From: <jouni.seppanen@gm...>  20041114 16:09:03

Hi, In Matlab, the command [i,j] =3D find(mat >=3D 3) causes i and j to hold the indices where the condition holds. (If there is only one output argument, it will hold indices to the flattened version of the condition.) Matplotlib's mlab.find() seems to work for onedimensional arrays only. Here's what I'm using to emulate Matlab's find; it only seems to work with Numeric, not numarray, and I have no idea whether this is an efficient way to achieve the goal. I was going to suggest that the utility be included in matplotlib, but perhaps it should then be generalized to work with numarray as well. I wonder if anyone has any ideas on how to do this? I'm a newcomer to matplotlib (and Numeric, etc.), so please do point out if there is a simpler way to achieve the effect of Matlab's find. def find(condition): """ Return the indices where condition is true. For arrays of N>=3D2 dimensions, returns a tuple T of N arrays such that the condition is true at indices (T[0][i],...,T[N1][i]). """ sh =3D condition.shape if len(sh) =3D=3D 1: return nonzero(condition) idx =3D indices(sh) cond =3D ravel(condition) return tuple([compress(cond, ravel(idx[i]))=20 for i in range(len(sh))]) =20 Jouni K Sepp=E4nen http://www.iki.fi/jks 