Update notebooks and scripts

sociopatterns.py

@@ -0,0 +1,106 @@
+#!/usr/bin/env python3
+
+import numpy as np
+import igraph as ig
+import dionysus as d
+
+import multiprocessing
+# from dask.distributed import Client
+
+from zigzag import sliding_windows, zigzag_network
+from wrcf import wrcf_diagram
+from sliced_wasserstein import diagram_array, SW_approx
+
+import dill
+
+
+def remove_inf(dgm):
+    """Remove infinite points in a persistence diagram.
+
+    :param dgm: Diagram
+
+    :return: the same diagram without the infinite points.
+    """
+    res = d.Diagram()
+    for p in dgm:
+        if p.death != np.inf:
+            res.append(p)
+    return res
+
+
+## Global parameters
+N_WINDOWS = 40
+
+## Computations
+ZIGZAG_PERS = True
+WRCF_PERS = True
+SW_KERNEL = True
+BOTTLENECK_DIST = True
+
+
+if __name__=="__main__":
+    print("Loading SocioPatterns dataset...", end="", flush=True)
+    g = ig.read("data/sociopatterns/infectious/infectious.graphml")
+    del g.es["id"]
+    # print(g.summary())
+    print("done.")
+
+    print("Temporal partitioning...", end="", flush=True)
+    wins = sliding_windows(g, 1/N_WINDOWS)
+    print("done.")
+
+    pool = multiprocessing.Pool(processes=multiprocessing.cpu_count())
+
+    if ZIGZAG_PERS:
+        print("Zigzag persistence...", end="", flush=True)
+        zz_dgms = pool.map(zigzag_network, wins)
+        dill.dump(zz_dgms, open("sociopatterns/zz_dgms.dill", "wb"))
+        print("done, saved.")
+
+    if WRCF_PERS:
+        print("WRCF...", end="", flush=True)
+        ## Collapse each subnetwork into a static graph: the weight is the
+        ## number of appearances of each edge
+        for w in wins:
+            w.es["time"] = np.repeat(1, len(w.es["time"]))
+            w.simplify(combine_edges="sum")
+            w.es["weight"] = w.es["time"]
+            del w.es["time"]
+        wrcf_dgms = pool.map(wrcf_diagram, wins)
+        dill.dump(wrcf_dgms, open("sociopatterns/wrcf_dgms.dill", "wb"))
+        print("done.")
+
+    pool.terminate()
+
+    if ZIGZAG_PERS and SW_KERNEL:
+        print("Sliced Wasserstein Kernel (zigzag)...", end="", flush=True)
+        zz_dgms1 = [dgm[1] for dgm in zz_dgms if len(dgm) > 1]
+        zz_gram1 = np.array([[SW_approx(zz_dgms1[i], zz_dgms1[j], 10)
+                              for i in range(len(zz_dgms1))] for j in range(len(zz_dgms1))])
+        dill.dump(zz_gram1, open("sociopatterns/zz_gram1.dill", "wb"))
+        print("done, saved.")
+    if WRCF_PERS and SW_KERNEL:
+        print("Sliced Wasserstein Kernel (WRCF)...", end="", flush=True)
+        wrcf_dgms1 = [dgm[1] for dgm in wrcf_dgms if len(dgm) > 1]
+        wrcf_gram1 = np.array([[SW_approx(wrcf_dgms1[i], wrcf_dgms1[j], 10)
+                                for i in range(len(wrcf_dgms1))] for j in range(len(wrcf_dgms1))])
+        dill.dump(wrcf_gram1, open("sociopatterns/wrcf_gram1.dill", "wb"))
+        print("done, saved.")
+
+    if ZIGZAG_PERS and BOTTLENECK_DIST:
+        print("Bottleneck distance (zigzag)...", end="", flush=True)
+        zz_dgms1 = list(map(remove_inf, zz_dgms1))
+        zz_distmat = np.array([[d.bottleneck_distance(zz_dgms1[i], zz_dgms1[j])
+                                for i in range(len(zz_dgms1))] for j in range(len(zz_dgms1))])
+        dill.dump(zz_distmat, open("sociopatterns/zz_distmat.dill", "wb"))
+        print("done, saved.")
+    if WRCF_PERS and BOTTLENECK_DIST:
+        print("Bottleneck distance (WRCF)...", end="", flush=True)
+        wrcf_dgms1 = list(map(remove_inf, wrcf_dgms1))
+        wrcf_distmat = np.array([[d.bottleneck_distance(wrcf_dgms1[i], wrcf_dgms1[j])
+                                  for i in range(len(wrcf_dgms1))] for j in range(len(wrcf_dgms1))])
+        dill.dump(wrcf_distmat, open("sociopatterns/wrcf_distmat.dill", "wb"))
+        print("done, saved.")
+
+
+