Scipy interp2d function produces z = f(x,y), I would like to solve for x
I was able to figure this out.  yvalue, zvalue, xmin, and xmax are known values.  By creating a linspace out of the possible values x can take on, a list can be created with all of the corresponding function values.  Then using argmin() we can find the closest value in the list to the known z value.  
f = interp2d(x,y,z)
xnew = numpy.linspace(xmin, xmax)
fnew = f(xnew, yvalue)
xindex = (numpy.abs(fnew - zvalue)).argmin()
xvalue = xnew(xindex)
I am using the 2d interpolation function in scipy to smooth a 2d image.  As I understand it, interpolate will return z = f(x,y).  What I want to do is find x with known values of y and z.  I tried something like this;
f = interp2d(x,y,z)
index = (np.abs(f(:,y) - z)).argmin()
However the interp2d object does not work that way.  Any ideas on how to do this?