You need to use numpy.logical_and. The and and or operators do not work elementwise on arrays to the best of my understanding. I think it is a limitation on the way logical operators are applied in python or maybe it is an intentional numpy limitation. I'm sure others on the list could explain better.
Also where is the wrong function. You want compress: In [8]: image2 = numpy.array([-1,1,1,1]) In [9]: image1 = numpy.array([1,-1,2,3]) In [10]: numpy.arange(len(image2)).compress(numpy.logical_and(image1 > 0, image2 > 0)) Out[10]: array([2, 3]) Others might have a better way but this at least works. --Tom On 3/27/07, Ludwig <[EMAIL PROTECTED]> wrote: > A bit new to numpy, trying to move over some IDL code. > > I have a complex array selection expression, where I need an array of indexes > as > a result, so I can use this as a selection expression to apply changes to a > different array. > > I have two images, image1 and image2, plus an array sigma, the result of a > previous calculation. All have the same shape. quality is a scalar threshold. > > I need the indexes where image1 and image2 are not 0 and the sigma value at > that > point is lower than my threshold. I then take these indices and store some > value > against this in a different array. > > In pseudo code: > > indexes = where(image1 > 0 and image2 > 0 and sigma < quality) > result[indexes] = i # scalar > > > When I run this numpy tells me that the that the truth value of the array > comparison is ambiguous -- but I do not want to compare the whole arrays here, > but the value for every point. > > How do I do this > > Regards > > Ludwig > > > > > > > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
