[SciPy-user] interp1d problem
Ben Webber
b.webber@uea.ac...
Mon Nov 3 09:00:05 CST 2008
Hi,
In CDAT I have been trying to use the interp1d class from the
scipy.interpolate package to interpolate 3-dimensional oceanographic data
along the time axis using cubic splines. This works fine for 1 or 2
dimensional data but fails for 3 dimensional data. However, using linear
interpolation works no matter what the dimensions. I have tried to simplify
the problem as much as possible and have created the following simplified
script:
import scipy
from scipy.interpolate import interp1d
test_array = [[[2,6],[10,7]],[[4,8],[12,9]],[[2,6],[10,7]],[[4,8],[12,9]]]
test_array = scipy.array(test_array)
test_axis = scipy.array(range(0,31,10))
myInterp = interp1d(test_axis,test_array,kind='cubic',axis = 0)
#-----------------fails here----------------------
new_axis = scipy.array(range(0,31))
new_data = myInterp(new_axis)
If kind is specified as 'linear' this script works. However, with kind as
'cubic', I get the following error:
Traceback (most recent call last):
File "cubic_interp.py", line 11, in <module>
myInterp = interp1d(timeax_array,theta_array,kind = 'cubic',axis = 0)
File
"/cvos/apps/CDAT-5.0.b1/lib/python2.5/site-packages/scipy/interpolate/interpolate.py",
line 235, in __init__
self._spline = splmake(x,oriented_y,order=order)
File
"/cvos/apps/CDAT-5.0.b1/lib/python2.5/site-packages/scipy/interpolate/interpolate.py",
line 697, in splmake
coefs = func(xk, yk, order, conds, B)
File
"/cvos/apps/CDAT-5.0.b1/lib/python2.5/site-packages/scipy/interpolate/interpolate.py",
line 431, in _find_smoothest
return dot(tmp, yk)
ValueError: objects are not aligned
The shape of the array is (4,2,2). The time axis is length 4, so it should
work. Can anybody explain this error?
Cheers,
Ben Webber
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