BF: ignore dtype for some doctests

matthew-brett · matthew-brett · commit e6d90df94e17 · 2012-09-05T13:14:55.000+01:00
Some doctests on 32 bit generate dtype identifiers; use doctest
machinery to ignore these.
diff --git a/nipy/algorithms/statistics/rft.py b/nipy/algorithms/statistics/rft.py
@@ -224,7 +224,7 @@ def __add__(self, other):
         --------
         >>> b = ECquasi([3,4,20], m=30, exponent=4)
         >>> c = ECquasi([1], m=30, exponent=4)
-        >>> b+c
+        >>> b+c #doctest: +IGNORE_DTYPE
         ECquasi(array([ 3,  4, 21]), m=30.000000, exponent=4.000000)
 
         >>> d = ECquasi([1], m=30, exponent=3)
@@ -325,7 +325,7 @@ def __sub__(self, other):
         --------
         >>> b = ECquasi([3,4,20], m=30, exponent=4)
         >>> c = ECquasi([1,2], m=30, exponent=4)
-        >>> print b-c
+        >>> print b-c #doctest: +IGNORE_DTYPE
         ECquasi(array([ 3,  3, 18]), m=30.000000, exponent=4.000000)
         """
         return self + (other * -1)
@@ -353,7 +353,7 @@ def deriv(self, m=1):
         Examples
         --------
         >>> a = ECquasi([3,4,5])
-        >>> a.deriv(m=2)
+        >>> a.deriv(m=2) #doctest: +IGNORE_DTYPE
         ECquasi(array([6]), m=inf, exponent=0.000000)
 
         >>> b = ECquasi([3,4,5], m=10, exponent=3)
diff --git a/nipy/core/reference/coordinate_map.py b/nipy/core/reference/coordinate_map.py
@@ -390,11 +390,11 @@ def __call__(self, x):
         >>> function = lambda x:x+1
         >>> inverse = lambda x:x-1
         >>> cm = CoordinateMap(input_cs, output_cs, function, inverse)
-        >>> cm([2,3,4])
-        array([3, 4, 5])
+        >>> cm([2.,3.,4.])
+        array([ 3.,  4.,  5.])
         >>> cmi = cm.inverse()
-        >>> cmi([2,6,12])
-        array([ 1,  5, 11])
+        >>> cmi([2., 6. ,12.])
+        array([ 1.,  5., 11.])
         """
         x = np.asanyarray(x)
         out_shape = (self.function_range.ndim,)
@@ -880,7 +880,7 @@ def __call__(self, x):
         ...                    [0,0,1,1],
         ...                    [0,0,0,1]])
         >>> affine_transform = AffineTransform(input_cs, output_cs, affine)
-        >>> affine_transform([2,3,4])
+        >>> affine_transform([2,3,4]) #doctest: +IGNORE_DTYPE
         array([3, 4, 5])
         >>> affine_transform_inv = affine_transform.inverse()
         >>> # Its inverse has a matrix of np.float
