[Numpy-discussion] replace voids in 2d dat with nearest neighbour value
Mon Apr 6 11:42:57 CDT 2009
Zachary Pincus wrote:
> Hi Christian,
> Check out this discussion from a little while ago on a very similar
> issue (but in 3d):
> Most of the suggestions should be directly applicable.
I'm in the early stages of testing the scipy.interpolate.Rbf(...)
function (one of the approaches Robert Kern suggested in the discussion
Zach mentioned) for a not too dissimilar application -- replacing the
bad pixels regions in Solar X-ray images captured by a damaged
detector. Preliminary results look promising for this application.
> On Apr 6, 2009, at 9:01 AM, Christian K. wrote:
>> I am looking for an elegant and fast way to fill the voids of a 2d
>> array with
>> neighbouring values. The array's size can be up to (1000, 1000) and
>> its values
>> are slowly varying around a mean value. What I call voids are values
>> which are
>> far from the mean value (+- 80%). A void usually extends over some
>> Currently I am using
>> tmp = N.ma.array(tmp, tmp<threshold)
>> data[tmp.mask] = tmp.mean()
>> which moves the voids closer to the mean value but which is still
>> far from
>> beeing a smooth interpolation.
>> Regards, Christian
>> Numpy-discussion mailing list
> Numpy-discussion mailing list
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