WIP: Updating timing scripts and heatmaps

timing/timing_individual_function.py

@@ -1,4 +1,6 @@
-import time
+import timeit
+import random
+import types
 
 import networkx as nx
 import pandas as pd
@@ -7,24 +9,29 @@
 
 import nx_parallel as nxp
 
+
+def execFunc(func, *args, **kwargs):
+    c = func(*args, **kwargs)
+    if isinstance(c, types.GeneratorType):
+        d = dict(c)
+    return d
+
+
 # Code to create README heatmaps for individual function currFun
 heatmapDF = pd.DataFrame()
 # for bipartite graphs
 # n = [50, 100, 200, 400]
 # m = [25, 50, 100, 200]
-number_of_nodes_list = [200, 400, 800, 1600]
+nodes = [75, 150, 300, 600]
 weighted = False
 pList = [1, 0.8, 0.6, 0.4, 0.2]
-currFun = nx.tournament.is_reachable
-"""
+currFun = nx.all_pairs_bellman_ford_path_length
 for p in pList:
-    for num in range(len(number_of_nodes_list)):
+    for num in nodes:
         # create original and parallel graphs
-        G = nx.fast_gnp_random_graph(
-            number_of_nodes_list[num], p, seed=42, directed=True
-        )
-
+        G = nx.fast_gnp_random_graph(num, p, seed=42, directed=True)
 
+        """
         # for bipartite.node_redundancy
         G = nx.bipartite.random_graph(n[num], m[num], p, seed=42, directed=True)
         for i in G.nodes:
@@ -35,6 +42,7 @@
                 G.add_edge(i, random.choice([node for node in G.nodes if node != i]))
             elif len(l) == 1:
                 G.add_edge(i, random.choice([node for node in G.nodes if node != i and node not in list(G.neighbors(i))]))
+        """
 
         # for weighted graphs
         if weighted:
@@ -45,55 +53,32 @@
         H = nxp.ParallelGraph(G)
 
         # time both versions and update heatmapDF
-        t1 = time.time()
-        c1 = currFun(H)
-        if isinstance(c1, types.GeneratorType):
-            d = dict(c1)
-        t2 = time.time()
-        parallelTime = t2 - t1
-        t1 = time.time()
-        c2 = currFun(G)
-        if isinstance(c2, types.GeneratorType):
-            d = dict(c2)
-        t2 = time.time()
-        stdTime = t2 - t1
+        parallelTime = timeit.timeit(lambda: execFunc(currFun, H), number=1)
+        stdTime = timeit.timeit(lambda: execFunc(currFun, G), number=1)
         timesFaster = stdTime / parallelTime
-        heatmapDF.at[number_of_nodes_list[num], p] = timesFaster
+        heatmapDF.at[num, p] = timesFaster
         print("Finished " + str(currFun))
-"""
 
 # Code to create for row of heatmap specifically for tournaments
-for num in number_of_nodes_list:
-    print(num)
-    G = nx.tournament.random_tournament(num, seed=42)
-    H = nxp.ParallelGraph(G)
-    t1 = time.time()
-    c = currFun(H, 1, num)
-    t2 = time.time()
-    parallelTime = t2 - t1
-    print(parallelTime)
-    t1 = time.time()
-    c = currFun(G, 1, num)
-    t2 = time.time()
-    stdTime = t2 - t1
-    print(stdTime)
-    timesFaster = stdTime / parallelTime
-    heatmapDF.at[num, 3] = timesFaster
-    print("Finished " + str(currFun))
+# for p in pList:
+#     for num in nodes:
+#         G = nx.tournament.random_tournament(num)
+#         H = nx_parallel.ParallelDiGraph(G)
+#         parallelTime = timeit.timeit(lambda: nx.tournament.is_reachable(H, 1, num), number=1)
+#         stdTime = timeit.timeit(lambda: nx.tournament.is_reachable(G, 1, num), number=1)
+#         timesFaster = stdTime / parallelTime
+#         timesFaster = stdTime/parallelTime
+#         heatmapDF.at[num, 3] = timesFaster
 
 # plotting the heatmap with numbers and a green color scheme
 plt.figure(figsize=(20, 4))
 hm = sns.heatmap(data=heatmapDF.T, annot=True, cmap="Greens", cbar=True)
 
 # Remove the tick labels on both axes
-hm.set_yticklabels(
-    [
-        3,
-    ]
-)
+hm.set_yticklabels(pList)
 
 # Adding x-axis labels
-hm.set_xticklabels(number_of_nodes_list)
+hm.set_xticklabels(nodes)
 
 # Rotating the x-axis labels for better readability (optional)
 plt.xticks(rotation=45)