SAS optimization and extension to multiple observations (code)

[dufourc1]

Based on https://github.com/mahalakshmi-sabanayagam/Clustering-Testing-Networks

def hist_apprx(graphs, n0=30):
    graphs_appr = []
    for graph in graphs:
        # degree sort
        nn = graph.shape[0]
        h = int(nn / n0)

        deg = torch.sum(graph, axis=1)
        id_sort = torch.argsort(-deg)

        graph_sorted = graph[id_sort]
        graph_sorted = graph_sorted[:, id_sort]

        # histogram approximation
        graph_apprx = torch.zeros((n0, n0), dtype=torch.float64).to(device=device)
        for i in range(n0):
            for j in range(i + 1):
                graph_apprx[i][j] = torch.sum(graph_sorted[i * h:i * h + h, j * h:j * h + h]) / (h * h)
                graph_apprx[j][i] = graph_apprx[i][j]

        graphs_appr.append(graph_apprx)

    return graphs_appr

[dufourc1]

Linked to #74