[SciPy-user] Linear Interpolation Question

Andrea Gavana andrea.gavana@gmail....
Mon Apr 28 08:32:25 CDT 2008

Hi All,

On Mon, Apr 28, 2008 at 12:41 PM, Andrea Gavana wrote:
> Hi All,
>   I have 2 matrices coming from 2 different simulations: the first
> column of the matrices is a date (time) at which all the other results
> in the matrix have been reported (simulation step). In these 2
> matrices, very often the simulation steps do not coincide, so I just
> want to interpolate the results in the second matrix using the dates
> in the first matrix. The problem is, I have close to 13,000 columns in
> every matrices, and repeating interp1d all over the columns is quite
> expensive. An example of what I am doing is as follows:
> # Loop over all the columns
> for indx in indices:
>    # Set up a linear interpolation with:
>    # x = dates in the second simulation
>    # y = single column in the second matrix simulation
>    function = interp1d(secondaryMatrixDates,
> secondaryMatrixResults[:, indx], kind='linear')
>    # Interpolate the second matrix results using the first simulation dates
>    interpolationResults = function(mainMatrixDates)
>    # I need the difference between the first simulation and the second
>    newMatrix[:, indx] = mainMatrixResults[:, indx] - interpolationResults
> This is somehow a costly step, as it's taking up a lot of CPU
> (increasing at every iteration) and quite a long time (every column
> has about 350 data). Is there anything I can do to speed up this loop?
> Or may someone suggest a better approach?
> Thank you very much for your suggestions.

Ok, I have tried to be smart and use interp2d, but interp2d gives me a
strange error message which I can't understand:

Traceback (most recent call last):
  File "D:\MyProjects\Interp2DSample.py", line 25, in <module>
    function = interp2d(xx, yy, z, kind="linear", copy=False)
  File "C:\Python25\lib\site-packages\scipy\interpolate\interpolate.py",
line 91, in __init__
    self.tck = fitpack.bisplrep(self.x, self.y, self.z, kx=kx, ky=ky, s=0.)
  File "C:\Python25\lib\site-packages\scipy\interpolate\fitpack.py",
line 677, in bisplrep
OverflowError: long int too large to convert to int

I am able to get this error message using this simple script:

import datetime
import numpy
from scipy.interpolate import interp2d

date1, date2 = [], []
numColumns = 13000

for year in xrange(2007, 2038):
    for month in xrange(1, 13):
        date1.append(datetime.date(year, month, 1).toordinal())
        date2.append(datetime.date(year, month, 5).toordinal())

timeSteps = len(date2)

x = [date1[0] for i in xrange(numColumns)]
y = date1
z = numpy.random.rand(timeSteps, numColumns)

xx, yy = numpy.meshgrid(x, y)

newX = [date2[0] for i in xrange(numColumns)]
newY = date2

function = interp2d(xx, yy, z, kind="linear", copy=False)

newZ = function(newX, newY)

Does anyone know what I am doing wrong? I am on Windows XP, Python
2.5, scipy, numpy

Thank you very much for your suggestions.


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