--- scipy/optimize/optimize.py.orig	2009-07-11 17:56:37.000000000 +1200
+++ scipy/optimize/optimize.py	2010-05-17 21:36:07.605336495 +1200
@@ -41,6 +41,12 @@
     m = asarray(m)
     return numpy.minimum.reduce(m,axis)
 
+def is_array_scalar(x):
+    """Test whether `x` is either a scalar or an array scalar.
+
+    """
+    return len(atleast_1d(x) == 1)
+
 abs = absolute
 import __builtin__
 pymin = __builtin__.min
@@ -1177,13 +1183,12 @@
 
     """
     # Test bounds are of correct form
-    x1 = atleast_1d(x1)
-    x2 = atleast_1d(x2)
-    if len(x1) != 1 or len(x2) != 1:
-        raise ValueError, "Optimisation bounds must be scalars" \
-                " or length 1 arrays"
+
+    if not (is_array_scalar(x1) and is_array_scalar(x2)):
+        raise ValueError("Optimisation bounds must be scalars"
+                         " or array scalars.")
     if x1 > x2:
-        raise ValueError, "The lower bound exceeds the upper bound."
+        raise ValueError("The lower bound exceeds the upper bound.")
 
     flag = 0
     header = ' Func-count     x          f(x)          Procedure'
--- scipy/optimize/tests/test_optimize.py.orig	2009-07-11 17:56:37.000000000 +1200
+++ scipy/optimize/tests/test_optimize.py	2010-05-18 21:31:39.000000000 +1200
@@ -159,10 +160,17 @@
         assert abs(x - 1.5) < 1e-6
         assert_raises(ValueError,
                 optimize.fminbound, lambda x: (x - 1.5)**2 - 0.8, 5, 1)
+
+    def test_fminbound_scalar(self):
         assert_raises(ValueError,
-                optimize.fminbound, lambda x: (x - 1.5)**2 - 0.8,
+                      optimize.fminbound, lambda x: (x - 1.5)**2 - 0.8,
                       np.zeros(2), 1)
 
+        assert_almost_equal(
+            optimize.fminbound(lambda x: (x - 1.5)**2 - 0.8, 1, np.array(5)),
+            1.5)
+
+
 class TestTnc(TestCase):
     """TNC non-linear optimization.