Re: solving equation system

On 2006-07-17, TG <girodt@xxxxxxxxx> wrote:

Ben C wrote:
On 2006-07-17, TG <girodt@xxxxxxxxx> 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

How about this:

from random import *

def solve(A, B):
return reduce(max, (float(b) / a for a, b in zip(A, B)))

def test():
A = [random() for i in range(4)]
B = [random() for i in range(4)]

x = solve(A, B)

for a, b in zip(A, B):
print a, b, a * x - b

test()

This only works if all elements of both A and B are positive.

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.

Is this an array of points, or an array of values, that contains only
one point?

- 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

Do you mean the vector L - W? (LW is a scalar, assuming dot product).

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.

Not very clear to me I'm afraid!
.

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