In fminbound, raise an error if non-scalar bounds are specified [pa…

…tch by

Neil Muller].  Closes scipy#544.

scipy/optimize/optimize.py

@@ -1136,7 +1136,7 @@ def fminbound(func, x1, x2, args=(), xtol=1e-5, maxfun=500,
 
       func : callable f(x,*args)
           Objective function to be minimized (must accept and return scalars).
-      x1, x2 : ndarray
+      x1, x2 : float or array scalar
           The optimization bounds.
       args : tuple
           Extra arguments passed to function.
@@ -1176,6 +1176,12 @@ def fminbound(func, x1, x2, args=(), xtol=1e-5, maxfun=500,
 
 
     """
+    # 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 x1 > x2:
         raise ValueError, "The lower bound exceeds the upper bound."
 

scipy/optimize/tests/test_optimize.py

@@ -147,7 +147,21 @@ def test_brent(self):
         assert max((err1,err2,err3,err4)) < 1e-6
 
 
-
+    def test_fminbound(self):
+        """Test fminbound
+        """
+        x = optimize.fminbound(lambda x: (x - 1.5)**2 - 0.8, 0, 1)
+        assert abs(x - 1) < 1e-5
+        x = optimize.fminbound(lambda x: (x - 1.5)**2 - 0.8, 1, 5)
+        assert abs(x - 1.5) < 1e-6
+        x = optimize.fminbound(lambda x: (x - 1.5)**2 - 0.8,
+                               numpy.array([1]), numpy.array([5]))
+        assert abs(x - 1.5) < 1e-6
+        assert_raises(ValueError,
+                optimize.fminbound, lambda x: (x - 1.5)**2 - 0.8, 5, 1)
+        assert_raises(ValueError,
+                optimize.fminbound, lambda x: (x - 1.5)**2 - 0.8,
+                      np.zeros(2), 1)
 
 class TestTnc(TestCase):
     """TNC non-linear optimization.