mod update corresponding examples

distance_types.py

@@ -6,7 +6,6 @@ from graph_tool.all import *
 
 from src import centrality
 from src import plot
-from src import fitting
 
 
 def random_graph(n=5000, seed=None):
@@ -40,19 +39,21 @@ def spatial_graph(adata):
 def apply(g, seed, weight, convex_hull, ax, ax2, method):
     # calculate centrality values
     vp, ep = method(g, weight=weight)
-    vp.a = np.nan_to_num(vp.a) # correct floating point values
+    ep.a = np.nan_to_num(ep.a) # correct floating point values
+    min_val, max_val = ep.a.min(), ep.a.max()
+    ep.a = (ep.a - min_val) / (max_val - min_val)
 
     # euklidian distance
-    quantification = plot.quantification_data(g, vp, convex_hull)
+    quantification = plot.quantification_data(g, ep, convex_hull)
     plot.quantification_plot(ax, quantification, None, None, "Euklidian Distance", None)
 
     # generate model based on convex hull and associated centrality values
     # path distance
-    quantification = plot.quantification_data_path_distance(g, weight, vp, convex_hull)
+    quantification = plot.quantification_data_path_distance(g, weight, ep, convex_hull)
     plot.quantification_plot(ax2, quantification, None, None, "Shortest Path Distance", None)
 
 
-points, seed = random_graph(n=5000)
+points, seed = random_graph(n=5000, seed=77011137629244244786159039169016117129)
 g, weight = spatial_graph(points)
 g = GraphView(g)
 # calculate convex hull
@@ -62,12 +63,13 @@ fig = plt.figure(figsize=(21, 5))
 ax1, ax2, ax3 = fig.subplots(1, 3)
 
 # plot graph with convex_hull
-# draw without any centrality measure `vp`
 vp, ep = betweenness(g, weight=weight)
-vp.a = np.nan_to_num(vp.a) # correct floating point values
+ep.a = np.nan_to_num(ep.a) # correct floating point values
+min_val, max_val = ep.a.min(), ep.a.max()
+ep.a = (ep.a - min_val) / (max_val - min_val)
 
-plot.graph_plot(fig, ax1, g, vp, convex_hull, f"Pointcloud (seed: {seed})")
+plot.graph_plot(fig, ax1, g, ep, convex_hull, f"Pointcloud (seed: {seed})", True)
 
 apply(g, seed, weight, convex_hull, ax2, ax3, betweenness)
 
-fig.savefig(f"Distance_5000_betweenness_euklidian.svg", format='svg')
+fig.savefig(f"Distance_5000_betweenness_edge_euklidian.svg", format='svg')