Update test_fcl_collision + Add a Python script to display benchmark data.

test/test_fcl_collision-bench.py

+import matplotlib.pyplot as plt
+import csv, sys, numpy as np
+from math import sqrt
+
+filename = sys.argv[1] 
+
+with open(filename, 'r') as file:
+    reader = csv.reader (file, strict = True)
+    fieldnames = None
+    #fieldnames = reader.fieldnames
+    converters = (str, int, int, int, float, lambda x: float(x)*1e-3)
+
+    for row in reader:
+        if fieldnames is None:
+            fieldnames = [ n.strip() for n in row]
+            values = []
+            continue
+
+        values.append ( [ c(v) for v, c in zip(row, converters) ] )
+
+request1 = values[:int(len(values)/2)]
+request2 = values[int(len(values)/2):]
+
+Ntransforms = 1
+while values[0][0:3] == values[Ntransforms][0:3]:
+    Ntransforms += 1
+
+splitMethods = ['avg', 'med', 'cen']
+BVs = list (set ([ v[0] for v in request1[::Ntransforms] ]))
+xvals = [ BVs.index(v[0]) + len(BVs)*v[2] + 3*len(BVs)*v[1] for v in request1[::Ntransforms] ]
+cases = [ v[0] + ("*" if v[1] == 1 else "") + " " + splitMethods[v[2]] for v in request1[::Ntransforms] ]
+
+idx_reorder = sorted (list(range(len(xvals))), key=lambda i: xvals[i])
+def reorder (l): return [ l[i] for i in idx_reorder ]
+
+xvals_s = reorder (xvals)
+cases_s = reorder (cases)
+
+# Time
+plt.figure(0)
+for i in range(Ntransforms):
+    plt.plot(xvals_s, reorder([ v[5] for v in request1[i::Ntransforms] ]) , '-.o', label=str(i))
+    plt.plot(xvals_s, reorder([ v[5] for v in request2[i::Ntransforms] ]) , ':+',  label=str(i)+"+lb")
+
+plt.legend()
+plt.xticks(ticks=xvals_s, labels=cases_s, rotation=90)
+plt.ylabel('Time (us)')
+plt.yscale('log')
+
+# Distance
+plt.figure(1)
+for i in range(Ntransforms):
+    plt.plot(xvals_s, reorder([ v[4] for v in request2[i::Ntransforms] ]) , ':+',  label=str(i)+"+lb")
+
+plt.legend()
+plt.ylabel('Distance lower bound')
+plt.xticks(ticks=xvals_s, labels=cases_s, rotation=90)
+
+plt.show()