[SciPy-user] Creating a Matrix from a Sum

[David Warde-Farley]

On 2-Jul-09, at 9:25 AM, Lorenzo Isella wrote:

> Dear All,
> I need some help to efficiently write an array manipulation. I suspect
> this could be a one-liner.
> Assume that you have a histogram of observations that you store in a
> vector x.
> Let us say that its i-th entry, x_i, corresponds to the number of
> observations in the i-th channel, for i=1,2...N. (or 0,1...N-1, please
> let me know if there is any potential 0/1 pitfall in the following).
> Now, for any two channels i and j, I want to calculate the probability
> of having an observation  in any other channel k, where  k>=max(i,j).
> That is to say
>
> P(i,j)=sum_{k=max(i,j)}^N x_k /C,
> where C=sum_{i=1}^N x_i is just a normalization factor.

Hm, there might be a simpler/more efficient way but this is what I  
came up with as far as 1-liners:

P = np.max(np.concatenate(np.broadcast_arrays(x[np.newaxis, :,  
np.newaxis], x[:, np.newaxis, np.newaxis]),axis=2),axis=2); P /= x.sum()