1 files changed, 18 insertions, 18 deletions
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py
index 469f35e58..e1a7ae67a 100644
--- a/numpy/lib/tests/test_function_base.py
+++ b/numpy/lib/tests/test_function_base.py
@@ -453,7 +453,7 @@ class TestHistogram(NumpyTestCase):
         assert_array_equal(a, 10)
 
     def check_normed_new(self):
-        # Check that the integral of the density equals 1. 
+        # Check that the integral of the density equals 1.
         n = 100
         v = rand(n)
         a,b = histogram(v, normed=True, new=True)
@@ -466,49 +466,49 @@ class TestHistogram(NumpyTestCase):
         a,b = histogram(v, bins, normed=True, new=True)
         area = sum(a*diff(b))
         assert_almost_equal(area, 1)
-    
-       
+
+
     def check_outliers_new(self):
         # Check that outliers are not tallied
         a = arange(10)+.5
-        
+
         # Lower outliers
         h,b = histogram(a, range=[0,9], new=True)
         assert_equal(h.sum(),9)
-        
+
         # Upper outliers
         h,b = histogram(a, range=[1,10], new=True)
         assert_equal(h.sum(),9)
-        
+
         # Normalization
         h,b = histogram(a, range=[1,9], normed=True, new=True)
         assert_equal((h*diff(b)).sum(),1)
-        
+
         # Weights
         w = arange(10)+.5
         h,b = histogram(a, range=[1,9], weights=w, normed=True, new=True)
         assert_equal((h*diff(b)).sum(),1)
-        
+
         h,b = histogram(a, bins=8, range=[1,9], weights=w, new=True)
         assert_equal(h, w[1:-1])
-        
-        
+
+
     def check_type_new(self):
         # Check the type of the returned histogram
         a = arange(10)+.5
         h,b = histogram(a, new=True)
         assert(issubdtype(h.dtype, int))
-        
+
         h,b = histogram(a, normed=True, new=True)
         assert(issubdtype(h.dtype, float))
-        
+
         h,b = histogram(a, weights=ones(10, int), new=True)
         assert(issubdtype(h.dtype, int))
-        
+
         h,b = histogram(a, weights=ones(10, float), new=True)
         assert(issubdtype(h.dtype, float))
-        
-        
+
+
     def check_weights_new(self):
         v = rand(100)
         w = ones(100)*5
@@ -518,19 +518,19 @@ class TestHistogram(NumpyTestCase):
         nwa,nwb = histogram(v, weights=w, normed=True, new=True)
         assert_array_almost_equal(a*5, wa)
         assert_array_almost_equal(na, nwa)
-        
+
         # Check weights are properly applied.
         v = linspace(0,10,10)
         w = concatenate((zeros(5), ones(5)))
         wa,wb = histogram(v, bins=arange(11),weights=w, new=True)
         assert_array_almost_equal(wa, w)
-        
+
         # Check with integer weights
         wa, wb = histogram([1,2,2,4], bins=4, weights=[4,3,2,1], new=True)
         assert_array_equal(wa, [4,5,0,1])
         wa, wb = histogram([1,2,2,4], bins=4, weights=[4,3,2,1], normed=True, new=True)
         assert_array_equal(wa, array([4,5,0,1])/10./3.*4)
-     
+
 class TestHistogramdd(NumpyTestCase):
     def check_simple(self):
         x = array([[-.5, .5, 1.5], [-.5, 1.5, 2.5], [-.5, 2.5, .5], \