Ben C wrote: > On 2006-07-17, TG <[EMAIL PROTECTED]> wrote: > > Hi there. > > > > Anyone knows how to use numpy / scipy in order to solve this ? > > > > * A is an array of shape (n,) > > * X is a positive float number > > * B is an array of shape (n,) > > * O is an array of shape (n,) containing only zeros. > > > > A.X - B = O > > min(X) > > Are we solving for A, B or X? And what do you mean by min(X)? > > If we're solving for X there will be many combinations of A and B for > which there is no solution.
Sorry for the poor explanation. I'm trying to put it clear now. i've got A and B. I'm looking for X. I made a mistake in my equation :-/ It's more like : A.X - B >= O Well, maybe it will be much more simple if I explain the underlying problem : I have an array of N dimensions (generally 2). - A first calculation gives me a set of integer coordinates inside this array, which I will call the point W. - After several other calculations, I've got a set of coordinates in this N dimensional space that are floating values, and not bound to the limits of my original N-array. This is the point L. What I want to do is to translate the point L along the vector LW in order to get a point L' which coordinates are inside the original N-dimensional array. Then it will be easy to get the closest integer coordinates from L'. I'm not sure this is clear ... pretty hard to talk about maths in english. -- http://mail.python.org/mailman/listinfo/python-list
