scipy.interpolate.interpn(points, values, xi, method='linear', bounds_error=True, fill_value=nan)[source]
The data dimension I want to interpolate is three-dimensional. The dimensions are like this
[90, 180, 8]. When the parameter method is set to 'cubic', an error will be reported：ValueError: interpn only understands the methods 'linear', 'nearest', and 'splinef2d'. You provided cubic. Why? Does 3D data not support such parameter settings?
I want to realize cubic Spline interpolation interpolation of 3D data.
Check your scipy version: the cubic mode was only added in scipy 1.10.