On 04.06.2015 23:01, Santiago Videla wrote:
From the docs I'd expect h[0][1] == np.mean(w) (which is the case) and h[1][1] == np.std(w) (which is not the case).
As it is written in the documentation, the second value computed is the standard deviation of the _mean_, not the standard deviation of the _population_, which is what you are computing. The standard deviation of the mean is: std(w) / sqrt(len(w))
In fact, I got to this issue trying to implement the analogous function to graph_tool.correlations.avg_neighbour_corr but looking at *in_neighbours* instead of *out_neighbours*
This is trivial, just compute the avg_neighbour_corr with the reversed graph: avg_neighbour_corr(GraphView(g, reversed=True), "in", "out") Best, Tiago -- Tiago de Paula Peixoto <tiago@skewed.de>