still didn't help as the interpolate1d function is too slow. I wrote my own cubic interpolate function that is MUCH faster.

Again, programming error and poor error messages were the problem.