Index: trunk/tests_python/amiseOptimalBw_test.py
===================================================================
--- trunk/tests_python/amiseOptimalBw_test.py	(revision 805)
+++ trunk/tests_python/amiseOptimalBw_test.py	(revision 806)
@@ -1,30 +1,29 @@
 import npstat as ns
 import unittest
 
 def densityScan(npoints):
-    assert npoints > 1
     xmin = 0.0
     xmax = 5.0
-    h = (xmax - xmin)/(npoints - 1)
+    h = (xmax - xmin)/npoints
     distro = ns.TruncatedDistribution1D(ns.Exponential1D(0.0, 1.0), xmin, xmax)
-    x, y = ns.scanDensity1D(distro, xmin, xmax, npoints)
+    x, y = ns.scanDensity1D(distro, xmin+h/2, xmax-h/2, npoints)
     return y, h
 
 class TestOptimalBw(unittest.TestCase):
     def test_amiseOptimalBwGauss(self):
         scanPoints = 10000
         sampleSize = 500
         scan, h = densityScan(scanPoints)
         bw, amise = ns.amiseOptimalBwGauss(0, sampleSize, scan, h)
         print("\nOptimal Gauss bw is", bw, "expected AMISE", amise)
 
     def test_amiseOptimalBwSymbeta(self):
         scanPoints = 10000
         sampleSize = 500
         symbetaPower = 4
         scan, h = densityScan(scanPoints)
         bw, amise = ns.amiseOptimalBwSymbeta(symbetaPower, 0, sampleSize, scan, h)
         print("\nOptimal symbeta bw is", bw, "expected AMISE", amise)
 
 suite = unittest.TestLoader().loadTestsFromTestCase(TestOptimalBw)
 unittest.TextTestRunner(verbosity=2).run(suite)